Stool and blood metabolomics in the metabolic syndrome: a cross-sectional study.

Autor: Ponce-de-Leon M; Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany. mariana.ponce-de-leon@outlook.com.; Epidemiology, Medical Faculty, Universität Augsburg, Augsburg, Germany. mariana.ponce-de-leon@outlook.com., Wang-Sattler R; Institute of Translational Genomics, Helmholtz Munich, Munich-Neuherberg, Germany.; German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany., Peters A; Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany.; German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany.; Institute of Epidemiology, Helmholtz Munich, Munich-Neuherberg, Germany.; Munich Heart Alliance, German Center for Cardiovascular Health (DZHK E.V), Munich, Germany., Rathmann W; German Diabetes Center (DDZ), Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.; German Center for Diabetes Research (DZD), Partner Düsseldorf, Munich-Neuherberg, Germany., Grallert H; German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany.; Institute of Epidemiology, Helmholtz Munich, Munich-Neuherberg, Germany.; Research Unit of Molecular Epidemiology, Helmholtz Munich, Munich-Neuherberg, Germany., Artati A; Metabolomics and Proteomics Core, Helmholtz Munich, Munich-Neuherberg, Germany., Prehn C; Metabolomics and Proteomics Core, Helmholtz Munich, Munich-Neuherberg, Germany., Adamski J; Institute of Experimental Genetics, Helmholtz Munich, Munich-Neuherberg, Germany.; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.; Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia., Meisinger C; Epidemiology, Medical Faculty, Universität Augsburg, Augsburg, Germany., Linseisen J; Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany.; Epidemiology, Medical Faculty, Universität Augsburg, Augsburg, Germany.
Jazyk: angličtina
Zdroj: Metabolomics : Official journal of the Metabolomic Society [Metabolomics] 2024 Sep 21; Vol. 20 (5), pp. 105. Date of Electronic Publication: 2024 Sep 21.
DOI: 10.1007/s11306-024-02166-3
Abstrakt: Introduction/objectives: Changes in the stool metabolome have been poorly studied in the metabolic syndrome (MetS). Moreover, few studies have explored the relationship of stool metabolites with circulating metabolites. Here, we investigated the associations between stool and blood metabolites, the MetS and systemic inflammation.
Methods: We analyzed data from 1,370 participants of the KORA FF4 study (Germany). Metabolites were measured by Metabolon, Inc. (untargeted) in stool, and using the AbsoluteIDQ ® p180 kit (targeted) in blood. Multiple linear regression models, adjusted for dietary pattern, age, sex, physical activity, smoking status and alcohol intake, were used to estimate the associations of metabolites with the MetS, its components and high-sensitivity C-reactive protein (hsCRP) levels. Partial correlation and Multi-Omics Factor Analysis (MOFA) were used to investigate the relationship between stool and blood metabolites.
Results: The MetS was significantly associated with 170 stool and 82 blood metabolites. The MetS components with the highest number of associations were triglyceride levels (stool) and HDL levels (blood). Additionally, 107 and 27 MetS-associated metabolites (in stool and blood, respectively) showed significant associations with hsCRP levels. We found low partial correlation coefficients between stool and blood metabolites. MOFA did not detect shared variation across the two datasets.
Conclusions: The MetS, particularly dyslipidemia, is associated with multiple stool and blood metabolites that are also associated with systemic inflammation. Further studies are necessary to validate our findings and to characterize metabolic alterations in the MetS. Although our analyses point to weak correlations between stool and blood metabolites, additional studies using integrative approaches are warranted.
(© 2024. The Author(s).)
Databáze: MEDLINE
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