Prognostic implication of lipidomics in patients with coronary total occlusion undergoing PCI. (29th June 2022)

• Record Type: Journal Article
• Authors: Zhou, You; Chen, Jinxiang; Li, Su; Chen, Ao; Dai, Chunfeng; Liu, Muyin; Lu, Danbo; Chen, Zhangwei; Wang, Xiangdong; Qian, Juying; Ge, Junbo
• Is Part Of: European journal of clinical investigation. Volume 52:Number 11(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-06-29
• Subjects: biomarker -- chronic total occlusion -- coronary artery disease -- lipidomics -- risk prediction; Pathology -- Periodicals; Medical research -- Periodicals; 616.075
• DOI: 10.1111/eci.13826
• Languages: English
• ISSNs: 0014-2972

Abstract

Abstract: Background: Predictors of prognosis in patients with coronary chronic total occlusion (CTO) undergoing elective percutaneous coronary intervention (PCI) have remained lacking. Lipidomic profiling enables researchers to associate lipid species with disease progression and may improve the prediction of cardiovascular events. Methods: In the present study, 781 lipids were measured by targeted lipidomic profiling in 350 individuals (50 healthy controls, 50 patients with coronary artery disease and 250 patients with CTO). L1‐regularized logistic regression was used to identify lipid species associated with adverse cardiovascular events and create predicting models, which were verified by 10‐fold cross‐validation (200 repeats). Comparisons were made between a traditional model constructed with clinical characteristics alone and a combined model built with both lipidomic data and traditional factors. Results: Twenty‐four lipid species were dysregulated exclusively in patients with CTO, most of which belonged to sphingomyelin (SM) and triacylglycerol (TAG). Compared with traditional risk factors, new model combining lipids and traditional factors had significantly improved performance in predicting adverse cardiovascular events in CTO patients after PCI (area under the curve, 0.870 vs. 0.726, p < .05; Akaike information criterion, 129 versus 156; net reclassification improvement, 0.312, p < .001; integrated discrimination improvement, 0.244, p < .001). Nomogram was built based on the incorporated model and proved efficient by Kaplan–Meier method. Conclusions: Lipidomic profiling revealed lipid species which may participate in the formation of CTO and could contribute to the risk stratification in CTO patients undergoing PCI.