Human twin studies suggest that only 20–30% of the variation in survival to about 85 years is determined by genetic variation [2]. However, the existence of rare families demonstrating remarkable clustering for extreme ages [3,4], the increased relative risks of survival amongst siblings of nonagenarians [5] and of centenarians [6,7,8,9,10,11,12,13], the fact that children of centenarians experience a marked delay in age-related diseases [14], and the

Based upon the hypothesis that exceptionally old individuals are carriers of multiple genetic variants that influence human lifespan, we conducted a genome-wide association study (GWAS) of centenarians. We began with a traditional one SNP at a time analysis to identify SNPs that are individually associated with exceptional longevity. We then used a novel approach to build a

family of genetic risk models based on Bayes rule which, while taking into account the simultaneous influence of many genetic variants, can accurately discriminate between subjects with average versus exceptional longevity. Next, we used this family of models to construct subject-specific genetic risk profiles that, by cluster analysis, can be used to discover sub-phenotypes of exceptional longevity that are characterized by different genetic signatures. Figure 1 summarizes the steps of the analyses.

set and NECS controls was more than 4 times the standard deviation, thus boosting the power of the study. For replication we used two additional sets. The replication set 1 (‘‘ELIX’’) consisted of 253 North American Caucasian subjects enrolled by Elixir Pharmaceuticals between 2001 and 2003. These individuals were born between 1890 and 1910 (age range of 89–114 years, median age 100) and were recruited and phenotyped using a protocol similar to the NECS. Referent subjects (n =341) were identified from the remaining Illumina controls and genetically matched to the 253 cases using the same matching algorithm used in the discovery set. The replication set 2 was composed of 60 centenarians that included 39 subjects of European ancestry enrolled in the NECS between June 2009 and September 2010 (age range 100–114, mean age 108) plus 21 centenarians (age range 101–115, mean age 107) not included in the discovery set during the genetic matching, and all available Caucasians samples from the Illumina control database not used in the above comparisons. Centenarians and controls in replication set 2 were not genetically matched to test the generalizability of the results. Figure 2 displays the age distributions of centenarians in the discovery and replication sets 1 and 2. We also used an additional set of 867 neurologically normal subjects used as controls for a Parkinson’s disease GWAS [21], to test the robustness of single

Results

Primary and secondary sets

subjects enrolled in the New England Centenarian Study (NECS) and 914 genetically matched controls. NECS subjects were Caucasians who were born between 1890 and 1910 with an age range of 95 to 119 years (median age 104 years). Approximately one-third of the NECS sample included centenarians with a first- degree relative also achieving exceptional longevity, thus enhanc- ing the sample’s power [19]. Controls included 241 genetically matched NECS referent subjects who were spouses of centenarian offspring or children of parents who died at an age #73 years, and 673 genetically matched subjects selected from the Illumina control database. For genetic matching we used a previously described algorithm [20] that groups subjects by ethnicities based on cluster analysis of the most informative principal components of genome-wide genotype data (Figure S1). Note that, based on the U.S. Social Security Administration’s 1920 birth cohort life table, the average life expectancy in the cohort is 82 years, with standard deviation of 7.9 years, so that the mean age of the cases in our study and the average life expectancy in the cohort differ by 2.69 times the standard deviation. Furthermore, the mean age of NECS controls was 75 years, with standard deviation 7 years. Therefore, the difference between mean age of centenarians in the discovery

Single SNP Analysis

First we conducted a traditional single SNP analysis in which we ranked SNPs in the discovery set by the strength of association. We employed both Bayesian and traditional frequentist analyses of 4 different genetic models (general/genotypic, allelic/additive, recessive and dominant associations) to maximize power [22,23]. With the Bayesian analysis, we scored each SNP association by the Bayes Factor (BF), which is the posterior odds for the association

 801 Centenarians from NECS (discovery)253 Centenarians from ELIX (replication 1)60 Centenarians from NECS (replica) ion 2)                    Discovery Set Replication Sets   801 centenarians 253 & 60 centenarians       Result 1; replication ofrs2075650 (            Result 2: 58-61% specificity, 58 85%  ignatures of exceptionallongevit 

Figure 1. Schematic showing the methodology used to discover genetic signatures of exceptional longevity (EL). The analysis included genetic matching to remove confounding by population stratification between cases and controls of the discovery and replication set 1, discovery and replication of single SNP associations, multivariate genetic risk modeling and generation of predictive genetic profiles, and cluster analysis of genetic risk profiles to discover genetic signatures of EL. doi:10.1371/journal.pone.0029848.g001

Density0.05Density0.050.150.100.000.150.100.00                                NECS Elix NECS 290 95 105° «115s 90 95 105° «115. Ss 90 95 105115AGE (Males) AGE (Males) AGE (Males)NECS Elix NECS 2[a IH A90 95 105115 90 95 105° 115 90 95 105° 115AGE (Females)AGE (Females)AGE (Females)