A landscape of gene expression regulation for synovium in arthritis

Feng Jiang, Shou-Ye Hu, Wen Tian, Nai-Ning Wang, Ning Yang, Shan-Shan Dong, Hui-Miao Song, Da-Jin Zhang, Hui-Wu Gao, Chen Wang, Hao Wu, Chang-Yi He, Dong-Li Zhu, Xiao-Feng Chen, Yan Guo, Zhi Yang () and Tie-Lin Yang ()
Additional contact information
Feng Jiang: Xi’an Jiaotong University
Shou-Ye Hu: Xi’an Jiaotong University
Wen Tian: Xi’an Jiaotong University
Nai-Ning Wang: Xi’an Jiaotong University
Ning Yang: Xi’an Jiaotong University
Shan-Shan Dong: Xi’an Jiaotong University
Hui-Miao Song: Xi’an Jiaotong University
Da-Jin Zhang: Xi’an Jiaotong University
Hui-Wu Gao: Xi’an Jiaotong University
Chen Wang: Xi’an Jiaotong University
Hao Wu: Xi’an Jiaotong University
Chang-Yi He: Xi’an Jiaotong University
Dong-Li Zhu: Xi’an Jiaotong University
Xiao-Feng Chen: Xi’an Jiaotong University
Yan Guo: Xi’an Jiaotong University
Zhi Yang: Xi’an Jiaotong University
Tie-Lin Yang: Xi’an Jiaotong University

Nature Communications, 2024, vol. 15, issue 1, 1-16

Abstract: Abstract The synovium is an important component of any synovial joint and is the major target tissue of inflammatory arthritis. However, the multi-omics landscape of synovium required for functional inference is absent from large-scale resources. Here we integrate genomics with transcriptomics and chromatin accessibility features of human synovium in up to 245 arthritic patients, to characterize the landscape of genetic regulation on gene expression and the regulatory mechanisms mediating arthritic diseases predisposition. We identify 4765 independent primary and 616 secondary cis-expression quantitative trait loci (cis-eQTLs) in the synovium and find that the eQTLs with multiple independent signals have stronger effects and heritability than single independent eQTLs. Integration of genome-wide association studies (GWASs) and eQTLs identifies 84 arthritis related genes, revealing 38 novel genes which have not been reported by previous studies using eQTL data from the GTEx project or immune cells. We further develop a method called eQTac to identify variants that could affect gene expression by affecting chromatin accessibility and identify 1517 regions with potential regulatory function of chromatin accessibility. Altogether, our study provides a comprehensive synovium multi-omics resource for arthritic diseases and gains new insights into the regulation of gene expression.

Date: 2024
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DOI: 10.1038/s41467-024-45652-x

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