Approved Research
Validating and characterising candidate genes for allele-specific nucleic acid therapies
Approved Research ID: 89567
Approval date: November 29th 2022
Lay summary
Our genome contains two copies of each human gene, each inherited from one parent. People inheriting an aberrant gene from one of their parents have an elevated risk of developing a genetic disease: While the normal gene produces a normal protein, the aberrant gene might produce a damaged protein that can lead to disease. This is the underlying cause for well-known diseases including lupus, Alzheimer's, and Parkinson's disease.
RNA interference (RNAi) is a biological mechanism that can silence specific genes. We can leverage this mechanism to design therapies that silence a target aberrant gene, while keeping the normal gene intact. Although a promising approach, many questions need to be answered before developing an RNAi therapy: Which mutation causes a gene to become aberrant? How can we verify that silencing the aberrant gene indeed alleviates the disease? What are the implications of silencing the aberrant gene? These questions can be addressed by analysing a dataset of individuals with measured genetic sequences and detailed biological measurements. The UK Biobank is one of the world's largest, most detailed such datasets, and is thus well-suited to address these questions.
In this project, we aim to leverage the wealth of data in the UK Biobank to advance our efforts to design RNAi therapies. Specifically, we aim to use the UK Biobank to guide our research and development efforts, focusing on several goals: First, we will study mutations that can cause genes to become aberrant (based on a literature survey) and verify that these mutations can indeed lead to disease. Second, we will identify biological measurements (such as blood measurements) that can help indicate how strongly we managed to silence our target genes. Third, we will design computational methods to predict the biological impact of silencing a target gene, by predicting how this will affect the biological measurements we identified. The UK Biobank could help us to achieve these goals in a precise and cost-effective manner, with the aim of alleviating the burden of many devastating diseases.
The duration of our project is expected to last multiple years, as is typical for drug research and development. The key bottleneck is typically the lengthy experiments required for validating our bioinformatically-generated hypotheses.