AI Article Synopsis
- - The study investigated potential biomarkers for metabolic dysfunction-associated steatohepatitis (MASH) using proteomic analyses of plasma and liver tissue from 64 patients undergoing liver biopsy for MASLD diagnosis.
- - Researchers found that 20 plasma proteins were significantly altered in MASH patients, with a notable AUROC of 0.671 for MASH detection; however, these proteins did not align with liver tissue protein changes.
- - A subgroup of 10 plasma proteins showed promise, yielding a higher AUROC of 0.793 and suggesting that certain plasma proteins reflecting liver tissue changes could enhance MASH detection accuracy.
Article Abstract
Background: Biomarkers for metabolic dysfunction-associated steatohepatitis (MASH) have been considered based on proteomic and lipidomic data from plasma and liver tissue without clinical benefits. This study evaluated proteomics-based plasma and liver tissue biomarkers collected simultaneously from patients with metabolic dysfunction-associated steatotic liver disease (MASLD).
Methods: Liver tissue and plasma samples were collected during liver biopsy to diagnose MASLD. Untargeted proteomics was performed on 64 patients.
Results: Twenty plasma proteins were up- or downregulated in patients with MASH compared with those without MASH. The potential biomarkers utilizing the best combinations of these plasma proteins had an area under the receiver operating curve (AUROC) of 0.671 for detecting those with MASH compared with those without it. However, none of the 20 plasma proteins were represented among the significantly regulated liver tissue proteins in patients with MASH. Ten of them displayed a trend and relevance in liver tissue with MASLD progression. These 10 plasma proteins had an AUROC of 0.793 for MASH identification and higher positive and negative predictive values.
Conclusion: The plasma and liver protein expressions of patients with MASH were not directly comparable. Plasma protein biomarkers that are also expressed in liver tissue can help improve MASH detection.
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| http://dx.doi.org/10.1002/prca.202300236 | DOI Listing |
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