Machine learning and single-cell RNA sequencing identify shared diagnostic genes and mechanistic links between antiphospholipid syndrome and carotid atherosclerosis.

Background: Antiphospholipid syndrome (APS) is an acquired autoimmune disorder characterized by recurrent vascular events in large, medium, or small vessels. These events contribute to cardiovascular disease primarily through thrombosis and atherosclerosis (AS). Carotid atherosclerosis (CAS) represents a particularly high-risk manifestation of subclinical AS in patients with APS. However, the shared molecular signatures linking APS and CAS remain unclear. Methods: Bulk transcriptome datasets from Gene Expression Omnibus (GEO) were analyzed to identify differentially expressed genes (DEGs) in APS and CAS. Common DEGs were characterized by Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and protein-protein interaction analyses. Candidate hub genes were prioritized by integrating Least Absolute Shrinkage and Selection Operator (LASSO), random forest, weighted gene co-expression network analysis (WGCNA), and MCODE, followed by diagnostic evaluation in independent datasets. Upstream regulatory networks and immune infiltration were assessed using Results: A total of 4,264 DEGs were identified in APS and 838 DEGs in CAS, including 52 common DEGs (43 upregulated and nine downregulated). These common DEGs were enriched in plasma-membrane and actin-cytoskeleton-related functions, with nominal KEGG signals involving oxytocin, Jak-STAT, and PI3K-Akt pathways. Cross-method prioritization highlighted