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Gut microbiota-derived TMA/TMAO and IRAK4 signaling in type 2 diabetes: Current evidence, knowledge gaps and future
Arnabjyoti Deva Sarma1, Moitrayee Devi1, Dinesh Kumar2
1Faculty of Allied and Healthcare Sciences, Assam down town University, Sankar Madhab Path, Gandhi Nagar, Panikhaiti, Guwahati, Assam 781026, India.
Abstract:
Diabetes mellitus type 2 (T2DM) is now considered an immunometabolic condition with a long-term low-grade inflammatory state, insulin resistance, and host-microbiome interactions. Emerging evidence suggests that gut microbiota-derived trimethylamine (TMA), its hepatic metabolite trimethylamine N-oxide (TMAO), and IRAK4-mediated innate immune signaling may contribute to metabolic inflammation and insulin resistance. However, direct mechanistic evidence linking these components remains limited, and most available data originate from preclinical studies. Gut microbiota produces TMA based on the nutrients present in the diet, such as choline, betaine, and l-carnitine, which are then oxidized in the liver to trimethylamine N-oxide (TMAO), a metabolite linked to inflammation, metabolic maladaptation, and cardiovascular issues. IRAK4, a signaling mediator of Toll-like receptor and interleukin-1 receptor, may induce NF- kB and MAPK signaling, which may contribute to metaflammation and defective insulin signaling. This overview highlights existing evidence of the TMAIRAK4 axis in the pathogenesis and insulin resistance in T2DM. We discuss current evidence suggesting that TMA/TMAO may influence innate immune signaling and inflammatory pathways associated with insulin resistance. Special attention is given to the interference with the IRSPI3KAkt-pathway by inflammatory signaling mediated by IRAK4. We also consider new treatment approaches, such as IRAK4 inhibitors, control of microbial TMA synthesis, and FMO3-based interventions. Lastly, we underscore important translational issues, such as inconsistency in the evidence about TMAO biology, microbiome diversity, insufficient human validation, and the necessity of multi-omics-based precision methods in patient stratification and personalized treatment.
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