Integrated Analysis of Serotonin-Related Biomarkers in Thoracic Aortic Aneurysm Based on Machine Learning and Single-Cell Sequencing Data

Background: Serotonin, as an important neurotransmitter and signaling molecule, can affect thoracic aortic aneurysm (TAA) by regulating vascular cell proliferation, angiogenesis, and immune status. This research aimed to conduct a comprehensive analysis to pinpoint serotonin-related biomarkers in TAA and to elucidate their potential molecular mechanisms. Methods: Biomarkers were selected and validated through differential expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning algorithms, and expression verification. Moreover, the constructed nomogram, enrichment analysis, immune infiltration analysis, and compound prediction validated the regulatory roles of the biomarkers in TAA. The single-cell dataset was analyzed to determine key cells and perform pseudo-time analysis. Simulated knockout of biomarkers was performed to determine their underlying functions and related pathways. Finally, reverse transcription quantitative PCR (RT-qPCR) was employed to confirm the expression levels of the biomarkers. Results: Overall, two biomarkers (CD300A and CLU) were determined to be associated with serotonin in TAA. The nomogram showed good performance in predicting TAA risk. These biomarkers were significantly enriched in the hematopoietic cell lineage and natural killer (NK) cell mediated cytotoxicity. Biomarker expression was significantly correlated with the infiltration proportions of M2 macrophages and neutrophils. The biomarkers were stably bound to tetrachlorodibenzodioxin and bisphenol A. Moreover, pseudo-time analysis demonstrated a notable correlation between biomarker expression and the differentiation status of monocytes/macrophages/dendritic cells (MonoMac/DC). Genes perturbed by knockout were enriched in the pyrimidine metabolism and RIG-I-like receptor signaling pathway. Finally, RT-qPCR validated that CLU was downregulated and CD300A was upregulated in the TAA group. Conclusions: Biomarkers (CD300A and CLU) associated with serotonin in TAA were identified, with their expression trends validated by RT-qPCR. This work provides novel bioinformatic insights, and direct functional experiments are required to support future therapeutic development for TAA.