Serum Lipidomic Screen Identifies Key Metabolites, Pathways, and Disease Classifiers in Crohn’s Disease

• Published in: Inflammatory bowel diseases Vol. 29; no. 7; pp. 1024 - 1037
• Main Authors: Ferru-Clément, Romain, Boucher, Gabrielle, Forest, Anik, Bouchard, Bertrand, Bitton, Alain, Lesage, Sylvie, Schumm, Phil, Lazarev, Mark, Brant, Steve, Duerr, Richard H, McGovern, Dermot P B, Silverberg, Mark, Cho, Judy H, Ananthakrishnan, Ashwin, Xavier, Ramnik J, Rioux, John D, Des Rosiers, Christine
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 05.07.2023
• Subjects: Biomarkers; Crohn Disease - pathology; Crohn's disease; Humans; Inflammation; Lipidomics; Lipids; Metabolites; subtype stratification; lipid biomarkers; comprehensive untargeted lipidomics; Crohn’s disease
• ISSN: 1078-0998; 1536-4844; 1536-4844
• DOI: 10.1093/ibd/izac281

Background There is an unmet medical need for biomarkers that capture host and environmental contributions in inflammatory bowel diseases (IBDs). This study aimed at testing the potential of circulating lipids as disease classifiers given their major roles in inflammation. Methods We applied a previously validated comprehensive high-resolution liquid chromatography-mass spectrometry–based untargeted lipidomic workflow covering 25 lipid subclasses to serum samples from 100 Crohn’s disease (CD) patients and 100 matched control subjects. Findings were replicated and expanded in another 200 CD patients and 200 control subjects. Key metabolites were tested for associations with disease behavior and location, and classification models were built and validated. Their association with disease activity was tested using an independent cohort of 42 CD patients. Results We identified >70 metabolites with strong association (P < 1 × 10-4, q < 5 × 10-4) to CD. Highly performing classification models (area under the curve > 0.84-0.97) could be built with as few as 5 to 9 different metabolites, representing 6 major correlated lipid clusters. These classifiers included a phosphatidylethanolamine ether (O-16:0/20:4), a sphingomyelin (d18:1/21:0) and a cholesterol ester (14:1), a very long-chain dicarboxylic acid [28:1(OH)] and sitosterol sulfate. These classifiers and correlated lipids indicate a dysregulated metabolism in host cells, notably in peroxisomes, as well as dysbiosis, oxidative stress, compromised inflammation resolution, or intestinal membrane integrity. A subset of these were associated with disease behavior or location. Conclusions Untargeted lipidomic analyses uncovered perturbations in the circulating human CD lipidome, likely resulting from multiple pathogenic mechanisms. Models using as few as 5 biomarkers had strong disease classifier characteristics, supporting their potential use in diagnosis or prognosis. Lay Summary This study reports a comprehensive untargeted lipidomic analysis of 600 serum samples from patients with Crohn’s disease and matched control subjects, identified and replicated ~70 metabolites associated with Crohn’s disease, and developed highly performing classification models (area under the curve > 0.84-0.97) with as few as 5 metabolites.