Evidence mapPaperPMID 40422918Full record

ArticleMetabolites2025

Lipid Subclasses Differentiate Insulin Resistance by Triglyceride-Glucose Index.

Khaled Naja, Najeha Anwardeen, Omar Albagha, Mohamed A Elrayess

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Article in Metabolites, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

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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

4 authors.

Khaled NajaBiomedical Research Center, QU Health, Qatar University, Doha P.O. Box 2713, Qatar.ORCID 0000-0001-9259-3082
Najeha AnwardeenBiomedical Research Center, QU Health, Qatar University, Doha P.O. Box 2713, Qatar.ORCID 0000-0002-7263-4905
Omar AlbaghaDivision of Genomics and Translational Biomedicine, College of Health and Life Sciences, Hamad Bin Khalifa University (HBKU), Doha P.O. Box 34110, Qatar.ORCID 0000-0001-5916-5983
Mohamed A ElrayessBiomedical Research Center, QU Health, Qatar University, Doha P.O. Box 2713, Qatar.ORCID 0000-0003-3803-4604

Funding

Qatar National Research Fund ARG01-0420-230007
6 · The paper itself

Abstract

backgroundInsulin resistance is a key driver of metabolic syndrome and related disorders, yet its underlying metabolic alterations remain incompletely understood. The Triglyceride-Glucose (TyG) index is an emerging, accessible marker for insulin resistance, with growing evidence supporting its clinical utility. This study aimed to characterize the metabolic profiles associated with insulin resistance using the TyG index in a large, population-based cohort, and to identify metabolic pathways potentially implicated in insulin resistance.

methodsHere, we conducted a cross-sectional study using data from the Qatar Biobank, including 1255 participants without diabetes classified as insulin-sensitive or insulin-resistant based on TyG index tertiles. Untargeted serum metabolomics profiling was performed using high-resolution mass spectrometry. Our statistical analyses included orthogonal partial least squares discriminate analysis and linear models.

resultsDistinct metabolic signatures differentiated insulin-resistant from insulin-sensitive participants. Phosphatidylethanolamines, phosphatidylinositols, and phosphatidylcholines, were strongly associated with insulin resistance, while plasmalogens and sphingomyelins were consistently linked to insulin sensitivity.

conclusionsLipid-centric pathways emerge as potential biomarkers and therapeutic targets for the early detection and personalized management of insulin resistance and related metabolic disorders. Longitudinal studies are warranted to validate causal relationships.

Indexed as

glycerophospholipidsmetabolomicsplasmalogenssphingomyelins

Identifiers

PMID40422918
PMCPMC12113954

What Socratic holds

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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.