| 要約: | In this thesis, the main scientific pursuit is that of leveraging information from genome-wide association studies (GWAS) in combination with gene expression datasets such as to narrow down the list of genes and cell-types that may be important for pharmacological targeting in heritable traits, particularly for inflammatory bowel disease (IBD). I will introduce this class of diseases and their particular manifestations, as well as the known environmental and genetic risk factors. Then, I will offer a brief review of the methods which have been used so far to highlight causal genes, pathways and cell-types using GWAS data. More focus is given towards the methods which use functional genomics data to augment the mechanism-seeking for GWAS hits. In chapter 2, I show through simulation that different genetic enrichment-testing methods can perform better than others depending on the architectural context. I also develop a novel meta-analysis technique which retains the best statistical power regardless of the particular genetic scenario being tested. I then apply these methods to datasets relevant for IBD research and identify actionable evidence, including cell-states and drugs that are likely to be important – as well as raising more questions about the complex aetiology of IBD. I dive into the difficulties and advantages of using single-cell gene expression data for these purposes, together with simulations to assess the precision of such investigations. Last but not least, the thesis showcases a novel RNA and chromatin accessibility dataset investigating the functions of different costimulations in T-cells. I then detail how this data helps us to interpret the functions of several GWAS risk variants in IBD and potentially other heritable immune traits.
|
|---|