Renal systems biology of patients with systemic inflammatory response syndrome.

Abstract

A systems biology approach was used to comprehensively examine the impact of renal disease and hemodialysis (HD) on patient response during critical illness. To achieve this, we examined the metabolome, proteome, and transcriptome of 150 patients with critical illness, stratified by renal function. Quantification of plasma metabolites indicated greater change as renal function declined, with the greatest derangements in patients receiving chronic HD. Specifically, 6 uremic retention molecules, 17 other protein catabolites, 7 modified nucleosides, and 7 pentose phosphate sugars increased as renal function declined, consistent with decreased excretion or increased catabolism of amino acids and ribonucleotides. Similarly, the proteome showed increased levels of low-molecular-weight proteins and acute-phase reactants. The transcriptome revealed a broad-based decrease in mRNA levels among patients on HD. Systems integration revealed an unrecognized association between plasma RNASE1 and several RNA catabolites and modified nucleosides. Further, allantoin, N1-methyl-4-pyridone-3-carboxamide, and N-acetylaspartate were inversely correlated with the majority of significantly downregulated genes. Thus, renal function broadly affected the plasma metabolome, proteome, and peripheral blood transcriptome during critical illness; changes were not effectively mitigated by hemodialysis. These studies allude to several novel mechanisms whereby renal dysfunction contributes to critical illness.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1038/ki.2015.150

Publication Info

Tsalik, Ephraim L, Laurel K Willig, Brandon J Rice, Jennifer C van Velkinburgh, Robert P Mohney, Jonathan E McDunn, Darrell L Dinwiddie, Neil A Miller, et al. (2015). Renal systems biology of patients with systemic inflammatory response syndrome. Kidney Int, 88(4). pp. 804–814. 10.1038/ki.2015.150 Retrieved from https://hdl.handle.net/10161/13306.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

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. 

Fowler

Vance Garrison Fowler

Florence McAlister Distinguished Professor of Medicine

Determinants of Outcome in Patients with Staphylococcus aureus Bacteremia
Antibacterial Resistance
Pathogenesis of Bacterial Infections
Tropical medicine/International Health

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


Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.