As far as we know, this is the first association study of longevity susceptibility genes adopting a high-throughput candidate gene approach in nona- genarians and centenarians who rarely appear in Korea. An understanding of the mechanisms under- lying aging and longevity by discovering novel susceptibility genes may lay the foundations for prediction, prevention, and treatment of age-re- lated diseases. Thus, the findings of the current study may provide a starting point to unravel genetic factors controlling longevity for future studies.

Statistical analysis

At each SNP, the genotyping call rate (CR ＞ 95%), minor allele frequency (MAF ＞ 2%), and deviation from Hardy-Weinberg equilibrium (HWE P ＜ 0.0001) were separately computed in the long-lived group and the young healthy group. Ancestral alleles for each SNP were determined using the dbSNP database. The SNPs-based whole genome association studies (SNPassoc) program implemented in the free downloadable statistical software environment R v. 2.6.2 (http://www.r-project.org) was used to perform the quality tests for genotypes (González et al., 2007). We performed preliminary analyses of linkage disequilibrium (LD) patterns using both D' and r2 and then selected a set of tagging SNPs within a gene for the haplotype-based analysis using Haploview v. 4.0 (http:// www.broad.mit.edu/mpg/haploview/ index.php/).

Methods

Subjects

We identified 137 long-lived individuals over 90 yr old including 35 centenarians from the Korean Centenarian Study, which began in 1999 (Choi et al., 2003). We also selected 213 healthy middle school students from indivi- duals who visited the Samsung Seoul Hospital for psychia- tric tests in 2003 to be used for comparison. Eight control samples from a three-generation family were included to test genotype quality. After informed consent was obtained from all subjects, a clinician interviewed study subjects and

We performed subsequent statistical analyses for each of four groups stratified by age and gender (nonagena- rians, male nonagenarians, female nonagenarians, and female centenarians). We assessed allelic association with the χ2-tests for individual SNPs and calculated the allelic

Bergman A, Atzmon G, Ye K, MacCarthy T, Barzilai N. Buffering mechanisms in aging: a systems approach toward uncovering the genetic component of aging. PLoS Comput

odds ratio (OR) and 95% confidence interval (CI) in both adjusted and stratified analyses using publicly available subroutines 'genassoc' and 'gamenu' in the STATA/SE v. 9 software package (http://www.gene.cimr.cam.ac.uk/clayton/ software/stata/).

Briollais L, Wang Y, Rajendram I, Onay V, Shi E, Knight J, Ozcelik H. Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population- based study in Ontario. BMC Med 2007;5:22

We performed genotypic association tests and logistic regression analyses implemented in the SNPassoc package in five different genetic models: codominant, dominant, recessive, over-dominant, and log-additive. To account for the impact of substructure or genetic relatedness among the subjects, we estimated the 'inflation factor (λ)' for each age-gender group and corrected P values by genomic control (Devlin and Roeder, 1999).

Capri M, Salvioli S, Sevini F, Valensin S, Celani L, Monti D, Pawelec G, De Benedictis G, Gonos ES, Franceschi C. The genetics of human longevity. Ann NY Acad Sci 2006;

We used general linear models for the regression of longevity on ambiguous haplotypes. Rare haplotypes with an allele frequency of less than 1% were combined in a group to be analyzed. We applied logistic regression models (LRMs) to perform two-way interaction analyses between two SNPs for each gene (Briollais et al., 2007). For each of four age/gender groups, we screened the most promising pairs of SNPs that yielded P ＜ 0.01 for the interaction likelihood ratio test (i.e. LRT = -2(logL - ij full(i,j) logL ) under the five genetic models. Subsequently, additive(i,j) we obtained the ORs and 95% CIs under the best fitting model for both marginal effects and interactions of the pair of SNPs.

Chanock SJ, Manolio T, Boehnke M, Boerwinkle E, Hunter DJ, Thomas G., Hirschhorn JN, Abecasis G., Altshuler D, Bailey-Wilson JE, Brooks LD, Cardon LR, Daly M, Donnelly P, Fraumeni JF Jr, Freimer NB, Gerhard DS, Gunter C, Guttmacher AE, Guyer MS, Harris EL, Hoh J, Hoover R, Kong CA, Merikangas KR, Morton CC, Palmer LJ, Phimister EG., Rice JP, Roberts J, Rotimi C, Tucker MA, Vogan KJ, Wacholder S, Wijsman EM, Winn DM, Collins FS. Replica- ting genotype-phenotype associations. Nature 2007;447: 655-60

Choi YH, Kim JH, Kim DK, Kim JW, Kim DK, Lee MS, Kim CH, Park SC. Distributions of ACE and APOE polymorphisms and their relations with dementia status in Korean centenarians. J Gerontol A Biol Sci Med Sci 2003;58: 227-31

We computed the statistical power of our sample sizes for each genotype using the web browser 'Genetic Power Calculator' (http://pngu.mgh.harvard.edu/~purcell/gpc/cc2. html) under an additive model with the assumption of disease allele frequencies of 0.3, D' of 1, and a longevity prevalence of 0.13% and 0.002% for the Korean nona- genarians and centenarians, respectively (Purcell et al., 2003).

Christensen K, Johnson TE, Vaupel JW. The quest for genetic determinants of human longevity: challenges and insights. Nat Rev Genet 2006;7:436-48

A, Berardelli M, Motta M, Monti D, Bonafé M, Ferrucci L, Deiana L, Pes GM, Carru C, Desole MS, Barbi C, Sartoni G., Gemelli C, Lescai F, Olivieri F, Marchegiani F, Cardelli M, Cavallone L, Gueresi P, Cossarizza A, Troiano L, Pini G, Sansoni P, Passeri G, Lisa R, Spazzafumo L, Amadio L, Giunta S, Stecconi R, Morresi R, Viticchi C, Mattace R, De Benedictis G, Baggio G. Do men and women follow different trajectories to reach extreme longevity? Italian Multicenter Study on Centenarians (IMUSCE). Aging (Milano) 2000;12:

Supplemental data