AI-guided discovery of the invariant host response to viral pandemics

Sahoo, D.; Katkar, G. D.; Khandelwal, S.; Behroozikhah, M.; Claire, A.; Castillo, V.; Tindle, C.; Fuller, M.; Taheri, S.; Rogers, T. F.; Beutler, N.; Ramirez, S.; Rawlings, S. A.; Pretorius, V.; Smith, D.; Burton, D. R.; Alexander, L. C.; Duran, J. M.; Crotty, S.; Dan, J. M.; Das, S.; Ghosh, P.

doi:10.1101/2020.09.21.305698

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bioRxiv · 10.1101/2020.09.21.305698

AI-guided discovery of the invariant host response to viral pandemics

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Abstract

We sought to define the host immune response, a.k.a, the "cytokine storm" that has been implicated in fatal COVID-19 using an AI-based approach. Over 45,000 transcriptomic datasets of viral pandemics were analyzed to extract a 166-gene signature using ACE2 as a seed gene; ACE2 was rationalized because it encodes the receptor that facilitates the entry of SARS-CoV-2 (the virus that causes COVID-19) into host cells. Surprisingly, this 166-gene signature was conserved in all viral pandemics, including COVID-19, and a subset of 20-genes classified disease severity, inspiring the nomenclatures ViP and severe-ViP signatures, respectively. The ViP signatures pinpointed a paradoxical phenomenon wherein lung epithelial and myeloid cells mount an IL15 cytokine storm, and epithelial and NK cell senescence and apoptosis determines severity/fatality. Precise therapeutic goals were formulated and subsequently validated in high-dose SARS-CoV-2-challenged hamsters using neutralizing antibodies that abrogate SARS-CoV-2*ACE2 engagement or a directly acting antiviral agent, EIDD-2801. IL15/IL15RA were elevated in the lungs of patients with fatal disease, and plasma levels of the cytokine tracked with disease severity. Thus, the ViP signatures provide a quantitative and qualitative framework for titrating the immune response in viral pandemics and may serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs. One Sentence SummaryThe host immune response in COVID-19. PANEL: RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe SARS-CoV-2 pandemic has inspired many groups to find innovative methodologies that can help us understand the host immune response to the virus; unchecked proportions of such immune response have been implicated in fatality. We searched GEO and ArrayExpress that provided many publicly available gene expression data that objectively measure the host immune response in diverse conditions. However, challenges remain in identifying a set of host response events that are common to every condition. There are no studies that provide a reproducible assessment of prognosticators of disease severity, the host response, and therapeutic goals. Consequently, therapeutic trials for COVID-19 have seen many more misses than hits. This work used multiple (> 45,000) gene expression datasets from GEO and ArrayExpress and analyzed them using an unbiased computational approach that relies upon fundamentals of gene expression patterns and mathematical precision when assessing them. Added value of this studyThis work identifies a signature that is surprisingly conserved in all viral pandemics, including Covid-19, inspiring the nomenclature ViP-signature. A subset of 20-genes classified disease severity in respiratory pandemics. The ViP signatures pinpointed the nature and source of the cytokine storm mounted by the host. They also helped formulate precise therapeutic goals and rationalized the repurposing of FDA-approved drugs. Implications of all the available evidenceThe ViP signatures provide a quantitative and qualitative framework for assessing the immune response in viral pandemics when creating pre-clinical models; they serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs.

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Sahoo, D., Katkar, G. D., Khandelwal, S., Behroozikhah, M., Claire, A., Castillo, V., Tindle, C., Fuller, M., Taheri, S., Rogers, T. F., Beutler, N., Ramirez, S., Rawlings, S. A., Pretorius, V., Smith, D., Burton, D. R., Alexander, L. C., Duran, J. M., Crotty, S., Dan, J. M., Das, S., Ghosh, P.. 2020-09-22. AI-guided discovery of the invariant host response to viral pandemics. https://doi.org/10.1101/2020.09.21.305698

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