Italy, were recruited for this study. The participants were genotyped for the (A/G)-308 polymorphism of the TNF gene. A genetic-demographic (GD) approach was used to analyze the data and compare survival functions between allele A carriers and non-carriers. The results showed that men carrying the A allele had a lower survival function than non-carriers at all ages (p<.044). Furthermore, the frequency of men carrying the A allele decreased with age (p<.019). No significant association was found in women. These findings suggest that allele A has a negative effect on life expectancy, specifically in men. Haplotype analysis confirmed the association of the TNF region with life expectancy in men. The addition of demographic information to genetic data allowed for a rational definition of age classes and taking into account cohort effects in mortality changes. The study aimed to investigate whether the (A/G)-308 polymorphism affects the probability of reaching extreme old age by genotyping healthy participants ranging from 19 to 110 years old. Genotyping was performed using standard procedures and primers summarized in Table 1. The association with longevity of haplotypes defined by alleles of three microsatellite loci (TNFa, TNFc, TNFe) and the (A/G)-308 polymorphism was also checked.The study recruited individuals from central and northern Italy whose parents and grandparents were also from the same area. The participants' health status was assessed, and no acute pathological conditions were present. The recruitment was part of a multi-center study on aging conducted between 1996 and 2004. Young and middle-aged volunteers were recruited from university students, workers, and blood donor centers, while elderly people (excluding centenarians) were mainly recruited from elderly residences. Centenarian age was verified by researching archival records in the City Hall and/or church registries, paying attention to the concordance between reported age and personal chronologies (age of marriage and military service for men, age of first and last pregnancy for women, age of children, etc.). Centenarians were contacted via telephone through members of their families after their family doctor was contacted.

The basis of the classical GD analysis (28) is the survival function S(x;t ) of a cohort. It is defined as the fraction of individuals in a population born at a certain time t who are still alive at time t  x. The sample included 0 individuals drawn from the Italian population, with ages ranging from 19 to 110 years. Cohorts from the 19th century up to the end of the 20th century are represented in it. For each cohort, the survival function was computed using Arlequin software, in which the likelihood of the observed data evaluated under the hypothesis of no association between loci is compared to that evaluated under the hypothesis of association. Differences in allele, genotype, and haplotype frequency distribution among age groups were tested by a Monte Carlo likelihood ratio chi-square test implemented in the statistical software package SPSS for Windows (SPSS, Inc., Chicago, IL). Tables of death counts per calendar year and per year of birth and of birth counts per year were reported for Italy in the Human Mortality Database (www.mortality.org). To take into account the dramatic changes in mortality that the cohorts under study experienced, a synthetic survival function S(x) was computed from the cohort survival functions as described in (29). The term synthetic was dropped for brevity in the text that follows. As data were available for both male and female subpopulations, distinct survival functions were computed for the two genders. If we regard the population (whole, male, or female) as consisting of carriers of A allele (AA and AG genotypes) and noncarriers of A allele (GG genotypes), we can define the survival functions S(x) and S(x) of carriers A and noncarriers, respectively. The marginal survival functions S(x) and S(x) were estimated from the A B genotypes and ages of the individuals in the sample by maximizing an appropriate likelihood (29). The null hypothesis S(x)  S(x)  S(x), which means that the A B TNF(A/G)-308 polymorphism does not affect survival, was tested using the likelihood ratio. Because in this case the probability distribution of the ratio is not known, it was empirically built up by Monte Carlo simulation (29) (1000 virtual samples). All analyses used a Matlab (MathWorks, Natick, MA) code described in (29).

The GD analysis of survival functions categorized individuals according to the presence or absence of the A allele at the TNF(A/G)308 locus. The survival function of carriers (AA plus AG) and noncarriers (GG) of the A allele was estimated, assuming that AA and AG genotypes have a comparable effect on the survival phenotype. This consideration came from literature data that report a functional role of allele A associated with a higher expression of TNF-a (1113). Furthermore, as the survival function is sex-specific, the analysis was carried out separately for men and women. Figure 1 shows the maximum likelihood estimates of the survival functions in male carriers and noncarriers of allele A (AA plus AG genotypes and GG genotype, respectively). At all ages, the survival function estimated in the A carriers (S(x)) was lower than that in the noncarriers (S(x)); furthermore, the null hypothesis S(x)  S(x)  S(x), where S(x) is the A B survival function estimated in the whole male population, was rejected with an empirical probability level of p  .044. In women, the survival functions of A and non-A participants were not significantly different from that of the population (p  .16; data not shown). Therefore, the data indicated a dominant, detrimental effect of allele A on survival, present in men but not in women.