Identification of the M1-like macrophage-associated diagnostic and therapeutic frameworks targeting carotid atherosclerosis patients: Integrative bioinformatic and multi-omic studies.

BACKGROUND

M1‑like macrophage dysregulation is a central driver of inflammation and plaque formation in atherosclerosis (AS). However, specific diagnostic and therapeutic targets for carotid atherosclerotic plaque remain incomplete.

OBJECTIVE

This study aims to identify M1‑like macrophage‑associated diagnostic biomarkers and potential therapeutic compounds for carotid atherosclerotic plaque using an integrative multi‑omics framework.

METHODS

Carotid atheromatous plaque of AS patients bulk profiles datasets(GSE163154, GSE43292 and GSE111782) were downloaded from GEO database. GSE163154 was designated for internal set for M1-like macrophage-associated DEGs via integration of CIBEROSORT and WGCNA frameworks. Next, GSE163154 was considered as training set for identification of M1-like macrophage-related hub genes and diagnostic model construction for alerting the formation of plaques via integrative bioinformatic and machine learning approaches. Besides, the heterogeneity of M1-like macrophage-related hub genes was estimated at carotid atherosclerotic plaque of AS patients single-cell transcriptomic dataset(GSE155514). Besides, CTD database and molecular docking were both performed for the natural compounds therapeutic framework identification targeting M1-like macrophage-related hub genes in eliminating carotid atherosclerotic plaque.

RESULTS

CPSF7 and ZNF609 could be considered as diagnostic biomarkers in prediction of carotid atherosclerotic plaque formation of AS patients mainly distributed at M1-like macrophage. Besides, Valproic acid and Quercetin can be considered as potential natural compounds for the treatment of carotid atherosclerotic plaque.

CONCLUSION

CPSF7 and ZNF609 are novel M1‑like macrophage‑associated biomarkers for carotid plaque detection, and valproic acid and quercetin are candidate therapeutic compounds in AS. These findings provide a novel perspective into AS patient clinical translation.