cohortsthatmayhavehadanimpactonourresults.Anexampleof a potential confounder is smoking behavior, which was not ad- equately measured in most elderly cohorts. However, none of the SNPs that were previously associated with smoking behavior in cohorts from European descent (according to the NHGRI GWAS Catalog (http://www.genome.gov/gwastudies/)), namely rs1051730, rs1329650 and rs4105144, show differences ≥ between cases ( 85 years) and controls in the joint analysis of the discovery and replication phase (all P . 0.05). We have to note that these SNPs only explain a small proportion of the vari- ance observed in smoking behavior. However, as the frequency of these proxy SNPs for smoking behavior is similar between cases and controls, we expect no obvious differences in smoking behavior between the groups.

(10,11) and is assumed to be determined by many genes (12,13). Furthermore, the genetic heterogeneity in ageing and lifespan regulation is expected to be high, because individual genes maycontributebyadiversityoflateactingdeleteriousstochastic (germline) variationresultinginagenetic component thatishard to disentangle (13). GWAS of complex late-onset diseases, such as osteoarthritis and Alzheimer’s disease, with sample sizes comparable to our current study (43–45), have identified more locicomparedwithGWASoflongevity.Thismostlikelyreflects the greater inherent complexity of the longevity trait, with its diverse spectrum of biological pathways subject to intrinsic and extrinsic (environmental) interactions. Hence, even larger GWAS (.50 000 long-lived individuals) may be required to identify additional longevity loci, preferably in the most strin- gent phenotype, i.e. the oldest old.

APOE/APOC1 locus, we identified a novel locus on chromosome 5q33.3 that associates with survival beyond 90 years. Although rs2149954 is associated with survival beyond 90 years at a genome-widesignificantlevelinourstudy,replicationinaddition- al cohorts from European as well as non-European descent is war- ranted. The minor allele of the lead SNP at this locus, rs2149954, promotes human longevity in a prospective meta-analysis by low- ering the risk of mortality owing to stroke and non-cardiovascular causes. The locus harbors a lincRNA and is implicated in blood pressure regulation, but the mechanismby which it influences lon- gevity likely also involves other traits.

Western populations, the human longevity trait suffers from etio- logical heterogeneity. Lifespan extension in the past generations owing to non-genetic factors likely created phenocopies diluting ≥ the genetic component of survival to ages 85 years. The ≥ genetic contribution to survival to ages 100 years is higher but will render smaller sample sizes for GWAS. This may explain

MATERIALS AND

All studies were analyzed separately using CC-assoc (https:// www.msbi.nl/dnn/Research/Genetics/Software/TestsforGWAS inrelatedindividuals(cc_assoc).aspx), which is based on a modi- fied version of the score test that takes into account imputation uncertainty and familial relatedness (46). SNPs with a low imputation quality ( R2 ≤ 40) and a MAF of ≤ 1 or ≤ 5% (if T n , 200) were excluded from analysis in the discovery cases phase. Adjustment for population stratification of the discovery studies was performed by multiplying the R2 -adjusted variances T of the score statistic with the genomic inflation factor (l ¼ range

Study populations

The discoveryanalysiswas performedin7729casesthatsurvived ≥ ≥ toages 85years(ofwhich5406alsosurvivedtoages 90years) and 16 121 controls below 65 years at baseline, from 14 studies. Replication was performed in 13 060 cases that survived to ages ≥ ≥ 85 years (of which 7330 also survived to ages 90 years) and 61 156 controls below 65 years at baseline, from 6 additional studies. All individuals were of European descent. The details of the discovery and replication studies can be found in Supple- mentary Material, Tables S1 and S2. Some cohorts only provided controls (GOYA, NTR, SU.VI.MAX, TwinsUK and WTCCC2) or only cases (BELFAST, CEPH centenarian cohort, Danish lon- + gevity study I/II, Leiden 85-plus Study I/II and Newcastle 85 Study), whereas others contained both (Calabria cohort, deCODE, EGCUT, GEHA Study, German longevity study, Leiden Longevity Study, Rotterdam Study I/II and TwinGene). The names of the studies in the tables and figures are based on the names of the cohorts containing the cases. The cases and con- trols used for each study originated from the same country (Sup- plementary Material, Table S1). The only exception is BELFAST (Northern Ireland), for which we used controls from the NTR (Netherlands). A check in the PROSPER study, which includes individuals from Northern Ireland and the Netherlands, showed that the allele frequencies in control individuals from both countries are similar for our SNPs (data not shown). All par- ticipants provided written informed consent, and the study was approved by the relevant institutional review boards.

Meta-analyses

For the meta-analyses, a fixed-effect approach was used. Scores and variances of the studies were combined to obtain a single meta-statistic, which was adjusted using the genomic inflation factor (l¼ 1.019, discovery phase only) (Supplementary Ma- terial, Fig. S1). For each analysis, we only used studies with at least 100 cases (Supplementary Material, Table S1). P-values ,5 × 1028 were considered genome-wide significant (47). To determine heterogeneity across the studies, the between-study variance was calculated.

Conditional analysis

To ascertain independent signals at the chromosome 19q13.32 locus, we performed a meta-analysis conditional on rs4420638 in all studies used for the discovery phase analysis in cases ≥ aged 85 years. The results are depicted in Supplementary Material, Figure S2 and Table S3.

Genotyping, imputation and genome-wide association analysis

Sex-stratified analysis