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pmid:32995790
AI-guided discovery of the invariant host response to viral pandemics.
Debashis Sahoo · Gajanan D Katkar · Soni Khandelwal · Mahdi Behroozikhah · Amanraj Claire · Vanessa Castillo · Courtney Tindle · MacKenzie Fuller · Sahar Taheri · Thomas F Rogers · Nathan Beutler · Sydney I Ramirez · Stephen A Rawlings · Victor Pretorius · David M Smith · Dennis R Burton · Laura E Crotty Alexander · Jason Duran · Shane Crotty · Jennifer M Dan · Soumita Das · Pradipta Ghosh
bioRxiv : the preprint server for biology · 2021 doi:10.1101/2020.09.21.305698
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Complete file
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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 vi ral p andemics, 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.\nONE SENTENCE SUMMARY: The host immune response in COVID-19.\nPANEL RESEARCH IN CONTEXT: Evidence before this study: The 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 study: This 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 evidence: The 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.", "claims": [{"id": "claim-data-access", "statement": "We searched GEO and ArrayExpress that provided many publicly available gene expression data that objectively measure the host immune response in diverse conditions.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32995790", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We searched GEO and ArrayExpress that provided many publicly available gene expression data that objectively measure the host immune response in diverse conditions."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Over 45,000 transcriptomic datasets of viral pandemics were analyzed to extract a 166-gene signature using ACE2 as a ‘seed’ gene.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:32995790", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "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."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Over 45,000 transcriptomic datasets of viral pandemics were analyzed to extract a 166-gene signature using ACE2 as a ‘seed’ gene.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:32995790"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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