Multi-scale Modeling and Viral Pandemics (12/9/2021)

Contributors
Slim Fourati, Emory University School of Medicine. Title: Ab initio molecular signatures predictive of susceptibility to viral infection.

Bingyang Wei, Texas Christian University. Title: Just Enough Requirements Engineering for Non-Computer Science Majors.
Institution/ Affiliation
Slim Fourati, Emory University School of Medicine.

Bingyang Wei, Texas Christian University.
Presentation Details (date, conference, etc.)

December 9, 2021, IMAG/MSM WG on Multiscale Modeling and Viral Pandemics

  1. Slim Fourati, Emory University School of Medicine. Title: Ab initio molecular signatures predictive of susceptibility to viral infection. Abstract: The response to respiratory viruses varies substantially between individuals, and little is known on molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine whether pre- or early post-exposure molecular factors could predict physiologic responses to viral exposure. Using peripheral blood gene expression profiles collected from healthy subjects prior to exposure to one of four respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV), as well as up to 24 h following exposure, we find that it is possible to construct models predictive of symptomatic response using profiles even prior to viral exposure. Analysis of predictive gene features reveals little overlap among models; however, in aggregate, these genes are enriched for common pathways. Heme metabolism, the most significantly enriched pathway, is associated with a higher risk of developing symptoms following viral exposure. This study demonstrates that pre-exposure molecular predictors can be identified and improves our understanding of the mechanisms of response to respiratory viruses. YouTube and Slides.
    https://www.nature.com/articles/s41467-018-06735-8 
  2. Bingyang Wei, Texas Christian University. Title: Just Enough Requirements Engineering for Non-Computer Science Majors. YouTube and Slides.