single variants to human longevity, have been published; still, only two genes repeatedly show an association, APOE and FOXO3A.3,31–34 One reason for this may be that the effect of the individual variant is believed to be small,35 and hence may not be easily identified by single variant analysis. Moreover, to avoid false positive findings, there is a need to correct for multiple testing as numerous variants are often tested at the same time. This requires very low P-values in order to obtain significance. Investigation of the combined effect of genetic variants of entire pathways is a recent approach,36 which may circumvent such difficulties. From a biological point of view, the rationale for such analysis is that it is the collective functions of the gene products in a pathway, which has a role in the cell, and, thus, the joint effect of the gene products is important to study. From a statistical point of view, a combined analysis of sets of SNPs and genes is also advantageous as it reduces the multiple testing burden and typically increases power.37,38

DNA was isolated from blood spot cards or full blood using QIAamp DNA Kits (Du¨sseldorf, Germany), and genotyping of all samples was performed on the Illumina GoldenGate platform (San Diego, CA, USA). Data cleaning of all samples were made according to the manufacturer’s recommendations in the GenomeStudio software (http://www.illumina.com/software/genomestudio_ software.ilmn). First samples and SNPs with a call rate o90% were excluded. Next, further data cleaning was done of SNPs with (a) a call rate 90–95%, (b) close clusters (score o2.3), (c) clusters of low intensity (score o0.2 or 40.8), (d) a heterozygote cluster shifting towards a homozygote cluster (score o0.13), (e) excess heterozygosity (score o(cid:3)0.3 or 40.2) and of (f) SNPs located on the X chromosome. Overall 8.8% of the individuals and 10.4% of the SNPs were excluded, leaving data on 592 SNPs in 77 genes from 1089 oldest-old and 736 controls. The 77 genes are listed by sub-process in Table 1. This data has been analyzed at the single-SNP level for the association to human longevity.40

In this study, we focus on common variation in 77 DNA-damage response and repair genes composing the above mentioned nine sub- processes. First, we investigate the association of the overall pathway with longevity. Next, we apply a gene-set method put forward by Wang et al39 to test whether any of the nine sub-processes is more associated with longevity than the other sub-processes. The analyses were carried out in a study population of 1089 oldest-old and 736 middle-aged Danes, whereas replication was done in a German study population of 763 long-lived individuals and 1085 controls.

Data set – genotype data of the replication population

Data on 700 SNPs from the same 77 gene regions was extracted from an existing data set of 664472 SNPs from the German replication sample.43 Genotyping was done using the Affymetrix Genome-Wide Human SNP Array 6.0 (San Francisco, CA, USA). Quality control was carried out in R44 and Plink;45 SNPs were included if (a) the call rate was Z95% in the cases and controls, (b) the MAF was Z0.02 in the controls or |MAF (controls) – MAF (cases)| 40.02 and (c) the Hardy–Weinberg equilibrium P-value in the controls was 40.01. Population stratification was found to be low.43 After visual inspection of cluster plots, 696 SNPs were applied in the replication study.

MATERIALS AND METHODS

Data set – subjects of the discovery population

Statistical analyses – self-contained set-based analysis

The details of the discovery population are described in Soerensen et al.40 The oldest-old were participants from The Danish 1905 Cohort Study,41 a nationwide population-based survey of an entire birth cohort, initiated in 1998 when 3600 birth cohort members were still alive; 2262 participated in the survey of which 1651 gave blood samples. The age range for the 1089 individuals included here was 92.2–93.8 years (29% males). The control group was of 736 individuals from the Study of Middle-Aged Danish Twins,42 started in 1998 by random selection of 2640 intact twin pairs from 22 consecutive birth years (1931–1952) via the nationwide Danish Central Person Registry. Only one twin from each twin pair was included in the present study, and the age range was 46.0–55.0 years (50% males). Due to minimal immigration into both cohorts, they are considered genetically homogenous, and population stratification is considered minimal. Permission to collect blood samples and usage of register-based information was granted by The Danish National Committee on Biomedical Research Ethics.

A set-based analysis of all SNPs was performed in Plink.45 We applied the most inclusive settings, (ie set-max 99999, set-r2 1 and set-p 1). Single-marker P-values from Cochran–Armitage’s trend test were summarized by the overall mean of all SNPs, thus estimating the average association of the entire SNP-set with longevity. Significance was determined by permuting the phenotype labels 10000 times.

Statistical analyses – competitive gene-set analysis

We performed a gene-set analysis using the competitive46 gene-set enrichment method published by Wang et al,39 which we implemented in R.44 The analysis was in four steps: step 1: an association analysis was conducted to calculate a statistic (respectively P-value) for each SNP, step 2: based on these, a gene statistic was assigned to each gene choosing the statistic corresponding to the most significant SNP in each gene, step 3: based on these gene statistics, the enrichment score was calculated for each of the nine sub-processes,

Table 1 The 77 genes grouped by biological sub-process