TY - JOUR
T1 - Serum Lipidomic Screen Identifies Key Metabolites, Pathways, and Disease Classifiers in Crohn's Disease
AU - NIDDK IBD Genetics Consortium, iGenoMed Consortium
AU - Ferru-Clement, Romain
AU - Boucher, Gabrielle
AU - Forest, Anik
AU - Bouchard, Bertrand
AU - Bitton, Alain
AU - Lesage, Sylvie
AU - Schumm, Phil
AU - Lazarev, Mark
AU - Brant, Steve
AU - Duerr, Richard H.
AU - McGovern, Dermot P.B.
AU - Silverberg, Mark
AU - Cho, Judy H.
AU - Ananthakrishnan, Ashwin
AU - Xavier, Ramnik J.
AU - Rioux, John D.
AU - Des Rosiers, Christine
N1 - Publisher Copyright:
© 2023 The Author(s). Published by Oxford University Press on behalf of Crohn's & Colitis Foundation. All rights reserved.
PY - 2023/7/1
Y1 - 2023/7/1
N2 - 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.
AB - 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.
KW - Crohn's disease
KW - comprehensive untargeted lipidomics
KW - lipid biomarkers
KW - subtype stratification
UR - http://www.scopus.com/inward/record.url?scp=85160528798&partnerID=8YFLogxK
U2 - 10.1093/ibd/izac281
DO - 10.1093/ibd/izac281
M3 - Article
C2 - 36662167
AN - SCOPUS:85160528798
SN - 1078-0998
VL - 29
SP - 1024
EP - 1037
JO - Inflammatory Bowel Diseases
JF - Inflammatory Bowel Diseases
IS - 7
ER -