TW200847056A - Genetic analysis systems and methods - Google Patents

Abstract

The present invention provides methods of determining a Genetic Composite Index score by assessing the association between an individual's genotype and at least one disease or condition. The assessment comprises comparing an individual's genomic profile with a database of medically relevant genetic variations that have been established to associate with at least one disease or condition.

Description

200847056 IX. INSTRUCTIONS: [Prior Art] The sequencing of the human genome and other recent developments in the human genome have revealed that the genome composition of any two people has a similarity of more than 99.9%. The relatively small number of variations in DNA between individuals causes differences in phenotypic traits and is associated with many human diseases, susceptibility to various diseases, and response to disease treatment. Variations in DNA between individuals exist in both coding and non-coding regions, and include base changes at specific loci in the genome 1) 1 VIII sequence, as well as insertions and deletions of DNA. The only line that appears at the single base position in the genome is called the mononucleotide polymorphism, or &quot;SNp,. Although SNPs are rare in human genome towels (4), they cause most DNA sequence variations between individuals, occurring approximately once every two (9) base pairs in the human genome (see Internati〇nal HapMap Project, www.hapmap.org) . When more human genetic information is available, we begin to understand the complexity of SNPs. Subsequently, the incidence of SNp in the genome becomes associated with the presence of various diseases and conditions and/or susceptibility to various diseases and conditions. With these correlations and other advances in human genetics, medical and personal health often develops patient-specific methods for medical and other choices, especially considering their genomic information. Therefore, it is desirable to provide individuals and their caregivers with information specific to the individual's personal genome, thereby providing personalized medical decisions and other decisions. SUMMARY OF THE INVENTION The present invention provides a method for assessing genotype correlation of an individual, which comprises 127264.doc 200847056 containing a) obtaining a genetic sample of the individual, ...generating a genomic profile of the individual' c) by comparing the individual The current database of genomic profiles and human genotypes and phenotypes to determine the genotype and phenotype of the individual, d) report the step c) to the individual or the individual's health care manager Etc. E) when the additional human genotype correlation becomes known, the database of human genotype correlations is updated with the additional human genotype correlation 'f) by comparing the individual's genome with step c) The profile or a portion thereof is associated with the additional human genotype to update the genotype association of the individual and to determine additional genotype correlations for the individual, and g) to report the step to the individual or the health care manager of the individual f) the results. The invention further provides a commercial method for assessing genotype correlation in an individual comprising: a) obtaining a genetic sample of the individual; b) generating a genomic profile of the individual; c) comparing the genomic profile of the individual with the human genotype The current database of correlations to determine the genotype correlation of the individual; d) the outcome of the determination of the genotype correlation of the individual to the individual in a manner of conservation; e) when additional human genotype correlation becomes When known, the database of human genotype correlations is updated with the additional human genotype correlation; f) updating the individual's gene by comparing the individual's genomic profile or a portion thereof to the additional human genotype Type correlation and determining additional genotype correlations for the individual, and g) providing the individual or the individual's health care manager with the results of the update of the individual's genotype correlation. Another sadness of this month is a method of generating an phenotypic profile of an individual comprising: a) providing a rule set containing rules, each rule indicating a correlation between at least one genotype and at least one phenotype , b) providing a data set comprising a genomic profile for each of the plurality of individuals 127264.doc 200847056, wherein each genomic profile comprises a plurality of genes M; e) periodically updating the rule set with at least a new rule' Wherein the at least one new rule indicates a correlation between genotypes and phenotypes that were not previously related to each other in the set of rules; d) applying a per-new rule to the genomic profile of at least one of the individuals, Thereby at least one genotype of the individual is associated with at least one phenotype and, depending on the situation e), a report containing the phenotypic profile of the individual is generated. This month also provides a system that includes a) a set of rules containing rules, each rule indicating a correlation between at least one genotype and at least one phenotype, and b) periodically using at least a new rule Updating the dynasty of the rule set, wherein the at least one new rule indicates a correlation between a genotype and a phenotype that were not previously related to each other in the rule set; c) a database containing a genomic profile of the plurality of individuals d) a code that applies the rule set to the genomic profiles of the individuals to determine the phenotypic profiles of the individuals; and 代码 generates a code for each individual's report. Another aspect of the present invention is to transmit the method and system described above via a network in a secure or non-secure manner. All publications and patent applications mentioned in this specification are hereby incorporated by reference in their entirety in the extent of the the the the the the The way it is incorporated into the general. [Embodiment] The present invention provides for generating a table genomic profile based on an individual or an individual group to generate a table </ br> and for easily based on the stored genomic profile. 127264.doc 200847056

Methods and systems for generating raw and updated phenotypic profiles. Genomic profiles are generated by determining genotypes from biological samples obtained from individuals. A biological sample obtained from an individual can be any sample from which a genetic sample can be obtained. The sample may be from a buccal swab, saliva, blood, hair or any other type of tissue sample followed by a biological sample to determine the genotype. The genotype can be any genetic k allogeneic or biomarker, such as a single nucleotide polymorphism (SNps), a haplotypes, or a sequence of genomes. The genotype can be the entire gene, and sequence of the individual. Genotypes can be analyzed by high yields that produce thousands or millions of data points, such as for microarray analysis of most or all known SNp. In other embodiments, the genotype can also be determined by high yield sequencing. The genotype forms the genomic profile of the individual. The genomic profile is stored in a digital manner and is readily accessible at any time to produce a phenotypic profile. A phenotypic profile is generated by applying rules that correlate or correlate genotypes with phenotypes. The rules can be based on scientific studies that demonstrate the correlation between genotype and phenotype. Relevance can be verified or confirmed by a committee of one or more experts. The association between an individual's genotype and phenotype can be determined by applying the rules to the individual's genomic profile. The phenotypic profile of the individual will have this determination. The determination can be a positive burial between the genotype of the individual and a given phenotype such that the individual has a given phenotype or will produce the phenotype. Alternatively, it can be determined that the individual does not have or does not produce a phenotype. In other embodiments, the determination may be a risk factor 'estimation or likelihood that the individual has or will produce a phenotype. The decision can be based on a number of (4) generations, and the complex number of filaments can be applied to the genome set to correlate the genotype of the individual with a particular phenotype. Judgment can also be specific to individuals, such as race, gender, lifestyle 127264.doc 200847056 (eg diet and exercise habits), age, environment (eg living place), family slave history, personal medical history and other known Phenotype. Specific factors Existing rules are achieved by including these factors. Alternatively, independent rules: hunting such factors are generated and should be phenotyped after the existing rules have been applied. (b) Edition &lt;^ Type may include any measurable trait or characteristic, such as psychology for a particular disease: or response to a pharmaceutical treatment'. Other phenotypes that may be included are the body and two such as height, weight, coat color, eye color, tanning sensitivity, memory, intelligence, optimism, and general factors. The phenotype may also include genetic comparisons with other individuals or organisms. For example, an individual may be interested in similar sensitivities between his or her genomic profile and a celebrity's genomic profile. It can also compare its genomic profile to other organisms such as bacteria, plants or other animals. At the same time, the set of related phenotypes of the individuals determined comprises the phenotypic profile of the individual. The phenotypic profile can be accessed via an online portal. Alternatively, when the phenotypic profile is present at a particular time, it can be provided in paper form, and subsequent updates are also provided in paper form. The phenotypic profile can also be provided by online people. This online entry can be viewed as a secure online entry. The user may be provided with access to a phenotypic profile for the process of generating a correlation between phenotype and genotype, determining the genomic profile of the individual, applying the rules to the genomic profile, and generating an phenotypic profile of the individual The individual serving. It may also provide access to non-users, which may have limited access to their phenotypic profiles and/or reports, or may have an initial report or phenotypic profile that may result in a death, but the updated report will only be available upon purchase. Produced afterwards. Health care such as caregivers, physicians and genetic counselors 127264.doc 200847056 Managers and providers can also access phenotypic profiles. In another aspect of the invention, user and non-use profiles can be generated and stored in a digital manner, but phenotypic profiles and reports are limited to the user. In another variation, the field “u prefetched” both the household and the non-user can access the genotype and phenotypic profile, but for the limited access, or limited Reporting, and the user has full access and can have the generated money. In another embodiment, both the user and the non-user

Initial access can be full, or all initial reports, but only the user can access the update report based on the stored genomic profile. In another aspect of the invention, information relating to the association of a plurality of genetic markers with one or more diseases or conditions is combined and analyzed to produce a Genetic Composite Index (GCI) score. This score has a known risk factor, as well as other information and assumptions, such as the frequency of the dual gene and the prevalence of the disease. GCI can be used to quantitatively estimate the association of a disease or condition with the combined effect of a genetic marker set. The GCI score can be used to provide a person who is not trained in genetics with a reliable (ie, stable), understandable, and/or intuitive meaning based on the current scientific study of the risk of the disease (4) and the relevant group. GCI scores can be used to generate GCI Plus scores. The GCI Plu_ score may contain all (10) assumptions, including the risk of the condition (such as the risk of life), age-limited prevalence, and/or age-limited morbidity. The life risk of the individual can then be calculated as the Gd P1US score, which is divided by the individual's GCI score divided by the average Gci score. The average GCI score can be determined from a group of individuals with similar ancestral backgrounds, such as a group of Caucasians, Asians, East Indians, or another group of individuals with a common ancestor background. Each group can include at least 5, 15, 15, 2, 25, 3, 127, 264.doc -11 - 200847056 35, 40, 45, 50, 55 or 60 individuals. In some embodiments, the average value can be determined from at least 75, 80, 95, or 1 individual. The GCI Plus score can be determined by determining the individual's GCI score, dividing the GCI score by the average relative risk and multiplying the risk of life by the condition or phenotype. For example, the information from Figure 22 and/or Figure 25 and the information in Figure 24 are used to calculate a GCI Plus score such as that in Figure 19. The present invention encompasses the use of GCI scores as described herein, and general techniques

It will be readily appreciated that the GCI Plus score or variant thereof can be used in place of the GCI score as described herein. In the case of the spirit, two diseases are produced for the disease or condition of the mother. These GCHf scores can be collected to form an individual's risk profile. . Ten knives can be stored in a digital way so that they are easily accessible at any time to create a dangerous profile. Risk profiles can be classified by a wide range of disease types, such as cancer, heart disease, metabolic disorders, psychiatric disorders, bone disorders or senile episodes. A wide range of disease types can be further divided into sub-categories. For example, t, for a wide variety of cancers, may list subtypes of cancer, such as by type (sarcoma, carcinoma or leukemia, etc.) or by tissue specificity (back, breast, egg)

Nest, testis, prostate, bone, lymph nodes, adrenal gland, esophagus P brain, lung, kidney, etc.). In another embodiment, the individual's GCI score is generated, which is an easy-to-understand information that the individual suffers from at least one disease or disease "f": a risk of sensibility. In a real = or = = disease or condition A plurality of (10) scores are generated. In another embodiment, the dream, the entrance access is at least one (10) score. Or, at least one (10) 127264.doc -12-200847056 2 can be provided in paper form. Provided in paper form. In the example, 'Xiao user provides at least one Gci score access, the user is the individual who subscribes to the service. In the implementation of the ## generation, the (4) households provide access, which can be subject to Access to at least one of its GCI scores, or it may have an initial report on at least one of the (10) scores it generates, but the update report will only be generated after the purchase is scheduled. In another embodiment

Health care managers and providers such as caregivers, physicians, and genetic counselors may also access at least one of the individual GCI scores. There may also be a basic reservation mode. The base schedule provides a phenotypic profile in which the user can choose to apply all existing rules to their genomic profile, or apply a subset of existing rules to their genomic profile. For example, it may choose to apply only rules to a working disease phenotype. The base reservation can have different levels in the predetermined category. For example, different levels of visual user need to be related to the number of phenotypes associated with their genomic profile or the number of people who can access their phenotypic profile. Another level of underlying planning may incorporate factors specific to the individual such as a known phenotype (such as age, gender, or medical history) into their phenotypic profile. A further level of base reservation may allow an individual to generate at least one GCI score for a disease or condition. If there is any change in at least one GCI score due to a change in the analysis used to generate the at least one GCI score, then a variation of this level may further allow the individual to account for at least one GCI score of the disease or condition to be produced. Automatic update. In some embodiments, the individual may be automatically updated by email, voice message, message, post or fax. Users can also generate reports with their phenotypic profiles and information about phenotypes (see 127264.doc -13 - 200847056 for phenotypic genetic and medical information). For example, the prevalence of population T phenotypes, genetic variants for correlation, knife mechanisms that cause phenotypes, therapies for phenotypes, therapeutic options for phenotypes, and preventive effects can be included in the report. In other embodiments, the report may also include information such as the similarity between a genotype of a scorpion and a genotype such as a celebrity or other famous person. Information about similarity may (without limitation) percentage of homology, number of identical variants, and possibly a phenotype. These reports may further contain at least one (10) score.

On the right-hand access report, the report can also provide links to other sites with other phenotypes of the phenotype, to online support groups and messages for people with the same phenotype or one or more similar phenotypes. The link to the board leads to the link of an online genetic counselor or physician, or to a telephone or personally arrange a link to a genetic counselor or physician. If the report is in paper form, the information may be the site location of the above link, or the genetic counselor or physician's phone number and the landlord user may also choose which phenotype to include in their phenotypic profile and what to include in their report News. Phenotypic profiles and reports can also be accessed by an individual's health care provider or provider, such as a caregiver, physician, psychiatry, psychologist, therapist, or genetic counselor. The user may be able to select whether the phenotypic profile and the sigma or portion thereof are accessed by the individual's health care manager or provider. The present invention also includes the preferred. This is intended to be an initial phenotypic profile and a reporting digital approach to maintaining its genomic profile. :: Users provide an opportunity to generate phenotypes with relevance from the latest research updates. In another embodiment, the user has the opportunity to generate a hazard profile and report with the relevance of new research updates from 127264.doc -14-200847056. When investigating new correlations between genotypes and phenotypes, diseases or conditions, new rules will be generated based on these new correlations and they can be applied to stored and maintained genomic profiles. The new rules can correlate genotypes that were not previously associated with any phenotype, correlate genotypes with new phenotypes, or provide an existing correlation based on genotypes and disease or condition to regulate GCI. The benchmark for scoring. The user may be informed of new relevance via email or other electronic means, and if the phenotype is of interest, it may choose to update its phenotypic profile with the new relevant φ. The user can select a reservation, which is an unlimited update payment for each update, multiple updates, or a specified time period (e.g., 3 months, 6 months, or 1 year). Another predetermined level may be that the user automatically updates his phenotypic profile or risk profile whenever a new rule is generated based on the new correlation, in lieu of the individual selection time to update its phenotypic profile or risk profile. In another aspect of the schedule, the user may direct the non-user to use rules that produce a correlation between the phenotype and the genotype, determine the genomic profile of the individual, apply the rules to the genomic profile, and generate an individual's phenotype Overview _ service. The user's guidance can be used to give the user a reservation or upgrade their existing discounted price. The directed individual may have free access for a limited time or have a discounted predetermined price. It can produce phenotypic profiles and reports as well as hazard profiles and reports for humans and non-human individuals. For example, an individual can include other mammals such as cows, horses, sheep, dogs or cats. A user as used herein is a human individual who subscribes to a service by purchasing or paying for one or more services. The service may include, but is not limited to, one or more of the following services: determine its or another 127264.doc -15- 200847056 genomic profile of a body (such as a child or pet of a user), obtain a phenotypic profile, update the form Profile overview, and reports based on their genomic and phenotypic profiles. In another aspect of the invention, a &quot;regional blending&quot; mechanism can be brought together from an individual to produce an individual's phenotypic profile. In a preferred embodiment, the individual can have an initial phenotypic profile generated based on genetic information. For example, generating an initial phenotypic profile including risk factors for different phenotypes and suggested therapeutic or preventive measures. For example, the profile may include information about available medications for a particular condition and/or about dietary changes Or recommendations for exercise therapy. Individuals may choose to visit a physician or genetic counselor or contact a physician or genetic counselor via a web portal or telephone to discuss their phenotypic profile. Individuals may decide to adopt amnesty action plans, such as using specific medications, changing them. Diet, etc. The individual can then submit a biological sample to assess changes in his physical condition and possible changes in risk factors. The individual can submit the biological sample directly to the facility (or associated facility that produces the genomic profile and phenotypic profile, such as Judging by the organization that generates the genetic profile and phenotypic profile and the contract with us Change. Or, an individual can use, a regional blending &quot; mechanism in which an individual can submit their saliva, blood, or other biological sample to a detection device in their home, analyze it by a third party, and transmit the data to Into another phenotypic profile. For example, an individual may receive an initial phenotypic report based on genetic data that reports an individual's increased risk of life-threatening myocardial infarction (MI). The report may also have preventive measures for reducing MI risk. Recommendations, such as cholesterol-lowering drugs and diet changes. Individuals can choose to contact a genetic counselor or physician to discuss the report and preventive measures and decide to change their diet. 127264.doc -16 - 200847056 After using the new drink, Individuals can visit their private physician to measure their cholesterol levels. 1. New information (cholesterol levels) can be transmitted (eg via the Internet) to organizations that have genomic information, and new information can be used to generate an individual's new phenotypic profile, and New risk factors for myocardial infarction and/or other conditions. Individuals may also use "regional blending, mechanisms or direct mechanisms to Determine the individual's response to specific drug therapy. For example, an individual can measure their response to an agent and can use information to determine a more effective treatment. Measurable information includes, but is not limited to, metabolite content, glucose content, ion content (eg, mom, sodium, potassium, iron), vitamins, blood cell count, body mass index (BMI), protein content, transcript content, The heart rate, etc., can be determined by a readily available method and can be used as a factor in the algorithm to combine with the initial genomic profile to determine the improved overall risk estimate score. "DNA sample" means any biological sample that can be isolated from an individual, including samples from which the genetic material can be isolated. As used herein, "genetic sample" refers to DNA obtained from or derived from an individual and/or Or RNA. As used herein, the term "genome" is intended to mean all complements of chromosomal DNA found in the human nucleus. The term "genomic DNA" refers to one or more chromosomal DNA molecules naturally present in the nucleus of a human, or a portion of a chromosomal DNA molecule. The term "genome profile" refers to a collection of information about an individual's genes, such as the presence or absence of a particular SNP or mutation. The genomic profile includes the genotype of the individual. The genomic profile can also be substantially the complete genomic sequence of the individual. In some embodiments, the genomic profile can be a complete genomic sequence of an individual of at least 60%, 80%, or 95〇/〇 127264.doc • 17- 200847056. The genomic profile can be about i〇〇% of the individual's whole genome sequence. Reference to a genomic profile, and a portion thereof, refers to a genomic profile of a subset of the genome profile of the entire genome. The term "genotype" refers to the specific genetic composition of an individual. Genotypes can include genetic variants and markers of an individual. Genetic markers and variants can include nucleotide repeats, nucleotide insertions, nucleotide deletions, chromosomal translocations, chromosomal duplications, or copy number variations. Replica variation can include microsatellite repeats, nucleotide repeats, centromeric repeats, or telomere repeats. Genotypes can also be SNPs, hapl〇types or dipl〇types. A single type can refer to a locus or a dual gene. A single type is also a set of statistically related single nucleotide polymorphisms (SNPs) on a single chromatogram. A double type is a single type. The term single nucleotide polymorphism or &quot;SNP&quot; refers to a specific locus on a chromosome that exhibits variability in the identity of a nitrogenous base relative to the locus present in the locus of the human population, such as at least One percent (1%). For example, when a body may have adenosine (A) at a particular nucleotide position of a given gene, the other may have cytosine (c), guanine (G), or thymine at this position. (T), so that SNp exists at this particular location. As used herein, the term &quot;SNP genomic profile&quot; refers to the base content of a given individual's DNA at the SNp site throughout the entire genomic DNA sequence of the individual. &quot;SNP Profile&quot; may refer to an entire genomic profile, or may refer to a portion thereof, such as a more localized SNP profile that may be associated with a particular gene or set of genes. The term &quot;phenotype&quot; is used to describe a quantitative trait or characteristic of an individual. Phenotypes include 127264.doc -18- 200847056 (but not limited to) medical and non-pathological conditions including diseases and conditions. The phenotype may also include physical traits such as coat color; physiological traits such as vital capacity; heart, rationality such as memory force; emotional traits such as ability to control anger; race, such as ethnic background; family tree, such as the birthplace of an individual; And age, such as the age of expectation or the starting age of a different phenotype. The phenotype may also be a single base _ 'where it is considered that one gene may be associated with a phenotype; or a multi-gene, wherein more than one gene is associated with a phenotype. &quot;rules&quot; are used to define the correlation between genotype and phenotype. Rules can define dependencies by numerical values, such as by percentage, risk factor, or trust score. Rules can have a correlation between multiple genotypes and phenotypes. &quot;rule set&quot; contains more than one rule. The "new rule" may be a rule indicating the correlation between genotype and phenotype, for which there is currently no rule. The new rules can make irrelevant genotypes related to phenotypes. The new rules can also correlate genotypes that have been associated with phenotypes with phenotypes that have not previously been associated with them. &quot;New Rule&quot; may also be an existing rule that is modified by including another rule. Existing rules may be due to known characteristics of the individual (such as race, genealogy, geography, gender, age, family history, or other prior judgments). The phenotype is improved. The use of "genotype-related" in this context refers to the statistical correlation between the genotypes of individuals (such as the presence of specific mutations), and tends to be like a specific disease. / or the likelihood of a phenotype of a mental state. The extent to which the frequency of a particular phenotype is determined in a particular genotype determines the likelihood of a genotype correlation or a particular phenotype. For example, as detailed herein, The production of lipoproteins with isoforms of SNPs is associated with an early onset of 127264.doc -19·200847056 Alzheimer's disease. Genotype correlation may also refer to a phenotype that does not tend to Correlation, or negative correlation. Genotype correlation may also indicate an individual having a phenotype or an estimate of a phenotype. Genotype correlation may be represented by a numerical value, such as a percentage, Relative risk factor, effect estimation, or trust scoring. The term &quot; phenotypic profile π refers to a collection of phenotypes associated with an individual's genotype. The phenotypic profile may include applying one or more rules to the genome. Information generated by the profile, or information about the genotype correlation applied to the genome profile. The phenotypic profile can be generated by applying rules that relate a plurality of genotypes to the phenotype. The likelihood or estimate can be numerically represented, such as Percentage, numerical hazard factor or numerical confidence interval. Probability can also be expressed in high, medium or low. The phenotypic profile can also indicate the presence or absence of a phenotype or the risk of producing a phenotype. For example, a phenotypic profile can indicate The presence of blue eyes, or a high risk of developing diabetes. The phenotypic profile may also indicate the predicted prognosis, the effectiveness of the treatment, or the response to treatment of the medical condition. The risk profile refers to more than one disease or condition. A collection of 〇(::1 scores. The GCI score is based on an analysis of the association between an individual's genotype and one or more diseases or conditions. GCI scores grouped by disease type. In addition, the hazard profile can show information about how GCI scores are predicted when adjusting individual age or various risk factors. For example, GCI scores for specific diseases can be considered for dietary changes or The effects of precautions (no smoking, medication, bilateral radical mastectomy, hysterectomy). GCI scores can be displayed numerically, graphically, audibly, or any combination of the foregoing. 127264.doc -20 - 200847056 As used herein, the term "online entry" refers to a source of information that can be easily accessed by an individual via the use of a computer and internet website, telephone or other means of accessing similar information. The online portal can be kept confidential. A website that provides links to other confidential and non-confidential websites, such as a confidential website that has an individual phenotypic profile, or a chain of non-secure websites that serve message boards for individuals sharing a particular phenotype. road.

The practice of the present invention may employ, unless otherwise indicated, conventional techniques and descriptions of molecular biology, cell biology, biochemistry, and immunology, which are within the skill of those skilled in the art. Such conventional techniques include nucleic acid isolation, polymer array synthesis, hybridization, ligation, and the use of marker detection hybridization. Specific instructions for suitable techniques are exemplified and referenced herein. However, other equivalent conventional procedures can also be used. Other prior art techniques and descriptions can be found in standard laboratory manuals and textbooks such as Genome Analysis: A Laboratory Manual Series (Vol. I-IV), PCR Primer: A Laboratory Manual 'Molecular Cloning: A Laboratory Manual (all from Cold Spring) Harbor Laboratory Press); Stryer, L. (1995) Biochemistry (4th Edition) Freeman, New York; Gait, &quot;Oligonucleotide Synthesis: A Practical Approach&quot; 1984, IRL Press, London, Nelson and Cox (2000); Lehninger, Principles of Biochemistry, 3rd edition, WH Freeman Pub, New York, Ν·Υ.; and Berg et al. (2002) Biochemistry, 5th edition, WH Freeman Pub., New York, Ν·Υ., all literature It is incorporated herein by reference in its entirety for all purposes. The method of the invention comprises analyzing an individual's genomic profile to provide the individual with molecular information about the phenotype 127264.doc -21 - 200847056. As detailed herein, the individual provides a genetic sample from which a personal genomic profile is generated. The profile information is queried for genotype correlation by comparing the individual's genomic profile against a database of established and confirmed human genotype correlations. A database of established and confirmed genotype correlations can be obtained from peer review literature and further judged by one or more experts in the field (such as geneticists, epidemiologists or statisticians) and authenticating. In a preferred embodiment, rules are generated based on the genotype correlation of the validation and applied to the genomic profile of the individual to generate a phenotypic profile. An individual or individual health care provider is provided with an individual's genomic profile, phenotypic profile analysis results, and explanations and supporting information to permit individualized selection of individual health care. The method of the present invention is detailed in Figure 1, wherein the genomic profile of the individual is first generated. The individual's genomic profile will contain information about individual genes based on genetic variation or labeling. Genetic variation is the genotype that makes up the genome profile. Such genetic variations or markers include, but are not limited to, single nucleotide polymorphisms, single nucleotide and/or polynucleotide repeats, single nucleotide and/or polynucleoside 1 deletions, and secret hygienic repeats (typical) 5_丨, a small number of nucleotide repeats of 0 (8) repeating units), dinucleotide repeats, trinucleotide repeats, sequence rearrangements (including translocations and replication), number of replicas (loss and increase in specific loci) ) and its analogues. Other genetic variations include chromosomal replication and translocation as well as centromere and telomere repeats. Genotypes can also include both single and double types. In some embodiments, the genomic profile can have at least 100,000, 300 000, 5 〇〇 or 1 〇〇〇 127 127264.doc • 22· 200847056 genotype. In some embodiments, the genomic profile can be substantially 70 positive bases, and sequences of the individual. In other embodiments, the genomic profile is at least 60% '80% or 95% of the individual's complete genomic sequence. The group profile can be a complete genome sequence of approximately 100% of individuals. Contains the genetics of the target. π includes, but is not limited to, unamplified genomic DNA or sample or amplified DNA (or cDNA). Such targets may be specific regions of the genomic marker that are of particular interest to the genomic DNA. In step 102 of Figure 1, the genetic sample of the individual is removed from the biological sample of the individual, including, but not limited to, blood, hair, skin, saliva, semen, urine, fecal matter, sweat, Oral and various body tissues. In some embodiments, the tissue sample can be collected directly by the individual, for example, the oral sample can be obtained by the individual using the swab against the inside of the cheek to obtain other samples such as saliva, semen, urine, fecal matter or sweat. The individual supplies itself. Other biological samples may be collected by a health care professional such as a blood draw, a nurse, or a physician. For example, a blood sample can be withdrawn from the individual by a shy. Tissue biopsy can be performed by a health care specialist, and health care professionals can also use kits to effectively obtain samples. The small columnar skin can be removed or a small sample of tissue or fluid can be removed using a needle. In these examples, the individual is provided with a kit of sample collection containers for biological samples of the individual. The kit also provides instructions for the individual to collect their own samples directly, such as how much hair is provided, urine 'sweat or saliva. The kit may also contain instructions for the individual's tissue samples to be collected by a health care professional. The kit can include a portion of the sample that can be collected by a third party, for example, a kit can be provided to a health care facility that then collects samples from the individual. The set 127264.doc -23- 200847056 may also provide a recycled package for the sample sent to the sample processing facility, wherein the genetic material is separated from the biological sample in step 104. Genetic samples of DNA or RNA can be isolated from biological samples according to any of a number of well known biochemical and molecular biological methods, see, for example, Sambrook, et al, Molecular Cloning: A Laboratory Manual (Cold Spring Harbor Laboratory, New York) ) (1989). There are also several commercially available kits and reagents for isolating DNA or RNA from biological samples, such as those available from DNA Genotek, Gentra Systems, Qiagen, Ambion, and other suppliers. Oral sample kits are readily available commercially, such as the MasterAmpTM Buccal Swab DNA extraction kit from Epicentre Biotechnologies, the same for kits for extracting DNA from blood samples, such as Extract from Sigma Aldrich. N-AmpTM. DNA from other tissues can be obtained by digesting tissue with a protease and heating, centrifuging the sample, and extracting the unwanted substance with phenol-chloroform to leave DNA in the aqueous phase. The DNA can then be further separated by ethanol precipitation. In a preferred embodiment, genomic DNA is isolated from saliva. For example, individuals can collect saliva samples for clinical treatment using the DNA self collection kit technology available from DNA Genotek. Samples can be conveniently stored and transported at room temperature. After the sample is passed to the appropriate laboratory for processing, the DNA is isolated by heat denaturation of the sample and protease digestion at 50 °C using reagents supplied by the collection kit supplier for at least one hour. The sample was then centrifuged and the supernatant was precipitated with ethanol. The DNA pellet was suspended in a buffer suitable for subsequent analysis. 127264.doc • 24-20084756 In another embodiment, RNA can be used as a genetic sample. In particular, genetic variants that are expressed can be identified from mRNA. The term "information RNA" or &quot;mRNA&quot; includes, but is not limited to, pre-mRNA transcripts, transcript processing intermediates, mature mRNAs and gene transcripts to be translated, or nucleic acids derived from mRNA transcripts. Transcript processing can include splicing, editing, and degradation. As used herein, a nucleic acid derived from an mRNA transcript refers to the following nucleic acid. For its synthesis, the mRNA transcript or a subsequence thereof is ultimately used as a template. Therefore, cDNA reverse-transcribed from mRNA, DNA amplified from cDNA, RNA transcribed from amplified DNA, and the like are derived from mRNA transcripts. RNA can be isolated from any of a number of body tissues using methods known in the art, such as separation of unfractionated whole blood using the PAXgeneTM Blood RNA System available from PreAnalytiX. Typically mRNA will be used to reverse transcribe cDNA, which will then be used for genetic variation analysis or amplification for gene variation analysis. Prior to genomic profiling, genetic samples were either reverse transcribed from free RNA or cDNA amplified. DNA can be amplified by a number of methods, many of which employ PCR. See, for example, PCR Technology: Principles and Applications for DNA Amplification (HA Erlich, ed., Freeman Press, NY, NY, 1992); PCR Protocols: A Guide to Methods and Applications (Innis et al., Academic Press, San Diego, Calif) , 1990); Mattila et al, Nucleic Acids Res. 19, 4967 (1991); Eckert et al, PCR Methods and Applications 1, 17 (1991); PCR (McPherson et al., IRL Press, Oxford); Patent Nos. 4,683,202, 127, 264, doc-25-2008-470,056, 4, 683, 195, 4,800, 159, 4, 965, 188, and 5, 333, 675, each incorporated herein by reference in its entirety Used for all purposes. Other suitable amplification methods include ligase chain reaction (LCR) (e.g., Wu and Wallace, Genomics 4, 560 (1989), Landegren et al, Science 241, 1077 (1988) and Barringer et al. Gene 89: 117 (1990). )), transcriptional amplification (especially deadd S (5: &quot;73-&quot; 77 (79) and WO88/10315), self-sustaining sequence replication {Guatelli et al, Proc· Nat, Acad·Sci. USA, 87 : 1874, 1 gjg other than W and W090/06995), selective amplification of target polynucleotide sequence d national patent No. 6,410,276), consensus sequence primer polymerase chain reaction PCR) (US Patent No. 4,437,975), random Primer polymerase chain reaction (AP-PCR) (U.S. Patent Nos. 5,413,909, 5,861,245), nucleic acid based sequence amplification (NABSA), rolling circle amplification (RCA), multiple displacement amplification (]\40 (US Patent Nos. 6,124,120 and 6,323,009) and ring-to-loop amplification (C2CA) (Dahl et al. Proc. Natl, Acad. Sci 101:4548 4553. (See U.S. Patent No. 5,409,818) , 5, 554, 5 17 and 6,063, 603, each of which is incorporated herein by reference. The method of amplifying is described in U.S. Patent Nos. 5,242,794, 5,494,810, 5,409,818, 4,988,617, 6,063,603 and 5,554,517, and U.S. Patent No. 09/854,317, each of which is incorporated by reference. Incorporation into this t uses one of several methods to perform the generation of genomic profiles in step 106, 127264.doc -26-200847056. Several methods are known in the art for identifying genetic variations, and include (but are not limited to) DNA sequencing, PCR-based methods, fragment length polymorphism assays (restriction fragment length polymorphism (RFLP), cleavage fragment length polymorphism (CFLP)), by any of several methods, Hybridization method using a dual gene-specific priming acid as a template (for example, TaqMan PCR method, invader method, DNA wafer method), method using primer extension reaction, mass spectrometry (MALDI-TOF/MS method), and the like In one embodiment, high density DNA arrays are used for SNP identification and profile generation. The arrays are commercially available from Affymetrix and Illumina (see Affymetrix GeneChip®). 500K Assay Manual, Affymetrix, Santa Clara, CA (incorporated by reference); Sentrix® humanHap650Y genotype analysis microbead wafer, Illumina, San Diego, CA)

For example, SNP profiles can be generated by genotyping more than 900,000 SNPs using the Affymetrix Genome Wide Human SNP Array 6.0. Alternatively, more than 50,000,000 SNPs analyzed via whole genome sampling can be determined by using the Affymetrix GeneChip Human Mapping 500K array set. In these assays, a single primer amplification reaction is used to amplify a subset of the human genome using restriction enzyme digestion, ligated human genomic DNA. As shown in Figure 2, the concentration of the ligated DNA can then be determined. The amplification is then broken and the quality of the sample is determined, followed by step 106. If the sample meets the PCR and fragmentation criteria, the sample is denatured, labeled, and then hybridized to a microarray consisting of small DNA probes at specific locations on the coated quartz surface. The amount of the marker associated with the amplified probe DNA 127264.doc -27- 200847056 is monitored to generate sequence information and the resulting SNP genotype analysis. Use the Affymetrix Gene Chip 50 OK Assay according to the manufacturer's instructions. Briefly, the isolated genomic DNA is first digested with NspI or Styl restriction endonuclease. The digested DNA is then ligated with NspI or Styl adapter oligonucleotides ligated to either NspI or Styl restriction DNA, respectively. The DNA containing the adaptor is ligated by PCR followed by amplification to generate an amplified DNA fragment between about 200 and 1100 base pairs (as evidenced by gel electrophoresis). The PCR product that meets the amplification criteria is purified and quantified for fragmentation. The PCR product was cleaved with DNase I for optimal DNA wafer hybridization. After cleavage, as confirmed by gel electrophoresis, the DNA fragment should be less than 250 base pairs and average about 180 base pairs. A terminal deoxynucleotidyl transferase is then used to label the sample that meets the fragmentation criteria with the biotin compound. The labeled fragments were then denatured and then hybridized into a GeneChip 250K array. After hybridization, the array was stained and subsequently scanned in a three-step method consisting of: streptavidin (S APE) staining followed by biotinylated anti-anti-streptavidin antibody (goat) The antibody amplification step, and finally stained with streptavidin (SAPE). After the labeling, the array is covered with an array of storage buffers and then scanned with a scanner such as the Affymetrix GeneChip Scanner 3000. As shown in Figure 3, after scanning, the Affymetrix GeneChip Human Mapping 500K Array Set was analyzed according to the manufacturer's guidelines. In short, use the gene chip operating software (GeneChip 127264.doc -28 - 200847056

Operating Software, GCOS) to obtain the original data. Information can also be obtained using the Affymetrix GeneChip Command ConsoleTM. The original data was obtained and analyzed by GeneChip Genotyping Analysis Software (GTYPE). For the purposes of the present invention, samples having a GTYPE interpretation rate of less than 80% are excluded. The samples were then analyzed using the BRLMM and/or SNiPer algorithm. Samples with a BRLMM interpretation rate of less than 95% or a SNiPer interpretation rate of less than 98% were excluded. Finally, correlation analysis was performed and samples with a SNiPer quality index of less than 0.45 and/or a Hardy-Weinberg p value of less than 0.00001 were excluded. In addition to DNA microarray analysis or in addition to DNA microarray analysis, genetic variation such as SNPs and mutations can be detected by DNA sequencing. DNA sequencing can also be used to sequence a substantial portion of an individual or an entire genomic sequence. Traditionally, common DNA sequencing has been based on polyacrylamide gel fractionation to resolve strand termination sheets #{Sanger # Λ, Proc. Natl. Acad, Sci, USA 74: 5463-5467 (7 977)). Alternative methods have been developed and continue to be developed to increase the speed and simplicity of DNA sequencing. For example, high yield and single molecule sequencing platforms are commercially available or are being developed by 454 Life Sciences (Branford, CTK Margw/ies et al, Nature (2005) 437:376-380 (2005)); Solexa (Hayward, CA) Helicos BioSciences Corporation (Cambridge, MA) (US Application No. 11/167046, June 23, 2005) and Li-Cor Biosciences (Lincoln, NE) (US Application No. 11/118031, 2005 4) Application for the development of the 29th. After generating the genomic profile of the individual in step 106, the profile is stored in a digital method in step 108, and the profile can be stored in a secure manner using a digital method. 127264.doc -29- 200847056 存 x 细 可 袼 袼 编码 编码 编码 编码 编码 概况It is stored as part of the data set and can be stored as a database, where the genome profile can be, and the human bank can be accessed again later. The data set contains a plurality of data points, each of which is related to - individual. Each data point can have a plurality of data elements. The potted material 70 is a unique identifier for the genomic profile of the individual. - can be a $ code. The other _ poor element is genotype information, such as individual The SNP or nucleotide sequence of the soil, and the data element corresponding to the genotype information can also be included in the f-point. For example, if the genotype information includes the SNP identified by microarray analysis, then the other The data elements may include the microarray L-number SNP rs number and the polymorphic core: acid. Other data elements may be the chromosomal location of the genotype, the quality metric of the data, the original data file, and the capital Image and extraction intensity scores, such as body data, medical data, ethnicity, genealogy, geography, gender, age, family history, known phenotypes, demographics, exposure data, birth patterns, behavioral data, and other known The specific factor # of the individual of the phenotype may also be incorporated as a data element. For example, the factors may include (but are not limited to) the following factors of the individual: birthplace, parents and/or grandparents, relative genealogy, residence, Ancestors' living places, environmental conditions, known health conditions, known drug interactions, family health status, lifestyle status, diet, exercise habits, marital status, and physical measurements such as weight, height, cholesterol, heart rate, blood pressure , glucose content, and other measurements known in the art. The factors mentioned above for relatives or ancestors of the individual (such as the mother and grandparent) may also be incorporated into the phenotype or The condition determines the risk of the individual. 127264.doc -30- 200847056 Special factors can be self-investigated or self-individual health care managers The information from the “inbound” profile is then accessible and used as needed. For example, in the initial assessment of an individual's genotype correlation, the entire information of the individual will be analyzed for genotype correlation (usually spanning or SNPs or other genomic sequences taken from the entire genome.) In subsequent analyses, the entire information, or a portion thereof, can be accessed from the stored or stored genomic profile as needed or appropriate. A database of genomic profiles and genotype correlations Comparison. ^ In step 110, genotype correlation is obtained from the scientific literature. The genotype of genetic variation is determined by analyzing individual populations that have tested for the presence or absence of one or more phenotypic traits of interest and genotype profiles. Relevance. The dual gene for each genetic variation or polymorphism in the profile is then examined to determine if the presence or absence of a particular dual gene is associated with the trait of interest. Correlation can be performed by standard statistical methods and a statistically significant correlation between genetic variation and phenotypic characteristics can be indicated. For example, it can be determined that the presence of the dual gene A1 at polymorphism A is associated with heart disease. By way of further example, it may be found that the combination of the dual gene A1 at polymorphism A and the dual gene B1 at polymorphism B is associated with an increased risk of cancer. The results of the analysis can be published in peer-reviewed literature, confirmed by other research groups, and/or analyzed by experts (such as geneticists, statisticians, epidemiologists, and physicians) and can also be validated. An example of the correlation between genotype and phenotype in Figures 4, 5 and 6 'The rules to be applied to the genome profile can be based on these correlations. For example, in Figures 4A and 4B, each column corresponds to a phenotype/locus/species 127264.doc -31 - 200847056

Family 'where Figures 4C through 41 contain further information about the relevance of each of these columns. For example, in Figure 4A, as shown in the short phenotype name index of Figure 4M, the "short phenotype name" of BC is an abbreviation for breast cancer. In the genus BC-4 of the gene locus, the gene LSP1 and Breast cancer related. The published or functional SNP identified by this correlation as shown in Figure 4C is rs3817198, wherein the dangerous dual gene is disclosed as C and the non-dangerous dual gene is τ. Via the basic disclosure such as in Figures 4A to 4G The disclosure identifies open SNp and dual genes. In the example of LSPk in Figure 4E, the basic disclosure is Ε_η et al, Nature 447:713-720 (2007). Figures 22 and 25 further list correlations. And the correlation in Figure 25 can be used to calculate the individual's risk to the condition or phenotype, for example, to calculate the GCI*GCI pius score. Gci or GCI Pius scores may also have information such as the prevalence of the disease, For example, in Figure 23. Alternatively, correlation can be generated from the storage of the genomic profile. For example, an individual with a stored genomic profile can also have known phenotypic information that is also stored. Analysis of the stored genomic profile and known phenotype can be Generate genotype related! For example, 250 individuals with a stored genomic profile also have their previous diagnostic information for the diagnosis of diabetes, perform an analysis of their genome (4) and compare it to a control group of non-diabetic individuals. The individual with diabetes has a higher material than the control group with a specific genetic variant and can produce a genotype correlation between the genetic variants of the pure urinary disease. The genotype and phase of the confirmation of the type are in step 112. Based on genetic variants and specific phenotypic production rules. For example, rules can be generated based on the phenotypes listed in Table 127264.doc -32- 200847056. Based on the rules of relevance, there may be other factors, such as gender ( For example, Figure 4) or race (Figures 4 and 5) to produce an effect estimate, such as those in Figures 4 and 5. Other measurements produced by the rules may be an estimate of relative risk increase, such as in Figure 6. Effect estimates and estimates of relative risk increases can come from public documents or from published literature. Alternatively, rules can be based on self-storing genomic profiles and previously known phenotypes. Correlation. In some embodiments, the rule is based on FIG. 22 and FIG. 25 in the correlation.

In a preferred embodiment, the genetic variant will be SNp. When SNp is present at a single point earlier, individuals with a particular SNp dual gene at one site are often predictive of carrying a particular SNp dual gene at other sites. The association of SNPs with dual genes that make individuals prone to disease or condition occur via linkage disequilibrium. The non-random association of dual genes at two or more loci in the sputum is expected to be randomized in the population by recombination. Formation occurs more frequently or less frequently. Other genetic markers or variants, such as nucleonucleotide repeats or insertions, may also be in linkage disequilibrium with genetic markers that are not associated with a phenotype. Example: The nuclear #^ insertion is phenotyped and the SNp is in linkage disequilibrium with the nucleotide insertion. A rule is generated based on the correlation between the SNP and the phenotype. It is also possible to generate rules based on the correlation between nucleotide insertions 盥砉 a i . Any one or both rules can be applied to * 1 * μ; the genomic profile, because the presence of one SNP &quot;specific risk factors, the other can increase the risk when combined. In addition, another risk factor is generated and is co-segregated by a combination of a conjugated unidirectional gene and a specific pair of genomic pairs of SNPs. The SNP dual gene 127264.doc -33 · 200847056 A specific combination along a chromosome is called a haplotype, and a DNA region which exists in a combined form may be referred to as a singular segment. When a single-type segment can be composed of one SNP, the single-type segment typically represents a continuous series of two or more SNPs exhibiting low simplicial diversity between individuals and having a generally low recombination frequency. Identification of a single type can be performed by identifying one or more SNPs located in a single type segment. Therefore, SNP profiles can generally be used to identify single-type segments without necessarily having to identify all SNPs in a given single-type segment. The genotype correlation between the SNP singular pattern and the disease, condition or physical state is gradually becoming known. For a given disease, a single-type pattern of a group known to have one of the diseases is compared to a group without the disease. By analyzing a number of individuals, the frequency of polymorphisms in the population can be determined, and then such frequencies or genotypes can be associated with a particular phenotype such as a disease or condition. Examples of known SNP-disease correlations include polymorphisms in complement factor Η in age-related macular degeneration (ταβίπ#乂, Sc/wce/ 3(10): 355-35 (2005)) and INSIG2 associated with obesity. The SNP correlation of variants near the gene includes polymorphisms of the 9p21 region including CDKN2 A and B, such as rsl0757274, rs2383206, rsl3333040, rs2383207, and rsl0116277 (i/e/ga^i&quot;&gt; , Science 316: 1491-1493 (2007); McPherson et al., Science 316·1488-1491 (2007)).

SNPs can be functional or non-functional. For example, functional SNPs have an effect on cellular function, thereby producing a phenotype, while non-functional SNPs have no functional effects, but are in linkage disequilibrium with functional SNPs. SNP 127264.doc •34- 200847056 may also be synonymous or non-synonymous. Synonymous SNPs are SNPs that produce the same polypeptide sequence in different forms and are non-functional SNp. If SNp produces a different polypeptide, the Bellein SNP is non-synonymous and may or may not be functional. SNp or other genetic markers used to identify singles in two or more single types can also be used to correlate the phenotype associated with the double type. Information about individual phenotypes, bitypes, and SNP profiles can be in an individual's genomic profile. In a preferred embodiment, for a rule based on a genetic marker that is in linkage disequilibrium with another genetic tag associated with a phenotype, the genetic marker can have an r2 or D greater than 0.5, scored, This technique is often used to determine the score of linkage disequilibrium. In a preferred embodiment, the score is greater than 〇6, 〇·7, 〇·8, 〇·9Ό, 0.95 or 0.99. Thus, in the present invention, the genetic marker used to correlate the phenotype with the genomic profile of the individual may be the same as or different from the phenotype of the phenotype or the published SNP. For example, using bc 4, the test SNP and the open SNP are identical, as are the test for dangerous and non-hazard dual genes that are identical to open dangerous and non-hazard dual genes (Figure 4A and Figure C). However, for BC-5, CASP8, and its association with breast cancer, the test SNP is different from its functional or open SNP, as is the testing of dangerous and non-hazardous dual genes that differ from open and non-hazardous dual genes. The test and disclosure of the dual gene is located relative to the positive strand of the genome, and from which it can be inferred to be a homozygous dangerous or non-dangerous genotype that can generate rules for the genomic profile to be applied to an individual such as a user. In some embodiments, the test SNP may not have been identified, but using published SNp information, the dual gene difference or SNp may be identified based on another assay such as TaqMan. For example, the AMD-5' disclosed SNP in Figure 25A is rsl061170, but the test $127264.doc-35-200847056 is not identified. Test SNPs can be identified by LD analysis with published SNPs. Alternatively, the test SNP may not be used, and instead TaqMan or other equivalent assays will be used to assess the genome of the individual with the test SNP. The test SNP can be a π direct &quot; or "tag&quot; SNP (Fig. 4E to Fig. 4G, Fig. 5). The direct SNP is the same test SNP as the public or functional SNP, such as for BC_4. The direct SNP can also be used for The relationship between FGFR2 and breast cancer, using SNP rs 1073640 in Europeans and Asians, where the secondary dual gene is A and other dual genes are the case, iVaiwre #7··7(10)7-70P3 (2007)). Another public or functional SNP for the association of FGFR2 with breast cancer is rsl219648, also in Europeans and Asians (//(10)(10)7. Labeled SNPs are used to test SNPs differently from functional or open SNPs, such as BC-5 The tag SNP can also be used for other genetic variants, such as for CAMTAl (rs4908449), 9p21 (rsl0757274, rs2383206, rsl3333040, rs2383207, rsl0116277), COLlAl (rsl800012), FVL (rs6025), HLA-DQAl (rs4988889, rs2588331). ), eNOS (rsl799983), MTHFR (ral801133) &amp; APC (rs289333 80) iSNP. The SNP database is publicly available, for example, from the International HapMap Project (see www_hapmap.org,

The International HapMap Consortium, Nature 426:789-796 (2003) 5 Sl The International HapMap Consortium, Nature 437:1299-1320 (2005)) &gt; A IS ^ 0 ^ ^ f # (Human Gene Mutation Database, HGMD), Open database (see www.hgmd.org) and single nucleotide polymorphism database (Single Nucleotide Polymorphism 127264.doc · 36 · 200847056 database, dbSNPV inflammation at www.ncbi.nlm.nih.gov/ sNp/). These poor stocks provide SNP single scraping, + private early or enough to determine the SNP single type mode. Therefore, these SNP databases are capable of detecting genetic risk factors for a wide range of diseases and conditions, such as cancer, fire &amp; igniting diseases, cardiovascular diseases, neurodegenerative diseases and infectious diseases. These diseases or conditions can work, and there are treatments and therapies before and after the combination. Treatment may include (iv) sexual treatment and improvement: and treatment of the condition, including lifestyle changes.

It can also be tested: such as physical traits, physiological traits, psychological traits, emotional shame, a family spectrum and many other phenotypes of age. Physical traits may include the color of the eye of the eye, the body, or the shape of the body, such as energy, endurance, and agility. The rationality may include intelligence, memory performance, or learning performance. Race and genealogy can include the identification of ancestors or races, the source of individual ancestors. The age of I can be a judgment of the true age, or (4) the genetics of /, relative to the age of the general group. For example, the true age of an individual, 38 years old, however, its genetics can be determined by its memory ability or physical health status can be an average of 28 years old. Another age trait can be the planned life of the individual. Other phenotypes may also include non-medical conditions, such as "fun" phenotypes. Such phenotypes may include comparisons with well-known individuals, such as foreign dignitaries, politicians, celebrities, inventors, athletes, musicians, artists, merchants, and infamous individuals, such as criminals. Other "fun" phenotypes may include comparisons with other organisms, such as bacteria, insects, plants, or non-human animals. For example, an individual may be interested in knowing how their genomic profile compares to their pet dog or to the genus profile of the predecessor. In step 114, the rules are applied to store the genomic profile to generate a phenotypic profile of step 127264.doc - 37 · 200847056. For example, the information in Figures 4, 5, or 6 can form a basis for rules or tests applied to an individual's genomic profile. The rules may include information about testing SNPs and dual genes, and the effect estimates of Figure 4, where the unit of effect estimation (UNITS) is the unit of effect estimation, such as OR, or the odds ratio (95% confidence interval) or average. . In a preferred embodiment, the effect estimates can be genotype risk (Fig. 4C to Fig. 4G), such as homozygous risk (homoz or RR), heterozygous heterozygotes (heteroz or RN), and non-hazard homozygotes (homoz or NN). . In other embodiments, the effect estimate may be carrier risk, which is RR or RN vs NN. In still other embodiments, the effect estimate can be based on dual gene, dual gene risk, such as r vS. N. There may also be genotype effect estimates for two loci (Fig. 4J) or three loci (Fig. 4K) (e.g., nine possible genotype combinations estimated for two locus effects and rrrr, RRNn, etc.). The test SNP frequency in the published HapMap is also indicated in Figures 4H and 41. In other embodiments, the signals from Fig. 21, Fig. 22, Fig. 23, and/or Fig. 25 can be used to generate information for the genomic profile applied to the individual. For example, Lu's poor news can be used to generate individual GCI or GCI Plus scores (eg, Figure 19). Such scores can be used to generate information about the genetic risk of one or more of the phenotypic profiles of an individual, such as an estimated life risk (e.g., Figure 15). These methods allow for the calculation of the estimated life-risk or relative hazard of one or more of the phenotypes or conditions listed in Figure 22 or Figure 25. The risk of a single condition can be based on one or more SNPs. For example, the estimated hazard of a phenotype or condition may be based on at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 SNPs, wherein the SNP used to estimate the hazard may be public SNP, test SNP or 127264.doc •38· 200847056 Both (eg Figure 25). The estimated risk of the condition can be based on the SNPs listed in Figure 22 or Figure 25. In some embodiments, the risk of a condition can be based on at least one SNP. For example, an individual's assessment of the risk of Alzheimer's disease (Alzheimers, AD), colorectal cancer (CRC), osteoarthritis (〇A), or exfoliation of glaucoma (XFG) may be based on 1 SNP ( For example, AD is rs4420638, CRC is rs6983267, OA is rs4911178 and XFG is rs2165241). For other conditions such as obesity (BMIOB), Graves disease (GD), or golden stagnation (HEM), the estimated risk for an individual may be based on at least 1 or 2 SNPs (eg, BMIOB is rs9939609) And/or rs9291171; GD is DRB1 *0301 DQA1 *0501 and / or rs3 087243; HEM is rsl800562 and / or rsl29128). For conditions such as, but not limited to, myocardial infarction (MI), multiple sclerosis (MS), or psoriasis (PS), 1, 2, or 3 SNPs can be used to assess an individual's risk of developing the condition ( For example, MI is rsl866389, rsl333049, and/or rs6922269; MS is rs6897932, rsl2722489, and/or DRB1*1501; PS is rs6859018, rsll209026, and/or HLAC*0602). For the estimated risk of an individual having Leg Leg Syndrome (RLS) or Celiac Disease (CelD),

2, 3, or 4 SNPs (for example, RLS is rs6904723, rs2300478, rsl026732, and / or rs9296249; CelD is rs6840978, rsll571315, rs2187668, and / or DQA1*0301 DQB1*0302). For prostate cancer (PC) or lupus (SLE), 1, 2, 3, 4, or 5 SNPs can be used to estimate the risk of PC or SLE in an individual (eg, PC is η4242384, rs6983267, rsl6901979, rsl7765344, and/or Rs4430796 ; SLE 127264.doc -39- 200847056

For rsl2531711, rsl0954213, rs2004640, DRB1*0301 and/or DRB1 * 1501). For estimating the life risk of an individual with macular degeneration (AMD) or rheumatoid arthritis (RA), 1, 2, 3, 4, 5 or 6 SNPs can be used (for example, AMD is rsl0737680, rsl0490924, rs541862, Rs2230199, rsl061170 and/or rs9332739; RA is rs6679677, rsll203367, rs6457617, DRB*0101, DRB1*0401 and/or DRB1*0404). 1, 2, 3, 4, 5, 6 or 7 SNPs (eg, rs3803662, rs2981582, rs4700485, rs3817198, rsl7468277, rs6721996, and/or rs3803662) may be used to estimate the life risk of an individual with breast cancer (BC). . For estimating the life risk of an individual with Crohn's disease (CD) or type 2 diabetes (T2D), 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 SNPs (eg, CD is rs2066845, rs5743293, rsl0883365, rsl7234657, rsl0210302, rs9858542, rsll805303, rsl000113, rsl7221417, rs2542151, and/or rsl0761659; T2D is rsl3266634, rs4506565 'rsl0012946, rs7756992, rsl0811661, rsl2288738, rs8050136, rsllll875, Rs4402960, rs5215 and / or rsl801282). In some embodiments, the SNP used as a benchmark for determining risk may be in linkage disequilibrium with the SNPs mentioned above or listed in Figure 22 or Figure 25. An individual's phenotypic profile can include many phenotypes. Assessing the risk of a patient suffering from a disease or other condition, such as a possible drug response (including metabolism, efficacy, and/or safety) by the method of the present invention, is particularly predictive or diagnostic for susceptibility to a variety of unrelated diseases and conditions, regardless of In individuals with symptoms, symptoms 127264.doc -40- 200847056 无 or asymptomatic, including carriers of one or more disease/disease-biased dual genes. Because &&apos; these methods provide a general assessment of an individual's susceptibility to a disease or condition without the need to test any intended concept for a particular disease or condition. For example, the methods of the present invention can assess an individual's susceptibility to any of the conditions listed in Table 4, Figure 4, Figure 5, or Figure 6 based on the genomic profile of the individual. In addition, the (iv) method can assess an individual's estimated life risk or relative risk for one or more phenotypes or conditions, such as those shown in Figure 22 or Figure 25. Preferably, the assessment provides information on two or more of these conditions, preferably 3, 4, 5, 10, 20, 50, 1 or even more of these conditions. In the preferred implementation, the profile is generated by applying at least two rules to the genome profile of the individual. In other embodiments, at least 5 rules are applied to the genomic profile of the individual. A phenotypic-rule can be applied to a single gene phenotype. More than one rule can also be applied to a single phenotype, such as a multi-gene phenotype or an early genetic phenotype, where multiple genetic variants in a single gene affect the likelihood of having the phenotype. After the initial screening of the genomic profile of the individual patient, when other nucleotide variants such as SNPS become known, the genotype correlation of the individual is performed (or obtained) by comparison with the other nucleotide acid variants Update. For example, one or more of the scientific literature for browsing the relevance of a new genotype may be performed by a technician in the field of genetics, such as daily, weekly or monthly. This new genotype correlation can then be further confirmed by one or more committees of experts in the field. Step 112 may then be periodically updated with the new rules based on the newly confirmed relevance. 127264.doc -41 - 200847056 The new rules may include genotypes or phenotypes without existing rules. For example, genotypes that are not associated with any phenotype are found to be associated with a new phenotype or an existing phenotype. The new rules can also be used to correlate previously phenotypes without genotypes associated with them. New rules can also be established for genotypes and phenotypes with existing rules. For example, there are rules based on the correlation between genotype A and phenotype A. The new study reveals that genotype B is associated with phenotype A and produces new rules based on this correlation. Another example is to find that phenotype 6 is associated with genotype A and thus can generate new rules. Rules can also be generated for findings based on known correlations but not the relevance of the initial identification in the published scientific literature. For example, the reportable genotype c is associated with phenotype C. Another publication reports that genotype D is associated with phenotype D. Phenotype C and phenotype D are related symptoms, for example, phenotype c may be shortness of breath, and phenotype D is small lung capacity. Correlation between genotype c and phenotypic D or genotype 〇 and phenotype C can be found and via existing stored genomic profiles of individuals with genotype c and genotype d and phenotype C and phenotype D Methodology or confirmation by other research. New rules can then be generated based on the correlation between new findings and confirmations. In another embodiment, a stored genomic profile of a plurality of individuals with a particular or related phenotype can be studied to determine the genotype shared by the individual and the correlation can be determined. New rules can be generated based on this correlation. Rules can also be generated to improve existing rules. For example, the correlation between genotype and phenotype can be partially paralyzed by known individual characteristics, such as race, genealogy, ethics, gender, age, family history, or the individual's The phenotype is known. Rules based on such known individual characteristics can be generated 127264.doc -42- 200847056 and incorporated into existing rules to provide improved rules. The choice of improvement rules to be applied will depend on the individual individual factors of the individual. For example, the rule may be based on the fact that the individual has a phenotype E of 35% when the individual has genotype E. However, if the individual has a specific race, the probability is 5%. Based on this result, new rules can be generated and applied to individuals with specific races. Alternatively, an existing rule determined to be 35% can be applied, and then another rule based on the phenotype is applied. Rules based on known individual characteristics can be determined from scientific literature or based on studies that store genomic profiles. When a new rule is developed, or a new rule can be applied on a regular basis (such as at least once a year), a new rule can be added and applied to the genome profile in step 1 i 4 . Information on the risk of an individual suffering from a disease can also be extended to allow for a finer analysis of the technological advances in the SNP genome profile. As indicated above, the initial SNp genome set can be easily generated using microarray technology for scanning 5 〇〇, s snp. Given the nature of the singular segment, this number takes into account the representative profile of all SNPs in the individual's genome. Despite this, it is estimated that there are usually about 10 million SNPs in the human base group (International pjapMap program; www.hapmap.org). Because technological advances allow for practical, cost-effective analysis of SNPs with finer detail levels, such as 1, 〇〇〇, 〇〇〇, 1,5 〇〇, 〇〇〇, 2,000, 〇〇〇, 3,0〇〇, 〇〇〇 or more of the state 1&gt; microarray, or the entire genome sequencing 'so can produce a more detailed SNP genomic profile. Similarly, cost-effective analysis of more detailed SNP genome profiles and updates to the master database of snp·disease correlations will be achieved through advances in computer analysis. After generating the phenotypic profile in step 116, the user or his or her health care management 127264.doc -43- 200847056 can access their genomic or phenotypic profile via an online portal or website, as in step 118. A report containing the phenotypic profile and other information related to the phenotype and genomic profile may also be provided to the user or his health care manager, as in steps 120 and 122. These reports can be printed, stored in the user's computer or viewed online. The sample line report is shown in Figure 7. Users can choose to display a single phenotype or more than one phenotype. Users can also have different viewing options, such as the "Quick View" option in Figure 7. The phenotype can be a medical condition and different treatments and symptoms in the quick report can be linked to other pages that contain additional information about the treatment. For example, by clicking on a pharmaceutical agent, it will lead to a website containing information about the dosage, cost, side effects and effectiveness. It can also compare pharmaceuticals with other treatments. The website may also contain a website to the pharmaceutical manufacturer. Another link may provide the user with a choice to generate a pharmacogenomic profile that will include information based on their genomic profile, such as it may react to the agent. Links to the surrogate may also be provided, such as Preventive behaviors such as fitness and weight loss, as well as links to dietary supplements, diet plans and links to neighbouring fitness clubs, health clinics, health providers, daily spas and the like. Education is also available. And information videos, an overview of available treatments, possible treatments and general recommendations. Online reports can also provide access to personal arrangements Physicians or genetic counseling or contact with the link of the online physician, providing the user with an opportunity to request more information about their phenotypic profile. Links to online genetic counseling and physician enquiries can also be provided in the online report. The report can also be viewed in other formats, such as 斟w as shown in the comprehensive phenotype of 127264.doc -44- 200847056, which provides more details on each type. For example, there may be a user-generated phenotype More detailed statistics on the likelihood of more typical symptoms or phenotypes, such as sample symptoms of medical conditions, or areas of non-medical conditions such as height, or more information about genes and genetic variants Such as group morbidity, for example, worldwide, or in different countries, or in different age ranges or genders. For example, Figure 5 shows an overview of the estimated lifespan risk of many conditions. Individuals can see For more information on specific conditions, such as prostate cancer (Figure 16) or Crohn's disease (Figure 17) ° In another embodiment, the report can be an "fun" table , such as the genomic profile of an individual similar to the genomic profile of a well-known individual such as Albert Einstein. The bio-report can show the similarity between the genomic profile of the individual and the genomic profile of Einstein and can further show Einstein's predictive IQ and individual predictive IQ. Other information may include the genomic profile of the general population and how its IQ is compared to the genomic profile of the individual and Einstein and its Q. In another embodiment, the report may show all tables that have been associated with the user's genomic profile. In other embodiments, the report may only display a phenotype that is positively correlated with the genomic profile of the individual. In other formats, the individual may choose to display a particular subpopulation of the phenotype, such as a medical phenotype only, or may only function The medical phenotype. For example, the functional phenotype and its associated genotypes may include Crohn's disease (associated with IL23R and CARD 15),! Type 2 diabetes (associated with HLA-DR/DQ), lupus (related to hla-DRBI), psoriasis (HLA-C), multiple sclerosis (hla_dqA1), Gracie's disease (hla_127264.doc -45- 200847056 DRB 1 Rheumatoid-like spp inflammation (HLA-DRB1), type 2 diabetes (TCF7L2), breast cancer (BRCA2), colon cancer (Apc), intermittent memory (KIBRA), and osteoporosis (C0L1A1). Individuals may also choose to display a subtype of phenotype in their reports, such as only an inflammatory disease for a medical condition, or only a physical trait for a non-medical condition. In some embodiments, the individual may choose to display all conditions by highlighting their condition (eg, Figure 15a, Figure 5D), highlighting a condition with only high risk (5) 15B), or only having a low risk. The condition (Fig. 15C) calculates the estimated risk for the individual. Information submitted and communicated to an individual by an individual may be confidential and confidential, and access to such information may be controlled by the individual. Information derived from complex genomic profiles can be provided to individuals in the form of regulatory approval, comprehensibility, medical relevance, and/or high impact leanness. Information can also be of general concern, not medically relevant. Information can be communicated confidentially to individuals in a number of ways, including (but not limited to) portal interfaces and/or emails. More preferably, the information is provided to the individual in a confidential manner (if the individual so chooses) through the portal interface, and the individual can access the information confidentially and voluntarily. The interface is preferably accessed by a wire Internet website or alternatively by means of a private, secure and easily accessible phone or other means. Provide genomic profiles, phenotypic profiles and reports to individuals or their health humiliators by transmitting data via the Internet. Thus, Figure 8 is a simplified diagram showing representative example logic devices through which phenotypic profiles and reports can be generated. Figure 8 shows a computer system (or digital device) 800 for receiving and storing genomic profiles, analyzing genotype-related soil genotype correlation analysis generation rules, applying rules to genomic profiles, and generating phenotypic profiles and reports. . The computer system 8 can be viewed as 127264.doc 46- 200847056 A logical device that can read instructions from the media 811 and/or the network 805, which can optionally be connected to the server 809 having the fixed media 8 12 . The system shown in Figure 8 includes a CPU 801, a disk drive 803, optional input devices such as a keyboard 815 and/or slippery air 816, and an optional monitor 8〇7. Data communication to a local or remote server 809 can be made via the indicated communication medium. The communication medium can include any component that transmits and/or receives data. For example, a communication medium can be a network connection, a wireless connection, or an internet connection. This connection provides communication via the World Wide Web. It is contemplated that information relating to the present invention may be transmitted via such networks or connections for receipt and/or review by the counterpart 822. The recipient 822 can be, but is not limited to, an individual, a user, a health care provider, or a health care manager. In one embodiment, the computer readable medium includes a medium suitable for transmitting the results of the analysis of the biological sample or genotype correlation. The media can include results regarding the phenotypic profile of the individual subject, wherein the results are obtained using the methods described herein. The entry point for individuals who are better served as individuals for receiving and evaluating genomic data will be sufficient for individuals to track their samples from collection to testing and results. The relative risk of a common genetic disorder based on its genomic profile is introduced to the individual via population access. The user can choose which rules to apply to their genomic profile via the portal. In one implementation, - or multiple web pages will have a phenotype list and each side of the table s can be selected in the phenotypic profile of the phenotype. The phenotype can be linked to information about the phenotype to help the user develop an informed choice about the phenotype that they need to include in their phenotypic profile. The web page may also have a phenotype grouped according to the disease group, for example, a disease that may be used by 127264.doc -47-200847056 or a disease that does not work. For example, the user can write only the phenotypes that are active = such as HLA_DQA1 and chyle. The user also has to choose to treat the symptoms before or after the symptoms. For example, an individual may choose a pre-existing phenotype for pre-symptomatic treatment (in addition to the increased screening) in the case of a pre-symptomatic treatment with no symptoms of a Chu diet. Another example may be Azhai's disease, Star (10)atin, exercise, vitamins and mental work, and symptoms. Blood stasis is another example of 'avoiding oral contraceptives and sputum 〗 〖Exemption: pre-symptomatic treatment. An example of a phenotype that is treated with approved symptoms is a wet-type AMD associated with CFH, in which an individual can obtain laser treatment for his condition. The wind phenotype can also be grouped according to the type or type of disease or condition, such as nerve killing, internal knives, immunology, and the like. Phenotypes can also be divided into medical and non-commercial phenotypes. Other subgroups of phenotypes on the web page can be classified into physical traits, rational traits, psychological traits, or emotional traits. The web page may further provide for selecting a portion of the group phenotype by selecting a box. For example, select all • Type I, medical-only phenotypes, non-medical-related phenotypes, phenotypes that only work, phenotypes that only work, different disease groups, or interesting tables in the “fun” table. Types may include comparisons with celebrities or other well-known individuals, or comparisons with other animals or even other organisms. A list of genomic profiles that can be used for comparison can also be provided on the web page to the user to select to compare with the user's esthetic profile. 1 Search engines can also be provided at the online portal to help users navigate through the portals, search for phenotypes, or search for specific terms or poor news that are revealed by their phenotypic profiles or reports. Links to access partner services and product offerings are also available on 127264.doc -48· 200847056. Other links for individuals with common or similar phenotypes to support groups, message boards, and chat rooms are also available. The online portal also provides links to other sites that have more information about the phenotype in the user's phenotype profile. Online portals also provide services that allow users to share their phenotypic profiles and reports with friends, family or health care managers. The user can choose to display the phenotype in the phenotypic profile that they want to share with their friends, family, or health care manager. Phenotypic profiles and reports provide individuals with personalized genotype correlations. The genotype correlation provided to individuals can be used to determine the choice of personal health care and lifestyle. If there is a strong correlation between genetic variants and treatable diseases, detection of genetic variants can help determine the initiation of treatment and/or individual monitoring. In the presence of a statistically significant correlation, but not as a strong correlation, an individual may review the information with an individual physician and decide on a suitably beneficial course of action. Given that a particular genotype correlation may be beneficial to an individual's possible course of action, including therapeutic treatment, monitoring the possible or therapeutic effects of the treatment, or lifestyle changes in diet, exercise, and other personal habits/activities. For example, a phenotype such as celiac disease may have a pre-symptomatic treatment of a no-fruit diet. Similarly, genotype-related information can be applied via pharmacogenomics to predict the likely response an individual will have to treatment with a particular agent or agent therapy, such as the likely efficacy or safety of a particular drug treatment. The user may choose to provide a genomic and phenotypic profile to their health care manager, such as a physician or genetic counselor. The genome and phenotypic profile can be accessed directly by the health care official, printed by the user to the health care manager, 127264.doc -49- 200847056, or via an online portal (such as the beginning of the phase, the cloth I The link on the online report) sends 1 to the health care manager. This transfer of appropriate information will allow the patient to act in concert with his or her physician. In detail, the discussion between the patient and his or her physician can be achieved through the entry and access of the individual: the link to learn information, and the storage of the patient's genomic information into their medical records: capabilities. Medical information can include prevention and health information. The information provided to individual patients by the present invention will enable patients to make informed choices about their health care. In this way, the patient will be able to make choices that can help them avoid and/or delay the disease that is more likely to occur in their individual genomic profile (hereditary DNA). In addition, patients will be able to adopt treatment options that are personally appropriate for their particular medical needs. Individuals will also have access to their ability to develop patients and need this information to help their physicians develop a genotype of poor therapeutics. Genotype-related information can also be combined with genetic counseling to suggest a spouse reconsideration and potential genetic concerns for mothers, fathers, and/or children. The Genetic Adviser can provide information and support to users with a phenotypic profile that shows an increased risk of developing a particular condition or disease. It can explain information about the condition, analyze the genetic pattern and the risk of recurrence, and review the available choices with the user. Genetic counselors can also provide supportive advice to guide users to community or national support services. It can include genetic counseling and (4) scheduled programs. In some embodiments, genetic counseling can be scheduled within 24 hours of the need and can be obtained during periods such as evening, week#, weekdays, and/or false alarms. The entrance to the individual will also help to convey additional information beyond the initial screening. Will be 127264.doc -50- 200847056

Inform individuals about new scientific findings about their individual genetic profiles, such as information about new treatment or prevention strategies for their current or underlying conditions. These new findings can also be passed to their health care managers. In a preferred embodiment, the e-mail is used to inform the user or his or her health care provider of new genotype correlations and new studies regarding the phenotype in the user's profile. In other embodiments, an &quot;fun&quot; phenotype email is sent to the user, e.g., an email can be known, and its genomic profile is consistent with Abraham Lincoln's genomic profile 7; and other information is available via the online portal. The present invention also provides a recipe for generating new rules, improving rules, combining rules, periodically updating rule sets with new rules, maintaining a genomic profile in a confidential manner, and applying the rules to a genome profile to determine a phenotypic profile. And a computer code system for generating reports. Computer code is used to inform users of new relevance or revision of relevance, new or revised rules, and new reports or revisions such as new prevention and health information, information about new treatments under development, or new available treatments. Commercial Methods The present invention provides a commercial method for assessing the genotype correlation of an individual, 'based on comparing the genomic profile of a patient relative to a clinically derived poor repository of established medically relevant genetic variants. The present invention further provides for an individual to store a genetic peak condition assessment that is not originally known for a new correlation to produce an updated phenotypic profile of the individual, without requiring the individual to: a commercial method of biological sample. A flow chart illustrating the business method is shown in Figure 9. When an individual initially needs and purchases a personalized genomic profile of many common human diseases, conditions, and genotype correlations of the body 127264.doc -51 - 200847056 state, the subject business method The revenue source portion is generated in step 101. Needed and purchased; conducted through many sources, including (but not limited to) online network population, online (4) services, and individual sources of personal physician or personal medical concern. In a second alternative embodiment, the genomic profile can be provided free of charge and a source of revenue is generated at a subsequent step (such as step 103).

The user or customer requests to purchase a phenotypic profile. In response to the need and step U) 3, a collection kit for providing biological samples for genetic sample separation is provided to the customer. When it is necessary to make an online, telephone or collection set that cannot be easily presented on the body for other sources of customers, the collection set is provided by a courier such as a courier service that is delivered on the same day or overnight. The collection kit includes - a container for the sample, and a packaging material for delivering the sample to a laboratory that produces the genomic profile. The kit may also include instructions for sending the sample to a sample processing facility or laboratory, and instructions for obtaining a genomic profile and phenotypic profile, which can be performed via an online portal. 0 As detailed above, genomic DNA Available from any of a number of types of biological samples. Preferably, genomic DNA is isolated from saliva using a commercially available collection kit such as a collection kit available from DNA Genotek. The use of saliva and the kit allows non-diffuse sample collection because the customer conveniently provides a saliva sample in the container of the collection kit and then seals the container. In addition, saliva samples can be stored and transported at room temperature. After storing the biological sample in a collection or sample container, the customer passes the sample to the laboratory for processing in step 丨〇5. Typically, customers can use the packaging materials provided in the collection kits, such as the same day or overnight delivery service, to deliver/send samples to the lab at 127264.doc -52- 200847056. Laboratories processing samples and generating genomic profiles can comply with the guidelines and requirements of appropriate government agencies. For example, in the United States, the processing laboratory may be one or more of, such as the Fosd and Drug Administration (FDA) or the Centers for Medicare and Medicaid Services (CMS). Regulatory agencies and/or one or more national agencies regulate. In the United States, clinical laboratories are accredited or approved under the 1988 Clinical Laboratory Improvement Amendments (CLIA). In step 107, the laboratory processes the previously described sample to isolate a genetic sample of DNA or RNA. Analysis of the isolated genetic samples and generation of the genomic profile are then performed in step 109. Preferably, a genomic SNP profile is generated. As mentioned above, several methods are available for generating SNP profiles. Preferably, a high density array such as that purchased from Affymetrix or Illumina is used for SNP identification and profile generation. For example, a SNP profile can be generated using the Affymetrix GeneChip assay as described in more detail above. As technology advances, there may be other technology vendors that can generate high density SNP profiles. In another embodiment, the user's genomic profile will be the user's genomic sequence. Preferably, the genotype data is translated into a code, entered in step 111, and stored in a secure database or vault in step 113, and the information is stored therein for later reference. Genomic profiles and related information can be confidential, restricting access to this private information and genome profile to 127264.doc -53- 200847056 by individuals and/or their personal physicians __ ^ can also be permitted by users such as individual families and Access by others of the genetic counselor. On the site of the room. Alternatively, 'by the processing laboratory to generate a separate database containing the database or the vault can be located in the processing experiment database can be located in a separate location. The genomic profile data in this case can be transferred to the facility in step 111.

After generating an individual's genomic profile, the genetic variation of the individual is then compared in step 115 against a clinically derived database of established medically relevant genetic variants. Alternatively, the genotype correlation may not be medically relevant, but it is still incorporated into a database of genotype correlations, such as physical traits such as eye color, or &quot; phenotypes such as similarity to celebrity genomic profiles. Medical-related SNPs may have been established by scientific literature and related sources. Non-SNP genetic variants can also be established to correlate with phenotypes. Typically, the association of a SNP with a given disease is established by comparing a single-type pattern of a group of people known to have a disease with a group without the disease. By analyzing a number of individuals, the frequency of polymorphisms in the population can be determined, and then these genotype frequencies can be associated with a particular phenotype such as a disease or condition. Alternatively, the phenotype can be a non-medical condition. The C-related SNP and non-SNP genetic variants can also be determined by analyzing the individual's stored genome profile rather than by available public literature. An individual with a stored genomic profile can reveal a previously determined phenotype. Analysis of the individual's genotype and revealed phenotype can be compared to their analysis without phenotype to determine the relevance that can then be applied to other genomic profiles. Individuals who have determined their 127264.doc -54- 200847056 genome profile can fill out a questionnaire about the phenotype of the previous shirt. The questionnaire may contain questions regarding medical and non-medical conditions such as previously diagnosed diseases, family history of medical conditions, lifestyle, physical traits, psychological traits, age, social life, environment, and the like. In one embodiment, if an individual fills in a questionnaire, they can determine their genomic profile for free. In some embodiments, the questionnaire will be periodically filled in by individuals to access their phenotypic profiles and reports for free. In other embodiments, the individual filling out the survey form may have a poorly scheduled upgrade so that it has more access than its previous predetermined level, or it may purchase or update the reservation at a reduced cost. First, in step 121, the Research/Clinical Advisory Committee approves all information stored in the database of medically relevant genetic variants for scientific accuracy and importance', if approved in step 119, combined with review by appropriate government agencies and Supervision. For example, in the United States, FDA can provide oversight by approving cold-form methods used to identify genetic variants (usually SNPs, transcript levels, or mutations). In step 123, the scientific literature and other relevant sources are monitored for other genetic variants - disease or condition correlation, and after confirming their accuracy and importance, as well as review and approval by government agencies, such other in step 125 Genotype correlation is added to the master repository. The pool of approved and validated medically relevant genetic variants combined with a genome-wide individual profile will advantageously allow for the implementation of a genetic risk assessment of a large number of diseases or conditions. Compilation of an individual's genomic profile can be accomplished by comparing individual nucleotide (genetic) variants or markers to a library of human nucleotide variants that have been associated with a particular phenotype (such as disease, condition, or physical state). Determine individual genotype correlations. By comparing the individual's genomic profile with the gene 127264.doc -55- 200847056 type, the main Shenzu Temple can tell the individual whether it is positive or negative for genetic risk factors and to what extent. The individual will receive the relative risk and/or propensity of the disease state (eg, Alzheimer's disease, heart disease, blood disease, blood coagulation). ^ + and 5 ' may include genotype correlations in Table 1. In addition, the SNP disease correlations in the library may include, but are not limited to, the other relevant correlations in Figures 5 and 6 as shown in Figure 4. Therefore, the Lord

9 &quot; The method of providing a risk analysis of the disease and condition in any of the intended effects of the disease and condition. In, he knows 4 columns,! The genotype correlation of the Geegen genome individual profile is a non-medical related phenotype, such as &quot;interesting, phenotypic or physical traits, such as coat color. In a preferred embodiment, a rule or set of rules is applied to an individual's genomic profile or SNp profile as described above. Applying the rules to the genomic profile produces an individual's phenotypic profile. Therefore, with the discovery and confirmation of new correlations, the main database of human genotype correlations is extended with other genotype correlations. Updates can be made by accessing appropriate information from the genomic profile of the individual stored in the database, as needed or appropriate. For example, new genotype correlations that become known can be based on specific genetic variants. The determination of whether the individual can be sensitive to the new genotype can then be made by searching and comparing the gene portion of the entire genomic profile of the individual. The results of the genomic query are preferably analyzed and interpreted to be presented to the individual in an understandable format. In step 117, the results of the initial 127264.doc • 56·200847056 screening are then provided to the patient in a confidential, confidential form by mail or via the online portal interface as detailed above. The report may contain a phenotypic profile and genomic information about the phenotype in the phenotypic profile, such as basic genetics of the genes involved or statistics of genetic variants in different populations. Additional information based on phenotypic profiles that can be included in the report is improved identification and sub-categorization of prevention strategies, health information, therapies, symptom understanding, early detection protocols, intervention protocols, and phenotypes. After the initial screening of the individual's genomic profile, a controlled moderate update may be made or may be performed. As new genotype correlations emerge and are confirmed and approved, an update of the individual's genomic profile can be made or made available to the master database along with the update. New rules based on new genotype correlations can be applied to the initial genome overview to provide an updated phenotypic profile. In step 127, an updated genotype correlation profile can be generated by comparing the genomic profile of the individual to the relevant portion of the new genotype correlation. For example, if a new genotype correlation is found to be based on a variant of a particular gene, then the gene portion of the individual's genomic profile can be analyzed for the new genotype correlation. In this case, you can apply – or multiple new rules to produce ± update the phenotypic profile, ❿# with the entire rule of the applied rules. The results of the updated genotype correlation of the individual are provided in a confidential manner in step 129. A service provided to users or customers. Schedules and combinations of different levels of genomic profiling can be provided. Similarly, the level of pre-exposure can be varied to provide individuals with a selection of services that they wish to receive with their genotype correlation.服务 ^ U This service level will vary depending on the level of the individual's purchase of the service. 127264.doc -57- 200847056 The user's entry level schedule can include a genomic profile and an initial phenotypic profile. This can be a base predetermined level. Different, and other services may be provided in the basic predetermined level. For example, a particular predetermined level may provide guidance to physicians and other options for genetic counseling, specific expertise in treating or preventing a particular disease. Genetic counseling can be obtained online or by telephone. In the case of a fine example, the predetermined price may depend on the number of phenotypes selected by the individual for his phenotypic profile. Alternatively—choose whether the user chooses to access online genetic counseling. In other cases, the pre-existing provides the genotype correlation of the initial whole genome, maintaining the individual's genome profile in the database; if the individual chooses this, the database can be kept secret. &amp; initial analysis, complex, can generate subsequent analysis and additional results after individual requirements and additional payments. This can be a premium grade reservation. In one embodiment of the business method, an update of the individual's risk is performed and the corresponding poor is provided to the individual based on the subscription. Updates are available to purchase subscribers (subscribers). The genotype correlation analysis subscription provides an update of a particular species or subset of new genotype correlations based on individual preferences. For example, an individual may only wish to be informed of a genotype correlation with a known treatment or prevention regimen. To help an individual decide whether to perform another analysis, individuals can be provided with information about other genotype correlations that have become available. This information can be easily sent to users by mail or email. In a premium subscription, there may be other levels of service, such as those mentioned in the underlying subscription. Other booking modes are available in the premium class. For example, 127264.doc -58- 200847056 Lu's rain level provides users with unlimited updates and reports. The user's profile can be updated when the new relevance and rule day f' is determined. At this level, users can also access an unlimited number of individuals, such as family members and health care administrators. Users also have unlimited access to online genetic counselors and physicians. Subscriptions below the Premier level may offer more limited features, such as limited updates. Users may have a limited number of updates to the genome profile during the booking period, for example 4 times a year. At another booking level, users can update their stored genome profile once a week, once a month, or once a year. In another embodiment, the user may only have the option to update a limited number of phenotypes of their genome profiles. Personal portals will also conveniently allow individuals to maintain reservations for hazard or related updates and information updates, or to request updated risk estimates and information. As described above, different booking levels may be provided to allow an individual to select various levels of genotype correlation results and updates, and the user may select different booking levels via their personal portal. Any of these predetermined options will contribute to the source of revenue for the subject business approach. The source of revenue for the subject business approach will also be increased by adding new customers and users, with a new genome profile added to the database. Table 1: Representative genes with genetic variants associated with phenotypes. Gene phenotype A2M - Alzheimer's disease ABCA1 HDL cholesterol ABCB1 HIV ABCB1 Epilepsy ABCB1 Kidney transplantation complications ABCB1 Digoxin, serum concentration ABCB1 - to the sinus disease; ulcerative colitis _ 127264. Doc -59- 200847056 Gene phenotype ABCB1 Parkinson's disease ABCC8 Type 2 diabetes ABCC8 Type 2 diabetes ABO Myocardial infarction ACADM Medium chain thiol-CoA dehydrogenase deficiency ACDC Type 2 diabetes ACE Type 2 diabetes ACE Hypertension ACE Alzheimer's disease ACE Myocardial infarction ACE Cardiovascular ACE Left ventricular hypertrophy ACE Coronary artery disease ACE Coronary atherosclerosis ACE Diabetic retinopathy ACE Systemic lupus ACE Arterial blood pressure ACE Erectile dysfunction ACE Lupus ACE Polycystic kidney disease ACE Stroke ACPI Type 1 Diabetes ACSM1 (LIP)c Cholesterol Content ADAM33 Asthma ADD! Hypertension ADD1 Arterial Blood Pressure ADH1B Alcohol Abuse ADH1C Alcohol Abuse ADIPOQ Type 2 Diabetes ADIPOQ Obesity ADARA2A Panic Disorder ADRB1 Hypertension ADRB1 Heart Failure ADRB2 Asthma ADRB2 Hypertension ADRB2 Obesity ADRB2 Artery Gold pressure ADRB2 Type 2 diabetes ADRB3 Obesity ADRB3 Type 2 diabetes ADRB3 Hypertension AGT Hypertension 127264.doc -60- 200847056 Gene phenotype AGT Type 2 diabetes AGT Essential hypertension AGT Myocardial infarction AGTR1 Hypertension AGTR2 Hypertension AHR Breast cancer ALAD Lead poisoning ALDH2 Alcoholism ALDH2 Alcohol abuse ALDH2 Colorectal cancer ALDRL2 Type 2 diabetes ALOX5 Asthma ALOX5AP Asthma APBB1 Alzheimer's disease APC Colorectal cancer APEX1 Lung cancer APOA1 Coronary arteriosclerosis APOA1 HDL cholesterol APOA1 Coronary artery disease APOA1 Type 2 diabetes APOA4 2 Type 2 Diabetes APOA5 Triglyceride APOA5 Coronary Arteriosclerosis APOB Hypercholesterolemia APOB Obesity APOB Cardiac Tumor APOB Coronary Artery Disease APOB Coronary Heart Disease APOB Type 2 Diabetes APOC1 Alzheimer's Disease APOC3 Triglyceride APOC3 Type 2 Diabetes APOE Zhaimo's disease APOE type 2 diabetes APOE multiple sclerosis APOE coronary arteriosclerosis APOE Parkinson's disease APOE coronary heart disease APOE myocardial infarction APOE stroke APOE Alzheimer's disease APOE coronary artery disease 127 264.doc -61 - 200847056 Gene phenotype APP Alzheimer's disease AR Prostate cancer AR Breast cancer ATM Breast cancer ATP7B Wilson disease ATXN80S Spinal cerebral ataxia BACE1 Alzheimer's disease BCHE Az Hermann's disease BDKRB2 Hypertension BDNF Alzheimer's disease BDNF Bipolar disorder BDNF Parkinson's disease BDNF Schizophrenia BDNF Memory BGLAP Bone mineral density BRAF Thyroid cancer BRCA1 Breast cancer BRCA1 Breast cancer; Ovarian cancer BRCA1 Ovarian cancer BRCA2 Breast cancer BRCA2 Breast cancer; Ovarian cancer BRCA2 Ovarian cancer BRIP1 Breast cancer C4A Systemic lupus erythematosus CALCR Bone mineral density CAMTA1 Intermittent memory CAPN10 Type 2 diabetes CAFN10 Type 2 diabetes CAPN3 Muscular atrophy CARD15 Crohn's disease CARD 15 Crohn's disease; Ulcerative colitis CARD15 Inflammatory bowel disease CART Obesity CASR Bone mineral density CCKAR Schizophrenia CCL2 Systemic lupus erythematosus CCL5 HIV CCL5 Asthma CCND1 Colorectal cancer CCR2 HIV CCR2 HIV infection CCR2 Hepatitis C CCR2 Myocardial infarction 127264.doc -62- 200847056

Gene phenotype CCR3 Asthma CCR5 HIV CCR5 HIV infection CCR5 Hepatitis C CCR5 Asthma CCR5 Multiple sclerosis CD14 Atopic dermatitis (atopy) CD14 Asthma CD14 Crohn's disease CD14 Crohn's disease; Ulcerative colitis CD14 Periodontitis CD14 Total IgE CDH1 Prostate cancer CDH1 Colorectal cancer CDKN2A Melanoma CDSN Psoriasis CEBPA Myeloid leukemia CETP Coronary arteriosclerosis CETP Coronary heart disease CETP Hypercholesterolemia CFH Macular degeneration CFTR Cystic fibrosis CFTR Pancreatitis CFTR Cystic fibrosis CHAT Alzheimer's disease CHEK2 Breast cancer CHKNA7 Schizophrenia CMA1 Atopic dermatitis CNR1 Schizophrenia COL1A1 Bone mineral density COL1A1 Osteoporosis COL1A2 Bone mineral density COL2A1 Osteoarthritis COMT Schizophrenia COMT Breast cancer COMT Parkinson Disease COMT Bipolar disorder COMT Obsessive-compulsive disorder COMT Alcoholism CR1 Systemic lupus erythematosus CRP C-reactive protein CST3 Alzheimer's disease 127264.doc -63- 200847056

Gene phenotype CTLA4 Type 1 diabetes CTLA4 Gracies CTLA4 Multiple sclerosis CTLA4 Rheumatoid arthritis CTLA4 Systemic lupus erythematosus CTLA4 Lupus erythematosus CTLA4 Celiac disease CTSD Alzheimer's disease CX3CR1 HIV CXCL12 HIV CXCL12 HIV infection CYBA Coronary artery Hardening CYBA Hypertension CYP11B2 Hypertension CYP11B2 Left ventricular hypertrophy CYP17A1 Breast cancer CYP17A1 Prostate cancer CYP17A1 Endometriosis CYP17A1 Endometrial cancer CYP19A1 Breast cancer CYP19A1 Prostate cancer CYP19A1 Endometriosis CYP1A1 Lung cancer CYP1A1 Breast cancer CYP1A1 Colorectal cancer CYP1A1 Prostate cancer CYP1A1 Esophageal cancer CYP1A1 Endometriosis CYP1A1 Cytogenetic study CYP1A2 Schizophrenia CYP1A2 Colorectal cancer CYP1B1 Breast cancer CYP1B1 Glaucoma CYP1B1 Prostate cancer CYP21A2 21-Hydroxylase deficiency CYP21A2 Congenital adrenal hyperplasia CYP21A2 Congenital adrenal hyperplasia CYP2A6 Smoking behavior CYP2A6 is tested for CYP2A6 lung cancer CYP2C19 Helicobacter pylori (H. pylori) infection CYP2C19 phenytoin CYP2C19 stomach disease 127264.doc -64- 200847 056 Gene phenotype CYP2C8 Plasmodhim falciparum dysentery CYP2C9 Anticoagulant complication CYP2C9 Warfarin sensitivity CYP2C9 Response to warfarin therapy CYP2C9 Colorectal cancer CYP2C9 phenytoin CYP2C9 Acetate coumarin ( Acenocoumarol) CYP2C9 coagulation disorder CYP2C9 high gold pressure CYP2D6 colorectal cancer CYP2D6 Parkinson's disease CYP2D6 CYP2D6 weak metabolizer phenotype CYP2E1 lung cancer CYP2E1 colorectal cancer CYP3A4 prostate cancer CYP3A5 prostate cancer CYP3A5 esophageal cancer CYP46A1 Alzheimer's disease DBH spirit Schizophrenia DHCR7 History-Lim-Opitz Syndrome DISCI Schizophrenia DLST Alzheimer's Disease DMD Muscular Dystrophy DRD2 Alcoholism DRD2 Schizophrenia DRD2 Smoking Behavior DRD2 Parkinson's Disease DRD2 Late Cardiac dyskinesia DRD3 Schizophrenia DRD3 Delayed dyskinesia DRD3 Bipolar disorder DRD4 Attention deficit hyperactivity disorder DRD4 Schizophrenia DRD4 Favorite novelty DBD4 ADHD DRD4 Personality trait DRD4 Heroin spill DKD4 Alcohol abuse DRD4 wine Poisoning DRD4 Personality disorder DTNBP1 Schizophrenia EDN1 South blood pressure 127264.doc -65- 200847056 Gene phenotype EGFR Lung cancer ELAC2 Prostate cancer ENPP1 Type 2 diabetes EPHB2 Prostate cancer EPHX1 Lung cancer EPHX1 Colorectal cancer EPHX1 Cytogenetic study EPHX1 Chronic obstructive pulmonary disease / COPD ERBB2 Breast cancer ERCC1 Lung cancer ERCC1 Colorectal cancer ERCC2 Lung cancer ERCC2 Cytogenetic study ERCC2 Bladder cancer ERCC2 Colorectal cancer ESR1 Bone mineral density ESR1 Bone mineral density ESR1 Breast cancer ESR1 Endometriosis ESR1 Osteoporosis ESR2 Bone mineral density ESR2 Breast cancer Estrogen receptor Body bone mineral density F2 Coronary heart disease F2 Stroke F2 Venous thromboembolism F2 Pre-convulsive F2 Thrombosis F5 Venous thromboembolism F5 Pre-convulsive F5 Myocardial infarction F5 Stroke F5 Ischemic stroke F7 Coronary arteriosclerosis F7 Myocardial infarction F8 Hemophilia F9 Hemophilia FABP2 type 2 glycocalyx FAS Alzheimer's disease FASLG multiple sclerosis FCGR2A systemic lupus erythematosus FCGR2A lupus 127264.doc -66- 200847056

Gene phenotype FCGR2A Periodontitis FCGR2A Rheumatoid arthritis FCGR2B Lupus erythematosus FCGR2B Systemic lupus erythematosus FCGR3A _ Systemic lupus erythematosus FCGR3A Lupus erythematosus FCGR3A Periodontitis FCGR3A Arthritis FCGR3A Rheumatoid arthritis FCGR3B Periodontitis FCGR3B Periodontal Disease FCGR3B Lupus erythematosus FGB Fibrinogen FGB Myocardial infarction FGB Coronary heart disease FLT3 Myeloid leukemia FLT3 Leukemia FMR1 Fragile X syndrome FRAXA Fragile X syndrome FUT2 Helicobacter pylori infection FVL Factor V Leiden G6PD G6PD Lack of G6PD 13⁄4 bilirubin disease GABRA5 bipolar disorder GBA Gaucher disease GBA Parkinson's disease GCGR (FAAH, ML4R, UCP2) Constitution / obesity GCK type 2 diabetes GCLM (F12, TLR4) atherosclerosis , myocardial infarction GDNF schizophrenia GHRL obesity GJB1 Charcot-Marie-Tooth disease GJB2 deafness GJB2 non-symptomatic sensorineural hearing loss GJB2 sensorineural hearing loss GJB2 hearing loss / deafness GJB6 non Syndrome-type sensory nerve Hearing loss GJB6 Hearing loss/Deafness GNAS Hypertension GNB3 High gold pressure GPX1 Lung cancer GRIN1 Schizophrenia 127264.doc -67- 200847056

Gene phenotype GRJN2B Schizophrenia GSK3B Bipolar disorder GSTM1 Lung cancer GSTM1 Colorectal cancer GSTM1 Breast cancer GSTM1 Prostate cancer GSTM1 Cytogenetic research GSTM1 Bladder cancer GSTM1 Esophageal cancer GSTM1 Head and neck cancer GSTM1 Leukemia GSTM1 Parkinson's disease GSTM1 Gastric cancer GSTP1 Lung cancer GSTP1 Colorectal GSTP1 Breast Cancer GSTP1 Cytogenetic Research GSTP1 Prostate Cancer GSTT1 Lung Cancer GSTT1 Colorectal Cancer GSTT1 Breast Cancer GSTT1 Prostate Cancer GSTT1 Bladder Cancer GSTT1 Cytogenetic Study GSTT1 Asthma GSTT1 Benzene Poisoning GSTT1 Esophageal Cancer GSTT1 Head and Neck Cancer GYS1 Type 2 Diabetes HBB Thalassemia HBB Β-thalassemia HD Huntington's disease HFE Hemochromatosis HFE Ion content HFE Colorectal cancer HK2 Type 2 Diabetes HLA Rheumatoid arthritis HLA Type 1 Diabetes HLA Behcet's Disease HLA Celiac disease HLA Psoriasis HLA Gracies 127264.doc -68 - 200847056 Gene phenotype HLA Multiple sclerosis HLA Schizophrenia HLA Asthma HLA Diabetes HLA-A Lupus HLA-A Platinum disease HLA-A HIV HLA-A Type 1 diabetes HLA-A Graft-versus-host disease HLA-A Multiple sclerosis HLA-B Leukemia HLA-B Bercy's disease HLA-B Celiac disease HLA-B 1 Type 2 Diabetes HLA-B Graft-versus-host disease HLA-B Sarcoidosis HLA-C Psoriasis RLA-DPA1 Alpha treatment HLA-DPB1 Type 1 diabetes HLA-DPB1 Asthma HLA-DQA1 Type 1 diabetes HLA-DQA1 chyle; write HLA -DQA1 Cervical cancer HLA-DQA1 Asthma HLA-DQA1 Multiple sclerosis HLA-DQA1 Type 2 diabetes; Type 1 diabetes HLA-DQA1 Lupus erythematosus HLA-DQA1 Recurrent miscarriage HLA-DQA1 Psoriasis HLA-DQB1 Type 1 diabetes HLA-DQB1 X-ray HLA-DQB1 Multiple Sclerosis HLA-DQB1 Cervical cancer HLA-DQB1 Lupus erythematosus HLA-DQB1 Over-abortion HLA-DQB1 Arthritis HLA-DQB1 Asthma HLA-DQB1 HIV HLA-DQBI Lymphoma HLA-DQB1 Tuberculosis HLA-DQBI Rheumatoid arthritis HLA-DQBI type 2 diabetes HLA-DQBI graft versus host disease 127264.doc -69- 200847056

Gene phenotype HLA-DQB1 narcolepsy HLA-DQB1 rheumatoid arthritis HLA-DQB1 sclerosing cholangitis HLA-DQB1 type 2 diabetes; type 1 diabetes HLA-DQB1 Gracie's disease HLA-DQB1 hepatitis C HLA-DQBI Chronic hepatitis C HLA-DQB1 Malaria HLA-DQBI Plasmodium falciparum malaria HLA-DQBI Melanoma HLA-DQBI Psoriasis HLA-DQBI Sjogren's syndrome HLA-DQBI Systemic lupus erythematosus HLA-DRBl type 1 Diabetes HLA-DRB1 Multiple Sclerosis HLA-DRBl Systemic Lupus Erythematosus HLA-DRBI Rheumatoid Arthritis HLA-DRBl Cervical Cancer HLA-DRBI Arthritis HLA-DRBI Celiac Disease HLA-DRBI Lupus Erythematosus HLA-DRBl Sarcoma Disease HLA-DRBl HIV HLA-DRBl Tuberculosis HLA-DRBl Gracies HLA-DRBl Lymphoma HLA-DRBl Psoriasis HLA-DBB1 Asthma HLA-DRBl Crohn's disease HLA-DRB1 Graft-versus-host disease HLA-DRBl Chronic C-type Hepatitis HLA-DRBl narcolepsy HLA-DRBl systemic sclerosis HLA-DRBl Hugh-linked syndrome HLA-DRBl type 1 diabetes HLA-DRBl rheumatoid arthritis HLA-DRBl sclerosing cholangitis HLA-DRBl 2 Diabetes; Type 1 diabetes HLA-DRBl Helicobacter pylori infection HLA-DRBl C hepatitis HLA-DRBl juvenile arthritis HLA-DRBl platinum disease 127264.doc -70- 200847056

Gene phenotype HLA-DRB1 malaria HLA-DRB1 melanoma HLA-DRB1 recurrent miscarriage HLA-DRB3 psoriasis HLA-G recurrent miscarriage HMOX1 coronary atherosclerosis HNF4A type 2 diabetes HNF4A type 2 diabetes HSD11B2 hypertension HSD17B1 breast cancer HTR1A major depression HTR1B alcohol Dependent on HTR1B Alcoholism HTR2A Memory HTR2A Schizophrenia HTR2A Bipolar disorder HTR2A Inhibition HTR2A Major depression HTR2A Suicide HTR2A Alzheimer's disease HTR2A Anorexia nervosa HTR2A High stress HTR2A Obsessive-compulsive disorder HTR2C Schizophrenia HTR6 Azhai Mohs disease HTR6 schizophrenia HTRA1 wet type age-related macular degeneration IAPP type 2 diabetes IDE Alzheimer's disease IFNG tuberculosis IFNG type 1 diabetes IFNG graft versus host disease IFNG hepatitis B IFNG multiple sclerosis IFNG asthma IFNG Breast cancer IFNG kidney transplantation IFNG kidney transplantation complications IFNG long brother IFNG reverse abortion IGFBP3 breast cancer IGFBP3 prostate cancer 127264.doc -71 - 200847056

Gene phenotype IL10 Systemic lupus erythematosus IL10 Asthma IL10 Graft versus host disease IL10 HIY DL10 Kidney transplantation IL10 Kidney transplantation complications IL10 Hepatitis B IL10 Adolescent arthritis IL10 Longevity IL10 Multiple sclerosis IL10 Recurrent miscarriage 1L10 Rheumatoid arthritis IL10 Tuberculosis IL12B Type 1 Diabetes IL12B Asthma IL13 Asthma IL13 Atopic dermatitis IL13 Chronic obstructive pulmonary disease/COPD ILI3 Gracies ILIA Periodontitis ILIA Alzheimer's disease IL1B Periodontitis IL1B Alzheimer's disease IL1B Gastric cancer IL1R1 type 1 diabetes IL1RN gastric cancer IL2 asthma; eczema; allergic disease IL4 asthma IL4 atopic dermatitis IL4 HIV IL4R asthma IL4R atopic dermatitis 1L4R total serum IgE IL6 bone mineralization IL6 kidney transplantation IL6 kidney transplantation complications IL6 Longevity EL6 Multiple Sclerosis IL6 Bone Mineral Density IL6 Bone Mineral Density IL6 Colorectal Cancer IL6 Adolescent Arthritis IL6 Rheumatoid Arthritis 127264.doc -72- 200847056 Gene phenotype IL9 Asthma INHA Premature ovarian failure INS Type 1 Diabetes INS Type 2 Diabetes INS type 1 diabetes INS obesity INS prostate cancer INSIG2 obesity INSR type 2 diabetes INSR hypertension INSR polycystic ovary syndrome IPF1 type 2 diabetes IRS1 type 2 diabetes IRS1 type 2 diabetes IRS2 type 2 diabetes ITGB3 myocardial infarction ITGB3 coronary atherosclerosis ITGB3 coronary heart disease ITGB3 myocardial infarction KCNE1 EKG Abnormal KCNE2 EKG abnormality KCNH2 EKG abnormal KCNH2 long QT syndrome KCNJ11 type 2 diabetes KCNJ11 type 2 diabetes KCNN3 schizophrenia KCNQ1 EKG abnormal KCNQ1 long QT syndrome KIBRA intermittent memory KLK1 hypertension KLK3 prostate cancer KRAS colorectal cancer LDLR hypercholesterolemia LDLR Hypertension LEP Obesity LEPR Obesity LIG4 Breast Cancer UPC Coronary Arteriosclerosis LPL Coronary Artery Disease LPL Southern Lipidemia LPL Triglyceride LRP1 Alzheimer's Disease 127264.doc -73- 200847056 Gene phenotype LRP5 Bone mineral density LRRK2 Parkinson's disease Disease LRRK2 Parkinson's disease LTA type 1 diabetes 哮喘 Asthma LTA Systemic lupus erythematosus LTA Abortive disease UTC4S Asthma MAOA Alcoholism MAOA Schizophrenia MAOA Bipolar disorder MAOA Smoking behavior M AOA Personality Disorder MAOB Parkinson's Disease MAOB Smoking Behavior MAPT Parkinson's Disease MAPT Alzheimer's Disease MAPT Dementia MAPT Frontotemporal Dementia MAPT Progressive Nuclear Paralysis MC1R Melanoma MC3R Obesity MC4R Obesity MECP2 Reiter's Syndrome ( Rett syndrome) MEFV Familial Mediterranean fever MEFV Amyloidosis MICA Type 1 diabetes MICA Beth's disease MICA Celiac disease MICA Rheumatoid arthritis MICA Systemic lupus erythematosus MLH1 Colorectal cancer MME Alzheimer's disease MMP1 Lung cancer MMP1 Ovary Cancer MMP1 Periodontitis MMP3 Myocardial infarction MMP3 Ovarian cancer MMP3 Rheumatoid arthritis MPO Lung cancer MPO Alzheimer's disease MPO Breast cancer 127264.doc -74- 200847056 Genetic phenotype MPZ Summer-horse-Graphic disease MS4A2 Asthma MS4A2 Atopic dermatitis MSH2 Colorectal cancer MSH6 Colorectal cancer MSR1 Prostate cancer MTHFR Colorectal cancer MTHFR Type 2 Diabetes MTHFR Neural tube defect MTHFR Hypercysteine MTHFR Venous thromboembolism MTHFR Coronary arteriosclerosis MTHFR Alzheimer's disease MTHFR Esophageal cancer MTHFR pre-convulsive MTHFR anti Abortion MTHFR Stroke MTHFR Deep vein thrombosis MT-ND1 Type 2 Diabetes MTR Colorectal cancer MT-RNR1 Non-synchronous group Sensory neuron hearing loss MTRR Neural tube defect MTRR High cysteine MT-TL1 Type 2 diabetes MUTYH Colorectal cancer MYBPC3 Myocardium MYH7 Myocardial MYOC Primary Open Angle Glaucoma MYOC Glaucoma NATl Colorectal Cancer NAT1 Breast Cancer NATl Bladder Cancer NAT2 Colorectal Cancer NAT2 Bladder Cancer NAT2 Breast Cancer NAT2 Lung Cancer NBN Breast Cancer NCOA3 Breast Cancer NCSTN Alzheimer's Disease NEUROD1 Type 1 Diabetes NF1 Multiple neurofibromatosis 1 NOS1 Asthma 127264.doc -75- 200847056 Gene phenotype NOS2A Multiple sclerosis NOS3 Hypertension NOS3 Coronary heart disease NOS3 Coronary atherosclerosis NOS3 Coronary artery disease NOS3 Myocardial infarction NOS3 Acute coronary syndrome NOS3 Arterial blood pressure NOS3 Pre-preperfusion NOS3 Nitric oxide NOS3 Alzheimer's disease NOS3 Asthma NOS3 Type 2 diabetes NOS3 Cardiovascular disease NOS3 Bercy's disease NOS3 Erectile dysfunction NOS3 Chronic renal failure NOS3 Misdiagnosis NOS3 Left ventricular hypertrophy NOS3 NOS3 diabetic retinopathy NOS3 stroke NOTCH4 schizophrenia NPY alcohol abuse NQOl lung cancer NQOl colorectal cancer NQOl benzene poisoning NQOl bladder cancer NQOl Parkinson's disease NR3C2 hypertension NR4A2 Parkinson's disease NRG1 schizophrenia NTF3 schizophrenia OGGI lung cancer OGGI Colorectal cancer OLR1 Alzheimer's disease OPA1 Glaucoma OPRM1 Alcohol abuse OPRM1 Substance-dependent OPTN Primary open-angle glaucoma P450 Agent metabolism PADI4 Rheumatoid arthritis 127264.doc •76- 200847056 Genetic phenotype PAH Phenylketoneuria Symptoms / PKU PAI1 Coronary heart disease PAI1 Asthma PALB2 Breast cancer PARK2 Parkinson's disease PARK7 Parkinson's disease PDCD1 Lupus erythematosus PINK1 Parkinson's disease PKA Memory PKC Memory PLA2G4A Schizophrenia PNB schizophrenia POMC Obesity PON1 Coronary arteriosclerosis PON1 Parkinson's disease Disease PON1 Type 2 Diabetes PON1 Atherosclerosis PON1 Coronary artery disease PONi Coronary heart disease PON1 Alzheimer's disease PONI Longevity PON2 Coronary arteriosclerosis PON2 Premature delivery PPARG Type 2 diabetes PPARG Obesity PPARG 2 Type 2 diabetes PPARG colorectal cancer PPARG hypertension PPARGC1A type 2 diabetes PRKCZ type 2 diabetes PRL systemic lupus erythematosus PRNP Alzheimer's disease PRNP Creutzfeldt-Jakob disease PRNP Tang Jie Er's disease (Jakob- Creutzfeidt disease) PRODH schizophrenia PRSS1 pancreatitis PSEN1 Alzheimer's disease PSEN2 Alzheimer's disease PSMB8 type 1 diabetes PSMB9 type 1 diabetes PTCH non-melanoma skin cancer PTGIS hypertension 127264.doc •77- 200847056

Gene phenotype PTGS2 Colorectal cancer PTH Bone mineral density PTPNll Noonan syndrome ΡΊΤΝ22 Rheumatoid arthritis PTPRC Multiple sclerosis PVT1 End stage renal disease RAD51 Breast cancer RAGE Diabetic retinopathy RBI Retinal blastoma RELN Schizophrenia REN Hypertension RET Thyroid cancer RET Hirschsprung's disease RFC1 Neural tube defects RGS4 Schizophrenia RHO Retinitis pigmentosa RNASEL Prostate cancer RYR1 Malignant fever SAA1 Amyloidosis SCG2 Hypertension SCG3 Obesity SCGB1A1 Asthma SCN5A Bru Addition syndrome (Brngada syndrome) SCN5A EKG abnormality SCN5A Long QT syndrome SCNN1B Hypertension SCNN1G Hypertension SERPINA1 COPD SERPINA3 Alzheimer's disease SERPINA3 COPD SERPINA3 Parkinson's disease SERPINEl Myocardial infarction SERPINE1 Type 2 diabetes SERPINEl Coronary arteriosclerosis SERPINEl Obesity SERPINEl Pre-convulsion SERPINEl stroke SERPINEl two blood pressure SERPINEl recurrent miscarriage SERPINEl venous thromboembolism SLC11A1 tuberculosis SLC22A4 Crohn's disease; ulcerative SLC22A5 colitis Crohn's disease; ulcerative colitis 127264.doc -78 - 200847056

Gene phenotype SLC2A1 Type 2 diabetes SLC2A2 Type 2 diabetes SLC2A4 Type 2 diabetes SLC3A1 Cystamine SLC6A3 Attention deficit hyperactivity disorder SLC6A3 Parkinson's disease SLC6A3 Smoking behavior SLC6A3 Alcoholism SLC6A3 Schizophrenia SLC6A4 Depression SLC6A4 Major depression SLC6A4 Schizophrenia SLC6A4 Suicide SLC6A4 Alcoholism SLC6A4 Bipolar disorder SLC6A4 Personality traits SLC6A4 Attention deficit hyperactivity disorder SLG6A4 Alzheimer's disease SLC6A4 Personality disorder SLC6A4 Panic disorder SLC6A4 Alcohol abuse SLC6A4 Affective disorder SLC6A4 Anxiety disorder SLC6A4 Smoking behavior SLC6A4 Major depression Symptoms; bipolar disorder SLC6A4 heroin abuse SLC6A4 colorectal irritability SLC6A4 migraine SLC6A4 obsessive-compulsive disorder SLC6A4 suicidal behavior SLC7A9 cystine urinary SNAP25 ADHD SNCA Parkinson's disease S0D1 ALS/muscle atrophic lateral sclerosis SOD2 breast cancer SOD2 lung cancer S0D2 prostate cancer SPINK1 Pancreatitis SPP1 Multiple Sclerosis SRD5A2 Prostate Cancer STAT6 Asthma STAT6 Total IgE 127264.doc -79- 200847056 Gene phenotype SULT1A1 Breast cancer SULT1A1 Colon Rectal cancer TAPI type 1 diabetes TAPI Lupus erythematosus TAP2 Type 1 diabetes TAP2 Type 1 diabetes TBX21 Asthma TBXA2R Asthma TCF1 Type 2 diabetes TCF1 Type 2 diabetes TF Alzheimer's disease TGFB1 Breast cancer TGFB1 Kidney transplantation TGFB1 Kidney transplantation complications TH Schizophrenia THBD myocardial infarction TLR4 asthma TLR4 Crohn's disease; ulcerative colitis TLR4 sepsis TNF asthma TNFA cerebrovascular disease TNF type 1 diabetes TNF rheumatoid arthritis TNF systemic lupus erythematosus TNF kidney transplantation TNF psoriasis TNF sepsis TNF type 2 diabetes TNF Alzheimer's disease TNF Crohn's disease TNF type 1 diabetes TNF B hepatitis TNF kidney transplantation complications TNF multiple sclerosis TNF schizophrenia TNF chyle rot TNF obesity TNF recurrent miscarriage TNFRSF11B bone density TNFRSF1A rheumatoid Arthritis TNFRSF1B rheumatoid arthritis TNFRSF1B systemic lupus erythematosus 127264.doc -80- 200847056

Gene phenotype TNFRSF1B Arthritis TNNT2 Cardiomyopathy TP53 Lung cancer TP53 Breast cancer TP53 Colorectal cancer TP53 Prostate cancer TP53 Cervical cancer TP53 Ovarian cancer TP53 Smoking TP53 Esophageal cancer TP73 Lung cancer TPH1 Suicide TPH1 Major depression TPH1 Suicidal behavior TPH1 Schizophrenia TPMT Thio Thiol-transferase activity TPMT White J&amp;L disease TPMT Inflammatory bowel disease TPMT Thiopurine S-methyltransferase phenotype TSC1 Tuberous sclerosis TSC2 Tuberous sclerosis TSHR Gracie disease TYMS Colorectal cancer TYMS Gastric cancer TYMS Esophageal cancer UCHL1 Parkinson's disease UCP1 Obesity UCP2 Obesity UCP3 Obesity UGT1A1 Hyperbilirubinemia UGT1A1 Gilbert syndrome UGT1A6 Colorectal cancer UGT1A7 Colorectal cancer UTS2 Type 2 diabetes VDR Bone mineral density VDR Prostate cancer VDR Bone mineral Density VDR Type 1 Diabetes VDR Osteoporosis VDR Bone VDR Breast Cancer VDR Lead Poisoning 127264.doc -81 - 200847056 Gene phenotype VDR Tuberculosis VDR Type 2 Diabetes VEGF Breast cancer vit D rec Idiopathic short VKORC1 Reversing warfarin therapy Should be WNK4 Hypertension 肺癌 Lung cancer XPC Lung cancer XPC Cytogenetics XRCC1 Lung cancer XRCC1 Cytogenetics XRCC1 Breast cancer XRCC1 Bladder cancer XRCC2 Breast cancer XRCC3 Breast cancer XRCC3 Cytogenetic research XRCC3 Lung cancer XRCC3 Bladder cancer ZDHHC8 Schizophrenia genetic composite index (GCI) Many The cause of the condition or disease is due to genetic and environmental factors. Recent advances in genotyping techniques have provided an opportunity to identify the association between disease and genetic markers in the entire genome. In fact, many recent studies have found such associations in which specific dual genes or genotypes are associated with increased risk of disease. Some of these studies involved the collection of a set of test cases and a control group, as well as a comparison of the distribution of the dual genes for genetic markers between the two populations. In some of these studies, the association between a particular genetic marker and a disease is a measure of separation from other genetic markers that is treated as a background and not illustrated in the statistical analysis. Genetic markers and variants may include SNPs, nucleotide repeats, nucleotide insertions, nucleotide deletions, chromosomal translocations, chromosomal duplications, or copies. 127264.doc -82 - 200847056 Replica variation can include microsatellite repeats, nuclear bud repeats, centromeric repeats, or telomere repeats. In the present invention, information relating to the association of multiple genetic markers with - or a plurality of diseases or conditions is combined and analyzed to produce (10) ° ten knives. The GCI score can be used to provide a person who is not genetically trained to be able to compare the individual risk of a disease with a relevant group based on a scientific study. (ie, stable), understandable, and/or intuitive. The robust GCI scores used to generate the combined effects of different loci in one embodiment are based on the individual risk reported for each locus studied. For example, S, identifying the disease or condition of interest and then querying for information about the disease or condition and one or more genetic loci, including (a) not in the database, the patent disclosure, and the scientific literature. Associated information. Use quality standards to verify and evaluate these sources of information. In some embodiments, the evaluation process includes multiple steps. In other embodiments, the source of information is evaluated for multiple quality criteria. Use information from sources of information to identify the odds or relative risk of one or more genetic loci for each disease or condition of interest φ. In an alternate embodiment, the odds ratio (〇R) or relative risk (RR) of at least one genetic locus is not available from available sources of information. Then use 〇) reported multiple ORFs of the same locus, (2) the frequency of the dual gene from a data set such as the HapMap data set, and/or (3) from available resources (eg, CDC, National Center for The disease/condition prevalence of Health Statistics, etc., is calculated to account for the RR of all the dual genes of interest. In one embodiment, the 〇R of 127264.doc-83-200847056 multiple dual genes of the same locus is estimated separately or independently. In a preferred embodiment, the OR of the plurality of dual genes of the same locus is combined to account for the dependence between 〇 R of the different dual genes. In some embodiments, an established disease model (including but not limited to such as multiplication, addition, Hazard-modified, dominant effect) is used to generate a hazard indicative of an individual according to the selected model. Intermediate scoring. In another embodiment, a plurality of methods (4) for analysing the disease or condition of interest and methods for correlating the results obtained from such contiguous types are used; thereby reducing the possible errors introduced by selecting a particular disease model To the minimum. This method minimizes the impact of the prevalence of the relative risk calculations (IV) on the prevalence, the frequency of the dual gene, and the reasonable error of the OR estimate. Since the prevalence rate estimates the &quot;linear&quot; or monotonic nature of RR, it is incorrect to estimate that the prevalence has little effect on the final score; the constraint is that the same model is applied consistently to all individuals who produce the report. In another embodiment, a method of considering environmental/behavior/demographic data as the other &quot;locus&quot; is used. In related embodiments, the information may be obtained from a source of information, such as a medical or scientific literature or database (eg, association of smoking with lung cancer, or from an insurance health risk assessment) in one embodiment, for one or more complexities Disease production (10) counts. Complex diseases can be affected by multiple genes, environmental factors and their interactions. #After studying complex diseases, it is necessary to analyze a large number of possible interactions. In one embodiment, a procedure is used to correct Multiple comparisons, such as Branfini correction. In an alternative embodiment, the Simess test is used to control total significance when there is no dependency between tests or exhibits a particular type of dependence. Doc -84 - 200847056 Degree (also known as "family error rate") (Sarkar S. (1998)). Some likelihood inequalities for ordered MTP2 random variables: evidence from Simess's hypothesis (Ann Stat 26:494-504 The Simes test rejects the following null hypothesis: If ^^ is a moxibustion/foot, any moxibustion can be 1, .., and the ruler, then all the test hypothesis is true. (Simes RJ (1986) An im Proven Bonferroni procedure for multiple tests of significance. Biometrika 73:751-754·).

Other embodiments that can be used in the context of multi-gene and multi-environment factor analysis control the false discovery rate, i.e., the expected ratio of rejected null hypotheses that are falsely rejected. As in microarray studies, this method is especially useful when one of the null hypotheses can be assumed to be false. Devlin et al. (2003, Analysis of multilocus models of association. Genet Epidemiol 25:36-47) proposed Benjamini and Hochberg (1995, Controlling) to control false discovery rates when testing a large number of possible gene x gene interactions in a multilocus association study. The false discovery rate: a practical and powerful approach to multiple testing. JR Stat Soc Ser B 57: 289-300) Gradually increase the variant of the program. The Benjamini and Hochberg programs are related to the Simes test; setting A:* such that it rejects the corresponding hypothesis; In fact, when all null hypotheses are true, the Benjamini and Hochberg programs are restored to the Simes test (Benjamini Y, Yekutieli D (2001) The control of the false discovery rate in multiple testing under dependency. Ann Stat 29:1165-1188) o In some embodiments, compared to the individual population, the 127264.doc -85-200847056 individual is ranked based on the intermediate score to generate a final grade score, which can be expressed as a rank in the group, such as the 99th percentile. Or 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87,

86, 85th, 84th, 83rd, 82nd, 81st, 8th, 79th, 78th, 77th, 76th, 75th, 74th, 73rd, 72nd, 71st, 70th , 69th, 65th, 60th, 55th, 50th, 45th, 40th, 40th, 35th, 30th, 25th, 20th, 2nd, 4th, 4th, 2nd, 2nd Bit. In another embodiment, the rating score can be displayed as a range, such as the 100th to the 95th percentile, the 95th to the 85th percentile, the 85th to the 60th percentile, or the 100th and the 100th. Any subrange between the quantiles. In yet another embodiment, the individual is ranked by quality, such as the highest 75th quartile, or the lowest 25th quartile. In another embodiment, the individual is ranked in comparison to the average or median score of the population. In her case, the group compared to the individual includes a large number of people from a variety of geographic and ethnic backgrounds, such as global groups. In other embodiments, the population compared to the individual is limited to a particular geography, genealogy, race, gender, age (fetus, infant, child, adolescent, juvenile, adult, elderly individual), disease state (such as symptomatic, asymptomatic, Carrier, early hair: late episode). In some embodiments, the group system compared to the individual is paid for information reported in public and/or private information sources. ^8] Use the display to make the individual's GCI score or GCI Plus cry: See 4 - In some embodiments 'use a screen (such as a computer monitor two-screen) to visualize each display, such as with relevant information Personal entrance. In another embodiment, the display is a static display, such as the printed 127264.doc -86 - 200847056 page. In an embodiment, the display may include, but is not limited to, the following: + the heart is more than one: 蔹, 渚 i i-5, π·20, 2i_ 25, 26-30, 31-35, 36- 40, 41·45, 46-50, 51_55, 56_ 60, 61-65, 66-70, 7ΐ·75, 76 8g, 8i 85, 86_9〇, 91_ 95 96_1GG) color or gray level gradient, thermometer, quantity Rule, pie chart, histogram or bar chart. For example, Figures 18 and 19 show different displays for MS and Figure 2G shows for Crohn's disease. In another embodiment, a thermometer is used to display GCI scores and disease/condition prevalence. In another embodiment, the thermometer displays a level that varies with the reported GCI score, such as Figures 15 through 17, the color corresponding to a hazard. The thermometer can show an increase in chromaticity with the GCI juice (such as the blue from the lower GCI score gradually becoming the higher GCI scored red). In the _ related embodiment, the thermometer shows the level as a function of both the reported GCI score and the change in chromaticity as the hazard level increases. In an alternate embodiment, the individual's points are passed to the individual by using auditory feedback. In one embodiment, the audible feedback is a verbal description of a high or low hazard level. In another embodiment, the auditory feedback is a description of a special SGCI score such as a number, a percentile, a range, a quartile, or a comparison to a group average or median Ga score. In an embodiment, the audible feedback is delivered by a person in person or via a telecommunications device such as a telephone (landline, mobile or satellite) or via a personal portal. In another embodiment, the audible feedback is delivered by an automated system such as a computer. In one embodiment, the audible feedback is delivered as part of an interactive audio response (IVR) system that allows the computer to detect sound and use the button sound of a regular telephone. 127264.doc -87· 200847056. In another embodiment, the individual can interact with the central server via the IVR system. The IVR system can make pre-recorded or dynamically generated audio responses to interact with the individual and provide them with an audible feedback of their level of danger. In one example, the individual can call the number answered by the IVR system. The IVR system requires the subject to select an option from a menu such as a button tone or sound menu, as appropriate after entering the authentication code, security code or experiencing the voice recognition protocol. One of these options provides the individual with a level of danger. In another embodiment, the display is used to visualize the individual's GCI scores and to communicate using audible feedback, such as via a personal portal. This combination may include a visual display and auditory feedback of the GCI score, which discusses the association of the gci score with the overall health of the individual and may suggest possible preventive measures. In one example, a multi-step process is used to generate a GCI score. Initially, the relative risk of the odds ratio from each genetic marker was calculated for each condition to be studied. For each prevalence value, 〇1, 〇 〇2, and •5 calculate the GCI score of the HapMap CEU population based on the 〃, L-rate and HapMaP dual gene frequencies. If the GCI score is unchanged at the change prevalence, the only assumption considered is the existence of a multiplicative model. Otherwise, the model is determined to be sensitive to prevalence. For any combination of uninterpreted values, relative hazards and scoring distributions in the HapMap population are obtained. For each new individual, the individual score is compared to the HapMap distribution and the score is scored as the individual's rank in the population. The resolution of the reported scores can be lower due to assumptions made during the process. The group will be divided into component digits (3_6 bin), and the reported - will be the level of the individual -. The number of bins may vary for different diseases based on considerations such as the resolution of the score for each disease. The average level will be used if there is no equivalence between the scores of HapMap individuals and 127264.doc -88 - 200847056. In one embodiment, a higher GCI score is interpreted as an indication of an increased risk of developing or diagnosing a condition or disease. In another embodiment, the GCI score is derived using a mathematical model. In some embodiments, the GCI scoring is based on a mathematical model that resolves the incomplete nature of the underlying information about the population and/or disease or condition. In some embodiments, the mathematical model is included as a calculation

A specific at least one hypothesis of a portion of the GCI scoring benchmark, wherein the hypothesis includes, but is not limited to, assuming a given odds ratio value; a presumed prevalence of known conditions; assuming a genotype frequency in the known population; It is assumed that the customer is from the same family background as the population used for the study and HapMap; the assumed risk of merger is the product of the different risk factors of the individual genetic markers. In some embodiments, '(10) also includes the multiplicative genotype of the genotype as a product of the frequency of the dual gene of each of the individual or individual genetic markers (eg, different SNPs or genetic markers are not present in the population) Dependency). The multiplication model calculates (10) the score based on the product of the risk of the individual genetic marker based on the hypothesis that the risk attributed to the genetic marker set is based on the hypothesis. This means that = the contribution of different genetic markers to the risk of the disease is independent of other legacy ^ = the cause of the form, there is a dangerous dual gene and a non-hazardous pair of mouth, ~ (four) pass mark. In _ ζ·, we instructed Sanguang genotype values one by one. The genotype information of an individual can be described by a vector in which the number of even genes in question is 1 or 2 depending on the location. By indicating the position, the heterozygous genotype of the medium is relatively dangerous compared to the homozygous non-hazard dual gene at the same position as 127264.doc -89- 200847056. In other words, we define Λ similarly, we indicate the relative risk of the genotype as = under the multiplication model, we assume that the risk of individuals with genotypes (g!, ···, ) is GC7 (gi,... , = . Multiply mode ι = ϊ Type 1 has previously been used in the literature to simulate case-control studies, or for visualization purposes. Estimated relative risk.

In another embodiment, the relative risk of different genetic markers is known and the multiplicative model can be used for risk assessment. However, in some of the examples including the association study, the report on the relative risk is excluded. In some case-control studies 9, the relative risk is not directly calculated directly from the data without further assumptions. To replace the relative risk of reporting, the genotype's odds ratio (〇r) is usually reported, which is the advantage of having a given risk genotype (r/s of heart disease or disease without a given risk genotype) The comparison: Formally: 〇&lt;= yelling from the dominance rate to obtain relative danger may require other assumptions. For example, assume that the frequency of the dual gene in the entire population is known or estimated and π·(this equal frequency (four) from, for example, includes 12〇 Estimation of the current data set of the HapMap dataset of the stained & body] and/or the prevalence of known diseases P=P can be derived from the above three equations: 127264.doc 200847056 P^ap{D\nin)^ B^p(D\nir) + c* φ|π), ^Μ) ι-尸(四)ν;|), ζ ι-ρ(ι&gt;|^|) ο By definition of relative danger, divide by; 7iYD After the |AA·〉 item, the first equation can be rewritten as: 1 ^ ci -¥ +

且 And therefore, the last two equations can be rewritten as OR] = rr^P)+bK+c^i α + (6 -/7)4 + c4, (1) ORf ~ {ap)+bXx +c4 a + Z^+(c-/7)4. It should be noted that when α=1 (the frequency of the non-hazard dual gene is 1), Equation System 1 is equivalent to Zhang and Yu of Zhang and J. (What's the relative risk? A method of correcting the odds ratio in cohort studies JAMA, 280: 1690-1, 1998), which is incorporated herein by reference in its entirety. In contrast to zhang &amp; Yu formula, some embodiments of the invention consider the frequency of dual genes in a population, which can affect relative risk. Moreover, some embodiments consider the relative risk interdependence. Contrary to independently calculating each of the relative risks. Equation 1 can be rewritten as two quadratic equations, and at most four can be used to solve the equations, where the starting point 127264.doc -91 - 200847056 is set to the dominant rate. For example 4 = like 丨 and name = create 2. For example: 八,^2)=6^((2 + (6一+4)一4 ·(("一+〇名), /2(^5^)= 〇Rf{o + b^ + (c — p)^i)^* ((α·~ρ)++ c^i) The solution to this special equation is equivalent to the minimum value of the function λ].

Therefore, dg d is -2f\ (λ!, λ2) · b. (λ2 - OR2) + 2f2 (Xi, λ2 ) (21^ + ολ2 + a - OR^b - p + OR^p), dg , d into a 2 (2 (in i',). e. (λ! - ORJ+2((^^2)(2(^2 + bXi + a - OR2c - p + OR2p). In this example, We start with the setting, ;;0 = 〇&amp; We will set the value [epsil〇n]=10-iQ to the tolerance constant via this algorithm. In iteration i, we define:

γ=ιηιη 0.001, X;

Yi-l [epsilon]+10 ^r(xi-i5yi-ii [epsilon]+10 άλ1 dgάλ. Then I set: Wυ^(Χμ,Υμ), yi m milli(Ά-ι). Repeat these iterations until Tolerance, where the difference in the supply code is 127264.doc _ 200847056 is set to ίο·7. In this example, these equations give different values of α, Ζ &gt;, c, ρ, 6^, and 〇 and 2. Correct solution. Figure 1. The relative risk estimate is stable. In some examples, the effects of different parameters (prevalence, dual gene frequency, and odds ratio error) on the estimation of relative risk are measured. The prevalence rate is estimated to have a relative risk value, calculated from a group of values of different odds ratios and different dual gene frequencies (according to HWE), and the results of such calculations are plotted for prevalence values in the range of 0 to 1. Figure 10. In addition, for a fixed value of prevalence, the relative hazard of changing the frequency of a pair of even genes can be plotted. Figure 丨 In all cases, § P — 0, λρΟΑ and λ2 = 〇 Τ?2, and when i, λι=λ2 = 〇. This can be directly from the equation In addition, in some embodiments, when the frequency of the dangerous dual gene is higher, ^ is closer to the linear function and closer to the concave function with the bounded first derivative. In the limit case, when C is called, a2 = 〇r2+p(i-〇r2)h〇r is broad. R〇R2\lP)+pOR}right-, the latter is also close to a linear function. When the risk-dual gene frequency is low, and λ 2 is close to the function 1 /;; In the extreme case, when c = 〇, 七 \ R \ inch 1 -p + pOA ’ —l — p + pOR:. This indication does not significantly affect the relative risk of gain for high-risk-dual gene frequencies. In addition, for low-risk-dual gene frequencies, if the prevalence rate is replaced by the prevalence value of ρ, = α, the relative risk will be multi-phase &quot;^ difference. This is illustrated in parts (C) and (d) of Fig. 11. It should be noted that for the high-risk 127264.doc •93- 200847056 risk-dual gene frequency, the two maps are similar, and when there is a high deviation between the relative risk values for the low-dual gene frequency, the deviation is less than 2 times. Calculating the GCI Score In one embodiment, the genetic composite index is calculated by using a reference set representing the relevant population. This reference set can be one of the populations in the HapMap, or another genotype data set. In this embodiment, the GCI is calculated as follows. For each of the tamping risk loci, the equation system is used to calculate the relative risk from the dominance rate. Then multiply the scores of each individual in the ten different reference sets. The GCI of an individual with a multiplied score s is the fraction of all individuals in the reference set with the score 〆 &amp; For example, if an individual in the reference set of 5〇% has a multiplication score less than s, then the individual's final GCI score will be 〇 5. Other Models In one embodiment, a multiplicative model is used. In an alternate embodiment, other models can be used to determine the purpose of the GCI scoring. Other suitable models include (but are not limited to): Additive mode s. Under the additive model*, the risk of individuals with genotypes (gi,.) is assumed to be %/(&,&quot;.,&)=. Generalized additive model. Under the generalized additive model, it is assumed that there is a function/make the genotype (gl,.&quot;, the risk of the individual of gJ is . /=1 Harvard Improvement Score (Het). This score is derived from gA Colditz et al. So that the score is applied to genetic markers (Harvar (j) reported in (3) to prevent the fourth volume of Harvard cancer dsk index 127264.doc -94- 200847056 W Controls, 11:477-488, 2000, A ^ ^ mode is incorporated in this article) 〇 Het scores 舻 么 么 μ μ μ 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上 大体上This can be applied to situations where the risk of phase-crossing is difficult to estimate. For the fixed-difference month, the intermediate function g is defined as: g(x): 〇1&lt;χ&lt;1.09 5 1.09 &lt;χ &lt; 1.49 101.49 &lt;χ&lt; 2.99 252.99 &lt; χ &lt; 6.99 50 6.99 &lt; χ

Then 'calculate the amount of special phase, where (for the SNP in the reference population, the frequency of the heterozygous individual. The material function, defined as gamma = ringing, and the Harvard improved score (Het) is simply defined as the reading. /= 1 1 Harvard Improvement Score (〒(四)p This score is similar to the Het score, except that the value het is replaced by the value h〇m = g “(4), and the towel i is the frequency of the individual with the homozygous danger-dual gene Maximum-dominance rate. In this model, it is assumed that one of the genetic markers (the one with the greatest odds ratio) gives the lower bound of the combined risk of the entire group. Formally, it has a genotype (gl, _&quot;, g〇 The individual's score is divided into scores. In an example, for 10 SNPs associated with T2D, based on

Multiple models in the HapMap CEU population calculate GCI scores. The relevant SNPs are rs7754840, rs4506565, rs7756992, rsi〇811661, rsl2804210, rs8050136, rsiiii875, rs44〇2960, 127264.doc -95 - 200847056 rs5215, rsl801282. For each of these SNPs, the odds ratios of the three possible genotypes are reported in the literature. The CEU group consists of thirty groups of mother-father-child triads. Use sixty parents from this group to avoid dependencies. One of the 10 SNPs was excluded from having one of the individuals, thereby producing a group of 59 individuals. The GCI level for each individual is then calculated using several different models. It has been observed that for this data set, different models produce highly correlated results. Figure 12 and Figure 13. Calculate the Spearman correlation between each pair of models (Table 2), which shows that the multiplicative and additive models have a correlation coefficient of 0.97, and therefore the use of additive or multiplicative models for gci scoring will be robust of. Similarly, the correlation between the Harvard improved scoring and multiplication model is 0.83, and the correlation coefficient between the Harvard scoring and adding models is 〇·7. However, using the maximum odds ratio as a genetic score produces a binary score defined by a SNP. Overall, these results indicate that the scoring hierarchy provides a robust framework that minimizes model dependencies. Table 2: Spielman correlations on the scoring distribution of CEU data between model pairs

The effect of changes in the prevalence of T2D on the resulting distribution was measured. Prevalence values ranged from 0.001 to 0.512 (Figure 14). For the case of T2D, it was observed that different 127264.doc -96-200847056 μ row rate values produced the same order of individuals, text inversion correlation &gt; 〇 9 9 , so it can be assumed that the prevalence rate is fixed at 0.01. Extending the model to any number of variants In another embodiment, the model can w μ 芏 appear as a possible morpheme of the number h. Previous considerations have dealt with the case of mutans, which are variants (like, rr, rr). Typically, any number of variants can be found in the cluster when the SNP is associated. For example, between the two genetic markers

The interactions associated with the condition are stored in nine possible variants. This produces eight different odds ratio values. Also to make the initial generalization 'can be assumed to exist... kinds of possible variants a0,&quot;.,ak, where the frequency is /〇, 7ι", eight, the measured odds ratio is 1, 〇 and 1...·, 〇&amp;, and the relative relative risk value is 7 'Λ1,···, /^. In addition, all relative dangers and odds ratios can be assumed to be relatives, and the other hand is relative to the count, and therefore Λ

Judgment Σ^Λί 0Ri=, ^- ο Σ^Λΐ ~λίΡ i=0 In addition, if you set Bu^, this produces the following equation. COR, 广Cp + OR^p, and thus, 127264.doc -97 - 200847056 ί=0 i:QC - ρ + Q&amp;p, or ι=Σ— i^Cp^O^p

The latter is /, there is a formula of the variable (6). This equation can be no (four) (basically up to a different solution). A ladder optimization tool can be used to get the closest solution to ^ΣΜ. ^ The present invention uses a robust scoring architecture to quantify hazard positive... When the model can produce different scoring, the result is usually phase 1. Therefore, the quantification of 逍 逍 is usually independent of the model used. , &amp; risk factors Estimated relative risk case-control studies Methods for estimating relative risk from multiple dominance rates in case-control studies are also provided in the present invention. In contrast to the sputum method, this method considers the frequency of the dual gene, the prevalence of the disease, and the relative risk of different dual genes.

Risk, dependence. The efficacy of the method of simulating a case-control study was measured, and the three tolerances were extremely accurate. Methods In the case of testing the association of a specific SNP with disease D, 11 and Ν represent the dangerous and non-hazard dual genes of this particular SNP. It is assumed that the individual is homozygous for the dangerous dual gene 'to the (four) dangerous dual gene, respectively, heterozygous or homozygous, (丨)P(RN|D) and p(NN|D) indicate the possibility of being affected by the disease, heart, fRN And fNN is used to indicate the definition of three genotypes in the population. The relative risk is defined as: 127264.doc -98- 200847056 p(d\rn) mp(d\nn) o In case-control studies, the estimated value P (RR) |D), P (RR Bu D), that is, the frequency of RR in the case and control group, and the estimated P(RN|D), P(RN|~D), P(NN|D), and P( NN Bu D), which is the frequency of RN and NN in the case and control group. To estimate the relative hazard, use Bayes law to obtain: P(RR\D)fNN ^ ' P(NN\D)fRR, p(d\rn)/nn m ' ρ{ώ\νν) /μ ο Therefore, if the frequency of genotypes is known, then we can use them to calculate relative hazards. The frequency of genotypes in the population cannot be calculated from the case-control study itself, as it is dependent on the prevalence of disease in the population. In particular, if the prevalence of the disease is p(D), then: fRR two P(M\D)p(D)+P(RR\~D)(lp(D)), fRN=P(RN\ D) p(D)+P(RN\~D)(lp(D)), fNN=P(NN\D)p(D)+P(NN\~D)(lp(D)). 127264.doc -99- 200847056 When p(D) is small enough, the frequency of genotypes can approximate the frequency of genotypes in the control population, but this is not an accurate estimate when the prevalence is high. However, given a reference set (for example, HapMap [reference]), we can estimate the genotype frequency based on this reference set. Most current studies do not use reference sets to estimate relative hazards and only report odds. The odds ratio can be written as: 〇R ^P(RR\D)P(NN\-D) M ~ P(NN\D)P(RR\- D)

〇R = P(RN\D)P(NN\-D) m ~ P(NN\D)P(RN\- D) The dominance rate is usually advantageous because cobalt with a dual gene frequency in the population is usually not required In order to calculate the odds ratio, genotype frequencies in cases and controls are usually required. In some cases, the genotype data itself is not available, but summary information such as the rate of advantage is available. This is the case for performing a meta-analysis based on the results of previous case-control studies. In this situation, it is demonstrated how the self-improvement rate is relatively dangerous. Use the following equation to hold the fact: P(D) = 4^(〇|收)+^Ρ(ϋ|ΝΝ). If this equation is divided by P(D|NN), then we get: This allowable odds ratio is written in the following way: ρΦ) (D) P(D\RR)(lP(D\NN))^ ρ(Ρ\ΝΝ P{D\NN)(lP(D\RR))^ mp(D) p(D\NN) m 127264.doc 100· 200847056 4b + fm - p(D) '朋肋一ρφ),. By similar calculations, the following equation system results are obtained: a^RR = input 跋--RR^RR ^ -^RN^RN ^ΝΝ ~ Ρ(^) fRR^ +fNN ~Ρ(〇)λκκ ORrn = ~^R ^RR ^^RN^rn Hf^ -p(D) Equation 1 If the prevalence rate, frequency, and prevalence of genotypes in a population are known, the relative risk can be obtained by solving this equation set. This should be two quadratic equations, and therefore it has a maximum of four solutions, and as shown below, there is usually one possible solution to this equation. It should be noted that when fNN = l, the equation system 丨 is equivalent to the Zhang&amp;Yu formula; however, the frequency of the dual gene in the population is considered here. In addition, our approach considers the fact that two relative hazards are dependent on each other, while previous methods recommend independent calculation of each of the relative hazards. The relative risk of multiple-dual gene loci. If multiple markers or other multi-dial variants are considered, the calculations are slightly more complicated. A0,al,··.,^ indicates possible k+Ι dual genes, where a〇 is a non-hazard dual gene. It is assumed that the frequency of the dual gene in the population of k+i possible dual genes is f〇, fi, f2, ..., & For the dual gene i, the relative risk and odds ratio are defined as: 127264.doc -101 - 200847056 1 P(D\a0) z household (4ai-/&gt;(/%)) —, an i-p(z %). The following equation applies to the prevalence of disease: Ρφ) = χ/;Ρ(%) i=0 〇 Therefore, by dividing the two sides of the equation by p(D|a〇), we get

Thereby producing:

OR Σ/Λ -p〇D) /=0 1 ---- ΣΜ-^ρ(ΰ)

By setting c = tA /=〇 by defining c, it is: The result is A, = C. __ p(D)OR^C^p(D) Therefore,

Even p{D)OR^C-p{D) This is a polynomial equation with a variable C. Once C is determined, the relative hazard is determined. The polynomial has the number of k+1, and thus we expect to have at most k+Ι solutions. However, since the right side of the equation is strictly decreasing as a function of c', usually only one solution of this equation exists. This solution is easily obtained using a binary search because the solution is limited to C=1 and 0=; /=〇 Relative risk estimate is solid. Measure each of the different parameters (population 127264.doc 200847056 rate, use 0-to-one gene frequency and odds ratio error) to estimate the relative risk and the prevalence of the relative risk for the relative risk. Role, from different odds ratios, different dual gene frequencies - group value calculation (according to HWE) relative risk, and the results of these calculations are plotted for the prevalence values in the range of 〇1. 9

In addition, for a fixed value of the prevalence rate, the relative risk of the change depending on the frequency of the dangerous _ dual gene. Obviously, in all cases, when P(D) = 0 'human rr = 0Rrr and kN = 〇 RRN, and when 〆 (7) = ι, XRR^RN = "This can be calculated directly from the equation! When the frequency of the dangerous dual gene is high, the near-linear case, and ^ is close to the concave function with bounded second derivative. When the frequency of the dangerous·dual gene is low, ^ and λΚΝ are close to the case of W/P(D). This means that for high-risk, dual gene frequencies, the erroneous estimation of prevalence does not unduly affect the relative risk of the invention. The following examples illustrate and clarify the invention. The scope of the invention is not limited by such examples.

EXAMPLE I Generation and Analysis of SNP Profiles Individuals are provided with sample tubes in kits, such as kits available from DNA Genotek, in which individuals sample saliva (about 4 ml from which genomic DNA will be extracted). The saliva sample is sent to a CLIA-certified laboratory for processing and analysis. Samples are typically sent to the facility by overnight mailing with a shipping container that is conveniently provided to the individual in the collection kit. In a preferred embodiment, genomic DNA is isolated from saliva. For example, 127264.doc 200847056, using DNA self-collection kit technology available from DNA Genotek, individuals collect about 4 ml of saliva samples for clinical treatment. After the sample is passed to the appropriate laboratory for processing, the DNA is isolated by heat denaturation of the sample and 5 minutes of death, usually by protease digestion with reagents supplied by the collection kit supplier for at least one hour. The sample was then centrifuged and the supernatant was precipitated with ethanol. The DNA pellet was suspended in a buffer suitable for subsequent analysis.

Individual genomic DNA is isolated from saliva samples according to well-known procedures and/or procedures provided by the manufacturer of the collection kit. Typically, the sample is first heat denatured and subjected to protease digestion. Next, the sample was centrifuged and the supernatant was retained. The supernatant was then precipitated with ethanol to yield a centrifugation block containing approximately 5-16 ng of genomic DNA. The DNA pellet was suspended in 1 mM THs pH 7.6, i mM EDTA (TE). The SNp profile is generated by hybridizing genomic DNA to a commercially available high density SNp array, such as an array known from Affymetrix or Ulumina, using instruments and instructions provided by the array manufacturer. The individual's SNP profile is stored in a confidential database or vault. The patient's data structure is queried for the risk-indicating SNP by comparing it to a clinically derived database of established medical-related SNPs whose presence in the genome is associated with a particular disease or condition. This database contains information on the statistical relevance of specific SNPs and SNPs to specific diseases or conditions. For example, as shown in Example m, the polymorphism of the lipoprotein £ gene produces a different isoform of the protein, which in turn is associated with the statistical likelihood of developing Alzheimer's disease. As another example, an individual having a variant of the gold coagulant factor v known as the coagulation factor V mutation has an increased tendency to coagulate 127264.doc -104 - 200847056. Many of the genes in which SNPs have been associated with disease or condition phenotypes are shown in Table 1. The information in the database is approved by the Research/Clinical Advisory Committee for its scientific accuracy and importance and can be reviewed under the supervision of government agencies. As more SNP-disease correlations emerge from the scientific community, the database is continually updated. The results of analyzing the individual's SNP profile are provided to the patient confidentially by an online portal or email. Provide explanations and supportive information to the patient, such as the information shown in Example iv for mutations in Factor V. Accessing an individual's SNP profile information, such as via an online portal, will facilitate discussion with the patient's physician and allow the individual to select personalized medicine.

Example II Update of Genotype Correlation In response to the initial determination of the genotype correlation of an individual, a Genome Profile was generated to generate genotype correlation and the results were provided to the individual as described in Example I. After initially determining the genotype correlation of an individual, then when other genotype correlations become known, it is determined or determinable to update the correlation. The user has a quality level reservation and maintains his genotype profile in a confidential database. Perform an update correlation on the stored genotype profile. For example, an initial genotype correlation such as described in Example ί above may be such that a particular individual does not have Αρ〇Ε4 and therefore does not favor early-onset Alzheimer's disease, and the individual does not have coagulation Factor V mutation. After this initial decision, the 'new correlation' can become known and confirmed so that the polymorphism of a given gene (hypothetical gene χυζ) is associated with a specific condition (hypothetical condition 321). Add this new genotype correlation to the core of the human genotype correlation 127264.doc -105- 200847056. The update is then provided to the particular individual by first retrieving the relevant gene XYZ data from the genomic profile of the particular individual stored in the confidential database. The XYZ data of the relevant gene of a particular individual is compared with the updated master database information of the gene XYZ. From this comparison, the susceptibility or genetic predisposition of a particular individual to the condition 3 21 was determined. The result of this determination is added to the genotype correlation of a particular individual. The specific individual is provided with an updated result of whether the particular individual is susceptible or genetically predisposed to the condition 321 , as well as explanatory and supporting information.

Example III ® Correlation of the ApoE4 Locus with Alzheimer's Disease The risk of Alzheimer's disease (AD) has been implicated in the polymorphism of the lipoprotein E (APOE) gene, which produces APOE Three isoforms, called ApoE2, ApoE3, and ApoE4. The equivalent work is different from each other due to one of the residues 112 and 158 or two amino acids in the APOE protein. ApoE2 contains 112/1 58 cys/cys; ApoE3 contains 112/1 58 cys/arg; and ApoE4 contains 112/1 5 8 arg/arg. As shown in Table 3, the risk of developing Alzheimer's disease at an earlier age increases with an increase in the number of APOE ε4 gene copies. Similarly, as shown in Table 3, the relative risk of AD increases as the number of APOE ε4 gene replicas increases. Table 3: Prevalence of AD dangerous dual genes (Corder et al, Sc/wce. 261: 921-3, 1993) APOE ε4 Replica prevalence Alzheimer's disease risk episode age 0 73% 20% 84 1 24 % 47% 75 2 3% 91% 68 127264.doc • 106 - 200847056 Table 4: Relative risk of AD with ApoE4 (Farrer et al., 丄 4ΜΑ· 278:1349-56, 1997) ΑΡΟΕ genotype odds ratio ε2ε2 0.6 Ε2ε3 0.6 ε3ε3 1.0 ε2ε4 2.6 ε3ε4 3.2 ε4ε4 14.9

EXAMPLE IV Information for Coagulation Factor V Mutant Positive Patients The following information is illustrative of information available to individuals with a genomic SNP profile displaying a gene with a Factor V mutation. Individuals may have a base reservation in which information may be available in an initial report format. What is the clotting factor V mutation? A clotting factor V mutation is not a disease, it is the presence of a specific gene transmitted from a parent of a person. Factor V mutation is a variant of protein factor V (5) required for blood coagulation. People who are deficient in factor V are likely to have severe bleeding, while blood with a person with a factor V mutation has an increased tendency to coagulate. People with a coagulation factor V mutation are five times more likely to develop a blood clot (thrombotic disease) than others in the group. However, many people with this gene will not suffer from blood clots. In the United Kingdom and the United States, 5% of the population carries one or more genes for Factor V mutations, far more than the number of people who will actually have thrombosis. How do you get a clotting factor V mutation? The gene of factor V is passed down from the parents of someone. As with all genetics 127264.doc -107- 200847056 levy--a gene is inherited from the mother and one is inherited from the father. Therefore, it is possible to inherit: two normal genes, or one coagulation factor v mutant gene and one normal gene' or two coagulation factor 乂 mutant genes. Having a coagulation factor v mutant gene will produce a slightly higher risk of developing thrombosis but having two genes makes the risk much higher. What are the symptoms of the clotting factor V mutation? No signs ‘ unless you have a blood clot (blood test). What is a dangerous signal? Take the common problem for the blood clots in the legs. This problem is indicated by the legs becoming swollen, painful and red. In rare cases, pulmonary blood clots (pulmonary thrombosis) may occur, making breathing difficult. Depending on the size of the blood clot, this can vary within the range that only draws attention to the patient experiencing severe breathing difficulties. In even rarer cases, a clot may be present in the arm or another part of the body. Since the clots are formed in the veins that carry blood into the heart rather than the arteries that carry blood out of the heart, the coagulation factor v mutation does not increase the risk of coronary blood test. What can be done to avoid blood clots? Coagulation factor V mutations only slightly increase the risk of developing a blood clot and many people with this condition will not experience thrombosis. We can do a lot to avoid clots. Avoid standing or sitting in the same position for a long time. When traveling long distances, it is important to exercise regularly, blood can't be static, and overweight or smoking will greatly increase the risk of blood clots. Women with clotting factor V mutations should not take birth control pills because this will Significantly increase the chance of developing thrombosis. Women with clotting factor V mutations should also consult their doctor before conception 127264.doc -108- 200847056, as this may increase the risk of thrombosis. How do doctors discover if you have Coagulation factor v mutations? Genes of coagulation factor V mutations can be found in blood samples. Blood clots in the legs or arms can usually be detected by ultrasound examination. They can also be injected into the blood to make the clots stand out. Clots are detected by x-rays. Pulmonary blood clots are difficult to detect, but usually doctors will use radioactive materials to test the distribution of blood flow in the lungs and the distribution of air in the lungs. The two modes should match, and the mismatch indicates the clot. The presence of clotting factor V mutations? People with clotting factor V mutations do not need treatment unless their blood begins to produce clots, in which case The doctor will prescribe a blood-dilution (anticoagulant) drug such as warfarin (such as Marevan) or heparin to prevent further clots. Treatment will usually last for three to six months, but if there are several clots It can take longer. In severe cases, the process of drug treatment can be repeated indefinitely. In rare cases, blood clots may need surgical removal. How to treat clotting factor V mutation during pregnancy? A woman with a coagulation factor V mutation will need to be treated with a heparin coagulant drug during pregnancy. The same applies to a woman with only one coagulation factor V mutation, a previous blood clot, or a family history of blood clots. All women with coagulation factor v mutations may need to wear special stockings to prevent clots during the last half of pregnancy. After the child is born, he can prescribe anticoagulant heparin. 127264.doc 109- 200847056 Prognosis produces coagulation The risk of the block increases with age, but only a few of those who have been over 100 years old with the gene have been found to have thrombosis. The National Society for Genetic Counselors (nsgc) can provide a list of genetic counselors in your area, as well as a poor family history. Search for an online database at www.nsgc.org/consumer. The preferred embodiment has been shown and described herein, but it will be apparent to those skilled in the art that the embodiments are provided by way of example only. It is to be understood that various alternatives to the embodiments of the invention described herein may be used to practice the invention. The scope of the invention is intended to be Methods and structures within the scope of the invention. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a flow chart illustrating the method aspect of the present invention. Figure 2 is an example of genomic DNA quality control measurement. Figure 3 shows an example of the quality control measurement of the parent. Figure 4 is a table from the published literature with representative genotype correlations for testing § Νρ and effect estimates. Α·υ indicates genotype correlation of single-locus; j) indicates genotype correlation of two loci; κ) indicates genotype correlation of three loci; L) is race and country for Α_κ The abbreviation ^ index; Μ) is the index of the abbreviations, heritability and heritability of short phenotype names in Α·Κ. Figures 5A-J are tables of representative genotype correlations with effect estimates. 127264.doc -110- 200847056 Figure 6A-F is a table of representative genotype correlations and estimated relative hazards. Figure 7 is a sample report. Figure 8 is a schematic illustration of a system for analyzing and transporting a port group and phenotype profile via a network. Figure 9 is a flow chart illustrating the aspect of the business method herein. Figure 10: The effect of estimates of prevalence on relative risk estimates. The parent® table corresponds to a different value for the frequency of the dual gene in the population under the assumed Hardy-Weinberg Equilibrium. The two black lines correspond to the odds ratios of 9 and 6, the two red lines correspond to the 4, and the two blue lines correspond to the odds ratios of 3 and 2. Figure 11: Effect of the estimation of the frequency of the dual gene on the relative risk estimate. Each - chart corresponds to a different value of the prevalence in the population. The two black lines correspond to the odds ratios of 9 and 6. 'Two red lines correspond to 6 and 4, and the two blue lines correspond to the odds ratios of 3 and 2. Figure 12: Pairwise comparison of the absolute values of different models. Figure 13: Pairwise comparison of grading values (GCI scores) based on different models. The Spearman correlation (Spearman c_lati〇n) between the different pairs is given in Table 2. Figure 14: The effect of the prevalence report on GCI scoring. The Spearman correlation between any two prevalence values is at least 0.99. Figure 15 is a legend of a sample web page from a personalized portal. Figure 16 is a legend of a sample web page from a personalized portal for the risk of prostate cancer in an individual. Figure 17: A sample web page from a personalized portal for individuals with a risk of Crohn's 127264.doc -111 - 200847056 disease. Figure 18 is a histogram of GCI scores for multiple malignancies using two SNPs based on HapMAP. Figure 19 is a graph showing the lifetime risk of individuals with multiple sclerosis using GCI Plus. Figure 20 is a histogram of the GCI score for Crohn's disease. Figure 21 is a table of correlations for multiple loci. Figure 22 is a table of SNP and phenotypic correlation. Figure 23 is a table of phenotypes and prevalence rates. Figure 24 is a glossary of the abbreviations in Figures 21, 22 and 25. Figure 25 is a table of SNP and phenotypic correlation. [Main component symbol description] 800 801 803 805 807 809 Computer system (or digital device) CPU drive Network 珲 Optional monitor Server 811, 812 Media 815 Keyboard 816 Mouse 822 Each other 127264.doc

Claims (1)

200847056 X. Patent application scope: 1 · A method for assessing the genotype correlation of an individual, comprising: a) obtaining a genetic sample of the individual; b) generating a genomic profile of the individual; c) by comparing the The current database of individual genome profiles and human genotypes and phenotypes to determine the genotype and phenotype of the individual; d) report to the individual or the individual's health care manager, step c) ❿ these results; e) updating the human genotype correlation database with the other human genotype correlation when another human genotype correlation becomes known; and f) by comparing step c) The genomic profile of the individual or a portion thereof is associated with the other human genotype to update the genotype of the individual and to determine another genotype correlation of the individual; and g) to the individual or the individual The health care manager reports the results of step f). 2. The method of claim 1, wherein the third party obtains the genetic sample. 3. The method of claim 1 wherein the generation of the genomic profile is achieved by a third party. 4. 4. The method of claim 1, wherein the results are scored based on GCI or GCI Plus. 5. The method of claim 1, wherein the report includes the method of transmitting the results via the network 〇 127264.doc 200847056 6 · the method of claim 1, wherein the report of the results is via one, owing to the portal ( 〇n]ine portal) reached. 7. The method of claim 1, wherein the report of the results is achieved by paper or by e-mail. 8. The method of claim 1, wherein the report includes reporting the results in a confidential manner. 9. The method of claim 1, wherein the report includes reporting the results in a non-confidential manner. 1. The method of claim 1, wherein the individual's genomic profile is stored in a confidential database or vault. The method of claim 1, wherein the individual is a subscriber (12), such as a method of requesting an item, wherein the individual is not a user. The method of claim 1, wherein the genetic sample is Dna. 14. The method of claim 1, wherein the genetic sample is RNA. 1 5 · The method of claim ,, wherein the genomic profile is a single nucleotide polymorphism (p〇lym〇rphism) genome profile, and the human genotype correlation is a single nucleotide State phenomenon correlation, the other human base-type correlation is a single nucleotide polymorphism correlation. 16. The method of J.J.J.J., wherein the genomic profile comprises a load, a deletion of the age of the plug, or a copy of the human genotype correlation is human, broken, inserted, deleted or repetitive, the other _ Relevance is wear, insertion, deletion or repeated correlation. , soil type-type quest k method 'where the genomic profile genome genome profile. i 127264.doc 200847056 1 8 · The method of Ί眚炎1, wherein the method comprises evaluating two or more genotype correlations. 19 士士士主 ^ Ming's method of item 1, where the method involves assessing one or more than one genotype correlation. 20. The method of item 1, wherein the human genotype correlation database: has genetic variants of one or more of the genes listed in Table 1 and phenotypes associated with the genetic variants. 21. The method of claim 1, wherein the human genotype correlation database - has genetic variants and/or genetic variants of one or more of the genes listed in Figure 4, Figure 5, Figure 6, Figure 22, or Figure 25. The phenotype associated with these genetic variants. The method of claim 1, wherein the human genotype correlation database 3 has genetic variants determined from the genome profiles of the individuals and a previously determined phenotype revealed by the individuals. The method of claim 1, wherein the human genotype correlation database has a single nucleotide of each of the genes listed in Table 1 or Figure 4, Figure 5, Figure 0, Figure 22 or Figure 25. State phenomena and phenotypes associated with such single nucleotide polymorphisms. The method of claim 1, wherein the genetic sample is from a biological sample selected from the group consisting of blood, hair, skin, saliva, semen, urine, fecal matter, sweat, and buccal samples. 25. The method of claim 15, wherein the genotype correlation is a correlation between a single nucleotide polymorphism and a disease or condition. 26' The method of claim 15, wherein the genotype correlation is a correlation between a single nucleotide stagnation phenomenon and a phenotype of a non-medical condition. 27. The method of claim </RTI> wherein the genomic profile is generated using a high density DNA microarray. 28. A method of seeking a sputum in May, wherein the genomic profile is generated using genomic DNA sequencing. The method of claim 24, wherein the genetic sample is a genome and the biological sample is saliva. 3. A method comprising: a) providing a set of rules comprising rules, each rule indicating a correlation between at least one genotype and at least one phenotype; b) providing each of the plurality of individuals a set of genomic profiles, wherein each genomic profile comprises a majority of genotypes; 0 periodically updating the set of rules with at least one new rule, wherein the at least one new rule indicates a genotype and a table that were not previously related to each other in the set of rules Correlation between types; and d) applying each new rule to the genomic profile of at least one of the individuals, thereby correlating at least one genotype of the individual with at least one phenotype. 3 1 • The method of claim 3, further comprising: e) generating a report containing the phenotypic profile of the individual. 32. The method of claim 30, further comprising, after step (b): 1) applying the rules of the set of rules to the genomic profiles of the individuals to determine phenotypic profiles of the individuals And ii) generate a report containing an overview of the individual's initial phenotype. 33. The method of claim 31 or 32, wherein providing the report comprises transmitting the report via the network 127264.doc -4 - 200847056. 34. If the method of claim 31 or 32 is provided, the eight-pass M-port is provided by you in a secret manner. 35. The method of claim 31 or 32, wherein the report is provided in a non-confidential manner. The report is via an online entry into the report by paper or electronic. 36. The method of claim 31 or 32, wherein the report is provided . 37. The method of claim 31 or 32, wherein the mail is provided. A method of claim 30 wherein the new rule relates an unrelated genotype to a phenotype. 39. The method of claim 30, wherein the new rule relates a related genotype to a previously unrelated phenotype in the set of rules. 4. The method of claim 30, wherein the new rule modifies one of the rules in the set of rules. The method of claim 30, wherein the new rule is generated by correlation of the genotypes of the individuals of the genomes with the previously determined phenotypes of the individuals. 1] The method of claim 30 wherein the rules relate a majority of the genotype to a phenotype. 43. The method of claim 30, wherein applying the new rule further comprises determining the at least in part based on the individual selected from the group consisting of race, genealogy, (4), sex/age, family history, and previously determined phenotype Phenotype 127264.doc 200847056 44. The method of claim 3, wherein the genotype comprises a nucleotide repeat, a nucleotide insertion, a nucleotide deficiency, a chromosomal translocation, a chromosome repeat, or a copy number (copy number) variation. The method of claim 44, wherein the plurality of copies are microsatellite repeated nuclear I repeats, centromeric repeats, or telomeric repeats. 46. The method of claim 3, wherein the genotype comprises a mononuclear acid polymorphism. 47. The method of claim 3, wherein the genotypes comprise a single type (four) kiss (four) and a double type (diplotypes). 48. The method of claim 3, wherein the genotypes comprise a linkage disequilibrium between the genetic markers and a single nucleotide polymorphism associated with a phenotype. 49. The method of claim 30, wherein the phenotypic profile indicates the presence or absence of the quantitative trait or the risk of the quantitative trait. The method of claim 30, wherein the phenotypic profile indicates the likelihood that an individual having a gene i has or will have a phenotype. 51. The method of claim 50, wherein the likelihood is based on 0 (^ or GCI Plus scoring. 52. The method of claim 5, wherein the probability is an estimated life risk. 53. The method of item 3, wherein the correlations are curated. For example, the method of the monthly claim 3G 'where the rule set contains at least: the sacrificial rule. 55. The method of claim 30, wherein the rule set includes At least 5 rules. 56. The method of claim 30, wherein the rule set comprises rules based on the genotype correlations in Table i. 127264.doc 200847056 57. The method of claim 3G, wherein the rule (4) A method comprising the correlation of the genotypes based on Figure 4, Figure 5, Figure 6, Figure 22 or Figure 25. The method of claim 30, wherein the phenotype comprises a quantitative trait. The method of claim 59, wherein the phenotypic profile indicates the presence or absence of the medical condition, the risk of developing the medical condition, and the prognosis of the medical condition / treatment of the effectiveness of the medical condition, or the medical The method of claim 58. The method of claim 58, wherein the quantitative trait comprises a phenotype of a non-medical condition. 62. The method of claim 58, wherein the quantitative trait is selected from the group consisting of Physical traits, physiological traits, psychological traits, emotional traits, races, genealogy, or age. 63. The method of claim 30, wherein the individuals are humans. 64. The method of claim 30, wherein the individuals are 65. The method of claim 30, wherein the individual is a user. 66. The method of claim 30, wherein the individual is not a user. 67. The method of claim 30, wherein the genome The method comprises at least one genotype. The method of claim 30, wherein the genomic profile comprises at least 4 〇〇, genotypes. 69. The method of claim 30, wherein the genomic profile comprises at least The method of claim 30, wherein the genomic profile comprises at least 127264.doc 200847056 1,000 5000 genotypes. 71. The method of claim 30, wherein the genome General A method comprising substantially the entire genome sequence. 72. The method of claim 30, wherein the data set comprises a plurality of data points, wherein each of the poor points is associated with a body; and a plurality of data elements, wherein the data elements comprise At least one element selected from the group consisting of: the individual's unique signature, genotype information, microarray SNp identification number, SNP rs number, chromosomal location, polymorphic nucleotides, quality metrics, raw shell file, image, extraction intensity Scoring, physical data, medical data, species, genealogy, geography, gender, age, family history, known demographics, exposure (exp0sure) data, lifestyle data, and behavioral data. 73. The method of seeking the item 30, which is regularly updated and applied at least once a year. 74. The method of claim 30, wherein the providing the data set comprises obtaining a genome profile of each of the plurality of individuals by: (i) performing genetic analysis of the genetic samples of the individuals, and (ii) The analysis is encoded in a readable format. 76. The method of claim 30, the method of claim 30, the method of claim 30, the method of claim 30, the method of claim 30, the method of claim 30, the method of claim 30, wherein the phenotype profile comprises a single gene Phenotype. The following information based on the phenotypic profile of the phenotype profile: the phenotype of the phenotype: the prevention strategy, wherein the phenotypic profile comprises a multi-gene phenotype. The report contains an overview of the initial phenotype. The report contains an updated phenotype profile. Wherein the report further comprises an improved identification and sub-scores of the phenotypes selected from one or more of 127264.doc 200847056 health information, therapy, symptom understanding, early detection protocols, intervention protocols, and phenotypic profiles. The method of claim 30, further comprising: e) adding a new genomic profile of the new individual to the individual data set, f) applying the rule set to the genomic profile of the new individual; and g) generating the Initial report of the phenotypic profile of the new individual. 81. The method of claim 30, comprising: e) adding a new genomic profile of the individual; 0 applying the rule set to the new genomic profile of the individual; and g) generating a new report of the phenotypic profile of the individual . 82. A system comprising: a) a set of rules comprising rules, each rule indicating a correlation between at least one genotype and at least one phenotype; b) periodically updating the rule set with at least one new rule a code, wherein the at least one new rule indicates a correlation between a genotype and a phenotype that were not previously related to each other in the rule set; c) a database containing a genome profile of a majority of individuals; d) applying the rule set The genomic profiles of the individuals to determine the phenotypic profile of the individuals; and e) the code that produces the reports for each individual. The system of claim 8 wherein the report is transmitted via the network. 84. The system of claim 82, wherein the report is provided in a confidential manner. Monthly proposal 8 2 ’ 其中 where the report was provided in a non-confidential manner. 127264.doc 200847056 86. The system of claim 82, wherein the report is provided via an online portal. 7. The system of claim 82 wherein the report is provided by paper or email. 88. The system of claim 82, further comprising code to inform the individual of new or revised relevance. 89. The system of claim 82, further comprising code to inform the individual of new or revised rules applicable to the genomic profile of the individual. 90. The system of claim 82, further comprising code for informing the individual about new or revised prevention and health information about the phenotype of the phenotypic profile of the individual. 91. A kit comprising: a) at least one sample collection container; b) instructions for obtaining a sample from an individual; c) an indication of the genomic profile of the individual obtained from the sample by an online portal; d) via The inline access accesses a description of the phenotypic profile of the individual obtained from the sample; and e) a package for delivering the sample collection container to the sample processing facility. 92. An online portal (on_iine p〇rtal) comprising a website for an individual to access a saidir phenotype profile wherein the website allows the individual to perform at least one of: a) selecting a genomic profile to be applied to the individual These rules; b) view the initial report and update report on the website; 127264.doc -10· 200847056 C) print the initial report and update report from the website; d) store the initial report and update report from the website In the individual's computer; e) obtaining prevention and health information about the individual's phenotypic profile; f) obtaining an online or telephone connection for genetic counseling; g) extracting information for sharing with a physician/genetic consultant; and/or h) accessing Partner service and product offering. 93. The online portal of claim 92, wherein the information is transmitted via the network. 94. The online entry of claim 92, wherein the website is confidential. 95. As requested in line 92, the website is not confidential. 96. The online portal of claim 92, wherein the individual is provided with one or more options for the level of security of the individual or one or more portions thereof. 97. The online entry of claim 92, wherein the phenotypic profile comprises a medical condition that is functional. 98. The online entry of claim 92, wherein the phenotypic profile comprises a medical condition without existing precautions or existing therapies. 99. The online entry of claim 92, wherein the phenotypic profile comprises a non-medical condition. 100. A method for assessing an individual's risk of developing a condition comprising: a) obtaining an individual's genotype; b) determining a GCI or GCIPlus score from the genotype; c) generating a report from the GCI or GCI Plus score And d) providing the report to the individual or the individual's health care manager. 127264.doc -11- 200847056 101 - A method for assessing an individual's risk of developing a condition comprising: a) obtaining an individual's genotype; b) generating a genomic profile of the individual; c) from the genomic profile and genotype A database of correlations to determine the risk of an individual suffering from a condition; d) from c) generating a report; e) obtaining new information from the individual; f) determining a new risk of developing a condition by combining the new information; From f) generating a report; and h) providing the report to the individual or the individual's health care manager. 102. A method of assessing an individual's risk of developing a condition, comprising: a) obtaining an individual's genotype; b) generating a genomic profile of the individual; c) determining the individual from the genomic profile and the genotype-related database The risk of developing a condition based on more than one SNP; d) generating a report from c); appealing to e) providing the report to the individual or the health care manager of the individual. 103. The method of claim 100, 101 or 1 wherein the genotype of the individual is obtained directly from the individual. 104. The method of claim 100, 101 or 102, wherein the genotype of the individual is obtained from a third party. 105. The method of claim 100, 101 or 102, wherein the providing is achieved via a network transfer. 106. The method of claim ι〇1, wherein the new information is obtained from the individual 127264.doc -12- 200847056 sample. 107. The method of claim 101, wherein the new information is obtained from an individual's physical measurements. 108. The method of claim 101 or 102, wherein the hazard is derived from a GCI or GCI Plus score. 109. The method of claim 100 or 108, wherein the GCI or GCI Plus scores and has a family tree of the individual. 110. The method of claim 100 or 108, wherein the 〇(:1 or (}(:;11&gt;1118 scores and has the gender of the individual. 111. The method of claim 100 or 108, wherein the (:1 or 〇(::11&gt;11^ scores and has the individual-specific factor, wherein the factors are not derived from the genotype. 112. The method of claim 111, wherein the factors are selected from the individual Groups consisting of: birthplace, parents and/or grandparents, relatives' genealogy, place of residence, ancestral residence, environmental conditions, known health status, known drug interactions, family health status, lifestyle status, diet, The method of claim 107 or 112, wherein the physical measurement of the individual is selected from the group consisting of: gold pressure, heart rate, glucose content, generation 5 Contains 1, ion content, body weight, height, cholesterol content, vitamin content, blood cell count, body mass index (BMI), protein content, and transcript content. 114. A method for assessing the risk of an individual suffering from a condition , which comprises: a) obtaining the genotype of the individual; 127264.doc -13· 200847056 b) generating the genomic profile of the individual; c) determining the individual suffering from Alzheimer's disease (AD), colorectal cancer (CRC) , the risk of osteoarthritis (OA), or exfoliative glaucoma (XFG), which is based on the following: AD is rs4420638, CRC is rs6983267, OA is rs4911178, XFG is rs2165241; d) report from c) e) providing the report to the individual or the individual's health care manager. 115. The method of claim 102, wherein the hazard is determined from at least 3, 4, 5, 6, 7, 8, 9, 10 or 11 SNPs. 116. The method of claim 102, wherein the hazard is determined from at least two SNPs. The method of claim 116, wherein the risk is determined for obesity (BMIOB), and at least one of the at least two SNPs is rs9939609 or rs9291171 〇118. The method of claim 116, wherein the risk is directed to Graves Disease (GD) determines that at least one of the at least two SNPs is rs3087243, DRB1*0301 DQA1*0501, or is in linkage disequilibrium with DRB1*0301 DQA1*0501. 119. The method of claim 116, wherein the risk is determined for hemochromatosis (HEM) and at least one of the at least two SNPs is rsl800562 or rsl29128. 120. The method of claim 116, wherein the risk is determined for myocardial infarction (MI), and at least one of the at least two SNPs is rsl 866389, 127264.doc-14/200847056 rsl333049 or rs6922269. 121. The method of claim 116, wherein the risk is determined for multiple sclerosis (MS) and at least one of the at least two SNPs is rs6897932, rsl2722489 or DRB1*1501. The method of claim 116, wherein the risk is determined for psoriasis (PS), and at least one of the at least two SNPs is rs6859018, rsll209026 or HLAC*0602 〇 123. The risk is determined for restless legs syndrome (RLS) and at least one of the at least two SNPs is rs6904723, rs2300478, rsl026732 or rs9296249. 124. The method of claim 116, wherein the risk is determined for celiac disease (CelD) and at least one of the at least two SNPs is rs6840978, rsll571315, rs2187668 or DQA1*0301 DQB1*0302. 125. The method of claim 116, wherein the risk is determined for prostate cancer (PC), and at least one of the at least two SNPs is rs4242384, rs6983267, rsl6901979, rsl7765344, or rs4430796 〇 126. The method wherein the risk is determined for lupus (SLE) and at least one of the at least two SNPs is rsl2531711, rsl0954213, rs2004640, DRB1*0301 or DRB1*1501. The method of claim 116, wherein the risk is determined for macular degeneration (AMD), and at least one of the at least two SNPs is rsl0737680, rsl0490924, rs541862, rs2230199, rsl061170 or rs9332739 〇128. The method of 116, wherein the risk is determined for rheumatoid joint 127264.doc -15- 200847056 inflammation (RA), and at least one of the at least two SNPs is rs6679677, rsll203367, rs6457617, DRB*0101, DRB 1 *0401 or DRB 1*0404. 129. The method of claim 116, wherein the risk is determined for breast cancer (BC), and at least one of the at least two SNPs is rs3803662, rs2981582, rs4700485, rs3817198, rsl7468277, rs6721996 or rs3803662. 130. The method of claim 116, wherein the risk is determined for Crohn's disease (Crohn, disease, CD), and at least one of the at least two SNPs is rs2066845, rs5743293, rsl0883365, rsl7234657, rsl0210302, Rs9858542, rsll805303, rsl000113, rsl7221417, rs2542151 or rsl0761659. The method of claim 116, wherein the risk is determined for type 2 diabetes (T2D), and at least one of the at least two SNPs is rsl3266634, rs4506565, rsl0012946, rs7756992, rsl0811661, rsl2288738, rs8050136, rsllll875 , rs4402960, rs5215 or rsl801282 〇127264.doc -16-