Evidence map›Paper›PMID 42437920›Full record

ArticleCardiovascular diabetology2026

Multi-omics signatures of circulating factors associated with cardiorespiratory fitness adaptations in individuals with prediabetes.

Candela Diaz-Canestro, Kit Cheung, Enrique Roche, Jose Manuel Sarabia, Michael Andrew Tse, Aimin Xu

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Article in Cardiovascular diabetology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Candela Diaz-CanestroCenter for Molecular Cardiology, University of Zurich, Schlieren, Switzerland. candela.diazcanestro@uzh.ch.
Kit CheungCenter for Molecular Cardiology, University of Zurich, Schlieren, Switzerland.
Enrique RocheDepartment of Applied Biology-Nutrition, Institute of Bioengineering, Miguel Hernandez University (UMH), 03202, Elche, Spain.
Jose Manuel SarabiaAlicante Institute for Health and Biomedical Research (ISABIAL), 03010, Alicante, Spain.
Michael Andrew TseCentre for Sports and Exercise, Active Health Clinic, The University of Hong Kong, Hong Kong, China.
Aimin XuState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong, China. amxu@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with insulin resistance exhibit reduced cardiorespiratory fitness (CRF), assessed by peak oxygen consumption (VO₂peak), compared with healthy age-matched individuals. Although high-intensity interval training (HIIT) can substantially improve VO₂peak, there is considerable interindividual variability in this response. Therefore, further research is needed to elucidate the molecular mechanisms underlying the heterogeneous response of VO₂peak to HIIT in individuals with prediabetes.

methodsProteomic analyses of serum samples, along with fecal metagenomic and targeted metabolomic profiling, were conducted in medication-naïve, overweight and obese Chinese men with prediabetes (n = 35; aged 24-62 years). All participants underwent a 12-week HIIT intervention, and biological samples were collected both before and after the intervention to evaluate exercise-induced alterations in circulating proteins, gut microbial composition, and metabolite profiles.

resultsAfter 12 weeks of HIIT, mean VO₂peak increased by 0.47 L/min with individual responses ranging from 0 to 1.7 L/min. Baseline levels of short-chain fatty acid (SCFA)-producing genera, including Prevotella (β = 105.65, P = < 0.001, FDR = 0.034), Coprococcus (β = 50.22, P = 0.01, FDR = 0.39), and Hungatella (β = 40.72, P = 0.025, FDR = 0.50), were positively associated with ΔVO₂ peak. In contrast, baseline levels of the erythropoiesis-stimulating hormone erythropoietin (EPO) (β = -279.03, P = 0.024, FDR = 0.99) were negatively associated with ΔVO₂ peak. Exercise-induced changes in growth hormone 1 (β = 63.97, P = 0.04, FDR = 0.99) were positively associated with ΔVO₂ peak, whereas exercise-induced changes in BTB and CNC Homology 1 (β = -250.82, P = 0.01, FDR = 0.99), a repressor of heme oxygenase-1, were negatively associated with ΔVO₂ peak. In multiple linear regression analysis including clinical variables, percentage lean mass (β = 64.17, P = 0.0005) was the strongest variable associated with ΔVO₂peak. The clinical model explained 27% of the variance which increased to 37% (P = 0.002) upon inclusion of exercise-associated circulating factors such as EPO.

conclusionsOur findings reveal that baseline proteomic and metagenomic signatures are associated with VO₂peak adaptations. These multi-omics signatures may support the clinical implementation of personalized exercise interventions to improve CRF in individuals with prediabetes.

Indexed as

Cardiorespiratory FitnessHigh-Intensity Interval TrainingMetabolomicsPrediabetic StateProteomicsAdaptation, PhysiologicalAdultBiomarkersChinaFecesGastrointestinal MicrobiomeHumansMaleMetagenomicsMiddle AgedMultiomicsBiomarkersCardiorespiratory fitnessGut microbiomeHigh-intensity interval trainingPrediabetesProteomics

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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.