Some of the Louisiana samples were genotyped using the SNPlex technology (Applied Biosystems), which is based on the oligonucleotide ligation assay combined with multiplex PCR amplification. Primers were designed according to the SNPlex Design Pipeline for the following SNPs: rs449647, rs769446, rs405509, rs8176330, andSubjects, respectively. Seven hundred and fifteen subjects of known geographic ancestry (European, African, Asian, or Indian) were used as a reference. For each individual, Structure 2.2 estimates the proportion of ancestry from each of four populations. We used a burn-in of 15,000 iterations and ran 20,000 replications. Three replicate runs were performed on each dataset. The largest proportion values in each run were used to calculate the average ancestry proportion for each individual. Individuals were assigned to a specific geographic origin if the average was larger than a predetermined assignment probability (0.9 in this study) or considered admixed if the average was less. All haplotype analyses were performed on samples stratified for ethnic affiliation, as described here.

Deficit Index: Following previously published reports (Kulminski et al., 2008; Searle et al., 2008), our deficit index was derived as the unweighted count of the number of deficits divided by the total number of possible deficits for an individual. The self-reported medical history questionnaire was administered to all study participants, and its components were used to construct the deficit index. This was supplemented with items from an activities of daily living (ADL) questionnaire. Responses were grouped to create broader categories where similar ailments were defined more than once. After applying the above criteria, 42 deficits were included in the compilation of the index.

Linkage disequilibrium approaches to the analysis of gene-gene interactions have been proposed (Zhao et al., 2006), and the modeling of gene-gene interactions using association analysis of non-contiguous haplotypes has been implemented (Woo et al., 2006). We took a similar approach. The haplotype frequencies for the combination of SNP in APOE, HRAS1, and LASS1 were estimated by an Expectation-Maximization (EM) algorithm implemented in Arlequin (Excoffier et al., 2005). The SD was determined by the parametric bootstrap procedure in Arlequin (100 bootstraps). Those haplotype combinations present at a frequency of 0.01 or greater in the 20- to 59-year-old group in Georgia and in Louisiana were analyzed further. This cutoff was taken based on the considerations from comparison of statistical and molecular haplotyping for sample sizes as small as 17 (Tishkoff et al., 2000). The frequency estimates in case and control groups were used to generate 2 x 2 contingency tables to test significance of associations of the respective haplotype combinations with exceptional longevity. Fisher's exact test was used to assess significance. The sequential Dunn-Sidak procedure was used to adjust the exact P-values for multiple comparisons of haplotype combinations. The adjustment included seven such combinations independently identified in the Georgia and Louisiana samples in the subpopulations of European origin (Table S4). In the African-origin subpopulations, there were seven and three such combinations in these samples, respectively. A stringent criterion of adjusted P < 0.01 (two-sided) was used to identify the potentially interacting combinations.