Evidence map›Paper›PMID 40640808›Full record

ArticleCardiovascular diabetology2025

Preclinical atherosclerosis and prediabetes: a cross-sectional metabolic assessment in apparently healthy population.

Natalia Zieleniewska, Jacek Jamiołkowski, Marcin Kondraciuk, Michal Ciborowski, Katarzyna Ptaszyńska, Małgorzata Chlabicz, Marlena Dubatówka, Urszula Roszkowska, Irina Kowalska, Karol Kamiński

Abstract read
In one paragraph

Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Observational
  4. Causal Associations Between Human Blood Metabolites and Cardio-Cerebrovascular Diseases: A Mendelian Randomisation Study.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
    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

10 authors.

Natalia ZieleniewskaDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.
Jacek JamiołkowskiDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.
Marcin KondraciukDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.
Michal CiborowskiMetabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, Białystok, Poland.
Katarzyna PtaszyńskaDepartment of Cardiology and Internal Medicine, University Hospital of Bialystok, Białystok, Poland.
Małgorzata ChlabiczDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.
Marlena DubatówkaDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.
Urszula RoszkowskaDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland.
Irina KowalskaDepartment of Internal Medicine and Metabolic Diseases, Medical University of Bialystok, Białystok, Poland.
Karol KamińskiDepartment of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Białystok, Poland. fizklin@wp.pl.

Funding

Uniwersytet Medyczny w Białymstoku B.SUB.25.506
6 · The paper itself

Abstract

introductionPrediabetes and preclinical atherosclerosis are interrelated conditions contributing to cardiovascular risk, even in apparently healthy individuals. Metabolomics provides insights into the early metabolic alterations underpinning these diseases.

objectivesThis study aimed to investigate the shared and distinct metabolic signatures associated with prediabetes and preclinical atherosclerosis in a population with low to moderate cardiovascular risk, using a targeted metabolomic approach.

methodsA cross-sectional analysis was performed on 447 participants (mean age 39.7 ± 9.6 years) from the Białystok PLUS cohort. Prediabetes was diagnosed based on HbA1c and OGTT criteria. Preclinical atherosclerosis was assessed by carotid ultrasound. Targeted metabolomics profiling encompassed 434 metabolites and 218 metabolite sums or ratios using HPLC-MS/MS. Statistical analyses included ANOVA, linear regression, correlation analysis, and metabolite set enrichment analysis (MSEA).

resultsPrediabetes was significantly associated with preclinical atherosclerosis (30.8% vs. 19.5%, p = 0.006). Prediabetes had a broader metabolic impact than atherosclerosis, particularly affecting amino acid and lipid metabolism. Glutamic acid, lactic acid, and L-alanine were strongly associated with prediabetes. Trimethylamine N-oxide (TMAO) was uniquely linked to both prediabetes and its interaction with atherosclerosis, suggesting a context-dependent metabolic response. Glutaminase activity emerged as a robust shared metabolic feature of both conditions. Pathway analyses revealed converging disturbances in glutathione and folate metabolism, mitochondrial function, and redox regulation.

conclusionsPrediabetes is associated with more pronounced metabolic alterations than preclinical atherosclerosis. TMAO and glutaminase activity may represent key metabolic links between these conditions. These findings highlight the potential of metabolomics in identifying early biomarkers and mechanisms relevant to the prevention of cardiometabolic diseases.

Indexed as

AtherosclerosisCarotid Artery DiseasesEnergy MetabolismMetabolomicsPrediabetic StateAdultAsymptomatic DiseasesBiomarkersCross-Sectional StudiesFemaleGlycated HemoglobinHumansMaleMethylaminesMiddle AgedPolandBiomarkersGlycated Hemoglobinhemoglobin A1c protein, humanMethylaminestrimethyloxamine

Identifiers

PMID40640808
PMCPMC12247261

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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.