Efficacy of Xiaokeqing granules and lifestyle intervention in treating prediabetes mellitus considering metabolomic biomarkers: A randomised controlled trial

Abstract

Background: Prediabetes mellitus (PDM) is receiving increasing attention as a precursor to type 2 diabetes mellitus. Lifestyle and traditional Chinese medicine (TCM) interventions are effective for PDM prevention and treatment. Therefore, we conducted a preliminary investigation and an exploratory randomised controlled trial to assess the effects of a combined lifestyle and TCM intervention on PDM indicators.

Aim: To study the effectiveness of Xiaokeqing granules (XQG) and lifestyle interventions in PDM participants while using metabolomics to identify potential markers.

Methods: Forty PDM participants with yin deficiency syndrome with excessive heat were recruited and randomly allocated to the control (Con) group or the XQG group (20 per group). The Con group underwent lifestyle interventions, whereas the XQG group underwent lifestyle and XQG interventions. The follow-up duration was 2 months. Fasting blood glucose, 2-hour postprandial glucose (2hPG), glycated haemoglobin A1c, fasting insulin, homeostasis model assessment-insulin resistance levels, and serum metabolomics characteristics were compared via liquid chromatography-tandem mass spectrometry analysis.

Results: There were significant differences in 2hPG between the two groups (P < 0.05) in the intention-to-treat analysis and per-protocol analysis. The intervention method used in this study was safe (P > 0.05). Groenlandicine, kaempferol, isomangiferin, etc., are the XQG constituents absorbed in the blood. N-Nervonoyl methionine and 5-hydroxy-L-tryptophan are core potential metabolomic biomarkers for the effectiveness of XQG and lifestyle interventions. HTR1A, HTR2C, SLC6A4, etc., are the core targets of XQG and lifestyle interventions, as well as the reason for their clinical efficacy. Possible mechanistic pathways include tryptophan metabolism, pantothenate and certificate of analysis biosynthesis, lysine degradation and biosynthesis of cofactors.

Conclusion: This pilot study provides evidence that a combined XQG and lifestyle intervention can improve 2hPG in participants with PDM. The mechanism of action is related to multiple constituents, targets and pathways.

Keywords: Lifestyle; Metabolomics; Prediabetes mellitus; Tryptophan metabolism; Two-hour postprandial glucose; Xiaokeqing granules.

Figure 1

Consolidated standards of reporting trials participant flow chart. PDM: Prediabetes mellitus; Con: Control; XQG: Xiaokeqing granule; ITT: Intention to treat; PP: Per-protocol.

Figure 2

Identification of Xiaokeqing granule constituents absorbed in the blood. A: Positive-ion chromatograms of the serum of the Xiaokeqing granule group; B: Negative ion chromatograms of the serum of the Xiaokeqing granule group. TIC: Total ion chromatogram.

Figure 3

Comparisons of metabolites between the control group and Xiaokeqing granule group. A: Comparison of the positive-ion metabolite profiles by orthogonal partial least squares discriminant analysis (OPLS-DA); B: Comparison of the negative ion metabolite profiles by OPLS-DA; C: Volcano plot of the significantly differentially abundant metabolites; D: Metabolic Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway topology analysis; E: Metabolic KEGG pathway enrichment analysis network. Green circles represent differentially metabolites, orange and yellow triangles represent differentially KEGG pathways, and the size represents the number of metabolites in the pathways. Con: Control; XQG: Xiaokeqing granule; FC: Fold change; VIP: Variable importance in projection; CoA: Certificate of analysis.

Figure 4

Comparisons of potential biomarkers between the control group and Xiaokeqing granule group. A: Important biomarkers according to random forest analysis; B: Important biomarkers according to least absolute shrinkage and selection operator regression analysis; C: Receiver operating characteristic analysis of the two core metabolomics biomarkers; D: Receiver operating characteristic curve analysis of the joint core metabolomics biomarkers. TPR: True positive rate; FPR: False positive rate; AUC: Area under the curve; CI: Confidence interval.

Figure 5

Network pharmacology and molecular docking. A: Key targets; B: Molecules docking heatmap of Xiaokeqing granule constituents absorbed in the blood, core metabolomics biomarkers and key targets; C: Molecular docking visualization of groenlandicine and HTR2C; D: Molecular docking visualization of 5-hydroxy-L-tryptophan and SLC6A4.