Evidence map›Paper›PMID 33381523›Full record

ArticleFrontiers in molecular biosciences2020

Distinctive Metabolomics Patterns Associated With Insulin Resistance and Type 2 Diabetes Mellitus.

Xinyun Gu, Mohammed Al Dubayee, Awad Alshahrani, Afshan Masood, Hicham Benabdelkamel, Mahmoud Zahra, Liang Li, Anas M Abdel Rahman, Ahmad Aljada

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

52 citing papers in PubMed, 75 citations in OpenAlex.

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  12. The MDA-MB-231 Breast Cancer Cell Secretomes Modify Metabolomes ofInternational journal of molecular sciences · 2025
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  17. Untargeted metabolomics reveals the impact of Liraglutide treatment on metabolome profiling and metabolic pathways in type-2 diabetes mellitus.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024
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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

9 authors at 5 institutions in 2 countries.

Xinyun GuDepartment of Chemistry, University of Alberta, Edmonton, AB, Canada.
Mohammed Al DubayeeDepartment of Medicine, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.
Awad AlshahraniDepartment of Medicine, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.
Afshan MasoodObesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
Hicham BenabdelkamelObesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
Mahmoud ZahraDepartment of Biochemistry and Molecular Medicine, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Liang LiDepartment of Chemistry, University of Alberta, Edmonton, AB, Canada.
Anas M Abdel RahmanDepartment of Biochemistry and Molecular Medicine, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Ahmad AljadaDepartment of Biochemistry and Molecular Medicine, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Alfaisal University · SAKing Abdullah International Medical Research Center · SAKing Saud University · SAUniversity of Alberta · CAKing Faisal Specialist Hospital & Research Centre · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity is associated with an increased risk of insulin resistance (IR) and type 2 diabetes mellitus (T2DM) which is a multi-factorial disease associated with a dysregulated metabolism and can be prevented in pre-diabetic individuals with impaired glucose tolerance. A metabolomic approach emphasizing metabolic pathways is critical to our understanding of this heterogeneous disease. This study aimed to characterize the serum metabolomic fingerprint and multi-metabolite signatures associated with IR and T2DM. Here, we have used untargeted high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) to identify candidate biomarkers of IR and T2DM in sera from 30 adults of normal weight, 26 obese adults, and 16 adults newly diagnosed with T2DM. Among the 3633 peak pairs detected, 62% were either identified or matched. A group of 78 metabolites were up-regulated and 111 metabolites were down-regulated comparing obese to lean group while 459 metabolites were up-regulated and 166 metabolites were down-regulated comparing T2DM to obese groups. Several metabolites were identified as IR potential biomarkers, including amino acids (Asn, Gln, and His), methionine (Met) sulfoxide, 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, serotonin, L-2-amino-3-oxobutanoic acid, and 4,6-dihydroxyquinoline. T2DM was associated with dysregulation of 42 metabolites, including amino acids, amino acids metabolites, and dipeptides. In conclusion, these pilot data have identified IR and T2DM metabolomics panels as potential novel biomarkers of IR and identified metabolites associated with T2DM, with possible diagnostic and therapeutic applications. Further studies to confirm these associations in prospective cohorts are warranted.

Indexed as

chemical isotope labeling liquid chromatographyclinical metabolic panelinsulin resistanceobesitytype 2 diabetes mellitusuntargeted metabolomics profiling

Identifiers

PMID33381523
PMCPMC7768025
OpenAlexW3112932318

What OpenQuestion holds

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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 OpenQuestion graph.