Other phenotypic variables: Collection of data for health deficit variables construction of the deficit index are essentially described (Jazwinski et al., 2010). Briefly, the index (DI) was derived as the unweighted count of number of deficits divided by the total number possible deficits (N = 48) in an individual. The reported medical history questionnaire was administered to all study participants, and its components used to construct the deficit index. This was supplemented with items from an activities-of-daily (ADL) questionnaire. The continuous-scale function performance test involves the performance of ten standardized tasks (CS-PFP10) representing activities of daily living including carrying, donning clothes, sweeping the floor, loading a climbing stairs along with a 6-min timed walk (Guralnik et al., 1996, 2005). The Yale Physical Activity is to assess physical function and activity (DiPietro et al., 1993). We used one of its indices, Yale Energy Expenditure (YEE), which is the time spent for each activity multiplied by intensity code, expressed as kilocalories per Mini-Mental State Examination (MMSE) was used to screen for cognitive impairment (Folstein et al., Rovner and Folstein, 1987). Age of subjects verified using both documentary evidence and graphic questionnaires. Mortality data were obtained using Social Security Death Index search.

Genotyping: The Illumina GoldenGate assay was performed according to the manufacturer's instructions. SNPs were selected according to the Illumina Assay Design Tool. Following completion of the assay, all the samples were analyzed using Illumina GenomeStudio. Initial clustering was performed with the 10th percentile GenCall score set at 0.4 for both samples and SNPs. Samples with call rates below 90% were removed, and those remaining samples were re-clustered. SNPs not in Hardy-Weinberg proportions or with minor allele frequency lower than 1% were removed.

SNP rs7896005 (A/G; A is ancestral) is located in an intron of SIRT1. It is part of a large linkage disequilibrium (LD) block encompassing the entire gene (Online Resource 2). The A allele of rs7896005 shows great ethnic variation in frequency: in the HapMap-CEU sample, its frequency is 0.288; whereas in Asian and African samples, it exceeds 0.8. The SNP rs132793 (G/A) is located in the intergenic region between the convergent XRCC6 and NHP2L1 genes on chromosome 22 (Online Resource 3). According to the dbSNP database, the G allele of rs132793 is ancestral with its frequency ranging from about 0.8 in the HapMap-CEU sample to almost unity in the HapMap-YRI. It is located about 3.6 kb downstream from the end of the last exon of XRCC6 and about 6.3 kb downstream from the end of the last exon of NHP2L1. XRCC6 is about 4,300 nucleotides long from the first exon to the last (including introns), and the NHP2L1 is about 1,500 nucleotides long. NHP2L1 is a human orthWith regards to SIRT1 and telomere maintenance, the XRCC6 SNP rs132793 in the 30 flanking region of this gene is in high linkage disequilibrium (D0 = 1) with two SNPs in the promoter region and one in the first intron of XRCC6 (Online Resource 3). This SNP has been used as a marker for XRCC6 in several studies (Sobczuk et al. 2010; Li et al. 2011; Liu et al. 2007). No significant differences in genotype distribution of the SNP were observed between males and females, and the population sample was in Hardy-Weinberg proportions for variation at this locus (P >| 0.1).

In Fig. 1, a plot of normal log-transformed telomere length (T/S) versus age with a linear regression slope is shown. Each circle represents an individual subject. The mean T/S ratios significantly differed between subjects grouped according to the genotypes of rs132793 (P = 1.91 x 10^-2, Table 4). The mean T/S values increased as the number of copies of the minor allele A increased, resulting in significant differences between GG and AA groups (P = 4.36 x 10^-2) and GG and AG + AA combined groups (P = 4.42 x 10^-2). The association of T/S with rs132793 was examined in detail using multiple linear regression (Table 3). The additive mode of inheritance for the genetic effect of the minor allele was statistically significant (model b), and the significance persisted after adjustment for age (model c). These results indicate that shorter telomeres are associated with rs132793.

It is worth noting that the overall gender difference in health status may well reflect the shorter telomeres associated with rs132793, as males scored significantly better than females on the DI (P = 1.62 x 10^-5). According to Cox regression, there was no association of T/S with survival (P >| 0.1), but survival was highly dependent on age (P = 9.14 x 10^-12).

Regarding SIRT1 and telomere length, the SIRT1 SNP rs7896005, located in an intron and part of an LD block in SIRT1, had a significant association with T/S independent of age and XRCC6 SNP rs132793 (Table 3). The minor allele A of rs7896005 was associated with longer telomeres. In addition, the frequency of the minor allele of the SIRT1 SNP rs7896005 was higher in the long-lived cases (C90 years old) than in the young controls (20-59 years old) of the LHAS population (Table 5), and logistic models predicted that the odds of homozygotes of the minor allele being associated with the long-living case group is more than two-fold higher than the odds of other genotype carriers (Table 6).

Finally, we tested whether rs132793 is associated with longevity, but found no significant differences in allele and genotype frequencies between nonagenarian cases and young controls of the LHAS population (Table 5). Incorporation of the XRCC6 SNP rs132793 in the same logistic model with the SIRT1 SNP rs7896005 showed that the association with longevity of SIRT1 persists independently of XRCC6 (Table 6).