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Schrauwen, I.

Publications and source records attributed to Schrauwen, I..

3 recordsLinked to original sources

Delineating the molecular and phenotypic spectrum of the SETD1B-related syndrome

Pathogenic variants in SETD1B have been associated with a syndromic neurodevelopmental disorder including intellectual disability, language delay and seizures. To date, clinical features have been described for eleven patients with (likely) pathogenic SETD1B sequence variants. We perform an in-depth clinical characterization of a cohort of 36 unpublished individuals with SETD1B sequence variants, describing their molecular and phenotypic spectrum. Selected variants were functionally tested using in vitro and genome-wide methylation assays. Our data present evidence for a loss-of-function mechanism of SETD1B variants, resulting in a core clinical phenotype of global developmental delay, language delay including regression, intellectual disability, autism and other behavioral issues, and variable epilepsy phenotypes. Developmental delay appeared to precede seizure onset, suggesting SETD1B dysfunction impacts physiological neurodevelopment even in the absence of epileptic activity. Interestingly, males are significantly overrepresented and more severely affected, and we speculate that sex-linked traits could affect susceptibility to penetrance and the clinical spectrum of SETD1B variants. Finally, despite the possibility of non-redundant contributions of SETD1B and its paralogue SETD1A to epigenetic control, the clinical phenotypes of the related disorders share many similarities, indicating that elucidating shared and divergent downstream targets of both genes will help to understand the mechanism leading to the neurobehavioral phenotypes. Insights from this extensive cohort will facilitate the counseling regarding the molecular and phenotypic landscape of newly diagnosed patients with the SETD1B-related syndrome.

genetics↗

Transcriptional profiling of Multiple System Atrophy cerebellar tissue highlights differences between the parkinsonian and cerebellar sub-types of the disease

Multiple system atrophy (MSA) is a rare adult-onset neurodegenerative disease of unknown cause, with no effective therapeutic options, and no cure. Limited work to date has attempted to characterize the transcriptional changes associated with the disease, which presents as either predominating parkinsonian (MSA-P) or cerebellar (MSC-C) symptoms. We report here the results of RNA expression profiling of cerebellar white matter (CWM) tissue from two independent cohorts of MSA patients (n=66) and healthy controls (HC; n=66). RNA samples from bulk brain tissue and from oligodendrocytes obtained by laser capture microdissection (LCM) were sequenced. Differentially expressed genes (DEGs) were obtained and were examined before and after stratifying by MSA clinical sub-type. We detected the highest number of DEGs in the MSA-C group (n = 747) while only one gene was noted in MSA-P, highlighting the larger dysregulation of the transcriptome in the MSA-C CWM. Results from both bulk tissue and LCM analysis of MSA-C showed a downregulation of oligodendrocyte genes and an enrichment for myelination processes with a key role noted for the QKI gene. Additionally, we observed a significant upregulation of neuron-specific gene expression in MSA-C and an enrichment for synaptic processes. A third cluster of genes was associated with the upregulation of astrocyte and endothelial genes, two cell types with a key role in inflammation processes. Finally, network analysis in MSA-C showed enrichment for {beta}-amyloid related functional classes, including the known Alzheimers disease (AD) genes, APP and PSEN1. This is the largest RNA profiling study ever conducted on post-mortem brain tissue from MSA patients. We were able to define specific gene expression signatures for MSA-C highlighting the different stages of the complex neurodegenerative cascade of the disease that included alterations in several cell-specific transcriptional programs. Finally, several results suggest a common transcriptional dysregulation between MSA and AD-related genes despite the clinical and neuropathological distinctions between the two diseases.

genomics↗

Complex genetic network underlying the convergent of Rett Syndrome like (RTT-L) phenotype in neurodevelopmental disorders

Mutations of the X-linked gene encoding methyl-CpG-binding protein 2 (MECP2) cause classical forms of Rett syndrome (RTT) in girls. Patients with features of classical Rett syndrome, but do not fulfill all the diagnostic criteria (e.g. absence of a MECP2 mutation), are defined as atypical Rett syndrome. Genes encoding for cyclin-dependent kinase-like 5 (CDKL5) and forkhead box G1 (FOXG1) are more commonly found in patients with atypical Rett syndrome. Nevertheless, a subset of patients who are recognized to have an overlapping phenotype with RTT but are lacking a mutation in a gene that causes typical or atypical RTT are described as having Rett syndrome like phenotype (RTT-L). Whole Exome Sequencing (WES) of 8 RTT-L patients from our cohort revealed mutations in the genes GABRG2, GRIN1, ATP1A2, KCNQ2, KCNB1, TCF4, SEMA6B, and GRIN2A, which are seemingly unrelated to Rett syndrome genes. We hypothesized that the phenotypic overlap in RTT and RTT-L is caused by mutations in genes that affect common cellular pathways critical for normal brain development and function. We annotated the list of genes identified causing RTT-L from peer-reviewed articles and performed a protein-protein interaction (PPI) network analysis. We also investigated their interaction with RTT (typical or atypical) genes such as MECP2, CDKL5, NTNG1, and FOXG1. We found that the RTT-L-causing genes were enriched in the biological pathways such as circadian entrainment, the CREB pathway, and RET signaling, and neuronal processes like ion transport, synaptic transmission, and transcription. We conclude that genes that significantly interact with the PPI network established by RTT genes cause RTT-L, explaining the considerable feature overlap between genes that are indicated for RTT-L and RTT.

genomics↗