In-and-Out Molecular Changes Linked to the Type 2 Diabetes Remission after Bariatric Surgery: An Influence of Gut Microbes on Mitochondria Metabolism

Abstract

Different kinds of gastrointestinal tract modulations known as "bariatric surgery" are actually the most effective treatment for obesity and associated co-morbidities, such as type 2 diabetes (T2DM). The potential causes of those effects have yet to be explained. In our study, we focused on molecular changes evoked by laparoscopic sleeve gastrectomy leading to T2DM remission. Two complementary metabolomics techniques, namely, liquid chromatography coupled with mass spectrometry (LC-MS) and gas chromatography mass spectrometry (GC-MS), were used to study those effects in a group of 20 obese patients with T2DM selected from a cohort of 372 obese individuals who underwent bariatric surgery and did not receive anti-diabetic treatment afterward. Modified levels of carnitines, lipids, amino acids (including BCAA) and α- and β-hydroxybutyric acids were detected. Presented alterations suggest a major role of mitochondria activity in T2DM remission process. Moreover, some of the observed metabolites suggest that changes in gut microbiota composition may also correlate with the tempo of diabetes recovery. Additional analyses confirmed a relationship between biochemical and clinical parameters and the aforementioned metabolites, thereby, highlighting a role of mitochondria and microbes. Our data suggests that there is a previously undescribed relationship between mitochondria and gut microbiota, which changes after the bariatric surgery. More investigations are needed to confirm and explore the observed findings.

Keywords: GC-MS; LC-MS; bariatric surgery; diabetes remission; laparoscopic sleeve gastrectomy; metabolomics.

Figure 1

Changes in HOMA-IR (with its standard deviation) during follow-up after the bariatric surgical procedure in the groups with quicker (blue) and slower (orange) diabetes remission.

Figure 2

PLS-DA plots demonstrating the differences in the metabolome of the examined groups (▲—patients before the surgery, ●—one month after and quicker remission, ■—one month and slower remission). The left panel shows all patients clustered together before surgery and separated patients with quicker diabetes remission whose metabolic profiles differ after one-month post-surgery. A prediction of patients with slower remission by PLS-DA model built based on patients before and one-month post-surgery placed slower remission group exactly between the other groups (right panel). R² = 0.947, Q² = 0.434; Pareto Scaling, Log transformed data.

Figure 3

Selected Spearman correlation analysis results presented as heat maps for quicker (top) and slower (bottom) T2DM remission groups. Statistically significant correlations are marked with ☆. Time points: 0—before the surgery, 1—one month after, 3—three months after; Metabolites: “before”—before the surgery, “after”—one month post-surgery.

Figure 4

Summary of Pathway Analysis for group with quicker (left) and slower (right) diabetes remission.