Procedures performed were in accord with institutional guidelines and were approved by the Institutional review Board of Kuakini Medical Center. Written informed con- sent was obtained from all study participants or from family representatives if participants could not provide consent.

For strength of association, odds ratios were estimated using logistic regression models from SAS (22). Linear regression models were used for continuous variables, and logistic regression models were used for categorical variables in testing for associations between genotype and aging phe- notypes, adjusting for case–control status and age at baseline.

Genotyping

For reasons of power, we included only common SNPs, that is, those having a minor allele frequency (MAF) greater than or equal to 10% in the Japanese population as indicated by the JSNP database (http://snp.ims.u-tokyo.ac.jp) and with reference to the dbSNP/HapMap database (HapMap release 23a/phase II March 2008 on National Center for Biotechnology Information B36 assembly, dbSNP b126—http://www.ncbi.nlm.nih.gov/projects/SNP/). These included tagging SNPs (tagSNPs) plus 10 kb of 5′- and of 3′-flanking DNA for ATF1, CBL, and JUN (Table 1). The minimal coefficient of determination (r2) value at which all alleles are to be captured was set to a threshold of 0.8 for the identification of all tagSNPs. In the case of EXO1, we genotyped only a single functional SNP in the promoter, this being the only SNP associated with longevity of seven tested (21). For CDKN2B we chose a SNP implicated in β-cell function (14).

Results

Characteristics of Participants

population at the 1991–1993 examination are shown in Supplementary Table 1. The long-lived cases were older; had lower waist:hip ratio, plasma glucose, plasma insulin, homeostatic model assessment (HOMA), and grip strength; had nonsignificantly lower plasma triglycerides; were bet- ter able to walk 0.8 km; had better self-rated health; and had lower prevalence of cancer and cardiovascular disease (cor- onary heart disease, stroke, and hypertension). The higher systolic blood pressure of cases reflects the rise in isolated systolic hypertension with age. There was no difference in cognitive abilities screening instrument score between cases and controls.

tem (Gentra Systems, Inc.) and quantified using PicoGreen staining (Molecular Probes, Eugene, Oregon). SNPs were genotyped using allelic discrimination assays. TaqMan rea- gents (purchased from Life Technologies; formerly Applied Biosystems, Inc) were used for PCr amplification under standard conditions with AmpliTaq Gold DNA polymer- ase (Perkin-Elmer Corp.). PCr products were detected by TaqMan assay, using a 6-FAM-labeled fluorescence reso- nance energy transfer probe for one allele and a VIC-labeled probe for the other allele, with minor groove binding quench- ers to enhance assay signal. PCr products were measured using an ABI Prism 7000 Sequence Detection System.

Pathway Analysis

http://gncpro.sabiosciences.com/gncpro/gncpro.php), we were able to confirm functional connections (as defined by links to peer-reviewed publications) between proteins of all of the genes chosen (eg, upregulation, downregulation, coexpression, chemical modification, physical interaction, predicted protein interaction, predicted transcription fac- tor regulation, or other relation; Supplementary Figure 1). The analysis also provided potential candidates for future genetic studies.

Genotype data were managed through an integrated database system sample management–data processing system of proven accuracy (8). All positive controls on each genotyping plate were evaluated for consistency. Call rates for markers exceeded 98%.

Genetic Association Findings

As shown in Table 1, only SNP rs6589722 in CBL was significant (p = .015), with SNP rs17356414 in JUN being marginal (p = .082).

Table 1. Frequency of Minor Allele of Each SNPs Tested in Long-Lived Case Versus Control Participants

Single Nucleotide Total Number of Minor Allele Frequency of Cases/ Polymorphism ID Alleles Case/Controls Controls; n (%; 95% CI) χ2 p-Value ATF4 rs1048310 G/T 208/399 44/82 (10.6/10.3; –0.03 to 0.04) 0.027 0.87 rs6519194 A/G 206/397 12/17 (2.9/2.1; –0.01 to 0.029) 0.69 0.41 rs738288 A/G 205/396 4/11 (0.98/1.4; –0.02 to 0.011) 0.37 0.54 CBL rs6589722 A/C 209/402 80/111 (19/14; 0.009 to 0.099) 5.9 0.015 rs12786104 G/T 210/398 181/380 (43/47; –0.10 to 0.012) 2.4 0.12 rs11217184 A/G 212/396 157/299 (37/38; –0.06 to 0.05) 0.06 0.80 rs2249466 C/T 207/394 136/256 (33/32; –0.05 to 0.06) 0.02 0.90 rs7914 A/G 190/376 150/306 (39/41; –0.07 to 0.048) 0.16 0.69 rs2511837 A/G 212/398 143/236 (34/30; –0.01 to 0.096) 2.1 0.14 CDKN2B rs10811661 C/T 213/402 182/380 (43/47; –0.10 to 0.013) 2.3 0.13 EXO1 rs1776180 C/G 206/401 11/18 (5.3/4.4; –0.01 to 0.025) 3.6 0.16 JUN rs2999131 C/G 208/391 132/226 (32/29; –0.03 to 0.083) 1.0 0.31 rs1815274 C/T 212/401 164/279 (37/35; –0.02 to 0.096) 1.8 0.18 rs17356414 T/C 212/401 113/252 (27/20; –0.010 to 0.006) 3.0 0.082 rs1853432 A/T 213/398 184/359 (43/45; –0.08 to 0.039) 0.41 0.52

Note: CI = confidence interval.

One-way ANOVA detected no relationship between factors associated with insulin sensitivity, a potential intermediate phenotype of longevity, and genotype. For nonnormally distributed variables, we used log transforma- tion to approximate a normal distribution. There was no association between other phenotypes and any of the SNPs in Table 1 (Supplementary Table 2). Nor was there a rela- tionship between any of the genotypes and maximum age attained in either the case or the control groups (data not shown).

variants not present in other populations, may exist that could be associated with longevity.

For the two SNPs with marginal association with lon- gevity before Bonferroni correction, no significant associa- tion was found with a range of aging-related phenotypes, common diseases or a combined phenotype representing “healthy aging.”