PURPOSE:

• Researchers continue to analyze populations and the relative contribution of genetic makeup to longevity
• In the past, constructing large family trees have been laborious with limited geographic scope
• Previous studies have estimated the heritability of longevity to be approximately 25%
• Genomewide association studies have not been successful thus far at identifying specific genetic variants associated with longevity
• Kaplanis et al., (Science, 2018) leveraged large publicly available online databases to construct family trees and better refine the contribution of genetics to lifespan

METHODS:

• The authors used a crowd-sourcing website in the genealogy domain
• Coverage of almost all countries in the Western world
• The site scans and merges profiles that can be co-managed resulting in large family trees
• 86-million publicly available profiles were downloaded for the purpose of this study
• Demographic and geographic data were also extracted
• Authors adjusted longevity to be the difference between the age of death from the expected lifespan

RESULTS:

• 3-million family trees were created
• The largest family tree spanned 13-million individuals, connected by shared ancestry and marriage
• Only 16% of variation in how long people live is due to genes
• Over time, people married partners who were less closely related
  • Migration and ability of long distance travel contributed to this data
  • Cultural factors also played a role: During the 19^th century, there was a 50-year lag between increased familial dispersion and the decline of genetic relatedness between couples, suggesting that transportation is not the only reason for decreased consanguinity in Western societies

CONCLUSION:

• Genetics may only account for 16% of variation in longevity, which is considerably less than previous estimated
• This study harnessed the power of social media, new technologies and collaboration between basic research and consumer genetic genealogy databases
• This approach can be used to answer important questions in biomedical research, aside from anthropology, public health and economics

Learn More – Primary Sources:

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

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