Dissecting genotype-phenotype associations in Down Syndrome using WGS and WES Data​

Down syndrome (DS), caused by trisomy 21, provides a valuable model to investigate how chromosomal dosage imbalance drives phenotypic variability and disease susceptibility. The overexpression of genes on chromosome 21 perturbs transcriptional and epigenetic regulation, contributing to a broad spectrum of comorbidities, including congenital heart defects, leukemia, immune dysregulation, and early-onset Alzheimer’s disease. Advances in genomic technologies, particularly Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS), now enable the identification of both coding and non-coding variants underlying these conditions. This PhD project aims to elucidate the genetic mechanisms contributing to both chromosome 21–linked and non–chromosome 21–linked comorbidities in DS. By integrating WES and WGS data, it identifies and interprets novel variants associated with the heterogeneous clinical presentation of DS. Through exploratory analyses, large-cohort association testing, and integrative interpretation, this work establishes a robust methodological framework for genotype–phenotype association studies in DS. The OPBG cohort served as a pilot to develop and validate this analytical workflow, focusing on common conditions such as hypothyroidism, myopia, and hypermetropia. Building on this foundation, the analysis of the larger BIG cohort (n>130) expanded the investigation to congenital heart defects, recurrent respiratory infections, and other major comorbidities, uncovering candidate genes with potential roles in DS pathogenesis. Overall, this thesis represents one of the first genome-wide efforts to investigate the genetic architecture of DS comorbidities beyond chromosome 21. By demonstrating the polygenic and multisystemic nature of these conditions, it provides both biological insights and a conceptual framework for future large-scale and multi-omic studies on genotype–phenotype relationships in DS.