Conclusions
The results of this study stress the importance of using several statistical approaches for identifying alleles in GWAS of complex traits, as well as the importance of using established metabolic pathways involved in the regulation of these traits for confirming research findings. The latter creates an important link between population-based GWAS and the results of experimental studies focused on verifying molecular biological mechanisms, metabolic pathways, and protein interaction networks affecting phenotypic traits. The longevity alleles selected in this study differ from those selected in the studies of Lunetta et al. and Newman et al. discussed above. As results of our study show, one possible reason for this could be differences in the allele selection procedures. The control for observed covariates was also different. In contrast to Newman et al., we did not control for observed covariates that could be considered as mediators of genetic influence on lifespan (e.g., physiological variables) in our study. Although controlling for such covariates may reduce effects of nongenetic factors affecting lifespan through these covariates, it may also reduce the number of selected genetic variants affecting this trait (see also Supplemental Data). The fact that the majority of detected SNPs were located in genes and were intronic indicates a potentially pivotal role of changes in intronic enhancers and in gene/protein expression (not related to the changes in protein structure) in achieving longevity, as compared to the role of the changes in coding exons. This hypothesis needs further testing. The SNPs identified in our study do not have exact overlaps with the SNPs found in other recent GWAS of longevity. While recognizing all the possible statistical reasons for such lack of replication (discussed above), it is important to stress that on the level of gene functions, pathways, cell responses, and health effects, in which the identified SNPs or related genes are involved, there are clear overlaps across respective studies, as well as with many other (not genome-wide) genetic association studies of aging and longevity (Table 4). For example, rs2024714 is one of the 27 I-longevity SNPs, which is located in the intronic region of CDH4, a cell adhesion gene involved in brain information processing and tumor suppression. In an earlier GWAS conducted by Framingham researchers using the Affymetrix 100K SNP array, a polymorphism (rs1970546This text appears to be a list of references. No corrections are necessary.Moosmang S, Haider N, Klugbauer N, et al. Role of hippocampal Cav2+ channels in NMDA receptor-independent synaptic plasticity and spatial memory. J Neurosci; 

ODonovan MC, Craddock NJ, Owen MJ. Genetics of psychosis; insights from views across the genome. Hum Genet; 

Kempton MJ, Ruberto G, Vassos E, et al. Effects of the CACNA2D2 risk allele for bipolar disorder on cerebral gray matter volume in healthy individuals. Am J Psychiatry; 

Deelen J, Beekman M, Uh H-W, et al. Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited. Aging Cell; 

Mue M, Vaupel JW, Holm N, Harvald B. Longevity is moderately heritable in a sample of Danish twins born 1870-1900. J Gerontol; 

Herskind AM, Mue M, Holm NV, et al. The heritability of human longevity: A population-based study of Danish twin pairs born 1870-1900. Hum Genet; 

Hill WG, Goddard ME, Visscher PM. Data and theory point to mainly additive genetic variance for complex traits. PLoS Genet; 

Falconer DS, Mackay TFC. Introduction to Quantitative Genetics. Addison Wesley Longman, Harlow, Essex, UK; 

Fisher RA. The Genetical Theory of Natural Selection. Oxford, Clarendon Press; 

Lee SH, Wray NR, Goddard ME, Visscher PM. Estimating missing heritability for disease from genome-wide association studies. Am J Hum Genet; 

Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: A tool for genome-wide complex trait analysis. Am J Hum Genet; 

Visscher PM, Hill WG, Wray NR. Heritability in the genomics era-concepts and misconceptions. Nat Rev Genet; 

Novelli V, Anselmi CV, Roncarati R, et al. Lack of replication of genetic associations with human longevity. Biogerontology; 

Torkamani A, Scott-Van Zeeland AA, Topol EJ, Schork NJ. Annotating individual human genomes. Genomics; 

Tong D-d, Jiang Y, Li M, et al. RUNX3 inhibits cell proliferation and induces apoptosis by TGF-beta-dependent and -independent mechanisms in human colon carcinoma cells. Pathobiology; 

Subramaniam MM, Chan JY, Yeoh KG, et al. Molecular pathology of RUNX3 in human carcinogenesis. Biochim Biophys Acta Rev Cancer; 

Fainaru O, Shseyov D, Hantisteanu S, Groner Y. Accelerated chemokine receptor-mediated dendritic cell migration in Runx3 knockout mice and the spontaneous development of asthma-like disease. Proc Natl Acad Sci USA; 

Naoe Y, Setoguchi R, Akiyama K, et al. Repression of interleukin-17 in T helper type 1 cells by Runx/Cbf beta binding to the Il17 silencer. J Exp Med; 

Hollingsworth JW, Maruoka S, Boon K, et al. In utero supplementation with methyl donors enhances allergic disease in mice. J Clin Invest; 

Kamide K, Kokubo Y, Yang J, et al. Hypertension susceptibility genes on chromosome 2p24-p25 in a general population. J Hypertens; 

Imada Y, Fujimoto M, Hirata K, et al. Large scale study for asthma in the Japanese population. BMC Notes; 

Guerra-Crespo M, Gleason D, Sistos A, et al. Epidermal growth factor-alpha induces neurogenesis and improvement in a chronic stroke model. 

Cavin LG, Wang F, Factor VM, et al. Transforming growth factor-alpha inhibits the intrinsic pathway of apoptosis through activation of nuclear factor-kappa B in mice. 

Kamide K, Yang J, Matayoshi T, et al. Genetic polymorphisms of L-type calcium channel alpha 1C and alpha 1D subunit genes are associated with sensitivity to the anti-hypertensive effects of L-type dihydropyridine calcium-channel blockers. Circ J;