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已发表论文
通过综合生物信息学和验证对动脉粥样硬化和钙化主动脉瓣疾病中 FBP1 的跨疾病识别：功能分析及治疗靶点探索
Authors Xu H , Xu Y, Wang X, Yan Z, Geng T, Wu J, Li Y, Guo M
Received 15 May 2025
Accepted for publication 12 November 2025
Published 19 November 2025 Volume 2025:18 Pages 16135—16156
DOI https://doi.org/10.2147/JIR.S540540
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Durga Prasanna Misra
Haowen Xu,1,* Yifan Xu,2,* Xueyi Wang,3 Zhisheng Yan,4 Ting Geng,5 Jinpeng Wu,2 Yongxin Li,1 Mingjin Guo1
1Department of Vascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, People’s Republic of China; 2Department of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, People’s Republic of China; 3Department of Vascular Surgery, Rongcheng City People’s Hospital, Rongcheng, 264300, People’s Republic of China; 4Department of Interventional Medicine, The Eighth People’s Hospital of Qingdao, Qingdao, 266000, People’s Republic of China; 5Interventional Operating Room, The Eighth People’s Hospital of Qingdao, Qingdao, 266000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Mingjin Guo, Department of Vascular Surgery, The Affiliated Hospital of Qingdao University, 16 Jiang Su Road, Qingdao, 266000, People’s Republic of China, Email qduahvasc@163.com Yongxin Li, Department of Vascular Surgery, The Affiliated Hospital of Qingdao University, 16 Jiang Su Road, Qingdao, 266000, People’s Republic of China, Email Li.yongxin@outlook.com
Purpose: Atherosclerosis (AS) and calcific aortic valve disease (CAVD) are common in aging populations and share metabolic dysregulation, chronic inflammation, and cellular aging. Shared immunometabolic biomarkers and therapeutic targets remain insufficiently defined. This study aimed to identify Cross-disease biomarkers linking AS and CAVD and to explore their translational potential.
Methods: Four Gene Expression Omnibus (GEO) microarray datasets related to AS and CAVD were integrated. Differentially expressed genes (DEGs) were identified within each disease, and Cross-disease genes (CGs) were obtained by intersecting DEGs across the two diseases. Functional enrichment and protein–protein interaction analyses were performed. Machine learning (LASSO and Random Forest) refined candidate biomarkers. Immune infiltration was estimated with CIBERSORT, and a microRNA–transcription factor regulatory network was constructed. Molecular docking screened small molecules targeting the hub gene. Diagnostic performance was evaluated in independent datasets, and expression was validated in human tissues by qPCR and Western blot.
Results: We identified 147 CGs enriched in immune and metabolic pathways. Fructose-1,6-bisphosphatase 1 (FBP1) emerged as a hub gene with strong diagnostic value across datasets. FBP1 expression correlated with alterations in multiple immune cell populations and was embedded within a regulatory network of predicted microRNAs and transcription factors. Docking analysis highlighted apigenin and kaempferol as candidate FBP1-targeting compounds. Experimental validation confirmed FBP1 upregulation in AS and CAVD tissues.
Discussion: FBP1 represents a shared immunometabolic biomarker and potential therapeutic target that links metabolic reprogramming to immune dysregulation in AS and CAVD. These findings provide a rationale for further translational studies evaluating FBP1-centered interventions.
Keywords: atherosclerosis, calcific aortic valve disease, machine learning, immunology, molecular docking
1Department of Vascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, People’s Republic of China; 2Department of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, People’s Republic of China; 3Department of Vascular Surgery, Rongcheng City People’s Hospital, Rongcheng, 264300, People’s Republic of China; 4Department of Interventional Medicine, The Eighth People’s Hospital of Qingdao, Qingdao, 266000, People’s Republic of China; 5Interventional Operating Room, The Eighth People’s Hospital of Qingdao, Qingdao, 266000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Mingjin Guo, Department of Vascular Surgery, The Affiliated Hospital of Qingdao University, 16 Jiang Su Road, Qingdao, 266000, People’s Republic of China, Email qduahvasc@163.com Yongxin Li, Department of Vascular Surgery, The Affiliated Hospital of Qingdao University, 16 Jiang Su Road, Qingdao, 266000, People’s Republic of China, Email Li.yongxin@outlook.com
Purpose: Atherosclerosis (AS) and calcific aortic valve disease (CAVD) are common in aging populations and share metabolic dysregulation, chronic inflammation, and cellular aging. Shared immunometabolic biomarkers and therapeutic targets remain insufficiently defined. This study aimed to identify Cross-disease biomarkers linking AS and CAVD and to explore their translational potential.
Methods: Four Gene Expression Omnibus (GEO) microarray datasets related to AS and CAVD were integrated. Differentially expressed genes (DEGs) were identified within each disease, and Cross-disease genes (CGs) were obtained by intersecting DEGs across the two diseases. Functional enrichment and protein–protein interaction analyses were performed. Machine learning (LASSO and Random Forest) refined candidate biomarkers. Immune infiltration was estimated with CIBERSORT, and a microRNA–transcription factor regulatory network was constructed. Molecular docking screened small molecules targeting the hub gene. Diagnostic performance was evaluated in independent datasets, and expression was validated in human tissues by qPCR and Western blot.
Results: We identified 147 CGs enriched in immune and metabolic pathways. Fructose-1,6-bisphosphatase 1 (FBP1) emerged as a hub gene with strong diagnostic value across datasets. FBP1 expression correlated with alterations in multiple immune cell populations and was embedded within a regulatory network of predicted microRNAs and transcription factors. Docking analysis highlighted apigenin and kaempferol as candidate FBP1-targeting compounds. Experimental validation confirmed FBP1 upregulation in AS and CAVD tissues.
Discussion: FBP1 represents a shared immunometabolic biomarker and potential therapeutic target that links metabolic reprogramming to immune dysregulation in AS and CAVD. These findings provide a rationale for further translational studies evaluating FBP1-centered interventions.
Keywords: atherosclerosis, calcific aortic valve disease, machine learning, immunology, molecular docking