Identification of Macrophage-Related Biomarkers for Abdominal Aortic Aneurysm Through Combined Single-Cell Sequencing and Machine Learning

Abstract

Guoqing Yao,1,* Xuemei Hu,2,* Daqiang Song,3 Jin Yao,4 Deqing Chen,2 Tiankuo Luan,5 Yu Zhao1 1Department of Vascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China; 2Department of Endocrinology, The People’s Hospital of Rongchang District, Chongqing, 402460, People’s Republic of China; 3Chongqing Key Laboratory of Molecular Oncology and Epigenetics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China; 4School of Acu-Mox and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, People’s Republic of China; 5Department of Anatomy, Chongqing Medical University, Chongqing, 400016, People’s Republic of China*These authors contributed equally to this workCorrespondence: Tiankuo Luan, Department of Anatomy, Chongqing Medical University, Chongqing, 400016, People’s Republic of China, Email [email protected] Yu Zhao, Department of Vascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China, Email [email protected]: The relationship between macrophages and the progression of abdominal aortic aneurysms (AAA) remains unclear, and effective biomarkers are lacking. In this study, we elucidated the mechanism whereby macrophages promote AAA development and identified associated biomarkers, with the goal of developing new targeted therapies and improving patient outcomes.Patients and Methods: Differential expression analysis, weighted gene co-expression network analysis, and single-cell analysis were used to identify macrophage-related genes in an AAA dataset. Machine learning algorithms identified THBS1, HCLS1, DMXL2, and ZEB2 as key macrophage-related genes upregulated in AAA; these four hub genes were then used to construct a nomogram as an auxiliary tool for clinical diagnosis. Subsequent downstream single-cell and CellChat analyses were conducted to observe the interactions between macrophages and fibroblasts and analyze potential pathways.Results: Single-cell validation confirmed enhanced THBS1 expression in macrophages in AAA. CellChat analysis revealed enhanced interactions between macrophages and fibroblasts in AAA through THBS1–CD47 signaling. Finally, an analysis of clinical samples from patients with AAA confirmed the high expression of THBS1 and CD47 in AAA and that THBS1 promotes the progression of AAA through the TNF-NFκB signaling pathway. Our findings reveal the THBS1–CD47 signaling pathway as a critical mechanism in macrophage-driven AAA progression, highlighting THBS1’s potential as a therapeutic target.Conclusion: Our findings highlight THBS1 as a potential driver of macrophage-mediated AAA formation and an important biomarker for AAA diagnosis. The study results would help in improving treatment outcomes in patients with AAA. These findings provide a foundation for the development of diagnostic tools and targeted therapies for AAA, potentially improving early detection and patient outcomes. Keywords: abdominal aortic aneurysm, macrophage, single-cell sequencing, machine learning algorithm, cell chat

Keywords

• abdominal aortic aneurysm
• macrophage
• single-cell sequencing
• machine learning algorithm
• cellchat