Population Genetics Studies On Identifying Health And Longevity Associated Genes Based On Multinomics

Background:Global aging has attracted great attention from all walks of life.The core issue of aging population is the health problems caused by degenerative changes in aging.The realization of healthy aging is of great significance to the health maintenance of the elderly population.The long-lived population is in good health and has the characteristics of delaying or even avoiding the onset of chronic diseases,which is the best model to study healthy aging.Longevity is a complex life process jointly affected by multiple environmental factors.Systematic studies on the internal and external factors affecting longevity at the levels of genome,transcriptome,epigenome and metabolome are of great help to excavate longevity related biomarkers and explore longevity mechanism.It also has guiding significance for how to prevent aging diseases and realize healthy aging.Objective:1.To identify longevity-cardiovascular health associated variant(longCav)in Chinese long-lived populations.2.To analyze the transcriptome expression profile of the long-lived population in Guangxi,China.Comparing the expression profiles of people with and without a family history of longevity to screen the Biomarkers for long-lived people.3.DNA methylation biological clock was used to construct a real biological age evaluation model of Chinese long-lived population.Methods:1.Whole-exome sequencing(WES)and genome-wide Association Studies(GWAS)methods were used to select long-lived cardiovascular health(longCav)from 13,275 samples of 5107 healthy and long-lived individuals and 8,469 age-matched healthy controls.2.mRNA-seq sequencing technique was used to detect the expression levels of12 with history of longevity,76 without history of longevity and 50 local healthy controls without history of longevity,a total of 138 healthy samples.The differences in expression profile,biological process,KEGG pathway and disease enrichment between people with and without a history of longevity were compared,and the co-expression of genes and the protein interaction between the two groups were analyzed.Support Vector Machine(SVM)classification algorithm was used to screen the Biomarker for longevity.3.The methylation levels of target regions of P2RX6,EDARADD,IPO8,NHLRC1 and SCGN in 261 samples were measured by Bisulfite Sequence PCR(BSP).All samples was divided into 9 groups within the range of 20-110 years old,and each group was 10 years apart.The methylation levels of each gene target region were detected in different age groups,and an assessment model of "real" physiological age response calibrated by methylation level was established.The coincidence rate between the age assessment model and the actual age was determined by cross-validation.Results:1.We identified 2 longCavs(TFPI rs7586970 T,p=0.013,OR=1.100.ADAMTS7 rs3825807 A,p=0.017,OR=1.198).The variants interact with APOE ?3 to maintain lipid balance and promote longevity by maintaining a balance of lipid metabolism.2.A total of 581 differentially expressed genes were obtained from the healthy and long-lived group and the local healthy control,among which 92 genes were up-regulated and 489 genes were down-regulated.A total of 31 genes showed significant difference in expression level(|log2FC|>2).The gene expression profile of the group with and without a history of longevity was different.The biological processes,KEGG pathways and disease enrichment of the genes involved in the group with longevity history were different from those without history of longevity.The co-expression patterns and protein interactions of the two groups of differentially expressed genes were different.The longevity biomarkers were determined by ROC curve,AUC>0.99.3.The methylation levels of the target regions of EDARADD,NHLRC1,SCGN,P2RX6 and IPO8 were correlated with age.The methylation status of target regions of NHLRC1 changed from heterozygous methylation to homozygous methylation with age.Age(y)inferential model:y=3.1 98-0.870*P2RX6-5.966*EDARADD-0201*IPO8-0.582*NHLRC1-1.622*SCGN+52.417*Region.This age model can explain the age change of 94.4%of the experimental population.Conclusions:1.Identify 2 longCavs in a long-lived population that promote longevity by interacting with APOE ?3 to maintain lipid balance.2.MRNA-seq results showed that the gene expression profile of the group with and without a history of longevity was different.It reveals that there are differences in the signaling pathway and mechanism between people with or without history of longevity to achieve the goal of longevity.3.The target regions of EDARADD,NHLRC1,SCGN,P2RX6 and IPO8 can be used to construct an effective age inferential model for Chinese long-lived population.Longevity is a complex mechanism,and the results of this study are helpful to further research on the mechanism of longevity and provide a reliable research basis for the realization of potential clinical applications.