ArticleMetabolism open2026
Baseline metabolite profiles predict the glucose-lowering efficacy of exenatide in patients with type 2 diabetes.
Article in Metabolism open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Aims: Individual heterogeneity in the glucose-lowering response to glucagon-like peptide-1 receptor agonists (GLP-1RAs), including exenatide, limits efficient treatment selection for type 2 diabetes mellitus (T2DM). This study assessed whether baseline clinical characteristics together with serum metabolomic features could predict the glucose-lowering efficacy of exenatide. Methods: A total of 93 Chinese adults with T2DM received exenatide treatment for 16 weeks. Treatment response was defined by glycated hemoglobin (HbA1c) change value (ΔHbA1c): responders (ΔHbA1c ≤ -0.3%, n = 70) and non-responders (ΔHbA1c > -0.3%, n = 23). Baseline serum metabolites were profiled by non-targeted liquid chromatography-mass spectrometry. Predictors of exenatide-induced glucose-lowering response were screened and modeled using univariate and multivariate logistic regression analysis and evaluated with receiver-operating characteristic (ROC) analysis. Results: At baseline, responders presented with a higher HbA1c level and a lower HDL-C level than non-responders. Logistic regression analysis indicated that baseline HbA1c and HDL-C levels were associated with ΔHbA1c after treatment. Metabolomic comparison analysis identified 15 discriminative serum metabolites between two groups. Among these metabolites, butenylcarnitine, LysoPC(18:2(9Z,12Z)) and PC(20:3(5Z,8Z,11Z)/20:3(5Z,8Z,11Z)) were correlated with the exenatide-induced glucose-lowering response. Baseline clinical characteristics (higher HbA1c level and lower HDL-C level) combined with the metabolomic features [lower butenylcarnitine, higher LysoPC(18:2(9Z,12Z)) and higher PC(20:3(5Z,8Z,11Z)/20:3(5Z,8Z,11Z)] predicted better glucose-lowering response to exenatide, with a sensitivity, specificity and area under the ROC curve of 78.1%, 90.0% and 0.895, respectively. Conclusions: Combination of the baseline clinical characteristics (HbA1c and HDL-C) and metabolite profiles [butenylcarnitine, LysoPC(18:2(9Z,12Z)) and PC(20:3(5Z,8Z,11Z)/20:3(5Z,8Z,11Z))] can effectively predict glucose-lowering efficacy of exenatide in patients with T2DM.
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