Assessment of genotype-to-phenotype relationships for the purpose of novel therapeutic development
Approved Research ID: 53192
Approval date: December 17th 2019
NGM is a research-focused drug discovery company with an 11-year history of making important contributions to basic biomedical research and transforming those discoveries into novel therapeutics. NGM recognizes the immense importance of human genetics and the UK Biobank's extensive phenotypic data as a means for both novel target discovery and for determining the patients most likely to benefit from the therapies we are currently developing. With clinical programs in the areas of liver disease, metabolic disease, ophthalmology and oncology, the diversity of our interests nicely parallels the diversity of phenotypic data available in the biobank. NGM would specifically like to explore genotype-phenotype relationships within these data with the ultimate goal of translating those discoveries into new treatments for disease. We will start by applying statistical genetics approaches which will mainly focus on rarely-occurring DNA variants which are found in just a handful of people. By comparing their unique genetics to the broad assortment of traits, we can better understand the relationship between the genes and patient health. Understanding the connection in humans between certain genes and the traits that they govern is an essential first step in developing new therapies that will ultimately benefit a large number of patients. The therapies currently under development at NGM would also benefit as our insight into the human biology of their protein targets is fairly limited. We also plan to publish our findings from this work, as we have done many times in the past (i.e. Hsu et al. Nature 2017, Ge et al. Cell Metab. 2018, Harrison et al. Lancet 2018), so that these data can be shared with the scientific community and the public. This motivation precisely fits the UK Biobank's desire to support health-related research and advance the public interest.
Drug discovery and development is plagued by clinical failures that result from a lack of continuity between the biology of the animal models where these targets are validated and the human disease. Drug targets with human genetics support have been demonstrated to be many times more likely to succeed in clinical development for just this reason. Thus, we aim to apply the genotype and phenotype data available in the biobank to better understand the human biology of targets for which we have drugs currently in development and to identify new targets for diseases with significant unmet medical needs.
We aim to apply standard GWAS and PheWAS approaches for unbiased genome and phenome-wide discovery enhanced by a focused effort to characterize the functional impact of missense variants for targets of particular interest. We also will pay close attention to individuals that are homozygous carriers for rare, loss-of-function variants as phenotypic data from even a single individual may elucidate novel human biology.
Independent associations between different cardiovascular risk factors/genetic variants with heart failure with preserved ejection fraction (HFpEF) versus reduced ejection fraction (HFrEF) have not been fully understood. We will conduct a population genetics-based rare variants study to identify modifier genes affecting the variability in the heart failure outcome. The strategy is to study the clinical measurements of HFpEF and HFrEF and their comorbid conditions available in UK Biobank data and further conduct cross-phenotype or phenotype-modifying genetic study.