n  25,007 participants with 8444 deaths, only SNPs with MAF   3% are presented. p-values are for the inverse variance-weighted for NCBI Build 36. HRs are for each additional coded allele. Number of supporting SNPs is the number of SNPs within 500 kilo base pairs of CEU release 22 (r2   (cid:5)0.10) and have association p-value  0.05. Key: Chr, chromosome; LD, linkage disequilibrium; MAF, minor allele frequency; SNP, single nucleotide polymorphism. a For information on all SNP associations with p-value   10-4 see Supplementary Table S2. b Study-specific information is presented in the order: RS, CHS, FHS, ARIC, AGES, HABC, BLSA, InCHIANTI, SHIP; “(cid:4)”  coded allele of mortality, “?”  not tested.

n  25,007 participants with 8444 deaths, only SNPs with MAF   3% are presented. p-values are for the inverse variance-weighted meta-analysis. Distances to genes are given in base pairs. Position is for NCBI Build 36. HRs are for each additional coded allele. Number of supporting SNPs is the number of SNPs within 500 kilo base pairs of the top SNP that are in LD with the top SNP in the HapMap   

subunit 5-like (ORC5L, 7q22.1), and potassium voltage- gated channel, KQT-like subfamily, member 4 (KCNQ4, 1p34). Similarly, in the time to event analysis 3 of the 8 top SNPs showed considerable overlap and the same direction of effect in the time to death analysis. These SNPs were close to the following genes: MDS1 and EVI1 complex locus (MECOM, 3q24-q28), succinate-CoA ligase, ADP- forming, beta subunit (SUCLA2, 13q12.2-q13.3), and ST3 beta-galactoside alpha-2,3-sialyltransferase 3 (ST3GAL3, 1p34.1).

)stneve4137htiw599,61 (cid:5)n(eulav-pybdeknar,tneveotemitrofstrohoc8fosisylana-atemmorfsnoitaicossa)5-01 (cid:1)eulav-p(PNS8poT forebmuNtceffeydutSeulav-pRHycneuqerFdedocnoNdedoCmorf)pb(ecnatsiDtsesolCnoitisoPrhCPNSrebmuN sPNSgnitroppusanoitceridelelladedocelellaelellaenegtsesolceneGecnerefer 6-- (cid:4)(cid:4)-?–60-E20.319.033.0GA703YACTA17787839199121401sr1 27 (cid:4)- (cid:4)- (cid:4)(cid:4)(cid:4)(cid:4)60-E73.381.180.0CT016411MOCEM073961071321925861sr2 371--   (cid:4)(cid:4)(cid:4)60-E34.390.144.0CT9609212ALCUS32758274316791008sr3 04 (cid:4)(cid:4)(cid:4)(cid:4)(cid:4)(cid:4)(cid:4)(cid:4)60-E51.490.136.0CT68026211DTLE96170508136926111sr4 2 (cid:4)(cid:4)(cid:4)(cid:4)(cid:4)(cid:4)(cid:4)(cid:4)60-E01.671.180.0CT07571B2NIRG94760041213404674sr5 031--- (cid:4)-------—60-E97.658.080.0GA8260321AIRG07891625150352113sr6 63-----—60-E22.898.041.0CA332833A6LOC336539732279420201sr7 911- (cid:4)(cid:4)(cid:4)(cid:4)(cid:4)(cid:4)60-E13.980.124.0CT116243LAG3TS5148893415277632sr8  sPNSgnitroppusforebmuN.elelladedoclanoitiddahcaeroferasRH.63dliuBIBCNrofsinoitisoP.sriapesabninevigerasenegotsecnatsiD.sisylana-atemdethgiew-ecnairavesrevniehtroferaseulav-p llanonoitamrofniroF.50.0 (cid:1)eulav-pnoitaicossaevahdna)01.0 (cid:2)2r(22esaelerUECpaMpaHehtniPNSpotehthtiwDLnieratahtPNSpotehtforiapesabolik005nihtiwsPNSforebmunehtsi .21SelbaTyratnemelppuSees4-01 (cid:1)eulav-phtiwsnoitaicossaPNS .msihpromylopeditoelcunelgnis,PNS;muirbiliuqesidegaknil,DL;oitardrazah,RH;emosomorhc,rhC;riapesab,pb:yeK ;tnevefoksirsesaercedelelladedoc (cid:5)”-“;tnevefoksirsesaercnielelladedoc (cid:5)” (cid:4)“;ITNAIHCnI,ASLB,CBAH,SEGA,CIRA,SHF,SHC,SR:redroehtnidetneserpsinoitamrofnicfiiceps-ydutSa .detsetton (cid:5)”?“

Finally, we evaluated candidate genes for aging by iden- tification and classification of networks, pathways, biolog- ical processes, and molecular functions. The candidate genes were derived from the meta-analyses of GWAS and included the reference genes closest to the SNPs associated with p r< 1  10(cid:3)3 (time to death: 862 genes, time to event: 704 genes). We used PANTHER (Mi et al., 2007; Thomas et al., 2003, 2006) and IPA software (www.ingenuity.com) for these analyses. PANTHER compares these gene lists to the reference list using the binomial test for each molecular function, biological process, or pathway term. IPA builds networks by searching the Ingenuity Pathways Knowledge Base for interactions between the identified genes and all other gene objects stored in the knowledge base.

)stneve4137htiw599,61 (cid:5)n(eulav-pybdeknar,tneveotemitrofstrohoc8fosisylana-atemmorfsnoitaicossa)5-01 (cid:1)eulav-p(PNS8poT

processes overrepresented in the PANTHER analysis were developmental processes, neuronal activities, signal transduc- tion, neurogenesis, ectoderm development, and cell adhesion. For the analysis of time to incident event, developmental pro- cesses and neuronal activities were overrepresented among other biological process (Table 4). The analyses also high- lighted the Wnt signaling pathway. The Wnt signaling path- way is ubiquitous and known to be involved in cancer but also plays an important role in the early stages of the development of the central nervous system, in synaptic formation by axon guidance, and in modulating fibrosis during muscle repair scored high in both traits under study (Brack et al., 2007; Inestrosa and Arenas, 2010; Keeble et al., 2006; Ulloa and Martí, 2010). For extended tables see Supplementary Tables S13 and S14. In addition, Ingenuity identified 1 network with p  10(cid:3)31 containing 26 genes involved in processes related to nervous system develop- ment and function for the analysis of time to death (Fig. 2) and 1 network with p  10(cid:3)40 containing 28 genes involved in cellular function and development for time to event (Supplementary Fig. S3).

IPA analysis highlighted the following genes associated with the time to death trait: NTRK2 (neurotrophic tyrosine kinase, receptor, type 2)—a member of the neurotrophic tyrosine receptor kinase family. This kinase is a membrane- bound receptor that, upon neurotrophin binding, phospho- rylates itself and members of the mitogen-activated protein kinase (MAPK) pathway. Signaling through this kinase leads to cell differentiation. Second in line were NCAM1 (neural cell adhesion molecule 1)—a cytoskeletal binding