Evidence map›Paper›PMID 33228610›Full record

SynthesisBMC endocrine disorders2020

Metabolite biomarkers of type 2 diabetes mellitus and pre-diabetes: a systematic review and meta-analysis.

Jianglan Long, Zhirui Yang, Long Wang, Yumei Han, Cheng Peng, Can Yan, Dan Yan

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC endocrine disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 3 pooled it
4.8field-weighted citation impact, top 4% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

59 citing papers in PubMed, 3 syntheses or guidelines pooled it, 108 citations in OpenAlex.

  1. Pooled it
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  4. Review
  5. The Complex Relation of Branched-Chain Amino Acids and Inflammation in the Obesity and Diabetes Context.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
    Review
  6. Metabolomic profiling and vitamin D pathway investigation in diabetic foot ulcer patients.Metabolomics : Official journal of the Metabolomic Society · 2026
    Article
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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

7 authors at 4 institutions in 2 countries.

Jianglan LongBeijing Key Laboratory and Joint Laboratory for International Cooperation of Bio-characteristic Profiling for Evaluation of Rational Drug Use, Capital Medical University Affiliated Beijing Shijitan Hospital, Beijing, 100038, China.
Zhirui YangBeijing Key Laboratory and Joint Laboratory for International Cooperation of Bio-characteristic Profiling for Evaluation of Rational Drug Use, Capital Medical University Affiliated Beijing Shijitan Hospital, Beijing, 100038, China.
Long WangDepartment of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, 21218, USA.
Yumei HanBeijing Physical Examination Center, Beijing, 100077, China.
Cheng PengChengdu University of Traditional Chinese Medicine, Chengdu, 611130, China.
Can YanGuangzhou University of Chinese Medicine, Guangzhou, 510006, China. Yanc020@126.com.
Dan YanBeijing Key Laboratory and Joint Laboratory for International Cooperation of Bio-characteristic Profiling for Evaluation of Rational Drug Use, Capital Medical University Affiliated Beijing Shijitan Hospital, Beijing, 100038, China. pharmsci@126.com.ORCID http://orcid.org/0000-0002-1288-4144
Capital Medical University · CNChengdu University of Traditional Chinese Medicine · CNGuangzhou University of Chinese Medicine · CNJohns Hopkins University · US

Funding

National Natural Science Foundation of China 81773891the Beijing Municipal Science and Technology Commission 2018000021223TD09, 2018-2-2242, 7194280the National Great New Drugs Development Project of China 2017ZX09301-040
6 · The paper itself

Abstract

backgroundWe aimed to explore metabolite biomarkers that could be used to identify pre-diabetes and type 2 diabetes mellitus (T2DM) using systematic review and meta-analysis.

methodsFour databases, the Cochrane Library, EMBASE, PubMed and Scopus were selected. A random effect model and a fixed effect model were applied to the results of forest plot analyses to determine the standardized mean difference (SMD) and 95% confidence interval (95% CI) for each metabolite. The SMD for every metabolite was then converted into an odds ratio to create an metabolite biomarker profile.

resultsTwenty-four independent studies reported data from 14,131 healthy individuals and 3499 patients with T2DM, and 14 included studies reported 4844 healthy controls and a total of 2139 pre-diabetes patients. In the serum and plasma of patients with T2DM, compared with the healthy participants, the concentrations of valine, leucine, isoleucine, proline, tyrosine, lysine and glutamate were higher and that of glycine was lower. The concentrations of isoleucine, alanine, proline, glutamate, palmitic acid, 2-aminoadipic acid and lysine were higher and those of glycine, serine, and citrulline were lower in prediabetic patients. Metabolite biomarkers of T2DM and pre-diabetes revealed that the levels of alanine, glutamate and palmitic acid (C16:0) were significantly different in T2DM and pre-diabetes.

conclusionsQuantified multiple metabolite biomarkers may reflect the different status of pre-diabetes and T2DM, and could provide an important reference for clinical diagnosis and treatment of pre-diabetes and T2DM.

Indexed as

MetabolomeBiomarkersDiabetes Mellitus, Type 2HumansPrediabetic StatePrognosisBiomarkersBiomarkerMetabolitePre-diabetes; meta-analysisType 2 diabetes mellitus

Identifiers

PMID33228610
PMCPMC7685632
OpenAlexW3109112590

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.