Single-cell expression quantitative trait loci in brain health and disease: a framework for drug target and biomarker discovery

Disorders of the brain and nervous system are a leading cause of disability worldwide, spanning a wide range of phenotypes across the neurological, psychiatric, behavioural and structural spectrum. In an otherwise complicated model where phenotypic presentation is the result of complex interplay between genetics and environment, the study of their genetic architecture provides an anchor point to understand the relationships between genetic variation, phenotypic risk and the molecular mechanisms between them. In the past twenty years, genome-wide association studies (GWAS) combined with molecular quantitative trait loci (QTL) projects have identified thousands of genetic variants and the genes they regulate associated with brain-related phenotypes. Only recently has it been possible to profile molecular traits at the single-cell level, providing a new and context-specific dimension to study these relationships. In Chapter 3, I present one of the largest expression quantitative trait loci (eQTL) studies to date in the human brain, profiled from single-nuclei to identify cell-type specific patterns of genetic regulation. I show that a substantial proportion of eQTLs are cell-type specific, outperforming traditional bulk-tissue eQTL studies both in terms of total discovery and biological relevance. I further demonstrate in Chapter 4 that these eQTLs are dynamic, their association affected by both the presence of disease pathology as well as age. Brain phenome-wide genetic colocalisation Chapter 5 shows a high degree of cell-type specificity associated with trait pre-disposition and that even colocalisation patterns are dynamic as a result of disease pathology. Finally, using samples unbiased by disease presence I show in Chapter 6 the first results of Mendelian Randomisation (MR) for causal inference in the brain anchored in cell-type specific eQTLs, identifying putative novel drug targets and biomarkers for brain health and disease.