Research Geert Vandeweyer

Abstract

Life-science is a data science; it relies on the generation, sharing and integrated analysis of vast quantities of digital data. ELIXIR is a European Research Infrastructure that brings together international resources in life-sciences to form a single infrastructure enabling scientists to find and share data, exchange expertise and access advanced tools and large scale computational facilities, across borders and disciplines. The Belgian ELIXIR Node offers a portfolio of services in data management and analysis to help researchers adopt best practices of Open Science and perform their research efficiently. We bring together expertise in Flanders in human health and plant sciences, focusing on federated learning, and enabling data integration and interpretation. A new priority area is the establishment of a sensitive data infrastructure in Belgium. We also provide training for researchers and developers. Our mission is to ensure that researchers in Flanders and Belgium can focus on their research question, rather than on technical details of data, interoperability, compute resources, etc. by providing tailored solutions based on an interoperable infrastructure across Europe.

Researcher(s)

• Promoter: Meysman Pieter
• Co-promoter: Vandeweyer Geert

Research team(s)

• ADReM Data Lab (ADReM)

Project type(s)

• Research Project

Abstract

Dynamic mutations, stretches of repetitive DNA sequences that inherit unstably in pedigrees, are an important cause of intellectual disability and autism. In this project, we argue that the number of a specific class of dynamic mutations, the CGG-repeats is grossly underestimated. We focus in on CGG-repeats, as these have already been implicated in multiple disorders and moreover because these induce epigenetic silencing of associated repeats. Using the latest algorithms we will catalogue all repeats in the genome and annotate which ones are potentially prone to expansion. In a large patient cohort, we will search for expansions of any of those repeat. The repeat expansions will be experimentally validated. Up till now, the epigenetic changes accompanying dynamic mutations have been presented as an all or nothing effect. In this application, we will challenge this dogma and will more accurately define epigentic changes associated with the full range of CGG-repeats at several loci in the human genome. In addition, we will define one novel repeat expansion disorder by creating a cellular model and subject this to transcriptomic and neuronal network analysis. In summary, our project will increase our insights in the role CGG-repeats play in the human genome and in neurodevelopmental disease.

Researcher(s)

• Promoter: Kooy Frank
• Co-promoter: Vandeweyer Geert

Research team(s)

• Medical Genetics (MEDGEN)

Project website

Project type(s)

• Research Project

Abstract

Lung cancer is a heterogeneous disease with high prevalence and mortality. Despite improvements in treatment, lung cancer takes over 1,000 lives each day in Europe alone. The benefit of targeted therapy is illustrated for ALK-driven non-small cell lung cancer (NSCLC), with a median survival of 7 years, compared to <20% overall 5 year survival for lung cancer in general. As targeted inhibitors do not actively kill tumor cells, aberrant cells remain dormant in the patient. To tackle inevitable resistance and disease progression, novel generation drugs are needed to target the resistance mechanism. However, for ROS1-fusions, a relatively recently described oncogene representing 1-2% of NSCLC, only a single targeted drug is currently approved. Hence, patients resort to chemotherapy, off-label use or clinical studies on disease progression. Due to the scarcity of ROS1+ NSCLC, clinical decisions are guided by sporadic case reports and in vitro experiments based on synthetic setups in non-human cell models. Here, we couple modern genome engineering and computational prediction on drug/target interactions with patient-driven efforts to generate relevant disease models. We will introduce 13 known and predicted resistance mutations into 6 patient-derived cell lines, followed by experimental and computational evaluation of available targeted drugs. Complementing experimental and computational data results in an objective model to guide clinical decision making in rare cancer types.

Researcher(s)

• Promoter: Van Camp Guy
• Co-promoter: Pauwels Patrick
• Co-promoter: Vandeweyer Geert

Research team(s)

Project type(s)

• Research Project

Abstract

Neurodevelopmental disorders (NDD) are disorders which affect learning ability. Since genetic defects in many genes are linked to NDD's, diagnosis and treatment are difficult. Moreover, for the majority of NDD patients, the genetic cause remains unknown. However, there is growing evidence that for different NDDs a common molecular pathway is affected. For example, there is an enrichment of genes involved in chromatin remodelling. Disorders caused by mutations in genes regulating chromatin remodelling are called chromatinopathies. In this project, we want to study five distinct chromatinopathies: Kabuki, Kleefstra, Gabriele-de Vries, Helsmoortel-Van der Aa and a syndromic type of autism caused by mutations in KMT2D, EHMT1, YY1, ADNP and CHD8 respectively. The rationale for studying these five disorders is that the corresponding genes are involved in shared biological processes and that they have overlapping clinical features. We thus hypothesize that mutations in these five genes give rise to unique as well as common downstream effects in gene transcription and translation.

Researcher(s)

• Promoter: Kooy Frank
• Co-promoter: Vandeweyer Geert
• Fellow: Van Rossem Kirsten

Research team(s)

• Medical Genetics (MEDGEN)

Project website

Project type(s)

• Research Project

Abstract

Neurodevelopmental disorders (NDDs) represent a large and heterogeneous group of rare disorders. Individual types of NDDs with a known genetic etiology are typically rare, owing to the very high number of individual genes that are causative for such conditions, but their aggregate societal impact is dramatic. Among the causative mutated genes, most are involved in two broad functional domains, synaptic processes and chromatin regulation ("epigenetic mechanisms"). In this proposal we selected five distinct NDDs: Kabuki, Kleefstra, Gabriele-de Vries, Helsmoortel-Van der Aa, and a syndromic type of Autism Spectrum Disorder (ASD) caused, respectively, by mutations in KMT2D, EHMT1, YY1, ADNP and CHD8. The uniquely informative edge of jointly studying these specific NDDs stems from the involvement of the causative genes in inter-related chromatin pathways, both directly and through their associated protein partners, and from the observation of major overlapping clinical features. We thus hypothesize that mutations in these five genes give rise to major transcriptional dysregulation in both common as well as unique gene regulatory networks, thereby generating shared and unique downstream effects in gene transcription and translation. Therefore, the IMPACT collaborative project aims to reveal common molecular and cellular signatures of chromatinopathy gene disruptions. Such converging mechanisms of disease offer an attractive target for the development of knowledge-based therapeutic interventions across individual NDDs that can potentially be useful for designing interventions suitable for multiple related rare neurodevelopmental disorders.

Researcher(s)

• Promoter: Kooy Frank
• Co-promoter: Vandeweyer Geert

Research team(s)

Project website

Project type(s)

• Research Project

Abstract

Genomic medicine is driving the field of precision medicine, but its extensive use of genomic information is highly disruptive to current medical procedures, IT infrastructure and towards the role of clinical geneticists. We explored the feasibility to share large scale genomic data while preserving privacy, in combination with extensive clinical interpretation resources. Here, we present the resulting platform, WiNGS, enabling broad implementation of genomic medicine. WiNGS is aimed at breaking down the complexity of analyzing genome sequencing data. It uses a federated data model to optimize ICT requirements of Whole Genome Sequencing (WGS) interpretation. Both genotype and phenotype data of individuals are kept locally, at the geographically distributed genomic centers, to ensure data protection. To facilitate setup, locale data stores are provided as a containerized module including the noSQL database and all required communication routines. Centralized access through the WiNGS online interface is managed through access control lists, allowing cross-center collaboration and meta-analysis. Whereas sensitive data is kept at local data stores, sample-independent information is managed centrally. We provide variant annotation as a centralized service, together with the phenotype and disease knowledge base used to classify variants. This further reduces infrastructural requirements of individual centers, whilst synchronizing information across centers.

Researcher(s)

• Promoter: Vandeweyer Geert

Research team(s)

Project type(s)

• Research Project

Abstract

While the introduction of next generation sequencing led to a breakthrough in the discovery of novel genes responsible for neurodevelopmental disorders, most notably intellectual disability and autism, our understanding of the underlying disease causing pathology is lagging behind, in part due to the extreme genetic heterogeneity. Despite substantial in silico evidence that many diseases genes responsible for neurodevelopmental disorders cluster in a relatively limited number of protein protein interaction (PPI) networks, no experimental work on the subtle phenotypical effects that disturbances of such a network may cause has been reported to our knowledge. In this application, we therefore zoom in for the first time on the effects of the combined genetic variation present in an entire PPI network, rather than on the effect of mutations in single genes. We selected the AnkyrinG interactome, as it is a well-defined interaction network that is strongly connected with multiple neurodevelopmental disorders. By a detailed characterization of the genetic variation present in the AnkyrinG interactome in a large patient cohort, in combination with transcriptomics, proteomics and validation studies, we want to define the role of this PPI network as a unifying factor in neurodevelopmental disorders.

Researcher(s)

• Promoter: Kooy Frank
• Co-promoter: Vandeweyer Geert

Research team(s)

Project website

Project type(s)

• Research Project

Abstract

Recent advances in the technology of sequencing have boosted the hunt for novel disease genes in various disorders beyond the throughput of classic functional follow-up. For neurodevelopmental disorders, and more specifically intellectual disability, sequencing both unaffected parents and the patient has been very successful in identifying de novo mutations as a major cause of disease. Using this approach, our group recently identified the ADNP gene as one of the more frequent causes of intellectual disability and autism. However, patients often harbour variants for which interpretation of the functional consequences is less straightforward. Functional investigation of such variants on relevant patient material is most often impossible as this would require brain biopsy. Recently, the technique of inducing pluripotent stem cells from skin biopsies and differentiating them into various cell types, has enabled the generation of patient-derived and disease-relevant in vitro cell cultures. Although this technique is very powerful, it requires large investments in both equipment and expertise to successfully set it up as part of a functional study, while scalability remains limited. Therefore, we propose a mid-throughput and cost-efficient approach for the functional validation of variant causality in disease-relevant tissues. Based on a wildtype culture of human Neural Stem Cells, specific variants can be introduced through Crispr/Cas9, followed by differentiation into neuronal cultures. The feasibility of the assay will be validated using the well defined AnkyrinG protein-protein interaction network for which aberrations have known and measurable outcomes.

Researcher(s)

• Promoter: Vandeweyer Geert

Research team(s)

Project type(s)

• Research Project

Abstract

Today, technologies exist that are able to screen complete human genomes for genetic defects, hereby producing massive amounts of data. These techniques include microarrays for the detection of duplicated or missing genomic material and next-generation sequencing for the detection of variation at the nucleotide level. In parallel, extensive public resources contain additional biological information on the observed variation to aid in interpretation of the data. While some variants show full penetrance, others can be present in both seemingly healthy and severely impaired family members, indicating that disease modifying variants play a role in the clinical presentation. This led to the formulation of a 'many genes, common pathways' paradigm. To study genetic variation under this paradigm, novel models placing interpretation of individual results in a context of multiple patients are mandatory. Searching for common patterns over large patient cohorts might identify recurrently affected pathways with a critical role in the studied disease. Simultaneously considering multiple variants affecting such a pathway will thus help to explain both the observed phenotype and combined with pedigree information, the intrafamilial variability. Here, we will investigate how we can apply state-of-the-art data mining methods to reveal hidden relationships between variants, with the goal of gaining new insights in the molecular pathology of heritable diseases, focusing on cognitive disorders.

Researcher(s)

• Promoter: Kooy Frank
• Co-promoter: Laukens Kris
• Fellow: Vandeweyer Geert

Research team(s)

Project website

Project type(s)

• Research Project

Abstract

Autism, perhaps best characterized by a lack of social skills, is a poorly understood disorder. We know little about the different types of the disorder. Though is clear that genetics plays an important role in the occurrence of the disorder, of very few forms of autism the cause is known. In this project, we will study a form of autism that is caused by mutations in a single gene called ADNP. Mutations in this gene lead to autism in almost all patients known to date. Using an established mouse model of Adnp-autism, which mimics the disorder allows us to study the disorder in vivo, and to test drugs for possible later use in humans. It is known that a specific part of the ADNP protein called NAP can replace many of the functions of the entire protein, thereby indicating that NAP can be a primary drug candidate for testing in the Adnp-autism mouse model. In addition, as we know little of the consequences of the mutation in human cells, we will produce neuron-specific cell types generated from patient-derived skin biopsies, using the technique of induced-pluripotent stem cells. Thus, we will be able to study the processes that are disturbed in patient brain cells. By applying a variety of state of the art technologies, our network will detect novel pathways in cells disturbed in ADNP, and in related forms of autism. Once we characterized those pathways, we can then try to modify them for clinical benefit, using novel drugs. Finally, since many unrelated patients share the very same ADNP mutation, we will determine the mechanism of how these mutations arise. Knowledge of the mutational mechanism may be another way of detecting or preventing the disease in the future.

Researcher(s)

• Promoter: Kooy Frank
• Co-promoter: Vandeweyer Geert

Research team(s)

Project type(s)

• Research Project

Abstract

Despite substantial in silico evidence that many diseases genes responsible for neurodevelopmental disorders cluster in a relatively limited number of protein protein interaction (PPI) networks, no experimental work on the subtle phenotypical effects that disturbances of such a network may cause has been reported to our knowledge. In this application, we therefore zoom in for the first time on the effects of the combined genetic variation present in an entire PPI network, rather than on the effect of mutations in single genes. We selected the AnkyrinG interactome, as it is a well-defined interaction network that is strongly connected with multiple neurodevelopmental disorders. By a detailed characterization of the genetic variation present in the AnkyrinG interactome in a large patient cohort, in combination with transcriptomics, proteomics and validation studies in animal models, we want to define the role of this PPI network as a unifying factor in neurodevelopmental disorders.

Researcher(s)

• Promoter: Kooy Frank
• Co-promoter: Vandeweyer Geert
• Fellow: Cappuyns Elisa

Research team(s)

Project website

Project type(s)

• Research Project

Abstract

Today, technologies exist to screen complete human genomes for genetic defects, hereby producing vast amounts of data. These techniques include microarrays for the detection of duplicated or missing genomic material and next-generation sequencing for the detection of variation at the nucleotide level. In parallel, extensive but distributed public resources contain biological information on the observed variation, to aid in interpretation of the data. To study genetic variation under a "many genes, common pathways" paradigm, or under oligogenic inheritance, interpretation of individual results in a context of multiple patients is mandatory. To overcome genetic heterogeneity, this context must be lifted from gene level to higher biological or functional levels. Searching for common patterns of affected pathways over large patient cohorts might thus identify recurrently affected pathways with a critical role in the disease. Simultaneously considering multiple variants affecting such a pathway will thus help to explain both the observed phenotype and combined with pedigree information, the intrafamilial variability. Here, we will generate a performant and scalable framework of patient, variant, and annotation information. This framework is mandatory for applying state-of-the-art data mining methods to reveal hidden relationships between the variants in relation to patient phenotype, with the goal of gaining new insights in the molecular pathology of heritable diseases.

Researcher(s)

• Promoter: Vandeweyer Geert

Research team(s)

Project type(s)

• Research Project

Abstract

Imprinting refers to mono-allellic expression of genes. It is involved in developmental disorders and in tumor development. As the extend of imprinting in human is currently unknown, we will use RNA-sequencing to generate a comprehensive atlas of imprinted genes and parental origins of the expressed alleles. This will be of great value in the interpretation of genome wide data, from techniques such as microarray and whole exome sequencing.

Researcher(s)

• Promoter: Vandeweyer Geert

Research team(s)

Project type(s)

• Research Project

Abstract

In this project, we will investigate how we can apply state-of-the-art data mining methods to reveal hidden relationships between variants, with the goal of gaining new insights in the molecular pathology of heritable diseases, focusing on cognitive and cardiac disorders.

Researcher(s)

• Promoter: Kooy Frank
• Co-promoter: Laukens Kris
• Co-promoter: Loeys Bart
• Co-promoter: Van den Bulcke Tim
• Fellow: Vandeweyer Geert

Research team(s)

Project type(s)

• Research Project