| Application: | 44288, A meta-investigation of combinatorial mutation signatures in broad disease categories |
| Title: | Analysis of Genetic Host Response Risk Factors in Severe COVID-19 Patients |
| Size: | 879511 B |
| Archived: | 19 Mar 2021 |
| Stability: | Complete |
| Personal: | No individual-level data |
Return 3252
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Notes
BACKGROUNDEpidemiological studies indicate that as many as 20% of individuals who test positive for COVID-19 develop severe symptoms that can require hospitalization. These symptoms include low platelet count, severe hypoxia, increased inflammatory cytokines and reduced glomerular filtration rate. Additionally, severe COVID-19 is associated with several chronic co-morbidities, including cardiovascular disease, hypertension and type 2 diabetes mellitus. The identification of genetic risk factors that impact differential host responses to SARS-CoV-2, resulting in the development of severe COVID-19, is important in gaining greater understanding into the biological mechanisms underpinning life-threatening responses to the virus. These insights could be used in the identification of high-risk individuals and for the development of treatment strategies for these patients.
METHODS
As of June 6, 2020, there were 976 patients who tested positive for COVID-19 and were hospitalized, indicating they had a severe response to SARS-CoV-2. There were however too few patients with a mild form of COVID-19 to use this cohort as our control population. Instead we used similar control criteria to our previous study looking at shared genetic risk factors between severe COVID-19 and sepsis, selecting controls who had not developed sepsis despite having maximum comorbidity risk and exposure to sepsis-causing pathogens.
RESULTS
Using a combinatorial (high-order epistasis) analysis approach, we identified 68 proteincoding genes that were highly associated with severe COVID-19. At the time of analysis, nine of these genes have been linked to differential response to SARS-CoV-2. We also found many novel targets that are involved in key biological pathways associated with the development of severe COVID-19, including production of pro-inflammatory cytokines, endothelial cell dysfunction, lipid droplets, neurodegeneration and viral susceptibility factors.
CONCLUSION
The variants we found in genes relating to immune response pathways and cytokine production cascades, were in equal proportions across all severe COVID-19 patients, regardless of their co-morbidities. This suggests that such variants are not associated with any specific comorbidity, but are common amongst patients who develop severe COVID-19. Among the 68 severe COVID-19 risk-associated genes, we found several druggable protein targets and pathways. Nine are targeted by drugs that have reached at least Phase I clinical trials, and a further eight have active chemical starting points for novel drug development. Several of these targets were particularly enriched in specific co-morbidities, providing insights into shared pathological mechanisms underlying both the development of severe COVID-19, ARDS and these predisposing co-morbidities. We can use these insights to identify patients who are at greatest risk of contracting severe COVID-19 and develop targeted therapeutic strategies for them, with the aim of improving disease burden and survival rates.
Application 44288
A meta-investigation of combinatorial mutation signatures in broad disease categories
The proposed study aims to address three research questions: * Are there genetic defect patterns common to broad categories of disease such as all cancers, all psychiatric disorders, or all musculoskeletal disorders? * Conversely, are there genetic patterns that help protect people against broad categories of disease, such as cancer or cardiovascular disease? * Are there genotypic variant signatures allowing stratification of patients that could inform the risk of developing a disorder and likelihood of drug therapy response? The proposed research would improve our understanding of the genomic basis of disease formation (or disease prevention). We hope to identify individual genetic defects or combinatorial defect clusters that are commonly associated with broad categories of disease, that is, found in significantly higher numbers of patients compared to healthy controls. Similarly, we hope to identify protective signatures that are found in many more healthy controls compared to afflicted individuals. In addition, we hope to develop new improved ways of identifying patients at risk of developing a disease or its complications, and enable patients to be treated with a drug therapy regimen that is tailored to their individual needs. Successful results would help future researchers identify means to increase human longevity and wellness by manipulating genetic mechanisms involved in broad categories of disease. Through follow-on studies, researchers may identify new drugs that work across broad categories of disease. Such drugs with broad applicability may cost less to develop, test, and bring to market, thus helping everyone afflicted with those diseases. Tailoring therapies to patients' individual needs may significantly reduce the burden on the healthcare system through reduced side effects due to drug interaction or lack of therapy response, leading to hospital admissions. The project duration is 24 months.
| Lead investigator: | Dr Sayoni Das |
| Lead institution: | PrecisionLife Ltd |
2 related Returns
| Return ID | App ID | Description | Archive Date |
|---|---|---|---|
| 3251 | 44288 | Identification and Analysis of Shared Risk Factors in Sepsis and High Mortality Risk COVID-19 Patients | 19 Mar 2021 |
| 3134 | 44288 | Systematic drug repurposing to enable precision medicine: A case study in breast cancer | 18 Feb 2021 |
1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 3253 | Analysis of Genetic Host Response Risk Factors in Severe COVID-19 Patients | Taylor et al | 2014 | medRxiv (2020) |
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