COVID-19 Disease Study

Generating more insights, faster, from smaller datasets

Healthcare Biopharma

View all disease studies

68

novel gene targets identified - 70% of these are now independently validated

29

opportunities for approved drugs and candidates that could be repurposed as COVID-19 treatments

13

of these drug candidates evaluated in clinical trials

Overview

As the first wave of the COVID-19 pandemic surged around the world in early 2020, scientists and clinicians united in an unprecedented effort to understand the disease, its diverse symptoms and severities, and how to treat it. As part of this effort, we analyzed genetic host response risk factors in the first small cohort of 779 severe COVID-19 patients reported from the UK Biobank.

Using our unique combinatorial analytics platform, we identified drivers of different aspects of disease biology in specific patient subgroups and generated insights into the genetics, clinical presentation, pathology, and treatment of COVID-19 patients. The level of insights generated are not achievable with other analysis tools.

The SARS-CoV-2 virus posed an unprecedented new threat to world health, and in early 2020 the clinical implications for patients were unclear. There were no approved vaccines for COVID-19, and the only genetic associations identified for severe COVID-19 risk were linked to the ABO gene and a narrow region on chromosome 3¹. The medical community scrambled to understand the range of symptoms the disease caused and why some patients only presented with mild symptoms, but others developed life-threatening disease.

We seized the opportunity to analyze the first small cohort of 779 severe COVID-19 patients reported in the UK Biobank. We wanted to shed light on which host genes were implicated with the most severe forms of the disease and why there were so many different symptoms.

Novel disease-associated mechanisms that we identified were validated by subsequent combinatorial analysis of the de-identified patient health records (non-genetic data comprising longitudinal diagnosis, claims, and lab data) in the UnitedHealth Group COVID-19 Data Suite. Several of the novel targets have also been subsequently validated in collaborative studies into drug repurposing using viral plaque assays and other disease models^2,3.

COVID-19 Disease Architecture

genes associated with host immune response to virus infection

genes associated with regulation of inflammatory cytokines

genes for lipid storage, signaling and droplet production

genes associated with cardiovascular and endothelial cell functions

genes associated with Wnt/B-catenin signaling

genes associated with neurodegenerative diseases

Druggable targets associated with ARDS, sepsis and other life-threatening complications

Our approach outperformed global efforts to identify genetic factors for severe COVID-19 susceptibility, producing more proprietary insights, novel clinical biomarkers, and novel drug targets than any other analysis.

Our first COVID-19 analysis was completed 12 months earlier than COVID-19 Host Genetics Initiative – within just 3 weeks of the first UK Biobank dataset on ~750 patients becoming available.

In our analysis, we identified many more loci and genes associated with severe COVID-19 than any study performed since, including the results from global research collaborations that had more time, resource, and data.

We were the first to report 68 genes associated with severe disease and linked to all the major symptoms. These findings (including 48 of the genes and 13 drug repurposing candidates) have since been extensively validated by our collaborators and independently by other groups around the world.

Publications and Collaborators - frontiers

Combinatorial analysis of phenotypic and clinical risk factors associated with hospitalized COVID-19 patients

Read the paper

The COVID-19 PHARMACOME: Rational Selection of Drug Repurposing Candidates from Multimodal Knowledge Harmonization

Read the paper

Our initial COVID-19 study identified shared genetic risk factors in sepsis and high mortality risk patients plus 59 drug repurposing candidates

Read the paper

Analysis of Genetic Host Response Risk Factors in Severe COVID-19 Patients

Read the paper

References

Shelton, J.F., Shastri, A.J., Ye, C. et al. Trans-ancestry analysis reveals genetic and nongenetic associations with COVID-19 susceptibility and severity. Nat Genet 53, 801–808 (2021). https://doi.org/10.1038/s41588-021-00854-7
Schultz, B., Zaliani, A., Ebeling, C. et al. A method for the rational selection of drug repurposing candidates from multimodal knowledge harmonization. Sci Rep 11,11049 (2021); doi: https://doi.org/10.1038/s41598-021-90296-2
Sugiyama MG, Cui H, Redka DS, Karimzadeh M et al. Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease. bioRxiv 2021.04.13.439274; doi: https://doi.org/10.1101/2021.04.13.439274
Analysis of Genetic Host Response Risk Factors in Severe COVID-19 Patients. https://www.medrxiv.org/content/10.1101/2020.06.17.20134015v2.full.pdf (2020)
Das, S., Pearson, M., Taylor, K. et al. (2021) Combinatorial analysis of phenotypic and clinical risk factors associated with hospitalized COVID-19 patients Front. Digit. Health, 08 July 2021 | https://doi.org/10.3389/fdgth.2021.660809
COVID-19 Host Genetics Initiative. Mapping the human genetic architecture of COVID-19. Nature (2021)

COVID-19 Disease Study

Generating more insights, faster, from smaller datasets

68

29

13

Overview

Background

Understanding COVID-19 and finding novel drug targets

COVID-19 Disease Architecture

Outcomes and validation

Comparison of global efforts to identify genetic factors for severe COVID-19 susceptibility

Read more about the validation of our COVID-19 data

Collaborators

United Healthcare

Optum Labs

UK Biobank

Publications

Ongoing studies

Long COVID

References

Discuss our Covid-19 Disease Study

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