Abstract
Background: Mitochondrial dysfunction with oxidative stress contributes to nonalcoholic fatty liver disease (NAFLD) progression. We investigated the steatosis predictive efficacy of a novel non-invasive diagnostic panel using metabolic stress biomarkers. Methods: Altogether, 343 subjects who underwent magnetic resonance imaging-based liver examinations from a population-based general cohort, and 41 patients enrolled in a biopsy-evaluated NAFLD cohort, participated in the development and validation groups, respectively. Serologic stress biomarkers were quantitated by enzyme-linked immunosorbent assay. Results: Multivariate regression showed that waist-to-hip ratio, fibroblast growth factor (FGF) 21, FGF19, adiponectin-to-leptin ratio, insulin, albumin, triglyceride, total-cholesterol, and alanine-aminotransferase were independent predictors of steatosis (rank-ordered by Wald). The area under receiver-operator characteristics curve [AUROC (95%CI)] of the metabolic stress index for steatosis (MSI-S) was 0.886 (0.85−0.92) and 0.825 (0.69−0.96) in development and validation groups, respectively. MSI-S had higher diagnostic accuracy (78.1%−81.1%) than other steatosis indices. MSI-S notably differentiated steatosis severities, while other indices showed less discrimination. Conclusion: MSI-S, as a novel non-invasive index, based on mitochondrial stress biomarker FGF21 effectively predicted steatosis. Furthermore, MSI-S may increase the population that could be excluded from further evaluation, reducing unnecessary invasive investigations more effectively than other indices.
Original language | English |
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Article number | 896334 |
Journal | Frontiers in Endocrinology |
Volume | 13 |
DOIs | |
Publication status | Published - 2022 May 19 |
Bibliographical note
Funding Information:This research was funded by the Medical Research Center Program (NRF-2017R1A5A2015369) and in part by the Basic Science Research Program (NRF-2018R1C1B6005036) from the Ministry of Science and ICT, Republic of Korea.
Publisher Copyright:
Copyright © 2022 Chang, Ahn, Kang, Koh, Kim, Baik, Huh, Lee, Kim and Park.
All Science Journal Classification (ASJC) codes
- Endocrinology, Diabetes and Metabolism