Evidence map›Paper›PMID 37552540›Full record

SynthesisJCI insight2023

Mitochondrial metabolites predict adverse cardiovascular events in individuals with diabetes.

Jessica A Regan, Robert J Mentz, Maggie Nguyen, Jennifer B Green, Lauren K Truby, Olga Ilkayeva, Christopher B Newgard, John B Buse, Harald Sourij, C David Sjöström and 10 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in JCI insight, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

13 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Biomarkers of Cardiac Metabolic Flexibility in Health, HFrEF and HFpEF.International journal of molecular sciences · 2026
    Review
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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

20 authors at 9 institutions in 6 countries.

Jessica A ReganDuke Molecular Physiology Institute, Durham, North Carolina, USA.
Robert J MentzDuke University Department of Medicine, Durham, North Carolina, USA.
Maggie NguyenDuke Molecular Physiology Institute, Durham, North Carolina, USA.
Jennifer B GreenDuke University Department of Medicine, Durham, North Carolina, USA.
Lauren K TrubyDuke Molecular Physiology Institute, Durham, North Carolina, USA.
Olga IlkayevaDuke Molecular Physiology Institute, Durham, North Carolina, USA.
Christopher B NewgardDuke Molecular Physiology Institute, Durham, North Carolina, USA.
John B BuseUniversity of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, North Carolina, USA.
Harald SourijDepartment of Internal Medicine, Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria.
C David SjöströmLate-stage Development, Cardiovascular, Renal and Metabolism, Biopharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.
Naveed SattarInstitute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, United Kingdom.
Robert W McGarrahDuke Molecular Physiology Institute, Durham, North Carolina, USA.
Yinggan ZhengCanadian VIGOUR Centre, University of Alberta, Edmonton, Alberta, Canada.
Darren K McGuireUniversity of Texas Southwestern Medical Center and Parkland Health and Hospital System, Dallas, Texas, USA.
Eberhard StandlDiabetes Research Group at Munich Helmholtz Center, Munich, Germany.
Paul ArmstrongCanadian VIGOUR Centre, University of Alberta, Edmonton, Alberta, Canada.
Eric D PetersonUniversity of Texas Southwestern Medical Center and Parkland Health and Hospital System, Dallas, Texas, USA.
Adrian F HernandezDuke University Department of Medicine, Durham, North Carolina, USA.
Rury R HolmanDiabetes Trials Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.
Svati H ShahDuke Molecular Physiology Institute, Durham, North Carolina, USA.
Duke University · USParkland Health & Hospital System · USUniversity of Alberta · CAAstraZeneca (Sweden) · SEHelmholtz Zentrum München · DEMedical University of Graz · ATUniversity of Glasgow · GBUniversity of North Carolina at Chapel Hill · USUniversity of Oxford · GB

Funding

Pilot & Feasibility ProgramP30DK124723 · NIDDK · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI P Darrell Neufer · 2020 to 2026
$11.0M
MULTIDISCIPLINARY HEART &VASCULAR DISEASEST32HL007101 · NHLBI · DUKE UNIVERSITY · PI FREEDMAN, NEIL J. · 1985 to 2020
$9.8M
Postdoctoral Training in Cardiovascular Clinical ResearchT32HL069749 · NHLBI · DUKE UNIVERSITY · PI MARK, DANIEL B · 2003 to 2023
$6.7M
Stimulating Access to Research in Residency (StARR) - NHLBIR38HL143612 · NHLBI · DUKE UNIVERSITY · PI Mai ElMallah, David H. Harpole · 2018 to 2026
$2.6M
NHLBI NIH HHS R38 HL143612NHLBI NIH HHS T32 HL007101NHLBI NIH HHS T32 HL069749NIDDK NIH HHS P30 DK124723
6 · The paper itself

Abstract

Metabolic mechanisms underlying the heterogeneity of major adverse cardiovascular (CV) event (MACE) risk in individuals with type 2 diabetes mellitus (T2D) remain unclear. We hypothesized that circulating metabolites reflecting mitochondrial dysfunction predict incident MACE in T2D. Targeted mass-spectrometry profiling of 60 metabolites was performed on baseline plasma samples from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS; discovery cohort) and Exenatide Study of Cardiovascular Event Lowering (EXSCEL; validation cohort) biomarker substudy cohorts. A principal components analysis metabolite factor comprising medium-chain acylcarnitines (MCACs) was associated with MACE in TECOS and validated in EXSCEL, with higher levels associated with higher MACE risk. Meta-analysis showed that long-chain acylcarnitines (LCACs) and dicarboxylacylcarnitines were also associated with MACE. Metabolites remained associated with MACE in multivariate models and favorably changed with exenatide therapy. A third cohort (Cardiac Catheterization Genetics [CATHGEN]) with T2D was assessed to determine whether these metabolites improved discriminative capability of multivariate models for MACE. Nine metabolites (MCACs and LCACs and 1 dicarboxylacylcarnitine) were associated with time to MACE in the CATHGEN cohort. Addition of these metabolites to clinical models minimally improved the discriminative capability for MACE but did significantly down reclassify risk. Thus, metabolites reporting on dysregulated mitochondrial fatty acid oxidation are present in higher levels in individuals with T2D who experience subsequent MACE. These biomarkers may improve CV risk prediction models, be therapy responsive, and highlight emerging risk mechanisms.

Indexed as

Cardiovascular DiseasesCardiovascular SystemDiabetes Mellitus, Type 2BiomarkersCarnitineExenatideHumansMitochondriaacylcarnitineBiomarkersCarnitineExenatideCardiologyCardiovascular diseaseDiabetesMetabolismMitochondria

Identifiers

PMID37552540
PMCPMC10544215
OpenAlexW4385666835

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.