Evidence mapPaperPMID 42375094Full record

ArticleBiomolecules & therapeutics2026

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

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

Abstract read
In one paragraph

Article in Biomolecules & therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Munki ChooDepartment of Paramedicine, Kyungil University, Gyeongsan 38428, Republic of Korea.
Chaeyoung LeeDepartment of Biological Sciences, University of Ulsan, Ulsan 44610, Republic of Korea.
Sunghyouk ParkNatural Product Research Institute, College of Pharmacy, Seoul National University, Seoul 08826, Republic of Korea.
Hyuk Nam KwonDepartment of Biological Sciences, University of Ulsan, Ulsan 44610, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BiobankCirrhosisDiagnostic markersLiver cancerNMR-based metabolomics

Identifiers

PMID42375094
PMCPMC13324540

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.