全基因组关联分析揭示了痛风的新致病途径*。

IF 31.7 1区 生物学 Q1 GENETICS & HEREDITY
Tanya J. Major, Riku Takei, Hirotaka Matsuo, Megan P. Leask, Nicholas A. Sumpter, Ruth K. Topless, Yuya Shirai, Wei Wang, Murray J. Cadzow, Amanda J. Phipps-Green, Zhiqiang Li, Aichang Ji, Marilyn E. Merriman, Emily Morice, Eric E. Kelley, Wen-Hua Wei, Sally P. A. McCormick, Matthew J. Bixley, Richard J. Reynolds, Kenneth G. Saag, Tayaza Fadason, Evgenia Golovina, Justin M. O’Sullivan, Lisa K. Stamp, Nicola Dalbeth, Abhishek Abhishek, Michael Doherty, Edward Roddy, Lennart T. H. Jacobsson, Meliha C. Kapetanovic, Olle Melander, Mariano Andrés, Fernando Pérez-Ruiz, Rosa J. Torres, Timothy Radstake, Timothy L. Jansen, Matthijs Janssen, Leo A. B. Joosten, Ruiqi Liu, Orsolya I. Gaal, Tania O. Crişan, Simona Rednic, Fina Kurreeman, Tom W. J. Huizinga, René Toes, Frédéric Lioté, Pascal Richette, Thomas Bardin, Hang Korng Ea, Tristan Pascart, Geraldine M. McCarthy, Laura Helbert, Blanka Stibůrková, Anne-K. Tausche, Till Uhlig, Véronique Vitart, Thibaud S. Boutin, Caroline Hayward, Philip L. Riches, Stuart H. Ralston, Archie Campbell, Thomas M. MacDonald, Akiyoshi Nakayama, Tappei Takada, Masahiro Nakatochi, Seiko Shimizu, Yusuke Kawamura, Yu Toyoda, Hirofumi Nakaoka, Ken Yamamoto, Keitaro Matsuo, Nariyoshi Shinomiya, Kimiyoshi Ichida, Chaeyoung Lee, Linda A. Bradbury, Matthew A. Brown, Philip C. Robinson, Russell R. C. Buchanan, Catherine L. Hill, Susan Lester, Malcolm D. Smith, Maureen Rischmueller, Hyon K. Choi, Eli A. Stahl, Jeff N. Miner, Daniel H. Solomon, Jing Cui, Kathleen M. Giacomini, Deanna J. Brackman, Eric M. Jorgenson, Hongbo Liu, Katalin Susztak, Suyash Shringarpure, Alexander So, Yukinori Okada, Changgui Li, Yongyong Shi, Tony R. Merriman
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引用次数: 0

摘要

痛风是一种慢性疾病,是在高尿酸血症的情况下对沉积的单钠尿酸盐结晶的先天性免疫反应引起的。在这里,我们通过一项对 260 万人(包括 120,295 名痛风患者)进行的全基因组关联研究(GWAS),深入探讨了痛风中鲜为人知的炎症成分的分子机制。我们发现了 377 个基因位点和 410 个基因独立信号(149 个以前未报道过的尿酸盐和痛风基因位点)。此外,我们还发现了 65 个在尿酸盐中有信号的位点(来自 630,117 人的 GWAS),但在痛风中没有信号。一个优先排序方案确定了痛风炎症过程中的候选基因,包括参与表观遗传重塑、细胞渗透压和 NOD 样受体蛋白 3 (NLRP3) 炎症小体活性调节的基因。孟德尔随机分析提供了证据,证明具有不确定潜能的克隆造血在痛风中起着因果作用。我们的研究确定了痛风炎症发病机制中适合后续研究的候选基因和分子过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A genome-wide association analysis reveals new pathogenic pathways in gout*

A genome-wide association analysis reveals new pathogenic pathways in gout*

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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来源期刊
Nature genetics
Nature genetics 生物-遗传学
CiteScore
43.00
自引率
2.60%
发文量
241
审稿时长
3 months
期刊介绍: Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation. Integrative genetic topics comprise, but are not limited to: -Genes in the pathology of human disease -Molecular analysis of simple and complex genetic traits -Cancer genetics -Agricultural genomics -Developmental genetics -Regulatory variation in gene expression -Strategies and technologies for extracting function from genomic data -Pharmacological genomics -Genome evolution
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