Evidence map›Paper›PMID 38065238›Full record

ArticleThe Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation2024

Metabolomic profiling during ex situ normothermic perfusion before heart transplantation defines patterns of substrate utilization and correlates with markers of allograft injury.

Lauren K Truby, Lydia Coulter Kwee, Dawn E Bowles, Sarah Casalinova, Olga Ilkayeva, Michael J Muehlbauer, Janet L Huebner, Christopher L Holley, Adam D DeVore, Chetan B Patel and 7 more

Open access · greenAbstract read
In one paragraph

Article in The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
8.3field-weighted citation impact, top 2% 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

19 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Differential transcriptomic and metabolomic landscape between human hearts donated after cardiac vs brain death.The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation · 2026
    Article
  4. Review
  5. Article
  6. Recipient plasma metabolomics as a predictor of heart transplant severe primary graft dysfunction.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2026
    Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Improving metabolic support during normothermicFrontiers in cardiovascular medicine · 2025
    Review
  14. Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. European Society of Organ Transplantation (ESOT) Consensus Statement on Machine Perfusion in Cardiothoracic Transplant.Transplant international : official journal of the European Society for Organ Transplantation · 2024
    Review
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

17 authors at 3 institutions in 1 country.

Lauren K TrubyUniversity of Texas Southwestern Medical Center, Dallas, Texas.
Lydia Coulter KweeDuke Molecular Physiology Institute, Durham, North Carolina.
Dawn E BowlesDuke University Medical Center, Durham, North Carolina.
Sarah CasalinovaDuke University Medical Center, Durham, North Carolina.
Olga IlkayevaDuke Molecular Physiology Institute, Durham, North Carolina.
Michael J MuehlbauerDuke Molecular Physiology Institute, Durham, North Carolina.
Janet L HuebnerDuke Molecular Physiology Institute, Durham, North Carolina.
Christopher L HolleyDuke University Medical Center, Durham, North Carolina.
Adam D DeVoreDuke University Medical Center, Durham, North Carolina.
Chetan B PatelDuke University Medical Center, Durham, North Carolina.
Lillian KangDuke University Medical Center, Durham, North Carolina.
Michelle Mendiola PlaDuke University Medical Center, Durham, North Carolina.
Ryan GrossDuke University Medical Center, Durham, North Carolina.
Robert W McGarrahDuke Molecular Physiology Institute, Durham, North Carolina.
Jacob N SchroderDuke University Medical Center, Durham, North Carolina.
Carmelo A MilanoDuke University Medical Center, Durham, North Carolina.
Svati H ShahDuke Molecular Physiology Institute, Durham, North Carolina. Electronic address: svati.shah@duke.edu.
Duke Medical Center · USDuke University · USThe University of Texas Southwestern Medical Center · US

Funding

Postdoctoral Training in Cardiovascular Clinical ResearchT32HL069749 · NHLBI · DUKE UNIVERSITY · PI MARK, DANIEL B · 2003 to 2023
$6.7M
NHLBI NIH HHS T32 HL069749
6 · The paper itself

Abstract

backgroundCardiac metabolism is altered in heart failure and ischemia-reperfusion injury states. We hypothesized that metabolomic profiling during ex situ normothermic perfusion before heart transplantation (HT) would lend insight into myocardial substrate utilization and report on subclinical and clinical allograft dysfunction risk.

methodsMetabolomic profiling was performed on serial samples of ex situ normothermic perfusate assaying biomarkers of myocardial injury in lactate and cardiac troponin I (TnI) as well as metabolites (66 acylcarnitines, 15 amino acids, nonesterified fatty acids [NEFA], ketones, and 3-hydroxybutyrate). We tested for change over time in injury biomarkers and metabolites, along with differential changes by recovery strategy (donation after circulatory death [DCD] vs donation after brain death [DBD]). We examined associations between metabolites, injury biomarkers, and primary graft dysfunction (PGD). Analyses were performed using linear mixed models adjusted for recovery strategy, assay batch, donor-predicted heart mass, and time.

resultsA total of 176 samples from 92 ex situ perfusion runs were taken from donors with a mean age of 35 (standard deviation 11.3) years and a median total ex situ perfusion time of 234 (interquartile range 84) minutes. Lactate trends over time differed significantly by recovery strategy, while TnI increased during ex situ perfusion regardless of DCD vs DBD status. We found fuel substrates were rapidly depleted during ex situ perfusion, most notably the branched-chain amino acids leucine/isoleucine, as well as ketones, 3-hydroxybutyrate, and NEFA (least squares [LS] mean difference from the first to last time point -1.7 to -4.5, false discovery rate q < 0.001). Several long-chain acylcarnitines (LCAC), including C16, C18, C18:1, C18:2, C18:3, C20:3, and C20:4, increased during the perfusion run (LS mean difference 0.42-0.67, q < 0.001). Many LCACs were strongly associated with lactate and TnI. The change over time of many LCACs was significantly different for DCD vs DBD, suggesting differential trends in fuel substrate utilization by ischemic injury pattern. Changes in leucine/isoleucine, arginine, C12:1-OH/C10:1-DC, and C16-OH/C14-DC were associated with increased odds of moderate-severe PGD. Neither end-of-run nor change in lactate or TnI was associated with PGD.

conclusionsMetabolomic profiling of ex situ normothermic perfusion solution reveals a pattern of fuel substrate utilization that correlates with subclinical and clinical allograft dysfunction. This study highlights a potential role for interventions focused on fuel substrate modification in allograft conditioning during ex situ perfusion to improve allograft outcomes.

Indexed as

BiomarkersHeart TransplantationMetabolomicsPerfusionAdultAllograftsFemaleHumansMaleMiddle AgedMyocardiumBiomarkersdonation after circulatory determination of deathex situ normothermic perfusionheart transplantationmetabolomic profilingprimary graft dysfunction

Identifiers

PMID38065238
PMCPMC12323694
OpenAlexW4389409377

What OpenQuestion holds

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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 OpenQuestion graph.