Serum Citramalic Acid Emerges as Key Predictor of Fatty Liver Disease Trajectories

A large population-based cohort study has identified a multi-omics signature that tracks the eight-year course of metabolic dysfunction-associated steatotic liver disease (MASLD), pointing to serum citramalic acid as the single strongest molecular contributor to disease severity. The findings, published in BMC Medicine, combine gut microbial sequencing with targeted metabolite profiling to build risk scores that predict both new-onset and persistent disease.

The research drew on 1,694 participants from the Guangzhou Nutrition and Health Study. Researchers profiled gut metagenomics alongside targeted metabolomics of fecal and serum samples. Liver fat was quantified using MRI-derived hepatic steatosis measures, while disease trajectories over eight years were reconstructed from repeated ultrasound examinations, allowing the team to assess disease progression over time.

By integrating these data layers, the investigators identified nine microbial species, thirteen fecal metabolites, and thirteen serum metabolites associated with MASLD severity. Serum citramalic acid ranked highest among all features, making it the standout candidate biomarker in the analysis.

The predictive power of the molecular signatures was tested against the long-term disease course. Risk scores built from microbial, fecal metabolite, and serum metabolite data each predicted incident MASLD over eight years, with per-standard-deviation hazard ratios of 1.04, 1.18, and 1.21 respectively. The associations were stronger for persistent MASLD, with per-standard-deviation odds ratios of 1.27, 1.62, and 2.23.

Beyond prediction, multi-omics clustering revealed three distinct MASLD subtypes with different metabolic profiles. Metabolic dysfunction worsened progressively from Subtype A through Subtype C, a trend that was statistically significant. Subtype C carried an elevated risk of type 2 diabetes, with an odds ratio of 2.70 and a 95 percent confidence interval of 1.61 to 4.55.

Key results were replicated in an external validation cohort.

To probe whether citramalic acid plays a role beyond correlation, the team administered the compound to mice fed a high-fat diet. The supplementation exacerbated metabolic dysfunction and hepatic steatosis in the animals and disrupted hepatic pathways involved in lipid metabolism and cellular stress responses. These animal experiments provide mechanistic support for citramalic acid as a contributor to disease progression, though findings in mice do not establish effects in humans.

MASLD is recognized as a heterogeneous condition, and early predictors for risk stratification have remained limited. The study’s contribution lies in linking longitudinal imaging-based disease trajectories to molecular profiles spanning the gut microbiome and circulating and fecal metabolites, an approach that captures the disease’s variability rather than treating it as a single entity.

The authors conclude that the identified multi-omics features provide early biomarkers for risk stratification and potential precision prevention of MASLD.

Subject of Research: Multi-omics predictors and subtypes of metabolic dysfunction-associated steatotic liver disease and the role of serum citramalic acid

Article Title: Multi-omics signatures of 8-year trajectories and heterogeneity of metabolic dysfunction-associated steatotic liver disease reveal serum citramalic acid as a key contributor

Article References: Zhong, H., Huang, L., Jiang, Z., Ru, D.-M., Wang, X., Mamuti, R., Zhou, F., Miao, Z., Xi, Y., Zeng, F.-F., Yan, Y., Hu, W., Xu, F., Yang, S.-H., Zheng, J.-S., Huang, Y., Dong, X.-L., & Chen, Y.-M. (2026). Multi-omics signatures of 8-year trajectories and heterogeneity of metabolic dysfunction-associated steatotic liver disease reveal serum citramalic acid as a key contributor. BMC Medicine. https://doi.org/10.1186/s12916-026-05339-0

Image Credits: AI Generated

DOI: 10.1186/s12916-026-05339-0

Keywords: MASLD, fatty liver disease, citramalic acid, metabolomics, gut microbiome, multi-omics, risk stratification, type 2 diabetes, hepatic steatosis, cohort study, precision prevention, signatures