This study used the largest sample size to-date to investigate 15 of the top AlzGene hits (AlzGene, accessed October 2010) which were originally identified in a LOAD GWAS. Meta-analyses remained significant at three loci after addition of our data: GAB2 (rs10793294, OR = 0.78, p = 0.007), LOC651924 (rs6907175, OR = 0.91, p = 0.01) and TNK1 (rs1554948, OR = 0.92, p = 0.02). Although our data alone provided no support for an association of TNK1 with LOAD (OR = 1.00, p = 0.99), the AlzGene meta-analyses odds ratios for both GAB2 (0.69) and LOC651924, (0.89) were well replicated in our series (OR = 0.89 and 0.94, respectively) albeit that neither variant was significant (p = 0.40 and 0.37, respectively). We also investigated nine additional variants (in EBF3, LMNA, BCR, THEM5, PCK1, MYH13, CTSS, UBD and TRAK2) identified by Grupe et al. but found no significant associations following meta-analyses.
Our meta-analyses which include nine independent studies comprising 9,072 individuals provide good evidence that GAB2
(rs10793294 OR = 0.78, p
= 0.007) is a genuine candidate LOAD locus. These data are further supported by a recent family-based study (Schjeide et al. 2009a
), which revealed significant association of another GAB2
variant (rs7101429) in 399 families (p
= 0.002), thus strengthening the evidence for GAB2
. In consideration of this association of GAB2
with LOAD in families, we performed our logistic regression (additive model) analyses again on the total dataset with the 112 NCRAD LOAD patients with a family history of AD removed. We found that removing these samples gave a comparable association to our initial analyses (all samples: n
= 4,969, OR = 0.94, p
= 0.20; no family history: n
= 4,857, OR = 0.95, p
= 0.36; data not shown). We also found a comparable association of GAB2
with age-at-onset after removal of these samples (all samples: n
= 2,416, U
= 692,338.5, p
= 0.68; no family history: n
= 2,304, U
= 628,587, p
= 0.76; data not shown). Notably, in another family-based study by the same group, eight variants included in this manuscript (GALP
) were tested but failed to show association with LOAD in 457 families (Schjeide et al. 2009b
); this is compatible with our meta-analyses of variants in GWA_14q32.13
(rs3800324) and GALP
(rs3745833) which revealed no association with LOAD.
Our meta-analyses also provided evidence that LOC651924 is a true candidate locus (OR = 0.91, p = 0.01). Although only one out of the nine series studied revealed significant association (p < 0.05), the effect of the variants were in the same direction (with comparable ORs) in seven of the series. As a result, the meta-analysis revealed significant association thus supporting the evidence for LOC651924 as a LOAD candidate.
The 15 variants we analyzed showed remarkable across-study heterogeneity. The Breslow–Day p values for the initial, Mayo follow-up and overall meta-analyses of the 15 variants we analyzed are summarized in Table and Online Resource 6. Overall, meta-analysis of the variants in four genes (GAB2, TRAK2, LMNA and PCK1) gave Breslow–Day p values ranging from <0.0001 to 0.002 that are significant even after Bonferroni correction for 15 variants analyzed (p < 0.003). The variants in seven genes had nominally significant or highly suggestive Breslow–Day p values that ranged from 0.01 to 0.06, and the variants in the three remaining genes had Breslow–Day p values of 0.12 to 0.25. Thus, our analysis of 15 promising LOAD variants suggests that LOAD variants may often show noteworthy series to series heterogeneity. If the heterogeneity we observed is real and if it occurs as frequently as our data suggest, then many genetic variants may influence LOAD susceptibility in a way that depends on genetic and/or environmental factors that vary from series to series.
It is now clear that, apart from the well-known APOE alleles, common genetic variants have only weak association with LOAD. Whether many of these variants have odds ratios that truly vary because they depend on environmental and/or genetic factors that differ from series to series is currently unclear. What is clear is that variants of this type are likely to be missed if genetic association studies focus exclusively on replicable associations that become highly significant when many series are combined. To find important susceptibility alleles with effects that vary from series, it may be necessary to consider and to understand variants that show significant association in some series and highly significant heterogeneity on meta-analysis even though meta-analysis provides no evidence for association.
It is important to recognize that spurious heterogeneity can occur owing to publication bias wherein only those series that, by chance, have false-positive results are published. When these series are combined with follow-up series with ORs that vary randomly around 1.0, Breslow–Day testing can show significant, but misleading evidence of heterogeneity. One way to mitigate this problem is to determine if, when initial series are eliminated, the follow-up studies show heterogeneity. In the current study, the variants in GAB2 and in LMNA had Breslow–Day p values of 0.0002 and 0.002 in the Mayo follow-up series alone that retain significance even after Bonferroni correction for 15 variants tested. It is worth noting that both the GAB2 and LMNA variants also showed significant heterogeneity in the initial studies with p values of 0.0009 and 0.01, respectively and in the overall meta-analysis with p values of <0.0001 and 0.0004, respectively. Since it appears that two of the 15 variants we studied showed true series to series heterogeneity, it seems appropriate to consider that the heterogeneity observed for many of the other variants may also be real.
One interesting cause of heterogeneity occurs when the “heterogeneous” variant is merely a tag for the truly functional variant (or multiple rare variants each with strong functional effects) and the degree of linkage disequilibrium between these variants differs between series leading to weaker and/or opposing effects. When this is the case, variants (e.g., those in GAB2 and GWA_14q32.13) that show significant heterogeneity between multiple, large, case–control series could be used to identify candidate regions for targeted sequencing and haplotype analysis that resolves the heterogeneity thereby identifying functional variants that show replicable, significant association.
We also investigated whether the 15 variants were associated with age-at-onset. Although we have suggestive evidence that PGBD1 and EBF3 may be associated with age-at-onset and that LMNA may interact with APOE ε4, due to the multiple tests performed and the relatively weak p values obtained (all p > 0.02), we suggest that further investigation into these findings is required in order to determine whether these were merely due to chance or if they represent true associations.
Finally, we tested for pairwise interactions between the 15 variants evaluated in this study as well as with APOE ε4, BIN1 (rs744373), CLU (rs11136000), CR1 (rs3818361), EXOC3L2 (rs597668) and PICALM (rs3851179). Seven pairs showed nominally significant synergy factors (p values ranging from 0.007 to 0.05), but none remained significant after correction for the 105 tests performed (p < 0.0005). It is possible that many epistatic interactions exist between LOAD genes, of which relatively few combinations have been tested here. We therefore propose that future studies of candidate LOAD genes apply tests for epistasis with other candidate genes in order to identify otherwise hidden interactions that could contribute greater risk than any gene individually.
Overall, this study represents a thorough, independent follow-up study of 15 of the top LOAD candidate genes, in a large case–control series and provides further evidence for the association of GAB2 and LOC651924 (6q24.1) with LOAD. In addition, we have provided suggestive evidence that, in our series, two genes (PGBD1 and EBF3) are potentially associated with age-at-onset of LOAD.
The experiments described in this manuscript comply with the current laws of the United States of American where they were performed. Approval was obtained from the ethics committee or institutional review board of each institution responsible for the ascertainment and collection of samples (Mayo Clinic College of Medicine, Jacksonville, FL and Mayo Clinic College of Medicine, Rochester, MN, USA). Written informed consent was obtained for all individuals that participated in this study.