CN113718026A - Reagent and product for diagnosing diabetic nephropathy disease and application thereof - Google Patents
Reagent and product for diagnosing diabetic nephropathy disease and application thereof Download PDFInfo
- Publication number
- CN113718026A CN113718026A CN202111021406.4A CN202111021406A CN113718026A CN 113718026 A CN113718026 A CN 113718026A CN 202111021406 A CN202111021406 A CN 202111021406A CN 113718026 A CN113718026 A CN 113718026A
- Authority
- CN
- China
- Prior art keywords
- tnfaip6
- diabetic nephropathy
- runx3
- runx
- sample
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 208000007342 Diabetic Nephropathies Diseases 0.000 title claims abstract description 69
- 208000033679 diabetic kidney disease Diseases 0.000 title claims abstract description 68
- 239000003153 chemical reaction reagent Substances 0.000 title claims abstract description 20
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title description 8
- 101000847156 Homo sapiens Tumor necrosis factor-inducible gene 6 protein Proteins 0.000 claims abstract description 65
- 102100032807 Tumor necrosis factor-inducible gene 6 protein Human genes 0.000 claims abstract description 65
- 108010079362 Core Binding Factor Alpha 3 Subunit Proteins 0.000 claims abstract description 44
- 239000000090 biomarker Substances 0.000 claims abstract description 20
- 102000012666 Core Binding Factor Alpha 3 Subunit Human genes 0.000 claims abstract 9
- 108090000623 proteins and genes Proteins 0.000 claims description 48
- 239000000523 sample Substances 0.000 claims description 34
- 230000014509 gene expression Effects 0.000 claims description 33
- 102000004169 proteins and genes Human genes 0.000 claims description 26
- 239000012502 diagnostic product Substances 0.000 claims description 12
- 230000003321 amplification Effects 0.000 claims description 11
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 11
- 239000011230 binding agent Substances 0.000 claims description 10
- 150000007523 nucleic acids Chemical class 0.000 claims description 10
- 238000012163 sequencing technique Methods 0.000 claims description 10
- 210000004369 blood Anatomy 0.000 claims description 8
- 239000008280 blood Substances 0.000 claims description 8
- 238000004422 calculation algorithm Methods 0.000 claims description 7
- 102000039446 nucleic acids Human genes 0.000 claims description 6
- 108020004707 nucleic acids Proteins 0.000 claims description 6
- 238000001514 detection method Methods 0.000 claims description 5
- 238000003766 bioinformatics method Methods 0.000 claims description 4
- 239000003795 chemical substances by application Substances 0.000 claims description 4
- 238000005094 computer simulation Methods 0.000 claims description 4
- 238000007899 nucleic acid hybridization Methods 0.000 claims description 4
- 238000002360 preparation method Methods 0.000 claims description 4
- 230000003053 immunization Effects 0.000 claims description 3
- 238000002649 immunization Methods 0.000 claims description 3
- 239000000203 mixture Substances 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 238000010276 construction Methods 0.000 claims description 2
- 238000009472 formulation Methods 0.000 claims 1
- 238000003745 diagnosis Methods 0.000 abstract description 15
- 230000001105 regulatory effect Effects 0.000 abstract description 2
- 238000003759 clinical diagnosis Methods 0.000 abstract 1
- 102100025369 Runt-related transcription factor 3 Human genes 0.000 description 34
- 238000000034 method Methods 0.000 description 26
- 238000004458 analytical method Methods 0.000 description 9
- 238000005516 engineering process Methods 0.000 description 9
- 238000012549 training Methods 0.000 description 9
- 239000003550 marker Substances 0.000 description 8
- 210000001519 tissue Anatomy 0.000 description 8
- 206010027525 Microalbuminuria Diseases 0.000 description 7
- 239000000047 product Substances 0.000 description 7
- 210000004027 cell Anatomy 0.000 description 6
- 108020004414 DNA Proteins 0.000 description 5
- 206010012601 diabetes mellitus Diseases 0.000 description 5
- 201000010099 disease Diseases 0.000 description 5
- 238000013399 early diagnosis Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 238000007619 statistical method Methods 0.000 description 5
- 238000010200 validation analysis Methods 0.000 description 5
- 239000000872 buffer Substances 0.000 description 4
- 239000000306 component Substances 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 238000003018 immunoassay Methods 0.000 description 4
- 238000007477 logistic regression Methods 0.000 description 4
- 239000002773 nucleotide Substances 0.000 description 4
- 125000003729 nucleotide group Chemical group 0.000 description 4
- 238000012216 screening Methods 0.000 description 4
- 230000035945 sensitivity Effects 0.000 description 4
- 108091028043 Nucleic acid sequence Proteins 0.000 description 3
- 230000002255 enzymatic effect Effects 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 230000001575 pathological effect Effects 0.000 description 3
- 102000040430 polynucleotide Human genes 0.000 description 3
- 108091033319 polynucleotide Proteins 0.000 description 3
- 239000002157 polynucleotide Substances 0.000 description 3
- 230000002441 reversible effect Effects 0.000 description 3
- 239000007787 solid Substances 0.000 description 3
- 238000012795 verification Methods 0.000 description 3
- 108091032973 (ribonucleotides)n+m Proteins 0.000 description 2
- 238000002965 ELISA Methods 0.000 description 2
- 101100476219 Homo sapiens RUNX3 gene Proteins 0.000 description 2
- 102000004856 Lectins Human genes 0.000 description 2
- 108090001090 Lectins Proteins 0.000 description 2
- 239000012472 biological sample Substances 0.000 description 2
- 238000001574 biopsy Methods 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 208000020832 chronic kidney disease Diseases 0.000 description 2
- 230000002596 correlated effect Effects 0.000 description 2
- 230000000875 corresponding effect Effects 0.000 description 2
- 230000009977 dual effect Effects 0.000 description 2
- 201000000523 end stage renal failure Diseases 0.000 description 2
- 239000012634 fragment Substances 0.000 description 2
- 239000011521 glass Substances 0.000 description 2
- 230000024924 glomerular filtration Effects 0.000 description 2
- 238000007901 in situ hybridization Methods 0.000 description 2
- 239000002523 lectin Substances 0.000 description 2
- 238000007834 ligase chain reaction Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 238000005192 partition Methods 0.000 description 2
- 210000002381 plasma Anatomy 0.000 description 2
- 238000003752 polymerase chain reaction Methods 0.000 description 2
- 108090000765 processed proteins & peptides Proteins 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000004393 prognosis Methods 0.000 description 2
- 201000001474 proteinuria Diseases 0.000 description 2
- 238000003127 radioimmunoassay Methods 0.000 description 2
- 238000007637 random forest analysis Methods 0.000 description 2
- 238000000611 regression analysis Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000003757 reverse transcription PCR Methods 0.000 description 2
- 239000000758 substrate Substances 0.000 description 2
- 238000003786 synthesis reaction Methods 0.000 description 2
- 230000001225 therapeutic effect Effects 0.000 description 2
- HVCOBJNICQPDBP-UHFFFAOYSA-N 3-[3-[3,5-dihydroxy-6-methyl-4-(3,4,5-trihydroxy-6-methyloxan-2-yl)oxyoxan-2-yl]oxydecanoyloxy]decanoic acid;hydrate Chemical compound O.OC1C(OC(CC(=O)OC(CCCCCCC)CC(O)=O)CCCCCCC)OC(C)C(O)C1OC1C(O)C(O)C(O)C(C)O1 HVCOBJNICQPDBP-UHFFFAOYSA-N 0.000 description 1
- 108090001008 Avidin Proteins 0.000 description 1
- 208000037157 Azotemia Diseases 0.000 description 1
- 238000008157 ELISA kit Methods 0.000 description 1
- 102000004190 Enzymes Human genes 0.000 description 1
- 108090000790 Enzymes Proteins 0.000 description 1
- 208000022461 Glomerular disease Diseases 0.000 description 1
- 229930186217 Glycolipid Natural products 0.000 description 1
- 101000857685 Homo sapiens Runt-related transcription factor 3 Proteins 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- 238000000636 Northern blotting Methods 0.000 description 1
- 101710163270 Nuclease Proteins 0.000 description 1
- 206010030113 Oedema Diseases 0.000 description 1
- 238000011529 RT qPCR Methods 0.000 description 1
- 208000001647 Renal Insufficiency Diseases 0.000 description 1
- 238000002105 Southern blotting Methods 0.000 description 1
- 108010090804 Streptavidin Proteins 0.000 description 1
- 101150012560 TNFAIP6 gene Proteins 0.000 description 1
- 101710169430 Tumor necrosis factor-inducible gene 6 protein Proteins 0.000 description 1
- LEHOTFFKMJEONL-UHFFFAOYSA-N Uric Acid Chemical compound N1C(=O)NC(=O)C2=C1NC(=O)N2 LEHOTFFKMJEONL-UHFFFAOYSA-N 0.000 description 1
- TVWHNULVHGKJHS-UHFFFAOYSA-N Uric acid Natural products N1C(=O)NC(=O)C2NC(=O)NC21 TVWHNULVHGKJHS-UHFFFAOYSA-N 0.000 description 1
- 229930003316 Vitamin D Natural products 0.000 description 1
- QYSXJUFSXHHAJI-XFEUOLMDSA-N Vitamin D3 Natural products C1(/[C@@H]2CC[C@@H]([C@]2(CCC1)C)[C@H](C)CCCC(C)C)=C/C=C1\C[C@@H](O)CCC1=C QYSXJUFSXHHAJI-XFEUOLMDSA-N 0.000 description 1
- 239000000654 additive Substances 0.000 description 1
- 230000000996 additive effect Effects 0.000 description 1
- 239000002220 antihypertensive agent Substances 0.000 description 1
- 229940127088 antihypertensive drug Drugs 0.000 description 1
- 239000003124 biologic agent Substances 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 102000043871 biotin binding protein Human genes 0.000 description 1
- 108700021042 biotin binding protein Proteins 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 239000012503 blood component Substances 0.000 description 1
- 230000036772 blood pressure Effects 0.000 description 1
- 210000001124 body fluid Anatomy 0.000 description 1
- 239000010839 body fluid Substances 0.000 description 1
- 230000036760 body temperature Effects 0.000 description 1
- 230000037396 body weight Effects 0.000 description 1
- 235000014633 carbohydrates Nutrition 0.000 description 1
- 150000001720 carbohydrates Chemical class 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000012350 deep sequencing Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 239000005547 deoxyribonucleotide Substances 0.000 description 1
- 125000002637 deoxyribonucleotide group Chemical group 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 230000037213 diet Effects 0.000 description 1
- 235000005911 diet Nutrition 0.000 description 1
- 239000003085 diluting agent Substances 0.000 description 1
- 208000035475 disorder Diseases 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000001378 electrochemiluminescence detection Methods 0.000 description 1
- 208000028208 end stage renal disease Diseases 0.000 description 1
- 238000006911 enzymatic reaction Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000000684 flow cytometry Methods 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 238000002509 fluorescent in situ hybridization Methods 0.000 description 1
- 238000002986 genetic algorithm method Methods 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 230000006589 gland dysfunction Effects 0.000 description 1
- 231100000852 glomerular disease Toxicity 0.000 description 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
- 229910052737 gold Inorganic materials 0.000 description 1
- 239000010931 gold Substances 0.000 description 1
- 238000012165 high-throughput sequencing Methods 0.000 description 1
- 238000009396 hybridization Methods 0.000 description 1
- 238000003119 immunoblot Methods 0.000 description 1
- 238000003317 immunochromatography Methods 0.000 description 1
- 238000013115 immunohistochemical detection Methods 0.000 description 1
- 238000001114 immunoprecipitation Methods 0.000 description 1
- 238000000338 in vitro Methods 0.000 description 1
- 238000001727 in vivo Methods 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 210000003734 kidney Anatomy 0.000 description 1
- 208000017169 kidney disease Diseases 0.000 description 1
- 201000006370 kidney failure Diseases 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 239000004816 latex Substances 0.000 description 1
- 229920000126 latex Polymers 0.000 description 1
- 210000002751 lymph Anatomy 0.000 description 1
- 239000006249 magnetic particle Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012067 mathematical method Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000001404 mediated effect Effects 0.000 description 1
- 108020004999 messenger RNA Proteins 0.000 description 1
- 239000002207 metabolite Substances 0.000 description 1
- 238000002493 microarray Methods 0.000 description 1
- 239000013642 negative control Substances 0.000 description 1
- 230000001537 neural effect Effects 0.000 description 1
- 238000007481 next generation sequencing Methods 0.000 description 1
- 230000000422 nocturnal effect Effects 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 239000013641 positive control Substances 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000035935 pregnancy Effects 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 239000002096 quantum dot Substances 0.000 description 1
- 230000009257 reactivity Effects 0.000 description 1
- 238000003753 real-time PCR Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000003118 sandwich ELISA Methods 0.000 description 1
- 210000002966 serum Anatomy 0.000 description 1
- 229910052709 silver Inorganic materials 0.000 description 1
- 239000004332 silver Substances 0.000 description 1
- 150000003384 small molecules Chemical class 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 210000001179 synovial fluid Anatomy 0.000 description 1
- 230000035488 systolic blood pressure Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 229940124597 therapeutic agent Drugs 0.000 description 1
- 210000001685 thyroid gland Anatomy 0.000 description 1
- 238000013518 transcription Methods 0.000 description 1
- 230000035897 transcription Effects 0.000 description 1
- 238000002054 transplantation Methods 0.000 description 1
- 230000000472 traumatic effect Effects 0.000 description 1
- 238000007473 univariate analysis Methods 0.000 description 1
- 208000009852 uremia Diseases 0.000 description 1
- 229940116269 uric acid Drugs 0.000 description 1
- 230000003966 vascular damage Effects 0.000 description 1
- 235000019166 vitamin D Nutrition 0.000 description 1
- 239000011710 vitamin D Substances 0.000 description 1
- 150000003710 vitamin D derivatives Chemical class 0.000 description 1
- 229940046008 vitamin d Drugs 0.000 description 1
- 239000011534 wash buffer Substances 0.000 description 1
- 238000001262 western blot Methods 0.000 description 1
Images
Classifications
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/158—Expression markers
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
- G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
- G01N2333/46—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans from vertebrates
- G01N2333/47—Assays involving proteins of known structure or function as defined in the subgroups
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/04—Endocrine or metabolic disorders
- G01N2800/042—Disorders of carbohydrate metabolism, e.g. diabetes, glucose metabolism
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/34—Genitourinary disorders
- G01N2800/347—Renal failures; Glomerular diseases; Tubulointerstitial diseases, e.g. nephritic syndrome, glomerulonephritis; Renovascular diseases, e.g. renal artery occlusion, nephropathy
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Biomedical Technology (AREA)
- Analytical Chemistry (AREA)
- Organic Chemistry (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Molecular Biology (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Wood Science & Technology (AREA)
- Zoology (AREA)
- Medical Informatics (AREA)
- Biotechnology (AREA)
- Biochemistry (AREA)
- Urology & Nephrology (AREA)
- Genetics & Genomics (AREA)
- Microbiology (AREA)
- Hematology (AREA)
- Public Health (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- General Physics & Mathematics (AREA)
- Biophysics (AREA)
- Medicinal Chemistry (AREA)
- Food Science & Technology (AREA)
- Cell Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
The invention discloses a reagent for diagnosing diabetic nephropathy, a product and application thereof, and particularly relates to biomarkers TNFAIP6 and RUNX3, wherein the TNFAIP6 and the RUNX3 are both up-regulated in diabetic nephropathy patients, and the combination of the TNFAIP6 and the RUNX3 has better diagnosis efficiency in the diagnosis of diabetic nephropathy, so that the TNFAIP6 and the RUNX3 can be used as diagnosis and/or treatment targets to be applied to clinical diagnosis and treatment of diabetic nephropathy.
Description
Technical Field
The invention belongs to the field of gene biological agents, and particularly relates to a reagent and a product for diagnosing diabetic nephropathy and application thereof.
Background
Diabetic Nephropathy (DN) is one of the most serious complications of diabetes, and is the major microvascular complication of diabetes, and DN mainly refers to Diabetic glomerulosclerosis, a glomerular disease mainly caused by vascular damage. Early stage is asymptomatic, and blood pressure may be normal or high. The incidence increases with the course of diabetes. The kidney volume is increased in the early stage of diabetes, the glomerular filtration rate is increased and is in a high filtration state, interstitial proteinuria or micro albuminuria gradually appears, continuous proteinuria, edema, hypertension and glomerular filtration rate reduction appear along with the prolongation of the disease course, and further renal insufficiency and uremia are one of the main death reasons of the diabetes.
DN is a main cause of End-stage renal disease (ESRD), once a patient progresses to ESRD, the patient needs to receive renal replacement and renal transplantation treatment, prognosis outcome is poor, blood sugar fluctuation, non-aryblood pressure, nocturnal systolic pressure, blood uric acid, vitamin D level, thyroid gland dysfunction and the like are the development risks of DN, the life quality of the patient is seriously influenced, and serious economic burden is brought to families, so that the DN generation development mechanism is clarified, and non-traumatic markers for early diagnosis of the DN patient are discovered and verified to have very important significance.
At present, the most common early diagnosis marker in clinical diabetic nephropathy patients is microalbuminuria. However, in practice, microalbuminuria still has many deficiencies and limitations as a diagnostic marker, and the microalbuminuria level of a patient is affected clinically by many other physiological and pathological factors, such as body temperature rise, diet, body weight, and the like. Secondly, the level of microalbuminuria is stable, for example, the use of antihypertensive drugs can reduce the level of microalbuminuria, which affects the judgment of kidney diseases of DN patients; and the level of microalbuminuria is less relevant to diabetic nephropathy in the early stages of DN. In view of this, there is a need in the art to find suitable markers that can be used for diagnosing DN, particularly early diagnosis of DN.
Disclosure of Invention
The invention aims to provide a reagent and a product for early screening and diagnosis of diabetic nephropathy based on machine learning and various statistical analysis methods, wherein the reagent and the product can be used for early screening and diagnosis of diabetic nephropathy to predict occurrence and development conditions of diseases, and provide an auxiliary diagnosis method for early diagnosis of diabetic nephropathy clinically.
In order to achieve the purpose, the invention adopts the following technical scheme:
in one aspect, the invention provides the use of a reagent for detecting a biomarker in a sample in the manufacture of a diagnostic product for diabetic nephropathy.
Further, the biomarkers are TNFAIP6 and RUNX 3.
Still further, the sample is selected from blood or tissue.
Still further, the sample is derived from a subject, preferably a human.
Still further, the diagnostic product comprises a reagent for detecting the expression level of TNFAIP6 and RUNX3 in a sample.
Further, the reagent includes a reagent for detecting the expression level of TNFAIP6 and RUNX3 in a sample by a sequencing technique, a nucleic acid hybridization technique, a nucleic acid amplification technique and a protein immunization technique.
Still further, the sequencing technologies are nucleic acid sequencing technologies, including chain terminator (Sanger) sequencing technology and dye terminator sequencing technology, and one of ordinary skill in the art will recognize that RNA is typically reverse transcribed into DNA prior to sequencing because it is less stable in cells and more susceptible to nuclease attack in experiments, and in addition, the sequencing technologies also include next generation sequencing technologies (i.e., deep sequencing/high throughput sequencing technologies), which is a single-molecule cluster-based sequencing-by-synthesis technology based on proprietary principles of reversible termination chemical reactions. Random fragments of genome DNA are attached to an optically transparent glass surface during sequencing, hundreds of millions of clusters are formed on the glass surface after the DNA fragments are extended and subjected to bridge amplification, each cluster is a monomolecular cluster with thousands of identical templates, and then four kinds of special deoxyribonucleotides with fluorescent groups are utilized to sequence the template DNA to be detected by a reversible edge-to-edge synthesis sequencing technology.
Still further, such nucleic acid hybridization techniques include, but are not limited to, In Situ Hybridization (ISH), microarrays, and Southern or Northern blots.
Still further, the nucleic acid amplification technique is selected from the group consisting of Polymerase Chain Reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), Transcription Mediated Amplification (TMA), Ligase Chain Reaction (LCR), Strand Displacement Amplification (SDA), and Nucleic Acid Sequence Based Amplification (NASBA).
Still further, the protein immunization techniques include sandwich immunoassays, such as sandwich ELISA, wherein the detection of the biomarkers TNFAIP6, RUNX3 is performed using two antibodies recognizing different epitopes on the biomarkers TNFAIP6, RUNX 3; radioimmunoassay (RIA), direct, indirect or contrast enzyme-linked immunosorbent assay (ELISA), Enzyme Immunoassay (EIA), Fluorescence Immunoassay (FIA), western blot, immunoprecipitation, and any particle-based immunoassay (e.g., using gold, silver or latex particles, magnetic particles, or quantum dots).
Still further, the agent is selected from:
primers for specifically amplifying TNFAIP6 and RUNX 3; or
A probe specifically recognizing TNFAIP6 and RUNX 3; or
A binding agent that specifically binds to a protein encoded by TNFAIP6, RUNX 3.
Still further, the binding agent that specifically binds to a protein encoded by TNFAIP6, RUNX3 includes a receptor for the protein, an antibody directed against the protein, a peptide antibody directed against the protein, a lectin that binds the protein, a bispecific dual binding agent, or a bispecific antibody.
Still further, the binding agent that specifically binds to a protein encoded by TNFAIP6, RUNX3 is an antibody directed against said protein.
In another aspect, the present invention provides a diagnostic product for diabetic nephropathy.
Further, the diagnostic product comprises reagents for detecting the biomarkers TNFAIP6 and RUNX 3.
Further, the agent is selected from:
primers for specifically amplifying TNFAIP6 and RUNX 3; or
A probe specifically recognizing TNFAIP6 and RUNX 3; or
A binding agent that specifically binds to a protein encoded by TNFAIP6, RUNX 3.
Still further, the binding agent that specifically binds to a protein encoded by TNFAIP6, RUNX3 includes a receptor for the protein, an antibody directed against the protein, a peptide antibody directed against the protein, a lectin that binds the protein, a bispecific dual binding agent, or a bispecific antibody.
Still further, the binding agent that specifically binds to a protein encoded by TNFAIP6, RUNX3 is an antibody directed against said protein.
Furthermore, the diagnostic product comprises a preparation, a kit, a chip and a test strip.
Further, the preparation is a biological preparation comprising reagents for detecting the biomarkers TNFAIP6, RUNX 3;
furthermore, the kit comprises an ELISA kit, a qPCR kit, an electrochemiluminescence detection kit, an immunoblotting detection kit, an immunochromatography detection kit, a flow cytometry analysis kit and an immunohistochemical detection kit;
still further, the kit further comprises instructions for whether the subject has, or is at risk for having, diabetic nephropathy.
Further, the diagnostic product also includes reagents for processing the subject sample.
In yet another aspect, the present invention provides the use of TNFAIP6, RUNX3 in the construction of a computational model or a system in which said computational model is embedded for the prediction of diabetic nephropathy;
wherein the calculation model is operated by a bioinformatics method with the expression levels of TNFAIP6 and RUNX3 as input variables, and outputs the risk probability of diabetic nephropathy.
In yet another aspect, the present invention provides a device for diagnosing diabetic nephropathy.
Further, the device comprises a processor, an input module and an output module;
the processor is used for carrying out logic operation on input information by adopting a bioinformatics method; an input module for inputting an expression level of TNFAIP6, RUNX3 in a sample, a computer readable medium comprising instructions that when executed by the processor perform an algorithm on the input expression level of TNFAIP6, RUNX 3; the output module is used for outputting whether the subject suffers from the diabetic nephropathy or risks suffering from the diabetic nephropathy.
Has the advantages that:
according to the invention, TNFAIP6 and RUNX3 are selected as gene markers for diagnosis, so that rapid and effective diagnosis of diabetic nephropathy can be realized, an auxiliary diagnosis method for early diagnosis of diabetic nephropathy is provided for a clinician, and further warning is provided for a subject so as to realize early intervention.
Drawings
Embodiments of the invention are described in detail below with reference to the attached drawing figures, wherein:
FIG. 1 shows the differential expression profiles of TNFAIP6 and RUNX3 gene mRNA, wherein, Panel A: TNFAIP6, training set, panel B: TNFAIP6, validation set, panel C: RUNX3, training set, graph D: RUNX3, validation set;
FIG. 2 shows ROC profile of TNFAIP6, RUNX3 gene for diagnosing diabetic nephropathy, wherein, panel A: TNFAIP6, training set, panel B: TNFAIP6, validation set, panel C: RUNX3, training set, graph D: RUNX3, validation set;
FIG. 3 shows ROC plots for TNFAIP6+ RUNX3 in combination for the diagnosis of diabetic nephropathy, wherein panel A: training set, graph B: and (5) verifying the set.
Detailed Description
In the context of the present invention, the term "marker", as well as "biomarker", "genetic marker", refers to an indicator of a patient's phenotype, such as a pathological state or a possible reactivity to a therapeutic agent, which can be detected in a biological sample of said patient, biomarkers including, but not limited to, DNA, RNA, proteins, small molecule metabolites, carbohydrates, glycolipid-based molecules, etc.;
in a particular embodiment of the invention, the marker is TNFAIP6 and/or RUNX3, preferably the markers are the genes TNFAIP6(TNF alpha induced protein 6, Gene ID: 7130) and RUNX3(RUNX family transcription factor 3, Gene ID: 864), encompassing full-length, unprocessed genes, as well as genes derived from any form of processing in the cell, which encompasses naturally occurring variants of the genes. Details of the gene TNFAIP6 and the gene RUNX3 are available at h ttps:// www.ncbi.nlm.nih.gov/gene.
In the context of the present invention, the term "sample", as well as "sample", "subject sample", refers to a composition obtained or derived from a subject of interest, which comprises cellular entities and/or other molecular entities to be characterized and/or identified, e.g. on the basis of physical, biochemical, chemical and/or physiological characteristics. The sample may be obtained from the blood of a subject and other fluid samples of biological origin and tissue samples, such as biopsy tissue samples or tissue cultures or cells derived therefrom. The source of the tissue sample may be solid tissue, such as from a fresh, frozen and/or preserved organ or tissue sample, biopsy tissue or aspirate; blood or any blood component; a body fluid; cells from any time of pregnancy or development of the individual; or plasma. The term "sample" includes a biological sample that has been treated in any way after it has been obtained, e.g., by treatment with a reagent, stabilization, or enrichment for certain components (e.g., proteins or polynucleotides), or embedded in a semi-solid or solid matrix for sectioning purposes. Samples described herein include, but are not limited to, whole blood, blood-derived cells, serum, plasma, lymph, synovial fluid, cell extracts, and combinations thereof.
In the context of the present invention, the term "primer", as well as "amplification primer", refers to a nucleic acid fragment comprising 5-100 nucleotides, preferably said primer or amplification primer comprises 15-30 nucleotides capable of initiating an enzymatic reaction (e.g., an enzymatic amplification reaction).
In the context of the present invention, the term "probe" refers to a nucleic acid sequence comprising at least 5 nucleotides, e.g.comprising 5 to 100 nucleotides, which probe is capable of hybridizing under the specified conditions with the expression product of the target gene or with the amplification product of this expression product to form a complex. The hybridization probes may also include labels for detection. Such labels include, but are not limited to, labels for fluorescent quantitative PCR or fluorescent in situ hybridization.
In the context of the present invention, the term "kit" refers to an article of manufacture (e.g., a package or container) comprising probes for specifically detecting the biomarker genes or proteins of the present invention;
in certain embodiments, the article of manufacture is marketed, distributed, or sold as a unit for performing the methods of the present invention. Such kits may comprise carrier means compartmentalized to receive, in close confinement, one or more container means (e.g., vials, tubes, etc.), each container means comprising one of the separate components to be used in the method. For example, one of the container means may comprise a probe that carries or can carry a detectable label. Such probes may be polynucleotides specific for polynucleotides of one or more genes comprising gene expression characteristics. Where the kit utilizes nucleic acid hybridization to detect a target nucleic acid, the kit can also have a container containing one or more nucleic acids for amplifying the target nucleic acid sequence and/or a container containing a reporter means, such as a biotin-binding protein, such as avidin or streptavidin, bound to a reporter molecule, such as an enzymatic, fluorescent, or radioisotope label;
a kit will generally comprise the above-described container and one or more additional containers containing commercially and user-desired materials, including buffers, diluents, filters, needles, syringes, and package inserts containing instructions for use. A label may be present on the container to indicate that the composition is for a particular therapeutic or non-therapeutic application, and may also indicate the direction of in vivo or in vitro use, such as those described above. Other optional components of the kit include one or more buffers (e.g., blocking buffer, wash buffer, substrate buffer, etc.), other reagents (e.g., substrate chemically altered by enzymatic labeling), epitope retrieval solutions, control samples (positive and/or negative controls), control sections, and the like.
In the context of the present invention, the term "diagnosis" or "diagnosis aid" refers to the identification or classification of a molecular or pathological state, disease or disorder. For example, by molecular characterization (e.g., characterized by the expression of a particular gene or one or a combination of the proteins encoded by the gene), the identification of whether or not and the risk of having diabetic nephropathy is identified.
As the skilled person will be familiar with, the step of correlating biomarker levels with a certain likelihood or risk may be carried out and carried out in different ways. Preferably, the measured concentrations of the protein and one or more other markers are mathematically combined and the combined value is correlated with the underlying diagnostic problem. The determination of marker values may be combined by any suitable prior art mathematical method.
Preferably, the mathematical algorithm applied in the biomarker combinations is a logarithmic function. Preferably, the result of applying such a mathematical algorithm or such a logarithmic function is a single value. Such values can be readily correlated to, for example, an individual's risk for diabetic nephropathy or to other diagnostic uses of interest that are helpful in assessing diabetic nephropathy patients, based on underlying diagnostic questions. In a preferred manner, such a logarithmic function is obtained as follows: a) classifying the individual into a group, e.g., a normal person, an individual at risk of having diabetic nephropathy, a patient having diabetic nephropathy, etc.; b) identifying markers that differ significantly between these groups by univariate analysis; c) logistic regression analysis to assess independent difference values of the markers that can be used to assess these different sets; d) a logarithmic function is constructed to combine the independent difference values. In this type of analysis, the markers are no longer independent, but represent a combination of markers.
The logarithmic function used to correlate marker combinations with disease preferably employs algorithms developed and obtained by applying statistical methods. For example, suitable statistical methods are Discriminant Analysis (DA) (i.e., linear, quadratic, regular DA), Kernel methods (i.e., SVM), nonparametric methods (i.e., k-nearest neighbor classifiers), PLS (partial least squares), tree-based methods (i.e., logistic regression, CART, random forest methods, boosting/bagging methods), generalized linear models (i.e., logistic regression), principal component-based methods (i.e., SIMCA), generalized additive models, fuzzy logic-based methods, neural network-and genetic algorithm-based methods. The skilled person will not have problems in selecting a suitable statistical method to evaluate the marker combinations of the invention and thereby obtain a suitable mathematical algorithm. In one embodiment, the statistical method used to obtain the mathematical algorithm used in assessing diabetic nephropathy is selected from DA (i.e., linear, quadratic, regular discriminant analysis), Kernel method (i.e., SVM), non-parametric method (i.e., k-nearest neighbor classifier), PLS (partial least squares), tree-based method (i.e., logistic regression, CART, random forest method, boosting method), or generalized linear model (i.e., logarithmic regression).
The area under the subject's working characteristic curve (AUC) is an indicator of the performance or accuracy of the diagnostic protocol. The accuracy of a diagnostic method is best described by its Receiver Operating Characteristics (ROC). ROC plots are line graphs of all sensitivity/specificity pairs derived from continuously varying decision thresholds across the entire data range observed.
The following examples are given to illustrate the present invention but not to limit the scope of the present invention.
Example 1 study of biomarkers associated with diabetic nephropathy
The purpose of this study was to screen out biomarkers associated with diabetic nephropathy based on machine learning analysis and to study their value for diagnosis or prognosis of diabetic nephropathy.
1. Research method
(1) Data used for research and preprocessing method
The method comprises the steps of searching public GENE EXPRESSION data related to diabetic nephropathy and complete annotations thereof in a GENE EXPRESSION comprehensive database (GEO database) by taking the 'diabetic nephropathy' as a key word, and selecting clinical sample information of diabetic nephropathy patients according to clinical information recorded in the public GENE EXPRESSION data. Downloading gene expression data of GSE30122 (normal: case 50: 19) from a GEO database (http:// www.ncbi.nlm.nih.gov/GEO /), downloading gene expression data of GSE142153 (normal: case 10: 23) from a GEO database (http:// www.ncbi.nlm.nih.gov/GEO /), and annotating them with an annotation file;
performing joint treatment and quality control by using fastp software to obtain cleardata, comparing the cleardata to a human reference genome (the version of the reference genome is GRCh38.d1.vd1) by using ICGC software to obtain a bam file, combining htseq software with an annotation file, quantifying the expression quantity of genes of the compared bam file, combining the expression quantities of multiple samples according to the ID of the genes to construct an M N gene expression quantity matrix, taking the average value of the multiple probes corresponding to the same gene as the expression quantity of the gene, storing the expression quantity matrix as an Rdata object file, performing characteristic marking on clinical information according to sample grouping information, naming a healthy control group sample as normal, and naming a diabetic nephropathy group sample as case; grouping data, and analyzing biomarkers related to diabetic nephropathy by using data from GSE30122, Rdata object files as verification sets and data from GSE142153, Rdata object files as training sets.
(2) Differential expression Gene analysis between healthy control group and diabetic nephropathy group
Analyzing the differential expression genes between the healthy control group and the diabetic nephropathy group by using a 'limma' packet in R software according to the grouping in the step (1), wherein the screening standard of the differential expression genes is adj<0.05，|log2FC|>0.5, screening genes that were significantly differentially expressed between the healthy control group and the diabetic nephropathy group.
2. Results of the study
The results obtained from the analysis study showed that TNFAIP6 and RUNX3 showed significant differential expression between the healthy control group and the diabetic nephropathy group, wherein TNFAIP6 and RUNX3 were both up-regulated in the diabetic nephropathy group compared to the healthy control group, and the expression profiles are shown in fig. 1A-D.
Example 2 evaluation of the diagnostic potency of the biomarkers TNFAIP6, RUNX3
1. Evaluation analysis method
The subject operating curve (ROC) was plotted using the R package "pROC", and AUC values, sensitivities, and specificities of the biomarkers TNFAIP6, RUNX3, TNFAIP6+ RUNX3, which were obtained from the study of example 1 and exhibited significant differential expression between the healthy control group and the diabetic nephropathy group, were analyzed to judge the diagnostic efficacy of the markers. Wherein, when evaluating and analyzing the diagnostic efficacy of TNFAIP6 and RUNX3 on diabetic nephropathy, the expression level (log2 expression level) of the gene is used for evaluating and analyzing, and the point corresponding to the largest Youden index is selected as the cutoff value, namely the optimal division threshold value is determined by the point with the largest Youden index; when the diagnosis efficacy of TNFAIP6+ RUNX3 on diabetic nephropathy is evaluated and analyzed, firstly, Logitics regression analysis is carried out on the TNFAIP6+ RUNX3 genes, in the Logitics regression analysis, the independent variable is TNFAIP6+ RUNX3, the dependent variable is the disease condition of the diabetic nephropathy, the probability of whether each individual suffers from the diabetic nephropathy can be calculated through a fitted regression curve, and different probability division threshold values are determined to obtain the prediction result. The optimal probability partition threshold is determined by the point with the largest Youden index, and according to the determined probability partition threshold, the AUC value, sensitivity, specificity and the like of the TNFAIP6+ RUNX3 combination in the training set and the verification set can be calculated.
2. Evaluating the results of the analysis
The results of evaluation and analysis show that the TNFAIP6+ RUNX3 combination is superior to TNFAIP6 and RUNX3 in diagnosing diabetic nephropathy, and TNFAIP6+ RUNX3 shows higher diagnostic efficacy whether in training set or verification set, the AUC values are 0.843 and 0.849 respectively, and the TNFAIP6+ RUNX3 combination has higher sensitivity and specificity (see Table 1, FIGS. 2A-D and 3A-B), which proves that the TNFAIP6+ RUNX3 combination can be used in the diagnosis of diabetic nephropathy.
TABLE 1 statistical results of AUC values of TNFAIP6 and RUNX3 in training set and validation set
The above embodiments are merely preferred embodiments of the present invention, and are not intended to limit the present invention, it should be noted that, for those skilled in the art, many modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be construed as the protection scope of the present invention.
Claims (10)
1. Use of a reagent for detecting a biomarker in a sample for the preparation of a diagnostic product for diabetic nephropathy, wherein the biomarker is TNFAIP6 or RUNX 3.
2. Use according to claim 1, wherein the sample is selected from blood or tissue.
3. The use of claim 1, wherein said diagnostic product comprises a reagent for detecting the level of expression of TNFAIP6 or RUNX3 in a sample.
4. The use of claim 3, wherein the reagent comprises a reagent for detecting the expression level of TNFAIP6 or RUNX3 in the sample by sequencing, nucleic acid hybridization, nucleic acid amplification, or protein immunization.
5. The use according to claim 4, wherein the agent is selected from:
primers for specifically amplifying TNFAIP6 and RUNX 3; or
A probe specifically recognizing TNFAIP6 and RUNX 3; or
A binding agent that specifically binds to a protein encoded by TNFAIP6, RUNX 3.
6. A diagnostic product for diabetic nephropathy, comprising reagents for the detection of the biomarkers TNFAIP6, RUNX 3.
7. The diagnostic product of claim 6, wherein the agent is selected from the group consisting of:
primers for specifically amplifying TNFAIP6 and RUNX 3; or
A probe specifically recognizing TNFAIP6 and RUNX 3; or
A binding agent that specifically binds to a protein encoded by TNFAIP6, RUNX 3.
8. The diagnostic product of claim 6 or 7, wherein the diagnostic product comprises a formulation, a kit, a chip, a strip.
Use of TNFAIP6, RUNX3 in the construction of a computational model or a system in which said computational model is embedded for the prediction of diabetic nephropathy;
wherein the calculation model is operated by a bioinformatics method with the expression levels of TNFAIP6 and RUNX3 as input variables, and outputs the risk probability of diabetic nephropathy.
10. An apparatus for diagnosing diabetic nephropathy, the apparatus comprising a processor, an input module, an output module;
the processor is used for carrying out logic operation on input information by adopting a bioinformatics method; an input module for inputting an expression level of TNFAIP6, RUNX3 in a sample, a computer readable medium comprising instructions that when executed by the processor perform an algorithm on the input expression level of TNFAIP6, RUNX 3; the output module is used for outputting whether the subject suffers from the diabetic nephropathy or risks suffering from the diabetic nephropathy.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111021406.4A CN113718026A (en) | 2021-09-01 | 2021-09-01 | Reagent and product for diagnosing diabetic nephropathy disease and application thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111021406.4A CN113718026A (en) | 2021-09-01 | 2021-09-01 | Reagent and product for diagnosing diabetic nephropathy disease and application thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113718026A true CN113718026A (en) | 2021-11-30 |
Family
ID=78680666
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111021406.4A Withdrawn CN113718026A (en) | 2021-09-01 | 2021-09-01 | Reagent and product for diagnosing diabetic nephropathy disease and application thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113718026A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118914572A (en) * | 2024-09-02 | 2024-11-08 | 长沙市中心医院 | CD5 biomarker for diagnosis of diabetic foot and application thereof |
-
2021
- 2021-09-01 CN CN202111021406.4A patent/CN113718026A/en not_active Withdrawn
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118914572A (en) * | 2024-09-02 | 2024-11-08 | 长沙市中心医院 | CD5 biomarker for diagnosis of diabetic foot and application thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2007035690A2 (en) | Methods for diagnosing pancreatic cancer | |
| CA2741117A1 (en) | Biomarkers for heart failure | |
| US20200109454A1 (en) | Nourin molecular biomarkers diagnose angina patients with negative troponin | |
| CN116287220B (en) | Molecular biomarkers and assay methods for rapid diagnosis of kawasaki disease | |
| CN114875149A (en) | Application of reagent for detecting biomarkers in preparation of product for predicting gastric cancer prognosis | |
| WO2024183369A1 (en) | Use of cited4 and/or metrn in differential diagnosis of intervertebral disc degeneration degree | |
| WO2015164616A1 (en) | Biomarkers for detection of tuberculosis | |
| CN102089443A (en) | Method and apparatus for determining a probability of colorectal cancer in a subject | |
| CN114164273B (en) | Squamous carcinoma prognosis marker, establishment method of prognosis risk assessment model and application of prognosis risk assessment model | |
| US20190024184A1 (en) | Distinguishing metastatic-lethal prostate cancer from indolent prostate cancer using methylation status of epigenetic markers | |
| CN118207336B (en) | Blood gene expression biomarker group for diagnosing and evaluating lung nodule cancer risk | |
| CN113718026A (en) | Reagent and product for diagnosing diabetic nephropathy disease and application thereof | |
| CN113584158A (en) | Use of biomarkers for diagnosing diabetic nephropathy | |
| CN117887870A (en) | Application of microbial markers in the diagnosis of hyperglycemia-related diseases | |
| CN117925835A (en) | Colorectal cancer liver metastasis marker model and application thereof in prognosis and immunotherapy response prediction | |
| WO2018174860A1 (en) | Methods and compositions for detection early stage lung adenocarcinoma with rnaseq expression profiling | |
| WO2023230617A2 (en) | Bladder cancer biomarkers and methods of use | |
| CN113969312A (en) | Marker for predicting susceptibility of ulcerative colitis patient to golimumab drug | |
| US20180356419A1 (en) | Biomarkers for detection of tuberculosis risk | |
| CN112575089A (en) | Application of gene in diagnosis of gastric cancer | |
| CN112680521A (en) | Product using gene as diagnostic marker and application thereof | |
| US20130073213A1 (en) | Gene Expression-Based Differential Diagnostic Model for Rheumatoid Arthritis | |
| CN118127149B (en) | Biomarker, model and kit for assessing risk of sepsis and infection in a subject | |
| WO2018174859A1 (en) | Methods and compositions for detection of early stage lung squamous cell carcinoma with rnaseq expression profiling | |
| CN113943802A (en) | Application of GOLT1B in prognosis of renal cancer |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20211130 |
|
| WW01 | Invention patent application withdrawn after publication |