Metabolic Stress Index Including Mitochondrial Biomarker for Noninvasive Diagnosis of Hepatic Steatosis

Jae Seung Chang, Jhii Hyun Ahn, Seong Hee Kang, Sang Baek Koh, Jang Young Kim, Soon Koo Baik, Ji Hye Huh, Samuel S. Lee, Moon Young Kim, Kyu Sang Park

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2 Citations (Scopus)


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 languageEnglish
Article number896334
JournalFrontiers in Endocrinology
Publication statusPublished - 2022 May 19

Bibliographical note

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


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