Estimates of the Heritability of Human Longevity Are Substantially Inflated due to Assortative Mating

Ruby, J. Graham; Wright, Kevin M.; Rand, Kristin A.; Kermany, Amir R.; Noto, Keith; Curtis, Don; Varner, Neal; Garrigan, Daniel; Slinkov, Dmitri; Dorfman, Ilya; Granka, Julie M.; Byrnes, Jake; Myres, Natalie M.; Ball, Catherine A.

doi:10.1534/genetics.118.301613

Cited by 159 publications

(131 citation statements)

References 43 publications

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“…Human aging is a very complex trait, affected by myriad factors aside from genetic predisposition. The magnitude of genetic contribution to human variation in aging is still debated, varying from around 15% to 30%, [ 91 ] but probably overestimated due to assortative mating in accordance to a recent suggestion [ 92 ] ; the population specificity contributes to moderate convergence between research results, since genes that affect human aging in one population may not be replicated in another. [ 93 ]…”

Section: Omics‐based Molecule‐pattern Biomarkersmentioning

confidence: 78%

Aging Biomarkers: From Functional Tests to Multi‐Omics Approaches

Kudryashova¹,

Burka²,

Kulaga

et al. 2020

Proteomics

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Aging results in various deleterious changes in the human body that may lead to loss of function and the manifestation of chronic diseases. While diseases can generally be reliably diagnosed, the aging process itself requires more sophisticated approaches to evaluate its progression. Numerous attempts have been made to establish biomarkers to quantify human aging at the cellular, tissue, and organismal level. Here, an up‐to‐date overview of biomarkers related to human aging with an emphasis on biomarkers that take into account different mechanisms of aging between individuals is provided. Classical discrete molecular and non‐molecular biomarkers handpicked by researches on the base of their strong correlation with age, as well as emerging omics‐based biomarkers, are discussed and potential future directions and developments in the field of aging assessment are outlined.

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Section: Omics‐based Molecule‐pattern Biomarkersmentioning

confidence: 78%

Aging Biomarkers: From Functional Tests to Multi‐Omics Approaches

Kudryashova¹,

Burka²,

Kulaga

et al. 2020

Proteomics

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“…Amidst growing evidence that genetic epidemiological studies can be susceptible to bias from fine-scale population structure, dynastic effects and assortative mating [26][27][28][29][30][31][32][33][34][35] , there is considerable interest in using genotype data from pedigrees to disentangle these effects and more accurately estimate trait heritability 5-8; 26-28; 33; 34; [36][37][38][39][40] . Family designs such as the transmission disequilibrium test 41 and sibling comparisons are protected from many of these biases by random segregation at meiosis 42; 43 .…”

Section: Discussionmentioning

confidence: 99%

Assortative mating and within-spouse pair comparisons

Howe

Battram

Morris

et al. 2020

Preprint

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Comparisons between cohabitating spouses have been proposed as an aetiological design method to reduce confounding and evaluate effects of the shared adulthood environment. However, assortative mating, a phenomenon where individuals select phenotypically similar mates, could distort associations. We evaluated the use of spousal comparisons, as in the within-spouse pair (WSP) model, for aetiological epidemiological research.Using directed acyclic graphs and simulations, we demonstrated that the WSP model can reduce confounding if spouses are correlated for an unmeasured confounder, but that WSP comparisons are susceptible to collider bias induced by assortative mating. Empirical analyses using spouse pairs in UK Biobank found evidence that genetic association estimates from the WSP model are attenuated compared to random pairs for single nucleotide polymorphisms (SNPs) associated with height (shrinkage: 23%; 95% CI 20%, 25%), educational attainment (74%; 95% CI 66%, 81%) and body mass index (23%; 95% CI 14%, 32% ) as well as for an alcohol consumption SNP (29%, 95% CI 5%, 46%). Some of these attenuations are likely to reflect effects of assortative mating because height and educational attainment are unlikely to be strongly influenced by the adulthood environment. In contrast, effect estimates of increasing age on coronary artery disease and systolic blood pressure were found to be concordant between random and spouse pairs. Assortative mating is likely to induce phenotypic and genetic structure between an individual and their spouse which complicates the interpretation of spousal comparisons in an aetiological context. A further consideration is that the joint participation of non-independent spouses in cohort studies could induce selection bias.

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“…0.5%) when excluding the epistatic interactions matrix (HE results with epistatic interactions were inconclusive due to large standard errors). We also tried to limit confounding due to shared environmental effects [2,84] by excluding ~399,000 pairs (~0.15%) of individuals with a shared household (spouses or parent-child pairs) from the analysis without excluding the individuals themselves, using HE (Methods). This led to a heritability estimate of 26.3% (s.e.…”

Section: Estimating the Heritability Of Longevity And Reproductive Fimentioning

confidence: 99%

“…Genealogical records can reflect social and cultural structures, and record the flow of genetic material throughout history. In recent years, very large pedigree records have come into existence, owing to collaborative digitization of large genealogical records [1,2] and to digitization of large cohorts collected by healthcare providers, spanning up to millions of individuals [3][4][5][6][7]. Such population-scale pedigrees allow investigating the sociological and epidemiological history of human populations on a scale that is orders of magnitude larger than existing studies.…”

Section: Introductionmentioning

confidence: 99%

Estimating variance components in population scale family trees

Shor

Geiger

Erlich

et al. 2018

Preprint

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The rapid digitization of genealogical and medical records enables the assembly of extremely large pedigree records spanning millions of individuals. Such pedigrees provide the opportunity to answer genetic and epidemiological questions in scales much larger than previously possible. Linear mixed models (LMMs) are often used for analysis of pedigree data. However, LMMs cannot naturally scale to large pedigrees spanning millions of individuals, owing to their steep computational and storage requirements. Here we propose a novel modeling framework called Sparse Cholesky factorIzation LMM (SciLMM), that alleviates these difficulties by exploiting the sparsity patterns found in large pedigree data. The proposed framework can construct a matrix of genetic relationships between trillions of pairs of individuals in several hours, and can fit the corresponding LMM in several days. We demonstrate the capabilities of SciLMM via simulation studies and by estimating the heritability of longevity in a very large pedigree spanning millions of individuals and over five centuries of human history. The SciLMM framework enables the analysis of extremely large pedigrees that was not previously possible. SciLMM

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Estimates of the Heritability of Human Longevity Are Substantially Inflated due to Assortative Mating

Abstract: Here, Ruby et al. analyze an unprecedented amount of public family tree data from Ancestry and determine that the heritability of human longevity was well below 10%, lower than the widely-held belief that lifespan...

Cited by 159 publications

References 43 publications

Aging Biomarkers: From Functional Tests to Multi‐Omics Approaches

Aging Biomarkers: From Functional Tests to Multi‐Omics Approaches

Assortative mating and within-spouse pair comparisons

Estimating variance components in population scale family trees

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