Journal article
Genetic variants linked to education predict longevity
Proceedings of the National Academy of Sciences - PNAS, Vol.113(47), pp.13366-13371
11/22/2016
DOI: 10.1073/pnas.1605334113
PMCID: PMC5127357
PMID: 27799538
Abstract
Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total n
= 79,702) and ∼2.4% lower risk for fathers (total n
= 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.
Details
- Title: Subtitle
- Genetic variants linked to education predict longevity
- Creators
- Riccardo E Marioni - Institute of Genetics and CancerStuart J Ritchie - University of EdinburghPeter K Joshi - University of EdinburghSaskia P Hagenaars - University of EdinburghAysu Okbay - Erasmus University RotterdamKrista Fischer - University of TartuMark J Adams - University of EdinburghW David Hill - University of EdinburghGail Davies - University of EdinburghReka Nagy - University of EdinburghCarmen Amador - Institute of Genetics and CancerKristi Läll - University of TartuAndres Metspalu - University of TartuDavid C Liewald - University of EdinburghArchie Campbell - University of EdinburghJames F Wilson - Medical Research CouncilCaroline Hayward - University of EdinburghTõnu Esko - University of TartuDavid J Porteous - University of EdinburghCatharine R Gale - University of EdinburghIan J Deary - University of EdinburghSocial Science Genetic Association ConsortiumKevin Thom (Contributor) - Economics
- Resource Type
- Journal article
- Publication Details
- Proceedings of the National Academy of Sciences - PNAS, Vol.113(47), pp.13366-13371
- DOI
- 10.1073/pnas.1605334113
- PMID
- 27799538
- PMCID
- PMC5127357
- NLM abbreviation
- Proc Natl Acad Sci U S A
- ISSN
- 0027-8424
- eISSN
- 1091-6490
- Grant note
- U01 AG009740 / NIA NIH HHS MC_U147585824 / Medical Research Council R01 AG015819 / NIA NIH HHS MC_U147585819 / Medical Research Council MC_U147585827 / Medical Research Council RF1 AG015819 / NIA NIH HHS MC_QA137853 / Medical Research Council G0400491 / Medical Research Council MC_U147574232 / Medical Research Council MC_UU_12011/1 / Medical Research Council
- Language
- English
- Date published
- 11/22/2016
- Academic Unit
- Economics
- Record Identifier
- 9984936840402771
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