1Epidemiology, Biostatistics and Biodemography, The Danish Aging Research Center, Institute of Public Health, University of Southern Denmark, Odense, 2Department of Clinical Genetics, Odense University Hospital, Odense, Denmark; 3Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, 4Department of Biology, Ecology and Earth Science, University of Calabria, Rende, Italy; 5Department of Molecular Biology and Genetics, The Danish Aging Research Aarhus University, Aarhus, Denmark; 6Laboratory of Molecular Gerontology, National Institute on Aging, National Institute of Health, Baltimore, MD, USA; 7Department of Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark *Correspondence: B Debrabant or M Soerensen, Epidemiology, Biostatistics and Biodemography, The Danish Aging Research Center, Institute of Public University of Southern Denmark, J.B. Winsloews Vej 9B, 5000 Odense C, Denmark. Tel: +45 65503544 (BD) or +45 65412822 (MS); Fax: +45 65503682 or +45 65414875 (MS); E-mail: bdebrabant@health.sdu.dk or msoerensen@health.sdu.dk 8These authors contributed equally to this work and are mentioned in alphabetical order. Received 14 November 2012; revised 7 November 2012; accepted 26 November 2013

1Epidemiology, Biostatistics and Biodemography, The Danish Aging Research Center, Institute of Public Health, University of Southern Denmark, Odense, Denmark; 2Department of Clinical Genetics, Odense University Hospital, Odense, Denmark; 3Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany; 4Department of Biology, Ecology and Earth Science, University of Calabria, Rende, Italy; 5Department of Molecular Biology and Genetics, The Danish Aging Research Center, Aarhus University, Aarhus, Denmark; 6Laboratory of Molecular Gerontology, National Institute on Aging, National Institute of Health, Baltimore, MD, USA; 7Department of Clinical

*Correspondence: B Debrabant or M Soerensen, Epidemiology, Biostatistics and Biodemography, The Danish Aging Research Center, Institute of Public Health, University of Southern Denmark, J.B. Winsloews Vej 9B, 5000 Odense C, Denmark. Tel: +45 65503544 (BD) or +45 65412822 (MS); Fax: +45 65503682 (BD) or +45 65414875 (MS); E-mail: bdebrabant@health.sdu.dk or msoerensen@health.sdu.dk 8These authors contributed equally to this work and are mentioned in alphabetical order.

Data set – subjects of the replication population

related disease and with higher mortality.15–18 Finally, mitochondrial DNA (mtDNA) is exposed to specifically high levels of ROS due to its vicinity to oxidative phosphorylation and is thus potentially exposed to high levels of oxidative damage. Specific proteins maintain the function and repair of mtDNA. Accumulation of mtDNA mutations and mitochondrial dysfunction, likely influenced by age-dependent changes in ROS and DNA repair processes, is thought to have important roles in the aging process.19–21

The details of the replication population are described in Nebel et al.43 The age ranges of the 763 long-lived individuals and the 1085 controls were 94–110 and 45–77 years, respectively (50% males). All participants were of the German ancestry. Approval was received from the ethics committee of the Christian- Albrechts-University.

Data set – genotype data of the discovery population

The details of the selection of sub-processes, genes and SNPs and the generation of genotype data are described in Soerensen et al.40 Sub-processes and genes were identified by a comprehensive literature search in five different databases (including http://www.ncbi.nlm.nih.gov). To cover the core biological functions of the sub-processes, five different databases were consulted (including http://www.biocarta.com). In total, 80 genes were chosen that belonged to one or more of the nine sub-processes. The gene regions plus 5000 base pairs upstream and 1000 base pairs downstream and candidate SNPs in these regions (previously associated SNPs, coding SNPs and SNPs with potential functional impact) were identified using the NCBI (http://www.ncbi.nlm.nih.gov) and UCSC (http://www.genome.ucsc.edu) genome browsers as well as other SNP databases (eg snpper.chip.org). To cover the common genetic variation within each genomic region, tagging SNPs were obtained from the HapMap consortium database (http:// www.hapmap.ncbi.nlm.nih.gov) for the CEU population and selected with the HaploView software (http://www.broadinstitute.org/haploview) with the R240.8 and MAF45% criteria.

are crucial to genetic stability, which is considered of major importance for the aging process and longevity from nematodes to humans.9,19,22–25 Also, research in animal models shows that overexpression or depletion of some of the genes in the processes affects the life span of the organism (eg POLB, RAD52 and TP5326–28), and common genetic variants in humans have been put forward as associated with longevity, for example, in WRN and MLH1).29,30