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Prediagnostic Plasma Metabolite Profiles and Prediction of Hepatocellular Carcinoma Risk: The Multiethnic Cohort
Sihao Han1, Jesse A Goodrich1,2, Hongxu Wang1
1Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California.
Background:
Hepatocellular carcinoma (HCC) is the most common primary liver cancer and often arises in cirrhosis cases. Current surveillance methods, including ultrasonography and α-fetoprotein, have limited sensitivity for early detection. Blood metabolomics may improve HCC risk prediction. We aimed to identify pre-diagnostic plasma metabolites associated with HCC risk and evaluate whether cirrhosis-related metabolites enhance prediction beyond established risk factors in a multiethnic population.
Methods:
We analyzed data from a nested case-control study with pre-diagnostic blood samples in the Multiethnic Cohort, including 240 HCC cases, 151 cirrhosis cases, and individually matched controls. Metabolome-wide association studies and pathway enrichment analyses were performed, followed by feature selection in the cirrhosis samples to construct HCC prediction models.
Results:
Of 294 metabolites analyzed, 53 were significantly associated with HCC after false discovery rate correction (odds ratios: 0.25-3.93). Pathway analyses highlighted perturbations in lipid and amino acid metabolism. Two cirrhosis-associated metabolites, glutamate and glycochenodeoxycholate, were consistently selected and improved HCC prediction. Adding these metabolites to known risk factors (age, sex, race/ethnicity, study area, BMI, smoking, alcohol consumption, and diabetes) increased the AUC from 0.64 to 0.73 (P < 0.001).
Conclusions:
Pre-diagnostic metabolomic profiling revealed metabolic alterations linked to HCC risk, emphasizing dysregulated amino acid and bile acid pathways within the cirrhosis context.
Impact:
Glutamate and glycochenodeoxycholate improved HCC risk prediction beyond established factors, supporting biologically plausible links between hepatic metabolic dysfunction and hepatocarcinogenesis. These findings highlight the potential of metabolomic biomarkers to enhance surveillance and risk stratification among patients with cirrhosis.