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GWAS and Meta-Analysis in Aging/Longevity.

Linda Broer1, Cornelia M van Duijn

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Summary
This summary is machine-generated.

Genome-wide association studies (GWAS) investigate the genetic basis of longevity. While the APOE gene is consistently linked to lifespan, no new genetic loci have been definitively identified, highlighting the complexity of this trait.

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Area of Science:

  • Genetics
  • Gerontology
  • Population Health

Background:

  • Longevity is a complex trait influenced by genetics, environment, and lifestyle.
  • Genome-wide association studies (GWAS) are effective for identifying genetic factors in complex traits with significant heritability.
  • Defining longevity varies across studies (e.g., 85+, 90+, 100+ years), impacting results.

Purpose of the Study:

  • To review and analyze findings from all conducted GWAS of human longevity.
  • To address the impact of different age cut-offs used to define longevity in genetic studies.
  • To identify consistent genetic associations and potential reasons for the lack of replicated findings.

Main Methods:

  • Systematic review and analysis of published genome-wide association studies (GWAS) focused on human longevity.
  • Comparison of results across studies utilizing diverse age thresholds for defining longevity.
  • Examination of genetic variants, including common and rare variants, associated with lifespan.

Main Results:

  • The Apolipoprotein E (APOE) gene is the only consistent genetic association found across multiple GWAS of longevity.
  • Despite identifying biologically plausible genes and pathways, no novel genetic loci for longevity have been conclusively validated.
  • Common genetic variants are estimated to explain over 80% of longevity's heritability, according to whole-genome analyses.

Conclusions:

  • Current GWAS findings for longevity are limited, with APOE being the primary consistent genetic marker.
  • The complexity of the longevity phenotype and potential heterogeneity may contribute to the lack of novel replicated genetic associations.
  • Future research requires increased statistical power, potentially through meta-analyses of existing and emerging GWAS data, to uncover common variants with small effects on lifespan.