2.1. Study participants

Asampleof386unrelatedGermancentenarianswasstudiedwhowerebetween 100 and 110 years of age at the time of recruitment (mean age: 101.3 years). The gender ratio was 79% females vs. 21% males. The 410 German control subjects were between 60 and 75 years of age (mean age: 66.6 years). They were collected by the same means to ensure that they match the centenarians as closely as possible in terms of ancestry, gender and geographical origin within the country [31]. The recruitment was performed in such a way as to minimize any systematic genetic differences between case and control samples that might arise due to very low lev- els of undetected population structure. The comparison of both groups revealed a genomicinflationfactor(cid:3)of1.00(basedon200random,genome-wideSNPs),indi- catingaverywellmatchedcollection.TheFrenchreplicationsamplecomprised541 centenarians(meanage:103.6years)and469youngercontrols(18–70years;mean 51.2 years) as described previously [32]. The gender ratio in the entire sample was 84.3% females vs. 15.7% males. To test for population stratification, 57 microsatel- litesfromtheAppliedBiosystemsLMS-MD10panelthatwerelocatedon6different chromosomes (chromosomes 2, 9, 10, 11, 17, and 18) were tested in all cases and controls.(cid:2)2-valueswerecalculatedfromtheallelecounts.Theobtainedmean(cid:2)2 of the G-test statistics for the markers was 1.00, which reflected the good matching of the French sample collection [33]. All German and French subjects gave informed, written consent prior to participation. The study was approved by the respective Ethics Committees of the participating centers.

2.2. Gene and SNP selection

The genes of interest were derived from extensive literature research and from the Panther Classification System (http://panther.appliedbiosystems.com/ navigation.jsp). They belong to longevity pathways (IIS and energy metabolism, apoptosis, cell cycle control, stress response and intracellular signaling) or are basedongeneticperturbationsinanimalmodelsandonhumandiseases.Theinves- tigated nsSNP-assays were obtained from Applied Biosystems (Foster City, USA) and represent a subset of a large panel of 19779 nsSNPs described elsewhere [34] (http://marketing.appliedbiosystems.com/mk/get/GAAS HUMAN SNPGENO#). Altogether, we investigated 500 nsSNPs in 343 candidate genes (Supplementary

In our analysis of the three candidate SNPs in the German and French samples, we also adjusted for APOE, the only gene shown to have a large effect (OR≈2) on longevity [17,19], to reduce possible bias and confounding as well as to generate better estimates of the ORs. The results differed only negligibly from the non-adjusted ones (data not shown).

(http://marketing.appliedbiosystems.com/mk/get/GAAS HUMAN SNPGENO#). Altogether, we investigated 500 nsSNPs in 343 candidate genes (Supplementary Table).

2.3. Genotyping methods

Genotyping of the German samples was performed with the SNPlexTM Geno- typing System (Applied Biosystems, Foster City, USA) [35]. The typing in the French replication sample was carried out with TaqMan® SNP Genotyping Assays (Applied Biosystems).

4. Discussion

Previously, we have identified a polymorphism in the EXO1 gene as a likely modulator of human longevity in a targeted nsSNP approach [29]. Such an experiment is rapid and cost-efficient as it allows the direct evaluation of possible functional variants. Here, we applied the same strategy for the investigation of addi-

2.4. Statistical analysis

Single marker case–control analyses on allele and genotype frequency data were performed with (cid:2)2-statistics with the open-source software GENOMIZER [36] (http://www.ikmb.uni-kiel.de/software.html). All analyzed nsSNPs had a minor allele frequency of at least 1%, a minimal overall call rate of 94% and

Table 1a

Longevity association statistics for three nsSNPs (German sample).

dbSNP ID Gene Chromosome Alleles MAF controls Corresponding P P OR 95% CI P CCA CCG additive n=410 AF centenarians n=386 rs770087 DUSP6 12 A/C 0.205 (C) 0.145 0.002 0.004 1.53 1.18–1.99 0.002 rs2301582 NALP1 17 C/T 0.385 (T) 0.448 0.011 0.016 1.30 1.06 –1.58 0.011 rs648802 PERP 6 C/G 0.430 (G) 0.493 0.012 0.045 1.29 1.06–1.57 0.015

MAF, minor allele frequency; AF, allele frequency; P , p-value obtained from an allele-based case–control comparison, using a (cid:2)2-test with 1 degree of freedom (df); P , p-value CCA CCG comparison, using a (cid:2)2-test with 2df; OR, odds ratio for attaining old age; 95% CI, 95% confidence interval for OR; P , p-value obtained from logistic regression analysis using an additive (multiplicativity of the odds ratios); P , p-value obtained from logistic regression analyzing the dominant–recessive model with the first allele dominant; P , p-value dom rez 1 dom rez 2 dominant–recessive model with the second allele dominant; Bonferroni, P value adjusted by the classical Bonferroni method for multiple testing (500 tests); Benjamini, P value CCA CCA of Benjamini et al. [39] for all 500 SNPs.

Table 1b

Subgroup analysis (females only) for three nsSNPs (German sample).

dbSNP ID Gene Chromosome Alleles MAF controls Corresponding P P OR 95% CI P P P CCA CCG additive dom rez 1 dom rez 2 n=332 AF centenarians n=304 rs770087 DUSP6 12 A/C 0.204 (C) 0.151 0.013 0.040 1.45 1.08–1.92 0.015 0.059 0.036 rs2301582 NALP1 17 C/T 0.389 (T) 0.453 0.021 0.046 1.30 1.04–1.63 0.024 0.039 0.153 rs648802 PERP 6 C/G 0.432 (G) 0.513 0.004 0.019 1.39 1.11–1.73 0.005 0.037 0.012

Table 2

Longevity association statistics for replication in French sample.

dbSNP ID Gene Chromosome Alleles MAF controls Corresponding P P OR CCA CCG n=469 AF centenarians n=541 rs770087 DUSP6 12 A/C 0.184 (C) 0.193 0.599 0.622 1.06 rs2301582 NALP1 17 C/T 0.353 (T) 0.368 0.486 0.762 1.07 rs648802 PERP 6 C/G 0.413 (G) 0.410 0.891 0.839 1.01

Table 3

Longevity association statistics for the combined analysis of the German and French samples.