Here we report the results of a genetic association study of tagging single-nucleotide polymorphisms (tagSNPs) that provided virtually complete coverage of key mTOR complex genes MTOR, RPTOR, and RICTOR, as well as RPS6KA1, in long-lived Americans of Japanese ancestry. The study tested for association of these genetic variants with living to more than 95 years of age and with multiple aging-related parameters in these subjects.

Genotyping 
Total cellular DNA was isolated from leukocytes using the PureGene system (Gentra Systems) and quantified using PicoGreen staining (Molecular Probes, Eugene, OR). SNPs genotyped were from within the gene and from a 5-kb region of DNA flanking either end of the genes MTOR, RPTOR, RICTOR, and RPS6KA1. TagSNPs were selected using Haploview, a program that defines a haplotype based on high correlation between the first and last markers and all intermediate markers. Supplementary Figures S1-S4 show the linkage disequilibrium blocks captured by the tagSNPs used. We restricted our selection to SNPs having a minor allele frequency of 10% in the Japanese population (as indicated by the HapMap database: http://hapmap.ncbi.nlm.nih.gov/; HapMap release 27/phase II + III, Feb 2009 on NCBI B36 assembly, dbSNP b126 http://www.ncbi.nlm.nih.gov/projects/SNP/). The minimal coefficient of determination (r2) value at which all alleles are to be captured was set to a threshold of .8 for the identification of all tagSNPs. Genotype data were managed through an integrated database system sample management-data processing system that has been proven to be accurate in other successful studies (5). All positive controls on each genotyping plate were evaluated for consistency. Call rates for markers exceeded 98%.

Genetic association Findings 
SNPs for MTOR, RPTOR, and RICTOR were genotyped at the University of Hawaii Cancer Center on the Illumina GoldenGate platform (high-throughput SNP genotyping on universal bead arrays (31)). SNPs for RPS6KA1 were detected by the TaqMan OpenArray System (Life Technologies). We implemented a series of quality control checks based on the Illumina metrics. For inclusion of data for a SNP, its call rate had to exceed .95 and the Hardy Weinberg equilibrium p needed to be >.01. Of the 81 tagSNPs genotyped, all met these criteria and were included. In addition, more than 96% concordance was observed for all SNPs for HapMap samples that were assayed for quality assurance.

The minor allele frequencies of each SNP tested in MTOR, RPTOR, RICTOR, and RPS6KA1 in cases and controls are presented in Tables 2-5, together with results of chi-square analyses. Differences that appeared statistically significant for two SNPs in RPTOR (rs7225574 and rs2589143) and one SNP in RICTOR (rs1239256) were lost after correction for multiple comparisons.

Phenotype-Genotype analyses 
Phenotype-genotype comparisons for each SNP with 40 different aging-related phenotypes in cases showed weak associations for 5 of 6 SNPs in MTOR, 38 of 61 in RPTOR, and 5 of 7 in RICTOR prior to correction for multiple testing (Supplementary Table S2). In all, 83 genotypic associations were observed with blood pressure (BP) and related clinicaland Exam 4 using canonical correlation. For BP, the mean of Exam 1 and Exam 2 data (substituting Exam 3 BP values if Exam 2 values were missing) was used. Variables were transformed when necessary to reduce skewness of the residuals from the regression of each phenotype on age and case-control status. The Wilks lambda test for association between the Exam 1 variables - log values of systolic and diastolic BP (log(SBP) and log(DBP)), serum cholesterol, body mass index, and log of subscapular skinfold thickness, adjusted for age at Exam 1 and case-control status was not significant (p = .29). Similarly, for the Exam 4 variables - grip strength, waist:hip ratio, body mass index, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, fasting serum glucose, log fasting insulin, log triglyceride level, and log of (101 CASI [cognitive abilities screening instrument] score), adjusted for age at Exam 4 and case-control status - Wilks test was not significant (p = .22). Although we cannot rule out associations between particular age-related phenotypes and individual SNPs, the findings suggest that overall, the actual number of associations observed did not exceed the expected numbers of associations that might be observed by chance alone.

Statistical analyses: Genotype frequencies of SNPs were evaluated for deviation from Hardy-Weinberg equilibrium. The Pearson chi-square test was used to compare cases and controls for differences in genotype frequencies. The 95% confidence intervals for allele frequencies were calculated as described (32). For analyses of phenotypes, linear regression models were used for continuous variables (with log transformation of skewed variables) and logistic regression models were used for categorical variables to test for associations with genotypes, adjusting for case-control status and age at baseline. The analyses used the SAS statistical package.