Genome-wide association studies (GWAS) have successfully pinpointed numerous genetic loci and variants associated with complex traits and common diseases across the genome. However, an overwhelming proportion of these loci and variants reside in non-coding regions, complicating the identification of truly causal variants and elu- cidation of the underlying biological pathways. One approach to address this obstacle is the utilisation of advanced statistical methods as well as the expanding genetic and genomic resources, to prioritise functional variants and understand the molecu- lar mechanism behind their association with traits or diseases. Understanding the multifaceted complexity of genetic associations holds potential for uncovering novel therapeutic targets. Focusing on corneal resistance factor (CRF), a quantitative trait indicative of the cornea’s ability to withstand applied force, this project aims to deploy state-of-the art methods and datasets to seek deeper insights into the biological pathways influencing CRF and its associated diseases. First, to prioritise genes for CRF, I leveraged the genetic variants affecting splicing or expression levels of genes in cis from the Genotype-Tissue Expression project and highlighted CRF GWAS variants also implicated in changes in gene expression (eQTL), in non-eye tissues, by fine-mapping and colocalisation methods. A total of 73 genes for 48 (26.5%) CRF independent GWAS signals thus identified showed significant enrichment of transcripts level in specific cell types within the cornea and limbus, in line with a major role of these genes in collagen and extracellular matrix homeostasis. Second, to better understand the pathway dependent on the rare genetic disorder gene ZNF469, a presumed transcription factor and strong candidate target gene in the CRF GWAS but not nominated by the eQTL colocalisation, I analysed regulatory networks and genes transcriptionally affected in the cornea of mice lacking functional ZNF469, using a single cell RNA-seq data from adult mice. A few candidate target genes at CRF GWAS loci could be linked to ZNF469. Third, to associate CRF variants to pathways implicated in various phenotypes and diseases, I examined the pleiotropic effects of CRF variants by exhaustively searching phenotypes and GWAS data from two databases, GWAS Catalog and UK Biobank. As a result, supported by colocalisation of signals, over 400 GWAS exhibited at least one common functional locus with CRF GWAS. I also identified novel associations in those traits by phenome-wide association studies (PheWAS), by restricting the search space to those traits and conducting a replication study using FinnGen data. In summary, by employing statistical approaches and integrating various datasets, this project explored the functional pathways CRF GWAS variants involved in from three perspectives, yielding insights into the core genes and mechanism underlying CRF and associated phenotypes.