Atherosclerosis (AS) is a multifactorial disease and a leading cause of cardiovascular diseases, imposing a significant burden on global health. While there is considerable progress in elucidating its pathogenesis, the understanding of AS remains incomplete. Consequently, the identification of novel therapeutic targets is paramount to developing more comprehensive therapeutic interventions. We applied integrative approaches, including Summary-data-based Mendelian randomization (SMR), colocalization, and machine learning to prioritize causal genes. Experimental validation encompassed reverse transcription-real-time polymerase chain reaction (RT-qPCR), immunofluorescence, and single-cell RNA-seq in human plaques, complemented by ox-LDL-induced cellular models. Drug prediction and molecular docking were performed to assess therapeutic potential. A total of 15 relevant positive genes were identified by SMR, and the gene cadherin EGF LAG seven-pass G-type receptor 2(
CELSR2
) was verified as a key gene. Subsequent RT-qPCR and immunofluorescence of human carotid atherosclerotic plaques confirmed that CELSR2 showed different expression in the pathological state of AS. RT-qPCR combined with single-cell sequencing analysis led us to conclude that
CELSR2
is a key target in the pathogenesis of AS.
CELSR2
is an experimentally validated AS-related gene, which is important for unraveling the pathogenesis of AS and developing new therapeutic options.