If you could use a “molecular crystal ball” and see which sets of genes and variants could predict how long you’ll live, would you want to know? Researchers at the Swiss Institute of Bioinformatics (SIB) are defiantly interested in that information. So much so that they have just released data from a comprehensive study that used an innovative computational approach to analyze a dataset of over 116,000 individuals and probe 2.3 million human single-nucleotide polymorphisms (SNPs).
Findings from the new study—published recently in Nature Communications in an article entitled “Bayesian Association Scan Reveals Loci Associated with Human Lifespan and Linked Biomarkers”—revealed an unparalleled number of SNPs associated with lifespan (16), including 14 previously unknown variants. While the environment in which we live, including our socio-economic status and the food we eat, plays a considerable role in longevity, about 20% to 30% of the variation in human lifespan comes down to our genome. Changes in particular locations in our DNA sequence may hold some of the keys to human endurance.
“In our approach, we prioritized changes in the DNA known to be linked to age-related diseases in order to scan the genome more efficiently,” noted senior study investigator Zoltán Kutalik, Ph.D., group leader at SIB and assistant professor at the Institute of Social and Preventive Medicine (CHUV). “This is the largest set of lifespan-associated genetic markers ever uncovered.”
About 1 in 10 people carry some configurations of these markers that shorten their life by over a year compared with the population average. Moreover, the researchers found that a person inheriting a lifespan-shortening version of one of these SNPs may die up to seven months earlier.
“…we developed a Mendelian randomization-based method combining 58 disease-related GWA [genome-wide association] studies to derive longevity priors for all HapMap SNPs,” the authors wrote. “A Bayesian association scan, informed by these priors, for parental age of death in the UK Biobank study (n=116,279) revealed 16 independent SNPs with significant Bayes factor at a 5% false discovery rate (FDR). Eleven of them replicate (5% FDR) in five independent longevity studies combined; all but three are depleted of the life-shortening alleles in older Biobank participants.”
The SIB team found that most SNPs influenced lifespan by impacting more than a single disease or risk factor—for example, through being more addicted to smoking as well as being predisposed to schizophrenia. The discovered SNPs, combined with gene expression data, allowed the researchers to identify that lower brain expression of three genes neighboring the SNPs (involved in nicotine dependence) was causally linked to increased lifespan.
“Further analysis revealed that brain expression levels of nearby genes (RBM6, SULT1A1 and CHRNA5) might be causally implicated in longevity. Gene expression and caloric restriction experiments in model organisms confirm the conserved role for RBM6 and SULT1A1 in modulating lifespan,” the authors concluded.
“These three genes could, therefore, act as biomarkers of longevity, i.e., survival beyond 85 to 100 years,” commented study co-author Johan Auwerx, Ph.D., a professor at the EPFL. “To support this hypothesis, we have shown that mice with a lower brain expression level of RBM6 lived substantially longer.”
Study co-author Marc Robinson-Rechavi, Ph.D., a SIB group leader, and professor at the University of Lausanne, concluded that “interestingly, the gene expression impact of some of these SNPs in humans is analogous to the consequence of a low-calorie diet in mice, which is known to have positive effects on lifespan.”