Abstract
SummaryIn human longevity studies, single nucleotide polymorphism (SNP) analysis identified a large number of genetic variants with small effects, yet not easily replicable in different populations. New insights may come from the combined analysis of different SNPs, especially when grouped by metabolic pathway. We applied this approach to study the joint effect on longevity of SNPs belonging to three candidate pathways, the insulin/insulin‐like growth factor signalling (IIS), DNA repair and pro/antioxidant. We analysed data from 1,058 tagging SNPs in 140 genes, collected in 1825 subjects (1,089 unrelated nonagenarians from the Danish 1905 Birth Cohort Study and 736 Danish controls aged 46–55 years) for evaluating synergic interactions by SNPsyn. Synergies were further tested by the multidimensional reduction (MDR) approach, both intra‐ and interpathways. The best combinations (FDR<0.0001) resulted those encompassing IGF1R‐rs12437963 and PTPN1‐rs6067484, TP53‐rs2078486 and ERCC2‐rs50871, TXNRD1‐rs17202060 and TP53‐rs2078486, the latter two supporting a central role of TP53 in mediating the concerted activation of the DNA repair and pro‐antioxidant pathways in human longevity. Results were consistently replicated with both approaches, as well as a significant effect on longevity was found for the GHSR gene, which also interacts with partners belonging to both IIS and DNA repair pathways (PAPPA,PTPN1,PARK7, MRE11A). The combination GHSR‐MREA11, positively associated with longevity by MDR, was further found influencing longitudinal survival in nonagenarian females (p = .026). Results here presented highlight the validity of SNP‐SNP interactions analyses for investigating the genetics of human longevity, confirming previously identified markers but also pointing to novel genes as central nodes of additional networks involved in human longevity.
Highlights
Association studies can identify the association of individual gene variants to a given phenotype
We performed pathway-based case–control analysis, looking for epistatic interactions inside original assigned pathways and among different pathways by applying a multidimensional reduction (MDR) approach. We analysed those pairs of single nucleotide polymorphism (SNP) significantly enriched in cases respect to controls for their influence on survival in the oldest old
By testing all possible combinations among the 1,058 available variants, assuming a significance level p < .0001 and correcting for multiple comparisons (FDR
Summary
Association studies can identify the association of individual gene variants to a given phenotype Such analysis is unable to explain the biological complexity of several diseases and complex phenotypes such as human aging and longevity. Single-SNP analyses may miss such a complexity, primarily because if a genetic factor operates through a mechanism involving multiple genes, and is affected by environmental factors, the single investigation may not examine statistical interactions between loci that are informative about the biological and biochemical pathways underpinning the phenotype. Significant advances in statistical approaches make it possible to analyse multiple SNPs in large genetic data sets, considering the main pathway to which the gene belongs and possible covariates, as required in the analysis of complex traits (Curk, Rot & Zupan, 2011)
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