Helbig, Ingo

Diagnosing rare genetic diseases remains a major challenge despite widespread clinical testing. Long-read RNA sequencing (RNA-seq) offers a powerful approach to capturing the effects of genetic variants on the transcriptome, yet challenges with sequencing coverage, cost, tissue selection, and scalability have limited its clinical adoption. To address this, we developed STRIPE (Sequencing Targeted RNAs Identifies Pathogenic Events), a targeted long-read RNA-seq–based strategy for rare disease diagnosis and variant interpretation. STRIPE enables deep sequencing of full-length transcripts for any customized disease-specific gene panel such that a wide range of clinically informative readouts, including transcript aberrations and sequence variants, can be detected at haplotype-level resolution. Applying STRIPE to 88 individuals spanning two major rare disease groups, we accurately reidentified known pathogenic variants and revealed their transcript consequences, including many unexpected ones. For 8 of 15 splice site region variants, we observed more complex RNA processing defects beyond single exon skipping or cryptic splice site activation. Notably, we find that donor splice site variants frequently activate cryptic intronic polyadenylation sites, leading to premature transcript termination. Leveraging unique strengths of long-read RNA-seq, STRIPE also resolved variants of uncertain significance and uncovered disease-causing variants in five previously undiagnosed individuals. Overall, STRIPE is a powerful, adaptable, and scalable strategy with broad potential to improve clinical variant interpretation and advance genetic diagnosis of rare diseases.

Abstract Rare Mendelian disorders affect 300-400 million people globally. Although genetic testing has become widely adopted, gene-specific evidence for tailored variant interpretation remains scattered across resources. We present Gene Portals, a framework for gene-centered multimodal knowledge bases that co-localize expert-harmonized clinical data, functional assays, population variation, structural annotations and gene-specific ACMG/AMP specifications within a single resource. A modular interface integrates this unified evidence with VCEP-refined ACMG specifications to enable automated gene-specific variant classification, infer molecular mechanisms, and support cross-gene analyses. We demonstrate the framework’s utility across five Gene portals spanning eleven neurodevelopmental disorder-associated genes, integrating data from 4,423 individuals with 2,838 unique variants, 36,149 ClinVar submissions, and 1,044 expert-curated molecular readouts. By organizing evidence that is otherwise dispersed across multiple sources into a unified, queryable framework, the SCN, GRIN, CACNA1A, SATB2 and SLC6A1 Gene Portals became widely used community resources and provide an extensible template for standardized rare-disease variant interpretation and mechanism-aware discovery.

Abstract Background The majority of missense variants in clinical genetic tests are classified as variants of uncertain significance. Prior research has shown that the deleterious effects and the subsequent molecular consequence of variants are often conserved among paralogous protein sequences within a gene family. Here, we systematically quantified on an exome-wide scale if the existence of pathogenic variants in paralogous genes at a conserved position could serve as evidence for the pathogenicity of a new variant. For the gene family of voltage-gated sodium channels where variants and expert-curated clinical phenotypes were available, we also assessed whether phenotype patterns of multiple disorders for each gene were also conserved across variant positions within the gene family. Methods We developed a framework that assesses the presence of pathogenic missense variants located in conserved residues across paralogous genes. We systematically mapped 2.5 million pathogenic and general population variants from the ClinVar, HGMD, and gnomAD databases onto a total of 9,990 genes and aligned them by gene families. We evaluated the quantity of classifiable amino acids by utilizing pathogenic variants identified in databases alone and then compared this assessment to the inclusion of paralogous pathogenic variants. We validated and quantified the evidence of conserved pathogenic paralogous variants in variant pathogenicity classification. Results Considering conserved pathogenic variants in paralogous genes, increased the number of classifiable variants 2.8-fold across the exome, compared to pathogenic variants in the gene of interest alone. The presence of a pathogenic variant in a paralogous gene is associated with a positive likelihood ratio of 8.32 for variant pathogenicity. The likelihood ratio was gene family-specific. Across ten genes encoding voltage-gated sodium channels and 22 expert-curated disorders, we identified cross-paralog correlated phenotypes based on 3D structure spatial position. For example, the established loss-of-function disorders SCN1A-associated Dravet syndrome, SCN2A-associated autism, SCN5A-associated Brugarda Syndrome, and SCN8A-associated neurodevelopmental disorder without seizures were correlated in their spatial variant position on structure. Finally, we show that phenotype integration in paralog variant selection improves variant classification. Conclusion Our results show that paralogous variants, in particular with phenotype information can enhance our understanding of variant effects.

Abstract The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

AbstractNew onset refractory status epilepticus (NORSE), including its subtype with a preceding febrile illness known as febrile infection‐related epilepsy syndrome (FIRES), is one of the most severe forms of status epilepticus. The exact causes of NORSE are currently unknown, and there is so far no disease‐specific therapy. Identifying the underlying pathophysiology and discovering specific biomarkers, whether immunologic, infectious, genetic, or other, may help physicians in the management of patients with NORSE. A broad spectrum of biomarkers has been proposed for status epilepticus patients, some of which were evaluated for patients with NORSE. Nonetheless, none has been validated, due to significant variabilities in study cohorts, collected biospecimens, applied analytical methods, and defined outcome endpoints, and to small sample sizes. The NORSE Institute established an open NORSE/FIRES biorepository for health‐related data and biological samples allowing the collection of biospecimens worldwide, promoting multicenter research and sharing of data and specimens. Here, we suggest standard operating procedures for biospecimen collection and biobanking in this rare condition. We also propose criteria for the appropriate use of previously collected biospecimens. We predict that the widespread use of standardized procedures will reduce heterogeneity, facilitate the future identification of validated biomarkers for NORSE, and provide a better understanding of the pathophysiology and best clinical management for these patients.

ABSTRACT Background Multiple System Atrophy is a rare neurodegenerative disease with alpha‐synuclein aggregation in glial cytoplasmic inclusions and either predominant olivopontocerebellar atrophy or striatonigral degeneration, leading to dysautonomia, parkinsonism, and cerebellar ataxia. One prior genome‐wide association study in mainly clinically diagnosed patients with Multiple System Atrophy failed to identify genetic variants predisposing for the disease. Objective Since the clinical diagnosis of Multiple System Atrophy yields a high rate of misdiagnosis when compared to the neuropathological gold standard, we studied only autopsy‐confirmed cases. Methods We studied common genetic variations in Multiple System Atrophy cases (N = 731) and controls (N = 2898). Results The most strongly disease‐associated markers were rs16859966 on chromosome 3, rs7013955 on chromosome 8, and rs116607983 on chromosome 4 with P ‐values below 5 × 10 −6 , all of which were supported by at least one additional genotyped and several imputed single nucleotide polymorphisms. The genes closest to the chromosome 3 locus are ZIC1 and ZIC4 encoding the zinc finger proteins of cerebellum 1 and 4 (ZIC1 and ZIC4). Interpretation Since mutations of ZIC1 and ZIC4 and paraneoplastic autoantibodies directed against ZIC4 are associated with severe cerebellar dysfunction, we conducted immunohistochemical analyses in brain tissue of the frontal cortex and the cerebellum from 24 Multiple System Atrophy patients. Strong immunohistochemical expression of ZIC4 was detected in a subset of neurons of the dentate nucleus in all healthy controls and in patients with striatonigral degeneration, whereas ZIC4‐immunoreactive neurons were significantly reduced inpatients with olivopontocerebellar atrophy. These findings point to a potential ZIC4‐mediated vulnerability of neurons in Multiple System Atrophy. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society