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Early prognosis of respiratory virus shedding in humans.

ABSTRACT: This paper addresses the development of predictive models for distinguishing pre-symptomatic infections from uninfected individuals. Our machine learning experiments are conducted on publicly available challenge studies that collected whole-blood transcriptomics data from individuals infected with HRV, RSV, H1N1, and H3N2. We address the problem of identifying discriminatory biomarkers between controls and eventual shedders in the first 32 h post-infection. Our exploratory analysis shows that the most discriminatory biomarkers exhibit a strong dependence on time over the course of the human response to infection. We visualize the feature sets to provide evidence of the rapid evolution of the gene expression profiles. To quantify this observation, we partition the data in the first 32 h into four equal time windows of 8 h each and identify all discriminatory biomarkers using sparsity-promoting classifiers and Iterated Feature Removal. We then perform a comparative machine learning classification analysis using linear support vector machines, artificial neural networks and Centroid-Encoder. We present a range of experiments on different groupings of the diseases to demonstrate the robustness of the resulting models.

SUBMITTER: Aminian M

PROVIDER: S-EPMC8387366 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Early prognosis of respiratory virus shedding in humans.

Aminian M M Ghosh T T Peterson A A Rasmussen A L AL Stiverson S S Sharma K K Kirby M M

Scientific reports 20210825 1

This paper addresses the development of predictive models for distinguishing pre-symptomatic infections from uninfected individuals. Our machine learning experiments are conducted on publicly available challenge studies that collected whole-blood transcriptomics data from individuals infected with HRV, RSV, H1N1, and H3N2. We address the problem of identifying discriminatory biomarkers between controls and eventual shedders in the first 32 h post-infection. Our exploratory analysis shows that th ...[more]

PMID: 34433834

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Project description:Respiratory viruses are a cause of upper respiratory tract infections (URTI), but can be associated with severe lower respiratory tract infections (LRTI) in immunocompromised patients. The objective of this study was to investigate the genetic variability of influenza virus, parainfluenza virus and respiratory syncytial virus (RSV) and the duration of viral shedding in hematological patients. Nasopharyngeal swabs from hematological patients were screened for influenza, parainfluenza and RSV on admission as well as on development of respiratory symptoms. Consecutive swabs were collected until viral clearance. Out of 672 tested patients, a total of 111 patients (17%) were infected with one of the investigated viral agents: 40 with influenza, 13 with parainfluenza and 64 with RSV; six patients had influenza/RSV or parainfluenza/RSV co-infections. The majority of infected patients (n = 75/111) underwent stem cell transplantation (42 autologous, 48 allogeneic, 15 autologous and allogeneic). LRTI was observed in 48 patients, of whom 15 patients developed severe LRTI, and 13 patients with respiratory tract infection died. Phylogenetic analysis revealed a variety of influenza A(H1N1)pdm09, A(H3N2), influenza B, parainfluenza 3 and RSV A, B viruses. RSV A was detected in 54 patients, RSV B in ten patients. The newly emerging RSV A genotype ON1 predominated in the study cohort and was found in 48 (75%) of 64 RSV-infected patients. Furthermore, two distinct clusters were detected for RSV A genotype ON1, identical RSV G gene sequences in these patients are consistent with nosocomial transmission. Long-term viral shedding for more than 30 days was significantly associated with prior allogeneic transplantation (p = 0.01) and was most pronounced in patients with RSV infection (n = 16) with a median duration of viral shedding for 80 days (range 35-334 days). Long-term shedding of respiratory viruses might be a catalyzer of nosocomial transmission and must be considered for efficient infection control in immunocompromised patients.

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Early prognosis of respiratory virus shedding in humans.

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Early prognosis of respiratory virus shedding in humans.

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