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Circulating microRNAs as potential non-invasive biomarkers for diagnosis and severity assessment of Metabolic Dysfunction-Associated Steatotic Liver Disease: a case–control study

Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease (NAFLD), has become a major global health issue, affecting nearly 30% of the population, especially in developed countries. A Delphi consensus in June 2023 redefined NAFLD as MASLD to better reflect its metabolic origins. MASLD is diagnosed by identifying hepatic steatosis through imaging or biopsy, along with at least one cardiometabolic risk factor. It is associated with liver-related complications such as fibrosis, cirrhosis, and hepatocellular carcinoma (HCC), and extra hepatic conditions like cardiovascular and kidney disease, and metabolic syndrome. MicroRNAs (miR), which regulate gene expression and influence lipid metabolism, inflammation, and fibrosis, may serve as non-invasive biomarkers for MASLD. We aimed to assess the functional significance of circulating miR as accessible serum biomarkers for MASLD diagnosis. Methods In this case–control study, 30 MASLD patients and 20 healthy controls were evaluated. Diagnosis was based on clinical (anthropometric measures), biochemical, and imaging findings and severity was assessed using vibration-controlled transient elastography (VCTE). Serum levels of seven circulating MiRs were measured and correlated with metabolic and hepatic parameters. Results MASLD patients showed significantly elevated BMI, waist circumference, cholesterol, and triglycerides, and reduced HDL levels. miR-34a, miR-122, miR-21, miR-223, and miR-193a-5p were up regulated, while miR-422a and miR-29a were down regulated. miR-34a was the most predictive biomarker, followed by miR-223. Conclusion Specific circulating miR are closely linked to MASLD severity and may serve as effective non-invasive biomarkers for diagnosis, staging, and disease monitoring.
Language: English
Subfield: Epidemiology
Field: Medicine
Open Access status: diamond
OpenAlex ID: W4413878526
FWCI: 2.492
Cites: 66
Cited by: 4
Related to: 10