Multi-ancestry and multi-trait genome-wide association meta-analyses inform clinical risk prediction for systemic lupus erythematosus

Chachrit Khunsriraksakul, Qinmengge Li, Havell Markus, Matthew T. Patrick, Renan Sauteraud, Daniel McGuire, Xingyan Wang, Chen Wang, Lida Wang, Siyuan Chen, Ganesh Shenoy, Bingshan Li, Xue Zhong, Nancy J. Olsen, Laura Carrel, Lam C. Tsoi, Bibo Jiang and Dajiang J. Liu ()
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Chachrit Khunsriraksakul: Pennsylvania State University College of Medicine
Qinmengge Li: University of Michigan Medical School
Havell Markus: Pennsylvania State University College of Medicine
Matthew T. Patrick: University of Michigan Medical School
Renan Sauteraud: Pennsylvania State University College of Medicine
Daniel McGuire: Pennsylvania State University College of Medicine
Xingyan Wang: Pennsylvania State University College of Medicine
Chen Wang: Pennsylvania State University College of Medicine
Lida Wang: Pennsylvania State University College of Medicine
Siyuan Chen: Pennsylvania State University College of Medicine
Ganesh Shenoy: Pennsylvania State University College of Medicine
Bingshan Li: Vanderbilt University
Xue Zhong: Vanderbilt University Medical Center
Nancy J. Olsen: Pennsylvania State University College of Medicine
Laura Carrel: Pennsylvania State University College of Medicine
Lam C. Tsoi: University of Michigan Medical School
Bibo Jiang: Pennsylvania State University College of Medicine
Dajiang J. Liu: Pennsylvania State University College of Medicine

Nature Communications, 2023, vol. 14, issue 1, 1-14

Abstract: Abstract Systemic lupus erythematosus is a heritable autoimmune disease that predominantly affects young women. To improve our understanding of genetic etiology, we conduct multi-ancestry and multi-trait meta-analysis of genome-wide association studies, encompassing 12 systemic lupus erythematosus cohorts from 3 different ancestries and 10 genetically correlated autoimmune diseases, and identify 16 novel loci. We also perform transcriptome-wide association studies, computational drug repurposing analysis, and cell type enrichment analysis. We discover putative drug classes, including a histone deacetylase inhibitor that could be repurposed to treat lupus. We also identify multiple cell types enriched with putative target genes, such as non-classical monocytes and B cells, which may be targeted for future therapeutics. Using this newly assembled result, we further construct polygenic risk score models and demonstrate that integrating polygenic risk score with clinical lab biomarkers improves the diagnostic accuracy of systemic lupus erythematosus using the Vanderbilt BioVU and Michigan Genomics Initiative biobanks.

Date: 2023
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DOI: 10.1038/s41467-023-36306-5

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