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.
Using the vast genotype data archive of the UK Biobank, the proposed study aims to address three research questions:
* Are there combinatorial genotypic variant signatures common to broad categories of disease such as all cancers, all psychiatric disorders, or all musculoskeletal disorders?
* Conversely, are there combinatorial genotypic variant signatures associated with protection from broad categories of disease, such as cancer or cardiovascular disease?
* Are there combinatorial genotypic variant signatures allowing stratification of patients that could inform the risk of developing a disorder or its complications when affected and likelihood of drug therapy response?
Successful results would include
* Identification of individual variants (SNPs), multi-SNP clusters and/or multi-SNP & phenotype factor clusters that are commonly associated with broad categories of disease, that is, found in significantly higher numbers of cases compared to healthy controls
* Identification of protective multi-SNP signatures that are found in significantly larger numbers of healthy controls compared to afflicted individuals
* Identification of groups of patients most at risk of developing a disorder, with potential development of personalized combinatorial risk scores
* Stratification of patients for optimal therapy
* Identification of new drug targets for treatment or prevention of disease either through repurposing of known drugs or through design of novel drugs
PrecisionLife would like to extend the current scope of the project to include the use of WGS/WES data in UK Biobank to supplement and/or validate the findings generated by this Project from genotype data across a wide range of chronic disease areas.
This would enable better insights into:
- Identification of novel targets and patient stratification insights from combinatorial analysis of multi-omic features associated with disease risk/severity. Using whole genome and exome sequencing data will allow inclusion of a larger number of unbiased SNPs and genomic structural variations in the analyses.
- In silico validation of novel targets that were previously identified from UK Biobank genotype data using whole genome and exome sequencing data. This would involve detailed analysis of the roles and relevance of rare variants and structural variations associated with the targets.
- Development of whole-genome sequencing patient stratification biomarkers that can be used to stratify patients based on their disease risk/progression or treatment response.
- Enablement of new combinatorial analyses avoiding imputation in rarer disease areas with insufficient patient numbers in UK Biobank where other public or proprietary disease datasets have non-overlapping genotype data with the UK Biobank array data.