PLoS ONE (Aug 2009)

Genetic variation in healthy oldest-old.

  • Julius Halaschek-Wiener,
  • Mahsa Amirabbasi-Beik,
  • Nasim Monfared,
  • Markus Pieczyk,
  • Christian Sailer,
  • Anita Kollar,
  • Ruth Thomas,
  • Georgios Agalaridis,
  • So Yamada,
  • Lisa Oliveira,
  • Jennifer A Collins,
  • Graydon Meneilly,
  • Marco A Marra,
  • Kenneth M Madden,
  • Nhu D Le,
  • Joseph M Connors,
  • Angela R Brooks-Wilson

DOI
https://doi.org/10.1371/journal.pone.0006641
Journal volume & issue
Vol. 4, no. 8
p. e6641

Abstract

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Individuals who live to 85 and beyond without developing major age-related diseases may achieve this, in part, by lacking disease susceptibility factors, or by possessing resistance factors that enhance their ability to avoid disease and prolong lifespan. Healthy aging is a complex phenotype likely to be affected by both genetic and environmental factors. We sequenced 24 candidate healthy aging genes in DNA samples from 47 healthy individuals aged eighty-five years or older (the 'oldest-old'), to characterize genetic variation that is present in this exceptional group. These healthy seniors were never diagnosed with cancer, cardiovascular disease, pulmonary disease, diabetes, or Alzheimer disease. We re-sequenced all exons, intron-exon boundaries and selected conserved non-coding sequences of candidate genes involved in aging-related processes, including dietary restriction (PPARG, PPARGC1A, SIRT1, SIRT3, UCP2, UCP3), metabolism (IGF1R, APOB, SCD), autophagy (BECN1, FRAP1), stem cell activation (NOTCH1, DLL1), tumor suppression (TP53, CDKN2A, ING1), DNA methylation (TRDMT1, DNMT3A, DNMT3B) Progeria syndromes (LMNA, ZMPSTE24, KL) and stress response (CRYAB, HSPB2). We detected 935 variants, including 848 single nucleotide polymorphisms (SNPs) and 87 insertion or deletions; 41% (385) were not recorded in dbSNP. This study is the first to present a comprehensive analysis of genetic variation in aging-related candidate genes in healthy oldest-old. These variants and especially our novel polymorphisms are valuable resources to test for genetic association in models of disease susceptibility or resistance. In addition, we propose an innovative tagSNP selection strategy that combines variants identified through gene re-sequencing- and HapMap-derived SNPs.