ArticleNutrition journal2025
Development and validation of a multimodal model integrating gut microbiota and metabolite for identifying sarcopenia in patients with MASLD: a study from two centers in China.
Article in Nutrition journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
BACKGROUND AND
aimsMetabolic dysfunction-associated steatotic liver disease (MASLD) is a common chronic liver disease worldwide, and identifying sarcopenia is critical since it is correlated with poor prognosis. Little is known about mechanistic alterations in the pathogenesis of this condition. This study aimed to explore the alterations in the gut microbiome and metabolome in patients with sarcopenia and develop a predictive model.
methodsWe performed shotgun metagenomic sequencing and untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomic profiling of fecal samples from the discovery cohort (70 patients without sarcopenia, 30 with sarcopenia). A microbiota-metabolite score (MM score) was developed using LASSO regression to identify key microbiome and metabolite features associated with sarcopenia. A multimodal prediction model incorporating the MM score and clinical parameters was then developed and validated in an independent cohort of 50 patients.
resultsPatients with sarcopenia exhibited altered gut microbiota and metabolomic profiles, with significantly elevated Enterococcus faecium and Bacteroides vulgatus species, and elevated bile acids. Integration of the MM score with clinical variables (age, BMI, AST, presence of diabetes) resulted in a multimodal model with an AUC of 0.911, outperforming existing models including FIB-4 (AUC 0.765), NFS (AUC 0.724), and using only MM score alone (AUC 0.818). In a prospective validation cohort, the multimodal model demonstrated superior diagnostic performance (AUC 0.897), with significant improvements in clinical utility as evidenced by calibration curves and decision curve analysis.
conclusionsThis study developed a novel multimodal model combining gut microbiome, metabolomics, and clinical data for accurate prediction of sarcopenia, offering a promising approach for early identification of high-risk MASLD patients with sarcopenia.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.