LC/MS-Based Untargeted Metabolomics Study in Women with Nonalcoholic Steatohepatitis Associated with Morbid Obesity.
Laia BertranJordi CapelladesSonia AbellóJoan Durán-BertranCarmen AguilarSalomé MartinezFàtima SabenchXavier CorreigÓscar YanesTeresa AuguetCristóbal RichartPublished in: International journal of molecular sciences (2023)
This study investigated the importance of a metabolomic analysis in a complex disease such as nonalcoholic steatohepatitis (NASH) associated with obesity. Using an untargeted metabolomics technique, we studied blood metabolites in 216 morbidly obese women with liver histological diagnosis. A total of 172 patients were diagnosed with nonalcoholic fatty liver disease (NAFLD), and 44 were diagnosed with normal liver (NL). Patients with NAFLD were classified into simple steatosis ( n = 66) and NASH ( n = 106) categories. A comparative analysis of metabolites levels between NASH and NL demonstrated significant differences in lipid metabolites and derivatives, mainly from the phospholipid group. In NASH, there were increased levels of several phosphatidylinositols and phosphatidylethanolamines, as well as isolated metabolites such as diacylglycerol 34:1, lyso-phosphatidylethanolamine 20:3 and sphingomyelin 38:1. By contrast, there were decreased levels of acylcarnitines, sphingomyelins and linoleic acid. These findings may facilitate identification studies of the main pathogenic metabolic pathways related to NASH and may also have a possible applicability in a panel of metabolites to be used as biomarkers in future algorithms of the disease diagnosis and its follow-up. Further confirmatory studies in groups with different ages and sexes are necessary.
Keyphrases
- ms ms
- mass spectrometry
- metabolic syndrome
- insulin resistance
- weight loss
- bariatric surgery
- type diabetes
- end stage renal disease
- obese patients
- high fat diet induced
- newly diagnosed
- machine learning
- magnetic resonance imaging
- magnetic resonance
- chronic kidney disease
- fatty acid
- liquid chromatography
- prognostic factors
- deep learning
- gas chromatography mass spectrometry
- high resolution
- skeletal muscle
- case control
- tandem mass spectrometry