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已发表论文
基于单细胞加权基因共表达网络分析、孟德尔随机化分析及临床验证的阿尔茨海默病浆细胞亚群及分子标志物的鉴定
Authors Xin C, Zhi HW, Wu DH, Ding PL, Wang ZL, Wang YH
Received 10 May 2025
Accepted for publication 9 September 2025
Published 18 September 2025 Volume 2025:18 Pages 5641—5664
DOI https://doi.org/10.2147/IJGM.S539547
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Redoy Ranjan
Chao Xin,1,2 Hong-Wei Zhi,3 Da-Hua Wu,4 Peng-Li Ding,1 Zhong-Lin Wang,1,3 Ya-Han Wang4
1Shandong University of Traditional Chinese Medicine, Jinan, Shandong, People’s Republic of China; 2Affiliated Hospital of Shandong Academy of Traditional Chinese Medicine, Jinan, Shandong, People’s Republic of China; 3Shandong University of Traditional Chinese Medicine Affiliated Hospital, Jinan, Shandong, People’s Republic of China; 4Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Changsha, Hunan, People’s Republic of China
Correspondence: Zhong-Lin Wang, Affiliated Hospital of Shandong Academy of Traditional Chinese Medicine, Jingshi Road No. 16369, Lixia District, Jinan, Shandong, People’s Republic of China, Tel +86-0531-6861-6039, Email doctorzhonglinwang@outlook.com Ya-Han Wang, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Lushan Road No. 58, Yuelu District, Changsha, Hunan, People’s Republic of China, Tel +86-15811105935, Email wyahan621@outlook.com
Introduction: Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by gene expression alterations and immune dysregulation.
Methods: In this study, we downloaded the GSE181279 single-cell dataset from the Gene Expression Omnibus (GEO) and applied bioinformatic analysis and clinical subject validation.
Results: After quality control and harmony integration, we identified 21 cell subsets, including T cells, B cells, plasma cells, and macrophages. Plasma cells were significantly elevated in AD patients, and six plasma cell subtypes were associated with AD. High-dimensional weighted gene co-expression network analysis (hdWGCNA) revealed two AD-related modules. Mendelian randomization identified RGS1 as a key risk gene (p = 0.0123). Immune infiltration analysis showed RGS1 negatively correlated with macrophages and positively with tumor-infiltrating lymphocytes. Functional enrichment indicated that RGS1 is involved in JAK-STAT, NF-κB, and Wnt-β-catenin signaling pathways, suggesting a role in immune regulation and neuroinflammation. Furthermore, validation in AD patients confirmed that RGS1 expression levels were higher than in controls (p < 0.01).
Discussion: This study identified the key gene RGS1 related to AD and explored multiple signaling pathways associated with it, which provided important clues for the research on AD-related inflammation, gut microbiota, stretch-gated ion channel, and the evaluation of AD therapeutic targets.
Clinical Trial Registration Number: CTR20210477.
Keywords: alzheimer’s disease, mendelian randomization, single-cell analysis, key genes, clinical validation
1Shandong University of Traditional Chinese Medicine, Jinan, Shandong, People’s Republic of China; 2Affiliated Hospital of Shandong Academy of Traditional Chinese Medicine, Jinan, Shandong, People’s Republic of China; 3Shandong University of Traditional Chinese Medicine Affiliated Hospital, Jinan, Shandong, People’s Republic of China; 4Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Changsha, Hunan, People’s Republic of China
Correspondence: Zhong-Lin Wang, Affiliated Hospital of Shandong Academy of Traditional Chinese Medicine, Jingshi Road No. 16369, Lixia District, Jinan, Shandong, People’s Republic of China, Tel +86-0531-6861-6039, Email doctorzhonglinwang@outlook.com Ya-Han Wang, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Lushan Road No. 58, Yuelu District, Changsha, Hunan, People’s Republic of China, Tel +86-15811105935, Email wyahan621@outlook.com
Introduction: Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by gene expression alterations and immune dysregulation.
Methods: In this study, we downloaded the GSE181279 single-cell dataset from the Gene Expression Omnibus (GEO) and applied bioinformatic analysis and clinical subject validation.
Results: After quality control and harmony integration, we identified 21 cell subsets, including T cells, B cells, plasma cells, and macrophages. Plasma cells were significantly elevated in AD patients, and six plasma cell subtypes were associated with AD. High-dimensional weighted gene co-expression network analysis (hdWGCNA) revealed two AD-related modules. Mendelian randomization identified RGS1 as a key risk gene (p = 0.0123). Immune infiltration analysis showed RGS1 negatively correlated with macrophages and positively with tumor-infiltrating lymphocytes. Functional enrichment indicated that RGS1 is involved in JAK-STAT, NF-κB, and Wnt-β-catenin signaling pathways, suggesting a role in immune regulation and neuroinflammation. Furthermore, validation in AD patients confirmed that RGS1 expression levels were higher than in controls (p < 0.01).
Discussion: This study identified the key gene RGS1 related to AD and explored multiple signaling pathways associated with it, which provided important clues for the research on AD-related inflammation, gut microbiota, stretch-gated ion channel, and the evaluation of AD therapeutic targets.
Clinical Trial Registration Number: CTR20210477.
Keywords: alzheimer’s disease, mendelian randomization, single-cell analysis, key genes, clinical validation