APOE has been extensively examined with respect to human aging due to its role in AD and vascular disease. A longitudinal study following subjects for 18 years using 1094 individuals aged 75 and older showed that the risk of mortality was affected by the APOE gene. Risk was in- creased by 22% in those carrying the APOE &4 4 allele, decreased by 28% in those carrying the APOE ; €2 2 allele, and individuals carrying APOE  3 allele showed no significant difference in risk (Lewis and Brunner, 2004; Rosvall et al., 2009). The association between the APOE i i€2 2 variant and aging has been investigated in Finish centenarians, where a trend of association was observed—9%, 21%, and 25% in people aged 100 to 101, 102 to 103, and 104 years and older, respectively (Frisoni et al., 2001). SNP rs2075650 is '€4 known to be in tight LD with the APOE 4 allele (Yu et al., 2007). The direction of the effect of this SNP in our study  is compatible with previous findings for the APOE 4 allele (Christensen et al., 2006). Apolipoprotein E (APOE) is a major transporter of cholesterol and has been implicated in multiple age-related diseases including LOAD and vascular diseases (Panza et al., 2007).

The Manhattan plot shown in Fig. 5 represented a sce- nario before removal of these 5 false positive SNPs.

3.3. Power calculation

Power calculations indicate that a sample size approxi- mately between 3000 and 15,000 is required in order to have 80% power to detect an association with a MAF ranging above 0.05. Approximately 4000 to 19,000 samples will be needed if 95% power is required.

This estimation should be interpreted with caution as it is based on a number of assumptions (such as effect size and mode of inheritance), and gene-environment interaction 3 XE (G E) has not been taken into account.

We observed no evidence of association with the remain- ing LOAD genes implying that these genes are genuine LOAD genes with no detectable effects on human aging. However we cannot rule out the possibility that these genes may have a weak effect on aging that our dataset was not sufficiently large enough to detect.

4. Discussion

It is known that advancing age is one of the biggest risk factors for LOAD. The prevalence of LOAD has been estimated ranging from 0.6% in persons aged 65 to 69 years to 22.2% in persons aged 90 and older (Lobo et al., 2000). Because age is one of the biggest risk factors for LOAD, it is important to understand whether genes involved in LOAD play a role in successful aging.

We subsequently analyzed all SNPs on the Illumina chips after stringent QC procedures. The mean AAD for the samples analyzed was older than 80 years. This minimized the possibility of early death (prior to age 40 years) as a result of underlying nongenetic factors or highly penetrant genetic factors affecting our analysis (McGue et al., 1993).

In an assessment of all SNPs on the chip, none were found to approach genome-wide significance as calculated for this study (p y< 1.04  10(cid:3)7). The inability to detect any novel aging associated variants is likely the result of a lack of power. The calculation of power using QUANTO (ver- sion 1.2.4) has suggested a much larger sample size is required in order to detect an association with common variants. With rare exceptions, common variants are known to exert only small to moderate effects, according to previ- ous studies of many complex disorders and traits (Bodmer and Bonilla, 2008). Presenting our data on genes that lie between 10(cid:3)5 and 10(cid:3)8, while not making genome wide significance, may enable groups to identify genes for future study especially if there is overlap with other studies. Ad- ditionally these data could be used as part of a larger meta-analysis.

In this study, we have performed an association test of the top GWAS LOAD genes (APOE, CLU, PICALM, CR1, BIN1, ABCA7, MS4A6A, CD33, CD2AP, and EPHA1) with human aging using the most significant SNPs found in previ- ous studies. Apart from the well-documented association be- tween APOE and LOAD, the association with the other 9 genes was identified recently through large GWAS, each with a sample size of over 10,000 (Harold et al., 2009; Hollingworth et al., 2011; Lambert et al., 2009; Naj et al., 2011).

The results of our analysis provided compelling evidence of association between APOE locus (rs2075650) and human aging (p  5.27 xX 10(cid:3)4) (Table 3A) with risk effect based on the analysis of 1364 samples using AAD as a continuous trait. The minor allele frequency plot (Fig. 6) shows that the MAF of this SNP significantly decreases in the old AAD category (MAF  0.21; AAD ov> 89 years of age; n  228) compared with the other 4 younger AAD categories (MAF   0.27; AAD )=i 89; n   1136). Individuals homozy- gous for the minor allele “G” showed significantly lowered   AAD (p 0.002) compared with individuals homozygous

GWAS provide a method of identifying common genetic variations associated with disease or phenotype in an unbi- ased manner. However, it comes with a price of multiple testing given that many thousands of SNPs are tested si-

multaneously, and a very stringent significance threshold (p  5  10(cid:3)8) is often used to infer a genome-wide significant association and to avoid a large number of false positives (Bertram and Tanzi, 2008).

factors associated with aging. We have addressed this by correcting for AD status. However, it is possible that APOE association with age in the AD group could be due to its involvement in duration and severity of AD (Dal Forno et al., 2002). We do not however have clinical pathological features for these samples, and therefore cannot explore these endophenotypes.