Most human traits and disorders, such as body weight and cardiovascular disease, are complex or polygenic, influenced by numerous genetic and environmental factors. Although Genome-Wide Association Studies (GWAS) have identified thousands of genetic variants associated with a variety of phenotypes, the functional mechanisms of these variants are still poorly understood, and extracting biological insights from these findings remains a challenge.
Our research aims to elucidate the genetic basis and biological mechanisms of complex traits and diseases by developing novel conceptual models and statistical methods to analyze genotype-phenotype data. We will use the UK Biobank resource to address four key areas:
1. Identification of Key Disease Genes: Most GWAS variants are non-coding with unknown target genes, and the relevance of many implicated genes remains unclear. We aim to develop methods to identify key disease-relevant genes, improving our understanding of biological processes and guiding therapeutic target discovery.
2. Mechanistic Pathways from Genotype to Phenotype: We seek to understand how genetic perturbations propagate through molecular and physiological pathways to affect organismal phenotypes and how phenotypic heterogeneity maps to genetic architecture.
3. Gene-Environment Interactions: We will explore how genetic effects are modulated by environmental factors and identify the genes and pathways involved in these interactions.
4. Improving Polygenic Risk Prediction: We aim to improve the accuracy, biological interpretability, and equitable use of polygenic risk scores for disease prediction.
To accomplish these objectives, we will conduct broad analyses across multiple traits and disorders to derive generalizable principles, as exemplified in our recent study (Mostafavi et al., 2023, Nat. Genet.), and focused analyses on specific phenotypes to uncover biological insights applicable to other traits (e.g., Mostafavi et al., 2020, eLife).