Pilot study of myocardial ischemia-induced metabolomic changes in emergency department patients undergoing stress testing.

Abstract

BACKGROUND:The heart is a metabolically active organ, and plasma acylcarnitines are associated with long-term risk for myocardial infarction. We hypothesized that myocardial ischemia from cardiac stress testing will produce dynamic changes in acylcarnitine and amino acid levels compared to levels seen in matched control patients with normal stress tests. METHODS:We analyzed targeted metabolomic profiles in a pilot study of 20 case patients with inducible ischemia on stress testing from an existing prospectively collected repository of 357 consecutive patients presenting with symptoms of Acute Coronary Syndrome (ACS) in an Emergency Department (ED) observation unit between November 2012 and September 2014. We selected 20 controls matched on age, sex, and body-mass index (BMI). A peripheral blood sample was drawn <1 hour before stress testing and 2 hours after stress testing on each patient. We assayed 60 select acylcarnitines and amino acids by tandem mass spectrometry (MS/MS) using a Quattro Micro instrument (Waters Corporation, Milford, MA). Metabolite values were log transformed for skew. We then performed bivariable analysis for stress test outcome and both individual timepoint metabolite concentrations and stress-delta metabolite ratios (T2/T0). False discovery rates (FDR) were calculated for 60 metabolites while controlling for age, sex, and BMI. We built multivariable regularized linear models to predict stress test outcome from metabolomics data at times 0, 2 hours, and log ratio between these two. We used leave-one-out cross-validation to estimate the performance characteristics of the model. RESULTS:Nine of our 20 case subjects were male. Cases' average age was 55.8, with an average BMI 29.5. Bivariable analysis identified 5 metabolites associated with positive stress tests (FDR < 0.2): alanine, C14:1-OH, C16:1, C18:2, C20:4. The multivariable regularized linear models built on T0 and T2 had Area Under the ROC Curve (AUC-ROC) between 0.5 and 0.55, however, the log(T2/T0) model yielded 0.625 AUC, with 65% sensitivity and 60% specificity. The top metabolites selected by the model were: Ala, Arg, C12-OH/C10-DC, C14:1-OH, C16:1, C18:2, C18:1, C20:4 and C18:1-DC. CONCLUSIONS:Stress-delta metabolite analysis of patients undergoing stress testing is feasible. Future studies with a larger sample size are warranted.

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Citation

Published Version (Please cite this version)

10.1371/journal.pone.0211762

Publication Info

Limkakeng, Alexander T, Ricardo Henao, Deepak Voora, Thomas O'Connell, Michelle Griffin, Ephraim L Tsalik, Svati Shah, Christopher W Woods, et al. (2019). Pilot study of myocardial ischemia-induced metabolomic changes in emergency department patients undergoing stress testing. PloS one, 14(2). p. e0211762. 10.1371/journal.pone.0211762 Retrieved from https://hdl.handle.net/10161/20602.

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Scholars@Duke

Limkakeng

Alexander Tan Limkakeng

Professor of Emergency Medicine

Dr. Alexander T. Limkakeng, Jr., MD, MHSc, FACEP is a Professor of Emergency Medicine, Vice Chair of Clinical Research, Director of the Acute Care Research Team, and Director of the Resident Research Fellowship for the Department of Emergency Medicine in the Duke University School of Medicine in Durham, North Carolina.

Dr. Limkakeng has served as chair of the American College of Emergency Physicians (ACEP) Research Committee, and been the Course Director of the ACEP Research Forum from 2016-2018, the largest emergency medical research platform in the nation. He is also the Assistant Director of ACEP’s Emergency Medicine Basic Research Skills course. He was elected to the Nominating Committee of the Society of Academic Emergency Medicine.

As a researcher, Dr. Limkakeng has led multiple clinical trials and interdepartmental sponsored projects and is author on over 100 peer-reviewed manuscripts. These include studies in emergency conditions such as COVID-19, traumatic brain injury, hypertension, heart failure, thrombosis, stroke, envenomations, and septic shock. His research has been funded by grants and contracts totaling over $9 million dollars. He has lectured internationally on acute coronary syndrome, responsible conduct of research, design of clinical trials, and precision medicine in emergency care. He has led Duke’s involvement in NIH-funded research networks and in industry-funded work that led to FDA approval for multiple high-sensitivity cardiac troponin assays and point-of-care COVID-19 diagnostic tests. He has servesd as Co-PI for the Duke U24 Hub in the NIH Early Phase Pain Investigation Clinical Network (EPPIC-Net) (1U24NS114416) and now serves as a co-PI on the Duke U24 Hub award (1U24NS129498) in the NIH Strategies to Innovate Emergency Care Clinical Trials (SIREN) Network and in the NIH NINDS Strokenet network (1U24NS135250)

His personal research interest is finding new ways to diagnose acute coronary syndrome. In particular, he is interested in novel biomarkers and precision medicine approaches to this problem. The common element throughout this work is a focus on time-sensitive health conditions.
Henao

Ricardo Henao

Associate Professor of Biostatistics & Bioinformatics
Voora

Deepak Voora

Associate Professor of Medicine
Tsalik

Ephraim Tsalik

Adjunct Associate Professor in the Department of Medicine

My research at Duke has focused on understanding the dynamic between host and pathogen so as to discover and develop host-response markers that can diagnose and predict health and disease.  This new and evolving approach to diagnosing illness has the potential to significantly impact individual as well as public health considering the rise of antibiotic resistance.

With any potential infectious disease diagnosis, it is difficult, if not impossible, to determine at the time of presentation what the underlying cause of illness is.  For example, acute respiratory illness is among the most frequent reasons for patients to seek care. These symptoms, such as cough, sore throat, and fever may be due to a bacterial infection, viral infection, both, or a non-infectious condition such as asthma or allergies.  Given the difficulties in making the diagnosis, most patients are inappropriately given antibacterials.  However, each of these etiologies (bacteria, virus, or something else entirely) leaves a fingerprint embedded in the host’s response. We are very interested in finding those fingerprints and exploiting them to generate new approaches to understand, diagnose, and manage disease.

These principles also apply to sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Just as with acute respiratory illness, it is often difficult to identify whether infection is responsible for a patient’s critical illness.  We have embarked on a number of research programs that aim to better identify sepsis; define sepsis subtypes that can be used to guide future clinical research; and to better predict sepsis outcomes.  These efforts have focused on many systems biology modalities including transcriptomics, miRNA, metabolomics, and proteomics.  Consequently, our Data Science team has utilized these highly complex data to develop new statistical methods, furthering both the clinical and statistical research communities.

These examples are just a small sampling of the breadth of research Dr. Tsalik and his colleagues have conducted.  

In April 2022, Dr. Tsalik has joined Danaher Diagnostics as the VP and Chief Scientific Officer for Infectious Disease, where he is applying this experience in biomarkers and diagnostics to shape the future of diagnostics in ID. 

Shah

Svati Hasmukh Shah

Ursula Geller Distinguished Professor of Research in Cardiovascular Diseases
Woods

Christopher Wildrick Woods

Wolfgang Joklik Distinguished Professor of Global Health

1. Emerging Infections
2. Global Health
3. Epidemiology of infectious diseases
4. Clinical microbiology and diagnostics
5. Bioterrorism Preparedness
6. Surveillance for communicable diseases
7. Antimicrobial resistance

Ginsburg

Geoffrey Steven Ginsburg

Adjunct Professor in the Department of Medicine

Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms for developing and translating genomic information into medical practice and the integration of personalized medicine into health care.


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