Evidence map›Paper›PMID 35736441›Full record

ArticleMetabolites2022

Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS.

Leen Oyoun Alsoud, Nelson C Soares, Hamza M Al-Hroub, Muath Mousa, Violet Kasabri, Nailya Bulatova, Maysa Suyagh, Karem H Alzoubi, Waseem El-Huneidi, Bashaer Abu-Irmaileh and 2 more

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

17 citing papers in PubMed, 21 citations in OpenAlex.

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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

12 authors at 2 institutions in 2 countries.

Leen Oyoun AlsoudCollege of Pharmacy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.ORCID 0000-0002-3427-6131
Nelson C SoaresCollege of Pharmacy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.
Hamza M Al-HroubSharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.
Muath MousaResearch Institute of Science and Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.
Violet KasabriSchool of Pharmacy, The University of Jordan, Amman 11942, Jordan.
Nailya BulatovaSchool of Pharmacy, The University of Jordan, Amman 11942, Jordan.ORCID 0000-0001-6754-0325
Maysa SuyaghSchool of Pharmacy, The University of Jordan, Amman 11942, Jordan.ORCID 0000-0003-2042-8584
Karem H AlzoubiCollege of Pharmacy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.
Waseem El-HuneidiSharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.ORCID 0000-0002-1580-2589
Bashaer Abu-IrmailehHamdi Mango Center for Scientific Research, The University of Jordan, Amman 11942, Jordan.
Yasser BustanjiSharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.ORCID 0000-0003-1315-0609
Mohammad H SemreenCollege of Pharmacy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.ORCID 0000-0002-0169-7538
University of Sharjah · AEUniversity of Jordan · JO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sectional investigation used an untargeted metabolomics-based technique to uncover metabolomic alterations and their relationship to pathways in normoglycemic and prediabetic MetS participants to improve disease diagnosis. Plasma samples were collected from drug-naive prediabetic MetS patients (n = 26), normoglycemic MetS patients (n = 30), and healthy (normoglycemic lean) subjects (n = 30) who met the inclusion criteria for the study. The plasma samples were analyzed using highly sensitive ultra-high-performance liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). One-way ANOVA analysis revealed that 59 metabolites differed significantly among the three groups (p < 0.05). Glutamine, 5-hydroxy-L-tryptophan, L-sorbose, and hippurate were highly associated with MetS. However, 9-methyluric acid, sphinganine, and threonic acid were highly associated with prediabetes/MetS. Metabolic pathway analysis showed that arginine biosynthesis and glutathione metabolism were associated with MetS/prediabetes, while phenylalanine, D-glutamine and D-glutamate, and lysine degradation were highly impacted in MetS. The current study sheds light on the potential diagnostic value of some metabolites in metabolic syndrome and the role of their alteration on some of the metabolic pathways. More studies are needed in larger cohorts in order to verify the implication of the above metabolites on MetS and their diagnostic value.

Indexed as

MetaboAnalystmetabolic pathwaysmetabolic profilingmetabolic syndromemetabolitesUHPLC-ESI-QTOF-MSuntargeted metabolomics

Identifiers

PMID35736441
PMCPMC9227428
OpenAlexW4281608386

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.