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Metabolomic Alterations in Patients with Obesity and the Impact of Metabolic Bariatric Surgery: Insights for Future Research

Anastasiou, Ioanna A.; Kounatidis, Dimitris; Honka, Miikka-Juhani; Vallianou, Natalia G.; Rebelos, Eleni; Karamanolis, Nikolaos Nektarios; Dalamaga, Maria; Pantos, Constantinos; Mourouzis, Iordanis

Metabolomic Alterations in Patients with Obesity and the Impact of Metabolic Bariatric Surgery: Insights for Future Research

Anastasiou, Ioanna A.
Kounatidis, Dimitris
Honka, Miikka-Juhani
Vallianou, Natalia G.
Rebelos, Eleni
Karamanolis, Nikolaos Nektarios
Dalamaga, Maria
Pantos, Constantinos
Mourouzis, Iordanis
Katso/Avaa
metabolites-15-00434.pdf (716.9Kb)
Lataukset: 

MDPI AG
doi:10.3390/metabo15070434
URI
https://doi.org/10.3390/metabo15070434
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe202601216324
Tiivistelmä
Metabolomics has emerged as a vital tool for understanding the body's responses to therapeutic interventions. Metabolic bariatric surgery (MBS) is widely recognized as the most effective treatment modality for severe obesity and its associated comorbidities. This review seeks to analyze the current evidence on the metabolomic profiles of patients with obesity and the impact of various bariatric surgical procedures, with the objective of predicting clinical outcomes, including weight loss and remission of type 2 diabetes (T2D). The data gathered from original studies examining metabolomic changes following MBS have been meticulously compiled and summarized. The findings revealed significant alterations in metabolites across various classes, including amino acids, lipids, energy-related compounds, and substances derived from the gut microbiota. Notably, elevated preoperative levels of specific lipids, such as phospholipids, long-chain fatty acids, and bile acids, were correlated with postoperative remission of T2D. In conclusion, metabolite profiling holds great promise for predicting long-term responses to different bariatric surgery procedures. This innovative approach has the potential to facilitate personalized treatment strategies and optimize the allocation of healthcare resources.
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