Dominant-negative mutations in human IL6ST underlie hyper-IgE syndrome

Autosomal dominant hyper-IgE syndrome (AD-HIES) is typically caused by dominant-negative (DN) STAT3 mutations. Patients suffer from cold staphylococcal lesions and mucocutaneous candidiasis, severe allergy, and skeletal abnormalities. We report 12 patients from 8 unrelated kindreds with AD-HIES due to DN IL6ST mutations. We identified seven different truncating mutations, one of which was recurrent. The mutant alleles encode GP130 receptors bearing the transmembrane domain but lacking both the recycling motif and all four STAT3-recruiting tyrosine residues. Upon overexpression, the mutant proteins accumulate at the cell surface and are loss of function and DN for cellular responses to IL-6, IL-11, LIF, and OSM. Moreover, the patients’ heterozygous leukocytes and fibroblasts respond poorly to IL-6 and IL-11. Consistently, patients with STAT3 and IL6ST mutations display infectious and allergic manifestations of IL-6R deficiency, and some of the skeletal abnormalities of IL-11R deficiency. DN STAT3 and IL6ST mutations thus appear to underlie clinical phenocopies through impairment of the IL-6 and IL-11 response pathways

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.Peer Reviewe

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Funder: Bundesministerium für Bildung und ForschungFunder: Bundesministerium für Bildung und Forschung (BMBF)We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

IntroductionThe COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. MethodsExtensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.ResultsResults revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. DiscussionThe key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies

Land rights as an engine of growth ? An analysis of Cambodian land grabs in the context of development theory

Forceful evictions have become a serious problem in Cambodia with an increasing number of fami-lies being deprived of their land, homes and livelihoods without compensation. This article analysesCambodian land rights in the context of economic development theory. It assesses whether increas-ing economic inequalities, stemming from forceful evictions, can be categorized as an impediment toCambodian economic growth. The Cambodian case illustrates that a lack of good governance due tocorruption leads to the unequal distribution of land which, in turn, causes inequitable economic devel-opment. The paper concludes that Cambodia is trapped in a vicious cycle of inequality, which is upheld byelites who benefit from evictions and land concessions while evictees become trapped in poverty. Giventhat the population is growing angrier, the article warns of potential for a violent revolution that couldhave disastrous consequences for the Cambodian kingdom, a country that recently emerged from yearsof civil conflicts and is still in the process of rebuilding its social fabric

Assessment of genetic variant burden in epilepsy-associated brain lesions

It is challenging to estimate genetic variant burden across different subtypes of epilepsy. Herein, we used a comparative approach to assess the diagnostic yield and genotype-phenotype correlations in the four most common brain lesions in patients with drug-resistant focal epilepsy. Targeted sequencing analysis was performed for a panel of 161 genes with a mean coverage of > 400x. Lesional tissue was histopathologically reviewed and dissected from hippocampal sclerosis (n=15), ganglioglioma (n=16), dysembryoplastic neuroepithelial tumors (n=8) and ocal cortical dysplasia type II (n=15). Peripheral blood (n=12) or surgical tissue samples histopathologically classified as lesion-free (n=42) were available for comparison. Variants were classified as pathogenic or likely pathogenic according to American College of Medical Genetics and Genomics guidelines. Overall, we identified pathogenic and likely pathogenic variants in 25.9% of patients with a mean coverage of 383x. The highest number of pathogenic/ likely pathogenic variants was observed in patients with ganglioglioma (43.75%; all somatic) and dysembryoplastic neuroepithelial tumors (37.5%; all somatic), and in 20% of cases with focal cortical dysplasia type II (13.33% somatic, 6.67% germline). Pathogenic/likely pathogenic positive genes were disorder-specific and BRAF V600E the only recurrent pathogenic variant. This study represents a reference for diagnostic yield across the four most common lesion entities in patients with drug-resistant focal epilepsy. The observed large variability in variant burden by epileptic lesion type calls for whole exome sequencing of histopathologically well characterized tissue in a diagnostic setting and in research to discover novel disease-associated genes

Assessment of genetic variant burden in epilepsy-associated brain lesions

It is challenging to estimate genetic variant burden across different subtypes of epilepsy. Herein, we used a comparative approach to assess the genetic variant burden and genotype-phenotype correlations in four most common brain lesions in patients with drug-resistant focal epilepsy. Targeted sequencing analysis was performed for a panel of 161 genes with a mean coverage of >400x. Lesional tissue was histopathologically reviewed and dissected from hippocampal sclerosis (n = 15), ganglioglioma (n = 16), dysembryoplastic neuroepithelial tumors (n = 8), and focal cortical dysplasia type II (n = 15). Peripheral blood (n = 12) or surgical tissue samples histopathologically classified as lesion-free (n = 42) were available for comparison. Variants were classified as pathogenic or likely pathogenic according to American College of Medical Genetics and Genomics guidelines. Overall, we identified pathogenic and likely pathogenic variants in 25.9% of patients with a mean coverage of 383x. The highest number of pathogenic/likely pathogenic variants was observed in patients with ganglioglioma (43.75%; all somatic) and dysembryoplastic neuroepithelial tumors (37.5%; all somatic), and in 20% of cases with focal cortical dysplasia type II (13.33% somatic, 6.67% germline). Pathogenic/likely pathogenic positive genes were disorder specific and BRAF V600E the only recurrent pathogenic variant. This study represents a reference for the genetic variant burden across the four most common lesion entities in patients with drug-resistant focal epilepsy. The observed large variability in variant burden by epileptic lesion type calls for whole exome sequencing of histopathologically well-characterized tissue in a diagnostic setting and in research to discover novel disease-associated genes

Dominant-negative mutations in human IL6ST underlie hyper-IgE syndrome.

Autosomal dominant hyper-IgE syndrome (AD-HIES) is typically caused by dominant-negative (DN) STAT3 mutations. Patients suffer from cold staphylococcal lesions and mucocutaneous candidiasis, severe allergy, and skeletal abnormalities. We report 12 patients from 8 unrelated kindreds with AD-HIES due to DN IL6ST mutations. We identified seven different truncating mutations, one of which was recurrent. The mutant alleles encode GP130 receptors bearing the transmembrane domain but lacking both the recycling motif and all four STAT3-recruiting tyrosine residues. Upon overexpression, the mutant proteins accumulate at the cell surface and are loss of function and DN for cellular responses to IL-6, IL-11, LIF, and OSM. Moreover, the patients' heterozygous leukocytes and fibroblasts respond poorly to IL-6 and IL-11. Consistently, patients with STAT3 and IL6ST mutations display infectious and allergic manifestations of IL-6R deficiency, and some of the skeletal abnormalities of IL-11R deficiency. DN STAT3 and IL6ST mutations thus appear to underlie clinical phenocopies through impairment of the IL-6 and IL-11 response pathways