Analyzing age-specific genetic effects on human extreme age survival in cohort-based longitudinal studies

Abstract

The analysis of age-specific genetic effects on human survival over extreme ages is confronted with a deceleration pattern in mortality that deviates from traditional survival models and sparse genetic data available. As human late life is a distinct phase of life history, exploring the genetic effects on extreme age survival can be of special interest to evolutionary biology and health science. We introduce a non-parametric survival analysis approach that combines population survival information with individual genotype data in assessing the genetic effects in cohort-based longitudinal studies. Our approach is characterized by nonparametric analysis of late age survival to capture the observed pattern of mortality deceleration and frailty modeling to account for individual heterogeneity in unobserved frailty. The method is applied to ApoE genotype data in the Danish 1905 birth cohort to estimate effect of the e4 allele. Our results revealed an age-specific relative risk of the allele that increases nonlinearly with age and non-proportional patterns in hazard of death for carriers and non-carriers of the allele, suggesting that the e4 mutation preserves its deleterious effect that progressively affect human survival even at extreme ages.

Exploiting horizontal pleiotropy to search for causal pathways within a Mendelian randomization framework

“…Many other mechanisms exist that can lead to bias in MR, as has been described in detail elsewhere. Fourth, SNPs can appear to be outliers not through being pleiotropic, but through other mechanisms, such as population stratification (association of alleles with phenotypes being confounded by ancestral population), canalisation (developmental compensation to a genetic change) 2,35 , or the influence on phenotype being changeable across the life course 36 . Fifth, since MR-TRYX uses the resource from MR-Base, it is recommended that the user acknowledge the limitation and restriction of MR-Base 10 .…”

Cancer—Incidence, prevalence and mortality in the oldest-old. A comprehensive review

“…It has been estimated that 25 percent of the variability associated with longevity is explained by genetic contributions (Hjelmborg et al, 2006;Deelen et al, 2014). The genetic profiles associated with longevity have increasing influence with advanced age (Hjelmborg et al, 2006;Tan et al, 2012). A recent meta-analytic GWAS study confirmed the role of the previously identified APOE locus in longevity and identified an additional region on chromosome 5q33.3 associated with survival beyond 90 years of age (Deelen et al, 2014).…”

MR-TRYX: A Mendelian randomization framework that exploits horizontal pleiotropy to infer novel causal pathways

“…Many other mechanisms exist that can lead to bias in MR, as has been described in detail elsewhere. Fourth, SNPs can appear to be outliers not through being pleiotropic, but through other mechanisms, such as population stratification (association of alleles with phenotypes being confounded by ancestral population), canalization (developmental compensation to a genetic change) 2,41 , or the influence on phenotype being changeable across the life course 42 . Fifth, since MR-TRYX uses the resource from MR-Base, it is recommended that the user acknowledge the limitation and restriction of MR-Base 10 .…”