Here, we report upon a GWAS using a case-control study design in which we compared more than 760 centenarians and nonagenarians, who represent an exceptional longevity phenotype, with more than 1000 younger controls. We replicated and confirmed APOE as the major genetic determinant of survival into old age. In addition, when we tested the 33 SNPs of Sebastiani et al. in our samples, only the APOE-related marker was significant.rs2075650 showed a significant association. 

2. Materials and Methods 

2.4. Haplotype Analysis 

In stage 1, data underwent haplotype-based association analysis using a two-marker sliding window. Maximum-likelihood estimates of haplotype frequencies were obtained, and posterior probabilities of haplotypic genotypes were calculated for each individual. A score test for association with a binary phenotype was conducted, assuming an additive risk model for haplotypes. SNPs involved in the 5000 most significantly associated haplotypes underwent visual inspection of the corresponding cluster plots (see Supplementary methods). Haplotypes for which both SNPs passed the inspection were genotyped and analyzed in stage 2. The analysis was carried out in R v2.7.1 (R Development Team, 2008), using the haplo.score function of R package haplo.stats v1.3.8 (Schaid et al., 2002), which takes phase uncertainty into account.

In stage 1, we conducted a GWAS study on a total of 763 unrelated German long-lived individuals (LLI) between 94 and 110 years of age (mean age: 99.7 years; Table 1). The control group consisted of 1085 German individuals in stage 1 (age range: 45-77 years; mean age: 60.2 years) obtained from the Popgen (Krawczak et al., 2006) and KORA (Wichmann et al., 2005) biobanks. The regional genetic differences between northern and southern Germany are not significant (Lao et al., 2008; Steffens et al., 2006), so the two populations were pooled. The sex ratio was approximately 1:1. For validation in stage 2, we used a sample of 754 LLI with an age range of 95-108 years and a mean age of 96.9 years. The stage 2 control sample of 860 individuals (age range: 60-75 years; mean age: 67.3 years) was matched to the LLI as closely as possible in terms of ancestry, gender, and geographical origin. The sex ratio in this sample was 12:1 in favor of females. The lack of men in stage 2 implies that any male-specific effects observed in the initial screening may not be detectable in the follow-up sample. The description for the stage 1 samples is given in detail elsewhere (Krawczak et al., 2006; Nebel et al.,2005; Wichmann et al.,2005). For stage 2, it is published in Nebel et al.(2005). There are no mortality data available for the controls. However, based on current predictions, only a negligible proportion of younger controls will become long-lived. The probability for males is even lower (Human Mortality Database: www.demogr.mpg.de). 

The French sample used to investigate rs12741354 in ASTN1 comprised 536 centenarians (mean age: 103.7 years) and 508 younger controls (mean age: 50.8 years). Cases and controls were matched for gender and geographic origin (Blanche et al., 2001). The sex ratio was 5:1 in favor of females.

2.5. Testing for Association of 33 SNPs from Sebastiani et al. in German Samples 

To test the association findings of the study by Sebastiani et al., which were obtained from Illumina 370 CNV chips and Illumina 610 arrays, the German Affymetrix GWAS data had to be imputed since different genotyping technologies had been used. Genotype imputation was carried out using a hidden Markov model algorithm implemented in the software program BEAGLE v3.1.1 (Browning and Browning, 2009) and the HapMap 3 samples from the CEU, TSI, MEX, and GIH populations to infer missing autosomal genotypes in silico. To take imputation uncertainty into account, association analysis between the phenotype and the dosage data (expected allele counts) was performed using PLINK's logistic regression framework for dosage data (with flag-dosage).

3. Results 

DNA was isolated from blood samples of all participants using standard methods. All subjects gave written informed consent prior to participation. The protocols were approved by the respective institutional ethics review boards. The study workflow is given in Fig. 1.

3.1. Stage 1 Analyses 

We ranked the SNPs according to their minimum (P) of min P, P, and P. A total of 58,903 markers (8.9%) showed a significant association.et al., 2009) is located within 100 kb of SNP rs4420638. Therefore, we investigated the association between longevity and three common FOXO3A SNPs (rs2802292, rs2764264 and rs13220810). None of these SNPs showed significant association with longevity in our sample (Supplementary Table 2). We also genotyped SNP rs7514229 in EXO1, a gene that has been associated with DNA repair and cell cycle regulation (Matera et al., 2009), but found no significant association with longevity (Supplementary Table 2). These results suggest that the association between APOC1 and longevity is not mediated by FOXO3A or EXO1. 

PROCESSED TEXT:
Nominal P value <0.05. To reduce the rate of false-positive minimum results, cluster plots of the 1600 most significantly associated SNPs (all with P values <9.6 x 10^-6) were subjected to post-hoc visual inspection. Genotyping was done using the Affymetrix Genome-Wide Human SNP Array 6.0 (San Francisco, CA, USA) for individuals in stage 1 (see Supplementary methods for details). For validation, markers were genotyped in individuals from stage 2 along with controls. See Table 1 for a description of LLI and controls genotyped in the two stages of the study. 

Stage Sample No. Mean age (years) Median age (years) Age range (years) 

1 LLI 763 99.7 101 94-110 
1 Controls 1085 60.2 60 45-77 
2 LLI 754 96.9 97 95-108 
2 Controls 860 67.3 66.5 60-75 

LLI: long-lived individuals.