1203-P: Multiomics Imbalances Are Associated with Glycemic Control in Patients with Type 1 Diabetes

Introduction: Previous studies have indicated associations between the gut microbiota, metabolites, lipids and the onset of type 1 diabetes (T1D). We aimed to further investigate the characteristics of the gut microbiota, metabolites, and lipids in patients with T1D at different glycemic levels.

Methods: We divided 72 patients with T1D into two groups based on hemoglobin A1c (HbA1c) levels : one group with good glycemic control (GC, HbA1c < 7%, n=36) and another with poor glycemic control (PGC, HbA1c ≥ 7%, n=36). We conducted 16S rRNA sequence analysis of their fecal microbiota and analyzed serum metabolites and lipids. Differential expression of microbiota, metabolites, and lipids was identified, and we annotated associated pathways through differential metabolite and lipid analysis.

Results: The two groups with different glycemic control statuses exhibited distinct characteristics in microbiota, metabolites, and lipids. linear discriminant analysis, shapley additive explanations algorithm and machine learning algorithms revealed the enrichment of Bacteroides_nordii, Bacteroides_cellulosilyticus in the GC group, while Bacteroides_coprocola and Sutterella_wadsworthensis enriched in the PGC group. Functionally, several metabolic sets like fatty acid biosynthesis, glycerol phosphate shuttle and glycerolipid metabolism were different between two groups. Correlation analyses were performed between microbiota and metabolites/lipids. Bacteroides. nordii was negatively associated with D-fructose(hit by starch and sucrose metabolism) and MG(16:0)(hit by glycerolipid metabolism) while Bacteroides_coprocola was positively associated with benzoquinone(hit by glycerol phosphate shuttle).

Conclusions: We found evidence from a multi-omics perspective demonstrating the association between the multi-omics profiles of individuals with T1D and their glucose control status.