About 9,300 individuals from all generations of the FHS were genotyped for about 550,000 SNPs using Affymetrix 500K (genome-wide) and 50K (enriched with SNPs within genes) mapping arrays, overall representing a significant part of human genome variability. On average, 40% of SNPs were located within genes in the combined 550K set. In this study, we used information about 1,471 genotyped partici- pants of the FHS Original cohort who passed quality control (QC), including 1,173 individuals for whom life spans were available. Information about 517 individuals (all deceased) from the FHSO cohort was used for validating the connec- tion between life span and genetic variants in this cohort using ‘‘longevity’’ alleles obtained in the analyses on the original FHS cohort. Individual information on the SNP genotyping and phenotypic traits collected in the FHS was obtained through the dbGaP web site, upon request for con- trolled access for individual level data (www.ncbi.nlm.nih .gov/projects/gap/cgi-bin/study.cgi?study_id=phs000007.v3 .p2/). The histograms of the life span distribution for two groups of deceased individuals (genotyped+nongenotyped and genotyped) from the original FHS cohort are shown in Fig. 1, a and b, respectively.

To address this problem and enhance the efficiency of studying joint genetic effects on aging/longevity traits in this paper, we first used six statistical models for allele selection procedures: (1) Normal linear (N), (2) Cox (C), and (3) lo- gistic (L) regressions; (4) generalized estimation equation (GEE); (5) mixed model (MM); and (6) gene frequency (GF) method. Then we evaluated the joint influence of SNP alleles selected with each of the six methods on life span, as well as the effect on life span of the SNPs from the overlapping set of alleles selected with all of the six statistical procedures. In all regression methods, possible effects of observed covariates on the results of selection were taken into account. These include gender, birth cohort, and smoking status, taken from the original cohort data of the Framingham Heart Study (FHS). Then we used SNP alleles influencing life span in the FHS Original cohort to predict the relationship between the number of ‘‘longevity’’ alleles and life span in the FHS Off- spring cohort.

Percent 30 40 50 60 70 80 90 100Lifespan  60 65 70 75 80 85 90 95 100 105Lifespan

Finally, we reviewed current literature and online infor- mation sources to explore functional properties of genes re- lated to ‘‘longevity’’ SNPs in the overlapping set of SNPs selected in the six statistical procedures. The findings that corresponding genes have functional relevance to physio- logical aging and/or aging-associated health disorders would support a causal relationship between these SNPs and life span.

Data and Methods

Framingham Study Data

In this study, we used genetic and nongenetic data for the FHS Original and Offspring cohorts. The FHS Original co- hort was launched at Exam 1 in 1948 (9/1948–4/1953) and has continued with biennial examinations to the present. The FHS Original cohort consists of 5,209 respondents (55% fe- males) aged 28–62 years residing in Framingham, Massa- chusetts, between 1948 and 1951.11 Nearly all subjects were Caucasians. Examination included an interview, physical examination, and laboratory tests.

The Offspring cohort (FHSO) was launched at Exam 1 in 1971 (8/1971–9/1975) and has on average been examined every 3–4 years since enrollment. The FHSO dataset consists of a sample of 3,514 biological descendants of the Original cohort, 1,576 of their spouses, and 34 adopted Offspring for a total sample of 5,124 subjects (52% females).12,13 The FHSO subjects were enrolled in 1971–1975 using research protocols similar to those of the FHS, so that comparisons of the results from the FHSO and the FHS could be made.

FIG. 1. The histograms of life span distribution for (a) 4,760 deceased (genotyped and nongenotyped) and (b) 1,173 de- ceased genotyped individuals from the original Framinghan Heart Study (FHS) cohort.

Validating polygenic influence on lifespan in the FHSO cohort

The use of the Shapiro–Wilk test indicates that the normal approximation of the life span distribution for genotyped individuals can be used (for more information about other descriptive statistics relevant to these analyses, see Supple- mental Material (www.liebertpub.com/rej).

To be sure that ‘‘longevity’’ alleles from each of the six sets had a joint effect on life span, not only in population of the FHS original cohort but also in population of other individ- uals (whose genetic information was not used in the allele selection procedure), we calculated values of respective in- dices for each of the 517 individuals from the FHSO cohort. Then we estimated parameters of linear regressions consid- ering life span as a function of respective indices.

QC procedure

Following Lunetta et we applied a GWAS QC proce- dure (call rate‡80%; minor allele frequency [MAF]>1%; Hardy–Weinberg equilibrium [HWE]>10-7) to the data on genotyped (550K SNPs) individuals from the original cohort in the FHS. (See Table S1 and Fig. S3 in Supplemental Data for additional information concerning call rates and other infor- mation about selected SNPs; see also Discussion section).

Analyses and Results

Normal regression

The N regression procedure for selecting longevity alleles (with p value threshold £ 10-7) was applied to 1,173 mem- bers of the original FHS cohort who passed the QC proce- dure and for whom life span data were available. The implementation of this procedure resulted in 823N-longevity alleles.

Identifying ‘‘longevity’’ alleles