The analysis of the effects of genetic variants on human life expectancy has employed ever large databases in recent years: more genes, more sequences, more people. As the data grows, the likely size of the effect of genetic variation on human longevity has become smaller. Outside of a few interesting genes, such as those relating to blood cholesterol levels and cardiovascular disease risk, he picture is one of countless variants with small, interacting, environment-dependent effects, different in every study population.
How much of this picture is a true assessment versus a consequence of larger effects being hidden in the interactions between gene variants? Past studies have near all focused on a variant by variant analysis, considering each variant alone - and so this is an interesting question. Interesting or not, it remains the case that there may be no practical application here, however. Old people are still aged, damaged, and increasingly frail, whether or not they carry rare gene variants associated with longevity. Finding ways to emulate survivors to old age is an inherently poor approach to the treatment of aging, at least in comparison to working towards the repair of the underlying molecular damage that causes aging, in order to produce rejuvenation.
A major goal of aging research is identifying genetic targets that could be used to slow or reverse aging - changes in the body and extend limits of human lifespan. However, the majority of genes that showed the anti-aging and pro-survival effects in animal models were not replicated in humans, with few exceptions. Potential reasons for this lack of translation include a highly conditional character of genetic influence on lifespan, and its heterogeneity, meaning that better survival may be result of not only activity of individual genes, but also gene-environment and gene-gene interactions, among other factors.
In this paper, we explored associations of genetic interactions with human lifespan. We selected candidate genes from well-known aging pathways (IGF1/FOXO growth signaling, P53/P16 apoptosis/senescence, and mTOR/SK6 autophagy and survival) that jointly decide on outcomes of cell responses to stress and damage, and so could be prone to interactions. We estimated associations of pairwise statistical epistasis between SNPs in these genes with survival to age 85+ in the Atherosclerosis Risk in Communities study, and found significant effects of interactions between SNPs in IGF1R, TGFBR2, and BCL2 on survival to age 85 and older. We validated these findings in the Cardiovascular Health Study sample, using survival to age 85+, and to the 90th percentile, as outcomes.
Our results show that interactions between SNPs in genes from the aging pathways influence survival more significantly than individual SNPs in the same genes, which may contribute to heterogeneity of lifespan, and to lack of animal to human translation in aging research.