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*Author for correspondence:

E-mail Address: alexander.limkakeng@duke.edu

Division of Emergency Medicine, Duke University, Durham, NC 27710, USA

Sequencing & Genomic Technologies Shared Resource, Duke Center for Genomic & Computational Biology, Duke University, Durham, NC, USA

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Ace Hatch

Division of Medical Oncology, Duke University, Durham, NC 27710, USA

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Andrew B Nixon

Division of Medical Oncology, Duke University, Durham, NC 27710, USA

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Olga Ilkayeva

Duke Molecular Physiology Institute, Duke University, Durham, NC 27710, USA

Division of Endocrinology, Metabolism & Nutrition, Duke University School of Medicine, Durham, NC 27710, USA

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David Corcoran

Genomic Analysis & Bioinformatics Shared Resource, Duke Center for Genomic & Computational Biology, Duke University, Durham, NC 27710, USA

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Jennifer Modliszewski

Genomic Analysis & Bioinformatics Shared Resource, Duke Center for Genomic & Computational Biology, Duke University, Durham, NC 27710, USA

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Shannon Michelle Griffin

Division of Emergency Medicine, Duke University, Durham, NC 27710, USA

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Geoffrey S Ginsburg

Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC 27710, USA

Division of Cardiology, Duke University, Durham, NC 27710, USA

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Deepak Voora

Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC 27710, USA

Division of Cardiology, Duke University, Durham, NC 27710, USA

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Published Online:25 Apr 2022https://doi.org/10.2217/pme-2021-0021

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Abstract

Both transcriptomics and metabolomics hold promise for identifying acute coronary syndrome (ACS) but they have not been used in combination, nor have dynamic changes in levels been assessed as a diagnostic tool. We assessed integrated analysis of peripheral blood miRNA and metabolite analytes to distinguish patients with myocardial ischemia on cardiac stress testing. We isolated and quantified miRNA and metabolites before and after stress testing from seven patients with myocardial ischemia and 1:1 matched controls. The combined miRNA and metabolomic data were analyzed jointly in a supervised, dimension-reducing discriminant analysis. We implemented a baseline model (T0) and a stress-delta model. This novel integrative analysis of the baseline levels of metabolites and miRNA expression showed modest performance for distinguishing cases from controls. The stress-delta model showed worse performance. This pilot study shows potential for an integrated precision medicine approach to cardiac stress testing.

Plain language summary

The study of small sequences of ribonucleic acids (miRNAs) and byproducts of cellular metabolism (metabolites) could help us to identify important cardiac conditions such as not enough blood and oxygen supply to the heart (acute coronary syndrome). We obtained blood samples from patients getting cardiac stress tests (a noninvasive test to see if the patient has enough blood flow to their heart) before and after their test, then compared the levels of miRNAs and metabolites in them. We compared the levels in patients who had abnormal stress tests with those that had normal tests. We believe this could be a model for a new type of cardiac stress test if validated in more patients.

Tweetable abstract

Can metabolomics + miRNAs augment imaging in cardiac stress tests? This study examines an integrative analysis of pre- and post- stress samples to determine if combining these data can help differentiate myocardial ischemia.

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Keywords:

Papers of special note have been highlighted as: • of interest; •• of considerable interest

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Vol. 19, No. 4

Supplemental Materials

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Downloaded 36 times

History

Received 11 February 2021

Accepted 23 February 2022

Published online 25 April 2022

Published in print July 2022

Information

Keywords

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.futuremedicine.com/doi/suppl/10.2217/pme-2021-0021

Author contributions

AT Limkakeng: conceptualization, funding acquisition, data curation, investigation, supervision, methodology, project administration, visualization, writing – original draft preparation, writing – review & editing. L-L Rowlette: data curation, formal analysis, investigation, methodology, resources, validation, writing – review & editing. A Hatch: formal analysis, investigation, methodology, resources, validation, writing – review & editing. AB Nixon: formal analysis, investigation, methodology, resources, validation, writing – review & editing. O Ilkayeva: data curation, formal analysis, investigation, methodology, resources. D Corcoran: conceptualization, formal analysis, methodology, supervision, visualization, writing – review & editing. J Modliszewski: conceptualization, formal analysis, methodology, visualization, writing – review & editing. SM Griffin: data curation, investigation, methodology, project administration, writing – review & editing. ELT: conceptualization, funding acquisition, methodology, writing – review & editing. GS Ginsburg: conceptualization, funding acquisition, resources, supervision, writing – review & editing. D Corcoran: conceptualization, methodology, funding acquisition, visualization, resources, supervision, writing – review & editing.

Acknowledgments

The authors would like to acknowledge the assistance of A Morgan who helped typeproof and edit the manuscript.

Financial & competing interests disclosure

The current study was made possible by funding support via a Pilot Grant from the Emergency Medicine Foundation. Samples were collected in a prior study that was supported by an investigator-initiated grant from Abbott Laboratories. The authors retained possession of all data and decision on whether to publish at all times. GS Ginsburg reports having an unlicensed patent on a metabolomic finding. Ginsburg also serves on the Scientific Advisory Board for CardioDx. GS Ginsburg, AT Limkakeng and D Voora have received research funding from Abbott Laboratories. Limkakeng has also received prior research grants from Roche International, and Siemens Healthcare Diagnostics. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Editorial board disclosure

GS Ginsburg is a member of the Personalized Medicine Editorial Board. They were not involved in any editorial decisions related to the publication of this article, and all author details were blinded to the article's peer reviewers as per the journal's double-blind peer review policy.

Ethical conduct of research

We have obtained appropriate institutional review board approval for this study. In addition, informed consent has been obtained from the participants involved.

Data sharing statement

We will share data for individual participants that underlie the results after deidentification, in addition to the study protocol and data analytic plan. Data will be available upon publication for a time period of 1 year for researchers who propose a sound proposal and sign a data use agreement. Proposals should be directed to the corresponding author.

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A precision medicine approach to stress testing using metabolomics and microribonucleic acids

Abstract

Plain language summary

Tweetable abstract

Graphical abstract

References