Our Work

Global Febrile Illness Diagnostics

Project Objectives

**Task 1.**
Develop and deliver a validated, highly accurate (>85%) host-based RNA assay for the diagnosis of viral and bacterial infections inclusive of pathogens of emerging importance for the global warfighter.

**Task 1.1.**
Leverage existing clinical samples for gene expression assay development. We will generate host gene expression RNA sequencing data from existing, exquisitely phenotyped, clinically relevant samples. Deliverable: Whole blood gene expression data from patients with infection due to bacterial infections (n=120) including typical gram-positive, gram-negative, and those pathogens with special relevance to the global warfighter (e.g., Brucella spp., Coxiella burnettii, Leptospira, Salmonella spp.), viral infections (n=120) including influenza/RSV/HRV, dengue, and chikungunya and patients with non-infectious illness (n=60). [8 month mark]

**Task 1.2.**
Evaluation of existing classifiers for respiratory bacterial and viral infection in the existing cohort of well-phenotyped patients with confirmed infections of relevance to the modern global warfighter (Assay v1.0). Deliverable: Assessment of performance of existing classifiers including AUC, sensitivity, specificity, negative and positive predictive values. [12 month mark]

**Task 1.3.**
Generate and validate novel classifiers of viral, bacterial, and non-infectious illness inclusive of diseases relevant to the modern global warfighter (Assay v2.0). We will use the data generated in Task 1.1 to develop gene expression classifiers using both well-known and novel statistical methods. Deliverable: Validated mRNA biomarker panel to differentiate bacterial vs. viral vs. non-infectious illness. [18 month mark]

**Task 1.4.**
Migrate and optimize classifiers to an RT-PCR platform (Assay v.2.0) and validate in additional samples from our well-phenotyped global biorepository. Deliverable: Validated RT-PCR assay (2.0) for differentiating viral, bacterial, and non-infectious illness for diseases relevant to the modern global warfighter. [24 month mark]

**Task 1.5.**
Translate to a primate ortholog assay (RT-PCR) for ultimate use in samples from previous and ongoing NHP challenge studies with high consequence global pathogens (e.g., viral hemorrhagic fever, B. pseudomallei, monkeypox). Deliverable: RT-PCR assay (v3.0) for differentiating viral, bacterial, and non-infectious illness optimized for use in NHP used in USAMRIID protocols. [36 month mark]

**Task 2.**
Develop and deliver a validated, host-based protein assay for the diagnosis of viral and bacterial infections inclusive of pathogens of emerging importance for the global warfighter.

**Task 2.1.**
Complete unbiased proteomic investigation from plasma samples from patients with adjudicated viral or bacterial infection, and non-infectious SIRS controls. We will generate unbiased proteomic data from existing samples. Deliverable: Unbiased proteomic data from the patients in Task 1.1. [12 month mark]

**Task 2.2.**
Statistical modeling of an optimized and minimized protein/pathway set capable of discriminating pathogen class with > 85% accuracy. We will use the data generated in Task 2.1 to develop proteomic classifiers using sparse classification methods and discriminative factor models and assess performance metrics for the assay from Task 2.2 including sensitivity, specificity, and AUC, and optimize the composition of the classifier. Deliverable 1: Proteomic biomarker panel to differentiate bacterial vs. viral vs. non-infectious illness. [18 month mark] Deliverable 2: Performance metrics of the classifier and optimized composition. [24 month mark]

**Task 2.3.**
Development of quantitative MRM assays for diagnosis of viral vs bacterial infection. We will migrate the classifier from Task 2.2 to a MRM assay platform and test the MRM assay on existing samples and define performance metrics of the assay. Deliverable 1: An optimized bacterial/viral/non-infectious classifier on a non

Project Policy Impact Description

At present, our ability to identify the etiology of febrile illness is limited by nonspecific clinical presentations, low sensitivity and prolonged time to positivity of current pathogen specific methods, and in some cases difficulty in determining whether presence of pathogen alone indicates invasive disease. Consequently, there is a compelling need for novel diagnostic approaches to accurately discriminate between viral and bacterial etiology versus non-infectious causes of febrile illness. The host response to pathogens uses pattern recognition receptors tied to specific transcriptional responses that can be measured at the mRNA and protein levels [16, 17]. We hypothesize that we can harness this response to generate robust classifiers and high fidelity assays to distinguish bacterial and viral illnesses that are inclusive of high consequence pathogens of relevance to the modern warfighter. In previous work, we have demonstrated that the host response to common pathogens, in the form of pathogen-class specific, host gene expression classifiers, can address this diagnostic dilemma. The concept of host-based biomarkers of infection is not new. However, only recently has progress in technology for generation of genomic and proteomic data coupled with advances in mathematical and statistical analysis of complex data sets allowed the prospect of rapid and accurate prediction of infection based upon host biomarker profiling. Our team has been at the forefront in the development of host biomarker classifiers of infectious diseases[1-4, 18-20]. We have previously demonstrated that the host response transcriptome, proteome, and metabolome discern pathogen class exposure with high fidelity and specificity. Furthermore, the host response classifiers we have developed can predict those who will go on to symptomatic disease among an exposed population who have not yet developed symptoms. In the proposed work, we will use our existing biorepository of exquisitely phenot

Faculty

Department & School

Medicine: Infectious Diseases
School of Medicine

Collaborators

  • USAMRIID

Project Status

Ongoing

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