2.3. Statistical

non-carriers of the respective genotypes (Yashin et al., 1999, 2000; Tan et al., 2002). In particular, parametric, semi-parametric, non-parametric and relative-risk models were used to discover possible differences between the survivorship of carriers and non-carriers of TT, GG and GT genotypes. Only the non-parametric model gave adequate parametrization of mortality rates in Gompertz’s form, with corresponding modelled survival curves giving appropriate approximation to empirical survival function for the whole population. Therefore we tested the formal hypothesis of gene longevity effects (standard likelihood ratio test) by the non-parametric model, and calculated p-values based on upper-tail x2 values (MATLAB software).

2. Materials and methods

2.1. Population sample

An appropriate campaign of recruitment was launched in Calabria (southern Italy) for genetic studies on ageing in 1999, excepted for centenarians whose recruitment started beginning from 1994. The recruitment campaign was focused on University students and staff for 18–60 years old people, thermal baths and aged people-Academy for 60–80 years old people. As to the centenarians, they were identified through the birth registers of the Municipalities of Calabria and then contacted. Only subjects born and living in Calabria were invited to take part to the study and after a detailed explanation of the research project, more than 90% of the contacted persons agreed to participate and gave their informed consent to studies on ageing carried out by the present research group. For each subject routine blood analyses were carried out and, in addition, subjects older than 60 years underwent a complete clinical and geriatric assessment. A total of 801 unrelated subjects (331 males and 470 females) free of clinically overt pathologies and having routine blood parameters in the normal sex- and age-specific range were enrolled in the study. The sample included 120 subjects older than 100 years (36 males and 84 females). These centenarians, classified in the categories A and B according to the criteria reported by Franceschi et al. (2000), were in a fairly good health status and did not suffer major pathologies or disabilities.

Note that in this study we deal with cross-sectional data, where gene frequencies for different ages are calculated for individuals from different cohorts. We combine this information with demographic life table data to evaluate age patterns of mortality rates and survival functions for carriers of respective genes or genotypes. Before statistical calculations using cross-sectional data on genetic markers were made, we performed preliminary historic-demo- graphic analysis of the Italian population where data came from. Such analysis was needed to make sure that migration processes did not produce much change in the initial frequencies of respective genes and genotypes in the cohorts participating in the cross-sectional study.

The method described by Weir (1996) was used to assess ; linkage disequilibrium D and to check the null hypothesis D ¼ 0; between the G477T marker of SIRT3 and each of the markers previously analysed at the loci HRAS1 (Bonafe` et al., 2002) and IGF2, INS, TH (De Luca et al., 2001). Maximum Likelihood Estimation (MLE) was used to estimate the haplotypic frequencies (Arlequin 1.1 software).

2.2. DNA analyses

3. Results

After DNA extraction from blood buffy coats of 50 subjects randomly chosen, a 738 bp DNA fragment

By searching for variability in the evolutionary conserved domain of the SIRT3 gene (exon 2–exon 3) we

Survival Functions405060 70Age (Years)— (GG)Modeleee Experiment80 90100

Survival Functions   — (17)Modeleee Experiment   40 50 60 70 80 90 100Age (Years)

Fig. 3. Survival functions for carriers of GG genotype among Italian males. Empirical and modelled survival function for the whole population are also shown (please note that the three curves almost completely overlap).

Fig. 1. Survival functions for carriers of TT genotype among Italian males. Empirical and modelled survival function for the whole population are also shown (please note that the empirical curve almost completely overlaps with the modelled one).

was observed in females (p ¼ 674 for TT; p ¼ 845 for GT; p ¼ 0: 777 for GG).

identified a silent G/T transversion at the position 477 of the coding region (G477T corresponding to Ser159Ser; AF083108). We used this marker to investigate possible modifications of the SIRT3 gene pool in people of increasing age, including the oldest old. We found that, in males, the TT genotype increased ðp ¼ 0: 0272Þ while the GT genotype decreased ðp ¼ 0: 0391Þ the value of the survival function; the GG genotype did not affect significantly the survival function ðp ¼ 0: 871Þ (Figs. 1–3; note that the modelled functions start from the minimal age present in the subpopulation of carriers of the respective genotype, and then scales along the age axes are different). As previously observed for other loci (see Franceschi et al., 2000; De Luca et al., 2001 and references therein) the association between SIRT3 variability and survival was restricted to males,

The sample we were analysing in the present study had already been typed, at least in part, for markers of other genes spanning for 1.5 Mb about in the same region and associated with longevity (HRAS1, IGF2, INS, TH). Since the association between SIRT3 and survivorship could be due to allelic associations, we tested for linkage disequili- brium (LD) between the G477T marker of SIRT3 and markers of the above genes. In particular, after verification of the Hardy Weinberg equilibrium for the SIRT3 polymorphism (see Supplementary material), LD was checked between G477T polymorphism and HRAS1- 30 VNTR; IGF2-Ava II-RFLP; INS-Fok I-RFLP, and HUMTHO.1-STR. Results are shown in Tables 1–4, respectively, where it can be seen that the hypothesis D ¼ 0 cannot be rejected in any case.