Obesity and type 2 diabetes are major global health concerns. Emerging research highlights the gut microbiota's crucial role in metabolic health, influencing energy harvest and glucose metabolism. Inconsistencies in previous studies regarding the specific gut microbiota signatures associated with type 2 diabetes necessitate further investigation. While the association between the gut microbiota and type 2 diabetes is well-established, the variability in individual responses to dietary interventions, such as prebiotic supplementation, remains a significant challenge. This study aimed to address this variability by exploring the hypothesis that differences in the gut microbiome and metabolome (MIME) profiles could explain the variable responses to inulin supplementation. Specifically, the study hypothesized that MIME composition would differ across lean, obese, and diabetic individuals; that specific MIME patterns would explain the differential responses to inulin; and that the response to inulin could be predicted from baseline MIME signatures and clinical characteristics. Understanding these relationships is crucial for developing personalized nutritional interventions to effectively manage type 2 diabetes.

Previous studies have established a strong link between gut microbiota composition and both obesity and type 2 diabetes. Turnbaugh's seminal work demonstrated an obesity-associated gut microbiome with enhanced energy-harvesting capacity. Subsequent research confirmed differences in microbiota composition between lean and obese individuals, with further studies showing associations between gut microbiota and type 2 diabetes development. However, the findings on specific gut microbiota signatures in type 2 diabetes are inconsistent, with varying reports on alpha-diversity and specific taxa involved. For instance, some studies report a lower alpha-diversity in type 2 diabetes patients, while others find no significant difference compared to non-diabetic individuals. Similarly, the role of specific bacterial genera such as *Firmicutes*, *Bacteroidetes*, and *Proteobacteria* in the pathogenesis of type 2 diabetes remains debated. The impact of diet on shaping the gut microbiome and its subsequent influence on metabolic outcomes further complicates the picture. The variable responses to dietary fiber interventions, including inulin supplementation, highlight the need for personalized approaches in managing type 2 diabetes. Identifying microbial mediators of the beneficial effects of dietary fiber is essential for developing individualized treatment strategies.

This study employed a two-stage design: a cross-sectional case-control study and a prospective interventional trial. The cross-sectional study involved 49 newly diagnosed pre/diabetes patients (DM), 66 metabolically healthy overweight/obese (OB), and 32 healthy lean (LH) volunteers. Clinical variables, dietary intake, gut microbiome (16S rRNA sequencing), and fecal/serum metabolome (metabolomics profiling) were collected and analyzed. The prospective interventional trial enrolled 27 DM participants who received 10 g/day of inulin supplementation for three months. Baseline and post-intervention assessments mirrored those of the cross-sectional study, with additional measures including indirect calorimetry and a two-step glucose clamp. Gut microbiome analysis was performed using 16S rRNA gene sequencing, with data processed using DADA2. Plasma short-chain fatty acids (SCFAs) were analyzed by LC-MS. Fecal volatile organic compounds (VOCs) were analyzed using gas chromatography-time-of-flight mass spectrometry. Serum metabolites were analyzed using NMR spectroscopy. Statistical analysis involved centered log-ratio transformation for compositional data, LASSO regression for classification, and linear regression to identify predictors of metabolic response to inulin. Ethical approval was obtained from the Ethics Committee of University Hospital Kralovske Vinohrady.

The observational study revealed distinct MIME compositions among the three groups (LH, OB, DM), with OB exhibiting a profile closer to DM than LH. Alpha-diversity was significantly lower in OB and DM compared to LH. Several bacterial taxa showed significant differences in abundance across the groups, with some butyrate-producing bacteria being less abundant in the DM and OB groups. Fecal VOCs also showed differences between the groups. Serum metabolomics revealed distinct metabolic profiles, with overlapping signatures between OB and DM, highlighting the stronger influence of obesity compared to glycemic status. The interventional study showed that inulin supplementation significantly improved glycemic indices in the DM group, although the response was highly variable. The improved glycemic outcomes were associated with favorable baseline glycemic status and specific MIME signatures. Specifically, the abundance of certain bacterial taxa (*Blautia*, *Eubacterium halii* group, *Lachnoclostridium*, *Ruminiclostridium*, *Dialister*, *Phascolarctobacterium*), serum concentrations of branched-chain amino acid (BCAA) derivatives and asparagine, and fecal concentrations of indole and other VOCs were associated with improved glycemic response to inulin.

This study’s findings highlight the complex interplay between obesity, gut microbiota, and metabolic response to dietary interventions. The dominance of obesity over glycemic status in determining MIME signatures underscores the importance of addressing obesity in the management of type 2 diabetes. The large inter-individual variability in response to inulin supplementation emphasizes the need for personalized approaches. The identification of baseline MIME signatures and clinical characteristics as predictors of inulin response opens up new avenues for personalized nutrition. The association of improved glycemic response with higher baseline asparagine and lower *Dialister* or *Blautia* suggests potential mechanistic links between these factors and inulin’s metabolic effects. Further investigation is needed to elucidate these mechanisms and to validate the identified biomarkers in larger, independent cohorts.

This study demonstrated that obesity is a more significant determinant of MIME signatures than impaired glucose metabolism. The variable response to inulin supplementation in individuals with newly diagnosed pre/diabetes can be partially predicted using baseline clinical characteristics and MIME signatures. These findings suggest the potential for personalized nutritional interventions tailored to individual multi-omics profiles to enhance treatment efficacy in early-stage diabetes. Further validation in larger cohorts is needed.

The study's limitations include a relatively small sample size, limiting the generalizability of the findings. The cross-sectional nature of the observational study does not allow causal inferences. The age difference between the LH group and the other groups might have introduced some bias. The lack of dietary control in the interventional trial could have influenced the results. Finally, the absence of a control group in the interventional study limits the definitive conclusion on causality.