If our initial haplotype association had not been replicated in all four follow-up samples, it would have been difficult to argue against the possibility of a false positive. However, the probability of observing a second false positive of similar strength is low (<0.005). Other possible explanations for incomplete replication include undetected population structure, use of underpowered replication samples, and heterogeneity between samples. However, adjustment for potential population stratification via principal components only modestly diminished the associations reported here. Similarly, differential power based on sample size differences does not appear to explain the incomplete replication as the NECS sample was arguably the least well-powered due to small sample size and skewed case-control ratio. Heterogeneity between samples can occur for a variety of reasons, such as differential ascertainment of cases or between-sample differences in environmental exposures. One potential source of heterogeneity is differential ascertainment of LLI, as the minimum age for inclusion varied by meta-analysis test statistic.In the two-stage analysis, we accounted for case-control status and recomputed the test statistics for all SNPs and haplotypes. After 10,000 permutations, we computed adjusted P-values to reflect the probability of each result occurring by chance alone. To determine if our most extreme P-value was significantly different from what we would expect if there was no true association, we calculated an empirical P-value as the proportion of permutations in which a more extreme result was observed in any of the SNPs or haplotypes analyzed. To establish whether a significant excess of haplotypes with P < a was observed for a given a-level, we computed empirical P-values as the proportion of permutations in which we observed as many haplotypes with P < a as in our original data.

Acknowledgments: This work has been supported by grants from Glenn Award for Research in Biological Mechanisms of Aging (N.B.), NIH PO1 AG027734 (N.B.), NIHNIA Longevity Consortium U19 AG023122 (G.A., T.P), NIHNIA R56 AG027216 (C.B.), and NIHNHLBI R01 HL87681-01 (N.S.). We thank Drs. Gilles Thomas, Helene Blanche, and Valerie Morel for genotyping the French samples analyzed in this study and Narisu Narisu for providing technical assistance with the genotyping of the Stage 1 samples.

To account for multiple testing in the two-stage analysis, we performed permutation tests in R to obtain an empirical P-value for the best observed Malovini A, Illario M, Iaccarino G, Villa F, Ferrario A, Roncarati R, Anselmi CV, Novelli V, Cipolletta E, Leggiero E, Orro A, Rusciano MR, Milanesi L, Maione AS, Condorelli G, Bellazzi R, Puca AA (2011) Association study on long-living individuals from Southern Italy identifies rs10491334 in the CAMKIV gene that regulates survival proteins.