Platelet RNA-seq Reveals Genes Associated with Carotid Intima–Media Thickness: A Cross-sectional Study - Fan Guo; Zhanfei Tan; Jiaming Gao; Lanlan Li; Shujuan Xu; Yehao Zhang; Jianhua Fu; Jianxun Liu (TH Open)
Background: Although the association between platelet characteristics and the risk of developing atherosclerosis (AS) has been acknowledged, the specific role of platelets in AS development and progression remains unclear. Therefore, the aim of this study was to identify platelet characteristics in patients with and without AS to enhance the understanding of their pathophysiological functions and discover more sensitive biomarkers for AS diagnosis. Methods: We conducted a cross-sectional study involving AS patients and healthy controls (N). Based on the Chinese guidelines for diagnosing carotid and vertebral artery atherosclerosis and the 2010 American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines, we defined atherosclerosis (AS) using carotid ultrasound to measure intima-media thickness (IMT). General information such as sex, age, height, and weight was collected upon enrollment. A series of examinations, including physical exams, serum lipid profiles, blood glucose tests, liver and kidney function tests, platelet aggregation assays, and carotid artery ultrasounds, were performed. Platelets were extracted from plasma for RNA-seq analysis. Results: No statistically significant differences in age, sex, body mass index (BMI), or blood pressure were observed between the groups. Total triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (ApoB), red blood cell count (RBC), hemoglobin concentration (HGB), cholesterol levels, and carotid intima-media thickness (IMT) were significantly greater and vascular endothelial function was significantly lower in the AS group than in the N group. Using, RNA-seq we identified 784 differentially expressed genes—141 downregulated and 643 upregulated—with Gene Ontology enrichment showing significant associations with blood coagulation pathways, among others. Weighted correlation network analysis revealed four hub genes related to IMT: ITGA2B, TGFB1, PF4, and GP9. Conclusions: Our findings indicate moderate correlations of elevated ITGA2B (r=0.327; p=0.004), TGFB1 (r=0.362; p=0.001), PF4 (r=0.240; p=0.038), and GP9 (r=0.302; p=0.008) levels with increased IMT, suggesting that these genes may serve as predictive biomarkers for AS.