ArticleCell metabolism2022
Early prediction of incident liver disease using conventional risk factors and gut-microbiome-augmented gradient boosting.
Article in Cell metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 2 of them syntheses that pooled it.
What it found
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Who cites it
56 citing papers in PubMed, 2 syntheses or guidelines pooled it, 84 citations in OpenAlex.
- The interactions between host genome and gut microbiome increase the risk of psychiatric disorders: Mendelian randomization and biological annotation.Brain, behavior, and immunity · 2023Pooled it
- Targeting Gut Microbiota to Treat Hypertension: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Weight loss and alcohol reduction synergize for hepatic steatosis remission in elderly patients with metabolic alcohol-associated liver disease (MetALD): a retrospective cohort study.International journal of obesity (2005) · 2026Article
- Article
- Multi-kingdom profiling reveals altered gut phage-bacteria-metabolite interactions in MASLD.Nature communications · 2026Article
- Mycobiome dysbiosis and genetic predisposition to elevated IL-17A contribute to fibrosis in MASLD.JHEP reports : innovation in hepatology · 2026Article
- Value of Multiomics Over Clinical Risk Factors in Hypertension Prediction.Hypertension (Dallas, Tex. : 1979) · 2026Article
- Clinical and microbial correlates of response to lifestyle intervention in pediatric metabolic dysfunction-associated steatotic liver disease.Gut pathogens · 2026Article
- A community screening tool for neuropsychiatric symptoms in the elderly: integrating cortisol, microbiome, and social factors with machine learning.Translational psychiatry · 2026Observational
- Organ cross-talk: molecular mechanisms, biological functions, and therapeutic interventions for diseases.Signal transduction and targeted therapy · 2026Review
- Duodenal Fluid Microbiome Diversity and Pancreatic Cyst Status Among Patients Undergoing Pancreatic Surveillance.Gastro hep advances · 2026Article
- Synergistic effects ofFrontiers in nutrition · 2026Article
- Mechanistic insights into microbiome-dependent and personalized responses to dietary fibre in a randomized controlled trial.medRxiv : the preprint server for health sciences · 2025Article
- Beyond Discrete Diagnoses: Conceptualizing Obesity-associated Metabolic Disorders as a Unified, Dynamic Continuum.Current obesity reports · 2025Review
- Impact of gut microbiome on outcomes following endoscopic interventions in gastrointestinal disease.World journal of gastrointestinal endoscopy · 2025Article
- A hidden confounder for microbiome studies: medications used years before sample collection.mSystems · 2025Article
- The combination of dietary active dry yeast andAnimal nutrition (Zhongguo xu mu shou yi xue hui) · 2025Article
- Revolutionizing gastroenterology and hepatology with artificial intelligence: From precision diagnosis to equitable healthcare through interdisciplinary practice.World journal of gastroenterology · 2025Review
- Correlation Between Fecal Microbiota and Corticosteroid Responsiveness in Primary Immune Thrombocytopenia: an Exploratory Study.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
20 authors at 10 institutions in 4 countries.
Funding
Abstract
The gut microbiome has shown promise as a predictive biomarker for various diseases. However, the potential of gut microbiota for prospective risk prediction of liver disease has not been assessed. Here, we utilized shallow shotgun metagenomic sequencing of a large population-based cohort (N > 7,000) with ∼15 years of follow-up in combination with machine learning to investigate the predictive capacity of gut microbial predictors individually and in conjunction with conventional risk factors for incident liver disease. Separately, conventional and microbial factors showed comparable predictive capacity. However, microbiome augmentation of conventional risk factors using machine learning significantly improved the performance. Similarly, disease-free survival analysis showed significantly improved stratification using microbiome-augmented models. Investigation of predictive microbial signatures revealed previously unknown taxa for liver disease, as well as those previously associated with hepatic function and disease. This study supports the potential clinical validity of gut metagenomic sequencing to complement conventional risk factors for prediction of liver diseases.
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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.