For the IIS pathway, we selected genes encoding proteins that belong to the well-described core of the pathway, consisting of IGF1R/IR/IRR, IRS, PI3K, AKT/SGK, FOXO, and SIRT, or that had a direct activating or inhibiting effect on these core compo- nents (van der Horst and Burgering 2007; Taniguchi et al. 2006). In addition, we selected several FOXO target genes that play a role in cell-cycle inhibition, oxidative-stress resistance, metabolism, and apoptosis (van der Horst and Burgering 2007) (Fig. 1). For the TM pathway, we selected genes encoding proteins that were specifically associated with telomeres and belonged to telomerase and its associated factors or to

Four methods, PLINK set-based test, Global test, GRASS, and SNP ratio test (Table S2), were used to investigate the association of the SNP sets from the IIS and TM pathways with longevity. As a biological

set-based test, Global test, and SNP ratio test. GRASS was not used, since the underlying statistical method of this test is less suitable for analysis of gene SNP sets. Nine of the 68 IIS pathway gene SNP sets (AKT1, AKT3, FOXO4, IGF2, INS, PIK3CA, SGK1, SGK2, and YWHAG) and 1 of the 13 TM pathway gene SNP sets (POT1) showed an association (P<0.05) with longevity in at least two tests (Tables 5 and 6).

SNPs in 9 genes previously associated with eye and hair color (Eriksson et al. 2010) (Tables 3 and S3C). Both candidate pathways were consistently associated with longevity across all four tests (Table 4). We applied Bonferroni correction to adjust for the number of tested pathways (i.e., 2, so for significance P< 0.025). After Bonferroni correction, the IIS pathway SNP set remained significant in GRASS and Global test, while the TM pathway SNP set remained significant in the PLINK set-based test, GRASS, and Global test. Using the comparative approach in Global test as a competitive test, we also showed that the probability to find a random SNP set with the same amount of genes as the IIS or TM pathway and a comparable or lower P value is less than 5% (2.11% for the IIS and 2.95% for the TM pathway).

Discussion

To study the effect of the IIS and TM pathways on longevity, SNP set analysis on GWAS data of 403 nonagenarian cases and 1,670 population controls was performed. Both pathway SNP sets associated significantly with longevity. The gene SNP sets analysis showed that the association of the IIS pathway was scattered over several genes (AKT1, AKT3, FOXO4, IGF2, INS, PIK3CA, SGK1, SGK2, and YWHAG), while the association of the TM pathway seems to be mainly determined by one gene (POT1).

To determine which genes are mainly responsible for the observed association of the pathway SNP sets from the IIS and TM pathways with longevity, we also investigated the association of gene SNP sets from these pathways. Although the power to detect an association using gene SNP set analysis is lower than for pathway SNP set analysis, due to the larger amount of tests, it provides a ranking of genes based on the contribution to the observed associations of the path- ways. To analyze the gene SNP sets, we used the PLINK

The proteins encoded by the IIS gene SNP sets that associate with longevity are involved in several parts of the IIS pathway (Fig. 1). Akt1, Akt3, Foxo4, Igf2, Ins2, Pik3ca, and Sgk1 knockout mice all show

Table 2 Characteristics of the telomere maintenance pathway

Protein Gene Entrez gene ID Chr Start (bp) End (bp) Size (kb) SNPs Coverage TPP1 (shelterin) ACD 65057 16 66,248,916 66,252,219 3.30 2 50.00% Dyskerin (telomerase) DKC1 1736 X 153,644,225 153,659,158 14.93 1 NA GAR1 (telomerase) GAR1 54433 4 110,956,115 110,965,342 9.23 1 14.29% NHP2 (telomerase) NHP2 55651 5 177,509,072 177,513,567 4.50 2 33.33% NOP10 (telomerase) NOP10 55505 15 32,421,209 32,422,654 1.45 7 45.45% POT1 (shelterin) POT1 25913 7 124,249,676 124,357,273 107.60 25 55.56% TP1 (telomerase) TEP1 7011 14 19,903,666 19,951,419 47.75 21 40.00% TERC (telomerase) TERC 7012 3 170,965,092 170,965,542 0.45 1 25.00% TRF1 (shelterin) TERF1 7013 8 74,083,651 74,122,541 38.89 10 60.00% TRF2 (shelterin) TERF2 7014 16 67,946,965 67,977,375 30.41 6 57.14% RAP1 (shelterin) TERF2IP 54386 16 74,239,136 74,248,842 9.71 4 50.00% TERT (telomerase) TERT 7015 5 1,306,287 1,348,162 41.88 7 41.18% TIN2 (shelterin) TINF2 26277 14 23,778,691 23,781,720 3.03 1 14.29% Total 88

Chr Chromosome position of the gene according to NCBI Build 36, Start (bp) start position of the gene according to NCBI Build 36, End (bp) end position of the gene according to NCBI Build 36, Coverage coverage of genes based on Phased data HapMap II release 22 CEU, NA not available

3 Characteristics of the eye and hair color pathway proteins

Protein Gene Entrez gene ID Chr Start (bp) End (bp) Size (kb) SNPs Coverage ASIP ASIP 434 20 32,311,832 32,320,809 8.98 5 50.00% HERC2 HERC2 8924 15 26,029,783 26,240,890 211.11 9 41.67% IRF4 IRF4 3662 6 336,739 356,443 19.70 14 65.00% MC1R MC1R 4157 16 88,511,788 88,514,886 3.10 3 33.33% OCA2 OCA2 4948 15 25,673,616 26,018,053 344.44 82 58.00% SLC24A4 SLC24A4 123041 14 91,858,678 92,037,578 178.90 62 53.68% SLC45A2 SLC45A2 51151 5 33,980,478 34,020,537 40.06 15 44.83% TYR TYR 7299 11 88,550,688 88,668,575 117.89 22 56.00% TYRP1 TYRP1 7306 9 12,683,386 12,700,266 16.88 11 50.00% Total 223

Chr Chromosome position of the gene according to NCBI Build 36, Start (bp) start position of the gene according to NCBI Build 36, End (bp) end position of the gene according to NCBI Build 36, Coverage coverage of genes based on Phased data HapMap II release 22 CEU

would explain the scattered association in the IIS pathway.