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A Microbiome Toolkit for Multiomics Discovery Applied to Metabolic Diseases

Joshua B. Simpson, Joseph J. Garder, Joseph R. McGinley, Alexis C. Wood, Alain Bertoni, Yii-Der Ida Chen, Jerome I. Rotter, Kristi L. Hoffman, Lindsey B. Cundra, Vincent J. Maffei, Kari E. Wong, Elizabeth T. Jensen, Mark O. Goodarzi

Type 2 diabetes (T2D) and metabolic dysfunction-associated steatotic liver disease (MASLD) represent a major overlapping global health burden, with approximately 537 million adults living with T2D and 30–38% of the population diagnosed with MASLD. T2D often triggers MASLD and increases liver-related morbidity, while MASLD heightens the risk of developing T2D. Recent research implicates the human gut microbiome in the progression of these disorders through the gut-liver axis. Metagenomic studies have identified microbial gene signatures associated with host phenotypes central to both these diseases, specifically insulin resistance and hepatic steatosis. However, the microbial functions driving these diseases remain unclear. Metabolomics offers a promising avenue for defining these pathways, but integrating metagenomic and metabolomic data within either disease context remains technically and computationally challenging. This complexity limits the translation of multi-omics insights into actionable strategies for disease prevention and management.

Identifying-Changes-in-Phytocannabinoid-and-Endocannabinoid-Metabolites

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