Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance.

Autor: Ko ER; Division of General Internal Medicine, Department of Medicine, Duke Regional Hospital, Duke University Health System, Duke University School of Medicine, 3643 N. Roxboro St., Durham, NC, 27704, USA. emily.rayko@duke.edu., Reller ME; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.; Durham Veterans Affairs Health Care System, Durham, NC, USA.; Duke Global Health Institute, Duke University, Durham, NC, USA., Tillekeratne LG; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.; Durham Veterans Affairs Health Care System, Durham, NC, USA.; Duke Global Health Institute, Duke University, Durham, NC, USA.; Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka., Bodinayake CK; Duke Global Health Institute, Duke University, Durham, NC, USA.; Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka., Miller C; Clinical Research Unit, Department of Medicine, Duke University School of Medicine, Durham, NC, USA., Burke TW; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA., Henao R; Department of Biostatistics and Informatics, Duke University, Durham, NC, USA., McClain MT; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.; Durham Veterans Affairs Health Care System, Durham, NC, USA., Suchindran S; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA., Nicholson B; Institute for Medical Research, Durham, NC, USA., Blatt A; Division of Pediatric Infectious Diseases, Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA., Petzold E; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA., Tsalik EL; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.; Danaher Diagnostics, Washington, DC, USA., Nagahawatte A; Department of Microbiology, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka., Devasiri V; Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka., Rubach MP; Durham Veterans Affairs Health Care System, Durham, NC, USA.; Duke Global Health Institute, Duke University, Durham, NC, USA.; Programme in Emerging Infectious Diseases, Duke-National University of Singapore, Singapore, Singapore.; Kilimanjaro Christian Medical Center, Moshi, Tanzania., Maro VP; Kilimanjaro Christian Medical Center, Moshi, Tanzania.; Kilimanjaro Christian Medical University College, Moshi, Tanzania., Lwezaula BF; Kilimanjaro Christian Medical University College, Moshi, Tanzania.; Maswenzi Regional Referral Hospital, Moshi, Tanzania., Kodikara-Arachichi W; Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka., Kurukulasooriya R; Department of Microbiology, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka., De Silva AD; General Sir John Kotelawala Defence University, Colombo, Sri Lanka., Clark DV; The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.; Austere Environments Consortium for Enhanced Sepsis Outcomes (ACESO), Biological Defense Research Directorate, Naval Medical Research Center-Frederick, Ft. Detrick, MD, USA., Schully KL; Austere Environments Consortium for Enhanced Sepsis Outcomes (ACESO), Biological Defense Research Directorate, Naval Medical Research Center-Frederick, Ft. Detrick, MD, USA., Madut D; Durham Veterans Affairs Health Care System, Durham, NC, USA.; Duke Global Health Institute, Duke University, Durham, NC, USA., Dumler JS; Joint Departments of Pathology, School of Medicine, Uniformed Services University, Bethesda, MD, USA., Kato C; Centers for Disease Control and Prevention, National Center for Emerging Zoonotic Infectious Diseases, Atlanta, USA., Galloway R; Centers for Disease Control and Prevention, National Center for Emerging Zoonotic Infectious Diseases, Atlanta, USA., Crump JA; Duke Global Health Institute, Duke University, Durham, NC, USA.; Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka.; Kilimanjaro Christian Medical Center, Moshi, Tanzania.; Kilimanjaro Christian Medical University College, Moshi, Tanzania.; Centre for International Health, University of Otago, Dunedin, New Zealand., Ginsburg GS; Department of Medicine, Duke University School of Medicine, Durham, NC, USA.; National Institute of Health, Bethesda, MD, USA., Minogue TD; Diagnostic Systems Division, USAMRIID, Fort Detrick, Frederick, MD, USA., Woods CW; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.; Durham Veterans Affairs Health Care System, Durham, NC, USA.; Duke Global Health Institute, Duke University, Durham, NC, USA.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2023 Dec 18; Vol. 13 (1), pp. 22554. Date of Electronic Publication: 2023 Dec 18.
DOI: 10.1038/s41598-023-49734-6
Abstrakt: Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.
(© 2023. The Author(s).)
Databáze: MEDLINE
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