Project background
Diagnostic Whole Genome Sequencing (WGS) have revolutionized the care of patients, primarily analyzing the protein coding regions of all genes known to cause disease when mutated (~5000 known ?morbid genes?). Despite this success, more than 50% of the patients analyzed remain without a genetic diagnosis. A large part of the missing heritability in monogenic diseases is the estimated 30% of the pathogenic variants located within the 98% of the genome outside protein coding exons. Our project focuses on patients with severe neurological disorders with childhood onset in which a molecular diagnosis was not obtained after WGS-based diagnostics at AMG, OUS. A monogenic disease is highly likely in the recruited patients, since many of them have one or more of the following characteristics: progressive disease course, metabolic abnormalities, affected siblings and/or consanguineous parents. Many of the patients present with brain abnormalities found on clinical examination and/or detected on cerebral imaging (exemplified in Figure 1). Non-genetic causes, such as infection, trauma or hypoxia, have been excluded.
Fig. 1: Brain MRI showing corpus callosum anomaly (yellow arrow) and cerebellar atrophy (red arrow).
In our project, we expand the bioinformatics analyses to all known genes in the WGS-data, facilitating the identification of “novel disease genes”, i.e. detecting disease causing variants in one of the >15.000 genes not yet known to cause disease when mutated. We also perform transcriptome sequencing (RNA-seq) and combine analyses of RNA-seq and WGS-data to detect putative disease-causing variants in introns and extragenic sequences. We use patient fibroblasts to characterize how the variants detected affect cell physiology. We share potential novel disease genes through GeneMatcher.org to identify unrelated patients with overlapping phenotypes and mutations affecting the same gene. By performing RNA-seq we also elucidate knowledge about the underlying molecular mechanisms causing these severe diseases (exemplified in Figure 2).