Trans-ancestry GWAS identifies 59 loci and improves risk prediction and fine-mapping for kidney stone disease

Xi Cao, Minghui Jiang, Yunlong Guan, Si Li, Chen Duan, Yan Gong, Yifan Kong, Zhonghe Shao, Hongji Wu, Xiangyang Yao, Bo Li, Miao Wang (), Hua Xu () and Xingjie Hao ()
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Xi Cao: Huazhong University of Science and Technology
Minghui Jiang: Capital Medical University; China National Clinical Research Center for Neurological Diseases
Yunlong Guan: Huazhong University of Science and Technology
Si Li: Huazhong University of Science and Technology
Chen Duan: Zhongnan Hospital of Wuhan University
Yan Gong: Zhongnan Hospital of Wuhan University
Yifan Kong: Huazhong University of Science and Technology
Zhonghe Shao: Huazhong University of Science and Technology
Hongji Wu: Huazhong University of Science and Technology
Xiangyang Yao: Zhongnan Hospital of Wuhan University
Bo Li: Zhongnan Hospital of Wuhan University
Miao Wang: Huazhong University of Science and Technology
Hua Xu: Zhongnan Hospital of Wuhan University
Xingjie Hao: Huazhong University of Science and Technology

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract Kidney stone disease is a multifactorial disease with increasing incidence worldwide. Trans-ancestry GWAS has become a popular strategy to dissect genetic structure of complex traits. Here, we conduct a large trans-ancestry GWAS meta-analysis on kidney stone disease with 31,715 cases and 943,655 controls in European and East Asian populations. We identify 59 kidney stone disease susceptibility loci, including 13 novel loci and show similar effects across populations. Using fine-mapping, we detect 1612 variants at these loci, and pinpoint 25 causal signals with a posterior inclusion probability >0.5 among them. At a novel locus, we pinpoint TRIOBP gene and discuss its potential link to kidney stone disease. We show that a cross-population polygenic risk score, PRS-CSxEAS&EUR, exhibits superior predictive performance for kidney stone disease than other polygenic risk scores constructed in our study. Relative to individuals in the third quintile of PRS-CSxEAS&EUR, those in the lowest and highest quintiles exhibit distinct kidney stone disease risks with odds ratios of 0.57 (0.51–0.63) and 1.83 (1.68–1.98), respectively. Our results suggest that kidney stone disease patients with higher polygenic risk scores are younger at onset. In summary, our study advances the understanding of kidney stone disease genetic architecture and improves its genetic predictability.

Date: 2025
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DOI: 10.1038/s41467-025-58782-7

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