Identifizierung neuer Krankheitsgene als Ursache für Skelettfehlbildungen und syndromale geistige Behinderung

Die Stellung einer Diagnose, welche häufig nur durch Identifizierung der ursächlichen genetischen Veränderung möglich ist, hat für die genetische Beratung und klinische Betreuung von Patienten mit genetisch bedingten Erkrankungen einen hohen Stellenwert. Die molekulare Grundlage etwa der Hälfte aller bekannten monogenen Erkrankungen ist bisher unbekannt Seit Verfügbarkeit der Hochdurchsatzsequenzierung konnten die Diagnoserate und Anzahl an bekannten Krankheitsgenen deutlich erhöht werden. Im Rahmen dieser Arbeit wurden mittels Hochdurchsatzsequenzierung, vorwiegend Exomsequenzierung, Blutproben von Patienten mit Skelettfehlbildungssyndromen und syndromaler geistiger Behinderung untersucht. Über internationale Kooperationen konnten Kohorten von Patienten mit neuen Krankheitsgenen bzw. neuen Krankheitsentitäten gebildet werden. Der pathogene Effekt mehrerer der identifizierten Genveränderungen wurde in funktionellen In-vitro-Studien untersucht. Im Rahmen dieser Arbeit wurden die genetischen Ursachen für Catel-Manzke- und Fontaine-Progeroid-Syndrom untersucht. Als Ursache für Catel-Manzke-Syndrom haben wir biallelische pathogene Varianten in den Genen TGDS und KYNU identifiziert. Das TGDS-Protein spielt möglicherweise eine Rolle im Proteoglykanstoffwechsel. Das Enzym Kynureninase, das durch KYNU kodiert wird, katalysiert einen Schritt in der NAD+-Synthese. Trotz der Ähnlichkeit des resultierenden Phänotyps ist ein Zusammenhang zwischen dem TGDS- und KYNU-assoziierten Pathomechanismus bislang unklar. Als Ursache für Fontaine-Progeroid-Syndrom haben wir rekurrente De-novo-Varianten in SLC25A24, welches für einen mitochondrialen ATP-Mg/Pi-Transporter kodiert, identifiziert. In vitro wiesen wir eine mitochondriale Schwellung und Dysfunktion nach, welche bisher nicht als Ursache für Kraniosynostose-Syndrome beschrieben wurden und ihre pathogene Wirkung durch einen Einfluss der zellulären Differenzierung in den Schädelnähten entfalten könnten. Darüber hinaus wurden heterozygote pathogene Varianten in den Genen DLL1 und ACTB als Ursache für neue Formen der syndromalen geistigen Behinderung identifiziert. DLL1 kodiert für den Notch-Liganden Delta 1. Wenngleich zahlreiche Studien die Rolle des Notch-Signalweges in der Gehirnentwicklung untermauern, stellt diese Arbeit erstmals den Zusammenhang zu einem humanen primär entwicklungsneurologischen Phänotyp her. Mit der ACTB-assoziierten syndromalen Thrombozytopenie wird ein neuer Phänotyp beschrieben, der auf pathogenen Varianten in beta-Aktin beruht. Die Ergebnisse dieser Arbeit erweitern unser Verständnis der molekularen Ursachen unterschiedlicher genetisch bedingter Krankheitsbilder und geben neue Einblicke in verschiedene Mechanismen der Entwicklung des Skeletts und ZNS. Die gewonnenen Erkenntnisse können für die genetische Beratung und klinische Betreuung der betroffenen Familien genutzt werde und könnten die Grundlage für neue Therapieansätze darstellen.Finding a diagnosis is of great importance for genetic counseling and clinical care of patients with genetic diseases. Often, this is only possible through identifying the causative genetic alteration. But the molecular basis of around half of all known monogenic diseases is still unknown. When high-throughput sequencing becomes available, the diagnosis rate and the number of known disease genes increased significantly. Here, high-throughput sequencing, mainly exome sequencing, was used to study blood samples from patients with skeletal malformation syndromes and syndromic intellectual disability. Cohorts of patients with novel disease genes or novel disease entities were established through international collaborations. The pathogenic effect of several identified causative variants is further clarified in functional in vitro studies. In this work, the genetic causes of Catel-Manzke and Fontaine progeroid syndrome are investigated. We identified biallelic pathogenic variants in TGDS and KYNU as the cause of Catel-Manzke syndrome. The TGDS protein may play a role in proteoglycan metabolism. The enzyme kynureninase, encoded by KYNU, catalyzes a step in NAD+ synthesis. Despite the similarity of the resulting phenotype, a link between the TGDS- and KYNU-associated pathomechanisms remains unclear. We identified recurrent de-novo variants in SLC25A24 as the cause of Fontaine progeroid syndrome. SLC25A24 encodes a mitochondrial ATP-Mg/Pi transporter. In vitro, we detected mitochondrial swelling and dysfunction, which have not previously been described as a cause of craniosynostosis syndromes and may express their pathogenic effect through an influence of cellular differentiation in the cranial sutures. In addition, we identified heterozygous pathogenic variants in DLL1 and ACTB as the cause of novel forms of syndromic intellectual disability. DLL1 encodes the Notch ligand delta 1. Although numerous studies support a role for Notch signaling in brain development, this work is the first which links it to a human primary developmental neurological phenotype. ACTB-associated syndromic thrombocytopenia is a new phenotype described based on pathogenic variants in beta-actin. The results of this work expand our understanding of the molecular causes of different genetic phenotypes and provide new insights into different mechanisms of skeletal and central nervous system development. The findings can be used for genetic counseling and clinical management of affected families and can provide the basis for new therapeutic approaches

MutationDistiller: user-driven identification of pathogenic DNA variants

MutationDistiller is a freely available online tool for user-driven analyses of Whole Exome Sequencing data. It offers a user-friendly interface aimed at clinicians and researchers, who are not necessarily bioinformaticians. MutationDistiller combines Mutation- Taster’s pathogenicity predictions with a phenotypebased approach. Phenotypic information is not limited to symptoms included in the Human Phenotype Ontology (HPO), but may also comprise clinical diagnoses and the suspected mode of inheritance. The search can be restricted to lists of candidate genes (e.g. virtual gene panels) and by tissue-specific gene expression. The inclusion of GeneOntology (GO) and metabolic pathways facilitates the discovery of hitherto unknown disease genes. In a novel approach, we trained MutationDistiller’s HPO-based prioritization on authentic genotype–phenotype sets obtained from ClinVar and found it to match or outcompete current prioritization tools in terms of accuracy. In the output, the program provides a list of potential disease mutations ordered by the likelihood of the affected genes to cause the phenotype. MutationDistiller provides links to gene-related information from various resources. It has been extensively tested by clinicians and their suggestions have been valued in many iterative cycles of revisions. The tool, a comprehensive documentation and examples are freely available at https://www.mutationdistiller.org

VarFish: comprehensive DNA variant analysis for diagnostics and research

VarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of DNA variant data with a focus on rare disease genetics. It is capable of processing variant call files with single or multiple samples. The variants are automatically annotated with population frequencies, molecular impact, and presence in databases such as ClinVar. Further, it provides support for pathogenicity scores including CADD, MutationTaster, and phenotypic similarity scores. Users can filter variants based on these annotations and presumed inheritance pattern and sort the results by these scores. Variants passing the filter are listed with their annotations and many useful link-outs to genome browsers, other gene/variant data portals, and external tools for variant assessment. VarFish allows users to create their own annotations including support for variant assessment following ACMG-AMP guidelines. In close collaboration with medical practitioners, VarFish was designed for variant analysis and prioritization in diagnostic and research settings as described in the software's extensive manual. The user interface has been optimized for supporting these protocols. Users can install VarFish on their own in-house servers where it provides additional lab notebook features for collaborative analysis and allows re-analysis of cases, e.g. after update of genotype or phenotype databases

TGDS pathogenic variants cause Catel-Manzke syndrome without hyperphalangy

Catel-Manzke syndrome, also known as micrognathia-digital-syndrome, is a rare autosomal recessive disorder characterized by the combination of the two cardinal features Pierre-Robin sequence and bilateral hyperphalangy leading to ulnar clinodactyly (ulnar curvature of the phalanges) and radial deviation (radial angulation at the metacarpophalangeal joint) of the index finge

Broadening the phenotypic and molecular spectrum of FINCA syndrome: Biallelic NHLRC2 variants in 15 novel individuals

FINCA syndrome [MIM: 618278] is an autosomal recessive multisystem disorder characterized by fibrosis, neurodegeneration and cerebral angiomatosis. To date, 13 patients from nine families with biallelic NHLRC2 variants have been published. In all of them, the recurrent missense variant p.(Asp148Tyr) was detected on at least one allele. Common manifestations included lung or muscle fibrosis, respiratory distress, developmental delay, neuromuscular symptoms and seizures often followed by early death due to rapid disease progression.Here, we present 15 individuals from 12 families with an overlapping phenotype associated with nine novel NHLRC2 variants identified by exome analysis. All patients described here presented with moderate to severe global developmental delay and variable disease progression. Seizures, truncal hypotonia and movement disorders were frequently observed. Notably, we also present the first eight cases in which the recurrent p.(Asp148Tyr) variant was not detected in either homozygous or compound heterozygous state.We cloned and expressed all novel and most previously published non-truncating variants in HEK293-cells. From the results of these functional studies, we propose a potential genotype-phenotype correlation, with a greater reduction in protein expression being associated with a more severe phenotype.Taken together, our findings broaden the known phenotypic and molecular spectrum and emphasize that NHLRC2-related disease should be considered in patients presenting with intellectual disability, movement disorders, neuroregression and epilepsy with or without pulmonary involvement

CDK19-related disorder results from both loss-of-function and gain-of-function de novo missense variants

Purpose To expand the recent description of a new neurodevelopmental syndrome related to alterations in CDK19. Methods Individuals were identified through international collaboration. Functional studies included autophosphorylation assays for CDK19 Gly28Arg and Tyr32His variants and in vivo zebrafish assays of the CDK19(G28R) and CDK19(Y32H). Results We describe 11 unrelated individuals (age range: 9 months to 14 years) with de novo missense variants mapped to the kinase domain of CDK19, including two recurrent changes at residues Tyr32 and Gly28. In vitro autophosphorylation and substrate phosphorylation assays revealed that kinase activity of protein was lower for p.Gly28Arg and higher for p.Tyr32His substitutions compared with that of the wild-type protein. Injection of CDK19 messenger RNA (mRNA) with either the Tyr32His or the Gly28Arg variants using in vivo zebrafish model significantly increased fraction of embryos with morphological abnormalities. Overall, the phenotype of the now 14 individuals with CDK19-related disorder includes universal developmental delay and facial dysmorphism, hypotonia (79%), seizures (64%), ophthalmologic anomalies (64%), and autism/autistic traits (56%). Conclusion CDK19 de novo missense variants are responsible for a novel neurodevelopmental disorder. Both kinase assay and zebrafish experiments showed that the pathogenetic mechanism may be more diverse than previously thought.Peer reviewe

PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

GestaltMatcher Database - A global reference for facial phenotypic variability in rare human diseases

The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images - more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.</p