Evidence mapPaperPMID 41799733Full record

ArticleMetabolism open2026

Baseline metabolite profiles predict the glucose-lowering efficacy of exenatide in patients with type 2 diabetes.

Yunyi Le, Jin Yang, Qi Wu, Fei Li, Wei Fu, Wenhua Xiao, Haining Wang, Tianpei Hong, Rui Wei

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yunyi LeDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.
Jin YangDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.
Qi WuDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.
Fei LiDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.
Wei FuDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.
Wenhua XiaoDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.
Haining WangDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.
Tianpei HongDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.
Rui WeiDepartment of Endocrinology and Metabolism, State Key Laboratory of Female Fertility Promotion, Peking University Third Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

ExenatideGlucose-lowering efficacyNon-targeted metabolomicsType 2 diabetes mellitus

Identifiers

PMID41799733
PMCPMC12964271

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.