Novel diagnostic and treatment strategies are required due to the drastic rise in insulin resistance, which is a risk factor for metabolic syndrome and Type 2 diabetes. Personalized insights into the development and management of insulin resistance are provided by integrated multi-omics technologies, namely in the areas of metabolomics and gut microbiome characterization. The synergistic interaction between gut-derived metabolites and metabolomic patterns as potential predictive indicators for insulin resistance is explored in this research field. Early diagnosis could be revolutionized by the use of non-invasive biomarkers, such as circulating non-coding RNAs and microbial metabolites. Furthermore, individualized dietary approaches to manage insulin resistance in both obese and non-obese patients may be provided by personalized nutritional interventions that focus on the relationships between the microbiota and metabolome. Finally, real-time assessment of dietary interventions is made possible by longitudinal tracking employing multi-omics, which improves accuracy and efficacy in the management of insulin resistance.

The increasing incidence of insulin resistance (IR), primarily caused by sedentary lifestyles, poor dietary practices, and obesity, presents a serious threat to world health. There are still limitations in the early diagnosis and efficient management of IR despite advancements in treatment. Leveraging integrated multi-omics techniques, with an emphasis on the interaction between gut microbiota characterization and metabolomics, to provide tailored dietary recommendations, is one feasible answer. The objective of this study topic is to investigate the potential of gut-derived metabolomic patterns, specifically microbial metabolites, as predictive biomarkers for insulin resistance. This could offer a non-invasive means of early diagnosis. These biomarkers have the potential to enable personalized, real-time IR monitoring through longitudinal investigations when combined with circulating non-coding RNA. Personalized nutrition plans based on gut microbiota interactions with metabolic processes could also revolutionize the way we treat and maintain insulin resistance in both obese and non-obese patients. If improved multi-omics is used to follow such interventions properly, the results in preventing and treating insulin resistance may be more accurate and long-lasting.

The Research Topic, "Integrated Multi-Omics and Gut Microbiota Profiling for Personalized Diagnosis and Nutritional Management of Insulin Resistance," encourages contributions that investigate new approaches to insulin resistance diagnosis and nutritional management using multi-omics and microbiota analysis. Key themes include:

• Metabolomics and Gut Microbiota Synergy: Investigating how metabolomic patterns from gut-derived metabolites can serve as biomarkers for predicting insulin resistance.

• Non-Invasive Biomarkers: Highlighting the role of microbial metabolites and circulating non-coding RNA in providing non-invasive, early diagnostic tools for insulin resistance.

• Personalized Nutritional Interventions: Developing and tailoring dietary strategies for managing insulin resistance, with a focus on interactions between the gut microbiome and metabolome in both obese and non-obese individuals.

• Longitudinal Tracking: Using multi-omics to monitor real-time changes in metabolomics and gut microbiota during dietary interventions.

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Integrated Multi-Omics and Gut Microbiota Profiling for Personalized Diagnosis and Nutritional Management of Insulin Resistance