Abstract
This paper shows that the effects of causal SNPs on lifespan, estimated through GWAS, may be confounded and the genetic structure of the study population may be responsible for this effect. Simulation experiments show that levels of linkage disequilibrium (LD) and other parameters of the population structure describing connections between two causal SNPs may substantially influence separate estimates of the effect of the causal SNPs on lifespan. This study suggests that differences in LD levels between two causal SNP loci within two study populations may contribute to the failure to replicate previous GWAS findings. The results of this paper also show that successful replication of the results of genetic association studies does not necessarily guarantee proper interpretation of the effect of a causal SNP on lifespan.
Highlights
The results of many genome-wide association studies (GWAS) of complex traits suffer from a lack of replication (Shen et al, 2005; Gorroochurn et al, 2007; Greene et al, 2009; Hart et al, 2013; Ioannidis, 2015; Maxwell et al, 2015; Torrico et al, 2016)
In this paper we show that the estimates of the effects of a causal SNP on lifespan depend on the genetic structure of the population under study
We show that differences in population genetic structures can explain why genetic variants favorable for longevity in one population appear as harmful risk factors in another population
Summary
The results of many genome-wide association studies (GWAS) of complex traits suffer from a lack of replication (Shen et al, 2005; Gorroochurn et al, 2007; Greene et al, 2009; Hart et al, 2013; Ioannidis, 2015; Maxwell et al, 2015; Torrico et al, 2016). The frequencies of the genetic variants associated with these traits and their LD patterns may differ even if the genetic structures in the corresponding population cohorts were the same at birth.
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