Table 3 Ranking of the genes in the BER, HRR and RECQ sub- processes

Sub-process Gene p-gene (gene statistic) Rank BER WRN 2.1(cid:2)10(cid:3)8 3 APTX 3.6(cid:2)10(cid:3)8 4 NTHL1 1.4(cid:2)10(cid:3)7 5 POLB 1.8(cid:2)10(cid:3)5 6 RPA1 2.4(cid:2)10(cid:3)4 9 XRCC1 4.9(cid:2)10(cid:3)4 13 YBX1 1.5(cid:2)10(cid:3)3 16 PARP1 2.4(cid:2)10(cid:3)3 20 OGG1 2.8(cid:2)10(cid:3)3 21 PCNA 3.0(cid:2)10(cid:3)3 22 ERCC8 4.9(cid:2)10(cid:3)3 26 UNG 6.0(cid:2)10(cid:3)3 28 LIG3 1.9(cid:2)10(cid:3)2 36 POLD1 2.8(cid:2)10(cid:3)2 41 APEX1 2.9(cid:2)10(cid:3)2 42 HMGB1 3.6(cid:2)10(cid:3)2 43 RFC1 4.1(cid:2)10(cid:3)2 46 NEIL1 5.1(cid:2)10(cid:3)2 50 PNKP 6.3(cid:2)10(cid:3)2 51 LIG1 6.5(cid:2)10(cid:3)2 54 NEIL2 7.3(cid:2)10(cid:3)2 57 ERCC6 8.8(cid:2)10(cid:3)2 61 POLE 1.6(cid:2)10(cid:3)1 68 RECQL4 1.6(cid:2)10(cid:3)1 69 FEN1 1.9(cid:2)10(cid:3)1 73 RECQL5 8.1(cid:2)10(cid:3)1 77 HRR RAD52 4.3(cid:2)10(cid:3)18 1 NBN 2.1(cid:2)10(cid:3)3 18 MRE11A 4.0(cid:2)10(cid:3)3 24 RAD54L 2.7(cid:2)10(cid:3)2 39 LIG1 6.5(cid:2)10(cid:3)2 54 RAD51 7.8(cid:2)10(cid:3)2 59 RAD50 1.2(cid:2)10(cid:3)1 64 RECQ WRN 2.1(cid:2)10(cid:3)8 3 BLM 7.8(cid:2)10(cid:3)4 15 RECQL4 1.6(cid:2)10(cid:3)1 69 RECQL 2.0(cid:2)10(cid:3)1 75 RECQL5 8.1(cid:2)10(cid:3)1 77

As the three setups showed consistent results, the subsequent analyses in the discovery data were restricted to setup III. To examine which genes contributed to the nominal significance of BER, HRR and RECQ, the individual gene statistics for all genes in these sub-processes were inspected (see Table 3). These gene statistics enter the calculation of the enrichment score as weights and provide intuitive information about the extent to which the score was mainly determined by specific genes. We found several low-ranking genes in the case of BER, while for HRR the association was mostly due to a single gene, RAD52, and to a much lower degree NBN, MRE11A and RAD54L. Similarly, the P-value for RECQ was primarily due to WRN and to a smaller extent BLM. In a post-hoc analysis, we then repeated the gene-set analysis of BER, RECQ and HRR removing the respective lowest ranking gene from the data set. Only BER remained nominally significant (P-value¼0.037), while loss of significance of RECQ (P-value¼0.34) and HRR (P- value¼ 0.88) confirmed that the importance of RECQ and HRR each was induced by only one gene.

Replication study in German long-lived individuals and controls The single-SNP data from the German replication population can be found in the GWAS Central data base (www.gwascentral.org). Repeating the self-contained set-based analysis of all SNPs as well as the competitive gene-set analysis of BER, HRR and RECQ in the

Table 2 Competitive gene-set analysis of the genetic variation in the nine sub-processes of DNA-damage response and DNA repair in relation to human longevity

Setup I – w2 II – trend test III – best-test model Sub-processes P-value q-value P-value q-value P-value q-value DmgRes 0.113 0.171 0.475 0.556 0.299 0.447 BER 0.015 0.110 0.029 0.121 0.016 0.111 NER 0.679 0.681 0.556 0.563 0.679 0.681 MMR 0.434 0.553 0.498 0.556 0.686 0.681 HRR 0.035 0.110 0.004 0.030 0.025 0.111 NHEJ 0.099 0.171 0.163 0.286 0.112 0.231 RECQ 0.032 0.110 0.048 0.159 0.049 0.160 TeloFunc 0.076 0.159 0.077 0.163 0.130 0.231 MitoDNA 0.616 0.681 0.439 0.556 0.608 0.681

Abbreviations: BER, base excision repair; HRR, homologous recombinational repair; RECQ, RecQ helicase activities. Rank: overall rank of each gene among all 77 DNA-damage response and DNA repair genes. P-gene values below 0.05 are shown in bold. The P-gene values listed here were based on statistical setup III and the log-transformed P-gene values were used as weights in the calculation of the enrichment score. The P-gene values for setups I and II can be derived from Supplementary Table 1.

Abbreviations: BER, base excision repair; DmgRes, DNA-damage response; HRR, homologous recombinational repair; MitoDNA, mitochondrial DNA processes; MMR, mismatch repair; NER, nucleotide excision repair; NHEJ, non-homologous end-joining; RECQ, RecQ helicase activities; TeloFunc, telomere functioning.

males and females (data not shown). Similarly, stratification of the competitive gene-set analysis yielded consistent significance of BER. Still, HRR and RECQ did not show significance (setup III, data not shown). The latter might possibly be due to the reduction in sample size in the sex-stratified analysis. Altogether, in the present data, gender-specific differences do not appear to be overly relevant.