Abstract
Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10−8) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10−10). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.
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Acknowledgements
We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H.
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Authors and Affiliations
Contributions
Clinical ascertainment, contribution of samples, study coordination and data analysis. G.R.A., A.A., J.A., R.A., I.A., A. Brucker, P.N.B., E.B., M. Benchaboune, H.B., J.B., F.B., A. Boleda, C.B., K.E.B., M.H.B., K.P.B., M.S.C., P.C., A.C., D. Chen, D. Cho, I.C., I.J.C., J.E.C., A.J.C., C.A.C., M.D., J.-F.D., A.I.d.H., B.D., L.E., L.A.F., S.F., H.F., K.F., J.R.F., L.G.F., L.G., B.G., M.B.G., S.V.G., R.H.G., S.H.-L., S.A.H., J.L.H., J.H., M.A.H., C.H., S.J.H., J.R.H., I.M.H., A.W.H., J.D.H., F.G.H., C.B.H., D.J.H., T.I., S.K.I., M.P.J., N.K., J.C.K., I.K.K., T.E.K., C.C.W.K., B.E.K.K., M.L.K., R.K., J.L.K., A.M.K., S.L., T. Langmann, R.L., Y.T.E.L., K.E.L., T. Léveillard, M.L., H.H.L., G.L., D.L., A.J.L., H.L., D.A.M., G.M., T.M.M., I.L.M., J.A.M., J.E.M., J.C.M., S.M.M., P.M., S.M.-S., A.T.M., E.L.M., C.E.M., A.O., M.I.O., H.O., K.H.P., N.S.P., M.A.P.-V., E.A.P., C.A.R., A.J.R., G.R., J.-A.S., N.T.M.S., D.A.S., T.S., H.P.N.S., S.G.S., W.K.S., S.S., H.S., G.S., R.T.S., E. Souied, E. Souzeau, D.S., Z.S., A.S., A.G.T., B.T., E.E.T., C.M.v.D., C.N.v.S., B.J.V., J.J.W., B.H.F.W., D.E.W., C.W., A.W., Z.Y., J.R.W.Y., D.Z. and K.Z.
Phenotype committee. I.K.K. (lead), S.K.I. (lead), M.D. (lead), G.H.S.B., E.Y.C., I.C., A.I.d.H., S.F., M.B.G., J.L.H., I.M.H., A.W.H., C.C.W.K., B.E.K.K., M.L.K., R.K., T. Léveillard, A.J.L., K.H.P., J.J.W. and K.Z.
Data analysis. Team 1: quality control of data: J.L.B.-G., M.D., L.G.F., M. Gorski, W.I. and I.K.K. Team 2: single-variant analysis: L.G.F. (lead), I.M.H. (lead), G.R.A. (lead), W.I. (lead), J.L.B.-G., G.H.S.B., V.C., M.D., M. Gorski, F.G., M. Grunin, J.L.H., R.P.I., S.K.I., C.C.W.K., M.O., K.S. and X.Z. Team 3: pathway and rare variant burden analysis: L.G.F. (lead), J.N.C.B. (lead), M.S. (lead), G.R.A., M.A.B., M. Brooks, G.H.S.B., M.D.C., M.D., E.K.d.J., A.I.d.H., L.A.F., F.G., J.L.H., I.M.H., J.D.H., W.I., R.P.I., S.K.I., Y.J., M.A.M., M.O., M.A.P.-V., R.J.S., W.K.S., K.S., A.S., B.H.F.W., D.E.W. and X.Z. Team 4: analysis of non-SNP variation: R.P.I. (lead), S.K.I. (lead), P.N.B. (lead), G.R.A., M.D.C., L.G.F. and J.L.H. Team 5: functional data analysis: D.S. (lead), B.H.F.W. (lead), M.D. (lead), S.K.I. (lead), V.C., J.N.C.B., M.D.C., E.K.d.J., A.I.d.H., S.F., L.G.F., F.G., J.L.H., C.H., I.M.H., W.I., D.J.M., M.A.M., R.R., C.M.S., A.S. and X.Z.
Design of overall experiment. G.R.A., M.D., L.G.F., J.L.H., I.M.H., S.K.I., M.A.P.-V. and B.H.F.W.
Genotyping and quality control. K.F.D. (lead), J.R. (lead), L.G.F. (lead), M. Gorski (lead), G.R.A., J.L.B.-G., M.D.C., F.G., J.L.H., I.M.H., J.D.H., W.I., M.O. and X.Z.
Writing team. L.G.F. (lead), I.M.H. (lead), G.R.A., J.N.C.B., M.D., J.L.H., W.I., S.K.I., I.K.K., D.S. and B.H.F.W.
Critical review of manuscript. G.R.A., R.A., P.N.B., M.H.B., I.C., J.N.C.B., M.D., S.F., A.I.d.H., L.A.F., L.G.F., M.B.G., S.A.H., J.L.H., C.H., I.M.H., A.W.H., W.I., S.K.I., I.K.K., C.C.W.K., B.E.K.K., M.L.K., R.K., T. Léveillard, A.J.L., P.M., A.T.M., K.H.P., N.S.P., M.A.P.-V., D.A.S., D.S., A.S., J.J.W., B.H.F.W., D.E.W., J.R.W.Y. and K.Z.
Steering committee of IAMDGC. A.S., G.R.A., A.W.H., M.H.B., K.Z., B.H.F.W., I.M.H., M.D., L.A.F., K.H.P., I.K.K., D.S., T. Léveillard, A.J.L., I.C., S.K.I., S.A.H., N.S.P., B.E.K.K., R.K., D.A.S., M.A.P.-V., P.M., J.J.W., R.A., A.T.M., J.R.W.Y., J.L.H., S.F., A.I.d.H., P.N.B., M.L.K., M.B.G., D.E.W., C.H. and C.C.W.K.
Senior executive committee of IAMDGC. G.R.A., M.D., J.L.H., S.K.I., M.A.P.-V. and B.H.F.W.
Corresponding authors
Ethics declarations
Competing interests
D.E.W. and M.B.G. have inventor status on patents held by the University of Pittsburgh regarding the 10q26 AMD susceptibility locus. V.C., A.T.M. and J.R.W.Y. are co-inventors or beneficiaries of patents related to genetic discoveries in AMD. I.C. serves as a consultant for Novartis, Bayer, Allergan and Lycored. L.G.F. and B.H.F.W. receive royalties for AMD-related patents held by the University of Regensburg, G.R.A., A.S., M.I.O. and K.E.B. receive royalties for AMD-related patents held by the University of Michigan and G.R.A. is on the Scientific Advisory Board for the Regeneron Genetics Center. P.M. holds a consultant position for Bayer and Novartis. A.J.L. has acted as a consultant to Bayer, Allergan, Roche and Novartis. S.G.S. has acted as a consultant to Alimera and Bausch + Lomb and has received writing fees from Vindico.
Integrated supplementary information
Supplementary Figure 1 Flowchart of subject processing and quality control.
We removed technical controls and performed quality control (e.g., exclusion of subjects with low call rate, violation of Hardy-Weinberg equilibrium or unexpected duplicates). We then imputed all remaining subjects together with the 1000 Genomes Project reference panel (Phase I). We excluded external subjects (sample collection unconnected with this project), and subjects were classified by genetically inferred relatedness and ancestry. Advanced AMD cases with age below 50 years (n = 211) or subjects with missing phenotypes (n = 475) were classified as ‘unclear phenotype’. Subjects with advanced AMD and controls of any ancestry as well as European subjects with intermediate AMD were analyzed (green boxes).
Supplementary Figure 2 Quantile-quantile plot for genome-wide single-variant association analysis.
Shown are the observed P values (–log10 (P)) from the single-variant association analysis (16,144 advanced AMD cases versus 17,832 controls) for all variants (blue) and without the variants in the known AMD loci (green) compared to those expected under the null hypothesis (no association). The black dotted line indicates the identity (no association) and the 95% confidence interval. The observed P values are corrected by genomic control using λ of 1.130.
Supplementary Figure 4 A counterexample of credible set variants being able to depict the most likely causal variant(s) in the case of haplotype effects.
Haplotype analysis elucidated that rs116503776 (C2/CFB/SKIV2L), which is the sole 95% credible set variant in this signal, tags two previously described CFB missense variants, rs4151667 (CFB: p.Leu9His) and rs641153 (CFB: p.Arg32Gln). Using the 16,144 patients and 17,832 controls, we derived the SNP and haplotype associations for the three variants, with haplotypes estimated during imputation. Shown are odds ratios (ORs) and P values from Firth’s bias-corrected logistic regression, adjusting for principal components, DNA source and the other index variants in the locus (rs144629244, rs114254831 and rs181705462; locus-wide conditioning). (a) rs116503776 (SKIV2L intron) showed a stronger association than CFB: p.Leu9His or CFB: p.Arg32Gln and is thus included in the 95% credible set as the statistically most likely causal variant (in fact, as the sole credible set variant, posterior probability = 1.00; Supplementary Table 7). (b) Haplotype analysis showed that it is not the A allele of rs116503776 that carries the risk (H4) but rather its coinciding with the A allele of CFB: p.Leu9His or CFB: p.Arg32Gln (H2 and H3, respectively), which is supported by the rare haplotype with the CFB: p.Arg32Gln A allele without the rs116503776 A allele (H5) carrying risk.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–4, Supplementary Tables 1–20 and Supplementary Note. (PDF 2228 kb)
Supplementary Data Set 1: LocusZoom plots for each of the 52 identified signals.
Regional plots showing single-variant association P values of variants around each of the 52 index variants. Shown are also the location/direction of underlying genes and the location of the variants in the 95% credible sets. (PDF 1620 kb)
Supplementary Data Set 2: Extended results of the 34 lead variants in non-European subjects.
We analyzed the association of advanced AMD compared to control subjects in Asian (473 cases, 1,099 controls), African (52 cases, 361 controls) and ‘other ancestry’ (254 cases, 694 controls) groups for our 34 lead variants. Shown are frequencies, odds ratios and P values from the Firth-corrected logistic regression for all analyses. (XLSX 21 kb)
Supplementary Data Set 3: Variants in 95% credible sets and their annotation.
For each of the 52 index variants, the 95% credible set contains the minimal set of variants that add up to >95% posterior probability. (XLSX 136 kb)
Supplementary Data Set 4: Details about the identified rare protein-altering variants in CFH, CFI, TIMP3 and SLC18A8 that we found to be enriched in AMD cases (Table 2).
Here we show the variants of each gene below the optimal risk allele frequency that contributed to the observed significant burden. (XLSX 26 kb)
Supplementary Data Set 5: Genes in the 34 identified AMD locus regions.
Stated are all genes that overlap with the 34 AMD locus regions (defined by the 52 identified variants and their proxies (r2 ≥0.5, ±500 kb) as well as an indicator of whether this gene was also among the 368 genes in the narrow AMD locus regions (defined by 52 identified variants and their proxies (r2 ≥0.5, ±100 kb). (XLSX 110 kb)
Supplementary Data Set 6: Gene expression in retina and RPE/choroid for genes in 34 narrow AMD regions.
Gene expression in human retina tissue as well as retina pigment epithelium (RPE) or human choroid tissue for the 368 genes in 34 narrow AMD locus regions have been provided by two laboratories, the Weber laboratory and the Stambolian laboratory (Online Methods). A consensus rating was obtained by defining the gene as ‘expressed’ if it was expressed in both data sets. It was defined as ‘not expressed’ if it was found as not expressed in at least one laboratory and as ‘missing’ otherwise. (XLSX 34 kb)
Supplementary Data Set 7: Relevant eye phenotypes in genetic mouse models in 33 genes in the 34 narrow AMD regions.
We queried databases and conducted a literature search (Online Methods) for the 368 genes in the 34 narrow AMD regions and found relevant eye phenotypes for 33 of these genes. (XLSX 206 kb)
Supplementary Data Set 8
Approved and experimental drug targets among 368 genes in narrow AMD regions. We queried the DrugBank database (version 4.1; see URLs) to obtain overlap of the 368 genes in our 34 identified AMD regions with the drug target list. We found 31 of these genes to be a current drug target. (XLSX 46 kb)
Supplementary Data Set 9: Summary of biological and statistical evidence for genes in narrow AMD regions.
For all genes in the narrow AMD loci (Supplementary Data Set 5), we gathered evidence on whether the gene (i) was expressed in retina or RPE/choroid (Supplementary Data Set 6), (ii) had a retina or RPE/choroid phenotype in genetic mouse models (Supplementary Data Set 7), (iii) contained ≥1 variant in a 95% credible set by extending to ±50 kb around the gene (Supplementary Data Set 3) or (iv) had a significant rare variant burden (Table 2 and Supplementary File 4). Furthermore, we derived whether the credible set variants in the gene (±50 kb) contained (v) a protein-altering variant, (vi) a variant in the 5′ or 3′ UTR, (vii) another exonic coding variant or (viii) a putative promoter variant (Supplementary Data Set 3) or whether the gene (ix) was in an enriched molecular pathway (Supplementary Table 13) or (x) linked to an approved or experimental drug (Supplementary Data Set 8). (XLSX 56 kb)
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Fritsche, L., Igl, W., Bailey, J. et al. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. Nat Genet 48, 134–143 (2016). https://doi.org/10.1038/ng.3448
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DOI: https://doi.org/10.1038/ng.3448
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