Early prediction of incident liver disease using conventional risk factors and gut-microbiome-augmented gradient boosting.

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 i

SUBMITTER: Liu Y 

PROVIDER: S-EPMC9097589 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature