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CN103642902B - Genetic analysis systems and method - Google Patents

Genetic analysis systems and method Download PDF

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Publication number
CN103642902B
CN103642902B CN201310565723.1A CN201310565723A CN103642902B CN 103642902 B CN103642902 B CN 103642902B CN 201310565723 A CN201310565723 A CN 201310565723A CN 103642902 B CN103642902 B CN 103642902B
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genotype
phenotype
individuality
disease
genome atlas
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CN103642902A (en
Inventor
D·A·斯坦芬
M·F·菲利普庞
J·韦塞尔
M·卡吉尔
E·哈尔佩里恩
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Navigenics Inc
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Navigenics Inc
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Priority claimed from US11/781,679 external-priority patent/US20080131887A1/en
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Priority claimed from CN2007800500195A external-priority patent/CN101617227B/en
Publication of CN103642902A publication Critical patent/CN103642902A/en
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Abstract

The invention provides the method being determined hereditary composite index score by the dependency assessed between individual genotype and at least one disease or state.This assessment comprises the Genome Atlas of individuality compared with confirming as the database of the medical science correlative heritability of being correlated with at least one disease or state.

Description

Genetic analysis systems and method
The application's to be the applying date be on November 30th, 2007 and denomination of invention are the divisional application of No. 200780050019.5 applications for a patent for invention of " genetic analysis systems and method ".
Background technology
Other latest developments of human genome order-checking and human activities environment disclose, and any two person-to-person genomes form the similarity had more than 99.9%.Variation relatively a small amount of in DNA between Different Individual is the reason causing phenotypic character difference, and relevant with many human diseasess, the susceptibility to various disease and the reaction to disease treatment.Between individuality, the variation of DNA occurs in coding region and non-coding region, and comprises the change of base on specific site in genomic dna sequence, and the insertion of DNA and disappearance.The change occurred in genome on single base positions is called single nucleotide polymorphism, or " SNP ".
Although SNP relative rarity in human genome, but it accounts for the major part of mutant dna sequence between individuality, in human genome approximately every 1, there is a SNP (see InternationalHapMapProject, www.hapmap.org) in 200 base pairs.Owing to can obtain more human inheritance's information, the complicacy of SNP starts as people is understood.Thereupon, in genome, generation and the various diseases of SNP associate with the existence of state and/or susceptibility.
Owing to obtaining other progress in these dependencys and human genetics, generally speaking medical treatment and individual health care just develop towards the approach of personalization, and wherein patient selects making suitable medical treatment when considering his or her genomic information beyond other factors and other selection.Therefore, provide the genomic information of individual specific to this individuality with regard to needing to individual and their healthcare provider, thus personalized medicine and other decision-making are provided.
Summary of the invention
The invention provides a kind of method assessing individual genotype correlation, the method comprises: genetic material a) obtaining this individuality, b) Genome Atlas of this individuality is generated, c) by the Genome Atlas of this individuality is compared with the current database of the dependency of phenotype with human genotype, determine the dependency of this idiotype and phenotype, d) to care manager's report of this individuality or this individuality by step c) result that obtains, e) as known additional human genotype correlation, the human genotype correlation additional with this upgrades human genotype correlation's database, f) by by by step c) Genome Atlas of this individuality that obtains or its part upgrade the genotype correlation of this individuality compared with the human genotype correlation added, and determine the episome type dependency of this individuality, and g) to care manager's report of this individuality or this individuality by step f) result that obtains.
Invention further provides a kind of business method assessing individual genotype correlation, the method comprises: genetic material a) obtaining this individuality; B) Genome Atlas of this individuality is generated, c) by the Genome Atlas of this individuality being determined compared with human genotype correlation's database the genotype correlation of this individuality; D) result determining individual genotype correlation is provided to this individuality in the mode of encrypting; E) as known additional human genotype correlation, the human genotype correlation additional with this upgrades human genotype correlation's database; F) by the Genome Atlas of this individuality or its part being upgraded compared with additional human genotype correlation the genotype correlation of this individuality, and the episome type dependency of this individuality is determined; And the result of the genotype correlation upgrading this individuality g) is provided to the care manager of this individuality or this individuality.
Another aspect of the present invention is a kind of method generating individual phenotypic spectrum, the method comprises: a) provide the rule set (ruleset) comprising rule, each rule shows the dependency between at least one genotype and at least one phenotype, b) provide the data set of the Genome Atlas comprising each individuality in multiple individuality, wherein each Genome Atlas comprises Multi-genotype; C) with at least one this rule set of new regulation regular update, wherein this at least one new regulation shows the dependency previously between genotype not associated with each other in rule set and phenotype; D) each bar new regulation is applied to the Genome Atlas of at least one individuality, thus at least one genotype of this individuality and at least one phenotypic correlation are joined, and optionally, e) generate the report comprising the phenotypic spectrum of this individuality.
Present invention also offers a kind of system, this system comprises: rule set a) comprising rule, and each rule shows the dependency between at least one genotype and at least one phenotype; B) with the code of at least one this rule set of new regulation regular update, wherein this at least one new regulation shows the dependency previously between genotype not associated with each other in rule set and phenotype; C) database of the Genome Atlas of multiple individuality is comprised; D) this rule set is applied to individual Genome Atlas to determine the code of individual phenotypic spectrum; And e) generate the code of report of each individuality.
Another aspect of the present invention is transmitted by network in the mode of encrypting or do not encrypt in above-mentioned method and system.
The reference content introduced
The all publications mentioned in the description and patent application are hereby incorporated by, as each single publication or patent application especially with illustrate individually be incorporated herein by reference the same.
Particularly, the present invention relates to the following:
1. assess a method for individual genotype correlation, the method comprises:
A) genetic material of described individuality is obtained;
B) Genome Atlas of described individuality is generated;
C) by the Genome Atlas of described individuality is determined the genotype of described individuality and the dependency of phenotype with current mankind genotype compared with the correlation data storehouse of phenotype;
D) to care manager's report of described individuality or described individuality by step c) the described result that obtains;
E) when knowing additional human genotype correlation, described human genotype correlation's database is upgraded with described additional human genotype correlation; With
F) by by step c) the Genome Atlas of described individuality or its part upgrade the genotype correlation of described individuality compared with described additional human genotype correlation, and determine the episome type dependency of described individuality; With
G) to care manager's report of described individuality or described individuality by step f) the described result that obtains.
2. the method described in the 1st, wherein, third party obtains described genetic material.
3. the method described in the 1st, wherein, described generation Genome Atlas is undertaken by third party.
4. the method described in the 1st, wherein, described result is marked based on GCI or GCIPlus.
5. the method described in the 1st, wherein, described report comprises by result described in Internet Transmission.
6. the method described in the 1st, wherein, the described report of described result is by online entrance.
7. the method described in the 1st, wherein, the described report of described result is by paper or passes through e-mail.
8. the method described in the 1st, wherein, the mode that described report comprises encrypting reports described result.
9. the method described in the 1st, wherein, described report comprises reports described result in unencrypted mode.
10. the method described in the 1st, wherein, the Genome Atlas of described individuality is stored in encrypting database or strong room.
Method described in 11. the 1st, wherein, described individuality is registered user.
Method described in 12. the 1st, wherein, described individuality is nonregistered user.
Method described in 13. the 1st, wherein, described genetic material is DNA.
Method described in 14. the 1st, wherein, described genetic material is RNA.
Method described in 15. the 1st, wherein, described Genome Atlas is single nucleotide polymorphism Genome Atlas, and described human genotype correlation's database is mankind's single nucleotide polymorphism dependency, and described additional human genotype correlation is single nucleotide polymorphism dependency.
Method described in 16. the 1st, wherein, described Genome Atlas comprise truncate, insert, disappearance or repeat, described human genotype correlation's database be human truncations, insertion, disappearance or repeat dependency, and described additional human genotype correlation be truncate, insert, disappearance or repetition dependency.
Method described in 17. the 1st, wherein, described Genome Atlas is the full-length genome of described individuality.
Method described in 18. the 1st, wherein, described method comprises the genotype correlation of assessment 2 or more.
Method described in 19. the 1st, wherein, described method comprises the genotype correlation of assessment 10 or more.
Method described in 20. the 1st, wherein, described human genotype correlation's database comprises lists in genetic variant in one or more genes of table 1 and the phenotype relevant to described genetic variants useful.
Method described in 21. the 1st, wherein, described human genotype correlation's database comprise list in Fig. 4,5,6, genetic variant in one or more genes of 22 or 25 and the phenotype relevant to described genetic variant.
Method described in 22. the 1st, wherein, described human genotype correlation's database comprises the genetic variant determined by the described Genome Atlas of described individuality and the predetermined phenotype appeared by described individuality.
Method described in 23. the 1st, wherein, described human genotype correlation's database be included in table 1 or Fig. 4,5, single nucleotide polymorphism in described gene listed by 6,22 or 25 and the phenotype relevant to described single nucleotide polymorphism.
Method described in 24. the 1st, wherein, described genetic material is from the biological sample being selected from blood, hair, skin, saliva, seminal fluid, urine, fecal materials, sweat and buccal sample.
Method described in 25. the 15th, wherein, described genotype correlation is the dependency of single nucleotide polymorphism and disease and state.
Method described in 26. the 15th, wherein, described genotype correlation is the dependency of the phenotype of single nucleotide polymorphism and medical condition.
Method described in 27. the 1st, wherein, described Genome Atlas uses high-density DNA microarray to generate.
Method described in 28. the 1st, wherein, described Genome Atlas uses genomic dna order-checking to generate.
Method described in 29. the 24th, wherein, described genetic material is genomic dna and described biological sample is saliva.
30. 1 kinds of methods, the method comprises:
A) provide the rule set comprising rule, each rule shows the dependency between at least one genotype and at least one phenotype;
B) provide the data set of the Genome Atlas comprising each individuality in multiple individuality, wherein each Genome Atlas comprises Multi-genotype;
C) use at least one new regulation to upgrade described rule set termly, wherein said at least one new regulation shows the dependency previously in described rule set each other between incoherent genotype and phenotype; With
D) each bar new regulation is applied to the described Genome Atlas of one of at least described individuality, thus for described individuality, at least one genotype and at least one phenotypic correlation is joined.
Method described in 31. the 30th, the method comprises further:
E) report comprising the described phenotypic spectrum of described individuality is generated.
Method described in 32. the 30th, the method comprises further: in step b) after
I) the described rule of described rule set is applied to the described Genome Atlas of described individuality to determine a set of phenotypic spectrum of described individuality; With
Ii) report comprising the initial table type spectrum of described individuality is generated.
33. the 31st or method described in 32, wherein, provide described report to comprise and report by described in Internet Transmission.
34. the 31st or method described in 32, wherein, described report cryptographically provides.
35. the 31st or method described in 32, wherein, described report provides in an unencrypted manner.
36. the 31st or method described in 32, wherein, described report is provided by online entrance.
37. the 31st or method described in 32, wherein, described report provides with paper or e-mail.
Method described in 38. the 30th, wherein, described new regulation makes not associated genotype and phenotypic correlation join.
Method described in 39. the 30th, wherein, described new regulation make the genotype that associated with previously not in described rule set the phenotypic correlation of associated join.
Method described in 40. the 30th, wherein, described new regulation changes the rule in described rule set.
Method described in 41. the 30th, wherein, described new regulation is generated by the dependency from the genotype of the described Genome Atlas of described individuality and the predetermined phenotype of described individuality.
Method described in 42. the 30th, wherein, described rule makes Multi-genotype and a kind of phenotypic correlation join.
Method described in 43. the 30th, wherein, apply described new regulation comprise further at least partly based on be selected from race, family, geography, sex, the age, family history and predetermined phenotype the feature of described individuality determine described phenotypic spectrum.
Method described in 44. the 30th, wherein, described genotype comprises Nucleotide repetition, Nucleotide insertion, nucleotide deletion, chromosome translocation, karyomit(e) repeats or copy number makes a variation.
Method described in 45. the 44th, wherein, described copy number variation is micro-satellite repetition, Nucleotide repeats, kinetochore is repeated or telomere repeats.
Method described in 46. the 30th, wherein, described genotype comprises single nucleotide polymorphism.
Method described in 47. the 30th, wherein, described genotype comprises haplotype and double body type.
Method described in 48. the 30th, wherein, described genotype comprises the genetic marker with the single nucleotide polymorphism linkage disequilibrium of phenotypic correlation.
Method described in 49. the 30th, wherein, described phenotypic spectrum shows whether described quantitative trait exists or produce the risk of described quantitative trait.
Method described in 50. the 30th, wherein, described phenotypic spectrum shows that having genotypic individuality has or will have the probability of phenotype.
Method described in 51. the 50th, wherein, described probability is marked based on GCI or GCIPlus.
Method described in 52. the 50th, wherein, described probability is the lifetime risk estimated.
Method described in 53. the 30th, wherein, described dependency is through checking.
Method described in 54. the 30th, wherein, described rule set comprises at least 20 rules.
Method described in 55. the 30th, wherein, described rule set comprises at least 50 rules.
Method described in 56. the 30th, wherein, described rule set comprises the rule based on the described genotype correlation in table 1.
Method described in 57. the 30th, wherein, described rule set comprises the rule based on the described genotype correlation in Fig. 4,5,6,22 or 25.
Method described in 58. the 30th, wherein, described phenotype comprises quantitative trait.
Method described in 59. the 58th, wherein, described quantitative trait comprises medical condition.
Method described in 60. the 59th, wherein, described phenotypic spectrum show whether described medical condition exists, produce the risk of described medical condition, the prognosis of described medical condition, the result for the treatment of of described medical condition or the treatment for described medical condition reaction.
Method described in 61. the 58th, wherein, described quantitative trait comprises the phenotype of medical condition.
Method described in 62. the 58th, wherein, described quantitative trait is selected from health proterties, physiological character, mental trait, mood proterties, race, family or age.
Method described in 63. the 30th, wherein, described individuality is the mankind.
Method described in 64. the 30th, wherein, described individuality is non-human.
Method described in 65. the 30th, wherein, described individuality is registered user.
Method described in 66. the 30th, wherein, described individuality is nonregistered user.
Method described in 67. the 30th, wherein, described Genome Atlas comprises at least 100,000 kind of genotype.
Method described in 68. the 30th, wherein, described Genome Atlas comprises at least 400,000 kind of genotype.
Method described in 69. the 30th, wherein, described Genome Atlas comprises at least 900,000 kind of genotype.
Method described in 70. the 30th, wherein, described Genome Atlas comprises at least 1,000,000 kind of genotype.
Method described in 71. the 30th, wherein, described Genome Atlas comprises substantially whole genome sequence completely.
Method described in 72. the 30th, wherein, described data set comprises multiple data point, wherein each data point relates to individuality and comprises multiple data element, wherein said data element comprises the unique identification thing being selected from described individuality, genotype information, microarray SNP identifier, SNPrs identifier, chromosome position, polymorphic nucleotide, quality metric, raw data file, image, the intensity scores extracted, physical data, medical data, race, family, geographical, sex, age, family history, known phenotype, demographic data, expose data, at least one element of lifestyle data and behavioral data.
Method described in 73. the 30th, wherein, regular update and application occur at least one times for 1 year.
Method described in 74. the 30th, wherein, provides described data set to comprise the Genome Atlas being obtained each individuality in multiple individuality by following steps:
I) genetic analysis is carried out to the genetic material obtained by described individuality, and
Ii) with computer-reader form, described analysis is encoded.
Method described in 75. the 30th, wherein, described phenotypic spectrum comprises monogenic phenotype.
Method described in 76. the 30th, wherein, described phenotype comprises polygene phenotype.
Method described in 77. the 30th, wherein, described report comprises initial table type spectrum.
Method described in 78. the 30th, wherein, described report comprises the phenotypic spectrum of renewal.
Method described in 79. the 30th, wherein, described report comprises the information of the described phenotype about described phenotypic spectrum further, and this information is selected from one or more of the following stated: the accurate discriminating of phenotype described in preventive measure, health and fitness information, therapy, symptom understanding, early detection scheme, intervention plan and described phenotypic spectrum and disaggregated classification.
Method described in 80. the 30th, the method comprises further:
E) new individual new gene picture group spectrum is joined described individual data items to concentrate;
F) described rule set is applied to the described Genome Atlas of described new individuality; With
G) Initial Report of the phenotypic spectrum of described new individuality is generated.
Method described in 81. the 30th, the method comprises:
E) the new gene picture group spectrum of described individuality is added;
F) described rule set is applied to the described new gene picture group spectrum of described individuality; With
G) latest report of the phenotypic spectrum of described individuality is generated.
82. 1 kinds of systems, this system comprises:
A) comprise the rule set of rule, each rule shows the dependency between at least one genotype and at least one phenotype;
B) use the code of rule set described at least one new regulation regular update, wherein said at least one new regulation shows the dependency between the genotype that be not previously relative to each other in described rule set and phenotype;
C) database of the Genome Atlas of multiple individuality is comprised;
D) described rule set is applied to individual described Genome Atlas to determine the code of the phenotypic spectrum of described individuality; With
E) code of the report of each individuality is generated.
System described in 83. the 82nd, wherein, Internet Transmission is passed through in described report.
System described in 84. the 82nd, wherein, described report cryptographically provides.
System described in 85. the 82nd, wherein, described report provides in an unencrypted manner.
System described in 86. the 82nd, wherein, described report is provided by online entrance.
System described in 87. the 82nd, wherein, described report is provided by paper or e-mail.
System described in 88. the 82nd, this system comprises the code noticing dependency that is new or that revise to described individuality further.
System described in 89. the 82nd, this system comprises further notices the code of rule that can be applied to the new of the described Genome Atlas of described individuality or revise to described individuality.
System described in 90. the 82nd, this system comprises further notices the new of the described phenotype of the relevant described phenotypic spectrum of described individuality or the prevention of correction and the code of health and fitness information to described individuality.
91. 1 kinds of test kits, this test kit comprises:
A) at least one collection containers;
B) for obtaining the operation instruction of sample from individuality;
C) for being accessed the operation instruction of the Genome Atlas of the described individuality obtained by described sample by online entrance;
D) for being accessed the operation instruction of the phenotypic spectrum of the described individuality obtained by described sample by online entrance; With
E) for described collection containers being delivered to the packaging of described sample preparation mechanism.
92. 1 kinds of online entrances, this online entrance comprises the website that individuality can access described phenotypic spectrum, and wherein said website allows described individuality to carry out at least one operation as described below:
A) select described rule to be applied to the Genome Atlas of described individuality;
B) the initial report with upgrading is checked on the web;
C) print from described website initial with the report upgraded;
D) will be saved on the computer of described individuality from the initial of described website and the report upgraded;
E) prevention about the phenotypic spectrum of described individuality and health and fitness information is obtained;
F) genetic counseling that is online or phone connection is obtained;
G) information extraction is to share with doctor/genetic consultant; And/or
H) service obtaining collocation and the product provided.
Online entrance described in 93. the 92nd, wherein, described information passes through Internet Transmission.
Online entrance described in 94. the 92nd, wherein, described website is encryption.
Online entrance described in 95. the 92nd, wherein, described website is not encrypted.
Online entrance described in 96. the 92nd, wherein, described individuality has one or more options of the described security level of information or the one or more part relating to this individuality.
Online entrance described in 97. the 92nd, wherein, described phenotypic spectrum comprises the medical condition that can dispose.
Online entrance described in 98. the 92nd, wherein, described phenotypic spectrum comprises the medical condition without existing preventive actions or Current Therapy.
Online entrance described in 99. the 92nd, wherein, described phenotypic spectrum comprises medical condition.
Assess the individual a kind of method obtaining risk of state for 100. one kinds, the method comprises:
A) individual genotype is obtained;
B) determine that GCI or GCIPlus marks by described genotype;
C) report is generated by described GCI or GCIPlus scoring; With
D) described report is supplied to the care manager of described individuality or described individuality.
Assess the individual a kind of method obtaining risk of state for 101. one kinds, the method comprises:
A) individual genotype is obtained;
B) Genome Atlas of described individuality is generated;
C) risk of individual acquisition state is determined by described Genome Atlas and genotype correlation database;
D) by c) generating report;
E) new information is obtained from described individuality;
F) the new risk of acquisition state is determined by introducing described new information;
G) by f) generating report; With
H) described report is supplied to the care manager of described individuality or described individuality.
Assess the individual a kind of method obtaining risk of state for 102. one kinds, the method comprises:
A) individual genotype is obtained;
B) Genome Atlas of described individuality is generated;
C) determined the risk of individual acquisition state by described Genome Atlas and genotype correlation database, wherein said risk is based on more than a kind of SNP;
D) by c) generating report;
E) described report is supplied to the care manager of described individuality or described individuality.
Method described in 103. the 100th, 101 or 102, wherein, the genotype of described individuality directly obtains from described individuality.
Method described in 104. the 100th, 101 or 102, wherein, the genotype of described individuality obtains from third party.
Method described in 105. the 100th, 101 or 102, wherein, described in provide be pass through Internet Transmission.
Method described in 106. the 101st, wherein, described new information obtains from the biological sample of described individuality.
Method described in 107. the 101st, wherein, described new information obtains from the somatometry of individuality.
108. the 101st or method described in 102, wherein, described risk is marked by GCI or GCIPlus and is obtained.
109. the 100th or method described in 108, wherein, described GCI or GCIPlus scoring comprises the family of described individuality.
110. the 100th or method described in 108, wherein, described GCI or GCIPlus scoring comprises the sex of described individuality.
111. the 100th or method described in 108, wherein, described GCI or GCIPlus marks the factor comprised specific to described individuality, and wherein said factor is not be derived from described genotype.
Method described in 112. the 111st, wherein, described factor is selected from: individual birthplace, father and mother and/or grand parents, relationship family, position, residence, the position, residence of ancestors, envrionment conditions, known healthy state, known drug interaction, domestic hygiene condition, lifestyle conditions, diet, exercise habits, marital status and somatometry.
113. the 107th or method described in 112, wherein, the somatometry of described individuality is selected from: blood pressure, heart rate, glucose level, metabolite level, ion concentration, body weight, height, cholesterol levels, vitamin level, cytometry, weight index (BMI), protein level and transcript level.
Assess the individual a kind of method obtaining risk of state for 114. one kinds, the method comprises:
A) individual genotype is obtained;
B) Genome Atlas of described individuality is generated;
C) the individual risk obtaining Alzheimer (AD), colorectal carcinoma (CRC), osteoarthritis (OA) or exfoliation glaucoma (XFG) is determined, wherein, described risk is be be based on rs2165241 based on rs4911178 with for XFG based on rs6983267, for OA based on rs4420638, for CRC for AD;
D) by c) generating report;
E) described report is supplied to the care manager of described individuality or described individuality.
Method described in 115. the 102nd, wherein, described risk is determined by least 3,4,5,6,7,8,9,10 or 11 SNP.
Method described in 116. the 102nd, wherein, described risk is determined by least 2 SNP.
Method described in 117. the 116th, wherein, described risk is at least one for fat (BMIOB) and in described at least 2 SNP is rs9939609 or rs9291171.
Method described in 118. the 116th, wherein, described risk be at least one for Graves' disease (GD) and in described at least 2 SNP be rs3087243, DRB1*0301DQA1*0501 or the linkage disequilibrium with DRB1*0301DQA1*0501.
Method described in 119. the 116th, wherein, described risk is at least one for hemochromatosis (HEM) and in described at least 2 SNP is rs1800562 or rs129128.
Method described in 120. the 116th, wherein, described risk is at least one for myocardial infarction (MI) and in described at least 2 SNP is rs1866389, rs1333049 or rs6922269.
Method described in 121. the 116th, wherein, described risk is at least one for multiple sclerosis (MS) and in described at least 2 SNP is rs6897932, rs12722489 or DRB1*1501.
I22. the method described in the 116th, wherein, described risk is at least one for psoriasis (PS) and in described at least 2 SNP is rs6859018, rs11209026 or HLAC*0602.
Method described in 123. the 116th, wherein, described risk is at least one for restless legs syndrome (RLS) and in described at least 2 SNP is rs6904723, rs2300478, rs1026732 or rs9296249.
Method described in 124. the 116th, wherein, described risk is at least one for celiac disease (CelD) and in described at least 2 SNP is rs6840978, rs11571315, rs2187668 or DQA1*0301DQB1*0302.
Method described in 125. the 116th, wherein, described risk is at least one for prostate cancer (PC) and in described at least 2 SNP is rs4242384, rs6983267, rs16901979, rs17765344 or rs4430796.
Method described in 126. the 116th, wherein, described risk is at least one for lupus (SLE) and in described at least 2 SNP is rs12531711, rs10954213, rs2004640, DRB1*0301 or DRB1*1501.
Method described in 127. the 116th, wherein, described risk be at least one for macular degeneration (AMD) and in described at least 2 SNP be rs10737680, rs10490924, rs541862, rs2230199, rs1061170 or rs9332739.
Method described in 128. the 116th, wherein, described risk be at least one for rheumatoid arthritis (RA) and in described at least 2 SNP be rs6679677, rs11203367, rs6457617, DRB*0101, DRB1*0401 or DRB1*0404.
Method described in 129. the 116th, wherein, described risk be at least one for mammary cancer (BC) and in described at least 2 SNP be rs3803662, rs2981582, rs4700485, rs3817198, rs17468277, rs6721996 or rs3803662.
Method described in 130. the 116th, wherein, described risk be at least one for Crohn's disease (CD) and in described at least 2 SNP be rs2066845, rs5743293, rs10883365, rs17234657, rs10210302, rs9858542, rs11805303, rs1000113, rs17221417, rs2542151 or rs10761659.
Method described in 131. the 116th, wherein, described risk be at least one for diabetes B (T2D) and in described at least 2 SNP be rs13266634, rs4506565, rs10012946, rs7756992, rs10811661, rs12288738, rs8050136, rs1111875, rs4402960, rs5215 or rs1801282.
Accompanying drawing explanation
Fig. 1 is the schema illustrating method aspect of the present invention.
Fig. 2 is the example of genomic dna quality control method.
Fig. 3 is the example of hybridization quality control method.
Fig. 4 is the table of the Exemplary gene type dependency of open source literature from the SNP and Effect Evaluation with test.A-I) genotype correlation of individual gene seat is represented; J) genotype correlation of two locus is represented; K) genotype correlation of three locus is represented; L) be the index of the race that uses in A-K and country's abbreviation; M) be the reference of index, heritability and heritability that phenotype title abbreviation (ShortPhenotypeName) in A-K is abridged.
Fig. 5 A-J is the table of the Exemplary gene type dependency with Effect Evaluation.
Fig. 6 A-F is the table of the relative risk of Exemplary gene type dependency and estimation.
Fig. 7 is example report.
Fig. 8 is the diagram for the system analyzed and by Internet Transmission Genome Atlas and phenotypic spectrum.
Fig. 9 is the schema illustrating business method aspect of the present invention.
Figure 10: popularity (prevalence) evaluates the effect to relative risk assessment.Assuming that when Hardy-Weinberg equilibrium (Hardy-WeinbergEquilibrium), each curve corresponds to the different numerical value of colony's allelic frequency.Article two, black line corresponds to the odds ratio of 9 and 6, and two red lines correspond to the odds ratio of 6 and 4, and two blue lines correspond to the odds ratio of 3 and 2.
Figure 11: the effect that gene frequency evaluation is assessed relative risk.Each curve corresponds to the different numerical value of popularity in colony.Article two, black line corresponds to the odds ratio of 9 and 6, and two red lines correspond to the odds ratio of 6 and 4, and two blue lines correspond to the odds ratio of 3 and 2.
Figure 12: the paired comparisons of the absolute value of different model.
Figure 13: based on the paired comparisons of the grade point (GCI scoring) of different model.Give in table 2 different between Spearman dependency.
Figure 14: popularity report is to the effect of GCI scoring.Spearman dependency between any two popular angle value is at least 0.99.
Figure 15: be the figure of the example web page from individual entrance.
Figure 16: for illustrating that individual suffers from the figure of the example web page from individual entrance of the risk of prostate cancer.
Figure 17: for illustrating that individual suffers from the figure of the example web page from individual entrance of the risk of Crohn disease.
Figure 18: be the histogram using the GCI of the multiple sclerosis based on HapMAP of 2 SNP to mark.
Figure 19: for using the individual lifetime risk of the multiple sclerosis of GCIPlus.
Figure 20: the histogram that the GCI for Crohn disease marks.
Figure 21: be the table of limited loci dependency.
Figure 22: be the table of SNP and phenotypic correlation.
Figure 23: be the table of phenotype and popularity.
Figure 24: be the glossary of abbreviation in Figure 21,22 and 25.
Figure 25: be the table of SNP and phenotypic correlation.
Embodiment
The invention provides and generate phenotypic spectrum based on storage Genome Atlas that is individual or group of individuals, and generate based on the Genome Atlas stored original in method and system that the is phenotypic spectrum upgraded easily.By generating Genome Atlas by deriving from individual biological sample determination genotype.The biological sample obtained from individuality can be any sample that can be obtained genetic material by it.Sample can from the tissue sample of buccal swab, saliva, blood, hair or other type any.Then can by biological sample determination genotype.Genotype can be any genetic variant or biomarker, such as, and single nucleotide polymorphism (SNPs), haplotype (haplotype)) or genomic sequence.Genotype can be individual full gene group sequence.Genotype can be obtained by the high throughput analysis producing thousands of or millions of data points, such as, for microarray analysis that is most of or all known SNP.In other embodiments, genotype also can be checked order by high throughput and determine.
Genotype forms individual Genome Atlas.Genome Atlas carries out stored digital and is easy to put at any time conduct interviews to generate phenotypic spectrum.By applying the generate rule phenotypic spectrum making genotype and phenotypic correlation join or combine.Rule can be formulated based on the scientific research of the dependency shown between genotype and phenotype.The council that dependency can be made up of one or more expert carries out verifying (curate) or confirming.By rule being applied to individual Genome Atlas, the association between individual genotype and phenotype can be determined.Individual phenotypic spectrum will have this determinacy.This determines it can is the positive correlation between individual genotype and given phenotype, thus this individuality has given phenotype or by this phenotype of generation.Or, can determine that individuality does not have or will not produce given phenotype.In other embodiments, this determines it can is that risk factor, estimated value or individuality have and maybe will produce the probability of phenotype.
Can determine based on multiple rule, such as, multiple rule can be applied to Genome Atlas to determine associating of idiotype and particular phenotype.Deterministic process also can comprise the factor specific to individuality, such as race, sex, mode of life are (such as, diet and exercise habits), the age, environment (such as, dwelling places), family's medical history, personal history and other known phenotype.Being incorporated to of specific factor can comprise these factors by revising existing rule.Or, independent rule can be generated by these factors and after applying existing rule, be applied to individual phenotype and determine.
Phenotype can comprise any measurable proterties or characteristic, such as, for the susceptibility of certain disease or the reaction for pharmacological agent.Other phenotype that can comprise is body and mental trait, such as, and height, body weight, hair color, eye color, sunburn susceptibility, size, memory, intelligence, optimistic degree, overall disposition.Phenotype also can comprise heredity that is individual with other or organism and compare.Such as, individuality may be interested in the similarity between their Genome Atlas and the Genome Atlas of famous person.They also may make their gene mapping and other organism (such as bacterium, plant or other animal) compare.
In a word, the set of the determined Relevant phenotype of individuality is formed to the phenotypic spectrum of this individuality.Phenotypic spectrum can be accessed by online entrance.Or phenotypic spectrum can provide with paper form according to the form existed at specified time, and follow-up renewal also provides with paper form.Phenotypic spectrum also can be provided by online entrance.This online entrance can be optionally the online entrance of encryption.The access right of phenotypic spectrum can be supplied to registered user, this registered user be dependency between customized generation phenotype and genotype rule, determine individual Genome Atlas, rule be applied to Genome Atlas and generate the individuality of service of phenotypic spectrum of individuality.Access right also can be supplied to nonregistered user, and wherein they can have their phenotypic spectrum of access and/or the limited rights of report, or can allow to generate Initial Report or phenotypic spectrum, but only has by the customized report just generating renewal of paying.Care manager and supplier, such as paramedic, doctor and genetic consultant also can have the access right of phenotypic spectrum.
In another aspect of this invention, can be that registered user and nonregistered user generate Genome Atlas, and carry out stored digital, but can registered user be limited to for the access of phenotypic spectrum and report.In another modification, registered user and nonregistered user can access its genotype and phenotypic spectrum, but nonregistered user has restricted access rights or allows to generate limited report, but registered user has complete access rights and can allow to generate complete report.In another embodiment, registered user and nonregistered user can have access rights or complete Initial Report completely at first, but only registered user can access the report of the Genome Atlas renewal stored based on it.
In another aspect of this invention, combine and analyze and mark to obtain hereditary aggregative index (geneticcompositeindex) (GCI) about the information associated of multiple genetic marker with one or more diseases or state.This scoring includes known risk factor and out of Memory and hypothesis, such as, and the popularity of gene frequency and disease.GCI may be used for associating of the combined effect of qualitative assessment disease or state and a series of genetic marker.GCI scoring may be used for providing about reliable (such as, firm), intelligible and/or be familiar with intuitively of its Personal Risk compared with Reference Group to the people not trained by genetics based on existing scientific research.GCI scoring may be used for generating GCIPlus scoring.GCIPlus scoring can comprise all GCI and suppose, and this hypothesis comprises the sickness rate of the risk (such as, lifetime risk) of state, popularity that the age limits and/or age restriction.Then individual lifetime risk may be calculated to mark with individual GCI and to mark divided by the average GCI proportional GCIPlus that marks.Average GCI scoring can be determined by the group of individuals with similar family background, such as one group of Caucasian, Aisa people, people from East India or other there is the group of common family background.Described group can be made up of at least 5,10,15,20,25,30,35,40,45,50,55 or 60 individualities.In some embodiments, average GCI scoring can be determined by least 75,80,95 or 100 individualities.GCIPlus scoring by determining individual GCI scoring, removes this GCI and mark, and the lifetime risk being multiplied by state or phenotype can be determined by average relative risk.Such as, use and calculate GCIPlus scoring, such as, in Figure 19 from the information in the data of Figure 22 and/or Figure 25 and Figure 24.
The present invention includes and use GCI described here scoring, and those skilled in the art are easy to recognize that GCIPlus scoring or its modification replace the purposes of GCI described here scoring.
In one embodiment, GCI scoring is generated for each interested disease or state.These GCI can be concentrated to mark to form individual risk distribution figure (riskprofile).Stored digital can be carried out so that they can be put at any time to this GCI scoring to conduct interviews easily to generate risk distribution figure.Risk distribution figure can decompose according to large classification of diseases, such as, and cancer, heart trouble, metabolism disorder, abalienation, osteopathy or senile disease (ageon-setdisorder).Large classification of diseases can be broken down into subclass further.Such as, for the large classification of such as cancer, can such as by type (sarcoma, cancer knurl or leukemia etc.) or list the subclass of cancer by tissue specificity (nerve, mammary gland, ovary, testis, prostate gland, bone, lymphoglandula, pancreas, esophagus, stomach, liver, brain, lung, kidney etc.).
In another embodiment, generate individual GCI scoring, it provides the information obtaining the risk of at least one disease or state or the susceptibility at least one disease or state about individuality of easy understand.In one embodiment, multinomial GCI is generated for different diseases or state to mark.In another embodiment, at least one GCI scoring can be accessed by online entrance.Or can be provided to one item missing GCI with paper form and mark, follow-up renewal also provides with paper form.In one embodiment, provide the access at least one GCI scoring to registered user, this registered user is the individuality of booking service.In an alternative embodiment, access rights are provided to nonregistered user, wherein they can have the limited access rights of at least one in their GCI scoring of access, or they can allow the Initial Report of at least one generated in their GCI scoring, but by means of only the customized report just generating renewal of paying.In another embodiment, care manager and supplier, such as paramedic, doctor and genetic consultant, also can have the authority of at least one in the individual GCI scoring of access.
Here also basic registration mode can be had.Basic registration can provide phenotypic spectrum, and wherein registered user can select the Genome Atlas all existing rules being applied to they, or existing well-regulated subset is applied to their Genome Atlas.Such as, they can select the rule only applying the disease phenotype can disposing (actionable).Basic registration can have different levels in registration grade.Such as, different levels can depend on that registered user wants the phenotype number associated with their Genome Atlas, or depends on the number of personnel of the phenotypic spectrum can accessing them.Another level of basic registration can by the factor specific to individuality, and the phenotype (as age, sex or medical history) such as known already is incorporated to their phenotypic spectrum.Another level again of basic registration can allow individual at least one the GCI scoring generated for disease or state.If cause any change of at least one GCI scoring due to the change in the analysis for generating at least one GCI scoring, the variations of this level can allow individual automatic renewal of specifying at least one the GCI scoring generated for disease or state further.In some embodiments, e-mail, voice messaging, text message, postal delivery or fax can be passed through and notice renewal automatically to individuality.
Registered user also can generate the report of the phenotypic spectrum with them and the information (such as about heredity and the medical information of phenotype) about phenotype.Such as, the popularity of phenotype in colony, the genetic variant for dependency, the molecular mechanism causing phenotype, the methods for the treatment of for phenotype, the therapeutic choice for phenotype and protective action can be comprised in report.In other embodiments, report can also comprise the information of the similarity between such as individual genotype and the genotype of other individualities (as famous person or other celebrities).Information about similarity may be, but not limited to, number and the possible similar phenotype of percent homology, identical variation.These reports may further include at least one GCI scoring.
If online access is reported, then report and the link of other positions being connected to the further information had about phenotype also can be provided, be connected to the link of the online support group of the people with identical phenotype or one or more similar phenotype and message board, contact the link of online genetic consultant or doctor or be connected to the phone or on-the-spot link of preengaging that arrange genetic consultant or doctor.If report is paper form, then information can be the site location of above-mentioned link or the telephone number of genetic consultant or doctor and address.Which information is the phenotypic spectrum which phenotype registered user also can select be included in them neutralize is included in their report.Phenotypic spectrum and report also can be obtained by the care manager of individuality or supplier, such as paramedic, doctor, psychiatrist, psychologist, treatment expert or genetic consultant.Whether registered user also can select phenotypic spectrum and report or its partial content to be obtained by the care manager of individual or supplier.
The present invention also can comprise the senior level (premiumlevel) of registration.The senior level of registration digitally keeps its Genome Atlas after generation initial table type spectrum and report, and registered user can utilize the dependency of the renewal obtained by nearest research to generate phenotypic spectrum and report.In another embodiment, registered user can utilize the dependency of the renewal obtained by nearest research to generate risk distribution figure and report.Because research discloses genotype and the new dependency between phenotype, disease or state, new rule will be produced based on these new dependencys, and new rule can be applied to the Genome Atlas having stored and kept.New rule can associate previously do not associate with any phenotype genotype, genotype is joined with new phenotypic correlation, revise existing dependency or the basis adjusting GCI and mark be provided based on newfound genotype and associating between disease or state.Can inform by e-mail or other electronics mode the dependency that registered user is new, and if be interested phenotype, they can select the phenotypic spectrum upgrading them by new dependency.Registered user can be chosen as upgrade paying at every turn, be repeatedly upgrading or unlimitedly upgrading the logon mode of paying at the appointed time time limit (such as, 3 months, 6 months or 1 year).Another registration level can be, no matter when creates new rule based on new dependency, and registered user makes their phenotypic spectrum or risk distribution figure automatically upgrade, instead of when individual selection upgrades their phenotypic spectrum or risk distribution figure.
In the another aspect of registration, registered user can serve below to nonregistered user introduction: generate the association rules between phenotype and genotype, determines individual Genome Atlas, rule is applied to Genome Atlas, and generates individual phenotypic spectrum.Registered user can make registered user mention preferential service subscription price by introducing or make its existing registration upgrading.Recommended individuality can in finite time free access or enjoy discount cost of registering.
Phenotypic spectrum and report and risk distribution figure and report can be generated for the mankind and non-human individuals.Such as, individuality can comprise other Mammals, such as ox, horse, sheep, dog or cat.As used in this, registered user is the human individual by buying or pay one or more service and subscribed services.Service can include, but are not limited to following one or more: the Genome Atlas determining themselves or another individuality (child of such as registered user or pet); Obtain phenotypic spectrum; Updating form type spectrum and acquisition are based on their Genome Atlas and the report of phenotypic spectrum.
In another aspect of this invention, can assemble from individuality and show that " regional deployment (field-deployed) " mechanism is to generate individual phenotypic spectrum.In a preferred embodiment, individuality can have the initial table type spectrum generated based on genetic information.Such as, generate and comprise for not isophenic risk factor and the treatment of suggestion or the initial table type spectrum of preventive measures.Such as, phenotypic spectrum can comprise the information for the available pharmacological agent about a certain state and/or the suggestion for changes in diet or workout scheme.Individual can select to see the doctor or genetic consultant or by Web portal or phone contact doctor or genetic consultant to discuss their phenotypic spectrum.Individuality can determine to take certain course of action, such as, adopts specific pharmacological agent, changes their diet etc.
Then, individuality can submit to biological sample to assess the change of its physical state and may changing of risk factor subsequently.Individual such as, can determine this change by directly biological sample being submitted to the mechanism (or associated mechanisms, the mechanism concludeed a contract or treaty by the entity of the hereditary distribution plan of generation and phenotypic spectrum) generating Genome Atlas and phenotypic spectrum.Or individuality can utilize " regional deployment " mechanism, and wherein their saliva, blood or other biological sample can be submitted in the proofing unit at place of its family by individuality, are analyzed by third party, and data are through transmitting to be included in another phenotypic spectrum.Such as, individuality can receive initial phenotype report based on its genetic data thus to the individuality report of myocardial infarction (MI) lifetime risk with increase.This report also can have the suggestion of preventive measures to reduce the risk of MI, such as anticholesteremic agent and metatrophia.Individual can select to contact genetic consultant or doctor to discuss this report and preventive measures and to determine their diet of change.After adopting new diet for some time, individuality can go to see that their individual doctor is to measure its cholesterol levels.New information (cholesterol levels) can be transmitted (such as, pass through Internet) to the entity with genomic information, and new information is for generating individual new phenotypic spectrum, and the new risk factor of myocardial infarction and/or other state.
Individuality also can use " regional deployment " mechanism or directly mechanism to determine its individual reaction for concrete pharmacological agent.Such as, individuality can measure its reaction for medicine, and this information may be used for determining more effective treatment.Measurable information comprises, but be not limited to meta-bolites level, glucose level, ion concentration (such as, calcium, sodium, potassium, iron), VITAMIN, cytometry, weight index (BMI), protein level, transcript level, heart rate etc., these information can be determined by the method easily utilized and can comprise to assess mark to compose with initial gene picture group the overall risk combining to determine to revise in the algorithm.
Term " biological sample " refers to any biological sample that can be separated from individuality, and it comprises the sample that therefrom can be separated genetic material.As used herein, " genetic material " refers to DNA and/or RNA that be that obtain from individuality or that be derived from individuality.
As employed herein, term " genome " is used for representing a whole set of chromosomal DNA found in the nucleus of human body cell.Term " genomic dna " refers to that nature is present in the one or more chromosomal DNA molecule in the nucleus of human body cell, or a part for chromosomal DNA molecule.
Term " Genome Atlas " refers to one group of information about genes of individuals, and whether such as specific SNP or sudden change exist.Genome Atlas comprises individual genotype.Genome Atlas also can be individual basic complete genomic sequence.In some embodiments, Genome Atlas can be at least 60%, 80% or 95% of individual complete genomic sequence.Genome Atlas can be the individual complete genomic sequence of about 100%.When mentioning Genome Atlas, " its part " refers to the Genome Atlas of the subset of the Genome Atlas of full-length genome.
Term " genotype " refers to the specific genetic composition of individual DNA.Genotype can comprise individual genetic variant and genetic marker.Genetic marker and genetic variant can comprise Nucleotide repetition, Nucleotide insertion, nucleotide deletion, chromosome translocation, karyomit(e) repeats or copy number makes a variation.Copy number variation can comprise the repetition of micro-satellite, Nucleotide repeats, kinetochore is repeated or telomere repeats.Genotype also can be SNP, haplotype or double body type (diplotype).Haplotype can refer to locus or allelotrope.Haplotype also can be called one group of single nucleotide polymorphism (SNP) on the single chromatid that statistically associates.Double body type is one group of haplotype.
Term single nucleotide polymorphism or " SNP " refer to the specific gene seat showing variation (such as at least 1 percentage point (1%)) on chromosome relative to the identity of the nitrogenous choline be present in human population on a locus.Such as, when body may have adenosine (A) on the specific nucleotide position of given gene one by one, another individuality may have cytosine(Cyt) (C), guanine (G) or thymus pyrimidine (T) on this position, thus there is SNP on this specific position.
As used herein, term " SNP genomic profiles " refers to the base contents of individual DNA given on the SNP position of whole individual whole genome DNA sequence dna." SNP distribution plan " refers to complete genomic profiles, or refers to one part, the SNP distribution plan of more local that such as may be relevant with specific gene or specific one group of gene.
Term " phenotype " is for describing individual quantitative trait or feature.Phenotype includes, but are not limited to medical science and medical condition.Medical condition comprises disease and disorder.Phenotype also can comprise health proterties, such as color development, as the physiological character of lung volume, the mental trait kept as memory, the mood proterties as angry controllability, the racial traits as ethnic background, as the family feature of individuality class origin position and as age expectation or the age characteristics of not isophenic age of onset.Phenotype also can be monogenic, wherein it is believed that a gene may join with phenotypic correlation; Or polygenic, one of them above gene and phenotypic correlation join.
" rule " is for defining the dependency between genotype and phenotype.Rule can define dependency by numerical value, such as, by percentage, risk factor or confidence score.Rule can comprise the dependency of multiple genotype and phenotype." rule set " comprises more than one rule." new regulation " can be the rule showing the dependency of its rule at present between still non-existent genotype and phenotype.Not associated genotype and phenotypic correlation can join by new regulation.The genotype joined with phenotypic correlation also can join with the phenotypic correlation previously do not associated by new regulation." new regulation " also can be the existing rule revised by other factors (comprising another rule).Existing rule can due to the known features of individuality, such as race, family, geography, sex, age, family history or other phenotype previously determined, and revises.
As used in this, " genotype correlation " refers to the statistic correlation between idiotype (existence of such as a certain sudden change or multiple sudden change), and tends to the possibility that a kind of phenotype (such as specified disease, state, physical state and/or the mental status) occurs.The frequency observing particular phenotype under specific gene type exists determines the degree of genotype correlation or occurs the possibility of specific phenotype.Such as, as what describe in detail at this, cause the SNP of apolipoprotein E isotype relevant to bringing out Early onset Alzheimer.Genotype correlation also can refer to the dependency or the negative correlation that are wherein not inclined to generation phenotype.Genotype correlation also can represent that individuality has phenotype or tends to occur the assessment of phenotype.Can by numeric representation genotype correlation, such as percentage ratio, the relative risk factor, Effect Evaluation or confidence score.
Term " phenotypic spectrum " refers to the set of the multiple phenotypes relevant to individuality genotype or multiple genotype.Phenotypic spectrum can comprise by one or more rule being applied to information that Genome Atlas produces or the information about the genotype correlation that is applied to Genome Atlas.The generate rule phenotypic spectrum that can be associated with phenotype by the multiple genotype of application.Probability or assessment can be expressed as numerical value, such as percentage ratio, the risk factor of numeral or the fiducial interval of numeral.Probability also can be expressed as height, in or low.Phenotypic spectrum also can show whether phenotype exists or produce the risk of phenotype.Such as, phenotypic spectrum can show the existence of blue eyes or the excessive risk of diabetes occurs.The prognosis that phenotypic spectrum also can show to predict, the reaction of result for the treatment of or the treatment to medical condition.
Term risk distribution plan refers to the set for more than one disease or the GCI scoring of state.GCI scoring is based on to idiotype and the analysis associated between one or more diseases or state.Risk distribution figure can show the GCI scoring by classification of diseases grouping.Further, risk distribution figure can show how with Individual Age or multiple risk factor adjustment and predict the information of the change that GCI marks.Such as, for specified disease GCI scoring can consider changes in diet or take preventive measures (stop smoking, take medicine, underwent bilateral radical mastectomy, uterectomy) effect.GCI scoring can be shown as the combination of numerical value metering, figure display, audio feedback or any aforementioned manner.
As used herein, term " online entrance " refers to the information source of accessing easily the alternate manner that information carries out similar access individual by computer and internet site, phone or permission.Online entrance can be encryption website.This website can provide to encrypt with other and the linking of non-encrypted website, such as, connect the link of the encryption website with individual phenotypic spectrum or connect the link of non-encrypted website (message board as the individuality of total particular phenotype).
Except as otherwise noted, enforcement of the present invention can utilize the molecular biology in those skilled in the art's limit of power, cytobiology, biological chemistry and immunologic routine techniques and operation instruction.These routine techniquess comprise separate nucleic acid, polymer array synthesizes (polymerarraysynthesis), hybridization, connect the hybridization check of (ligation) and applying marking thing.Present invention illustrates the concrete illustration of proper technology and give reference.But, also can use the ordinary method of other equivalence.Other routine techniques and operation instruction can find in following standard laboratory manual and document: such as, genome analysis: laboratory manual series (volume I-IV) (GenomeAnalysis:ALaboratoryManualSeries (Vols.I-IV)), PCR primer: laboratory manual (PCRPrimer:ALaboratoryManual), molecular cloning: laboratory manual (MolecularCloning:ALaboratoryManual) (being all derived from CSH Press (ColdSpringHarborLaboratoryPress)), Stryer, L. (1995) biological chemistry (the 4th edition) Freeman, New York, Gait, " oligonucleotide is synthesized: hands-on approach (OligonucleotideSynthesis:APracticalApproach) " 1984, IRL press, London, Nelson and Cox (2000), Lehninger, biochemical theory, the third edition, W.H.FreemanPub., New York, N.Y., and (2002) biological chemistry such as Berg, the 5th edition, W.H.FreemanPub., New York, N.Y., the full content of above-mentioned all documents is incorporated herein by reference at this.
Method of the present invention comprises analyzes genes of individuals picture group spectrum to provide the molecular information about phenotype to individuality.As what describe in detail at this, individuality provides the genetic material generating individual Genome Atlas.By making Genome Atlas compare with the database established with the human genotype correlation verified, the data of query individual Genome Atlas related gene type dependency.The database of the genotype correlation established and verify can from the document of the peer review (peer-reviewed), and passed judgment on further by the council of expert one or more in this area (such as geneticist, epidemiologist or statistician), and verify.In a preferred embodiment, rule is formulated based on the genotype correlation of empirical tests, and is applied to individual Genome Atlas to generate phenotypic spectrum.Analytical results (phenotypic spectrum) and the explanation of genes of individuals picture group spectrum are supplied to the care manager of individuality or individual together with supportive information, thus give the ability of individuality health care being carried out to individualized selection.
Method of the present invention is described in detail in FIG, wherein first generates individual Genome Atlas.Genes of individuals picture group composes the information that will comprise about the genes of individuals based on heritable variation and genetic marker.Heritable variation is genotype, and its constitutive gene picture group is composed.These heritable variations or genetic marker comprise, but be not limited to the repetition of single nucleotide polymorphism, list and/or polynucleotide, list and/or polynucleotide disappearance, micro-satellite repetition (usually have 5 ~ 1, a small amount of Nucleotide of 000 repeating unit repeats), dinucleotides repetition, Trinucleotide repeats, sequence reorganization (comprising transposition and repetition), copy number variation (disappearance on specific gene seat and increase) etc.Other heritable variation comprises karyomit(e) repetition and transposition and kinetochore and repeats and telomere repetition.
Genotype also can comprise haplotype and double body type.In some embodiments, Genome Atlas can have at least 100,000,300,000,500,000 or 1,000,000 genotype.In some embodiments, Genome Atlas can be substantially individual complete genomic sequence.In other embodiments, Genome Atlas is the individual complete genomic sequence of at least 60%, 80% or 95%.Genome Atlas can be the individual complete genomic sequence of about 100%.The genetic material comprising target material includes, but are not limited to the DNA (or cDNA) of genomic dna or RNA sample or the amplification of not increasing.Target material can for comprising the specific region of the genomic dna of interested especially genetic marker.
In the step 102 of Fig. 1, individual genetic material is separated from the biological sample of individuality.These biological samples include, but are not limited to blood, hair, skin, saliva, seminal fluid, urine, fecal materials, sweat, oral cavity (buccal) and various bodily tissue.In some embodiments, tissue sample directly can gather from individuality, and such as buccal sample can be swabbed inside its cheek by individuality swab and obtain.Such as other sample of saliva, seminal fluid, urine, fecal materials or sweat also can be provided by individuality.Other biological sample can be extracted by health professional (such as bleeder, nurse or doctor).Such as, blood sample can be extracted from individuality by nurse.Biopsy can be undertaken by health professional, and health professional also can utilize test kit effectively to obtain sample.Little cylinder skin samples can be pipetted or use pin to pipette little tissue or fluid sample.
In some embodiments, the test kit of the specimen collection container had for individual biological sample is provided to individuality.Test kit also can provide the individual specification sheets directly gathering himself sample, such as, need to provide how many hairs, urine, sweat or saliva.Test kit also can comprise the individual specification sheets requiring to be extracted by health professional tissue sample.Test kit can comprise and by the place of third party's collected specimens, such as, test kit can be supplied to subsequently from the health institution of individual collected specimens.Test kit can also be provided for by Sample delivery to the return package of sample preparation mechanism, and in this mechanism, genetic material is separated (step 104) from biological sample.
Can according to the genetic material of any one method DNA isolation or the RNA from biological sample in several known organism chemistry and molecular biology method, see people such as such as Sambrook, molecular cloning: laboratory manual (MolecularCloning:ALaboratoryManual) (cold spring harbor laboratory, New York) (1989).Also several commercially available test kit for DNA isolation from biological sample or RNA and reagent is had, the test kit that such as can obtain from DNAGenotek, GentraSystems, Qiagen, Ambion and other supplier and reagent.Buccal sample test kit is easy to be commercially available, such as, derive from the MasterAmp of EpicentreBiotechnologies tMbuccalSwabDNA extracts test kit, extracts the test kit of DNA equally in addition, such as, derive from the Extract-N-Amp of SigmaAldrich from blood sample tM.The DNA being derived from other tissue can by with protease digestion tissue with heat-treat, Centrifuge A sample and the unwanted material of use phenol-chloroform extraction, to be stayed in aqueous phase by DNA and obtain.Then can by the further DNA isolation of ethanol precipitation.
In a preferred embodiment, isolation of genomic DNA from saliva.Such as, use the DNA that can obtain from DNAGenotek from gathering test kit technology, the individual saliva sample that gathers is used for Clinical Processing.Sample can at room temperature store easily and transport.After by Sample delivery to the suitable laboratory of carrying out processing, carry out DNA isolation by carrying out thermally denature and protease digestion (usually utilizing the reagent by gathering test kit supplier and providing to carry out at least 1 hour at 50 DEG C) to sample.Then Centrifuge A sample, and alcohol settling is carried out to supernatant liquid.DNA precipitation is suspended in and is suitable in the damping fluid of subsequent analysis.
In another embodiment, RNA can be used as genetic material.Especially, the heritable variation can expressed from mRNA qualification.Term " messenger RNA(mRNA) " or " mRNA " include, but are not limited to premessenger RNA transcript, transcript processing intermediate, prepare for the translation of a gene or multiple gene and the ripe mRNA transcribed or the nucleic acid being derived from mRNA transcript.Transcript processing can comprise montage, editor and degraded.As used in this, the nucleic acid being derived from mRNA transcript refers to that mRNA transcript or its subsequence finally serve as the nucleic acid of its synthesis template.Therefore, by the cDNA of mRNA reverse transcription, the DNA increased from cDNA, be derived from mRNA transcript from the RNA etc. that transcribes of DNA of amplification.Methods known in the art can be used from any one isolation of RNA several bodily tissue, such as, use the PAXgene obtained from PreAnalytiX tMblood rna system is isolation of RNA from unassorted (unfractionated) whole blood.Typically, mRNA will be used for reverse transcription cDNA, and cDNA is used subsequently or carries out increasing for genetic variation analysis.
Before Genome Atlas is analyzed, usually by the cDNA amplification genetic material of DNA or RNA reverse transcription.Can by multiple method DNA amplification, many in these methods employ PCR.See such as, round pcr: DNA cloning mechanism and application (PCRTechnology:PrinciplesandApplicationsforDNAAmplificati on) (Ed.H.A.Erlich, FreemanPress, NY, N.Y., 1992); PCR scheme: methods and applications guide (PCRProtocols:AGuidetoMethodsandApplications) (people such as Eds.Innis, AcademicPress, SanDiego, Calif., 1990); The people such as Mattila, NucleicAcidsRes.19,4967 (1991); The people such as Eckert, PCR method and application (PCRMethodsandApplications) 1,17 (1991); PCR (people such as Eds.McPherson, IRLPress, Oxford); With United States Patent (USP) the 4th, 683,202,4,683,195,4,800,159,4,965,188 and 5,333, No. 675, above-mentioned each document is incorporated herein by reference with its full content at this.
Other amplification method be applicable to comprises ligase chain reaction (LCR) (such as, Wu and Wallace, genomics, 4, 560 (1989), the people such as Landegren, science, 241, the people such as 1077 (1988) and Barringer, gene, 89:117 (1990)), transcription amplification (the people such as Kwoh, Proc.Natl.Acad.Sci.USA86:1173-1177 (1989) and WO88/10315), self-sustained sequence replication (the people such as Guatelli, Proc.Nat.Acad.Sci.USA, 87:1874-1878 (1990) and WO90/06995), selective amplification (the United States Patent (USP) the 6th of target polynucleotide sequence, 410, No. 276), consensus sequence primed polymerase chain reaction (CP-PCR) (United States Patent (USP) the 4th, 437, No. 975), arbitrarily primed polymerase chain reaction (AP-PCR) (United States Patent (USP) the 5th, 413, 909, 5, 861, No. 245), based on sequence amplification (nucleicacidbasedsequenceamplification) (NABSA) of nucleic acid, rolling circle amplification (RCA), multiple displacement amplification (multipledisplacementamplification) (MDA) (United States Patent (USP) the 6th, 124, 120 and 6, 323, No. 009) and ring to circle amplification (circle-to-circleamplification) (the C2CA) (people such as Dahl, Proc.Natl.Acad.Sci101:4548-4553 (2004)).(see United States Patent (USP) the 5th, 409,818,5,554,517 and 6,063, No. 603, above-mentioned each document is incorporated herein by reference at this).At United States Patent (USP) the 5th, 242,794,5,494,810,5,409,818,4,988,617,6,063,603 and 5,554, No. 517 and U.S. Patent application the 09/854th, describe other amplification method operable in No. 317, above-mentioned each document is incorporated herein by reference at this.
Use the generation of the Genome Atlas of any one completing steps 106 in several method.Several method in order to identify heritable variation known in the art, and these methods comprise, but any one DNA sequencing carried out be not limited by several method, the method of PCR-based, fragment length polymorphism analyzes (restriction fragment length polymorphism (RFLP), crack fragment length polymorphism (CFLP)), use allele specific oligonucleotide as template hybridizing method (such as, TaqManPCR method, invader method (invadermethod), DNA chip method), use the method for primer extension reaction, mass spectrometry (MALDI-TOF/MS method) etc.
In one embodiment, high-density DNA array is used for SNP qualification and distribution plan generation.These arrays can be buied (see Affymetrix from Affymetrix and Illumina 500KAssayManual, Affymetrix, SantaClara, CA (being incorporated herein by reference); humanHap650Y gene type superbead chip (genotypingbeadchip), Illumina, SanDiego, CA).
Such as, AffymetrixGenomeWideHumanSNPArray6.0 can be used to pass through more than 900, and the SNP of 000 carries out gene type to generate SNP distribution plan.Or, can by use AffymetrixGeneChipHumanMapping500KArraySet determine through complete genome sampling analysis more than 500,000 SNP.In these analytical procedures, that the subset of human genome uses digestion with restriction enzyme, that joint connects human gene group DNA is increased by single primer amplification reaction.As shown in Figure 2, the concentration of the DNA connected can then be determined.The DNA break then increased, and the quality determining sample before continuing step 106.If samples met PCR and fragmentation standard, then sex change, mark are carried out to sample and the microarray that forms with the little DNA probe of specific position on the quartzy face of coating is subsequently hybridized.Monitor with amplification DNA sequence dna change with the amount of the marker of each probe hybridization, thus produce sequence information and final SNP gene type.
The use of AffymetrixGeneChip500KAssay is carried out according to the guidance of manufacturers.In brief, first with the genomic dna that the digestion of NspI or StyI restriction endonuclease is separated.Then the DNA digested is connected with NspI or the StyI linker oligonucleotides of annealing with NspI or StyI restricted DNA respectively.Then the DNA comprising joint after connecting is undertaken increasing to produce the amplification of DNA fragments between about 200 to 1100 base pairs by PCR, and this confirmed by gel electrophoresis.The PCR primer meeting amplification standard carries out purifying with quantitatively to carry out fragmentation.PCR primer DNaseI carries out rupturing to reach best DNA chip hybridization.After fracture, DNA fragmentation should be less than 250 base pairs, and average out to 180 base pair, this is confirmed by gel electrophoresis.Then terminal deoxynucleotidyl transferase is used to meet the sample of fragmentation standard with biotin compound mark.Then by the fragment sex change of mark, then hybridize in GeneChip250K array.After hybridization, dye by the treating processes pair array of three steps before scanning, three described treating processess are made up of the following step: streptavidin phycoerythrin (SAPE) dyes, the antibody amplification step utilizing biotinylated anti-streptavidin antibody (goat) subsequently, and with the final dyeing of streptavidin phycoerythrin (SAPE).After the flag, array array keeps damping fluid to cover, and then scans with the scanner of such as AffymetrixGeneChipScanner3000.
After AffymetrixGeneChipHumanMapping500KArraySet scanning, carry out data analysis according to the guidance of manufacturers, as shown in Figure 3.In brief, GeneChip function software (GCOS) is used to obtain raw data.Also can by using AffymetrixGeneChipCommandConsole tMobtain data.Analyze with GeneChip genotypic analyses software (GTYPE) after obtaining primary data.For the purposes of the present invention, eliminating GTYPE calls the sample that rate (callrate) is less than 80%.Then with BRLMM and/or SNiPer Algorithm Analysis, sample is tested.Get rid of BRLMM call rate be less than 95% or SNiPer call the sample that rate is less than 98%.Finally, carry out association analysis, and get rid of SNiPer quality index and be less than 0.45 and/or Ha Di-Weinberg p-value sample of being less than 0.00001.
That analyzes as DNA microarray substituting or adding, and can detect heritable variation, such as SNP and sudden change by DNA sequencing.Also DNA sequencing can be used to check order to the major portion of individuality or full gene group sequence.Usually, conventional DNA sequencing is with analytic thread dististyle stage group people such as (, Proc.Natl.Acad.Sci.USA74:5463-5467 (1977)) Sanger based on polyacrylamide gel fractional separation.Alternative method that is that developed and that proceed to develop improves speed and the simplicity of DNA sequencing.Such as, high-throughput and single-molecule sequencing platform can from 454LifeSciences (Branford, CT) (the people such as Margulies, nature, (2005) 437:376-380 (2005)), Solexa (Hayward, CA), HelicosBioSciences company (Cambridge, MA) (in No. 11/167046th, the U. S. application that on June 23rd, 2005 submits to) and Li-CorBiosciences (Lincoln, NE) (in No. 11/118031st, the U. S. application that on April 29th, 2005 submits to) is commercially available, or just developed by them.
After generating individual Genome Atlas in step 106, digitizing stores this collection of illustrative plates in step 108, and this collection of illustrative plates can cryptographically store in digitizing.Encode to this Genome Atlas the part being stored as data set with computer-readable format, and can be stored as database, wherein Genome Atlas by " savings ", and can access later again.Data set comprises multiple data point, and wherein each data point relates to body one by one.Each data point can have multiple data element.A data element is the unique identifier identifying individual Genome Atlas.It also can be barcode.Another data element is genotype information, the SNP of such as genes of individuals group or nucleotide sequence.Data element corresponding to genotype information also can be included in data point.Such as, if genotype information comprises the SNP identified by microarray analysis, so other data element can comprise microarray SNP identifier, No. SNPrs and polymorphic nucleotide (polymorphicnucleotide).Other data element can be the chromosome position of genotype information, the quality metrics of data, raw data file, data image and extraction intensity scores.
Individual specific factors, such as body data, medical data, race, family, geography, sex, age, family history, known phenotype, demographic data, exposure data (exposuredata), lifestyle data, behavioral data and other known phenotype, also can be included as data element.Such as, these factors can comprise, but be not limited to individual: the position, residence of birthplace, father and mother and/or grand parents, relationship family, position, residence, ancestors, envrionment conditions, known healthy state, known drug interaction, domestic hygiene condition, mode of life condition, diet, exercise habits, marital status and physical measurement data (such as, body weight, height, cholesterol levels, heart rate, blood pressure, gentle other take off data known in the art of G/W).Individual relative or the above-mentioned factor of ancestors (such as, father and mother and grand parents) also can be introduced as data element and for determining individual phenotype or the risk of state.
Specific factor can obtain from questionnaire or from the care manager of individuality.Then, the information from the collection of illustrative plates of " savings " can be accessed and use by required.Such as, in the initial assessment of the genotype correlation of individuality, will individual full detail (usually on whole genome or the SNP that obtains from whole genome or other genome sequence) be analyzed for determining genotype correlation.In follow-up analysis, can access on demand or suitably from store or the full detail of Genome Atlas of savings or its part.
genome Atlas compares with genotype correlation database
In step 1l0, genotype correlation obtains from scientific literature.The genotype correlation of heritable variation is by determining in the analysis that whether there are one or more interested phenotypic characters and carry out the colony of the individuality that gene type spectrum is tested.Then detect to determine whether that specific allelic existence is associated with interested proterties to the allelotrope of heritable variation each in gene type spectrum or polymorphism.Correlation analysis can be carried out by standard statistical routines, and record the dependency of the statistically significant between heritable variation and phenotypic characteristic.Such as, may determine, the existence of the allelotrope A1 of polymorphism A is relevant to heart trouble.As a further example, may find at the allelotrope A1 of polymorphism A relevant to the increase of risk of cancer with the combination existence of the allelotrope B1 of polymorphism B.The result analyzed can be announced in peer review document, is confirmed, and/or is analyzed by Committee of Experts's (such as, geneticist, statistician, epidemiologist and doctor), and also can verify by other study group.
Be the example of the dependency between genotype and phenotype in Fig. 4,5 and 6, be wherein applied to rule between the genotype of Genome Atlas and phenotype based on these dependencys.Such as, in Fig. 4 A and B, each row corresponds to phenotype/locus/race, and wherein Fig. 4 C to I comprises the further information of the dependency of each row in these row.As an example, in Figure 4 A in " abbreviation of phenotype title " of the BC index of abridging as Fig. 4 M phenotype title the abbreviation for mammary cancer that indicates.In BC_4 (it is the class name of locus) this line, gene LSP1 is relevant to mammary cancer.As shown in FIG. 4 C, disclosed in this dependency is confirmed or functional SNP be rs3817198, and disclosed risk allelotrope is C, and non-risk allelotrope is T.Disclosed SNP and allelotrope are confirmed by publication (the basic open source literature such as, in Fig. 4 E-G).In the example of the LSP1 of Fig. 4 E, basic open source literature is the people such as Easton, nature, 447:713-720 (2007).Figure 22 and 25 has been further listed in dependency.The individual risk for a kind of state or phenotype of the correlation calculations in Figure 22 and 25 can be used, such as, calculate GCI or GCIPlus scoring.GCI or GCIPlus scoring also can introduce the information of the popularity of such as state, as in fig 23.
Or, dependency can be formed by the Genome Atlas stored.Such as, the individuality with the Genome Atlas of storage also might have stored known phenotypic information.Genotype correlation can be formed to the analysis of the Genome Atlas stored and known phenotype.As an example, 250 have and store the individuality of Genome Atlas also to have previous diagnosis be the storage information suffering from diabetes.Carry out analyzing to their Genome Atlas and and the control group of non-diabetic individuality compare.Then determine that previous diagnosis is that the individuality suffering from diabetes has the ratio of specific genetic variant compared with control group higher, thus can draw genotype correlation between specific genetic variant and diabetes.
In step 112, based on the dependency formation rule between certified genetic variant and particular phenotype.Such as can based on be mutually related genotype and the phenotype create-rule listed by table 1.Rule based on dependency can introduce other factors, and such as, sex (e.g., Fig. 4) or race's (Figure 4 and 5) are to produce as the Effect Evaluation in Figure 4 and 5.Other generation by rule is measured and can be assessed as the relative risk in Fig. 6 increases.The relative risk increase of Effect Evaluation and estimation from disclosed document, or can be calculated by disclosed document.Or rule can based on the dependency produced by the Genome Atlas stored and previously known phenotype.In some embodiments, rule can based on the dependency in Figure 22 and 25.
In a preferred embodiment, genetic variant is SNP.Although SNP occurs on unit point, be carried at that the allelic individuality of specific SNP on a site is usually measurable carries special SNP allelotrope on other site.SNP is produced by linkage disequilibrium (linkagedisequilibrium) with making the individual allelic dependency easily sending out disease or state, and the frequency that nonrandom association occurs the allelotrope wherein in colony on two or more locus is greater than or less than to be estimated to be randomly formed by recombinating and the frequency that obtains.
Other genetic marker or modification (such as Nucleotide repeats or inserts) also can be shown as the genetic marker generation linkage disequilibrium with specific phenotypic correlation.Such as, Nucleotide inserts and phenotypic correlation, and SNP and Nucleotide insert linkage disequilibrium occurs.Based on the dependency formation rule between SNP and phenotype.Also the rule inserting the dependency between phenotype based on Nucleotide can be formed.Arbitrary rule or two rules can be applied to Genome Atlas, because the existence of a SNP can provide a certain risk factor, another rule can provide another risk factor, and can increase risk when combined.
By linkage disequilibrium, the specific allelic combination easily sending out the allelotrope of disease and the specific allelotrope of SNP or SNP is divided into from (cosegregate).Be called haplotype along the allelic particular combination of chromosomal SNP, and the region of DNA territory that wherein they occur to combine can be called haplotype section.Although haplotype section can be made up of a SNP, typical haplotype segment table shows and shows low haplotype diversity between individuals and the series usually with 2 of low recombination frequency or the SNP of multiple vicinity.The qualification that the one or more SNP being arranged in haplotype section carry out haplotype can be tested and appraised.Like this, usual SNP distribution plan may be used for qualification haplotype section instead of must identify all SNP in given haplotype section.
Become known gradually in SNP haplotype pattern and the genotype correlation between disease, state or physical state.For given disease, by the known haplotype pattern with the lineup of this disease compared with the lineup without this disease.By analyzing many individualities, the frequency of polymorphism in colony can be determined, and these frequencies or genotype can be associated with specific phenotype (such as disease or state) subsequently.The disease associated example of known SNP-is included in and the polymorphism of complement factor H in age-related macular degeneration (people such as Klein, science, 308:385-389, (2005)) and relevant to obesity close iNSIG2the modification (people such as Herbert, science, 312:279-283 (2006)) of gene.Other known SNP dependency comprises such as, comprise polymorphism (such as relevant with myocardial infarction rs10757274, rs2383206, rs13333040, rs2383207 and rs10116277 (people such as Helgadottir in the 9p21 region of CDKN2A with B, science, 316:1491-1493 (2007); The people such as McPherson, science, 316:1488-1491 (2007)).
SNP can be functional or non-functional.Such as, functional SNP cellular function has impact, thus causes phenotype, but non-functional SNP functionally mourns in silence, but with functional SNP, linkage disequilibrium can occur.SNP also can be synonym or non-synonym.The SNP of synonym is the wherein multi-form SNP causing identical peptide sequence, and is non-functional SNP.If SNP causes not homopolypeptide, so SNP is non-synonym and can is functional or non-functional.Also may be used for associating the phenotype relevant to double body type for the identification of the SNP of the haplotype in double body type (it is 2 or multiple haplotype) or other genetic marker.Information about the haplotype of individuality, double body type and SNP distribution plan can in the Genome Atlas of individuality.
In a preferred embodiment, for the rule that the genetic marker forming linkage disequilibrium based on another genetic marker associated with phenotype produces, this genetic marker can have the r being greater than 0.5 2or D ' score, this score is usually in the art for determining linkage disequilibrium.In a preferred embodiment, score is greater than 0.6,0.7,0.8,0.90,0.95 or 0.99.As a result, in the present invention, for can be identical or be different from and the functional of phenotypic correlation or disclosed SNP by phenotype and the genetic marker that individual Genome Atlas associates.Such as, use BC_4, test SNP and disclosed SNP is identical, is identical (Fig. 4 A and C) as the risk of test and non-risk allelotrope with disclosed risk and non-risk allelotrope.But for BC_5, CASP8 and the dependency with mammary cancer thereof, test SNP is functional from it or disclosed SNP is different, and the risk as test is the same with non-risk allelotrope for disclosed risk with non-risk allelotrope.That tests is directed relative to genomic normal chain with disclosed allelotrope, and can infer homozygous risk or non-risk genotype from these row, and this can generate the rule of the Genome Atlas of the individuality for such as registered user.In some embodiments, also can not characterization test SNP, but use disclosed SNP information, allelic differences or SNP can be identified based on another analytical procedure (such as TaqMan).Such as, the AMD_5 in Figure 25 A, disclosed SNP is rs1061170, but does not have characterization test SNP.Can by the LD Analysis and Identification test SNP of disclosed SNP.Or, can not use test SNP, but there is with TaqMan or other suitable analytical procedure evaluation the genes of individuals group of this test SNP.
Test SNP can be " directly (DIRECT) " or " label (TAG) " SNP (Fig. 4 E-G, Fig. 5).Direct SNP is the test SNP identical with disclosed or functional SNP, such as, for BC_4.Use European and Asian SNPrs1073640, direct SNP also may be used for the FGFR2 dependency of mammary cancer, wherein secondary allelotrope is A and other allelotrope is G (people such as Easton, nature, 447:1087-1093 (2007)).Also be the FGFR2 dependency of the mammary cancer in European and Aisa people another disclosed in or functional SNP be rs1219648 (people such as Hunter, Nat.Genet.39:870-874 (2007)).Tag SNP is the situation that test SNP is different from functional or disclosed SNP, as the situation of BC_5.Tag SNP also may be used for other genetic variant, such as, for the SNP of CAMTA1 (rs4908449), 9p21 (rs10757274, rs2383206, rs13333040, rs2383207, rs10116277), COL1A1 (rs1800012), FVL (rs6025), HLA-DQA1 (rs4988889, rs2588331), eNOS (rs1799983), MTHFR (rs1801133) and APC (rs28933380).
The database of SNP openly can obtain from following place: such as, InternationalHapMapProject is (see www.hapmap.org, TheInternationalHapMapConsortium, nature, 426.789-796 (2003), and TheInternationalHapMapConsortium, nature, 437:1299-1320 (2005)), human mutation database (theHumanGeneMutationDatabase) (HGMD) public data storehouse (see www.hgmd.org) and single nucleotide polymorphism database (theSingleNucleotidePolymorphismdatabase) (dbSNP) (see www.ncbi.nlm.nih.gov/SNP/).These databases provide SNP haplotype, or make it possible to determine SNP haplotype pattern.Therefore, these snp databases make it possible to the genetic risk factors on the basis detected as large-scale disease and state (such as cancer, inflammatory diseases, cardiovascular diseases, neurodegenerative disease and transmissible disease).These diseases or state can be disposed, wherein its process and methods for the treatment of of current existence.Process can comprise preventive treatment and improve the process of symptom and state, comprises and changing lifestyles.
Also other phenotypes many can be detected, such as health proterties, physiological character, mental trait, mood proterties, race, family and age.Health proterties can comprise the proterties of height, color development, eye color, body or such as energy, endurance and agility.Mental trait can comprise intelligence, memory capability or learning capacity.Race and family can comprise the qualification of family or race, or where the ancestors of individuality come from.Age can be determine individual actual age, or the genetics characteristics of individuality makes it relative to the age residing for total colony.Such as, individual actual age is 38 years old, but its genetics characteristics can determine that its memory capability or health states may for average 28 years old.Other age proterties can be individual predicted life.
Other phenotype also can comprise medical condition, such as " amusement " phenotype.These phenotypes can comprise the contrast with well-known individuality, such as, and foreign noble, statesman, famous person, inventor, sportsmen, musician, artist, businessperson and notorious individuality (such as criminal).Other " amusement " phenotype can comprise the contrast with other organism, such as, and bacterium, insect, plant or inhuman animal.Such as, individual possibility is interested look at that the Genome Atlas contrast of its Genome Atlas and its pet dog or ex-president can be how.
In step 114, rule is applied to the Genome Atlas of storage with the phenotypic spectrum of generation step 116.Such as, the information in Fig. 4,5 or 6 can the basis of formation rule or test to be applied to individual Genome Atlas.Rule can comprise about test SNP and the information of allelotrope and Effect Evaluation in Fig. 4, and wherein, the UNITS of Effect Evaluation is the unit of Effect Evaluation, such as OR, or odds ratio (95% fiducial interval) or mean value.Effect Evaluation can be genotype risk (Fig. 4 C-G) in a preferred embodiment, such as, for homozygous risk (homoz or RR), risk heterozygote (heteroz or RN) and non-risk homozygote (homoz or NN).In other embodiments, Effect Evaluation can be carrier's risk (carrierrisk), and it is that RR or RN is to NN.In embodiment other again, Effect Evaluation can based on allelotrope, allelotrope risk, and such as R is to N.Here also there is the genotype effects evaluation (such as, for 9 kinds of two locus Effect Evaluation possible genotype combination: RRRR, RRNN etc.) of two locus (Fig. 4 J) or three locus (Fig. 4 K).The test SNP frequency in public HapMap is also have recorded in Fig. 4 H and I.
In other embodiments, from Figure 21,22, the information of 23 and/or 25 may be used for information generated to be applied to individual Genome Atlas.Such as, information may be used for generating individual GCI or GCIPlus scoring (such as, Figure 19).Scoring may be used for the information (such as, Figure 15) of the genetic risk (lifetime risk such as estimated) being created on one or more states in individual phenotypic spectrum.The method allows the estimation lifetime risk or the relative risk that calculate one or more phenotype listed by Figure 22 or 25 or state.The risk of single status can based on one or more SNP.Such as, the calculated risk for phenotype or state can based at least 2,3,4,5,6,7,8,9,10,11 or 12 SNP, and the SNP wherein for calculated risk can be disclosed SNP, test SNP or more both (such as, Figure 25).
Calculated risk for state can based on the SNP listed by Figure 22 or 25.In some embodiments, the risk of state can based at least one SNP.Such as, the individual assessment for the risk of Alzheimer's disease (AD), colorectal carcinoma (CRC), osteoarthritis (OA) or exfoliation glaucoma (XFG) can based on 1 SNP (such as, be rs4420638 for AD, be rs6983267 for CRC, be rs4911178 and be rs2165241 for XFG for OA).For other state, such as fat (BMIOB), Graves' disease (GD) or hemochromatosis (HEM), individual calculated risk can (be such as, rs9939609 and/or rs9291171 for BMIOB based at least 1 or 2 SNP; DRB1*0301DQA1*0501 and/or rs3087243 for GD; Rs1800562 and/or rs129128 for HEM).For such as, but be not limited to the state of myocardial infarction (MI), multiple sclerosis (MS) or psoriasis (PS), 1,2 or 3 SNP may be used for assessing the individual risk for these states (is such as, rs1866389, rs1333049 and/or rs6922269 for MI; Rs6897932, rs12722489 and/or DRB1*1501 for MS; Rs6859018, rs11209026 and/or HLAC*0602 for PS).In order to assess the individual risk of restless leg syndrome (RLS) or celiac disease (CelD), 1,2,3 or 4 SNP can be used (to be such as, rs6904723, rs2300478, rs1026732 and/or rs9296249 for RLS; Rs6840978, rs11571315, rs2187668 and/or DQA1*0301DQB1*0302 for CelD).For prostate cancer (PC) or lupus (SLE), 1,2,3,4 or 5 SNP may be used for assessing the individual risk for PC or SLE (is such as, rs4242384, rs6983267, rs16901979, rs17765344 and/or rs4430796 for PC; Rs12531711, rs10954213, rs2004640, DRB1*0301 and/or DRB1*1501 for SLE).In order to assess the individual lifetime risk of macular degeneration (AMD) or rheumatoid arthritis (RA), 1,2,3,4,5 or 6 SNP can be used (to be such as, rs10737680, rs10490924, rs541862, rs2230199, rs1061170 and/or rs9332739 for AMD; Rs6679677, rs11203367, rs6457617, DRB*0101, DRB1*0401 and/or DRB1*0404 for RA).In order to assess the individual lifetime risk of mammary cancer (BC), 1,2,3,4,5,6 or 7 SNP (such as, rs3803662, rs2981582, rs4700485, rs3817198, rs17468277, rs6721996 and/or rs3803662) can be used.In order to assess the individual lifetime risk of Crohn disease (CD) or diabetes B (T2D), 1,2,3,4,5,6,7,8,9,10 or 11 SNP can be used (to be such as, rs2066845, rs5743293, rs10883365, rs17234657, rs10210302, rs9858542, rs11805303, rs1000113, rs17221417, rs2542151 and/or rs10761659 for CD; Rs13266634, rs4506565, rs10012946, rs7756992, rs10811661, rs12288738, rs8050136, rs1111875, rs4402960, rs5215 and/or rs1801282 for T2D).In some embodiments, the SNP on the basis determined as risk can form linkage disequilibrium with above-mentioned or the SNP listed in Figure 22 or 25.
Individual phenotypic spectrum can comprise many phenotypes.Especially, no matter before having symptom, symptom or in asymptomatic individuality (comprising the carrier of the susceptible allele of one or more disease/states), suffered from the disease by method evaluating patient of the present invention or other state (such as, possible drug reaction, comprises metabolism, effect and/or security) risk make it possible to carry out prognosis or diagnositc analysis to the susceptibility of multiple incoherent disease and state.Therefore, these methods provide the overall merit for the private medical service of disease or state and do not need to imagine in advance the test of any specified disease or state.Such as, method of the present invention makes it possible to evaluate based on the private medical service of any one in various states listed in genes of individuals picture group spectrum his-and-hers watches 1, Fig. 4,5 or 6.Such as, and these methods allow the individuality evaluating one or more phenotypes or state to estimate lifetime risk or relative risk, those phenotypes in Figure 22 or 25.
Described evaluation preferably provides about 2 in these states kind or multiple information, and the information of 3,4,5,10,20,50,100 or even more kinds of state more preferably in these states.In a preferred embodiment, at least 20 rules be applied to individual Genome Atlas and obtain phenotypic spectrum.In other embodiments, at least 50 rules are applied to individual Genome Atlas.The single rule of phenotype can be applied to monogenic phenotype.Also may be used for single phenotype more than the rule of, there is the monogenic phenotype of the probability of this phenotype in such as, multiple genetic variant impacts in polygenic phenotype or term single gene.
After preliminary sweep is carried out to few patients's Genome Atlas, when knowing additional Nucleotide modification, by carrying out the renewal of (or employing) idiotype dependency with the comparison of these additional Nucleotide modification (such as, SNP).Such as, step 110 can be carried out with one or several those of ordinary skill finding the genetic arts of new gene type dependency termly by search scientific literature, e.g., every day, to carry out weekly or monthly.Then, new gene type dependency can be confirmed by the council of the one or more experts in this area further.Then, step 112 can to upgrade based on the new regulation of the effective dependency of new confirmation termly.
New regulation can be included in genotype outside existing rule or phenotype.Such as, the genotype do not associated with any phenotype is found and new or existing phenotypic correlation.New regulation also may be used for the dependency between the phenotype that previously associated with it without genotype.New regulation also can determine having had now well-regulated genotype and phenotype.Such as, the existing rule based on the dependency between genotype A and phenotype A.It is relevant to phenotype A that new research discloses genotype B, thus produces the new regulation based on this dependency.Therefore another example for finding that phenotype B is relevant to genotype A, and formulates new regulation.
Can find based on known but in disclosed scientific literature, do not carry out the initial dependency confirmed time lay down a regulation.Such as, may someone report, genotype C is relevant to phenotype C.Other publication report, genotype D is relevant to phenotype D.Phenotype C and D is relevant symptom, and such as phenotype C is short of breath, and phenotype D is less lung volume.Utilize the Genome Atlas with the individuality of genotype C and D and phenotype C and D of existing storage by statistical method, or can find and confirm genotype C and phenotype D or the dependency between genotype D and phenotype C by further studying.Then, new regulation can be generated based on dependency that is newfound and that confirm.In another embodiment, the gene type spectrum with multiple individualities of specific or Relevant phenotype of storage can be studied to determine these individual total genotype, and determine dependency.New regulation can be generated based on this dependency.
Also can lay down a regulation to revise existing rule.Such as, the dependency between genotype and phenotype may partly be determined by known personal feature, such as, and other known phenotype any of race, family, geography, sex, age, family history or individuality.The rule based on these known personal features can be formulated and introduce in existing rule to provide the rule of correction.The selection of the rule that application is revised will depend on individual particular individual factor.Such as, rule may be 35% based on the probability with phenotype E individual when individuality has genotype E.But if individuality is specific race, described probability is 5%.New regulation can be formulated based on this result and be applied to the individuality with this particular race characteristic.Or, the existing rule that determined value is 35% can be applied, then apply another rule based on the racial traits of this phenotype.Rule based on known personal feature can be determined by scientific literature or determining based on the Genome Atlas to storage.When creating new regulation, can add new rule in step 114 and be applied to Genome Atlas, or can apply them termly, such as 1 year at least one times.
The information of the individual risk of disease also can be expanded along with the technical progress of more high resolving power SNP Genome Atlas.As mentioned above, use for scanning 500, the microarray technology of 000 SNP can generate initial SNP genomic profiles easily.Assuming that the situation of haplotype section, this numeral can be used for the typical profile of all SNP in genes of individuals group.Even so, estimate usually about 1,000 ten thousand SNP (theInternationalHapMapProject to occur in human genome; Www.hapmap.org).Along with carrying out practical and economic parsing (such as 1 with higher level of detail to SNP, 000,000,1,500,000,2,000,000,3, the microarray of 000,000 or more SNP) or the technical progress of genome sequencing aspect, more detailed SNP genomic profiles can be generated.Similarly, possibility is become by the progress of computer analysis method technology by making the renewal of the economic analysis of meticulousr SNP genomic profiles and the disease associated master data base of SNP-.
After step 116 generates phenotypic spectrum, registered user or its care manager can as in step 118 by online entrance or their Genome Atlas of website visiting or phenotypic spectrum.Also phenotypic spectrum will can be comprised and other report about the information of phenotypic spectrum and Genome Atlas is supplied to registered user or its care manager, as described in step 120 and 122.Can by reporting printing out, in the computer that is stored in registered user or watch online.
Fig. 7 shows the online report of example.Registered user can select to show single phenotype or more than one phenotype.Registered user also can have and different watches option, such as, and " QuickView " option as shown in Figure 7.Phenotype can be medical condition and different treatment in fast report and symptom can link to the webpage that other comprises the further information about process.Such as, by clicking medicine, the website of the information comprised about dosage, expense, side effect and effect that can lead.Also medicine and other can be treated and compare.Website also can comprise the link of the website of targeted drug manufacturers.Another link can provide the option of generating medicine genomics (pharmacogenomic) collection of illustrative plates to registered user, this by comprise based on its Genome Atlas they for the information that may react of medicine.Also the link of the replacement scheme for medicine can be provided, such as preventative behavior (as sports (fitness) and lose weight); And also can provide diet is supplemented, the link of dietary program and the link for neighbouring health club, healthy clinic, health care and rehabilitation supplier, city type spa (dayspa) etc.Education and information video, the summary of available treatment, possible therapy and general recommendations also can be provided.
Online report also can provide and arranges the link of individual doctor or genetic counseling reservation or access the link of online genetic consultant or doctor, thus provides the chance of the more information about its phenotypic spectrum of inquiry for registered user.Online report also can be provided in the link of line genetic counseling and doctor's inquiry.
Also can watch report in other forms, such as, for the comprehensive observing of single phenotype, which provide the more details for each classification.Such as, the more detailed statistics occurring the possibility of phenotype about registered user can be there is; About the more information of classical symptom or phenotype, the representative symptom of such as medical condition or the scope of health medical condition (as height); Or about the more information of gene and genetic variant, such as colony's popularity, as in the world or in country variant, or the colony's popularity in different ages scope or sex.Such as, Figure 15 shows the summary of multi-mode estimation lifetime risk perhaps.Individuality can watch the more information of particular state (such as prostate cancer (Figure 16) or Crohn disease (Figure 17)).
In another embodiment, report can be the report of " amusement " phenotype, such as, and the similarity of the Genome Atlas of genes of individuals picture group spectrum and well-known individuality (as Albert Einstein).Report can show genes of individuals picture group spectrum and Einsteinian genes of individuals picture group compose between percent similarity, and the prediction IQ of Einsteinian prediction IQ and this individuality can be shown further.Further information can comprise the situation that the Genome Atlas of total group and its IQ and this individuality and Einsteinian Genome Atlas and IQ compare.
In another embodiment, report can show all phenotypes be associated with the Genome Atlas of registered user.In other embodiments, report only can show and determines phenotype positively related with the Genome Atlas of individuality.Individual can select the specific subclass showing phenotype in other forms, such as only medical science phenotype or the medical science phenotype that only can dispose.Such as, the phenotype can disposed and relevant genotype thereof can comprise Crohn disease (relevant to IL23R and CARD15), type 1 diabetes (being correlated with HLA-DR/DQ), lupus (being correlated with HLA-DRB1), psoriasis (HLA-C), multiple sclerosis (HLA-DQA1), Graves disease (HLA-DRB1), rheumatoid arthritis (HLA-DRB1), diabetes B (TCF7L2), mammary cancer (BRCA2), colorectal carcinoma (APC), episodic memory (KIBRA) and osteoporosis (COL1A1).Individual also can select the subclass showing phenotype in report, such as, the only inflammatory diseases of medical condition or the health proterties of only medical condition.In some embodiments, individual can select by highlight calculate calculated risk those states (such as, Figure 15 A, D), only have high risk state (Figure 15 B) or only there is the state of comparatively low risk (Figure 15 C) and show all states this individuality being calculated to calculated risk.
Paying and be sent to individual information can be encrypt and maintain secrecy, and can control the individual access to these information.The information obtained by complex genome collection of illustrative plates can be supplied to individual data that are that be correlated with as approved by management, intelligible, medical treatment and/or that have highly impact.Information also can be have general importance, and has nothing to do with medical treatment.Cryptographically can transmit information by several mode to individuality, described mode includes, but are not limited to Entry Interface and/or mailing.More preferably, information cryptographically (is so selected if individual) to provide to individuality by Entry Interface, the wherein individual access rights that this Entry Interface is had to safety and maintains secrecy.This interface provides preferably by online, internet site's entrance, or selectively, is provided the alternate manner of secret, safety and wieldy access by phone or allow.Genome Atlas, phenotypic spectrum and report are provided to individual or its care manager by the data transmission of network.
Therefore, Fig. 8 shows the block diagram that can be generated the representative illustration logical device of phenotypic spectrum and report by it.Fig. 8 shows computer system (or digital device) 800, and it is for receiving and store Genome Atlas, analyzing gene type dependency, based on genotype correlation create-rule, rule being applied to Genome Atlas and producing phenotypic spectrum and report.Computer system 800 can be understood as can from the logical device of medium 811 and/or the network port 805 reading command, and this network port 805 can optionally be connected with the server 809 with mounting medium 812.The system shown in Fig. 8 comprises CPU801, disc driver 803, optional input unit (such as keyboard 815 and/or mouse 816) and optional watch-dog 807.Can be completed by shown telecommunication media with the data corresponding of the server 809 of local or remote location.Telecommunication media can comprise any means transmitting and/or receive data.Such as, telecommunication media can be that network connection, wireless connections or internet connect.This connection can provide the communication on World Wide Web (WorldWideWeb).Can envision, the relevant data of the present invention to receive for a side 822 by these means and/or the network checked or connection transmit.Take over party 822 can be individuality, registered user, healthcare provider or care manager, but is not limited thereto.In one embodiment, computer-readable medium comprises the medium being suitable for the analytical results transmitting biological sample or genotype correlation.Described medium can comprise the result of the phenotypic spectrum about individual subject, wherein uses method described herein to obtain this result.
Individual's entrance receives and evaluates the basic interface of the individuality of genomic data by being preferably used as.Entrance also can tracking results from the process collecting test by enabling individuality follow the tracks of its sample.Accessed by entrance, introduce the relative risk of common genetic disease based on its Genome Atlas to individuality.By entrance, registered user can select which rule is applied to its Genome Atlas.
In one embodiment, one or more webpage will have the list of phenotype and have a square frame near each phenotype, and registered user can select square frame to be included in their phenotypic spectrum.Phenotype can link to the information relevant with this phenotype, selects advisably to wish to be included in the phenotype in its phenotypic spectrum about them to help registered user.Webpage also can have the phenotype by disease grouping (disease that the disease such as can disposed maybe can not be disposed) tissue.Such as, registered user only can select the phenotype that can dispose, such as HLA-DQA1 and celiac disease.Treat before registered user also can select the symptom of display phenotype or after symptom.Such as, the phenotype disposed (beyond further examination) that individuality is treated before can selecting to have symptom is treat before the symptom of GF diet for celiac disease.Another example can be Alzheimer, and before symptom, treatment is statins, exercise, VITAMIN and mentation.Thrombosis is another example, and before symptom, treatment avoids oral contraceptive and avoids normal time sitting.The example with the phenotype for the treatment of after the symptom of approval is the moist AMD relevant with CFH, wherein the individual laser therapy can carried out its state.
Phenotype also can be organized by the type of disease or state or kind, such as neuroscience, cardiovascular, internal secretion, immunity etc.Phenotype also can be grouped into medical science and non-medical phenotype.Other classification of phenotype on webpage can be carried out according to health proterties, physiological character, mental trait or mood proterties.Webpage can provide the subregion selecting one group of phenotype by selecting a square frame further.Such as, select all phenotypes, the phenotype that the phenotype of being only correlated with from medical science, only non-medical are correlated with, the phenotype only can disposed, the phenotype only can not disposed, different disease group or " amusement " phenotype." amusement " phenotype can comprise the contrast with famous person or other well-known individualities, or with the contrast of other animal or even other organism.The list that can be used for the Genome Atlas contrasted also can provide and contrast with the Genome Atlas of registered user for being selected by registered user on webpage.
Online entrance also can provide search engine, browses entrance, retrieval particular phenotype to help registered user or retrieves the particular term or information that are disclosed by its phenotypic spectrum or report.The link of the service of accessing collocation and the product provided also can be provided by entrance.The other link of the chatroom of the individuality being connected to support group, message board and have common or similar phenotype also can be provided.Online entrance also can provide and be connected to linking of other address with more information relevant with phenotype in registered user's phenotypic spectrum.Online entrance also can provide the service allowing registered user to share its phenotypic spectrum and report with friend, household or care manager.Registered user can select in phenotypic spectrum, show them and wish and the phenotype that its friend, household or care manager share.
Phenotypic spectrum and report provide individual individualized genotype correlation.The genotype correlation provided to individuality can be used in determining that individual health care and mode of life are selected.If found the strong correlation between the disease for the treatment of in genetic variant and can carrying out, the detection of genetic variant can help to determine to start disease treatment and/or Personal monitoring.In existence statistically significant dependency but when not thinking strong correlation, individuality can be discussed this information with individual doctor and determine suitable, useful action scheme.The potential action scheme that may be of value to individuality with regard to specific gene type dependency comprises carries out treating process, monitoring potential treatment needs or result for the treatment of or change lifestyles in diet, exercise and other personal habits/activity etc.Such as, the symptom treatment that phenotype (as celiac disease) can carry out GF diet can be disposed.Equally, by pharmacogenomics, genotype correlation information can be applicable to prediction must carry out may reacting of the individuality for the treatment of, the possible effect of such as particular medication or security by certain drug or courses of pharmaceuticals.
Registered user can select Genome Atlas and phenotypic spectrum to be supplied to its care manager, such as doctor or genetic consultant.Genome Atlas and phenotypic spectrum directly can be accessed by care manager, are printed a to give care manager by registered user, or by online entrance (such as by the link in online report), it are directly sent to care manager.
The transmission of this relevant information carries out making patient the action coordinated with its doctor.Particularly, the discussion between patient with its doctor and can be connected to medical information linking and making the genomic information of patient to be attached in its medical record and become possibility by individual entrance.Medical information can comprise prevention and health and fitness information.Select by the invention provides the wisdom that patient can be made to make for its health care to the information of individual patient.In this mode, the disease that patient can select to help them to avoid and/or postpone its genes of individuals picture group spectrum (DNA of heredity) more may cause.In addition, patient can adopt the treatment plan of the specific medical needs of its people applicable itself.Individual also by having the ability of its genotype data of access, if there is disease and need this information to help its doctor to form treatment strategies in them.
Genotype correlation information also can be combined for considering that the Mr. and Mrs given birth to advise with genetic counseling, and the potential heredity proposed for mother, father and/or child is paid close attention to.Genetic consultant can provide information and support to the registered user of the phenotypic spectrum of the risk of the particular state or disease with display increase.They can explain about this illness information, analyze hereditary pattern and risk of recurrence and with registered user, available selection be discussed.Genetic consultant also can provide support sexual counseling to recommend community or national Service supportive to registered user.Genetic counseling can comprise specific registration plan.In some embodiments, genetic counseling can be arranged in asked 24 hours and can to utilize within such as evening, Saturday, Sunday and/or false object time.
Individual entrance also transmits the Additional Information beyond initial examination by being convenient to.The individual new scientific discovery that will be apprised of about its individual inheritance's collection of illustrative plates, the such as or new treatment of sneak condition current about it or the information of preventive measure.New discovery also can pass to its care manager.In a preferred embodiment, new gene type dependency about the phenotype in the phenotypic spectrum of registered user and recent studies on is noticed by electronics to e-mail registry user or its healthcare provider.In other embodiments, the e-mail of " amusement " phenotype is sent to registered user, and such as electronic mail can inform that 77% of their its Genome Atlas and further information identical with the Genome Atlas of A Bailahan Lincoln is provided by online entrance.
Present invention provides a kind of for generate new regulation, modification rule, combining rule, regularly with new regulation update rule collection, safely maintenance Genome Atlas database, rule is applied to Genome Atlas to determine phenotypic spectrum and to be used for generating the computer generation code system of report.Computer code inform registered user new or the dependency revised and report that is new or that revise, such as there is new prevention and health and fitness information, about the information of new treatment in exploitation or the report of obtainable new treatment.
business method
The invention provides a kind of business method, the method assesses individual genotype correlation based on the Genome Atlas of patient with comparing of the clinical database of the medical science associated nucleotide modification of establishing.Invention further provides a kind of business method, the method uses the initial unknown new dependency of genes of individuals picture group spectrum assessment stored to generate individual updating form type spectrum, and submits other biological sample to without the need to individuality.Fig. 9 is the schema illustrating this business method.
At the genotype correlation of individual because multiple common human diseases, state and physical state when initial request and purchase individual Genome Atlas, partly produce the revenue stream of business method of the present invention in a step 101.Request and purchase can be undertaken by many sources, include but not limited to online Web portal, online health service and the individual doctor of individuality or the source of similar individual medical attention.In the embodiment substituted, Genome Atlas can provide free, and can generate revenue stream in step (such as step 103) subsequently.
Registered user or human consumer make the request buying phenotypic spectrum.There is provided collection test kit for gather the biological sample that in step 103 carry out genetic material be separated with buying to human consumer in response to demand.When request is made in online, be not easy to personal acquisition collection test kit by phone or other human consumer source, provide collection test kit by express delivery, such as, the express delivery service of the same day or payment overnight is provided.Gather that test kit comprises be sample container and for by sample rapid delivery to the wrapping material in laboratory generating Genome Atlas.Test kit also can comprise explanation sample being delivered to sample preparation mechanism or laboratory and the explanation of accessing its Genome Atlas and phenotypic spectrum, and this can be undertaken by online entrance.
Just as described above in detail, genomic dna can be obtained from any one type polytype biological sample.Preferably, collection test kit (such as from the test kit that the DNAGenotek buys) isolation of genomic DNA from saliva be purchased is used.The use of saliva and this test kit makes it possible to carry out not damaged sample collecting, because human consumer easily provides saliva sample in the container from collection test kit, then seals this container.In addition, saliva sample can at room temperature store and transport.
Biological sample is being left in collection or specimen container in after, in step 105 human consumer Sample delivery to the laboratory of carrying out processing.Typically, by such as on the same day or the rapid delivery of overnight courier service, human consumer can be used in and gather in test kit the wrapping material that provide by Sample delivery/send to laboratory.
Processing sample the laboratory generating Genome Atlas can be followed suitable government organs and be instructed and regulation.Such as, in the U.S., treating lab can by one or more federal agency of such as FDA (FDA) or medical insurance and Medicaid Service center (CentersforMedicareandMedicaidServices) (CMS) and/or one or more state organization management.In the U.S., can authorize according to the ClinicalLaboratoryImprovementAmendments (CLIA) of 1988 or approval clinical labororatory.
In step 107, laboratory as previously described processes genetic material with DNA isolation or RNA to sample.Then, in step 109, the genetic material be separated is analyzed and generated Genome Atlas.Preferably, genome SNP distribution plan is generated.As mentioned above, several method can be used to generate SNP distribution plan.Preferably, high density arrays (such as from Affymetrix or Illumina be purchased platform) is for SNP qualification and distribution plan generation.Such as, as described in more detail above, AffymetrixGeneChipassay is used to generate SNP distribution plan.Along with technical development, other technology suppliers of energy generating high density SNP distribution plan may be had.In another embodiment, the Genome Atlas of registered user will be the genome sequence of registered user.
After generating individual Genome Atlas, in step 111, preferably genotype data is encrypted, inputs, and in step 113 by this deposit data in encrypting database or strong room, wherein information stores in order to using in the future.Genome Atlas and can be secret for information about, limits this private information of access and Genome Atlas according to instruction that is individual and/or his or her individual doctor.Other people (such as individual household and genetic consultant) also can by registered user's permits access.
Database or strong room can be positioned at treating lab place on the spot.Or database can be positioned at independently place.In this case, the Genome Atlas data generated by treating lab can be transported to the independent mechanism comprising database in step 111.
After generating individual Genome Atlas, in step 115, the clinical database of the heritable variation of individuality to fixed medically relevant genetic variant is compared subsequently.Or genotype correlation can not be that medical science is correlated with but still is included in genotype correlation database, such as, as the health proterties of eye color, or as " amusement " phenotype with the similarity of famous person's Genome Atlas.
Medically relevant SNP can be set up by scientific literature and relevant sources.Also non-SNP genetic variant can be set up to join with phenotypic correlation.Usually, by the intimate haplotype pattern with the lineup of disease being set up compared with the lineup not having disease the SNP dependency of given disease.By analyzing many individualities, the frequency of polymorphism in colony can be determined, and these genotype frequencies can be associated with particular phenotype (such as disease or state) thereupon.Or phenotype can be medical condition.
Also can compose by the genes of individuals picture group of analyzing stored the SNP and non-SNP genetic variant that determine to be correlated with, instead of be determined by available open source literature.The individuality with the Genome Atlas of storage can disclose the phenotype previously determined.Can by the individual relative of the analysis of the genotype of individuality and the phenotype of announcement and not this phenotype than to determine the dependency that then may be used for other Genome Atlas.Determine that the individuality of its Genome Atlas can fill in the questionnaire about the phenotype previously determined.Questionnaire can comprise the problem of related medical and medical condition, the disease of such as previous diagnosis, the family history of medical condition, mode of life, health proterties, mental trait, age, social life, environment etc.
In one embodiment, if individuality fill in questionnaire, they just can freely determine its Genome Atlas.In some embodiments, individuality regularly fills out a questionnaire with its phenotypic spectrum of free access and report.In other embodiments, the individuality that fill in questionnaire can give registration upgrading, so that they have the access rights of the registration higher level more previous than it, or they can buy or more new registration with lower price.
In order to ensure science accuracy and importance, first all information left in step 121 in the genetic variant database that medical science is correlated with is checked and approved by research/clinical advisor group, if be authorized in step 119 simultaneously, checked and supervision by suitable government organs.Such as in the U.S., FDA can by checking and approving for confirming that the algorithm of genetic variant (being generally SNP, transcript level or sudden change) related data exercises supervision.In step 123, in order to additional genetic variant-disease or state dependency, scientific literature and other relevant sources are monitored, and after the accuracy confirming them and importance, and through the inspection of government organs and approval, add in master data base in these additional genotype correlation steps 125.
Through to check and approve and database and the full-length genome individuality collection of illustrative plates of medical science correlated inheritance modification of checking combines and carries out genetic risk assessment by advantageously allowing to a large amount of disease or state.After the Genome Atlas that compilation is individual, can by Nucleotide (heredity) modification of individuality or genetic marker be determined idiotype dependency compared with the database of the human nucleotide modification be associated with particular phenotype (such as disease, state or physical state).By by genes of individuals picture group spectrum with the master data base of genotype correlation compared with, can inform individuality whether find they for genetic risk factors be positive or negative and degree how.Individuality will receive about relative risk and/or the ill physique data on a large scale through the morbid state (such as, Alzheimer, cardiovascular diseases, blood coagulation) of scientific validation.Such as, the genotype correlation in table 1 can be comprised.In addition, the SNP in database is disease associated can include, but are not limited to those dependencys shown in Fig. 4.Also other dependency in Fig. 5 and 6 can be comprised.Business method of the present invention is because herein is provided venture analysis for a large amount of disease and state and without the need to understanding those diseases in advance and what risk is state may cause.
In other embodiments, the genotype correlation combined with the individual collection of illustrative plates of full-length genome is non-medical Relevant phenotype, the health proterties of such as " amusement " phenotype or such as color development.In a preferred embodiment, as mentioned above, rule or rule set are applied to individual Genome Atlas or SNP distribution plan.Rule is applied to the phenotypic spectrum of Genome Atlas generation for individuality.
Therefore, when discovery with when verifying new dependency, by the master data base of additional genotype correlation expansion human genotype correlation.Time when needed or suitably, the relevant information in can being composed from the genes of individuals picture group stored in a database by access be upgraded.Such as, the new gene type dependency known can based on specific gene modification.Then, can by only to obtain and in more individual complete genome picture group spectrum only this gene part and determine individual whether may by the impact of this new genotype correlation.
Preferably the result of genome inquiry is analyzed and explained so that with understandable form in passing individuality.Then, in step 117, as the result by posting or provided to patient in the mode of safety, secret by online Entry Interface initial examination described in detail above.
Report can comprise phenotypic spectrum and the genomic information about phenotype in phenotypic spectrum, such as, about basic genetic information or the demographic information of genetic variant in different groups of involved gene.The out of Memory based on phenotypic spectrum that can be included in report is preventive measure, health and fitness information, methods for the treatment of, symptom understanding, the further qualification of early detection scheme, intervention plan and phenotype and classification.After the initial examination of genes of individuals picture group spectrum, carry out maybe carrying out renewal that is controlled, appropriateness.
Occur when new genotype correlation and when being verified and checking and approving, in conjunction with the renewal of master data base, genes of individuals picture group spectrum upgraded or can obtain renewal.New regulation based on new genotype correlation can be applied to initial gene picture group spectrum with the phenotypic spectrum providing renewal.In this step 127 by the relevant portion of the Genome Atlas by individuality compared with new genotype correlation, the genotype correlation distribution plan of renewal can be generated.Such as, if find new genotype correlation based on the variation in specific gene, then can analyze this Gene Partial that genes of individuals picture group is composed with regard to new genotype correlation.In this case, one or more rule can be applied to the phenotypic spectrum generating and upgrade, instead of with having the whole rule set updating form type spectrum of the rule applied.In step 129, provide the result of individual renewal genotype correlation in the mode of encrypting.
The initial service that can be available to registered user or human consumer with the phenotypic spectrum upgraded.The difference registration level that Genome Atlas can be provided to analyze and combination thereof.Similarly, registration level can change to provide them to wish the selection with the volume of services of its genotype correlation accepted to individuality.Like this, the service registry level along with individual acquisition changes by the grade of service provided.
The entry level registration of registered user can comprise Genome Atlas and initial table type spectrum.This can be basic registration level.The different grades of service can be had in basis registration level.Such as, specific registration level can provide for genetic counseling, in treatment or prevention specified disease, have the doctor of special expertise and the introduction of other service option.Online or genetic counseling can be obtained by phone.In another embodiment, the price of registration may depend on the quantity of individual selection for the phenotype of its phenotypic spectrum.Another option may for whether registered user selects to access online genetic counseling.
In another situation, registration can provide the genotype correlation of initial full-length genome, maintains individual Genome Atlas in a database simultaneously; If so select individual, this database can be encryption.After this initial analysis, subsequent analysis and additional result can complete in individual requests with when paying the bill in addition.This can be advanced resistry.
In an embodiment of business method of the present invention, carry out the renewal of individual risk and corresponding information can be provided to individuality on registration basis.The registered user buying advanced resistry can obtain renewal.Registration for genotype correlation analysis can provide the particular type of new gene type dependency or the renewal of subclass according to individual preference.Such as, individuality may only wish to learn the genotype correlation that there is known treatment or prevention process.In order to help individual to determine whether carry out other analysis, information about available other genotype correlation can be provided to individuality.E-mail can be posted or send to this information easily to registered user.
In advanced resistry, the more grade of service can be there is, such as mentioned those in the registration of basis.Other registration mode can be provided in high-grade.Such as, highest ranking can provide unconfined renewal and report to registered user.When determining new dependency Sum fanction, the distribution plan of registered user can be upgraded.In this grade, registered user also can allow the individuality of unrestricted number to conduct interviews, such as kinsfolk and care manager.Registered user also can unrestrictedly access online genetic consultant and doctor.
Next registration level in high-grade can provide more restrictions in, the such as renewal of limited number of times.Registered user can carry out the renewal of limited number of times in period of registration to its Genome Atlas, such as, and 1 year 4 times.In another registration level, registered user can weekly, January upgrades the Genome Atlas that it stores once or annually.In another embodiment, registered user only can have a limited number of phenotype can selecting to upgrade its Genome Atlas.
Individual's entrance also to upgrade enabling individuality maintain easily for risk or dependency and/or the registration of information updating, or the risk assessment that upgrades of request and information.As mentioned above, different registration level can be provided with the genotype correlation result and the renewal that enable individuality select various level, and registered user can select different registration level by its people's entrance.
Any one in these registration options is made contributions to the revenue stream of business method of the present invention.The revenue stream of business method of the present invention is also increased by the new human consumer of interpolation and registered user, and wherein new Genome Atlas joins in database.
Table 1: there is the Exemplary gene with the genetic variant of phenotypic correlation.
Gene Phenotype
A2M Alzheimer
ABCA1 Cholesterol, HDL
ABCB1 HIV
ABCB1 Epilepsy
ABCB1 Complication of transplanted kidney
ABCB1 Digoxin, serum-concentration
ABCB1 Crohn disease; Ulcerative colitis
ABCB1 Parkinson's disease
ABCC8 Diabetes B
ABCC8 Diabetes, 2 types
ABO Myocardial infarction
ACADM Medium chain acyl-CoA dehydrogenase deficiency
ACDC 2 types, diabetes
ACE Diabetes B
ACE Hypertension
ACE Alzheimer
ACE Myocardial infarction
ACE Cardiovascular
ACE Left ventricular hypertrophy
Gene Phenotype
ACE Coronary artery disease
ACE Atherosclerosis, crown
ACE Retinopathy, diabetes
ACE Systemic lupus erythematous
ACE Blood pressure, artery
ACE Erectile dysfunction
ACE Lupus
ACE POLYCYSTIC KIDNEY DISEASE
ACE Apoplexy
ACP1 Diabetes, 1 type
ACSM1(LIP)c Cholesterol levels
ADAM33 Asthma
ADD1 Hypertension
ADD1 Blood pressure, artery
ADH1B Alcohol abuse
ADH1C Alcohol abuse
ADIPOQ Diabetes, 2 types
ADIPOQ Fat
ADORA2A Panic-stricken
ADRB1 Hypertension
ADRB1 In heart failure
ADRB2 Asthma
ADRB2 Hypertension
ADRB2 Fat
ADRB2 Blood pressure, artery
ADRB2 Diabetes B
ADRB3 Fat
Gene Phenotype
ADRB3 Diabetes B
ADRB3 Hypertension
AGT Hypertension
AGT Diabetes B
AGT Essential hypertension
AGT Myocardial infarction
AGTR1 Hypertension
AGTR2 Hypertension
AHR Mammary cancer
ALAD Toxicity of Lead
ALDH2 Alcoholism
ALDH2 Alcohol abuse
ALDH2 Colorectal carcinoma
ALDRL2 Diabetes B
ALOX5 Asthma
ALOX5AP Asthma
APBB1 Alzheimer
APC Colorectal carcinoma
APEX1 Lung cancer
APOA1 Atherosclerosis, crown
APOA1 Cholesterol, HDL
APOA1 Coronary artery disease
APOA1 Diabetes B
APOA4 Diabetes B
APOA5 Triglyceride level
APOA5 Atherosclerosis, crown
APOB Hypercholesterolemia
Gene Phenotype
APOB Fat
APOB Cardiovascular
APOB Coronary artery disease
APOB Coronary heart disease
APOB Diabetes B
APOC1 Alzheimer
APOC3 Triglyceride level
APOC3 Diabetes B
APOE Alzheimer
APOE Diabetes B
APOE Multiple sclerosis
APOE Atherosclerosis, crown
APOE Parkinson's disease
APOE Coronary heart disease
APOE Myocardial infarction
APOE Apoplexy
APOE Alzheimer
APOE Coronary artery disease
APP Alzheimer
AR Prostate cancer
AR Mammary cancer
ATM Mammary cancer
ATP7B Hepatolenticular degeneration
ATXN8OS Spinocebellar ataxia
BACE1 Alzheimer
BCHE Alzheimer
BDKRB2 Hypertension
Gene Phenotype
BDNF Alzheimer
BDNF Bipolar disorder
BDNF Parkinson's disease
BDNF Schizophrenia
BDNF Memory
BGLAP Bone density
BRAF Thyroid carcinoma
BRCA1 Mammary cancer
BRCA1 Mammary cancer; Ovarian cancer
BRCA1 Ovarian cancer
BRCA2 Mammary cancer
BRCA2 Mammary cancer; Ovarian cancer
BRCA2 Ovarian cancer
BRIP1 Mammary cancer
C4A Systemic lupus erythematous
CALCR Bone density
CAMTA1 Episodic memory
CAPN10 Diabetes, 2 types
CAPN10 Diabetes B
CAPN3 Muscular dystrophy
CARD15 Crohn disease
CARD15 Crohn disease; Ulcerative colitis
CARD15 Inflammatory bowel
CART Fat
CASR Bone density
CCKAR Schizophrenia
CCL2 Systemic lupus erythematous
Gene Phenotype
CCL5 HIV
CCL5 Asthma
CCND1 Colorectal carcinoma
CCR2 HIV
CCR2 HIV
CCR2 Hepatitis C
CCR2 Myocardial infarction
CCR3 Asthma
CCR5 HIV
CCR5 HIV
CCR5 Hepatitis C
CCR5 Asthma
CCR5 Multiple sclerosis
CD14 Atopy (atopy)
CD14 Asthma
CD14 Crohn disease
CD14 Crohn disease; Ulcerative colitis
CD14 Periodontitis
CD14 Total IgE
CDH1 Prostate cancer
CDH1 Colorectal carcinoma
CDKN2A Melanoma
CDSN Psoriasis
CEBPA Leukemia, marrow
CETP Atherosclerosis, crown
CETP Coronary heart disease
CETP Hypercholesterolemia
Gene Phenotype
CFH Macular degeneration
CFTR Cystic fibrosis
CFTR Pancreatitis
CFTR Cystic fibrosis
CHAT Alzheimer
CHEK2 Mammary cancer
CHRNA7 Schizophrenia
CMA1 Atopic dermatitis
CNR1 Schizophrenia
COL1A1 Bone density
COL1A1 Osteoporosis
COL1A2 Bone density
COL2A1 Osteoarthritis
COMT Schizophrenia
COMT Mammary cancer
COMT Parkinson's disease
COMT Bipolar disorder
COMT Obsessive compulsive neurosis
COMT Alcoholism
CR1 Systemic lupus erythematous
CRP C reactive protein
CST3 Alzheimer
CTLA4 Type 1 diabetes
CTLA4 Graves' disease
CTLA4 Multiple sclerosis
CTLA4 Rheumatoid arthritis
CTLA4 Systemic lupus erythematous
Gene Phenotype
CTLA4 Lupus erythematosus
CTLA4 Celiac disease
CTSD Alzheimer
CX3CR1 HIV
CXCL12 HIV
CXCL12 HIV
CYBA Atherosclerosis, crown
CYBA Hypertension
CYP11B2 Hypertension
CYP11B2 Left ventricular hypertrophy
CYP17A1 Mammary cancer
CYP17A1 Prostate cancer
CYP17A1 Endometriosis
CYP17A1 Carcinoma of endometrium
CYP19A1 Mammary cancer
CYP19A1 Prostate cancer
CYP19A1 Endometriosis
CYP1A1 Lung cancer
CYP1A1 Mammary cancer
CYP1A1 Colorectal carcinoma
CYP1A1 Prostate cancer
CYP1A1 The esophageal carcinoma
CYP1A1 Endometriosis
CYP1A1 Cell is studied
CYP1A2 Schizophrenia
CYP1A2 Colorectal carcinoma
CYP1B1 Mammary cancer
Gene Phenotype
CYP1B1 Glaucoma
CYP1B1 Prostate cancer
CYP21A2 21-hydroxylase lacks
CYP21A2 Adrenal,congenital hyperplasia
CYP21A2 Adrenal hyperplasia, inborn
CYP2A6 Cigarette smoking
CYP2A6 Nicotine
CYP2A6 Lung cancer
CYP2C19 Helicobacter pylori infection
CYP2C19 Phenytoin Sodium Salt
CYP2C19 Stomach trouble
CYP2C8 Malaria, plasmodium falciparum
CYP2C9 Anti-coagulant complication
CYP2C9 Method China makes susceptibility
CYP2C9 Fa Hualin treats, its reaction
CYP2C9 Colorectal carcinoma
CYP2C9 Phenytoin Sodium Salt
CYP2C9 Acenocoumarol reacts
CYP2C9 Blood coagulation disorders
CYP2C9 Hypertension
CYP2D6 Colorectal carcinoma
CYP2D6 Parkinson's disease
CYP2D6 The bad metabolizer phenotype of CYP2D6
CYP2E1 Lung cancer
CYP2E1 Colorectal carcinoma
CYP3A4 Prostate cancer
CYP3A5 Prostate cancer
Gene Phenotype
CYP3A5 The esophageal carcinoma
CYP46A1 Alzheimer
DBH Schizophrenia
DHCR7 Shi-Lun-Ao three syndrome
DISC1 Schizophrenia
DLST Alzheimer
DMD Muscular dystrophy
DRD2 Alcoholism
DRD2 Schizophrenia
DRD2 Cigarette smoking
DRD2 Parkinson's disease
DRD2 Tardive dyskinesia
DRD3 Schizophrenia
DRD3 Tardive dyskinesia
DRD3 Bipolar disorder
DRD4 Attention deficit disorder (ADD) [companion is how dynamic]
DRD4 Schizophrenia
DRD4 Strangely to seek (novelty seeking)
DRD4 ADHD
DRD4 Individual character
DRD4 Heroine is abused
DRD4 Alcohol abuse
DRD4 Alcoholism
DRD4 Personality disorder
DTNBP1 Schizophrenia
EDN1 Hypertension
EGFR Lung cancer
Gene Phenotype
ELAC2 Prostate cancer
ENPP1 Diabetes B
EPHB2 Prostate cancer
EPHX1 Lung cancer
EPHX1 Colorectal carcinoma
EPHX1 Hemapoiesis is studied
EPHX1 Chronic obstructive pulmonary disease/COPD
ERBB2 Mammary cancer
ERCC1 Lung cancer
ERCC1 Colorectal carcinoma
ERCC2 Lung cancer
ERCC2 Hemapoiesis is studied
ERCC2 Bladder cancer
ERCC2 Colorectal carcinoma
ESR1 Bone density
ESR1 Bone mineral density
ESR1 Mammary cancer
ESR1 Endometriosis
ESR1 Osteoporosis
ESR2 Bone density
ESR2 Mammary cancer
Estrogen receptor Bone mineral density
F2 Coronary heart disease
F2 Apoplexy
F2 Thromboembolism, vein
F2 Preeclampsia
F2 Thrombosis
Gene Phenotype
F5 Thromboembolism, vein
F5 Preeclampsia
F5 Myocardial infarction
F5 Apoplexy
F5 Apoplexy, ischemic
F7 Atherosclerosis, crown
F7 Myocardial infarction
F8 Hemophilia
F9 Hemophilia
FABP2 Diabetes B
FAS Alzheimer
FASLG Multiple sclerosis
FCGR2A Systemic lupus erythematous
FCGR2A Lupus erythematosus
FCGR2A Periodontitis
FCGR2A Rheumatoid arthritis
FCGR2B Lupus erythematosus
FCGR2B Systemic lupus erythematous
FCGR3A Systemic lupus erythematous
FCGR3A Lupus erythematosus
FCGR3A Periodontitis
FCGR3A Sacroiliitis
FCGR3A Rheumatoid arthritis
FCGR3B Periodontitis
FCGR3B Periodontopathy
FCGR3B Lupus erythematosus
FGB Fibrinogen
Gene Phenotype
FGB Myocardial infarction
FGB Coronary heart disease
FLT3 Leukemia, marrow
FLT3 Leukemia
FMR1 Fragile X syndrome
FRAXA Fragile X syndrome
FUT2 Helicobacter pylori infection
FVL Factor Ⅴ Leiden
G6PD G6PD lacks
G6PD Hyperbilirubinemia
GABRA5 Bipolar disorder
GBA Gaucher disease
GBA Parkinson's disease
GCGR(FAAH，ML4R，UCP2) Body weight/obesity
GCK Diabetes B
GCLM(F12，TLR4) Atherosclerosis, myocardial infarction
GDNF Schizophrenia
GHRL Fat
GJB1 Charcot Marie Tooth
GJB2 Deaf
GJB2 Hearing disability, sensory nerve non-syndrome
GJB2 Hearing disability, sensorineural
GJB2 Hearing disability/deafness
GJB6 Hearing disability, sensory nerve non-syndrome
GJB6 Hearing disability/deafness
GNAS Hypertension
GNB3 Hypertension
Gene Phenotype
GPX1 Lung cancer
GRIN1 Schizophrenia
GRIN2B Schizophrenia
GSK3B Bipolar disorder
GSTM1 Lung cancer
GSTM1 Colorectal carcinoma
GSTM1 Mammary cancer
GSTM1 Prostate cancer
GSTM1 Hemapoiesis is studied
GSTM1 Bladder cancer
GSTM1 The esophageal carcinoma
GSTM1 Head and neck cancer
GSTM1 Leukemia
GSTM1 Parkinson's disease
GSTM1 Cancer of the stomach
GSTP1 Lung cancer
GSTP1 Colorectal carcinoma
GSTP1 Mammary cancer
GSTP1 Hemapoiesis is studied
GSTP1 Prostate cancer
GSTT1 Lung cancer
GSTT1 Colorectal carcinoma
GSTT1 Mammary cancer
GSTT1 Prostate cancer
GSTT1 Bladder cancer
GSTT1 Hemapoiesis is studied
GSTT1 Asthma
Gene Phenotype
GSTT1 Benzene toxicity
GSTT1 The esophageal carcinoma
GSTT1 Head and neck cancer
GYS1 Diabetes B
HBB Thalassemia
HBB Thalassemia, β-
HD Heng Yandunshi tarantism
HFE Hemochromatosis
HFE Iron level
HFE Colorectal carcinoma
HK2 Diabetes B
HLA Rheumatoid arthritis
HLA Type 1 diabetes
HLA Behcet's disease
HLA Celiac disease
HLA Psoriasis
HLA Graves disease
HLA Multiple sclerosis
HLA Schizophrenia
HLA Asthma
HLA Diabetes
HLA Lupus
HLA—A Leukemia
HLA—A HIV
HLA—A Diabetes, 1 type
HLA—A Graft versus host disease (GVH disease)
HLA—A Multiple sclerosis
Gene Phenotype
HLA—B Leukemia
HLA—B Behcet's disease
HLA—B Celiac disease
HLA—B Diabetes, 1 type
HLA—B Graft versus host disease (GVH disease)
HLA—B Sarcoidosis
HLA—C Psoriasis
HLA—DPA1 Measles
HLA—DPB1 Diabetes, 1 type
HLA—DPB1 Asthma
HLA—DQA1 Diabetes, 1 type
HLA—DQA1 Celiac disease
HLA—DQA1 Cervical cancer
HLA—DQA1 Asthma
HLA—DQA1 Multiple sclerosis
HLA—DQA1 Diabetes, 2 types; Diabetes, 1 type
HLA—DQA1 Lupus erythematosus
HLA—DQA1 Gestation is lost, recurrence
HLA—DQA1 Psoriasis
HLA—DQB1 Diabetes, 1 type
HLA—DQB1 Celiac disease
HLA—DQB1 Multiple sclerosis
HLA—DQB1 Cervical cancer
HLA—DQB1 Lupus erythematosus
HLA—DQB1 Gestation is lost, recurrence
HLA—DQB1 Sacroiliitis
HLA—DQB1 Asthma
Gene Phenotype
HLA-DQB1 HIV
HLA—DQB1 Lymphoma
HLA—DQB1 Tuberculosis
HLA—DQB1 Rheumatoid arthritis
HLA—DQB1 Diabetes, 2 types
HLA—DQB1 Graft versus host disease (GVH disease)
HLA—DQB1 Hypnolepsy
HLA—DQB1 Sacroiliitis, rheumatoid
HLA—DQB1 Cholangitis, indurative
HLA—DQB1 Diabetes, 2 types; Diabetes, 1 type
HLA—DQB1 Graves' disease
HLA—DQB1 Hepatitis C
HLA—DQB1 Hepatitis C, chronic
HLA—DQB1 Malaria
HLA—DQB1 Malaria, plasmodium falciparum
HLA—DQB1 Melanoma
HLA—DQB1 Psoriasis
HLA—DQB1 Sjogren syndrome
HLA—DQB1 Systemic lupus erythematous
HLA—DRB1 Diabetes, 1 type
HLA—DRB1 Multiple sclerosis
HLA—DRB1 Systemic lupus erythematous
HLA—DRB1 Rheumatoid arthritis
HLA—DRB1 Cervical cancer
HLA—DRB1 Sacroiliitis
HLA—DRB1 Celiac disease
HLA—DRB1 Lupus erythematosus
Gene Phenotype
HLA—DRB1 Sarcoidosis
HLA-DRB1 HIV
HLA—DRB1 Tuberculosis
HLA—DRB1 Graves' disease
HLA—DRB1 Lymphoma
HLA—DRB1 Psoriasis
HLA-DRB1 Asthma
HLA—DRB1 Crohn disease
HLA—DRB1 Graft versus host disease (GVH disease)
HLA—DRB1 Hepatitis C, chronic
HLA—DRB1 Hypnolepsy
HLA—DRB1 Sclerosis, whole body
HLA—DRB1 Sjogren syndrome
HLA—DRB1 Type 1 diabetes
HLA—DRB1 Sacroiliitis, rheumatoid
HLA—DRB1 Cholangitis, indurative
HLA—DRB1 Diabetes, 2 types; Diabetes, 1 type
HLA—DRB1 Helicobacter pylori infection
HLA—DRB1 Hepatitis C
HLA—DRB1 Adolescent arthritis
HLA—DRB1 Leukemia
HLA—DRB1 Malaria
HLA—DRB1 Melanoma
HLA—DRB1 Gestation is lost, recurrence
HLA—DRB3 Psoriasis
HLA—G Gestation is lost, recurrence
HMOX1 Atherosclerosis, crown
Gene Phenotype
HNF4A Diabetes, 2 types
HNF4A Diabetes B
HSD11B2 Hypertension
HSD17B1 Mammary cancer
HTR1A Dysthymia disorders, heavy
HTR1B Alcohol dependence
HTR1B Alcoholism
HTR2A Memory
HTR2A Schizophrenia
HTR2A Bipolar disorder
HTR2A Depressed
HTR2A Dysthymia disorders, heavy
HTR2A Commit suiside
HTR2A Alzheimer
HTR2A Anorexia nervosa
HTR2A Hypertension
HTR2A Obsessive compulsive neurosis
HTR2C Schizophrenia
HTR6 Alzheimer
HTR6 Schizophrenia
HTRA1 Wet age related macular degeneration
IAPP Diabetes B
IDE Alzheimer
IFNG Tuberculosis
IFNG Type 1 diabetes
IFNG Graft versus host disease (GVH disease)
IFNG Hepatitis B
Gene Phenotype
IFNG Multiple sclerosis
IFNG Asthma
IFNG Mammary cancer
IFNG Renal transplantation
IFNG Complication of transplanted kidney
IFNG Long-lived
IFNG Gestation is lost, recurrence
IGFBP3 Mammary cancer
IGFBP3 Prostate cancer
IL10 Systemic lupus erythematous
IL10 Asthma
IL10 Graft versus host disease (GVH disease)
IL10 HIV
IL10 Renal transplantation
IL10 Complication of transplanted kidney
IL10 Hepatitis B
IL10 Adolescent arthritis
IL10 Long-lived
IL10 Multiple sclerosis
IL10 Gestation is lost, recurrence
IL10 Rheumatoid arthritis
IL10 Tuberculosis
IL12B Type 1 diabetes
IL12B Asthma
IL13 Asthma
IL13 Atopy
IL13 Chronic obstructive pulmonary disease/COPD
Gene Phenotype
IL13 Graves' disease
IL1A Periodontitis
IL1A Alzheimer
IL1B Periodontitis
IL1B Alzheimer
IL1B Cancer of the stomach
IL1R1 Type 1 diabetes
IL1RN Cancer of the stomach
IL2 Asthma; Eczema; Allergic disease
IL4 Asthma
IL4 Atopy
IL4 HIV
IL4R Asthma
IL4R Atopy
IL4R Total serum IgE
IL6 Bone mineralising
IL6 Renal transplantation
IL6 Complication of transplanted kidney
IL6 Long-lived
IL6 Multiple sclerosis
IL6 Bone density
IL6 Bone mineral density
IL6 Colorectal carcinoma
IL6 Adolescent arthritis
IL6 Rheumatoid arthritis
IL9 Asthma
INHA Premature ovarian failure
Gene Phenotype
INS Type 1 diabetes
INS Diabetes B
INS Diabetes, 1 type
INS Fat
INS Prostate cancer
INSIG2 Fat
INSR Diabetes B
INSR Hypertension
INSR Polycystic ovary syndrome
IPF1 Diabetes, 2 types
IRS1 Diabetes B
IRS1 Diabetes, 2 types
IRS2 Diabetes, 2 types
ITGB3 Myocardial infarction
ITGB3 Atherosclerosis, crown
ITGB3 Coronary heart disease
ITGB3 Myocardial infarction
KCNE1 EKG is abnormal
KCNE2 EKG is abnormal
KCNH2 EKG is abnormal
KCNH2 QT interval prolongation syndromes
KCNJ11 Diabetes, 2 types
KCNJ11 Diabetes B
KCNN3 Schizophrenia
KCNQ1 EKG is abnormal
KCNQ1 QT interval prolongation syndromes
KIBRA Episodic memory
Gene Phenotype
KLK1 Hypertension
KLK3 Prostate cancer
KRAS Colorectal carcinoma
LDLR Hypercholesterolemia
LDLR Hypertension
LEP Fat
LEPR Fat
LIG4 Mammary cancer
LIPC Atherosclerosis, crown
LPL Coronary artery disease
LPL Hyperlipidaemia
LPL Triglyceride level
LRP1 Alzheimer
LRP5 Bone density
LRRK2 Parkinson's disease
LRRK2 Parkinson's disease
LTA Type 1 diabetes
LTA Asthma
LTA Systemic lupus erythematous
LTA Septicemia
LTC4S Asthma
MAOA Alcoholism
MAOA Schizophrenia
MAOA Bipolar disorder
MAOA Cigarette smoking
MAOA Personality disorder
MAOB Parkinson's disease
Gene Phenotype
MAOB Cigarette smoking
MAPT Parkinson's disease
MAPT Alzheimer
MAPT Dull-witted
MAPT Frontotemporal dementia
MAPT Stein-leventhal syndrome
MC1R Melanoma
MC3R Fat
MC4R Fat
MECP2 Rett syndrome
MEFV Familial Mediterranean fever
MEFV Amyloidosis
MICA Type 1 diabetes
MICA Behcet's disease
MICA Celiac disease
MICA Rheumatoid arthritis
MICA Systemic lupus erythematous
MLH1 Colorectal carcinoma
MME Alzheimer
MMP1 Lung cancer
MMP1 Ovarian cancer
MMP1 Periodontitis
MMP3 Myocardial infarction
MMP3 Ovarian cancer
MMP3 Rheumatoid arthritis
MPO Lung cancer
MPO Alzheimer
Gene Phenotype
MPO Mammary cancer
MPZ Charcot Marie Tooth
MS4A2 Asthma
MS4A2 Atopy
MSH2 Colorectal carcinoma
MSH6 Colorectal carcinoma
MSR1 Prostate cancer
MTHFR Colorectal carcinoma
MTHFR Diabetes B
MTHFR Neural tube defect
MTHFR Homocysteine
MTHFR Thromboembolism, vein
MTHFR Atherosclerosis, crown
MTHFR Alzheimer
MTHFR The esophageal carcinoma
MTHFR Preeclampsia
MTHFR Gestation is lost, recurrence
MTHFR Apoplexy
MTHFR Thrombosis, Deep venou
MT—ND1 Diabetes, 2 types
MTR Colorectal carcinoma
MT—RNR1 Hearing disability, sensory nerve non-syndrome
MTRR Neural tube defect
MTRR Homocysteine
MT—TL1 Diabetes, 2 types
MUTYH Colorectal carcinoma
MYBPC3 Myocardosis
Gene Phenotype
MYH7 Myocardosis
MYOC Glaucoma, former angle of release
MYOC Glaucoma
NAT1 Colorectal carcinoma
NAT1 Mammary cancer
NAT1 Bladder cancer
NAT2 Colorectal carcinoma
NAT2 Bladder cancer
NAT2 Mammary cancer
NAT2 Lung cancer
NBN Mammary cancer
NCOA3 Mammary cancer
NCSTN Alzheimer
NEUROD1 Type 1 diabetes
NF1 Neurofibromatosis 1
NOS1 Asthma
NOS2A Multiple sclerosis
NOS3 Hypertension
NOS3 Coronary heart disease
NOS3 Atherosclerosis, crown
NOS3 Coronary artery disease
NOS3 Myocardial infarction
NOS3 Acute coronary syndrome
NOS3 Blood pressure, artery
NOS3 Preeclampsia
NOS3 Nitrogen protoxide
NOS3 Alzheimer
Gene Phenotype
NOS3 Asthma
NOS3 Diabetes B
NOS3 Cardiovascular diseases
NOS3 Behcet's disease
NOS3 Erectile dysfunction
NOS3 Renal failure, chronic
NOS3 Toxicity of Lead
NOS3 Left ventricular hypertrophy
NOS3 Gestation is lost, recurrence
NOS3 Retinopathy, diabetes
NOS3 Apoplexy
NOTCH4 Schizophrenia
NPY Alcohol abuse
NQO1 Lung cancer
NQO1 Colorectal carcinoma
NQO1 Benzene toxicity
NQO1 Bladder cancer
NQO1 Parkinson's disease
NR3C2 Hypertension
NR4A2 Parkinson's disease
NRG1 Schizophrenia
NTF3 Schizophrenia
OGG1 Lung cancer
OGG1 Colorectal carcinoma
OLR1 Alzheimer
OPA1 Glaucoma
OPRM1 Alcohol abuse
Gene Phenotype
OPRM1 Pharmacological dependence
OPTN Glaucoma, former angle of release
P450 Drug metabolism
PADI4 Rheumatoid arthritis
PAH Phenylketonuria/PKU
PAI1 Coronary heart disease
PAI1 Asthma
PALB2 Mammary cancer
PARK2 Parkinson's disease
PARK7 Parkinson's disease
PDCD1 Lupus erythematosus
PINK1 Parkinson's disease
PKA Memory
PKC Memory
PLA2G4A Schizophrenia
PNOC Schizophrenia
POMC Fat
PON1 Atherosclerosis, crown
PON1 Parkinson's disease
PON1 Diabetes B
PON1 Atherosclerosis
PON1 Coronary artery disease
PON1 Coronary heart disease
PON1 Alzheimer
PON1 Long-lived
PON2 Atherosclerosis, crown
PON2 Premature labor
Gene Phenotype
PPARG Diabetes B
PPARG Fat
PPARG Diabetes, 2 types
PPARG Colorectal carcinoma
PPARG Hypertension
PPARGC1A Diabetes, 2 types
PRKCZ Diabetes B
PRL Systemic lupus erythematous
PRNP Alzheimer
PRNP Creutzfeldt-Jacob disease
PRNP Jakob-Creutzfeldt disease
PRODH Schizophrenia
PRSS1 Pancreatitis
PSEN1 Alzheimer
PSEN2 Alzheimer
PSMB8 Type 1 diabetes
PSMB9 Type 1 diabetes
PTCH Skin carcinoma, non-melanoma
PTGIS Hypertension
PTGS2 Colorectal carcinoma
PTH Bone density
PTPN11 Exert southern syndromes
PTPN22 Rheumatoid arthritis
PTPRC Multiple sclerosis
PVT1 End stagerenaldisease
RAD51 Mammary cancer
RAGE Retinopathy, diabetes
Gene Phenotype
RB1 Retinoblastoma
RELN Schizophrenia
REN Hypertension
RET Thyroid carcinoma
RET Hirschsprung's disease
RFC1 Neural tube defect
RGS4 Schizophrenia
RHO Retinitis pigmentosa
RNASEL Prostate cancer
RYR1 Pernicious hyperpyrexia
SAA1 Amyloidosis
SCG2 Hypertension
SCG3 Fat
SCGB1A1 Asthma
SCN5A Brugada syndromes
SCN5A EKG is abnormal
SCN5A QT interval prolongation syndromes
SCNN1B Hypertension
SCNN1G Hypertension
SERPINA1 COPD
SERPINA3 Alzheimer
SERPINA3 COPD
SERPINA3 Parkinson's disease
SERPINE1 Myocardial infarction
SERPINE1 Diabetes B
SERPINE1 Atherosclerosis, crown
SERPINE1 Fat
Gene Phenotype
SERPINE1 Preeclampsia
SERPINE1 Apoplexy
SERPINE1 Hypertension
SERPINE1 Gestation is lost, recurrence
SERPINE1 Thromboembolism, vein
SLC11A1 Tuberculosis
SLC22A4 Crohn disease; Ulcerative colitis
SLC22A5 Crohn disease; Ulcerative colitis
SLC2A1 Diabetes B
SLC2A2 Diabetes B
SLC2A4 Diabetes B
SLC3A1 Cystinuria
SLC6A3 Attention deficit disorder (ADD) [companion is how dynamic]
SLC6A3 Parkinson's disease
SLC6A3 Cigarette smoking
SLC6A3 Alcoholism
SLC6A3 Schizophrenia
SLC6A4 Depressed
SLC6A4 Dysthymia disorders, heavy
SLC6A4 Schizophrenia
SLC6A4 Commit suiside
SLC6A4 Alcoholism
SLC6A4 Bipolar disorder
SLC6A4 Individual character
SLC6A4 Attention deficit disorder (ADD) [companion is how dynamic]
SLC6A4 Alzheimer
SLC6A4 Personality disorder
Gene Phenotype
SLC6A4 Panic-stricken
SLC6A4 Alcohol abuse
SLC6A4 Affective disorder
SLC6A4 Anxiety disorder
SLC6A4 Cigarette smoking
SLC6A4 Dysthymia disorders, heavy; Bipolar disorder
SLC6A4 Heroine is abused
SLC6A4 Irritable bowel syndrome
SLC6A4 Migraine
SLC6A4 Obsessive compulsive neurosis
SLC6A4 Suicide
SLC7A9 Cystinuria
SNAP25 ADHD
SNCA Parkinson's disease
SOD1 ALS/ amyotrophic lateral sclerosis
SOD2 Mammary cancer
SOD2 Lung cancer
SOD2 Prostate cancer
SPINK1 Pancreatitis
SPP1 Multiple sclerosis
SRD5A2 Prostate cancer
STAT6 Asthma
STAT6 Total IgE
SULT1A1 Mammary cancer
SULT1A1 Colorectal carcinoma
TAP1 Type 1 diabetes
TAP1 Lupus erythematosus
Gene Phenotype
TAP2 Type 1 diabetes
TAP2 Diabetes, 1 type
TBX21 Asthma
TBXA2R Asthma
TCF1 Diabetes, 2 types
TCF1 Diabetes B
TF Alzheimer
TGFB1 Mammary cancer
TGFB1 Renal transplantation
TGFB1 Complication of transplanted kidney
TH Schizophrenia
THBD Myocardial infarction
TLR4 Asthma
TLR4 Crohn disease; Ulcerative colitis
TLR4 Septicemia
TNF Asthma
TNFA Cerebrovascular disease
TNF Type 1 diabetes
TNF Rheumatoid arthritis
TNF Systemic lupus erythematous
TNF Renal transplantation
TNF Psoriasis
TNF Septicemia
TNF Diabetes B
TNF Alzheimer
TNF Crohn disease
TNF Diabetes, 1 type
Gene Phenotype
TNF Hepatitis B
TNF Complication of transplanted kidney
TNF Multiple sclerosis
TNF Schizophrenia
TNF Celiac disease
TNF Fat
TNF Gestation is lost, recurrence
TNFRSF11B Bone density
TNFRSF1A Rheumatoid arthritis
TNFRSF1B Rheumatoid arthritis
TNFRSF1B Systemic lupus erythematous
TNFRSF1B Sacroiliitis
TNNT2 Myocardosis
TP53 Lung cancer
TP53 Mammary cancer
TP53 Colorectal carcinoma
TP53 Prostate cancer
TP53 Cervical cancer
TP53 Ovarian cancer
TP53 Smoking
TP53 The esophageal carcinoma
TP73 Lung cancer
TPH1 Commit suiside
TPH1 Dysthymia disorders, heavy
TPH1 Suicide
TPH1 Schizophrenia
TPMT Thiopurine methyltransferase is active
Gene Phenotype
TPMT Leukemia
TPMT Inflammatory bowel
TPMT Thio-purine S-methyltransgerase phenotype
TSC1 Tuberous sclerosis
TSC2 Tuberous sclerosis
TSHR Graves' disease
TYMS Colorectal carcinoma
TYMS Cancer of the stomach
TYMS The esophageal carcinoma
UCHL1 Parkinson's disease
UCP1 Fat
UCP2 Fat
UCP3 Fat
UGT1A1 Hyperbilirubinemia
UGT1A1 Er Bei syndromes
UGT1A6 Colorectal carcinoma
UGT1A7 Colorectal carcinoma
UTS2 Diabetes, 2 types
VDR Bone density
VDR Prostate cancer
VDR Bone mineral density
VDR Type 1 diabetes
VDR Osteoporosis
VDR Bone amount
VDR Mammary cancer
VDR Toxicity of Lead
VDR Tuberculosis
Gene Phenotype
VDR Diabetes B
VEGF Mammary cancer
Vit D rec Idiopathic short stature
VKORC1 Warfarin therapy, its reaction
WNK4 Hypertension
XPA Lung cancer
XPC Lung cancer
XPC Hemapoiesis is studied
XRCC1 Lung cancer
XRCC1 Hemapoiesis is studied
XRCC1 Mammary cancer
XRCC1 Bladder cancer
XRCC2 Mammary cancer
XRCC3 Mammary cancer
XRCC3 Hemapoiesis is studied
XRCC3 Lung cancer
XRCC3 Bladder cancer
ZDHHC8 Schizophrenia
Heredity aggregative index (GCI)
The etiology of many states or disease is owing to h and E factor.The latest developments of genotyping technique have offered an opportunity to identify new the associating between disease with whole genomic genetic marker.In fact, much research recently has been found that these associate, wherein specific allelotrope or genotype relevant with the disease risks of increase.Some in these researchs comprise collection one group test case and one group of contrast and compare the allele distributions of genetic marker between Liang Ge colony.In some researchs of these researchs, being associated in when isolating with other genetic marker between specific genetic marker and disease measures, and other genetic marker processes as a setting and do not work in statistical study.
Genetic marker and modification can comprise SNP, Nucleotide repetition, Nucleotide insertion, nucleotide deletion, chromosome translocation, karyomit(e) repeats or copy number makes a variation.Copy number variation can comprise the repetition of micro-satellite, Nucleotide repeats, kinetochore is repeated or telomere repeats.
In one aspect of the invention, in conjunction with about many genetic markers and one or more diseases or state the information associated and carry out analyzing to obtain GCI and mark.GCI scoring can be used for providing reliable (that is, firm) of their diseased individuals risk compared with Reference Group, intelligible and/or be familiar with intuitively based on contemporary scientific research to not being subject to the people of genetics training.In one embodiment, the method generating the reliable GCI scoring of the combined effect of different genes seat is individual dangerous based on the report of the locus respectively studied.Such as, identify interested disease or state, then Query Information source (include, but are not limited to database, patent open and scientific literature) is to find the information associated of diseases related or state and one or more genetic loci.These information sources are through verifying that also functional quality standard is assessed.In some embodiments, evaluation process comprises multiple step.In other embodiments, with multiple quality standard sources of assessments.Be derived from the information of information resources for identifying odds ratio or the relative risk of one or more genetic loci for interested each disease or state.
In the embodiment substituted, can not obtain from available information source for the odds ratio (OR) of at least one genetic loci or relative risk (RR).Then use the multiple allelic report OR of (1) homologous genes seat, (2) from the gene frequency of data set (such as HapMap data set) and/or (3) from the disease/state popularity computation RR of available stock (such as, CDC, NationalCenterforHealthStatistics etc.) to draw all interested allelic RR.In one embodiment, respectively or assess the multiple allelic OR of homologous genes seat independently.In a preferred embodiment, in conjunction with the multiple allelic OR of homologous genes seat so that dependence (dependency) between not homoallelic OR to be described.In some embodiments, the disease model (including, but are not limited to model that improve as long-pending property (multiplicative), additivity (additive), Harvard, dominant effect) set up is for generating according to scoring in the middle of selected model representation individual risk.
In another embodiment, use the method for the multiple models analyzing interested disease or state, and the method is by interrelated for the result obtained by these different models; This makes the probable error can introduced by selecting specified disease model minimize.This method makes the impact of reasonable error on the calculating of relative risk in popularity, gene frequency and the OR assessment obtained by information source minimize.Due to " linearly " or the monotonicity feature of popularity assessment on the impact of RR, estimate that popularity only has seldom or not impact final scoring improperly; Assuming that identical model is as one man applied to all individualities generating report.
In another embodiment, method environment/behavior/demographic data considered as additional " locus " is used.In relevant embodiment, these data can be obtained by information source, such as medical science or scientific literature or database (such as, smoking w/ lung cancer association or from insurance industry health risk assessment).In one embodiment, GCI scoring is produced for one or more complex diseases.Complex disease can be affected by multiple gene, environmental factors and their interaction.When studying complex disease, the interaction that Water demand is possible in a large number.In one embodiment, the program of such as Bonferroni correction is for correcting multiple comparisons.In the embodiment substituted, when test is independently or shows the dependence of special type, Simes inspection is used to control overall significance level (also referred to as " family specific inaccuracy ") (SarkarS. (1998)).The proof (AnnStat26:494-504) that some probability representation for orderly MTP2 stochastic variable: Simes supposes.If 1, ..., for any k in K, p (k)≤α k/K, so all Kappa test specificity null hypothesiss of Simes inspection refusal are genuine overall null hypothesis (SimesRJ (1986) AnimprovedBonferroniprocedureformultipletestsofsignifica nce.Biometrika73:751-754).
Other embodiment that can use when polygene and multi-environment factor analysis controls false discovery rate (false-discoveryrate), i.e. the expectation ratio of the refusal null hypothesis of False Rejects.As in microarray research, when a part for null hypothesis can be assumed to mistake, this method is useful especially.The people such as Devlin (2003, propose modification that Benjamini and Hochberg (1995, Controllingthefalsediscoveryrate:apracticalandpowerfulap proachtomultipletesting.JRStatSocSerB57:289-300) that when in limited loci association study test in a large number possible gene × gene interaction control false discovery rate increase progressively program Analysisofmultilocusmodelsofassociation.GenetEpidemiol25: 36-47).Benjamini with Hochberg program is checked relevant with Simes; Setting k *=maxk so that p (k)≤α k/K, its refusal is all corresponds to p (1) ..., p (k *) k *null hypothesis.In fact, when all null hypothesiss are true time, Benjamini and Hochberg program simplification is Simes inspection (BenjaminiY, YekutieliD (2001) Thecontrolofthefalsediscoveryrateinmultipletestingunderd ependency.AnnStat29:1165-1188).
In some embodiments, individuality carries out ranking to produce final scoring based on wherein asking that the colony of scoring with individuality compares, this can be expressed as the ranking in colony, such as the 99th point of position or the 99th, 98,97,96,95,94,93,92,91,90,89,88,87,86,85,84,83,82,81,80,79,78,77,76,75,74,73,72,71,70,69,65,60,55,50,45,40,40,35,30,25,20,15,10,5 or 0 point of position.In another embodiment, scoring can be shown as scope, such as the 100 to 95 point of position, the 95 to 85 point of position, the 85 to 60 point of position or any subrange between the 100 to 0 point of position.In another embodiment again, individually carry out ranking by quartile, the 75th such as the highest quartile or the 25th minimum quartile.In further embodiment, the average or meta in individual and group is marked to compare and is carried out ranking.
In one embodiment, the colony compared with individuality comprises the people in a large number from different geography and ethnic background, such as global colony.In other embodiments, colony compared with individuality be limited to specific geographic, family, race, sex, the age (fetus, newborn infant, children, teenager, youth, grownup, the elderly individual), morbid state (such as, Symptomatic, asymptomatic, carrier, early send out, tardy).In some embodiments, the colony compared with individuality is derived from information that is open and/or personal information source report.
In one embodiment, display unit is used to make individual GCI scoring or GCIPlus mark visual.In some embodiments, display screen (such as, computer monitor or TV screen) for visual display, such as, has the individual entrance of relevant information.In another embodiment, display unit is static status display device, such as printer page.In one embodiment, display can comprise, but be not limited to one or more with lower device: case unit (bin) (such as, 1-5,6-10,11-15,16-20,21-25,26-30,31-35,36-40,41-45,46-50,51-55,56-60,61-65,66-70,71-75,76-80,81-85,86-90,91-95,96-100), colored or shade of gray, thermometer, scale, pie chart, column diagram or rod figure.Such as, Figure 18 and 19 be the difference display of MS and Figure 20 for for Crohn disease.In another embodiment, thermometer is for showing GCI scoring and disease/state popularity.In another embodiment, thermometer display is along with the level of the GCI scoring change of report, and such as, Figure 15 to 17, color is corresponding with risk.Thermometer can show the colourity change (such as, gradually changing to the redness of higher GCI scoring from the blueness of lower GCI scoring) increased with GCI scoring.In related embodiment, thermometer display is with the level of the GCI scoring change of report and the colourity change with risk class increase.
In the embodiment substituted, audio feedback is used to transmit individual GCI scoring to individuality.In one embodiment, audio feedback is danger classes is high or low verbal communication.In another embodiment, audio feedback is describing of special GCI scoring, and what such as numeral, hundredths, scope, quartile or average with colony or middle GCI marked compares.In one embodiment, lived people in person or by communicator, such as phone (landline telephone, portable phone or satellite phone) transmits audio feedback, or transmit audio feedback by individual entrance.In another embodiment, audio feedback is transmitted by automatic system (such as computer).In one embodiment, audio feedback is as the part transmission of interactive sound reaction (IVR) system, and this system is that a kind of computer that allows uses normal telephone calls to detect the technology of voice and keypad tone.In another embodiment, individuality can by IVR system and central server interaction.IVR system can be reacted to the audio frequency recorded in advance or dynamically produce with interactive with individuality and provide the audio feedback of its risk class to them.In one embodiment, individuality can call out the number of being answered by IVR.Such as, at optionally input authentication code, security code or after speech recognition program, IVR system allows object select option from menu, keypad tone or voice menu.One in these options can provide his or her risk class to individuality.
In another embodiment, individual GCI scoring uses display unit visual and uses audio feedback transmission, such as, by individual entrance.This combination can comprise visual display and the audio feedback of GCI scoring, and it discusses GCI scoring to the dependency of the holistic health of individuality and the possible preventive measures that can propose.
In one embodiment, multistep processes is used to generate GCI scoring.Start, for each state that will study, calculate the relative risk being derived from the odds ratio of each genetic marker.For p=0.01,0.02 ..., 0.5 each popular angle value, the GCI scoring of HapMapCEU colony calculates based on popularity and HapMap gene frequency.If GCI scoring is constant under the popularity of change, then there is optimum sample size in being uniquely assumed to of considering.In addition, can determine that this model pop degree is responsive.For any combination of never call value, obtain relative risk and the distribution of scoring in HapMap colony.For each new individuality, individual score and HapMap distribute and to compare and gained is marked as individual ranking in this colony.Due to the hypothesis done in process, the resolving power of the scoring of report may be lower.Colony will be divided into percentage point (3-6 case unit), and the case unit of report will be one that wherein individual ranking falls into.Based on such as the consideration of the resolving power of the scoring of each disease, the quantity of case unit can be different to various disease.When linking between the scoring of different HapMap individuality, average ranking will be used.
In one embodiment, higher GCI scoring is interpreted as representing the increase risk obtaining or had state or disease by diagnosis.In another embodiment, use mathematical model to show that GCI marks.In some embodiments, GCI scoring is based on the mathematical model illustrated as the incomplete feature on the basis of the information about colony and/or disease or state.In some embodiments, mathematical model comprises at least one hypothesis specific of the part as the basis calculating GCI scoring, and wherein said hypothesis includes, but are not limited to: the hypothesis of given advantage ratio; The hypothesis that the popularity of state is known; The hypothesis that genotype frequency in colony is known; With human consumer from the hypothesis with the colony that institute uses and the family background identical with HapMap; Merge the long-pending hypothesis that risk is the different risk factors of idiogenetics mark.In some embodiments, GCI also can comprise the long-pending hypothesis that genotypic polygene type frequency is the gene frequency of each SNP or idiogenetics mark (such as, different SNP or genetic marker are independently in whole colony).
optimum sample size
In one embodiment, under the risk owing to genetic marker set is the long-pending hypothesis owing to the risk of indivedual genetic marker, GCI scoring is calculated.This means that different genetic marker and other genetic marker are independently owing to the risk of disease.In form, existence has risk allelotrope r 1..., r kwith non-risk allelotrope n 1..., n kk genetic marker.In SNPi, we represent that three possible genotype values are r ir i, n ir iand n in i.Individual genotype information can by vector (g 1..., g k) describe, wherein according to the allelic number of risk on i position, g ican be 0,1 or 2.We pass through represent the relative risk of heterozygous genotypes in the same position compared with the non-risk allelotrope that isozygotys in i position.In other words, we define similarly, we represent r ir igenotypical relative risk is under optimum sample size, we have genotype (g at supposition 1..., g k) the risk of individuality be optimum sample size before this in document with Model case comparative study or for visual object.
assessment relative risk
In another embodiment, the relative risk for different genetic marker is known, and optimum sample size may be used for risk assessment.But comprise in the embodiment of association study at some, research and design prevents from reporting relative risk.In some case control studies, relative risk directly can not be calculated by data when further not supposing.Replace report relative risk, common mode is the odds ratio (OR) of reporter gene type, and it carries given risk genotype disease (r ir ior n ir i) probability to the ratio of probability not carrying given risk genotype disease.In form,
OR i 1 = P ( D | n i r i | ) P ( D | n i r i | ) · 1 - P ( D | n i n i | ) 1 - P ( D | n i r i | )
OR i 2 = P ( D | r i r i | ) P ( D | n i n i | ) · 1 - P ( D | n i n i | ) 1 - P ( D | r i r i | )
Find relative risk may require extra hypothesis by odds ratio.Such as, the gene frequency in whole population is supposed with known or process assesses (these by existing data set, such as, can comprise 120 chromosomal HapMap data sets and assess), and/or the popularity p=p (D) of hypothesis disease is known.Can be obtained by aforementioned three equatioies:
p=a·P(D|n in i)+b·P(D|n ir i)+c·P(D|r ir i)
OR i 1 = P ( D | n i r i | ) P ( D | n i r i | ) · 1 - P ( D | n i n i | ) 1 - P ( D | n i r i | )
OR i 2 = P ( D | r i r i | ) P ( D | n i n i | ) · 1 - P ( D | n i n i | ) 1 - P ( D | r i r i | )
By the definition of relative risk, divided by pP (D|n in i) after item, the first equation can be rewritten as:
1 P ( D | n i n i ) = a + bλ 1 i + cλ 2 i p ,
And therefore, latter two equation can be rewritten as:
OR 1 i = λ 1 i · ( a - p ) + bλ 1 i + cλ 2 i a + ( b - p ) λ 1 i + cλ 2 i
(1)
OR i 2 = λ 2 i · ( a - p ) + bλ 1 i + cλ 2 i a + bλ 1 i + ( c - p ) λ 2 i
It should be noted that, when a=1 (non-risk gene frequency is 1), equation system 1 be equal to Zhang and Yu formula in ZhangJ and YuK. (What ' stherelativerisk Amethodofcorrectingtheoddsratioincohortstudiesofcommonou tcomes.JAMA, 280:1690-1,1998, its full content is incorporated herein by reference).Contrary with Zhang and Yu formula, some embodiments of the present invention consider the gene frequency in colony, and it may affect relative risk.Other embodiment considers the interdependent property of relative risk.This is contrary with calculating each relative risk independently.
Equation system 1 can be rewritten as has four two quadratic equations that may separate at the most.Gradient descent algorithm (gradientdescentalgorithm) may be used for solving these equations, and wherein starting point is set to odds ratio, such as, with .
Such as:
f 1 ( λ 1 , λ 2 ) = OR i 1 ( a + ( b - p ) λ 1 i + cλ 2 i ) - λ 1 i · ( ( a - p ) + bλ 1 i + cλ 2 i )
f 2 ( λ 1 , λ 2 ) = OR i 2 ( a + bλ 1 i + ( c - p ) λ 2 i ) - λ 2 i · ( ( a - p ) + bλ 1 i + cλ 2 i )
These non trivial solution are found to be equivalent to find function g (λ 1, λ 2)=f 1(λ 1, λ 2) 2+ f 2(λ 1, λ 2) 2minimum value.
Therefore,
dg dλ 1 = 2 f 1 ( λ 1 , λ 2 ) · b · ( λ 2 - OR 2 ) + 2 f 2 ( λ 1 , λ 2 ) ( 2 bλ 1 + cλ 2 + a - OR 1 b - p + OR 1 p )
dg dλ 2 = 2 f 2 ( λ 1 , λ 2 ) · c · ( λ 1 - OR 1 ) + 2 f 1 ( λ 1 , λ 2 ) ( 2 cλ 2 + bλ 1 + a - OR 2 c - p + OR 2 p )
In this example, we are by setting x 0=OR 1, y 0=OR 2start.We will be worth [ε]=10 -10be set as the tolerance constant (toleranceconstant) of whole algorithm.In iteration i, we define γ = min { 0.001 , x i - 1 [ epsilon ] + 10 | dg dλ 1 ( x i - 1 , y i - 1 ) | , y i - 1 [ epsilon ] + 10 | dg dλ 2 ( x i - 1 , y i - 1 ) | } . Then, we set
x i = x i - 1 - γ dg dλ 1 ( x i - 1 , y i - 1 )
y i = y i - 1 - γ dg dλ 2 ( x i - 1 , y i - 1 )
Repeat these iteration until g (x i, y i) < tolerance, wherein in the code provided, tolerance is set as 10 -7.
In this embodiment, these equations give a, b, c, p, OR 1and OR 2the normal solution of different value.Figure 10
the steadiness of relative risk assessment
In some embodiments, different parameters (popularity, gene frequency and the odds ratio error) impact on the estimated value of relative risk is determined.In order to measure gene frequency and popularity estimated value to the impact of Relative risk value, calculate the relative risk (under HWE) of the value from one group of different odds ratio and different gene frequency, and these results calculated are drawn for the popular angle value in 0 to 1 scope.Figure 10.In addition, for fixing popular angle value, the relative risk of gained can as the function plotting of risk gene frequency.Figure 11.When p=0, λ 1=OR 1, and λ 2=OR 2, and as p=1, λ 1=λ 2=0.This can directly calculate from described equation.In addition, in some embodiments, when risk gene frequency height, λ 1closer to linear function, and λ 2closer to the concave function with bounded second derivative.In the limiting case, as c=1, λ 2=OR 2+ p (1-OR 2), and if OR 1≈ OR 2, the latter is equally close to linear function.When risk gene frequency is low, λ 1and λ 2close to the behavior of function 1/p.In the limiting case, as c=0, &lambda; 1 = O R 1 1 - p + pO R 1 , &lambda; 2 = O R 2 1 - p + pO R 2 . This shows, for high risk gene frequency, incorrect popularity estimated value can not affect the relative risk of gained significantly.In addition, for low risk gene frequency, if substitute correct popularity p with popular angle value p '=α p, so the relative risk of gained will be eliminated at the most coefficient.This is illustrated in (c) and (d) drawing of Figure 11.It should be noted that, for high risk gene frequency, two width drawings are quite similar, and for low gene frequency, there is higher deviation in the difference of Relative risk value, and this deviation is less than coefficient 2.
calculate GCI scoring
In one embodiment, the reference set representing Reference Group is used to calculate hereditary aggregative index.This reference set can be one of colony in HapMap or another genotype data collection.
In this embodiment, GCI is calculated as follows.Each in k risk genes seat, uses equation system 1 to calculate relative risk by odds ratio.Then, the long-pending property scoring of each individuality in reference set is calculated.The GCI with the individuality of long-pending property scoring s is the mark that reference data concentrates all individualities of the scoring with s '≤s.Such as, if the individuality of 50% has the long-pending property scoring being less than s in reference set, so the final GCI scoring of this individuality will be 0.5.
other model
In one embodiment, optimum sample size is used.In the embodiment substituted, other model can be used for the object determining that GCI marks.Other suitable model includes, but are not limited to:
Additive model.Under additive model, there is genotype (g 1... g k) the risk of individuality be assumed to be GCI ( g 1 , . . . , g k ) = &Sigma; i = 1 k f ( &lambda; g i i ) .
Generalized Additive Models.In Generalized Additive Models, suppose existence function f so that there is genotype (g 1... g k) the risk of individuality be
Harvard improvement scoring (Het).This scoring is drawn by people such as G.AColditz, thus this scoring is applied to genetic marker (Harvardreportoncancerpreventionvolume4:Harvardcancerrisk index.CancerCausesandControls, 11:477-488,2000, be incorporated herein its full content).Although function f carries out computing with advantage ratio instead of relative risk, Het scoring is the scoring of broad sense additivity in essence.This is useful when relative risk is difficult to assessment.In order to defined function f, intermediate function g is defined as:
g ( x ) = 0 1 < x &le; 1.09 5 1.09 < x &le; 1.49 10 1.49 < x &le; 2.99 25 2.99 < x &le; 6.99 50 6.99 < x
Then calculate amount, wherein for the frequency of SNPi heterozygous individual in whole reference group.Then function f is defined as f (x)=g (x)/het, and Harvard improvement scoring (Het) is defined as simply
Harvard improvement scoring (Hom).Except value het is worth replace beyond, this scoring is marked similar to Het, wherein, for having the frequency of the allelic individuality of risk of isozygotying.
Sharpest edges ratio.In this model, suppose that one of genetic marker (having of sharpest edges ratio) gives the lower bound of the constitution's risk of whole group of objects.In form, there is genotype (g 1... g k) the scoring of individuality be
comparison between scoring
In one embodiment, for 10 SNPs relevant to T2D, whole HapMapCEU colony calculates GCI scoring based on multiple model.Related SNP is rs7754840, rs4506565, rs7756992, rs10811661, rs12804210, rs8050136, rs1111875, rs4402960, rs5215, rs1801282.Each in these SNP, three possible genotypic odds ratios are reported in the literature.CEU colony is made up of three people's groups of 30 mother-father-children.In order to avoid dependence, adopt 60 father and mother from this colony.Get rid of and have in one of 10 SNP without the body one by one that calls, obtain 59 individual one group.Then several different model is used to calculate the GCI grade of each individuality.
Can observe, for this data set, different model produces the result of height correlation.Figure 12 and 13.Between each pair of model, calculate Spearman dependency (table 2), it demonstrates the relation conefficient that long-pending property and additive model have 0.97, and when therefore using additivity or optimum sample size, GCI scoring is firm.Similarly, the dependency between Harvard improvement scoring and optimum sample size is 0.83, and the relation conefficient between Harvard scoring and additive model is 0.7.But, use sharpest edges than producing as hereditary score the two points of scorings (dichotomousscore) defined by a SNP.Generally speaking, these results show, scoring ranking provides and makes the minimized stable framework of model dependency.
Table 2: model between CEU data scoring distribution Spearman dependency.
The impact that the variation measuring T2D popularity distributes on gained.Popular angle value changes (Figure 14) between 0.001 ~ 0.512.For the situation of T2D, can find out, different popular angle value causes individual identical sequence (Spearman dependency >0.99), therefore can suppose the artificial fixed value 0.001 of popularity.
by model extension to the modification of any amount
In another embodiment, model extension extremely can be there is the situation of the possible modification of any amount.Previous consideration relates to the situation of the possible modification (nn, nr, rr) of existence three.Usually, when known many SNP associations, the modification of any amount can be found in colony.Such as, when the interaction between two genetic markers is associated with state, there are nine kinds of possible modification.Which results in eight different advantage ratios.
In order to summarize prime formula, can suppose to there is the possible modification a of k+1 kind 0..., a k, there is frequency f 0, f 1..., f k, the odds ratio of mensuration is 1, OR 1..., OR kand the Relative risk value of the unknown is 1, λ 1..., λ k.Can suppose further, relative to a 0measure all relative risks and odds ratio, and therefore, &lambda; i = P ( D | a i ) P ( D | a o ) With OR i = P ( D | a i ) P ( D | a o ) &CenterDot; 1 - P ( D | a i ) 1 - P ( D | a o ) . Based on:
p = &Sigma; i = 0 k f i P ( D | a i ) ,
Can determine
OR i = &lambda; i &Sigma; i = 0 k f i &lambda; i - p &Sigma; i = 0 k f i &lambda; i - &lambda; i p .
And, if setting this causes following equation:
&lambda; i = C &CenterDot; OR i C - p + OR i p ,
And therefore,
C = &Sigma; i = 0 k f i &lambda; i = &Sigma; i = 0 k C &CenterDot; OR i f i C - p + OR i p ,
Or
1 = &Sigma; i = 0 k OR i f i C - p + OR i p .
The latter is the equation with a variable (C).This equation can produce many different solutions (substantially, the individual different solution of as many as k+1).Criteria optimization instrument (such as Gradient Descent) may be used for finding closest to C 0=∑ f it isolution.
Present invention uses for the quantitative stable scoring framework of risk factor.Although different genetic model can cause different scorings, result is normally correlated with.Therefore, the quantitative of risk factor does not rely on used model usually.
the case control study of assessment relative risk
The method being evaluated relative risk in case control study by multiallelic odds ratio is also provided in the present invention.Contrary with previous method, the method considers gene frequency, the popularity of disease and the dependence between not homoallelic relative risk.Determine the performance of case control study of the method to simulation, find it be pole accurately.
method
When testing the cognation of specific SNP and disease D, R and N represents the risk of this specific SNP and non-risk allelotrope.P (RR|D), P (RN|D) and P (NN|D) represent hypothesis individual respectively for risk allelotrope be isozygoty, for non-risk allelotrope be heterozygosis or isozygoty when be subject to the probability of sickness influence.F rR, f rNand f nNfor representing three genotypic frequencies in colony.Use these to define, relative risk is defined as
&lambda; RR = P ( D | RR ) P ( D | NN )
&lambda; RN = P ( D | RN ) P ( D | NN )
In case control study, P (RR|D), P (RR| ~ D) value (i.e. the frequency of RR in case and contrast) can be assessed, and P (RN|D), P (RN| ~ D), P (NN|D) and P (NN| ~ D), the i.e. frequency of RN and NN in case and contrast.In order to estimate relative risk, Bayes (Bayes) law can be used to obtain:
&lambda; RR = P ( RR | D ) f NN P ( NN | D ) f RR
&lambda; RN = P ( D | RN ) f NN P ( D | NN ) f RR
Therefore, if the frequency of known type, people can use them to calculate relative risk.In colony, genotypic frequency can not calculate from case-control study itself, because they depend on the popularity of disease in colony.Particularly, if the popularity of disease is p (D), then:
f RR=P(RR|D)p(D)+P(RR|～D)(1-p(D))
f RN=P(RN|D)p(D)+P(RN|～D)(1-p(D))
f NN=P(NN|D)p(D)+P(NN|～D)(1-p(D))。
As enough hour of p (D), genotypic frequency can close to the genotype frequency in control population, but when popularity height, this can not be estimated value accurately.But if provide comparable data collection (such as, HapMap [cite]), people can estimate genotype frequency based on comparable data collection.
Great majority research recently does not use comparable data collection to estimate relative risk, and only reports odds ratio.Odds ratio can be write
OR RR = P ( RR | D ) P ( NN | ~ D ) P ( NN | D ) P ( RR | ~ D )
OR RN = P ( RN | D ) P ( NN | ~ D ) P ( NN | D ) P ( RN | ~ D )
Owing to usually not needing the estimated value with colony's allelic frequency, so odds ratio is normally favourable; In order to calculate odds ratio, required is case and the genotype frequency in contrasting usually.
In some cases, genotype data itself is unavailable, but summary data (such as odds ratio) is available.This is the situation when carrying out meta (meta-analysis) based on the result from previous case control study.In this case, confirm how to find relative risk from odds ratio.Use the fact that following equation shows:
p(D)=f RRP(D|RR)+f RNP(D|RN)+f NNP(D|NN)
If this equation is divided by P (D|NN), we obtain
p ( D ) p ( D | NN ) = f RR &lambda; RR + f RN &lambda; RN + f NN
This makes odds ratio can be write as following form:
OR RR = P ( D | RR ) ( 1 - P ( D | NN ) ) P ( D | NN ) ( 1 - P ( D | RR ) ) = &lambda; RR p ( D ) p ( D | NN ) - p ( D ) p ( D ) p ( D | NN ) - p ( D ) &lambda; RR = &lambda; RR f RR &lambda; RR + f RN &lambda; RN + f NN - p ( D ) f RR &lambda; RR + f RN &lambda; RN + f NN - p ( D ) &lambda; RR
By similar calculating, obtain following equation system:
OR RR = &lambda; RR f RR &lambda; RR + f RN &lambda; RN + f NN - p ( D ) f RR &lambda; RR + f RN &lambda; RN + f NN - p ( D ) &lambda; RR
OR RN = &lambda; RN f RR &lambda; RR + f RN &lambda; RN + f NN - p ( D ) f RR &lambda; RR + f RN &lambda; RN + f NN - p ( D ) &lambda; RN .
Equation 1
If the genotype frequency in known advantages ratio, colony and the popularity of disease, then can obtain relative risk by solving this system of equations.
It should be noted that to there are two quadratic equations, therefore they have maximum four solutions.But, as shown below, a possible solution is existed usually for this equation.
It should be noted that, work as f nNwhen=1, equation system 1 is equal to Zhang and Yu formula; But, consider the gene frequency in colony here.And our method considers the following fact: two relative risks are depending therefrom, and previous method proposes to calculate each relative risk independently.
The relative risk of multiple alleles locus.If consider multiple labeling or other multiple alleles modification, calculate slightly complicated.A 0, a 1..., a kk+1 allelotrope, wherein a expressing possibility 0for non-risk allelotrope.Assume that for k+1 the possible gene frequency f of allelotrope in colony 0, f 1, f 2..., f k.For allelotrope i, relative risk and odds ratio are defined as
&lambda; i = P ( D | a i ) P ( D | a 0 )
OR i = P ( D | a i ) ( 1 - P ( D | a 0 ) ) P ( D | a 0 ) ( 1 - P ( D | a i ) ) = &lambda; i 1 - P ( D | a 0 ) 1 - P ( D | a i )
Following equation is applicable to the popularity of disease:
p ( D ) = &Sigma; i = 0 k f i P ( D | a i )
Therefore, by by equation both sides all divided by p (D|a 0), we obtain:
p ( D ) P ( D | a 0 ) = &Sigma; i = 0 k f i &lambda; i
Obtain:
OR i = &lambda; i &Sigma; i = 0 k f i &lambda; i - p ( D ) &Sigma; i = 0 k f i &lambda; i - &lambda; i p ( D ) ,
By setting C = &Sigma; i = 0 k f i &lambda; i , Obtain &lambda; i = C &CenterDot; OR i p ( D ) OR i + C - p ( D ) . Therefore, by the definition of C, draw:
1 = &Sigma; i = 0 k f i &lambda; i C = &Sigma; i = 0 k f i OR i p ( D ) OR i + C - p ( D ) .
This is the polynomial equation with a variable C.Once determine C, just determine relative risk.Polynomial expression is k+1 degree, and therefore we estimate to have k+1 solution at the most.But the right side due to equation strictly simplifies the function into C, so usually only a solution may be there is for this equation.Use binary search easily find this to separate because this Xie Jie in C=1 with C = &Sigma; i = 0 k O R i Between.
The stability of relative risk assessment.Measure the impact of variant parameter (popularity, gene frequency and odds ratio error) for the estimated value of relative risk.In order to measure gene frequency and popularity estimated value to the impact of Relative risk value, calculate relative risk by the value (under HWE) of one group of different odds ratio, different gene frequency, and the popular angle value in 0 to 1 scope is drawn to the result that these calculate.
In addition, for fixing popular angle value, the relative risk of gained is as the function plotting of risk gene frequency.Clearly, when all p (D)=0, λ rR=OR rRand λ rN=OR rN, and as p (D)=1, λ rR=λ rN=0.This directly can be calculated by equation 1.In addition, when risk gene frequency height, λ rRclose to linear performance, and λ rNclose to the concave function with bounded second derivative.When risk gene frequency is low, λ rRand λ rNclose to the performance of function 1/p (D).This means for high risk gene frequency, the erroneous estimate of popularity can not affect the relative risk of gained greatly.
Following examples illustrate and explain the present invention.Scope of the present invention is not limited to these embodiments.
example I
sNP distribution map generalization and analysis
There is provided the sample hose test kit (such as buying from DNAGenotek) to individuality, saliva sample (about 4ml) leaves in this stopple coupon by individuality, will extract genomic dna from saliva sample.Saliva sample is delivered to the laboratory of the CLIA certification carrying out processing and analyzing.Usually, sample is supplied to easily in individual transport container and is delivered to mechanism for testing by mailing overnight in collection test kit.
In a preferred embodiment, genomic dna is separated from saliva.Such as, use the DNA provided by DNAGenotek from gathering test kit technology, the individual about 4ml saliva sample gathered for Clinical Processing.By Sample delivery to suitable for the treatment of laboratory after, by the thermally denature of sample and protease digestion (usually using the reagent by gathering test kit supplier and providing to process at least one hour at 50 DEG C) DNA isolation.Subsequently, carry out centrifugal to sample, and alcohol settling is carried out to supernatant liquid.DNA throw out is suspended in and is suitable in the damping fluid of subsequent analysis.
According to known program and/or by gathering the program that provides of kit manufacturers, from saliva sample, be separated individual genomic dna.Usually, first thermally denature and protease digestion are carried out to sample.Then, centrifugation is carried out to sample, and retains supernatant liquid.Then supernatant liquid is carried out alcohol settling to obtain the precipitation of the genomic dna comprising about 5 ~ 16ug.DNA throw out is suspended in the EDTA (TE) of the Tris (pH7.6) of 10mM, 1mM.Use the instrument and operation instruction that are provided by array manufacturer, by genomic dna and the high-density SNP array (the high-density SNP array such as provided by Affymetrix or Illumina) be purchased are hybridized to generate SNP distribution plan.Individual SNP distribution plan is stored in encrypting database or strong room.
By with establish, compared with the clinical database of medical science related SNP (its existence in genome and given disease or state about), the data structure of inquiry patient is to find the SNP of imparting risk.This database comprises the information of the statistics dependency of specific SNP and SNP haplotype and specified disease or state.Such as, as shown in EXAMPLE III, the polymorphism in apolipoprotein E gene causes the different isotype of protein, and this is relevant with the statistics likelihood that Alzheimer occurs again.As another embodiment, the individuality with the modification of the clottable protein warmed factor Ⅴ being called factor Ⅴ Leiden has the blood coagulation trend of increase.Wherein many genes of SNP and disease or state phenotypic correlation are shown in Table 1.Checked and approved science accuracy and the importance of the information in database by research/clinical board of consultants, and can be checked by the government organs supervised.Can more new database continuously, because more, SNP-is disease associated occurs from scientific circles.
The analytical results of individual SNP distribution plan is provided to patient safety by online entrance or mail.Explanation and supportive information is provided, the information about factor Ⅴ Leiden such as, shown in EXAMPLE IV to patient.The doctor be convenient to patient is discussed by the secure access of the SNP profile information of individuality (such as by online entrance), and gives the ability selected is carried out for individualized medical treatment.
Example II
the renewal of genotype correlation
In response to the request initially determining idiotype dependency, generate Genome Atlas, obtain genotype correlation, and provide result to individuality as described in example I.After initially the determining of genotype correlation of individuality, subsequently when known additional genotype correlation, determine the dependency maybe can determining to upgrade.Registered user has advanced resistry and its gene type spectrum is kept in encrypting database.The dependency upgraded is carried out on the gene type spectrum stored.
Such as, as described in above example I, initial gene type dependency has determined that particular individual does not have ApoE4, and therefore not easily suffers from Early onset Alzheimer, and determines that this individuality does not have factor Ⅴ Leiden.After this is initially determined, new dependency becomes known and through checking, so that polymorphism in given gene (being assumed to be gene XYZ) is relevant to given state (being assumed to be state 321).The genotype correlation that this is new joins in the master data base of human genotype correlation.Then by first obtaining the data of genes involved XYZ from the Genome Atlas of the particular individual be stored in encrypting database, renewal is provided to particular individual.By the genes involved XYZ data of particular individual compared with the gene XYZ information of the master data base of renewal.The specific individual susceptibility for state 321 or ill physique is determined from this contrast.The result this determined joins in the genotype correlation of particular individual.By whether particular individual renewal result that is responsive to state 321 or the upper susceptible of heredity is supplied to particular individual together with explanatory and supportive information.
EXAMPLE III
the dependency of ApoE4 locus and Alzheimer
The risk having shown Alzheimer (AD) is relevant to the polymorphism in apo E (APOE) gene, and this polymorphism causes three kinds of isotypes of the APOE being called ApoE2, ApoE3 and ApoE4.These isotypes one or two amino acid on the residue 112 and 158 of APOE albumen is mutually different.ApoE2 comprises the halfcystine/halfcystine of 112/158; ApoE3 comprises the halfcystine/arginine of 112/158; Arginine/the arginine of 112/158 is comprised with ApoE4.As shown in table 3, the danger that Alzheimer was shown effect at the less age increases with APOE ε 4 gene copy number.Equally, as shown in table 3, the relative risk of AD increases with APOE ε 4 gene copy number.
The table allelic popularity of 3:AD risk (Corder etc., Science:261:921-3,1993)
Table 4: the AD relative risk (Farrer etc., JAMA:278:1349-56,1997) with ApoE4
APOE genotype Odds ratio
ε2ε2 0.6
ε2ε3 0.6
ε3ε3 1.0
ε2ε4 2.6
ε3ε4 3.2
ε4ε4 14.9
EXAMPLE IV
the information of factor Ⅴ Leiden positive patient
Following information is the example that possible be supplied to the information with the individuality demonstrating the genome SNP distribution plan that there is factor Ⅴ Leiden gene.This individuality can have can provide the basis of information to register in Initial Report.
what is factor Ⅴ Leiden
Factor Ⅴ Leiden is not disease, and it refers to the specific gene existed by the direct heredity of a people.Factor Ⅴ Leiden is the modification of the rho factor V (5) that blood coagulation needs.The people with factor Ⅴ disappearance more may seriously bleed, and the blood coagulation trend with the people of factor Ⅴ Leiden increases.
The people carrying factor Ⅴ Leiden gene has the risk of the appearance blood clot (thrombosis) of higher than others in colony 5 times.But never there is blood clot in many people with this gene.At UK and USA, one or more factor Ⅴ Leiden gene carries in 5% of colony, and this is far more than the quantity of people reality being suffered from thrombosis.
how you obtain factor Ⅴ Leiden
Factor V gene is by the direct heredity of a people.Heredity feature as in all, gene genetic from mother a heredity from father.Thus, may heredity: two normal genes or a factor Ⅴ Leiden gene and a normal gene or two factor Ⅴ Leiden genes.There is a factor Ⅴ Leiden gene and will cause the risk of slightly high generation thrombosis, but having two genes causes much bigger risk.
what the symptom of factor Ⅴ Leiden is
There is no symptom, unless you have blood clot (thrombosis).
what does is danger signal?
Modal problem is the blood clot at leg.Leg swelling, pain and rubescently demonstrate this problem.In rarer case, may occur lung's blood clot (lung thrombosis), it causes expiratory dyspnea.According to the size of blood clot, there is serious expiratory dyspnea from not almost being aware patient in the severity of this illness.In even rarer case, blood clot may occur in arm or other body part.Because these grumeleuses are formed in pumping blood to the vein of heart instead of be formed in artery (it exports blood from heart), factor Ⅴ Leiden can not make the risk of Coronary thrombosis increase.
what does and can avoid blood clot
Factor Ⅴ Leiden only slightly increases the risk causing blood clot, and many people with this state never thrombosis occur.A people can do many things to avoid and cause blood clot.Avoid standing for a long time or sitting with same posture.When long-distance travel, importantly take exercise regularly---blood must be made " not leave standstill motionless ".To stay up late or smoking greatly will increase and occur the risk of blood clot.The women carrying factor Ⅴ Leiden gene should not take Contraceptive pill, because this will enlarge markedly the chance suffering from thrombosis.The women carrying factor Ⅴ Leiden gene also should seek advice from its doctor, because this also can increase thrombotic risk before gestation.
how doctor finds whether you have factor Ⅴ Leiden
The gene of factor Ⅴ Leiden can find in blood sample.
Usually determined by ultrasonic examination at the blood clot of leg or arm.
A kind of material is being injected blood with after making blood clot manifest, blood clot also can be detected by X-ray.Clot in lung is more difficult to find, but doctor tests the distribution of intrapulmonary blood flow by using radioactive substance to go and flow to the distribution of the air in lung usually.These two kinds of distribution patterns should match---and unmatch list shows to there is blood clot.
how factor Ⅴ Ieiden processes
The people with factor Ⅴ Leiden does not need treatment, unless their blood starts condensation, in this case, doctor will output dilute blood (anticoagulant) medicine, such as warfarin (such as, tintorane) or heparin are to prevent further blood clot.Treatment will continue three to six months usually, but if there is several blood clot, then may need the longer time.When severe, the process of pharmacological agent may continue indefinitely; When extremely rare, blood clot may need operation to remove.
how to process at pregnancy duration factor Ⅴ Leiden
The women carrying two factor Ⅴ Leiden genes will need to accept the treatment of heparin clot promoting drug at pregnancy duration.Identical treatment is applicable to the women only carrying a factor Ⅴ Leiden gene itself previously having had blood clot or had blood clotting family history.
All women carrying factor Ⅴ Leiden gene may need to wear special stocking in case hemostasis grumeleuse in the gestation second half section.After child's birth, anticoagulation medicine heparin can be opened to them.
prognosis
Occur that the risk of blood clot increased with the age, but the people carrying this gene to 100 carry out with in the investigation at age, find that only minority once suffered from thrombosis.Genetic consultant association of country (TheNationalSocietyforGeneticCounselors (NSGC)) can provide the list of genetic consultant in your location and about the information setting up family history.Www.nsgc.org/consumer searches their online database.
Although shown at this and described the preferred embodiment of the present invention, very clear to those skilled in the art, these embodiments only provide by way of example.Many modification that those skilled in the art can expect now, change and replacement and do not depart from the present invention.Should be appreciated that, the many alternative for embodiments of the present invention described herein may be used for realizing the present invention.It is contemplated that following claim limits scope of the present invention, and the present invention covers method and structure in the scope of these claims and equivalent thereof.

Claims (20)

1. generate the method that individual hereditary aggregative index (GCI) is marked, the method comprises:
A) genetic material of described individuality is obtained;
B) Genome Atlas is generated from described genetic material;
C) by the Genome Atlas of described individuality is determined that the GCI of the phenotype of described individuality marks compared with the database of current mankind genotype correlation, wherein human genotype correlation is the dependency of genetic variant and phenotype, wherein said GCI scoring is tested and appraised odds ratio or the relative risk acquisition of one or more genetic loci, and
Wherein said phenotype is selected from Alzheimer's disease (AD), colorectal carcinoma (CRC), osteoarthritis (OA), exfoliation glaucoma (XFG), fat (BMIOB), Graves' disease (GD), hemochromatosis (HEM), myocardial infarction (MI), multiple sclerosis (MS), psoriasis (PS), restless leg syndrome (RLS), celiac disease (CelD), prostate cancer (PC), lupus (SLE), macular degeneration (AMD), rheumatoid arthritis (RA), mammary cancer (BC), Crohn disease (CD), diabetes B (T2D) and combination thereof,
And wherein said genetic variant is selected from SNP: be rs4420638 when described genotype is AD, described genotype is rs6983267 when being CRC, described genotype is rs4911178 when being OA, described genotype is rs2165241 when being XFG, described genotype is rs9939609 or rs9291171 when being BMIOB, is rs3087243 when described genotype is GD, DRB1*0301DQA1*0501 is rs1800562 or rs129128 when described genotype is HEM, is rs1866389 when described genotype is MI, rs1333049 or rs6922269 is rs6897932 when described genotype is MS, rs12722489 or DRB1*1501 is rs6859018 when described genotype is PS, rs11209026 or HLAC*0602 is rs6904723 when described genotype is RLS, rs2300478, rs1026732 or rs9296249 is rs6840978 when described genotype is CelD, rs11571315, rs2187668 or DQA1*0301DQB1*0302 is rs4242384 when described genotype is PC, rs6983267, rs16901979, rs17765344 or rs4430796 is rs12531711 when described genotype is SLE, rs10954213, rs2004640, DRB1*0301 or DRB1*1501 is rs10737680 when described genotype is AMD, rs10490924, rs541862, rs2230199, rs1061170 or rs9332739 is rs6679677 when described genotype is RA, rs11203367, rs6457617, DRB*0101, DRB1*0401 or DRB1*0404 is rs3803662 when described genotype is BC, rs2981582, rs4700485, rs3817198, rs17468277, rs6721996 or rs3803662 is rs2066845 when described genotype is CD, rs5743293, rs10883365, rs17234657, rs10210302, rs9858542, rs11805303, rs1000113, rs17221417, rs2542151 or rs10761659 is rs13266634 when described genotype is T2D, rs4506565, rs10012946, rs7756992, rs10811661, rs12288738, rs8050136, rs1111875, rs4402960, rs5215 or rs1801282,
With
D) report that described GCI marks.
2. method according to claim 1, wherein, third party obtains described genetic material.
3. method according to claim 1, wherein, described generation Genome Atlas is undertaken by third party.
4. method according to claim 1, wherein, described report comprises by result described in Internet Transmission.
5. method according to claim 1, wherein, described Genome Atlas is the full-length genome of described individuality.
6. method according to claim 1, wherein, the genotype correlation that described method comprises from 10 or more determines described multiple relative risk or odds ratio.
7. method according to claim 1, comprises further and generates GCIplus scoring.
8. method according to claim 1, wherein, described genetic material is from the biological sample being selected from blood, hair, skin, saliva, seminal fluid, urine, fecal materials, sweat and buccal sample.
9. method according to claim 1, wherein, described genotype correlation is the dependency of the phenotype of single nucleotide polymorphism and medical condition.
10. method according to claim 1, wherein, described Genome Atlas uses the method for the order-checking of high-density DNA microarray, genomic dna or PCR-based to generate.
11. methods according to claim 1, wherein, described result comprises the feature of described individuality being incorporated to and being selected from body data, medical data, demographic data, exposure data, lifestyle data, behavioral data, race, family, geography, sex, age, family history and predetermined phenotype further.
12. method according to claim 1, wherein, described Genome Atlas comprises the genetic marker with the genetic variant linkage disequilibrium of phenotypic correlation.
13. methods according to claim 1, wherein, described GCI scoring is the lifetime risk estimated.
14. method according to claim 1, wherein, described Genome Atlas comprises at least 100,000 kind of genetic variant.
15. method according to claim 1, wherein, described Genome Atlas comprises at least 400,000 kind of genetic variant.
16. methods according to claim 1, comprise report further about the information of described phenotype, and wherein this information is selected from preventive measure, health and fitness information, therapy, symptom understanding, the accurate discriminating of early detection scheme, intervention plan and described phenotype and disaggregated classification.
17. methods according to claim 11, wherein, described body data is selected from blood pressure, heart rate, glucose level, metabolite level, ion concentration, body weight, height, cholesterol levels, vitamin level, cytometry, weight index (BMI), protein level and transcript level.
18. method according to claim 1, comprises further:
F) described database is upgraded with at least one human genotype correlation; With
G) by by the Genome Atlas of described individuality and step f) described at least one human genotype correlation compared with generate the other relative risk of at least one of described phenotype or odds ratio;
H) from step g) the other relative risk of the described at least one determined or odds ratio calculate at least one hereditary aggregative index (GCI) upgraded; With
I) to care manager's report of described individuality or described individuality by step h) the described result that obtains.
19. method according to claim 1, wherein, the report that at least one GCI described marks comprises Internet Transmission.
20. method according to claim 19, wherein, described report comprises and marking by entering at least one GCI described in port transmission online.
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