Identification And Mechanism Of Longevity And Lipid Double-associated Genes And Multi-omics Study Of Healthy And Long-lived People

Background:Longevity genes,especially which are also associated with lipid metabolism balance regulation,play an important role in maintaining human health,promoting health of the elderly and delaying aging.However,the systematic study of the multi-omics combination between the double association of longevity and lipid metabolism has not yet been seen.Therefore,the systematic study of the phenome,genome,transcriptome and proteome associated with longevity will explore multi-dimensional factors and mechanisms influencing health and longevity.It also provides a new opportunity for the prevention and treatment of aging diseases and the realization of healthy aging.Objective:1.Identify and verify new longevity genes,especially double-associated with the regulation of lipid metabolism balance among the longevity population,and preliminarily explore its genetic mechanism.2.Carry out systematic research on phenotypes,genomes,transcriptomes and proteomes associated with longevity,and conjoint analysis to identify and verify the key genes that affect health and longevity by multiple omics.3.Construct a prediction model for the age clock of methylation and protein biology.Methods:This study included 31,920 healthy and longevity populations in China,including 2,432 cases in the Guangxi longevity cohort,and 29,488 cases in the multi-regional health and longevity cohort in China.1.Phenotypic cohort study was used registration and household questionnaire survey methods.2.Genome and transcriptome are both based on Illumina HiSeq 2500 sequencing,WES and GWAS data are identified and verified by case-control,mRNA/lncRNA and miRNA differential expression are analyzed,ENCODE,ChIP-seq and UCSC are combined to predict mutation function.And proteomics is used PH nano-HPLC-MS/MS to analysis the differential expression proteins.3.From the study of age clock,5 methylation sites were screened out from 513 CpG sites for targeted sequencing,telomere length and metabolic phenotype were introduced for age correction,and a model for individual biological age prediction was constructed.In addition,6 proteins were screened out of 1513 proteins from 8 protein expression trends to construct an age prediction model.Results and conclusions:1.Research on genes related to healthy longevity and lipid metabolism balance:?We discovered and verified that four new variants of ABO gene.They are significantly associated with longevity phenotype and metabolic phenotype,as follows:rs8176719 C,rs687621 G,rs643434 A,rs505922 C(prange=4.017E-03-6.778E-03;ORrange=1.073-1.083),and haplotype CGAC(LD;r2=0.944,p=4.926E-17;OR=1.315)is significantly associated with longevity.Metabolic phenotypic analysis results showed that rs687621 GG,rs643434 AX and rs505922 CX are significantly positively associated with HDL-c,LDL-c,TC,TG(prange=2.200E-05-0.036,ORrange=1.546-1.709)and normal BMI levels(prange=2.690E-04-0·026,ORrange=1.530-1.997).Biological mechanism analysis showed that ABO mutations regulate lipid metabolism by the two pathways of vWF/ADAMTS13 and sE-selectin/ICAM1 through O-linked glycosylation.?In the Chinese longevity cohort,we identified and verified that a new variant of the MTHFD1 gene was significantly associated with both longevity and metabolic phenotype,as follows:rs1950902(p genotype=0.004,p allele=0.004,OR=1.085,95%IC=1.026-1.146)was significantly positively associated with longevity.The results of metabolic phenotype analysis showed that gender(p=3.250E-62,OR=3.025),BMI(p threshold=2.810E-1 0,p low-2.760E-36,OR threshold=0.342,OR low=4.116)and TG(p threshold=2.210E-09,p high=1.300E-02,OR threshold=0.265,OR high=0.215)have a significant difference between longevity and the control group.The cumulative effect of these three factors(gender,genotype,BMI)(p=1.243E-04)are also significantly associated with longevity.Among male individuals with threshold BMI,not only were the rs 1950902 genotype AG and GG significantly associated with longevity(p=0.01 1),but also individuals carrying the rs 1950902 G allele were significantly associated with longevity(p=0.007,OR=2.462,95%CI=1.260-4.809).2.Multi-omics study of health and longevity:?A longevity phenotypic cohort study.The phenotypes of 4386 subjects(?90 years old)that are significantly associated with health and longevity and metabolism(BMI,blood pressure and blood lipids)(p<0.05).?In the whole exome study,342 mutations associated with longevity were found in 5790 indels.15 genes with 26 mutation sites involving both longevity and lipid metabolism have been identified and verified.?The whole transcriptomics study.Comparing longevity and control,we identified 320 differentially expressed genes,586 differentially expressed lncRNAs and 175 differentially miRNAs.Most of these genes are involved in the oxidative transmission process.The combined analysis of circRNA-miRNA-mRNA and lncRNA-miRNA-mRNA for differentially expressed genes shows that age-related differentially expressed genes are significantly enriched in the metabolism and immunity pathways,and form a regulatory network of multiple genes.?Whole proteomics analysis showed that a total of 2682 proteins were identified in different age groups.A total of 2638 protein were functionally predicted,mostly involving immunity,endocytosis,secretion and nervous system after annotating by GO,KEGG and COG/KOG three databases.A total of 233 differentially expressed proteins were obtained by comparing the adolescent,middle-aged and longevity groups.After comparison,the signal pathway with the highest difference expressed proteins is the neurodegenerative pathway,followed by the endocrine metabolism pathway.?Combined analysis of multiple omics,we screened all genes on the 134 signaling pathways involved in the identified 16 genes by our group at the transcriptional expression level,and finally obtained 53 differentially expressed genes.From the 320 genes shared by both the whole exome and transcriptome,19 shared differentially expressed genes were screened.From the 233 genes shared by both the whole exome group and the differentially expressed proteome,6 shared differentially expressed genes associated with health and longevity were screened.3.Research on methylation and protein clock:Combining five biological age(longevity)associated methylation sites,gender,and ethnicity for the first time successfully constructed a biological age prediction model y=-53.121*EDARADD-137.564*IPO8+141.040*NHLRC1-67.893*P2RX6+149.547*SCGN+4.592*sex+0.578*nation+64.185(R2=0.86,RMSE=7.34 years).The Kendall rank synergy coefficient of the telomere length verification model is 0.731,and p-value=5.783E-137.In addition,6 proteins were successfully screened out of 1513 proteins with different expressions in different age groups from 0-100 years old.The age prediction model y=-1.440 E-05*CFD+6.097 E-05*EFEMP1+1.036 E-05*CST3-4.236 E-09*IGHA2+6.690 E-09*IGHA1+2.375 E-05*ALB-22.322(R2=0.998,RMSE=1.146 years)was successfully constructed.