Human genetic and metabolite variation reveals that methylthioadenosine is a prognostic biomarker and an inflammatory regulator in sepsis
Abstract
Sepsis is a deleterious inflammatory response to infection with high mortality. Reliable
sepsis biomarkers could improve diagnosis, prognosis, and treatment. Integration of
human genetics, patient metabolite and cytokine measurements, and testing in a mouse
model demonstrate that the methionine salvage pathway is a regulator of sepsis that
can accurately predict prognosis in patients. Pathway-based genome-wide association
analysis of nontyphoidal Salmonella bacteremia showed a strong enrichment for single-nucleotide
polymorphisms near the components of the methionine salvage pathway. Measurement of
the pathway’s substrate, methylthioadenosine (MTA), in two cohorts of sepsis patients
demonstrated increased plasma MTA in nonsurvivors. Plasma MTA was correlated with
levels of inflammatory cytokines, indicating that elevated MTA marks a subset of patients
with excessive inflammation. A machine-learning model combining MTA and other variables
yielded approximately 80% accuracy (area under the curve) in predicting death. Furthermore,
mice infected with Salmonella had prolonged survival when MTA was administered before
infection, suggesting that manipulating MTA levels could regulate the severity of
the inflammatory response. Our results demonstrate how combining genetic data, biomolecule
measurements, and animal models can shape our understanding of disease and lead to
new biomarkers for patient stratification and potential therapeutic targeting.
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https://hdl.handle.net/10161/13814Published Version (Please cite this version)
10.1126/sciadv.1602096Publication Info
Wang, L; Ko, ER; Gilchrist, JJ; Pittman, KJ; Rautanen, A; Pirinen, M; ... Ko, DC (2017). Human genetic and metabolite variation reveals that methylthioadenosine is a prognostic
biomarker and an inflammatory regulator in sepsis. Science Advances, 3(3). 10.1126/sciadv.1602096. Retrieved from https://hdl.handle.net/10161/13814.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.
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Show full item recordScholars@Duke
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.
Dennis Ko
Associate Professor in Molecular Genetics and Microbiology
Using Pathogens to Decipher Genetic Variation Connecting Cell Biology and Disease
SusceptibilityDespite improvements in public health, advancements in vaccines, and
the development of many classes of antibiotics, infectious disease is still responsible
for over a quarter of all deaths worldwide. However, even for the most devastating
of pandemics, individuals demonstrate a large variability in the severity of infection.
The long-term goal of the lab is to understand the ge
Emily Ray Ko
Assistant Professor of Medicine
Clinical and translational research, COVID-19 therapeutics, clinical biomarkers for
infectious disease.
Martin Arthur Moseley III
Adjunct Professor in the Department of Cell Biology
Raul Salinas
Research Associate, Senior
J. Will Thompson
Adjunct Assistant Professor in the Department of Pharmacology & Cancer Biology
Dr. Thompson's research focuses on the development and deployment of proteomics and
metabolomics mass spectrometry techniques for the analysis of biological systems.
He served as the Assistant Director of the Proteomics and Metabolomics Shared Resource
in the Duke School of Medicine from 2007-2021. He currently maintains collaborations
in metabolomics and proteomics research at Duke, and develops new tools for chemical
analysis as a Princi
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 pre
Liuyang Wang
Assistant Research Professor of Molecular Genetics and Microbiology
Leveraging bioinformatics and big data to understand the intricacies of human diseases.
My overall research goals are centered on unraveling the molecular mechanism underpinning
human disease susceptibility and harnessing these findings to innovative diagnostic
and therapeutic strategies. I have adopted a multidisciplinary approach that integrates
genomics, transcriptomics, and computational biology. Leveraging high-throughput cellular
screening and genome-wide associ
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
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