TY - JOUR
T1 - Multi-ancestry and multi-trait genome-wide association meta-analyses inform clinical risk prediction for systemic lupus erythematosus
AU - Khunsriraksakul, Chachrit
AU - Li, Qinmengge
AU - Markus, Havell
AU - Patrick, Matthew T.
AU - Sauteraud, Renan
AU - McGuire, Daniel
AU - Wang, Xingyan
AU - Wang, Chen
AU - Wang, Lida
AU - Chen, Siyuan
AU - Shenoy, Ganesh
AU - Li, Bingshan
AU - Zhong, Xue
AU - Olsen, Nancy J.
AU - Carrel, Laura
AU - Tsoi, Lam C.
AU - Jiang, Bibo
AU - Liu, Dajiang J.
N1 - Funding Information:
This work was supported by the National Institutes of Health grants R01HG008983, R56HG011035, R01HG011035, R01GM126479, R21AI160138, R03OD032630, R01AI174108, R56HG012358, T32GM118294, T32LM012415, and U01AR071077. This work was also funded in part by the Penn State College of Medicine’s Artificial Intelligence and Biomedical Informatics (AIBI) Program in the Strategic Plan, the Lupus Research Alliance, CURE funds from the Pennsylvania Department of Health, and by generous support from Robert and Sevia Finkelstein. BioVU acknowledgment: The datasets used for part of the PRS analysis were obtained from Vanderbilt University Medical Center’s BioVU, which is supported by numerous sources: institutional funding, private agencies, and federal grants. These include the NIH funded Shared Instrumentation Grant S10OD017985 and S10RR025141; and CTSA grants UL1TR002243, UL1TR000445, and UL1RR024975. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. Genomic data are also supported by investigator-led projects that include U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962, R01HD074711; and additional funding sources listed at https://victr.vumc.org/biovu-funding/.
Funding Information:
This work was supported by the National Institutes of Health grants R01HG008983, R56HG011035, R01HG011035, R01GM126479, R21AI160138, R03OD032630, R01AI174108, R56HG012358, T32GM118294, T32LM012415, and U01AR071077. This work was also funded in part by the Penn State College of Medicine’s Artificial Intelligence and Biomedical Informatics (AIBI) Program in the Strategic Plan, the Lupus Research Alliance, CURE funds from the Pennsylvania Department of Health, and by generous support from Robert and Sevia Finkelstein. BioVU acknowledgment: The datasets used for part of the PRS analysis were obtained from Vanderbilt University Medical Center’s BioVU, which is supported by numerous sources: institutional funding, private agencies, and federal grants. These include the NIH funded Shared Instrumentation Grant S10OD017985 and S10RR025141; and CTSA grants UL1TR002243, UL1TR000445, and UL1RR024975. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. Genomic data are also supported by investigator-led projects that include U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962, R01HD074711; and additional funding sources listed at https://victr.vumc.org/biovu-funding/ .
Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - 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.
AB - 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.
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U2 - 10.1038/s41467-023-36306-5
DO - 10.1038/s41467-023-36306-5
M3 - Article
C2 - 36750564
AN - SCOPUS:85147562363
SN - 2041-1723
VL - 14
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 668
ER -