In conclusion, our genome-wide association study of all-cause mortality and survival free of major diseases did not identify any genome-wide significant associations but highlighted several loci with suggestive significance near genes related to neural regulation. Pathway and network analyses also identified an enrichment of genes associated with cellular and neural development and function, and cell communication that may contribute to variation in human aging. Future studies incorporating low frequency and rare variants, as well as larger sample sizes with more homogeneous populations, may help to further elucidate the genetic basis of human aging and longevity.2009; Leuba et al., 2004], GRIA1), and the maintenance of neural circuitry and synaptic plasticity (NETO1), or are associated with neurological diseases such as Alzheimer's disease (LMO4 [Leuba et al., 2004], BIN2, GRIA1, GRIN2B), and amyotrophic lateral sclerosis (GRIN2B). In addition, 6 of the 22 SNPs were in close proximity to genes associated with other aging phenotypes such as autophagy (ATG4C [Kenyon, 2010]), cancer (ATG4C [Maiuri et al., 2009], HIP1 [Bradley et al., 2007], HECW2 [Rotin and Kumar, 2009], VWA5A [Zhou et al., 2009], MECOM), and mitochondrial depletion syndrome (SUCLA2). Notably, BIN2, ATG4C, KCNQ4, MECOM, and SUCLA2 showed associations with both traits in our study. Few or none of the top hits from the GWAS were involved in common pathways of aging, typically addressed in candidate gene studies. For example, there was no specific evidence for genes involved in IGF-insulin signaling. However, this negative finding cannot be interpreted as evidence against the importance of IGF-insulin signaling, as well as other processes such as inflammation, oxidative stress, cellular damage and repair, growth hormone, and cell proliferation in aging. Moreover, it is possible that polymorphisms in related genes have an effect in the oldest old, who were represented by fewer numbers in our study population such that our study design would be underpowered to detect it. It is also conceivable that the neurological pathways identified by our analysis interact with the known candidate genes involved in aging (Bishop et al., 2010; Finch and Ruvkun, 2001). It is feasible that the traditional aging pathways are hierarchically controlled by neurons and that the brain might be the location coordinating physiological changes (Bishop et al., 2010; Finch and Ruvkun, 2001). Because neurons are particularly susceptible to damage caused by reactive oxygen species, limitations in cellular maintenance and repair might reinforce these pathways and accelerate aging (Finch and Ruvkun, 2001). An increased ability of neuronal cells to prevent or repair oxidative damage might result in beneficial hormonal signaling, otherwise deregulated with age, thus delaying the onset of age-related disease and directly regulating cognitive aging and life span (Bishop et al., 2010; Cutler and Mattson, 2006; de Magalhaes and Sandberg, 2005). Using the expression quantitative trait loci (eQTL) browser (eqtl.uchicago.edu/cgi-bin/gbrowse/eqtl/), we detected eQTL associated with HIP1, COL5A1, LOC340156, and SMARCA2 in time to death only. Interestingly, SNPs known to be associated with longevity and disease in the neighborhood of APOE (Deelen et al., 2011) or FOXO3A (Flachsbart et al., 2009; Willcox et al., 2008) only reached nominal significance (results not shown). These genes were originally identified in studies of centenarians; it is possible that our study of cohorts comprised of individuals from the general populations did not have sufficient statistical power to identify these genes with certainty. (Tan et al., 2008). While meta-analysis of GWAS has the power to detect small changes of allele frequencies between groups with the analyzed trait, true association signals may not be revealed based on a stringent genome-wide significance threshold. This situation, although limiting false positive findings, performs poorly in identifying false negatives as they may fall below the threshold. Network analyses using a less stringent significance threshold do not amend the overall negative finding of this study. However, it is well-recognized that within the many associations that failed to attain this level of significance lie true positive associations. Network analyses can provide useful information exploring multiple gene effects and their interactions. In conclusion, our analysis did provide suggestive evidence that aging is under neuronal control. Unfortunately, we have no relevant tissue or expression experiment available to further underscore or validate our findings. Future investigations of changes of gene expression with age at cellular and population levels are warranted. In fact, the interpretation of most GWAS results is difficult because individual results may involve many seemingly unrelated genes. Because PANTHER and IPA are built on different conceptual approaches, database sources, and different pathway classifications, they can be seen as complementary approaches. Our pathway and network analyses highlighted neuronal activities and organism developmental processes as major biological processes involved in aging. In addition, it highlighted Wnt signaling and showed that those involved in this pathway are related to age-related diseases and longevity.Study was supported by a grant from the National Institute of Arthritis, Musculoskeletal and Skin Diseases and the National Institute on Aging; R01 AR/AG 41398. This research was additionally supported by the following grants: AG033193, AG081220, NS17950, P30AG013846, 1R01- AG028321. English Longitudinal Study of Aging: Samples from the English Longitudinal Study of Ageing (ELSA) DNA Repository (EDNAR), received support under a grant (AG1764406S1) awarded by the National Institute on Aging (NIA). ELSA was developed by a team of researchers based at the National Centre for Social Research, University