Quantitative analysis of population-scale family trees with millions of relatives

Abstract

Family trees have vast applications in fields as diverse as genetics, anthropology, and economics. However, the collection of extended family trees is tedious and usually relies on resources with limited geographical scope and complex data usage restrictions. We collected 86 million profiles from publicly available online data shared by genealogy enthusiasts. After extensive cleaning and validation, we obtained population-scale family trees, including a single pedigree of 13 million individuals. We leveraged the data to partition the genetic architecture of human longevity and to provide insights into the geographical dispersion of families. We also report a simple digital procedure to overlay other data sets with our resource.

Longevity defined as top 10% survivors is transmitted as a quantitative genetic trait: results from large three-generation datasets

“…Although lifespan is not very heritable in the population at large 3 recent studies have been able to identify 30,31 and replicate 46 some lifespan associated alleles that lower the risk of age related diseases. Our results imply that to find loci that promote survival to the highest ages in the population, genetic studies should be based on long lived cases including at least parental mortality information but preferably also mortality information of siblings and other first and second degree family members.…”

“…Human lifespan has a low heritability (12-25%) 1–3 , whereas survival into extreme ages (longevity) clusters within families 4–8 . Studies showed that parents, siblings 4–6,8–11 , and children 6, 12–16 of longevous persons lived longer than first degree relatives of non-longevous persons or population controls.…”

“Arte et Labore”—A Blackburn Rovers fan's legacy in human complex trait genetics

“…Other software packages such as LDAK (Speed, Hemani, Johnson, & Balding, ) and GEMMA (Zhou & Stephens, ) also use REML. Very recently an analysis was published on huge human pedigrees and again the authors used REML (Kaplanis et al, ). Most use the average information algorithm developed by Robin and colleagues (Gilmour, Thompson, & Cullis, ).…”

Estimating variance components in population scale family trees

“…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.…”