Developmental disorders (DD) are severe and chronic disabilities that often leads to early childhood death, or long-term morbidity in the survivors. Due to the high burden of infectious disease in many African countries, active research into rare diseases such as DD has often been neglected. The genetic aetiology of DD is complex as DD syndromes are marked by both clinical- and genetic heterogeneity. The Deciphering Developmental Disorders in Africa study (DDD-Africa) was initiated to address this knowledge gap, and the resource that was built holds the potential for much discovery, especially by catalyzing new collaborations and through the application of data science approaches. We therefore propose to use the clinical information, genetic data, and DNA resources from the DDD-Africa study to investigate the following hypotheses: 1. An exome-based CNV calling workflow that incorporates different tools, will identify putative disease- causing structural variants, and increase the diagnostic yield for DD-ID patients. 2. Identifying genome-wide DNA methylations patterns will assist in diagnosing genetically unsolved African DD-ID patients. 3. Phenotype-aware, artificial intelligence software can improve genotype-phenotype correlation in African DD-ID patients. Through this study, we will increase the diagnostic yield of DD-ID in African patients and broaden the knowledge discovery potential for rare diseases in Africa. This work will furthermore increase health data science capacity in Africa and create an ecosystem that can provide local solutions for rare diseases such as DD in Africa.

Developmental disorders (DD) represent a spectrum of often severe disabilities that are present from birth or early childhood. The Deciphering Developmental Disorders in Africa study (DDD-Africa) was started to describe and define the causes of DD in Africa, and this resource holds the potential for much more discovery, using data science- and omics techniques. To advance our knowledge, we propose to use the clinical information, genetic data, and DNA resources from the DDD-Africa study to increase diagnostic yield and make new discoveries about the causes of DD in African patients. These findings will lead to population-relevant and scalable solutions for Africa, fast-tracking genomics efforts for global health.