control). 281 nested SNP sets were used to compute the posterior probability of exceptional longevity in the 4 subjects (y-axis) and were plotted against the number of SNPs in each set (x-axis). In the 107 year old, the first 5 SNP sets S =[rs2075650], S =[S , rs1322048], …, S =[S , rs6801173] 1 2 1 5 4 determine a posterior probability of exceptional longevity ranging between 0.54 and 0.28. This subject carries genotypes AA, AG, AG, CC, AA for the 5 SNPs respectively and, with the exclusion of genotype AA of rs2075650 that is more common in centenarians, the other genotypes are more common in controls than centenarians and determine a posterior probability of exceptional longevity that is lower than the posterior probability of average longevity. The sixth SNP set, S =[S , rs337656], predicts an almost 30% chance of exceptional longevity. The subject carries the AA genotype for the 6 5 SNP rs337656 that is more frequent in centenarians (Table S1), and carrying this genotype increases the posterior probability of exceptional longevity. The probability predicted by the next SNP sets increases steadily and all models with more than 20 SNPs predict more than a 50% chance of exceptional longevity. This genetic profile shows that the subject carries some combinations of SNP alleles that are associated with exceptional longevity, while other alleles are associated with ‘‘average longevity’’. However, the overall genetic risk profile determined by all 281 SNP sets makes a strong case for exceptional longevity because the majority of models predict more than an 80% chance of exceptional longevity. The genetic risk profile of the centenarian who died at age 119 years is even more convincing: with the exception of the first SNP, all subsequent SNP sets determine more than a 70% chance of exceptional longevity, and 272 of the 281 models predict more than an 80% chance for exceptional longevity. This profile shows that this subject is highly enriched for SNPs alleles that are more common in centenarians (longevity associated variants) and that probably played a determinant role in the extreme survival. The profile of the third subject, age 108 years, shows that different SNP sets determine different chances for exceptional longevity, and only the overall trend of genetic risk provides evidence for exceptional longevity. The fourth plot displays the profile of a control, and shows that this subject carries some longevity associated variants; however, the overall trend of genetic risk points to average longevity rather than exceptional longevity. doi:10.1371/journal.pone.0029848.g006

correlation between the top two PCs and the score predicted our model, and there appears to be none (Figure S10).

itself provides information about the different sets of longevity associated variants that drive a subject toward this probability. The same cluster analysis of predicted profiles in centenarians of the merged replication sets 1 and 2 identified 15 clusters with 8 or more subjects, while approximately 35% profiles clustered in groups of 7 or less. The two most predictive and the one least predictive clusters from the replication set are also shown in Figure 8. Figure S12 depicts all 15 clusters with 8 or more

Genetic Signatures

Some genetic risk profiles were recurrent and we speculated that groups of centenarians may have genetic risk profiles that are associated with different sub-types of exceptional longevity such as different prevalences or ages of onset of age-related diseases. To test this hypothesis, we used cluster analysis to group the genetic risk profiles into prototypical signatures. We then investigated whether groups of centenarians with particular genetic risk profiles shared specific age-related sub-phenotypes.

To examine the specificity of the profiles in characterizing exceptional longevity, we also generated genetic risk profiles of the control subjects in the discovery set and used cluster analysis to group them. Only 5 subjects had profiles that predicted exceptional longevity with more than 90% posterior probability (Figure S13). Other clusters with more than 8 subjects show that the majority of these profiles match either the lack of a predictive

Cluster analysis identified 26 groups of 8 to 94 centenarians (90% of the discovery set) with similar genetic risk profiles, while 10% of the centenarians had rare profiles that occur in groups of 7 centenarians or less. Figure 8 shows, for example, the 9 largest clusters while all clusters are shown in Figure S11. The prototypical genetic risk profiles associated with each cluster are informative displays of the longevity associated variants, and represent different genetic signatures of exceptional longevity. While the ensemble of genetic risk models provides a global estimate of the probability of exceptional longevity, the pattern

longevity associated variants of clusters C24–C25 in Figure S11. To further extend this analysis, we clustered the genetic profiles of all 4118 controls that include all controls in the discovery and replication sets 1 and 2. Cluster analysis identified several signatures, of which only 17% predict exceptional longevity with

A: Discovery SetB: Replication Set 1  0zSel sisson Sala es7:— |Ww00 0.2 04 06 o8 110 00 02 04 06 08 10Probability of EL Probability of ELC: Trend of Predictive Score D: Trend of Sensitivity:s 400+ 101+ 102+ 103+ 104+ 105+ 106+ 95+ 100+ 101+ 102+ 103+ 104+ 105+ 106+E: Replication Set 1 F: Replication Set 22 iia< 3<x2) ~~ izaw 0.0 0:2 04 06 08 1:0Probability of EL 010 02 0:4 06 08 110Probability of EL