The differences between the South and Central Italian and the German populations highlight the importance of taking into account population heterogeneity in this kind of studies.

Despite the biological interest of these results, each of the positive findings requires a follow-up analysis, and no conclusion can be made at present.

Those studies on ageing, which take into consideration demographic data, suggest that different susceptibility genes are likely to underlie the longevity phenotype in genetically different populations. The consequences are crucial with regard to the results (and interpretation) of replication studies.27 Our study is not the only one highlighting contrasting results from different populations, and we suggested that centenarians might be considered phenocopies who display the same pheno- type (longevity), but who have attained longevity by taking advantage of different gene/environment

Discussion

This work represents the results of the analysis on an unprecedented collection of centenarians and controls, and it can be considered the most extensive investigation ever carried out in a case–control study in a specific candidate chromosomal region in ageing.

Table 1 SIRT 3 locus meta-analysis (minor allele)

Allele frequencies Germany Central Italy South Italy France P-value minor Major Minor Major Minor Major Minor Major Minor Marker allele q value allele (%) allele (%) allele (%) allele (%) allele (%) allele (%) allele (%) allele (%) rs2293168 0.2636 0.8383 Controls 96.4 3.6 96.2 3.8 95.8 4.2 96.3 3.7 Centenarians 96.6 3.4 98.0 2.0 96.2 3.8 96.4 3.6 rs511744 0.4417 0.8383 Controls 68.6 31.4 66.8 33.2 67.7 32.3 71.5 28.5 Centenarians 73.6 26.4 68.4 31.6 58.9 41.1 70.7 29.3 rs3782115 0.9547 0.9547 Controls 68.6 31.4 67.4 32.6 66.1 33.9 71.6 28.4 Centenarians 74.7 25.3 66.1 33.9 60.6 39.4 70.0 30.0 rs7934919 0.2479 0.8383 Controls 78.8 21.2 72.4 27.6 74.2 25.8 72.8 27.2 Centenarians 79.8 20.2 72.6 27.4 70.7 29.3 76.9 23.1 rs1045288 0.4316 0.8383 Controls 72.2 27.8 70.3 29.7 71.1 28.9 75.2 24.8 Centenarians 77.8 22.2 70.5 29.5 64.8 35.2 74.3 25.7 rs939915 0.0145 0.145 Controls 80.1 19.9 90.0 10.0 89.6 10.4 80.8 19.2 Centenarians 77.4 22.6 86.1 13.9 91.8 8.2 76.6 23.4 rs559422 0.503 0.8383 Controls 91.8 8.2 93.6 6.4 92.6 7.4 90.9 9.1 Centenarians 91.2 8.8 93.9 6.1 96.1 3.9 92.0 8.0 rs3817630 0.8272 0.9547 Controls 70.7 29.3 67.7 32.3 67.0 33.0 70.8 29.2 Centenarians 74.5 25.5 64.5 35.5 69.2 30.8 70.5 29.5 rs11246020a 0.9488 0.9547 Controls 79.1 20.9 72.4 27.6 75.0 25.0 ND ND Centenarians 79.4 20.6 73.3 26.7 71.3 28.7 ND ND rs11555236a 0.9275 0.9547 Controls 79.2 20.8 72.5 27.5 74.7 25.3 ND ND Centenarians 79.4 20.6 73.0 27.0 71.3 28.7 ND ND

The table shows the P-values resulted from the meta-analysis pooling of four populations (Central Italy, South Italy, Germany and France) in the SIRT3 locus, together with the associated q-value, as far as the minor allele is concerned.

Allele frequencies 11p15.5 meta-analysis Germany Central Italy South Italy Frequent genotype Heterozigous Major Minor Major Minor Major Minor Markers allele (%) allele (%) allele (%) allele (%) allele (%) allele (%) P-value q-value P-value q-value rs4073591 Controls 57.0 43.0 62.0 38.0 54.8 45.2 0.002618 0.3141 Centenarians 56.1 43.9 52.2 47.8 58.2 41.8 rs4073590 Controls 56.9 43.1 62.0 38.0 54.3 45.7 0.004259 0.3407 Centenarians 55.8 44.2 52.2 47.8 58.3 41.7 rs11040489 Controls 78.8 21.2 72.0 28.0 70.0 30.0 0.005869 0.3521 Centenarians 81.0 19.0 77.2 22.8 79.4 20.6 rs4930001 Controls 69.1 30.9 60.3 39.7 55.8 44.2 0.010851 0.3619 Centenarians 71.1 28.9 65.3 34.7 61.4 38.6 rs800140 Controls 75.0 25.0 73.2 26.8 67.7 32.3 0.008109 0.3619 Centenarians 78.5 21.5 77.5 22.5 76.7 23.3 rs16928120 Controls 89.3 10.7 92.5 7.5 87.9 12.1 0.000577 0.1281 Centenarians 93.5 6.5 93.1 6.9 91.7 8.3

The table shows the P-values resulted from the meta-analysis pooling of three populations (Central Italy, South Italy, Germany) in the 11p15.5 only significant P-values are provided together with their associated q-value.

contributions.27 In fact, longevity, more than any other complex trait, may result from a lifelong (more than 100 years) interaction between genetic and environmental factors. Moreover, epigenetics and stochasticity could also contribute to longevity, but such topics are still largely unexplored in humans.

Despite the rather negative findings presented here, we are of the opinion that results deriving from unprece- dented studies involving such a large number of cente- narians should be disseminated, thus contributing to set up adequate strategies to disentangle complex and likely heterogeneous phenotypes.

As the number of males among centenarians is very low,28 it is difficult to set up gender-matched samples. The choice is then to have samples representative of the overall. Although earlier findings clearly indicate gender-specific associations, a stratification by gender in these centenarian populations leads to unacceptable power in the analyzes.

Acknowledgements

thank the GEHA – Genetics of Healthy Ageing Consortium, under the Sixth Framework Programme for RTD of the Commission – Priority 1. Life sciences, Genomics and

supported under the Sixth Framework Programme for RTD of the European Commission – Priority 1. Life sciences, Genomics and Biotechnology for health (contract no. LSHM-CT-2004-503270). For excellent technical assistance, we acknowledge the laboratory personnel of the Institute of Clinical Molecular Biology at the Christian-Albrechts-University Kiel.We thank the Biological Ressource Center at the Fondation Jean Dausset-CEPH for preparing and genotyping DNA samples of the French Population.