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Genetic Signatures of Exceptional Longevity in Humans

Overview of attention for article published in PLOS ONE, January 2012
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Title
Genetic Signatures of Exceptional Longevity in Humans
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0029848
Pubmed ID
Authors

Paola Sebastiani, Nadia Solovieff, Andrew T. DeWan, Kyle M. Walsh, Annibale Puca, Stephen W. Hartley, Efthymia Melista, Stacy Andersen, Daniel A. Dworkis, Jemma B. Wilk, Richard H. Myers, Martin H. Steinberg, Monty Montano, Clinton T. Baldwin, Josephine Hoh, Thomas T. Perls

Abstract

Like most complex phenotypes, exceptional longevity is thought to reflect a combined influence of environmental (e.g., lifestyle choices, where we live) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity in 801 centenarians (median age at death 104 years) and 914 genetically matched healthy controls. Using these data, we built a genetic model that includes 281 single nucleotide polymorphisms (SNPs) and discriminated between cases and controls of the discovery set with 89% sensitivity and specificity, and with 58% specificity and 60% sensitivity in an independent cohort of 341 controls and 253 genetically matched nonagenarians and centenarians (median age 100 years). Consistent with the hypothesis that the genetic contribution is largest with the oldest ages, the sensitivity of the model increased in the independent cohort with older and older ages (71% to classify subjects with an age at death>102 and 85% to classify subjects with an age at death>105). For further validation, we applied the model to an additional, unmatched 60 centenarians (median age 107 years) resulting in 78% sensitivity, and 2863 unmatched controls with 61% specificity. The 281 SNPs include the SNP rs2075650 in TOMM40/APOE that reached irrefutable genome wide significance (posterior probability of association = 1) and replicated in the independent cohort. Removal of this SNP from the model reduced the accuracy by only 1%. Further in-silico analysis suggests that 90% of centenarians can be grouped into clusters characterized by different "genetic signatures" of varying predictive values for exceptional longevity. The correlation between 3 signatures and 3 different life spans was replicated in the combined replication sets. The different signatures may help dissect this complex phenotype into sub-phenotypes of exceptional longevity.

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Geographical breakdown

Country Count As %
United States 13 3%
United Kingdom 8 2%
Germany 4 <1%
Netherlands 3 <1%
Brazil 3 <1%
Spain 3 <1%
India 1 <1%
Canada 1 <1%
Portugal 1 <1%
Other 4 <1%
Unknown 426 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 120 26%
Student > Ph. D. Student 85 18%
Student > Master 46 10%
Student > Bachelor 36 8%
Other 25 5%
Other 99 21%
Unknown 56 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 148 32%
Biochemistry, Genetics and Molecular Biology 70 15%
Medicine and Dentistry 69 15%
Computer Science 19 4%
Neuroscience 16 3%
Other 75 16%
Unknown 70 15%