Lipidomics emerges as a promising research field with the potential to help in personalized risk stratification and improve our understanding on the functional role of individual lipid species in the metabolic perturbations occurring in coronary artery disease (CAD). This study aimed to utilize a machine learning approach to provide a lipid panel able to identify patients with obstructive CAD. In this posthoc analysis of the prospective CorLipid trial, we investigated the lipid profiles of 146 patients with suspected CAD, divided into two categories based on the existence of obstructive CAD. In total, 517 lipid species were identified, from which 288 lipid species were finally quantified, including glycerophospholipids, glycerolipids, and sphingolipids. Univariate and multivariate statistical analyses have shown significant discrimination between the serum lipidomes of patients with obstructive CAD. Finally, the XGBoost algorithm identified a panel of 17 serum biomarkers (5 sphingolipids, 7 glycerophospholipids, a triacylglycerol, galectin-3, glucose, LDL, and LDH) as totally sensitive (100% sensitivity, 62.1% specificity, 100% negative predictive value) for the prediction of obstructive CAD. Our findings shed light on dysregulated lipid metabolism's role in CAD, validating existing evidence and suggesting promise for novel therapies and improved risk stratification.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11301671 | PMC |
| http://dx.doi.org/10.1021/acs.jproteome.4c00249 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Correlation of lipid profile APO A1 and APO B100 in chronic periodontitis patients leading to coronary artery disease.
Natl J Maxillofac Surg
November 2024
C.B.M.R., Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Background: Increased attention has been focused on the association of periodontal disease with cardio-metabolic syndrome. Although the associations are multi-factorial, very few studies have explored the role of lipoprotein Apo A1 and Apo B100 with chronic periodontitis. Additionally, obstructive sleep apnea (OSA), a chronic multi-factorial respiratory disease, consists of a temporary decrease or cessation of breath for ≥ 10 seconds and leads to a reduction in blood oxygen saturation of more than 3% to 4% and/or neurological arousal.
View Article and Find Full Text PDFElevated Inflammation and Adhesion Molecule hsCRP, GDF-15 and VCAM-1 in Angina Patients with Non-obstructive Coronary Artery Disease.
Malays J Med Sci
December 2024
Department of Internal Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kelantan, Malaysia.
Background: Non-obstructive coronary artery disease (NOCAD) is a condition in stable patients that experience angina despite not having significant coronary obstructive lesion. Knowledge on the role of certain biomarkers in patients with NOCAD is still limited. This study aimed to evaluate the roles of inflammation and adhesion molecules in the development of NOCAD.
View Article and Find Full Text PDFFeasibility of on-site CT-FFR analysis on cardiac photon-counting CT in evaluation of hemodynamically significant stenosis in comparison to invasive catheter angiography.
Eur J Radiol
January 2025
Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany. Electronic address:
Objectives: Coronary CT angiography (CCTA) is an excellent tool in ruling out coronary artery disease (CAD) but tends to overestimate especially highly calcified plaques. To reduce diagnostic invasive catheter angiographies (ICA), current guidelines recommend CT-FFR to determine the hemodynamic significance of coronary artery stenosis. Photon-Counting Detector CT (PCCT) revolutionized CCTA and may improve CT-FFR analysis in guiding patients.
View Article and Find Full Text PDFCAD-Q (COPD-Asthma Differentiation Questionnaire): Performance of a new diagnostic score to differentiate between COPD and asthma in adults.
BMC Pulm Med
January 2025
School of Medicine, Universidad de La Sabana, Chía, Colombia.
Background: Chronic obstructive pulmonary disease (COPD) and asthma are the two most prevalent chronic respiratory diseases, significantly impacting public health. Utilizing clinical questionnaires to identify and differentiate patients with COPD and asthma for further diagnostic procedures has emerged as an effective strategy to address this issue. We developed a new diagnostic tool, the COPD-Asthma Differentiation Questionnaire (CAD-Q), to differentiate between COPD and asthma in adults.
View Article and Find Full Text PDFA Machine Learning Model Using Cardiac CT and MRI Data Predicts Cardiovascular Events in Obstructive Coronary Artery Disease.
Radiology
January 2025
From the Department of Cardiology (T.P., K.H., T.G., A.L., E.G., A.U., J.G.D., P.H.), MIRACL.ai (Multimodality Imaging for Research and Analysis Core Laboratory: and Artificial Intelligence) (T.P., S.T., K.H., T.G., A.L., E.G., A.U., J.G.D., P.H.), Inserm MASCOT-UMRS 942 (T.P., K.H., T.A.S., T.G., A.L., E.G., A.U., J.G.D., P.H.), and Department of Radiology (T.P., V.B., L.H., T.G.), Université Paris Cité, University Hospital of Lariboisière, Assistance Publique-Hôpitaux de Paris, Paris, France; Cardiovascular Magnetic Resonance Laboratory (T.P., T.H., T.U., F.S., S.C., P.G., J.G.) and Cardiac Computed Tomography Laboratory (T.P., T.H., T.L., B.C., T.U., F.S., S.C., H.B., A.N., M.A., P.G., J.G.), Hôpital Privé Jacques Cartier, Institut Cardiovasculaire Paris Sud, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300 Massy, France; Scientific Partnerships, Siemens Healthcare France, Saint-Denis, France (S.T.); Department of Cardiology, Hôpital Universitaire de Bruxelles-Hôpital Erasme, Brussels, Belgium (A.U.); and Department of Cardiovascular Imaging, American Hospital of Paris, Neuilly, France (O.V., M.S.).
Background Multimodality imaging is essential for personalized prognostic stratification in suspected coronary artery disease (CAD). Machine learning (ML) methods can help address this complexity by incorporating a broader spectrum of variables. Purpose To investigate the performance of an ML model that uses both stress cardiac MRI and coronary CT angiography (CCTA) data to predict major adverse cardiovascular events (MACE) in patients with newly diagnosed CAD.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!