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Meta-Analysis
. 2021 Feb 24;12(1):1258.
doi: 10.1038/s41467-020-20851-4.

Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries

Puya Gharahkhani #  1 , Eric Jorgenson #  2 , Pirro Hysi #  3 , Anthony P Khawaja #  4   5 , Sarah Pendergrass #  6 , Xikun Han  7 , Jue Sheng Ong  7 , Alex W Hewitt  8   9 , Ayellet V Segrè  10 , John M Rouhana  10 , Andrew R Hamel  10 , Robert P Igo Jr  11 , Helene Choquet  2 , Ayub Qassim  12 , Navya S Josyula  13 , Jessica N Cooke Bailey  11   14 , Pieter W M Bonnemaijer  15   16   17 , Adriana Iglesias  15   16   18 , Owen M Siggs  12 , Terri L Young  19 , Veronique Vitart  20 , Alberta A H J Thiadens  15   16 , Juha Karjalainen  21   22   23 , Steffen Uebe  24 , Ronald B Melles  25 , K Saidas Nair  26 , Robert Luben  5 , Mark Simcoe  3   27   28 , Nishani Amersinghe  29 , Angela J Cree  30 , Rene Hohn  31   32 , Alicia Poplawski  33 , Li Jia Chen  34 , Shi-Song Rong  10   34 , Tin Aung  35   36   37 , Eranga Nishanthie Vithana  35   38 ; NEIGHBORHOOD consortium; ANZRAG consortium; Biobank Japan project; FinnGen study; UK Biobank Eye and Vision Consortium; GIGA study group; 23 and Me Research Team; Gen Tamiya  39   40 , Yukihiro Shiga  41 , Masayuki Yamamoto  39 , Toru Nakazawa  41   42   43   44 , Hannah Currant  45 , Ewan Birney  45 , Xin Wang  46 , Adam Auton  46 , Michelle K Lupton  7 , Nicholas G Martin  7 , Adeyinka Ashaye  47 , Olusola Olawoye  47 , Susan E Williams  48 , Stephen Akafo  49 , Michele Ramsay  50 , Kazuki Hashimoto  41 , Yoichiro Kamatani  51   52 , Masato Akiyama  51   53 , Yukihide Momozawa  54 , Paul J Foster  55   56 , Peng T Khaw  55   56 , James E Morgan  57 , Nicholas G Strouthidis  55   56 , Peter Kraft  58 , Jae H Kang  59 , Chi Pui Pang  34 , Francesca Pasutto  24 , Paul Mitchell  60 , Andrew J Lotery  29   30 , Aarno Palotie  61   62   63 , Cornelia van Duijn  16   64 , Jonathan L Haines  11   14 , Chris Hammond  3 , Louis R Pasquale  65 , Caroline C W Klaver  15   16   66   67 , Michael Hauser  68   69   70   71 , Chiea Chuen Khor  72 , David A Mackey  8   9   73 , Michiaki Kubo  74 , Ching-Yu Cheng  35   36   37 , Jamie E Craig  75 , Stuart MacGregor  7 , Janey L Wiggs  10
Collaborators, Affiliations
Meta-Analysis

Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries

Puya Gharahkhani et al. Nat Commun. .

Abstract

Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates.

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Conflict of interest statement

X.W. and A.A. are employed by and hold stock or stock options in 23andMe, Inc. J.W. is a consultant for Allergan, Editas, Maze, Regenxbio and has received sponsored research support from Aerpio Pharmaceuticals Inc. L.P. is a consultant for Eyenovia, Bausch + Lomb, Verily, and Nicox. T.L.Y. serves as a consultant to Aerpio Pharmaceuticals, Inc. A.P.K. is a consultant to Aerie, Allergan, Google Health, Novartis, Reichert, Santen and Thea. All remaining authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Study design.
This figure summarizes the four stages of this study, as well as the data resources and main analyses/results for each stage.
Fig. 2
Fig. 2. Correlation of SNP effect estimates between the European POAG meta-analysis and the replication dataset.
The x-axis shows effect estimates in log(OR) scale for the independent genome-wide significant loci obtained from the meta-analysis of POAG in Europeans (16,677 POAG cases vs. 199,580 controls). The y-axis shows the effect estimates in log(OR) scale for the same SNPs obtained from meta-analysis of the following three GWAS data: glaucoma self-reports in UKBB, POAG in Asians, and POAG in Africans (the overall sample size of 17,502 cases and 149,741 controls). Red dots are the previously identified risk loci and blue dots are the previously unreported risk loci identified in this study. Horizontal gray bars on each dot represent the 95% confidence intervals (CIs; mean values + / − 1.96*SEM) for the effect estimates in Europeans (from the GWAS meta-analysis of 16,677 POAG cases vs. 199,580 controls), and vertical gray bars shows the 95% CIs in the replication dataset (from the GWAS meta-analysis of 17,502 POAG cases vs. 149,741 controls). The blue line is the linear regression line best fitting the data. The shaded area shows the 95% CIs on the repression line. UKBB UK Biobank, POAG primary open-angle glaucoma, OR odds ratio.
Fig. 3
Fig. 3. Manhattan plots for the cross-ancestry meta-analysis.
Each dot represents a SNP, the x-axis shows the chromosomes where each SNP is located, and the y-axis shows −log10 P-value of the association of each SNP with POAG in the cross-ancestry meta-analysis (34,179 cases vs. 349,321 controls). The red horizontal line shows the genome-wide significant threshold (P-value = 5e-8; −log10 P-value = 7.30). The nearest gene to the most significant SNP in each locus has been labeled.
Fig. 4
Fig. 4. Association of the POAG risk loci with IOP and VCDR.
The x-axes show POAG effect estimates in log(OR) scale for the independent genome-wide significant loci obtained from the cross-ancestry meta-analysis. The y-axes show the effect estimates for the same SNPs obtained from the meta-analysis of IOP in UKBB + IGGC (mmHg scale; a) and the meta-analysis of VCDR in UKBB + IGGC (b). Blue line shows the regression line for IOP (a) and VCDR loci (b). Orange dots represent SNPs having P < 0.05 for IOP, purple dots P < 0.05 for VCDR, green dots P < 0.05 for both IOP and VCDR, and blue dots P > 0.05 for both IOP and VCDR. Horizontal gray bars on each dot represent the 95% confidence intervals (CIs; mean values + / −  1.96*SEM) for the POAG effect estimates (34,179 cases vs. 349,321 controls), and vertical gray bars shows the 95% CIs for IOP (N = 133,492; a) and VCDR (N = 90,939; b). The shaded area shows the 95% CIs on the repression line. Although none of the blue dots show an expected trend of association with IOP in a (their 95% CIs do not overlap with the regression line), the majority of them show a trend of association for VCDR in b. UKBB UK Biobank, IGGC International Glaucoma Genetics Consortium, IOP intraocular pressure, VCDR, vertical cup-to-disc ratio, POAG primary open-angle glaucoma, OR odds ratio.
See this image and copyright information in PMC

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