Work

NMR-Based Metabolic Profiling of Biobank Derived Blood Samples for the Identification of Liver Disease Biomarkers

Year: 2026

Type: article

Abstract: Liver disease remains a leading cause of global cancer mortality and predominantly originates from chronic liver cirrhosis. Current surveillance strategies often suffer from suboptimal sensitivity which necessitates the discovery of robust biomarkers for early detection. In this study we utilized blood resources from the National Biobank of Korea to evaluate the diagnostic potential of Nuclear Magnetic Resonance spectroscopy-based metabolomics in patients with cirrhosis and liver cancer. We aimed to identify specific biomarkers and investigate their correlation with clinical blood parameters by comparing the metabolic profiles of disease and healthy control groups. Multivariate statistical analysis demonstrated significant metabolic distinctions between liver disease patients and healthy controls. While the models successfully differentiated disease states the global metabolic landscape exhibited an overlap between cirrhosis and cancer groups suggesting a shared pathological background driven by systemic metabolic shifts. Quantitative assessment identified specific metabolic alterations characterizing the disease progression. We observed a marked accumulation of lactate and phenylalanine reflecting the Warburg effect and impaired hepatic hydroxylation capacity. Conversely branched chain amino acids specifically valine and isoleucine were significantly depleted in the disease groups indicating systemic metabolic stress. Receiver operating characteristic analysis revealed that a combinatorial biomarker panel yielded superior diagnostic accuracy compared to single markers. Furthermore, the validity of our metabolic profiling was corroborated by a strong correlation between the values predicted from metabolic profiles and clinically measured physiological parameters. Overall, our findings confirm the feasibility of utilizing retrospective biobank resources for high resolution metabolic phenotyping.

Source: Biomolecules & Therapeutics

DOI: 10.4062/biomolther.2026.084

Authors: Munki Choo, Chaeyoung Lee, Sunghyouk Park, Hyuk Nam Kwon

Institutions: Kyungil University, University of Ulsan, Seoul National University

Language: English

Topic: Metabolomics and Mass Spectrometry Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funders: University of Ulsan, Ajou University