# Serum-urine metabolic integration via UPLC-QTOF/MS uncovers shared pathway biomarkers for cirrhosis diagnosis

## TL;DR

This study uses metabolic profiling of serum and urine to identify shared biomarkers and pathways for diagnosing liver cirrhosis.

## Contribution

The study identifies four shared metabolites and three metabolic pathways across serum and urine for noninvasive cirrhosis diagnosis.

## Key findings

- 55 serum and 51 urine metabolites were dysregulated in cirrhosis patients.
- Four shared metabolites were identified in both serum and urine.
- Three co-regulated pathways were linked to cirrhosis progression.

## Abstract

Liver cirrhosis is the terminal stage of chronic liver disease, which is marked by high morbidity and mortality in its advanced phases. Although liver biopsy still serves as the gold - standard diagnostic method, the detection of serum and urine metabolites holds great promise for the identification of cirrhosis.

Untargeted metabolomics analysis was carried out using ultra - performance liquid chromatography coupled with quadrupole time - of - flight mass spectrometry (UPLC - QTOF/MS). We compared the serum and urine metabolic profiles between 30 healthy individuals and 28 liver cirrhosis patients to screen for biomarkers associated with liver cirrhosis.

A total of 55 endogenous metabolites showed dysregulation in serum, and 51 did so in urine. Four shared differential metabolites—glycoursodeoxycholic acid, urobilin, glycocholic acid, and urobilinogen—were identified in both biofluids. Pathway enrichment analysis revealed three co - regulated metabolic pathways: tryptophan metabolism, glycerophospholipid metabolism, and porphyrin metabolism (p < 0.05).

This study delineates the distinct metabolic signatures of cirrhosis and proposes a diagnostic strategy based on dual - biofluid analysis. The intersectional biomarkers and pathways elucidate the mechanisms linking bile acid homeostasis and hemoprotein catabolism to cirrhotic progression, offering a noninvasive approach for clinical detection.