Abstract
Gout is a chronic disease that is caused by an innate immune response to deposited monosodium urate crystals in the setting of hyperuricemia. Here, we provide insights into the molecular mechanism of the poorly understood inflammatory component of gout from a genome-wide association study (GWAS) of 2.6 million people, including 120,295 people with prevalent gout. We detected 377 loci and 410 genetically independent signals (149 previously unreported loci in urate and gout). An additional 65 loci with signals in urate (from a GWAS of 630,117 individuals) but not gout were identified. A prioritization scheme identified candidate genes in the inflammatory process of gout, including genes involved in epigenetic remodeling, cell osmolarity and regulation of NOD-like receptor protein 3 (NLRP3) inflammasome activity. Mendelian randomization analysis provided evidence for a causal role of clonal hematopoiesis of indeterminate potential in gout. Our study identifies candidate genes and molecular processes in the inflammatory pathogenesis of gout suitable for follow-up studies.
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Data availability
The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. Datasets will be made available at no cost for academic use (https://research.23andme.com/collaborate/#dataset-access/). Supplementary Table 40 contains summary statistics from 9,980 independently associated SNPs. For the full European GWAS, we took all SNPs at P < 1 × 10−4 and used the UK Biobank as the LD reference to clump at R2 < 0.01 within windows of 5 Mb from each lead SNP. This resulted in 2,480 SNPs. For each of the African, East Asian and Latinx GWAS, we removed the SLC2A9 and ABCG2 regions (chr4:9.32 Mb–11.21 Mb and chr4:86.79 Mb–90.23 Mb, respectively) and then took the 2,500 most significant remaining SNPs for each. Summary statistics from meta-analyses without the 23andMe dataset (the four ancestries, each for men only, women only and combined sexes) are available at the GWAS Catalog (https://www.ebi.ac.uk, dataset accessions GCST90428594–GCST90428605; https://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90428001-GCST90429000). The 1000 Genomes Project Phase 3 data were downloaded from http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/; information on the UK Biobank cohort can be viewed at https://www.ukbiobank.ac.uk/; the GWAS Catalog is available at https://www.ebi.ac.uk/gwas/; GTEx data were downloaded from https://gtexportal.org/home/datasets; variant information from dbSNP was downloaded from https://ftp.ncbi.nih.gov/snp/latest_release/VCF/GCF_000001405.25.gz; conversion-unstable positions used for SLALOM were downloaded from https://github.com/cathaloruaidh/genomeBuildConversion; GoDMC meQTL data were downloaded from http://mqtldb.godmc.org.uk/downloads; RELI transcription factor ChIP–seq data were from https://tf.cchmc.org/external/RELI/RELI_public_data.tar.bz2; baseline LD score version 1.1, cell type-specific and cell type group annotations were downloaded from https://alkesgroup.broadinstitute.org/LDSCORE/; functional annotations for PAINTOR were downloaded from https://ucla.box.com/s/x47apvgv51au1rlmuat8m4zdjhcniv2d; LDSC summary statistics of UK Biobank traits from the round 2 analysis were downloaded from https://nealelab.github.io/UKBB_ldsc/downloads.html; ABC enhancer–gene connection data were downloaded from ftp://ftp.broadinstitute.org/outgoing/lincRNA/ABC/AllPredictions.AvgHiC.ABC0.015.minus150.ForABCPaperV3.txt.gz; FATHMM scores for noncoding variants were obtained from http://fathmm.biocompute.org.uk/; ImmuNexUT eQTL data were downloaded from https://humandbs.biosciencedbc.jp/en/hum0214-v6; OneK1K eQTL data were downloaded from https://onek1k.s3.ap-southeast-2.amazonaws.com/onek1k_eqtl_dataset.zip; CHIP summary statistics were downloaded from https://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90102001-GCST90103000/; the Susztak Kidney Biobank is available at https://susztaklab.com/; a list of differentially expressed genes in stimulated monocytes can be obtained from Table S2 in the original paper128; GWAS data for white blood cell traits used in the gene prioritization analysis are available at https://www.ebi.ac.uk/gwas/; FANTOM5 TSS data were downloaded from https://fantom.gsc.riken.jp/5/datafiles/phase1.3/extra/TSS_classifier/; HaploReg is available at https://pubs.broadinstitute.org/mammals/haploreg/haploreg.php; GeneHancer tracks were accessed through USCS; KEGG, Reactome and GO pathway analyses were conducted at https://david.ncifcrf.gov/; and transcription factor-binding site enrichment was carried out at https://maayanlab.cloud/Enrichr/.
Code availability
Code for the main analyses is available at https://github.com/MerrimanLab/Gout_GWAS_Code, permanently deposited at Zenodo (https://doi.org/10.5281/zenodo.13350995)129.
Change history
05 November 2024
A Correction to this paper has been published: https://doi.org/10.1038/s41588-024-02017-w
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Acknowledgements
This article is dedicated to Philip C. Robinson. We thank the research participants and employees of 23andMe for making this work possible. The following members of the 23andMe Research Team contributed to this study: S. Aslibekyan, A. Auton, E. Babalola, R.K. Bell, J. Bielenberg, K. Bryc, E. Bullis, D. Coker, G. Cuellar Partida, D. Dhamija, S. Das, S.L. Elson, N. Eriksson, T. Filshtein, A. Fitch, K. Fletez-Brant, P. Fontanillas, W. Freyman, J.M. Granka, K. Heilbron, A. Hernandez, B. Hicks, D.A. Hinds, E.M. Jewett, Y. Jiang, K. Kukar, A. Kwong, K.-H. Lin, B.A. Llamas, M. Lowe, J.C. McCreight, M.H. McIntyre, S.J. Micheletti, M.E. Moreno, P. Nandakumar, D.T. Nguyen, E.S. Noblin, J. O’Connell, A.A. Petrakovitz, G.D. Poznik, A. Reynoso, M. Schumacher, A.J. Shastri, J.F. Shelton, J. Shi, S. Shringarpure, Q.J. Su, S.A. Tat, C.T. Tchakouté, V. Tran, J.Y. Tung, X. Wang, W.W., C.H. Weldon, P. Wilton and C.D. Wong. We thank the participants and staff of the UK Biobank study for their important contribution. This research has been conducted using the UK Biobank resource under application number 12611. We acknowledge the participants and investigators of the FinnGen study. The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health and by the NCI, the NHGRI, the NHLBI, the NIDA, the NIMH and the NINDS. This study was supported by grants from the Health Research Council of New Zealand to T.R.M. (08/075, 11/1075, 14/527), Arthritis New Zealand to T.R.M., Lottery Health New Zealand to T.R.M., JSPS KAKENHI (grant numbers 20H00566, 21KK0173, 17H04128, 22H00476, 20K23152, 21H03350, 17015018, 221S0001, 2221S0002, 16H06279 (PAGS), 16H06277, 22H04923 (CoBiA), 20H00568), AMED (JP21gm4010006, JP22km0405211, JP22ek0410075, JP22km0405217, JP22ek0109594), JST Moonshot R&D (JPMJMS2021, JPMJMS2024), the Takeda Science Foundation, the Bioinformatics Initiative of Osaka University Graduate School of Medicine, the Gout and Uric Acid Foundation of Japan and the Ministry of Defense of Japan, the National Natural Science Foundation of China (82220108015) and the National Key Research and Development Program of China (2022YFE0107600, 2022YFC2503300). Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006) and is currently supported by the Wellcome Trust (216767/Z/19/Z). Genotyping of the GS:SFHS samples was funded by the Medical Research Council UK, the Wellcome Trust (Wellcome Trust Strategic Award ‘Stratifying Resilience and Depression Longitudinally’ (STRADL), reference 104036/Z/14/Z), and analysis was supported by MRC University Unit core grant MC_UU_00007/10 (QTL in Health and Disease program). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
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T.J.M., R. Takei, M.P.L., N.A.S., R.K.T. and T.R.M. wrote the manuscript. T.J.M., R.T., H.M., M.P.L., N.A.S., R.K.T., W.-H.W., H.K.C., E.A.S., A.S., Y.O., C. Li, Y. Shi and T.R.M. designed the study. H.M., T.M.M., W.W., H.K.C., J.N.M., D.H.S., E.M.J., C. Lee, C. Li and T.R.M. managed an individual contributing study. H.M., M.P.L., W.W., M.J.C., A.J.P.-G., E.M., J.M.O’S., L.K.S., N.D., A.A., M.D., E.R., L.T.H.J., M.A., R.J.T., T.R., T.L.J., M.J., L.A.B.J., R. Toes, F.L., H.K.E., T.P., G.M.M., B.S., T.U., V.V., P.L.R., S.H.R., C. Lee, P.C.R., J.C., H.L., K.S. and S. Shringarpure critically reviewed the manuscript. T.J.M., R. Takei, M.P.L., N.A.S., R.K.T., Y. Shirai, W.W., M.J.C., A.J.P.-G., Z.L., A.J., M.E.M., E.M., E.E.K., W.-H.W., M.J.B., R.J.R., T.F., E.G., J.M.O’S., L.A.B.J., R.L., O.I.G., T.O.C., V.V., T.S.B., C.H., S.H.R., A.C., A.N., Y.K., Y.T., C. Lee, M.A.B., E.A.S., J.C., K.M.G., D.J.B., E.M.J., H.L., K.S., S. Shringarpure, Y.O., Y. Shi and T.R.M. carried out data acquisition, statistical methods and bioinformatic analyses. H.M., M.E.M., S.P.A.M., R.J.R., K.G.S., L.K.S., N.D., A.A., M.D., E.R., L.T.H.J., M.C.K., O.M., M.A., F.P.-R., R.J.T., T.R., T.L.J., M.J., T.O.C., S.R., F.K., T.W.J.H., R. Toes, F.L., P.R., T.B., H.K.E., T.P., G.M.M., L.H., B.S., A.-K.T., T.U., S.H.R., T.M.M., T.T., M.N., S. Shimizu, H.N., K.Y., K.M., N.S., K.I., C. Lee, L.A.B., M.A.B., P.C.R., R.R.C.B., C.L.H., S.L., M.D.S., M.R., J.N.M., D.H.S., E.M.J., K.S., A.S., Y.O., C. Li and T.R.M. recruited participants for the study.
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Extended data
Extended Data Fig. 1 Manhattan plots of full (combined sexes), male, and female African ancestry analysis.
The bars at the top of the Manhattan plots indicate where the genome-wide significant variants (P ≤ 5 × 10−8) are located. The red horizontal line indicates the P = 5 × 10−8 significance threshold.
Extended Data Fig. 2 Manhattan plots of full (combined sexes), male, and female East Asian ancestry analysis.
Manhattan plots show variants with -log10P ≤ 100 (loci that contain variants with -log10P > 100 are indicated with a triangle mark). The bars at the top of the Manhattan plots indicate where the genome-wide significant variants (P ≤ 5 × 10−8) are located. The red horizontal line indicates the P = 5 × 10−8 significance threshold.
Extended Data Fig. 3 Manhattan plots of full (combined sexes), male, and female European ancestry analysis.
Manhattan plots show variants with -log10P ≤ 100 (loci that contain variants with -log10P > 100 are indicated with a triangle mark). The bars at the top of the Manhattan plots indicate where the genome-wide significant variants (P ≤ 5 × 10−8) are located. The red horizontal line indicates the P = 5 × 10−8 significance threshold.
Extended Data Fig. 4 Manhattan plots of full (combined sexes), male, and female Latinx ancestry analysis.
Manhattan plots show variants with -log10P ≤ 100 (loci that contain variants with -log10P > 100 are indicated with a triangle mark). The bars at the top of the Manhattan plots indicate where the genome-wide significant variants (P ≤ 5 × 10−8) are located.
Extended Data Fig. 5 Manhattan plots of full (combined sexes), male, and female trans-ancestry meta-analysis.
Manhattan plots show variants with log10BF ≤ 100 (loci that contain variants with log10BF > 100 are indicated with a triangle mark). The bars at the top of the Manhattan plots indicate where the genome-wide significant variants (log10BF ≥ 6) are located. The red horizontal line indicates the log10BF = 6 significance threshold.
Extended Data Fig. 6 Bar plot of cell-type group enrichment of African, East Asian, European, and Latino gout GWAS for full, male-, and female-specific analyses.
Red dashed line: conservative p-value threshold of 4.2 × 10−4; Blue dashed line: p-value threshold of 5.0 × 10−3.
Extended Data Fig. 7 Bar plot of cell-type specific enrichment of African, East Asian, European, and Latino gout GWAS for full, male-, female-specific analyses.
Red dashed line: conservative p-value threshold of 1.9 × 10−5; Blue dashed line: p-value threshold of 2.2 × 10−4. Large dots: cell types with FDR-adjusted p-value ≤ 0.05.
Extended Data Fig. 8 Functional and pathway enrichment analyses of gout candidate genes.
The DAVID database was used to identify GO Biological Function term, KEGG and REACTOME pathways enriched in the gout GWAS dataset. Significance (FDR) of the enrichment is denoted on the x-axis, size of the circle denotes number of genes contributing to the enrichment term.
Extended Data Fig. 9 DGAT2: Example of genome organization at a candidate immune-priming lncRNA locus.
ENCODE H3K4me3 signal track from CD14+ monocytes indicates enrichment at the promoters of DGAT2, the lncRNA RP11-535A19.2 and UVRAG. ENCODE CTCF signal track from neutrophils and CD14+ monocytes indicates CTCF binding at rs11236533. Genehancer connections are in green and illustrate physical connections (Hi-C) between rs11236533 which disrupts a CTCF site and additional maximally-associated SNPs at two Genehancer regulatory elements. Red and blue dots indicate the CpG locations that are associated with co-localized meQTL and the color denotes direction of effect of the gout risk allele (red = higher methylation, blue = lower methylation). White lollipops represent maximally-associated SNPs at the locus within predicted cis regulatory elements.
Supplementary information
Supplementary Information
Supplementary Note and Figs. 1–7
Supplementary Tables
Supplementary Tables 1–42
Supplementary Data 1
LocusZoom plots of all ancestry-specific and trans-ancestral loci detected in the gout GWAS and of all loci detected in the sex-specific gout GWAS.
Supplementary Data 2
LocusZoom plots of all loci that demonstrated a signal of association with gout but not urate.
Supplementary Data 3
LocusZoom plots of all loci that demonstrated a signal of association with urate but not gout.
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Major, T.J., Takei, R., Matsuo, H. et al. A genome-wide association analysis reveals new pathogenic pathways in gout. Nat Genet 56, 2392–2406 (2024). https://doi.org/10.1038/s41588-024-01921-5
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DOI: https://doi.org/10.1038/s41588-024-01921-5
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