Large-scale whole-exome sequencing association studies identify rare functional variants influencing serum urate levels

Adrienne Tin, Yong Li, Jennifer A. Brody, Teresa Nutile, Audrey Y. Chu, Jennifer E. Huffman, Qiong Yang, Ming Huei Chen, Cassianne Robinson-Cohen, Aurélien Macé, Jun Liu, Ayşe Demirkan, Rossella Sorice, Sanaz Sedaghat, Melody Swen, Bing Yu, Sahar Ghasemi, Alexanda Teumer, Peter Vollenweider, Marina CiulloMeng Li, André G. Uitterlinden, Robert Kraaij, Najaf Amin, Jeroen van Rooij, Zoltán Kutalik, Abbas Dehghan, Barbara McKnight, Cornelia M. van Duijn, Alanna Morrison, Bruce M. Psaty, Eric Boerwinkle, Caroline S. Fox, Owen M. Woodward, Anna Köttgen

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Elevated serum urate levels can cause gout, an excruciating disease with suboptimal treatment. Previous GWAS identified common variants with modest effects on serum urate. Here we report large-scale whole-exome sequencing association studies of serum urate and kidney function among ≤19,517 European ancestry and African-American individuals. We identify aggregate associations of low-frequency damaging variants in the urate transporters SLC22A12 (URAT1; p = 1.3 × 10−56) and SLC2A9 (p = 4.5 × 10−7). Gout risk in rare SLC22A12 variant carriers is halved (OR = 0.5, p = 4.9 × 10−3). Selected rare variants in SLC22A12 are validated in transport studies, confirming three as loss-of-function (R325W, R405C, and T467M) and illustrating the therapeutic potential of the new URAT1-blocker lesinurad. In SLC2A9, mapping of rare variants of large effects onto the predicted protein structure reveals new residues that may affect urate binding. These findings provide new insights into the genetic architecture of serum urate, and highlight molecular targets in SLC22A12 and SLC2A9 for lowering serum urate and preventing gout.

Original languageEnglish (US)
Article number4228
JournalNature communications
Volume9
Issue number1
DOIs
StatePublished - Dec 1 2018
Externally publishedYes

Bibliographical note

Funding Information:
The authors gratefully acknowledge the resources generated by the NHLBI GO Exome Sequencing Project. A full list of Project members and funding information is found in Supplementary Note 3. Grants supporting individual investigators are listed below. Information about funding of the contributing parent studies is included in Supplementary Note 3. The work of Y.L. and A.K. was supported by KO 3598/4-1, and the work of A.K. additionally by KO 3598/3-1, CRC 1140, and CRC 992 (all German Research Foundation). The work of O.M.W. was supported by NIDDK R01DK114091 and American Heart SDG grant 14SDG18060004. Z.K. received financial support from the Leenaards Foundation, the Swiss Institute of Bioinformatics, and the Swiss National Science Foundation (31003A-169929) and SystemsX.ch (51RTP0_151019). A.D. is supported by a Veni grant (2015) from ZonMw. A.D., J.L., and C.M.vD. have used exchange grants from Personalized pREvention of Chronic Diseases consortium (PRECeDI) (H2020-MSCA-RISE-2014). The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.

Publisher Copyright:
© 2018, The Author(s).

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