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Genetic determinants of mortality. Can findings from genome-wide association studies explain variation in human mortality?

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Abstract

Twin studies have estimated the heritability of longevity to be approximately 20–30 %. Genome-wide association studies (GWAS) have revealed a large number of determinants of morbidity, but so far, no new polymorphisms have been discovered to be associated with longevity per se in GWAS. We aim to determine whether the genetic architecture of mortality can be explained by single nucleotide polymorphisms (SNPs) associated with common traits and diseases related to mortality. By extensive quality control of published GWAS we created a genetic score from 707 common SNPs associated with 125 diseases or risk factors related with overall mortality. We prospectively studied the association of the genetic score with: (1) time-to-death; (2) incidence of the first of nine major diseases (coronary heart disease, stroke, heart failure, diabetes, dementia, lung, breast, colon and prostate cancers) in two population-based cohorts of Dutch and Swedish individuals (N = 15,039; age range 47–99 years). During a median follow-up of 6.3 years (max 22.2 years), we observed 4,318 deaths and 2,132 incident disease events. The genetic score was significantly associated with time-to-death [hazard ratio (HR) per added risk allele = 1.003, P value = 0.006; HR 4th vs. 1st quartile = 1.103]. The association between the genetic score and incidence of major diseases was stronger (HR per added risk allele = 1.004, P value = 0.002; HR 4th vs. 1st quartile = 1.160). Associations were stronger for individuals dying at older ages. Our findings are compatible with the view of mortality as a complex and highly polygenetic trait, not easily explainable by common genetic variants related to diseases and physiological traits.

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Acknowledgments

We thank Nese Direk, Bart Ferket, Farzin Fakhry, John O. Younge, Felisia Ly, Raluca Mihaescu for their important contribution. This research was supported through funds from The European Community’s Seventh Framework Programme (FP7/2007-2013), ENGAGE Consortium, grant agreement HEALTH-F4-2007-201413. The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research NWO Investments (No. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Ageing (NCHA) project No. 050-060-810. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. TwinGene was supported by grants from the Ministry for Higher Education, the Swedish Research Council (M-2005-1112 and 2009-2298), GenomEUtwin (EU/QLRT-2001-01254; QLG2-CT-2002-01254), National Institutes of Health (Grant DK U01-066134) and the Swedish Foundation for Strategic Research (SSF; ICA08-0047).

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Authors and Affiliations

  1. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    Andrea Ganna, Patrik K. E. Magnusson, Nancy L. Pedersen & Erik Ingelsson

  2. Department of Epidemiology, Erasmus University Medical Centre, PO Box 2040, 3000 CA, Rotterdam, The Netherlands

    Fernando Rivadeneira, Albert Hofman, André G. Uitterlinden & Henning Tiemeier

  3. Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands

    Fernando Rivadeneira & André G. Uitterlinden

  4. Netherlands Consortium for Healthy Ageing (NCHA), Rotterdam, The Netherlands

    Fernando Rivadeneira, Albert Hofman & André G. Uitterlinden

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  1. Andrea Ganna
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  2. Fernando Rivadeneira
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  3. Albert Hofman
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  4. André G. Uitterlinden
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Correspondence to Henning Tiemeier.

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Ganna, A., Rivadeneira, F., Hofman, A. et al. Genetic determinants of mortality. Can findings from genome-wide association studies explain variation in human mortality?. Hum Genet 132, 553–561 (2013). https://doi.org/10.1007/s00439-013-1267-6

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