دورية أكاديمية
Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance
| العنوان: | Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance |
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| المؤلفون: | Emily R. Ko, Megan E. Reller, L. Gayani Tillekeratne, Champica K. Bodinayake, Cameron Miller, Thomas W. Burke, Ricardo Henao, Micah T. McClain, Sunil Suchindran, Bradly Nicholson, Adam Blatt, Elizabeth Petzold, Ephraim L. Tsalik, Ajith Nagahawatte, Vasantha Devasiri, Matthew P. Rubach, Venance P. Maro, Bingileki F. Lwezaula, Wasantha Kodikara-Arachichi, Ruvini Kurukulasooriya, Aruna D. De Silva, Danielle V. Clark, Kevin L. Schully, Deng Madut, J. Stephen Dumler, Cecilia Kato, Renee Galloway, John A. Crump, Geoffrey S. Ginsburg, Timothy D. Minogue, Christopher W. Woods |
| المصدر: | Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023) |
| بيانات النشر: | Nature Portfolio, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | Abstract 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. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2045-2322 |
| العلاقة: | https://doaj.org/toc/2045-2322Test |
| DOI: | 10.1038/s41598-023-49734-6 |
| الوصول الحر: | https://doaj.org/article/6b810e23001a49d88802db46e9e5c9d3Test |
| رقم الانضمام: | edsdoj.6b810e23001a49d88802db46e9e5c9d3 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20452322 |
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| DOI: | 10.1038/s41598-023-49734-6 |