Power calculations were undertaken using QUANTO version 1.2.4.The required sample size was estimated using an additive model created by the software.

3. Results

2.4. MAF analysis of SNPs responsible for LOAD

3.1. Dataset composition and QC

The full range of AAD (58–108 years) was separated into 5 AAD categories, the boundaries of which were selected to ensure each group contains an approximately equal number of samples. This ensures SNP minor allele frequencies across each of the age categories are directly comparable. This was

The combined GWAS dataset has a sample size 1385 before QC. After QC, 4 participants were removed for low genotyping rate (--mind 0.05) from the Mayo GWAS (Carrasquillo et al., 2010). A single sample from Bristol

SNP used in our study Gene SNP cited in literature LD (r2) Literature rs2075650 APOE rs2075650 — Harold et al. (2009) rs11136000 CLU rs11136000 — Harold et al. (2009) rs3851179 PICALM rs3851179 — Harold et al. (2009) rs3818361 CR1 rs3818361 — Hollingworth et al. (2011) rs744373 BIN1 rs744373 — Hollingworth et al. (2011) rs3764650 ABCA7 rs3764650 — Hollingworth et al. (2011) rs610932 MS4A6A rs610932 — Hollingworth et al. (2011) rs3865444 CD33 rs3865444 — Hollingworth et al. (2011) rs1485780 CD2AP rs9349407 0.913 Hollingworth et al. (2011) rs11767557 EPHA1 rs11767557 — Hollingworth et al. (2011)

The most significant single nucleotide polymorphisms (SNPs) found in previous late-onset Alzheimer’s disease (LOAD) genome-wide association studies (GWAS) were selected for testing for their effects on human life span. The SNPs, associated genes, and the GWAS are as indicated. “-” indicates the original index SNP was used rather than a proxy. Key: LD, linkage disequilibrium.

3411051880 | (c¥P2C9)152944476(TCERG1L) = 104x107 7.00 |6.75) o-#510460926 ¢ ee i     -log10(p-value)oa 4 .>= 5x10 — : x - -  ntChrt = Chr2 se Chr3 == Chr4 see ChrS me Chr6 ee Chi? = Chis == Chr se Chr10 ee Chrit Chri? se Chri3 meme Chri 4 mm Chr15 == Chri6

——me Chit Chr?  Chi3 Se Chr4 ee Chr5 em Chr6 ee Chi7 ee Chis Se Cho  Chr10 ee Chri Chri? em Chris em Chris mm Chri § Se Chri6Chi 7 Chris se Chrig = Chr20 em Chr21 se Chr22  

Fig. 5. Manhattan plot of genome-wide association studies (GWAS) in human aging. Chromosomal position is shown on the x-axis versus -log GWAS p 10 value on the y-axis. The threshold for genome-wide significance (p pa 1.04 LX | 10(cid:3)7) and p value threshold (p   5 5X | 10(cid:3)5) are indicated by the horizontal lines. Single nucleotide polymorphisms (SNPs) between these thresholds show “suggestive” associations. The 5 SNPs (highlighted by circles) exhibit significant differences in allele frequencies between samples from Mayo and Washington University (WashU) (see Fig. 4). Two of the 5 SNPs (rs4110518 and rs2944476) showed spurious genome-wide significant signals as a result of this bias.

 LOAD cases (mean AAD 81.63 years) and controls (mean AAD AH 76.09 years), and similarly between male (mean AAD  77.93 years) and female (mean AAD  82.17 years). Anaysis of variance (ANOVA) tests of the variance of AAD between the groups (LOAD cases vs. controls and male vs. female) were found to be significant (p << ( 0.001). This confirmed that AD status and gender were appropriate covariates.

was removed due to discrepancies between AAD and age at onset (AAO). An additional 16 samples were removed as genetic outliers by PCs analysis using EIGENSTRAT. This included 14 samples from the Mayo data, 1 from NIMH, and 1 from Belfast. The mean AAD in the pooled dataset (post QC) was greater than 80 years of age

The multidimensional scaling (MDS) plot showed 3 dis- tinct clusters. As expected each cluster represents different population ancestry—CEU, middle right; CHB/JPT, bottom left; and YRI, top left (Fig. 7). UK, USA, and HapMap_ CEU samples formed a single cluster. On closer inspection, slight deviation between UK and USA samples exists and this was accounted for by including PCs as covariates.

After stringent QC, there were 1364 samples (1031 LOAD cases and 333 controls, 608 male and 756 female) and 528,430 SNPs remaining for further analysis.

3.2. Analysis and results

Genomic control inflation factor ((cid:1) ) was calculated using EIGENSTRAT by iteratively including 0 to 10 PC (Price et al., 2006). We found that including 6 PC generated the lowest genomic control inflation factor ((cid:1)  1.003).

Assessment of the 10 LOAD susceptibility genes yielded compelling evidence of association of APOE locus   (rs2075650) with human aging (uncorrected p 5.27 10(cid:3)4), which withstood multiple testing after Bonferroni correction for 10 independent tests (Table 3A).

Minor Allele Frequency (MAF)0.50 -0.45 -0.400.350.300.250.200.15,0.100.050.00  —e APOE~@-clu—@—PICALM_—=> CRI—m-BINI—#—ABCAT—@-MS4A6A,+033> a CD2AP—@-EPHAL$73>73-78>78-82 >82-89 289Age at death (yrs)

Fig. 6. Minor allele frequency (MAF) analysis for 10 late-onset Alzheimer’s disease (LOAD) genes with respect to aging. The figure shows the relationship between single nucleotide polymorphism (SNP) MAFs and human aging, where age at death (AAD) is separated into 5 categories. Each AAD category contains roughly equal amounts of samples to avoid bias in sample sizes. All 10 known LOAD genes are shown together with the APOE locus highlighted in bold (all other loci in gray). The APOE locus (rs2075650) showed significant association with aging, with MAF   0.27, AAD — 89 years of age (n  1136), and MAF  0.21, AAD >t 89 years of age (n  228). None of the other gene loci were significantly associated with aging.