processes in human longevity and aging. Ten of the 22 suggestive associations identified in our analyses are in or near genes that are highly expressed in the brain (HECW2 [Rotin and Kumar, 2009], HIP1 [Blanpied et al., 2003], BIN2, GRIA1), were previously related to the regulation of neuronal excitability and plasticity (KCNQ4 [Van Eyken et al., 2006], LMO4 [Joshi et al., 2009; Leuba et al., 2004], GRIA1), and the maintenance of neural circuitry and syn- aptic plasticity (NETO1), or are associated with neurologi- cal diseases such as Alzheimer’s disease (LMO4 [Leuba et al., 2004], BIN2, GRIA1, GRIN2B), and amyotrophic lat- eral sclerosis (GRIN2B). In addition, 6 of the 22 SNPs were in close proximity to genes associated with other pheno- types of aging 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 syn- drome (SUCLA2). Notably, BIN2, ATG4C, KCNQ4, MECOM, and SUCLA2 showed associations with both traits in our study.

Few if any of the top hits from the GWAS were involved in common pathways of aging, typically ad- dressed in candidate gene studies. For example, there was no specific evidence for genes involved in IGF-insulin signaling. However, this negative finding cannot be in- terpreted as evidence against the importance of IGF- insulin signaling, as well as other processes such as inflammation, oxidative stress, cellular damage and re- pair, 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 repre- sented 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 candi- date 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 physi- ological 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 hor- monal 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 Magalhães and Sand- berg, 2005).

Using the expression quantitative trait loci (eQTL) browser (eqtl.uchicago.edu/cgi-bin/gbrowse/eqtl/) we de- tected eQTL associated with HIP1, COL5A1, LOC340156, and SMARCA2 in time to death only.

Interestingly, SNPs known to be associated with longev- ity and disease in the neighborhood of APOE (Deelen et al., 2011) orFOXO3A (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 com- prised 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, per- forms 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 anal- yses can provide useful information exploring multiple gene effects and their interactions.

In conclusion, our analysis did provide suggestive evi- dence that aging is under neuronal control. Unfortunately, we have no relevant tissue or expression experiment avail- able 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 diffi- cult because individual results may involve many seemingly unrelated genes. Because PANTHER and IPA are built on different conceptual approaches, database sources and dif- ferent pathway classifications, they can be seen as comple- mentary approaches. Our pathway and network analyses highlighted neuronal activities and organism developmental processes as major biological processes involved aging. In addition, it highlighted Wnt signaling and showed that those

Disclosure statement

The authors declare that no competing interests exist. All participants included in this analysis provided written informed consent.

National Institute of Aging R01 AG031890 with additional contribution from the National Institute of Neurological Disorders and Stroke. A full list of principal CHS investi- gators and institutions can be found at www.chs-nhlbi.org/ pi.htm. DNA handling and genotyping was supported in part by National Center for Research Resources grant M01- RR00425 to the Cedars-Sinai General Clinical Research Center Genotyping core and National Institute of Diabetes and Digestive and Kidney Diseases grant DK063491 to the Southern California Diabetes Endocrinology Research Cen-

Replication Samples