OR21-05 A Multinational Study of Serum Metabolomics and Lipidomics in the Pathophysiology and Non-invasive Diagnosis of Metabolic Dysfunction-Associated Steatotic Liver Disease

Abstract Disclosure: K. Stefanakis: None. N. Perakakis: None. O. Verrastro: None. M. Garcovich: None. L. Riccardi: None. M. Eslam: None. G.E. Markakis: None. G. Papatheodoridis: None. G. Mingrone: None. J. George: None. C.S. Mantzoros: None. The growing burden of metabolic dysfunction-associated steatotic liver disease (MASLD) and steatohepatitis (MASH), coupled with novel therapies targeting fibrotic MASH (F2–F3), underscores the need for deeper mechanistic insights and improved non-invasive test (NITs). In a multi-national biobank, we enrolled 443 biopsy-proven individuals (81 healthy controls, 362 patients, including 162 with MASH F≥2) across three countries (Italy, Greece, Australia) and two clinical center types (bariatric, gastroenterology-hepatology). A total of 839 metabolites and 840 lipid species were quantified in the serum of all 443 participants by ultra-high-performance liquid chromatography–tandem mass spectrometry. Beyond absolute changes, we employed supervised/unsupervised classifiers, clustering, and pathway enrichment analyses to map metabolites and lipids across the MASLD histological continuum. Early steatosis and MASLD were characterized by a pronounced surge in triglycerides conjugated with 16:0 (palmitic acid), together with elevated ceramides and inflammatory markers. Transition to MASH was marked by elevated BCAAs, bile acid metabolites, sphingolipids, urea cycle intermediates, and xenobiotic compounds (mannonate, hydroxybenzoate), alongside a further spike in triglycerides. In MASH F2–F3, 108 metabolites were markedly upregulated—notably 3-ureidopropionate (uracil pathway) and kynurenine (tryptophan pathway)—and 137 lipid species (chiefly glycerols with saturated fatty acids), whereas 21 metabolites (purines, n-acetylmethionine, steroidogenic intermediates) and 177 lipids (mainly phospholipids and ceramides) were significantly reduced. With advanced fibrosis (F3–F4), the triglyceride surge attenuated, yet inflammation persisted, coupled with dysregulated xenobiotic metabolism and depletion of >10 fibrinopeptide species, indicative of impaired coagulation. Weighted correlation analyses unveiled distinct modules of functionally and structurally similar metabolites and lipids co-varying with transaminases, GDF-15, activins and follistatins in significant fibrosis; separate from obesity-driven steatosis and early inflammation. Building on these comprehensive profiles, we developed categorical gradient-boosting models (4:1 training–validation split, repeated cross-validation with random resampling) using routine clinical variables (e.g., transaminases) and select metabolites such as 3-ureidopropionate, kynurenine, and sphingadienine. These models achieved cross-validated AUCs exceeding 88%—and up to 94%—in the validation cohort, outperforming over 20 established imaging- and biomarker-based NITs for detecting MASH, at-risk MASH, and F≥3. These findings define a novel paradigm for delineating mechanistic pathways that could reveal future therapeutic targets and streamline the development of accurate NITs. Presentation: Saturday, July 12, 2025

Authors

Institutions

Publication Details

Journal
Journal of the Endocrine Society
Published
2025-10-01
DOI
https://doi.org/10.1210/jendso/bvaf149.076
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

OR21-05 A Multinational Study of Serum Metabolomics and Lipidomics in the Pathophysiology and Non-invasive Diagnosis of Metabolic Dysfunction-Associated Steatotic Liver Disease

Christos Socrates Mantzoros, Georgios Markakis, Matteo Garcovich, Konstantinos Stefanakis et al.
Journal of the Endocrine Society
Liver Disease Diagnosis and Treatment
article

OR21-05 A Multinational Study of Serum Metabolomics and Lipidomics in the Pathophysiology and Non-invasive Diagnosis of Metabolic Dysfunction-Associated Steatotic Liver Disease

Christos Socrates Mantzoros, Georgios Markakis, Matteo Garcovich, Konstantinos Stefanakis, Nikolaos Perakakis, George Papatheodoridis, Laura Riccardi, Ornella Verrastro, Geltrude Mingrone, Mohammed Eslam, Jacob George
article en

Abstract

Abstract Disclosure: K. Stefanakis: None. N. Perakakis: None. O. Verrastro: None. M. Garcovich: None. L. Riccardi: None. M. Eslam: None. G.E. Markakis: None. G. Papatheodoridis: None. G. Mingrone: None. J. George: None. C.S. Mantzoros: None. The growing burden of metabolic dysfunction-associated steatotic liver disease (MASLD) and steatohepatitis (MASH), coupled with novel therapies targeting fibrotic MASH (F2–F3), underscores the need for deeper mechanistic insights and improved non-invasive test (NITs). In a multi-national biobank, we enrolled 443 biopsy-proven individuals (81 healthy controls, 362 patients, including 162 with MASH F≥2) across three countries (Italy, Greece, Australia) and two clinical center types (bariatric, gastroenterology-hepatology). A total of 839 metabolites and 840 lipid species were quantified in the serum of all 443 participants by ultra-high-performance liquid chromatography–tandem mass spectrometry. Beyond absolute changes, we employed supervised/unsupervised classifiers, clustering, and pathway enrichment analyses to map metabolites and lipids across the MASLD histological continuum. Early steatosis and MASLD were characterized by a pronounced surge in triglycerides conjugated with 16:0 (palmitic acid), together with elevated ceramides and inflammatory markers. Transition to MASH was marked by elevated BCAAs, bile acid metabolites, sphingolipids, urea cycle intermediates, and xenobiotic compounds (mannonate, hydroxybenzoate), alongside a further spike in triglycerides. In MASH F2–F3, 108 metabolites were markedly upregulated—notably 3-ureidopropionate (uracil pathway) and kynurenine (tryptophan pathway)—and 137 lipid species (chiefly glycerols with saturated fatty acids), whereas 21 metabolites (purines, n-acetylmethionine, steroidogenic intermediates) and 177 lipids (mainly phospholipids and ceramides) were significantly reduced. With advanced fibrosis (F3–F4), the triglyceride surge attenuated, yet inflammation persisted, coupled with dysregulated xenobiotic metabolism and depletion of >10 fibrinopeptide species, indicative of impaired coagulation. Weighted correlation analyses unveiled distinct modules of functionally and structurally similar metabolites and lipids co-varying with transaminases, GDF-15, activins and follistatins in significant fibrosis; separate from obesity-driven steatosis and early inflammation. Building on these comprehensive profiles, we developed categorical gradient-boosting models (4:1 training–validation split, repeated cross-validation with random resampling) using routine clinical variables (e.g., transaminases) and select metabolites such as 3-ureidopropionate, kynurenine, and sphingadienine. These models achieved cross-validated AUCs exceeding 88%—and up to 94%—in the validation cohort, outperforming over 20 established imaging- and biomarker-based NITs for detecting MASH, at-risk MASH, and F≥3. These findings define a novel paradigm for delineating mechanistic pathways that could reveal future therapeutic targets and streamline the development of accurate NITs. Presentation: Saturday, July 12, 2025

Journal of the Endocrine SocietyVol. 9(Supplement_1)
Università Cattolica del Sacro Cuore (IT), The University of Sydney (AU), Harvard University (US), National and Kapodistrian University of Athens (GR), Agostino Gemelli University Polyclinic (IT), University Hospital Carl Gustav Carus (DE), Athens State University (US), Technische Universität Dresden (DE)
Openalex Percentile: Top 59%
Liver Disease Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.