CN114107472A - Kit for specifically detecting sarcopenia through rs17480616 - Google Patents
Kit for specifically detecting sarcopenia through rs17480616 Download PDFInfo
- Publication number
- CN114107472A CN114107472A CN202010891147.XA CN202010891147A CN114107472A CN 114107472 A CN114107472 A CN 114107472A CN 202010891147 A CN202010891147 A CN 202010891147A CN 114107472 A CN114107472 A CN 114107472A
- Authority
- CN
- China
- Prior art keywords
- sarcopenia
- kit
- detecting
- genetic
- age
- 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.)
- Pending
Links
- 208000001076 sarcopenia Diseases 0.000 title claims abstract description 36
- 239000002773 nucleotide Substances 0.000 claims abstract description 4
- 125000003729 nucleotide group Chemical group 0.000 claims abstract description 4
- 238000000034 method Methods 0.000 claims description 13
- 239000000523 sample Substances 0.000 claims description 7
- 238000001514 detection method Methods 0.000 abstract description 13
- 208000034826 Genetic Predisposition to Disease Diseases 0.000 abstract description 3
- 239000007850 fluorescent dye Substances 0.000 abstract description 3
- 238000003753 real-time PCR Methods 0.000 abstract 1
- 230000002068 genetic effect Effects 0.000 description 14
- 210000003205 muscle Anatomy 0.000 description 14
- 108090000623 proteins and genes Proteins 0.000 description 11
- 241000282414 Homo sapiens Species 0.000 description 10
- 230000000694 effects Effects 0.000 description 9
- 230000035772 mutation Effects 0.000 description 7
- 210000000349 chromosome Anatomy 0.000 description 6
- 108020004414 DNA Proteins 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 5
- 108700028369 Alleles Proteins 0.000 description 4
- 201000010099 disease Diseases 0.000 description 4
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 4
- 230000001965 increasing effect Effects 0.000 description 4
- 238000012098 association analyses Methods 0.000 description 3
- 230000003247 decreasing effect Effects 0.000 description 3
- 238000003205 genotyping method Methods 0.000 description 3
- 239000003147 molecular marker Substances 0.000 description 3
- 238000012216 screening Methods 0.000 description 3
- 108090000790 Enzymes Proteins 0.000 description 2
- 102000004190 Enzymes Human genes 0.000 description 2
- DHMQDGOQFOQNFH-UHFFFAOYSA-N Glycine Chemical compound NCC(O)=O DHMQDGOQFOQNFH-UHFFFAOYSA-N 0.000 description 2
- TWRXJAOTZQYOKJ-UHFFFAOYSA-L Magnesium chloride Chemical compound [Mg+2].[Cl-].[Cl-] TWRXJAOTZQYOKJ-UHFFFAOYSA-L 0.000 description 2
- 230000003321 amplification Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000007717 exclusion Effects 0.000 description 2
- 102000054766 genetic haplotypes Human genes 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000003199 nucleic acid amplification method Methods 0.000 description 2
- 238000003908 quality control method Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000000611 regression analysis Methods 0.000 description 2
- 238000007894 restriction fragment length polymorphism technique Methods 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- FWMNVWWHGCHHJJ-SKKKGAJSSA-N 4-amino-1-[(2r)-6-amino-2-[[(2r)-2-[[(2r)-2-[[(2r)-2-amino-3-phenylpropanoyl]amino]-3-phenylpropanoyl]amino]-4-methylpentanoyl]amino]hexanoyl]piperidine-4-carboxylic acid Chemical compound C([C@H](C(=O)N[C@H](CC(C)C)C(=O)N[C@H](CCCCN)C(=O)N1CCC(N)(CC1)C(O)=O)NC(=O)[C@H](N)CC=1C=CC=CC=1)C1=CC=CC=C1 FWMNVWWHGCHHJJ-SKKKGAJSSA-N 0.000 description 1
- 238000001712 DNA sequencing Methods 0.000 description 1
- 241000287828 Gallus gallus Species 0.000 description 1
- 239000004471 Glycine Substances 0.000 description 1
- 101100440264 Homo sapiens CNOT4 gene Proteins 0.000 description 1
- 208000031226 Hyperlipidaemia Diseases 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- 208000026350 Inborn Genetic disease Diseases 0.000 description 1
- QNAYBMKLOCPYGJ-REOHCLBHSA-N L-alanine Chemical compound C[C@H](N)C(O)=O QNAYBMKLOCPYGJ-REOHCLBHSA-N 0.000 description 1
- 208000001132 Osteoporosis Diseases 0.000 description 1
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 235000004279 alanine Nutrition 0.000 description 1
- 235000001014 amino acid Nutrition 0.000 description 1
- 150000001413 amino acids Chemical class 0.000 description 1
- 206010003246 arthritis Diseases 0.000 description 1
- 238000007622 bioinformatic analysis Methods 0.000 description 1
- 239000012472 biological sample Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000002759 chromosomal effect Effects 0.000 description 1
- 230000001684 chronic effect Effects 0.000 description 1
- 230000009194 climbing Effects 0.000 description 1
- 210000002808 connective tissue Anatomy 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 230000006378 damage Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 239000008367 deionised water Substances 0.000 description 1
- 229910021641 deionized water Inorganic materials 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 206010012601 diabetes mellitus Diseases 0.000 description 1
- 235000005911 diet Nutrition 0.000 description 1
- 230000000378 dietary effect Effects 0.000 description 1
- 208000016097 disease of metabolism Diseases 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 230000000550 effect on aging Effects 0.000 description 1
- 230000001516 effect on protein Effects 0.000 description 1
- 238000001976 enzyme digestion Methods 0.000 description 1
- 239000012634 fragment Substances 0.000 description 1
- 208000016361 genetic disease Diseases 0.000 description 1
- 238000010353 genetic engineering Methods 0.000 description 1
- 230000007614 genetic variation Effects 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 229910001629 magnesium chloride Inorganic materials 0.000 description 1
- 239000003550 marker Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000010197 meta-analysis Methods 0.000 description 1
- 208000030159 metabolic disease Diseases 0.000 description 1
- 230000002503 metabolic effect Effects 0.000 description 1
- 239000011259 mixed solution Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000004220 muscle function Effects 0.000 description 1
- 210000001087 myotubule Anatomy 0.000 description 1
- 230000003234 polygenic effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 235000018102 proteins Nutrition 0.000 description 1
- 102000004169 proteins and genes Human genes 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 239000011535 reaction buffer Substances 0.000 description 1
- 239000013074 reference sample Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 108091008146 restriction endonucleases Proteins 0.000 description 1
- 210000003765 sex chromosome Anatomy 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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
-
- 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
- C12Q2600/156—Polymorphic or mutational markers
Landscapes
- Chemical & Material Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Health & Medical Sciences (AREA)
- Organic Chemistry (AREA)
- Wood Science & Technology (AREA)
- Analytical Chemistry (AREA)
- Zoology (AREA)
- Genetics & Genomics (AREA)
- Engineering & Computer Science (AREA)
- Pathology (AREA)
- Immunology (AREA)
- Microbiology (AREA)
- Molecular Biology (AREA)
- Biotechnology (AREA)
- Biophysics (AREA)
- Physics & Mathematics (AREA)
- Biochemistry (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
The invention discloses a kit for specifically detecting senile sarcopenia by detecting rs 17480616. The kit comprises a specific primer pair and a specific fluorescent probe pair for detecting the SNP locus of rs17480616, a conventional component for fluorescent quantitative PCR detection and the like. The kit of the invention estimates the genetic susceptibility of the individual senile sarcopenia by simultaneously detecting the genotype of the single nucleotide polymorphism locus on the rs17480616 closely related to the genetic susceptibility of the senile sarcopenia.
Description
Technical Field
The invention relates to the field of SNP typing detection in the technical field of genetic engineering, in particular to a kit for specifically detecting sarcopenia by detecting rs 17480616.
Background
Sarcopenia, also called Sarcopenia (Sarcopenia), is a chronic metabolic disease of the elderly characterized by decreased quality of skeletal muscle fibers, decreased muscle strength, decreased muscle endurance and metabolic capacity, increased connective tissue and fat, etc., as a function of age. Sarcopenia often causes the mobility of the old to be reduced, daily actions such as walking, sitting, climbing, lifting heavy objects and the like are influenced, and the hand is gradually free from binding the force of chicken. The muscle function is reduced, and the probability of accidental falling injury of the old is increased by 40 percent. Statistically, 50% of the elderly die from accidents due to falls. The risk of inconvenient actions of the sarcopenia old people is 2-5 times that of the old people of the same age, and the life quality and the self-care ability of the old people are seriously influenced.
Sarcopenia not only increases the risk of disability and loss of self-care ability of life, but also promotes the development of diseases such as osteoporosis and arthritis, and is also an important reason for inducing senile diseases such as hypertension, diabetes and hyperlipidemia. Sarcopenia has become one of the leading causes of disability and death worldwide. Sarcopenia occurs in 13-24% of the elderly under age 70, with a prevalence of up to 50% and even higher in those over age 80. Annual economic losses associated with sarcopenia exceed $ 1000 billion.
Numerous studies of candidate genes in the past have shown that many genes are associated with changes in human muscle mass. More than 40% of the genetic variations associated with the human lean body mass index (LMI) can produce differences in traits. With the progress of molecular genetics, it is found that sarcopenia is a polygenic genetic disease, and genetic association research of sarcopenia is carried out in many countries. At least 20 human genes or chromosomal regions have been detected by molecular genetics and reported to be associated with sarcopenia to date. In addition, both genetic and molecular epidemiological evidence suggests that genetic factors are involved in determining susceptibility to increased or lost muscle mass in specific dietary or drug regimes, as well as a high risk of developing other related diseases in sarcopenia patients. At present, many candidate genes exist, but most of the candidate genes are required to be further improved in detection accuracy.
As for the method for detecting sarcopenia genes, the conventional detection method at present includes Restriction Fragment Length Polymorphism (RFLP), which is a method for simply treating the PCR product of a patient by enzyme digestion and then detecting whether there is variation when the variation affects the enzyme cutting site of a certain Restriction enzyme. However, the method has the defects of long time consumption, complex operation, low accuracy and the like. The detection of gene polymorphism sites by PCR combined with DNA sequencing is also useful, but the application of this method in large-scale population screening or detection of multiple sites of multiple genes is limited. Therefore, it is necessary to establish a high-throughput, high-efficiency and low-cost SNP (single nucleotide polymorphism) typing method for sarcopenia susceptibility genes to realize clinical rapid detection or large-scale population screening.
Disclosure of Invention
The invention herein provides a kit for specifically detecting sarcopenia by detecting rs 17480616.
The invention aims to provide a screening method of SNP molecular markers of sarcopenia susceptibility genes, which is characterized in that a molecular marker locus rs17480616 is found to be positioned on a No. 7 chromosome 135123060 through a genome sequence of a large-scale genetic array sample of a British biological sample library and the muscle content of four limbs measured by a bioelectrical impedance method, and the mutation is C/G which is directly related to the muscle content of a human.
The invention provides an rs17480616 molecular marker amplification primer pair on 7q33 chromosome according to rs17480616 molecular marker sequence disclosed on NCBI, and an upstream primer of the primer pair: ATTTTGAAGTATTTACCTTT, respectively; a downstream primer: AACAATGTATTTTGTTTCTT, respectively; amplified fragment size: 311 bp. Simultaneously, a pair of detection primer pairs is provided, and genotype-fluorescent probe sequences are as follows: 5 '-FAM-GTCTTCCTTCc CATCAGGACT-TAMRA-3'; genotype two fluorescent probe sequence: 5 '-VIC-GTCTTCCTTCg CATCAGGACT-TAMRA-3'.
The rs17480616 SNP detection chip on chromosome 7q33 can be used for detecting the mutation of chromosome 7q33 segment C/G alone or in parallel. The detection chip is prepared by adopting a conventional construction method in the field.
The invention provides a kit for detecting sarcopenia genetic susceptibility. The kit comprises:
specific primer pair for detecting rs17480616 SNP polymorphism genotype of SEQ ID NO: 2 and 3; PCR reaction components (including Taq enzyme, dNTP mixed solution, MgCl2 solution, reaction buffer solution, deionized water and the like).
The main advantages of the invention
The rs17480616 SNP marker identified and obtained from the chromosome 7q33 can be used for identifying the human sarcopenia symptom, and the identification has the advantages of good accuracy and high specificity.
The detection method of the invention has simple steps, the SNP locus detection can be completed by one-step PCR, the amplification of the target sequence containing the SNP locus avoids a plurality of uncertain factors existing in the complex operation processes of repeated PCR and the like, thereby greatly improving the detection accuracy and embodying the accurate and simultaneously qualitative and quantitative analysis characteristics.
Detailed Description
EXAMPLE 1 obtaining molecular markers for SNPs
1, sample of
The samples used in the present invention were from a uk biosample bank (UKB) cohort of samples. The cohort was a large prospective study cohort containing 50 million participants between 48-73 years of age from all over the country in the uk. We use a series of strict nanocriterions. Exclusion criteria included inconsistency of self-reported sex with genetic sex, non-ploidy sex chromosomes, too high a heterozygosity, too high a genotype deletion rate, and the like. There were 48.7 million participants, and 450243 participants remained available for analysis after the exclusion of 3.7 million participants, of which 205513 were male and 244730 were female.
2, phenotype and modeling thereof
Body composition including muscle content and fat content was measured using a bioelectrical impedance method. The fat content and the muscle content of the arms and the legs are measured in sequence, and the muscle content of the limbs is obtained by adding the muscle content of the arms and the legs. Male and female are modeled separately. In each sex, the raw limb muscle mass was corrected using the limb fat mass, age square, first ten genetic principal components, the measurement location, and the chip used for genotyping as covariates. The corrected residuals were converted to standard normal distributions according to the inverse quantile method and used for downstream analysis.
3, genotype and quality control thereof
All participants were typed using a custom UKB genotyping chip, and genotypic information for 784256 Single Nucleotide Polymorphic Sites (SNPs) was obtained by genotyping on the autosome in total. Statistical methods of genotype filling were used to fill in large genomic reference panels. The panel consisted of the UK10K haplotype, the thousand genome 3-phase data, and the haplotype reference sample. Approximately nine thousand two million SNPs were co-complemented. As a nano-exclusion criterion, SNPs with a sub-allele frequency <0.1% and a filling precision <0.3 were excluded. After quality control, there were a total of nineteen million SNPs for downstream analysis.
4, genetic Association analysis
Within each gender group, genetic association analysis of the mixed linear model was performed using the BOLT-LMM software. After the correlation analysis for both sexes was completed, meta analysis was performed on the genetic correlation signals for both sexes using the inverse variance weighted fixed effect model of METAL software. The whole genome significance level was set at α =5 × 10-9. The SNP sites that achieved this significance level also met the gender specific significance level α =5 × 10-5. That is, significant correlation signals not only meta analyzed p-values <5 x 10-9, but also p-values <5 x 10-5 in both gender groups, respectively.
The magnitude of the effect of SNPs in the two sex panel was compared using the two-sided z-test. The identified SNP sites were annotated using the Variant Effect Predictor (VEP) software.
5, age Effect
As a typical geriatric disease, the genetic effects of sarcopenia may change with increasing age. Therefore, the patent also evaluates the trend of the SNP effect with age. The specific method is to divide UKB samples into 6 age groups: under age 45 (N =54608), 46-50 (N = 58865), 51-55 (N = 70253), 56-60 (N = 89479), 61-65 (N = 109696), and above age 66 (N = 67342). Genetic association analysis was performed using BOLT-LMM software within each age group. The generated regression coefficients were subjected to meta regression analysis for the average age of each group. The P value of the regression analysis was used as a criterion for the significance.
6, conclusion
The SNP site rs17480616 was identified in the UKB sample. Its effect value in the male sample was 0.04, the effect value in the female sample was 0.04, and the overall effect value was 0.04. The effect values did not differ in the male and female groups. The muscle content of the extremities corresponding to the three genotypes CC, GG and CG of rs17480616 is on average 25.1 kg, 21.8 kg and 18.4 kg, respectively, corresponding to a reduction of about 3 kg for each allele G.
Its main genetic association results are shown in Table 1
TABLE 1 genetic Association results of rs17480616
Note: c in allele C/G is the contributing allele.
This site is a missense mutation located on exon 2 of the CNOT4 gene on chromosome 7. The mutation results in the mutation of amino acid No. 7 of the encoded protein from alanine to glycine. Bioinformatic analysis showed that the mutation had a severe disruptive effect on protein function.
To further determine whether the genetic effect of rs17480616 changes with age, this patent also performed age-specific analysis. No age-specific effect was found as a result of the analysis.
In conclusion, the two allelic positions C and G of the missense mutation rs17480616 can well distinguish between high and low muscle groups. When the allele is G, it shows sarcopenia property, and when it is C, it does not show sarcopenia property. Allelic form GG results in a reduction in muscle content that ultimately leads to the development of sarcopenia, which is statistically extremely significant and thus can be detected by detecting this locus genotype.
The above description of the embodiments is only intended to illustrate the method of the invention and its core idea. It should be noted that, for those skilled in the art, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications will also fall into the protection scope of the claims of the present invention.
Sequence listing
<110> Suzhou Jinhao Biotechnology Ltd
<120> a kit for specifically detecting sarcopenia through rs17480616
<160> 5
<170> SIPOSequenceListing 1.0
<210> 1
<211> 311
<212> DNA
<213> Artificial sequence (Homo sapiens)
<400> 1
attttgaagt atttaccttt ctacatgcag gacaaagccc attttcatca gtgcgaattc 60
gatgccaaca aaatcggcaa atctggtagc cacaggtgca agggaaaaag ttgatatcat 120
ctatctccaa gggctccatg caaagagggc actccacagg gtcttccttc ncatcaggac 180
tgcgagacat cttcacgttt attaaacagc agcaaaagtt tataataatt taagggagaa 240
ggaagttcag cactgaaagc taaaatgtag gactttgacg acctgcatga gaagaaacaa 300
aatacattgt t 311
<210> 2
<211> 20
<212> DNA
<213> Artificial sequence (Homo sapiens)
<400> 2
attttgaagt atttaccttt 20
<210> 3
<211> 20
<212> DNA
<213> Artificial sequence (Homo sapiens)
<400> 3
aacaatgtat tttgtttctt 20
<210> 4
<211> 21
<212> DNA
<213> Artificial sequence (Homo sapiens)
<400> 4
gtcttccttc ccatcaggac t 21
<210> 5
<211> 21
<212> DNA
<213> Artificial sequence (Homo sapiens)
<400> 5
gtcttccttc gcatcaggac t 21
Claims (7)
1. A kit for detecting geriatric sarcopenia is characterized in that: the kit comprises a probe and a primer which can specifically detect SNP sites related to senile sarcopenia.
2. The kit of claim 1, comprising a probe and primers capable of specifically detecting rs 17480616.
3. The kit of claim 2, wherein: the kit comprises the nucleotide sequence shown in SEQ ID NO: 2-5.
SEQ ID NO: 2-5 in the preparation of a kit for detecting senile sarcopenia.
Use of rs17480616 as a target for detecting geriatric sarcopenia.
Application of rs17480616 in preparation of a kit for detecting geriatric sarcopenia.
7. A method for detecting geriatric sarcopenia comprising the use of a kit according to any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010891147.XA CN114107472A (en) | 2020-08-30 | 2020-08-30 | Kit for specifically detecting sarcopenia through rs17480616 |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010891147.XA CN114107472A (en) | 2020-08-30 | 2020-08-30 | Kit for specifically detecting sarcopenia through rs17480616 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114107472A true CN114107472A (en) | 2022-03-01 |
Family
ID=80360069
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010891147.XA Pending CN114107472A (en) | 2020-08-30 | 2020-08-30 | Kit for specifically detecting sarcopenia through rs17480616 |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114107472A (en) |
-
2020
- 2020-08-30 CN CN202010891147.XA patent/CN114107472A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8097415B2 (en) | Methods for identifying an individual at increased risk of developing coronary artery disease | |
| WO2008112177A2 (en) | Genemap of the human genes associated with schizophrenia | |
| US11584966B2 (en) | Piezo type mechanosensitive ion channel component 1 (PIEZO1) variants and uses thereof | |
| Kayashima et al. | Quantitative trait loci affecting atherosclerosis at the aortic root identified in an intercross between DBA2J and 129S6 apolipoprotein E-null mice | |
| US20100136543A1 (en) | Method for determining the genotype at the crohn's disease locus | |
| Sjakste et al. | SNPs of the PSMA6 gene: Investigation of possible association with myocardial infarction and type 2 diabetes mellitus | |
| US20030170665A1 (en) | Haplotype map of the human genome and uses therefor | |
| CN114107472A (en) | Kit for specifically detecting sarcopenia through rs17480616 | |
| CN114107469A (en) | Kit for specifically detecting sarcopenia through rs61754233 | |
| CN114107471A (en) | Kit for specifically detecting sarcopenia through rs141308595 | |
| CN114107470A (en) | Kit for specifically detecting sarcopenia through rs41265094 | |
| CN114107467A (en) | Kit for specifically detecting sarcopenia through rs112892337 | |
| CN114107473A (en) | Kit for specifically detecting sarcopenia through rs6540718 | |
| CN114107466A (en) | Kit for specifically detecting sarcopenia through rs28929474 | |
| CN114107468A (en) | Kit for specifically detecting sarcopenia through rs73181210 | |
| CN114107463A (en) | Kit for specifically detecting sarcopenia through rs143365597 | |
| CN114107465A (en) | Kit for specifically detecting sarcopenia through rs33966734 | |
| CN114107464A (en) | Kit for specifically detecting sarcopenia through rs35816944 | |
| CN112824537A (en) | Kit for specifically detecting sarcopenia through rs524533 | |
| WO2007032496A1 (en) | Method for determination of risk of type 2 diabetes | |
| KR102565803B1 (en) | Method for providing information for hypertension and kits using the same | |
| KR101881809B1 (en) | Biomarker for predicting of training response | |
| KR101881817B1 (en) | Biomarker for predicting of training response | |
| KR101881812B1 (en) | Biomarker for predicting of training response | |
| CN112824536A (en) | Kit for specifically detecting sarcopenia through rs545970 |
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 | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20220301 |