A Phenotypic Omics Study Based On GWAS Data To Study The Relationship Among 27 Clinical Biochemical Quantification Traits In Fangchenggang Men's Health Cohort

OBJECTIVE: Genome-wide association study(GWAS)refers to the discovery of the presence of a genetic variation within the entire human genome,ie single nucleotide polymorphism(SNP),screening for disease and complex traits.Related SNP sites.Clinical biochemical traits are an important measure of human vital function,and the disorder will cause the occurrence of diseases.Therefore,understanding the correlation between these traits and the genetic background has important reference value for the study of the occurrence of diseases.In this study,a series of experiments and bioinformatics methods were used to study the relationship between the 27 clinical biochemical traits of the male health cohort at Fangchenggang,from the relationship between phenotypeand phenotype to the interaction between protein and protein to the whole genome.The level of linkage disequilibrium studies the correlation between 27 clinical biochemical traits to find out the relationship between new clinical biochemical traits and further find out the key genes and sites affecting the relevant modules of clinical quantitative traits by mining genetic information..Methods: 1.Experimental methods:(1)The physiological values of 27 clinical biochemical traits in serum of 1999 subjects were measured.(2)Blood DNA extraction and genome-wide genotyping.2.Statistical methods:(1)The correlation among 27 clinical biochemical traits was studied through the following three methods: First,the correlation between clinical biochemical traits was studied based on the Spearman rank correlation coefficient.Second,the correlation between clinical biochemical traits was studied based on the improved Jaccard's coefficient.Third,regression analysis based on linkage disequilibrium scores examined the correlation between clinical biochemical traits.(2)Information mining: Firstly,Cytoscape was used to construct the genetic network inter-construction map and the network map analysis of the genes included in the search through the BioGRID database.Second,all important clinical biochemical markers share important sites and genes.Third,important shared sites are annotated and analyzed through the HaploReg database.Results: 1.We calculated the average of the physiological values of 27 clinical biochemical traits of 1999 blood samples from Fangchenggang men'shealth cohort and calculated the mean and 95% confidence intervals.We found that the physiological values of these traits were all in accordance with normal standards;Statistical analysis of Spearman's correlation coefficient found that the correlation between the 27 clinical biochemical traits can be aggregated into3 relational modules.The Spearman correlation coefficient r value of most of the modules is greater than 0.3;through the relevant sites The protein-protein interactions of the genes and the improved Jaccard correlation coefficient statistical analysis revealed that the correlations between the 27 clinical biochemical traits can be clustered into 4 modules,one more than the statistical analysis of Spearman correlation coefficients.Correlation module,and newly discovered immunoglobulin A(IgA)and testosterone(TE)(J=0.29),prostate specific antigen(PSA)(J=0.28)has an important correlation;regression based on the linkage disequilibrium score The significance of the(LDSC)statistical method,we performed a correlation analysis of clinical biochemical traits of the whole genome sites and found that these clinical biochemical markers The correlations between the targets were clustered into five modules.Relative to the existing literature,the linkage disequilibrium score regressions were found to be osteocalcin(osteocalcin)and the statistical analysis of the Spearman correlation coefficient and the correlation analysis of the Jaccard correlation coefficient.Cholesterol(rg=-0.65,P=0.0142)and low-density lipoprotein(LDL)(rg=-0.70,P-0.0483)have an important relationship,creatinine and follicle stimulating hormone(FSH)(Rg=-0.85,P=0.0309),oncofetal protein(CEA)(rg=-0.87,P=0.0265)has an important correlative relationship;2.Gene pleiotropicity,released as multiple effects produced by a single gene.It is important that the genes or sites that affect multiple phenotypes affect the disease at the same time,indicating that these genes or sites are hub genes or sites in the body.First of all,we have constructed 183 important genes by constructing a gene with a high“degree” value for gene mapping and genes that affect multiple clinical biochemical traits.Second,we dealt with the intersection of multiple clinical biochemical traits for P<10-3 loci,annotated through the HaploReg database and the SNP FUNCTION PREDICTION database,and found 81 important loci for the genes of these important loci.Intersection with 183 important genes obtained in the previous step revealed that 6 genes,HLA-B,UBASH3 B,POU5F1,AMFR,ANXA7,and PHB,are the intersections of these methods.There are five sites on these genes.It is rs7744057(HLA-B),rs10790521(UBASH3B),rs9263800(POU5F1),rs731119(AMFR),rs7074613(AMFR),and rs2671662(ANXA7).Conclusion: We conducted systematic bioinformatics analysis and data mining through the analysis of the 1999 full-genome level and 27 clinical biochemical traits.Combined with a variety of existing algorithms and improved algorithms,we found 27 commonly used clinical biochemical traits.Inter-relatedness.In addition,we further explored genetic information that affected the correlation of these clinical biochemical traits.The literature revealed that the genes we found,HLA-B,UBASH3 B,POU5F1,AMFR,ANXA7,and PHB,have important relationships with human diseases,rs7744057,rs10790521,rs9263800,rs731119,The HaploReg annotation results of rs7074613 and rs2671662 indicate that these sites are very important and highly researchable.This study provides a systematic and important theoretical basis for the complex clinical biochemical indicators and the genetic study of diseases.