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已发表论文
系统性硬化症新型生物标志物及潜在治疗靶点的鉴定：血浆蛋白质组全范围孟德尔随机化与转录组的综合分析
Authors Li H, Li Q, Chen X, Mo L , Wang Y, Liu X , Wang X, Qu Z, Wang J , Li Y
Received 23 September 2025
Accepted for publication 3 December 2025
Published 17 December 2025 Volume 2025:18 Pages 17561—17588
DOI https://doi.org/10.2147/JIR.S561740
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Anish R. Maskey
Hanchao Li,1 Qian Li,1 Xiaoxin Chen,2 Lingfei Mo,1 Yulu Wang,2 Xinyi Liu,1,2 Xiaohao Wang,3 Zechao Qu,3 Jing Wang,1 Yuanyuan Li1
1Department of Rheumatology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China; 2Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China; 3Department of Spine Surgery, Hong Hui Hospital, Xi’an Jiaotong University, Xi’an, People’s Republic of China
Correspondence: Yuanyuan Li, Department of Rheumatology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, 710061, People’s Republic of China, Email wudui220@163.com Jing Wang, Department of Rheumatology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, 710061, People’s Republic of China, Email kidip@163.com
Background: Systemic sclerosis (SSc) is a complex autoimmune connective tissue disease. This study aimed to identify novel biomarkers for SSc through an integrated analysis of plasma proteome-wide Mendelian randomization (MR) and transcriptome, as well as to explore the potential mechanisms.
Methods: The data used were obtained from public databases. Initially, key plasma proteins causally associated with SSc were identified through a two-sample MR analysis. Subsequently, based on the key diseases related to both key plasma proteins (genes) and key drugs targeting these proteins (genes), phenotype scanning was conducted to predict potential adverse side effects of key plasma proteins (genes). Single-cell RNA sequencing (scRNA-seq) analysis was performed to identify key cell types in GSE138669 dataset. Differentially expressed genes (DEGs) within key cell types in SSc were intersected with genes encoding key plasma proteins to obtain candidate biomarkers, whose functions were subsequently explored. By analyzing candidate biomarker expression in GSE138669 and GSE181549 datasets, the biomarkers were identified. Further exploration included regulatory network, cellular heterogeneity, and cell trajectory analyses.
Results: Initially, 106 plasma proteins (corresponding to 104 genes) were identified. It was revealed that targeting 12 key plasma proteins (like CD40LG) for treating SSc might lead to side effects related to specific key diseases (like mesothelioma). After recognizing epithelial cells and fibroblasts as key cell types, 8 candidate biomarkers associated with pathways like “proteasome” were identified. Notably, CCL19 and LOXL2 were identified as biomarkers, which exhibited elevated expression in SSc. Regulatory elements such as FOXL1 and hsa-miR-5001-5p were predicted to target biomarkers. Remarkably, differentiation stages of key cell type with heterogeneity and the biomarker expression patterns across these stages might be associated with SSc progression.
Conclusion: CCL19 and LOXL2 were identified as novel biomarkers for SSc, providing insights into the exploration of the disease’s pathogenesis and the development of new therapeutic targets.
Keywords: systemic sclerosis, mendelian randomization, plasma proteome, biomarker, single-cell RNA sequencing
1Department of Rheumatology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China; 2Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China; 3Department of Spine Surgery, Hong Hui Hospital, Xi’an Jiaotong University, Xi’an, People’s Republic of China
Correspondence: Yuanyuan Li, Department of Rheumatology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, 710061, People’s Republic of China, Email wudui220@163.com Jing Wang, Department of Rheumatology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, 710061, People’s Republic of China, Email kidip@163.com
Background: Systemic sclerosis (SSc) is a complex autoimmune connective tissue disease. This study aimed to identify novel biomarkers for SSc through an integrated analysis of plasma proteome-wide Mendelian randomization (MR) and transcriptome, as well as to explore the potential mechanisms.
Methods: The data used were obtained from public databases. Initially, key plasma proteins causally associated with SSc were identified through a two-sample MR analysis. Subsequently, based on the key diseases related to both key plasma proteins (genes) and key drugs targeting these proteins (genes), phenotype scanning was conducted to predict potential adverse side effects of key plasma proteins (genes). Single-cell RNA sequencing (scRNA-seq) analysis was performed to identify key cell types in GSE138669 dataset. Differentially expressed genes (DEGs) within key cell types in SSc were intersected with genes encoding key plasma proteins to obtain candidate biomarkers, whose functions were subsequently explored. By analyzing candidate biomarker expression in GSE138669 and GSE181549 datasets, the biomarkers were identified. Further exploration included regulatory network, cellular heterogeneity, and cell trajectory analyses.
Results: Initially, 106 plasma proteins (corresponding to 104 genes) were identified. It was revealed that targeting 12 key plasma proteins (like CD40LG) for treating SSc might lead to side effects related to specific key diseases (like mesothelioma). After recognizing epithelial cells and fibroblasts as key cell types, 8 candidate biomarkers associated with pathways like “proteasome” were identified. Notably, CCL19 and LOXL2 were identified as biomarkers, which exhibited elevated expression in SSc. Regulatory elements such as FOXL1 and hsa-miR-5001-5p were predicted to target biomarkers. Remarkably, differentiation stages of key cell type with heterogeneity and the biomarker expression patterns across these stages might be associated with SSc progression.
Conclusion: CCL19 and LOXL2 were identified as novel biomarkers for SSc, providing insights into the exploration of the disease’s pathogenesis and the development of new therapeutic targets.
Keywords: systemic sclerosis, mendelian randomization, plasma proteome, biomarker, single-cell RNA sequencing