title: Genetic signatures of exceptional longevity in humans.
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.
authors.affiliation: Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America. sebas@bu.edu
authors.forename: Paola
authors.initials: P
authors.lastname: Sebastiani
authors.forename: Nadia
authors.initials: N
authors.lastname: Solovieff
authors.forename: Andrew T
authors.initials: AT
authors.lastname: Dewan
authors.forename: Kyle M
authors.initials: KM
authors.lastname: Walsh
authors.forename: Annibale
authors.initials: A
authors.lastname: Puca
authors.forename: Stephen W
authors.initials: SW
authors.lastname: Hartley
authors.forename: Efthymia
authors.initials: E
authors.lastname: Melista
authors.forename: Stacy
authors.initials: S
authors.lastname: Andersen
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Dworkis
authors.forename: Jemma B
authors.initials: JB
authors.lastname: Wilk
authors.forename: Richard H
authors.initials: RH
authors.lastname: Myers
authors.forename: Martin H
authors.initials: MH
authors.lastname: Steinberg
authors.forename: Monty
authors.initials: M
authors.lastname: Montano
authors.forename: Clinton T
authors.initials: CT
authors.lastname: Baldwin
authors.forename: Josephine
authors.initials: J
authors.lastname: Hoh
authors.forename: Thomas T
authors.initials: TT
authors.lastname: Perls
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000235:genetics*; D000483:Alleles; D001499:Bayes Theorem; D015331:Cohort Studies; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease / Q000235:genetics; D015894:Genome, Human / Q000235:genetics*; D005838:Genotype; D006801:Humans; D008136:Longevity / Q000235:genetics*; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide