NDLI: H-NMR metabolomics identifies three distinct metabolic profiles differentially associated with cardiometabolic risk in patients with obesity in the Di@bet.es cohort

Content Provider	Springer Nature : BioMed Central
Author	Ozcariz, Enrique Guardiola, Montse Amigó, Núria Valdés, Sergio Oualla-Bachiri, Wasima Rehues, Pere Rojo-Martinez, Gemma Ribalta, Josep
Abstract	Background Obesity is a complex, diverse and multifactorial disease that has become a major public health concern in the last decades. The current classification systems relies on anthropometric measurements, such as BMI, that are unable to capture the physiopathological diversity of this disease. The aim of this study was to redefine the classification of obesity based on the different H-NMR metabolomics profiles found in individuals with obesity to better assess the risk of future development of cardiometabolic disease. Materials and methods Serum samples of a subset of the Di@bet.es cohort consisting of 1387 individuals with obesity were analyzed by H-NMR. A K-means algorithm was deployed to define different H-NMR metabolomics-based clusters. Then, the association of these clusters with future development of cardiometabolic disease was evaluated using different univariate and multivariate statistical approaches. Moreover, machine learning-based models were built to predict the development of future cardiometabolic disease using BMI and waist-to-hip circumference ratio measures in combination with H-NMR metabolomics. Results Three clusters with no differences in BMI nor in waist-to-hip circumference ratio but with very different metabolomics profiles were obtained. The first cluster showed a metabolically healthy profile, whereas atherogenic dyslipidemia and hypercholesterolemia were predominant in the second and third clusters, respectively. Individuals within the cluster of atherogenic dyslipidemia were found to be at a higher risk of developing type 2 DM in a 8 years follow-up. On the other hand, individuals within the cluster of hypercholesterolemia showed a higher risk of suffering a cardiovascular event in the follow-up. The individuals with a metabolically healthy profile displayed a lower association with future cardiometabolic disease, even though some association with future development of type 2 DM was still observed. In addition, H-NMR metabolomics improved the prediction of future cardiometabolic disease in comparison with models relying on just anthropometric measures. Conclusions This study demonstrated the benefits of using precision techniques like H-NMR to better assess the risk of obesity-derived cardiometabolic disease.
Related Links	https://cardiab.biomedcentral.com/counter/pdf/10.1186/s12933-024-02488-5.pdf
Ending Page	13
Page Count	13
Starting Page	1
File Format	HTM / HTML
ISSN	14752840
DOI	10.1186/s12933-024-02488-5
Journal	Cardiovascular Diabetology
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2024-11-07
Access Restriction	Open
Subject Keyword	Diabetes Angiology Cardiology Obesity Metabolomics Type 2 diabetes mellitus Cardiovascular disease Atherogenic dyslipidemia Hypercholesterolemia Metabolically healthy obesity
Content Type	Text
Resource Type	Article
Subject	Cardiology and Cardiovascular Medicine Internal Medicine Endocrinology, Diabetes and Metabolism
Journal Impact Factor	8.5/2023
5-Year Journal Impact Factor	8.9/2023

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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