Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease

Eleven susceptibility loci for late-onset Alzheimer’s disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer’s disease cases and 37,154 controls. In stage 2,11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer’s disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer’s disease. Alzheimer’s disease is a devastating neurological disorder primarily affecting the elderly. The disease manifests with progressive deterioration in cognitive functions, leading to loss of autonomy. The APOE gene (encoding apolipoprotein E) is a major genetic risk factor for Alzheimer’s disease1,2. Previous GWAS in individuals of European ancestry identified nine Correspondence should be addressed to P.A. ([email protected]) or J.W. ([email protected]). 87Full lists of members and affiliations appear in the Supplementary Note. 145These authors contributed equally to this work. 146These authors jointly directed this work. Note: Any Supplementary Information and Source Data files are available in the online version of the paper. AUTHOR CONRIBUTIONS Study concept and design: J.-C.L., C.A.I.-V., D. Harold, A.C.N., A.L.D., J.C.B., A.V.S., M.A.I., H. Schmidt, A.L.F., V.G., O.L.L., D.W.T., D. Blacker, T.H.M., T.B.H., J.I.R., W.A.K., M. Boada, R. Schmidt, R.M., A.H., B.M.P., J.L.H., P.A.H., M.L., M.A.P.-V., L.J.L., L.A.F., C.M.v.D., V.M., S. Seshadri, J.W., G.D.S. and P.A. Acquisition of data: J.-C.L., C.A.I.-V., D. Harold, C. Bellenguez, R. Sims, G.J., B.G.-B., G.R., N.J., V.C., C. Thomas, D.Z., Y.K., A.G., H. Schmidt, M.L.D., M.-T.B., S.-H.C., P.H., V.G., C. Baldwin, C.C., C. Berr, O.L.L., P.L.D.J., D.E., L. Letenneur, G.E., K.S., A.M.G., N.F., M.J.H., M.I.K., E.B.L., A.J.M., C.D., S.T., S. Love, E.R., P.S.G.-H., L.Y., M.M.C., D. Beekly, F.Z., O.V., S.G.Y., W.G., M.J.O., K.M.F., P.V.J., M.C.O., L.B.C., D.A.B., T.B.H., R.F.A.G.d.B., T.J.M., J.I.R., K.M., T.M.F., W.A.K., J.F.P., M.A.N., K.R., J.S.K.K., E.B., M.R., M. Boada, L.-S.W., J.-F.D., C. Tzourio, M.M.N., B.M.P., L.J., J.L.H., M.L., L.J.L., L.A.F., A.H., C.M.v.D., S. Seshadri, J.W., G.D.S. and P.A. Sample contribution: A. Ruiz, F. Pasquier, A. Ramirez, O.H., J.D.B., D. Campion, P.K.C., C. Baldwin, T.B., C.C., D. Craig, V.D., J.A.J., S. Lovestone, F.J.M., D.C.R., K.S., A.M.G., N.F., M.G., K. Brown, M.I.K., L.K., P.B.-G., B.M., R.G., A.J.M., D.W., E.R., J.G., P.S.G.H., J.C., A.L., A. Bayer, M.T., P. Bossù, G.S., P. Proitsi, J.C., S. Sorbi, F.S.-G., N.C.F., J.H., M.C.D.N., P. Bosco, R.C., C. Brayne, D.G., M. Mancuso, F.M., S. Moebus, P.M., M.D.Z., W.M., H. Hampel, A.P., M. Bullido, F. Panza, P.C., B.N., M. Mayhaus, L. Lannfelt, H. Hakonarson, S.P., M.M.C., M.I., V.A., S.G.Y., E.C., C. Razquin, P. Pastor, I.M., O.C., H. Soininen, S. Mead, D.A.B., L.F., C.H., P. Passmore, T.J.M., K. Bettens, A. Brice, D. Hannequin, K.R., M.R., M.H., D.R., C.G. and C.V.B. Data analysis: C.A.I.V., D. Harold, A.C.N., R. Sims, C. Bellenguez, G.J., A.L.D., J.C.B., G.W.B., B.G.-B., G.R., T.A.T.-W., N.J., A.V.S., V.C., M.A.I., D.Z., Y.K., B.N.V., C.-F.L., A.G., B.K., C. Reitz, J.R.G., O.V., W.A.K., K.L.L., K.L.H.-N., E.R.M., L.-S.W., B.M.P., M.L., V.M. and J.W. Statistical analysis and interpretation: J.-C.L., C.A.I.-V., D. Harold, A.C.N., C. Bellenguez, G.J., A.L.D., J.C.B., G.W.B., T.A.T.-W., A.V.S., V.C., M.A.I., B.N.V., Y.K., C.-F.L., B.K., C. Reitz, A.L.F., N.A., J.R.G., R.F.A.G.d.B., W.A.K., K.L.L., E.R.M., L.-S.W., B.M.P., L.J., J.L.H., P.A.H., M.A.P.-V., L.J.L., L.A.F., C.M.v.D., V.M., S. Seshadri, J.W., G.D.S. and P.A. Drafting of the manuscript: J.-C.L., C.A.I.-V., D. Harold, A.C.N., C. Bellenguez, A.L.D., J.C.B., A.V.S., R.M., B.M.P., J.L.H., M.A.P.-V., L.J.L., L.A.F., C.M.v.D., C.V.B., S. Seshadri, J.W., G.D.S. and P.A. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. NIH Public Access Author Manuscript Nat Genet. Author manuscript; available in PMC 2014 June 01. Published in final edited form as: Nat Genet. 2013 December ; 45(12): 1452–1458. doi:10.1038/ng.2802. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript other genomic regions associated with LOAD3–7. Recently, a rare susceptibility variant in TREM2 was identified8,9. The search for additional genetic risk factors requires large-scale meta-analysis of GWAS to increase statistical power. Under the banner of I-GAP (International Genomics of Alzheimer’s Project), we conducted a meta-analysis of 4 GWAS samples of European ancestry totaling 17,008 cases and 37,154 controls (stage 1) followed up by genotyping of 11,632 SNPs showing moderate evidence of association (P < 1 × 10−3 in stage 1) in an independent sample that included 8,572 cases and 11,312 controls (stage 2). In the stage 1 meta-analysis, we used data from four consortia: the Alzheimer’s Disease Genetic Consortium (ADGC), the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, the European Alzheimer’s Disease Initiative (EADI) and the Genetic and Environmental Risk in Alzheimer’s Disease (GERAD) Consortium (Table 1, Online Methods, Supplementary Table 1 and Supplementary Note). We used European population reference (EUR) haplotype data from the 1000 Genomes Project (2010 interim release based on sequence data freeze from 4 August 2010 and phased haplotypes from December 2010) to impute genotypes for up to 11,863,202 SNPs per data set. We excluded SNPs that did not pass quality control in each study (Supplementary Table 2 and Supplementary Note). Our meta-analysis included SNPs either genotyped or successfully imputed in at least 40% of the Alzheimer’s disease cases and 40% of the control samples across all data sets (7,055,881 SNPs; Online Methods). In each data set, genotype dosages were analyzed as described in the Supplementary Note (Supplementary Table 2). We performed meta-analysis of the results after applying genomic control correction to each study. The genomic control inflation factor for the meta-analysis was 1.087 for the full set of SNPs and 1.082 after excluding SNPs within the APOE locus (chr. 19: 45,409,039– 45,412,650) and within 500 kb of SNPs associated with Alzheimer’s disease at a prespecified level of genome-wide significance (P < 5 × 10−8) in stage 1 (see Supplementary Fig. 1 for quantile-quantile plots). In addition to the APOE locus, 14 genomic regions had associations that reached the genome-wide significance level (Fig. 1). Nine had been previously identified by GWAS as genetic susceptibility factors3–7, and five (HLA-DRB5–HLA-DRB1, PTK2B, SORL1, SLC24A4-RIN3 and DSG2) represent newly associated loci (Table 2). SORL1 had previously been identified as an Alzheimer’s disease gene through candidate gene approaches and in a GWAS combining ADGC and Asian samples10. Genes attributed to a signal were those closest to the most significantly associated SNP. However, we are aware that these are potentially not the causative genes. Detailed results for each region are given in Supplementary Figure 2–7. In stage 2, we selected for genotyping all stage 1 SNPs with a P value less than 1 × 10−3, excluding SNPs flanking APOE (chr. 19: 45,409,039–45,412,650) (n = 19,532; see URLs for database access). From the initial set of SNPs, 14,445 could be genotyped using Illumina iSelect technology. After quality control procedures (Online Methods), we considered 11,632 SNPs for association analysis. The stage 2 sample included 8,572 cases and 11,312 controls of European ancestry originating from Austria, Belgium, Finland, Germany, Greece, Hungary, Italy, Spain, Sweden, the UK and the United States (Table 1 and Supplementary Note). We observed 116 SNPs showing the same risk allele and direction of association in stages 1 and 2 that were significantly associated with Alzheimer’s disease risk in stage 2 after a strict Bonferroni correction for multiple testing (P < 4.3 × 10−6). Of these 116 SNPs, 80 had been associated at genome-wide significance with Alzheimer’s disease risk in stage 1. Additionally, in analyses in stage 2, 2,562 SNPs were associated with Alzheimer’s disease at a nominal level of significance (P < 0.05), having the same risk allele and direction of association as in stage 1. Lambert et al. Page 2 Nat Genet. Author manuscript; available in PMC 2014 June 01. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript The results from stages 1 and 2 and from the combined stage 1 and stage 2 data sets, which represent a secondary discovery effort, are shown in Table 2. With the exception of CD33 and DSG2, we nominally replicated all loci that surpassed the genome-wide significance level in stage 1. Inability to replicate DSG2 is not surprising, as evidence of association for this locus was based on data for a single SNP and was not supported by data from surrounding SNPs in linkage disequilibrium (LD, r2 > 0.8; Supplementary Fig. 7b). Moreover, seven new loci reached the genome-wide significance level in the combined analysis (Table 2). More detailed results for the seven newly identified LOAD loci are provided in Supplementary Figure 8–11. There was no significant heterogeneity across studies at any of the loci, except at DSG2 (Table 2 and Supplementary Fig. 12–16). To identify potential causative genes, we also examined all SNPs with association P < 5× 10−8 that were within 500 kb of the top SNP at each locus to identify cis expression quantitative trait locus (cis-eQTL) associations (Online Methods and Supplementary Table 3). The results from the combined stage 1 and stage 2 data sets also identified 13 loci with suggestive evidence of association (P < 1 × 10−6) (Supplementary Table 4). Among these, we detected a signal for rs9381040 (P = 6.3 × 10−7), which is located approximately 5.5 kb away from the 3′ end of TREML2 and 24 kb away from the 5′ end of TREM2. TREM2 was recently reported to carry a rare variant (encoding p.Arg47His) associated with threeto fourfold increased risk of developing Alzheimer’s disease8,9. This region also reached genome-wide significance in a study of cerebral spinal fluid levels of phosphorylated tau, a biomarker for Alzheimer’s disease11. Beyond the already known, GWAS-defined genes (ABCA7, BIN1, CD33, CLU, CR1, CD2AP, EPHA1, MS4A6A–MS4A4E and PICALM), the most significant new association was in the HLA-DRB5–DRB1 region (encoding major histocompatibility complex, class II, DRβ5 and DRβ1, respectively). This region is associated with immunocompetence and histocompatibility and, interestingly, with risk of both multiple sclerosis and Parkinson disease12,13. Owing to the complex genetic organization of the human leukocyte antigen (HLA) region on chromosome 6, we were unable to define which gene(s) are responsible for this signal (Supplementary Fig. 6a). The second strongest signal was within the SORL1 gene (encoding sortilin-related receptor, L(DLR class) 1). Our data clearly demonstrated that this gene was associated at genomewide significance in European samples. SORL1 is noteworthy, as it is associated with increased risk of both autosomal dominant and sporadic forms of Alzheimer’s disease14,15 and represents the first LOAD gene that directly connects aberrant trafficking and metabolism of the amyloid precursor protein (APP) to LOAD14. The third locus, PTK2B (encoding protein tyrosine kinase 2β), is only approximately 130 kb away from CLU, but we believe the two signals are independent because (i) the two most strongly associated SNPs within each of these two genes are not in LD (D′ = 0.06 and r2 = 0.003 as computed using 1000 Genomes Project data); (ii) a recombination peak exists between the two loci (Fig. 2); and (iii) conditional analysis in the stage 2 data confirmed the independence of the PTK2B association (Supplementary Fig. 17 and Supplementary Table 5). The protein encoded by PTK2B may be an intermediate between neuropeptide-activated receptors or neurotransmitters that increase calcium flux and the downstream signals regulating neuronal activity such as mitogen-activated protein kinase (MAPK) signaling16. PTK2B is involved in the induction of long-term potentiation in the hippocampal CA1 (cornu ammonis 1) region, a central process in the formation of memory17. We cannot, however, exclude the possibility that there are multiple signals in the PTK2B–CLU region that are functionally connected to a single gene. For instance, two SNPs associated with Lambert et al. Page 3 Nat Genet. Author manuscript; available in PMC 2014 June 01. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript genome-wide significance in the PTK2B–CLU region are eQTLs for the gene DPYSL2 that has been implicated in Alzheimer’s disease18 (Supplementary Table 3). The fourth locus was SLC24A4 (encoding solute carrier family 24 (sodium/potassium/ calcium exchanger), member 4). The SLC24A4 gene encodes a protein involved in iris development and hair and skin color variation in humans in addition to being associated with the risk of developing hypertension19,20. SLC24A4 is also expressed in the brain and may be involved in neural development21. Of note, in the vicinity of the most strongly associated SNP is another gene called RIN3 (encoding Ras and Rab interactor 3), and its gene product directly interacts with the BIN1 gene product22, a protein that may be connected to tau-mediated pathology23. In addition to these four loci reaching genome-wide significance in stage 1, seven new loci reached genome-wide significance in the combined analysis. The strongest association at one of these new loci was intronic in the ZCWPW1 gene (encoding zinc finger, CW type with PWWP domain 1), whose corresponding protein modulates epigenetic regulation24. However, the region defined by all the SNPs associated with Alzheimer’s disease risk in our data is large and contains about ten genes (Supplementary Fig. 9b). Another interesting possible candidate gene in the ZCWPW1 region is NYAP1, as disruption of the corresponding gene in mice affects brain size, neurite elongation and, more generally, neuronal morphogenesis25. Our data do not resolve which gene in this region may be causal. A second locus was within the CELF1 gene (encoding CUGBP, Elav-like family member 1), whose gene product is a member of the protein family that regulates pre-mRNA alternative splicing26. As with the ZCWPW1 locus, the region of interest is large and contains about ten genes (Supplementary Fig. 10a). Among these genes is MADD (encoding MAP kinase–activating death domain), the reduced expression of which may affect longterm neuronal viability in Alzheimer’s disease27. A discrete signal was observed adjacent to NME8 (encoding NME/ NM23 family member 8), which is responsible for primary ciliary dyskinesia type 6 (ref. 28). The FERMT2 gene (encoding fermitin family member 2) is expressed in the brain. Its corresponding protein localizes to cell matrix adhesion structures, activates integrins, is involved in the orchestration of actin assembly and cell shape modulation, and is an important mediator of angiogenesis29. An association between the Drosophila melanogaster ortholog of FERMT2 (fit1/fit2) and tau-mediated toxicity was recently described30. We identified a fifth signal on chromosome 20 at CASS4 (encoding Cas scaffolding protein family member 4). Little is known about the function of the encoded protein. However, the Drosophila CASS family ortholog (p130CAS) binds to CMS, the Drosophila ortholog of CD2AP (CMS), a known Alzheimer’s disease susceptibility gene (Table 2) that is involved in actin dynamics31. Another locus was identified at INPP5D (encoding inositol polyphosphate-5-phosphatase, 145 kDa) on chromosome 2. INPP5D is expressed at low levels in the brain, but the encoded protein has been shown to interact with CD2AP, whose corresponding gene is one of the Alzheimer’s disease genes previously identified by GWAS32, and to modulate, along with GRB2, metabolism of APP33. We identified a seventh signal adjacent to MEF2C (encoding myocyte enhancer factor 2). Mutations at this locus are associated with severe mental retardation, stereotypic Lambert et al. Page 4 Nat Genet. Author manuscript; available in PMC 2014 June 01. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript movements, epilepsy and cerebral malformation34. The MEF2C protein limits excessive synapse formation during activity-dependent refinement of synaptic connectivity and thus may facilitate hippocampal-dependent learning and memory35. In summary, our Alzheimer’s disease GWAS meta-analysis has identified 11 new susceptibility loci in addition to the already known ABCA7, APOE, BIN1, CLU, CR1, CD2AP, EPHA1, MS4A6A–MS4A4E and PICALM genes. However, we were not able to replicate association of CD33 in our stage 2 analysis (P = 0.61). We did not detect any biases in terms of imputation in our discovery data sets or genotyping in our replication data sets (data not shown), suggesting a potential statistical fluctuation across our populations as an explanation for the lack of replication. However, recent data suggest that genetically determined decreased CD33 expression might reduce Alzheimer’s disease risk and interfere with amyloid β peptide clearance36, a dysfunction thought to be central in late-onset forms of Alzheimer’s disease37. Further investigations in independent case-control studies will thus be required to confirm or refute the association of CD33 with Alzheimer’s disease. The newly associated loci reinforce the importance of some previously suspected pathways such as APP (SORL1 and CASS4) and tau (CASS4 and FERMT2) in pathology. Several candidate genes at these loci are involved in pathways already shown to be enriched for association signal in Alzheimer’s disease GWAS38,39, such as immune response and inflammation (HLA-DRB5–DRB1, INPP5D and MEF2C), which is also supported by the described association of Alzheimer’s disease with CR1 (ref. 3) and TREM2 (refs. 8,9), cell migration (PTK2B) and lipid transport and endocytosis (SORL1). Our results also suggest the existence of new pathways underlying Alzheimer’s disease. These pathways could include hippocampal synaptic function (MEF2C and PTK2B), cytoskeletal function and axonal transport (CELF1, NME8 and CASS4), regulation of gene expression and posttranslational modification of proteins, and microglial and myeloid cell function (INPP5D). Examining the genetic effect attributable to all the associated loci, we demonstrated that the most strongly associated SNPs at each locus other than APOE had population-attributable fractions (PAFs) or preventive fractions between 1.0–8.0% in the stage 2 sample (Supplementary Table 6). Strong efforts in sequencing and post-GWAS analyses will now be required to fully characterize the candidate genes and functional variants responsible for the association of these GWAS-identified loci with Alzheimer’s disease risk and to understand their exact roles in the pathophysiology of Alzheimer’s disease40,41. URLs. 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