Research Questions:
1. Do transcriptional risk scores (TRS), derived from single-cell expression quantitative trait loci (sc-eQTL) data, differ between individuals with neuroinflammatory and neurodegenerative disorders and non-neurological controls?
2. Do observed cell-type-specific TRS differences (e.g. in immune and glial cells) reflect pathway-specific processes in a disease-specific manner?
3. Are TRS associated with alterations in brain structure and connectivity, as measured by advanced imaging-derived phenotypes?
Objectives:
1. To compare TRS between individuals with neuroinflammatory conditions and neurodegenerative diseases, as well as controls without neurological disease.
2. Cross-Trait Analysis: Explore shared genetic architecture between TRS, and clinical diagnoses using cross-trait correlations and genetic overlap metrics, adjusting for potential confounders (BMI, smoking, alcohol consumption, educational attainment and socio-economic factors etc).
3. Biomarker Development: Assess the potential of combined TRS and brain imaging derived phenotypes (IDPs) to identify disease subtypes and support early diagnosis across neuroinflammatory and neurodegenerative conditions.
Scientific Rationale:
Neurodegenerative and neuroinflammatory diseases are driven by complex interactions between genetic risk, environmental risk factors (which are also potential confounders) and brain structure. While brain volumetric change is a well-established biomarker of disease progression, its integration with functional, cell-type-specific genetic risk remains limited. Single-cell transcriptomic studies have revealed distinct cellular pathways involved in disease. However, the relevance of these pathways at a whole-brain level, and their relationship with in-vivo structural imaging, remains poorly understood. The UK Biobank provides a unique opportunity to explore this interaction at scale using population-level imaging and genomic data.
