Utilizing ClinGen gene-disease validity and dosage sensitivity curations to inform variant classification.

Understanding whether there is enough evidence to implicate a gene's role in a given disease, as well as the mechanisms by which variants in this gene might cause this disease, is essential to determine clinical relevance. The National Institutes of Health-funded Clinical Genome Resource (ClinGen) has developed evaluation frameworks to assess both the strength of evidence supporting a relationship between a gene and disease (gene-disease validity), and whether loss (haploinsufficiency) or gain (triplosensitivity) of individual genes or genomic regions is a mechanism for disease (dosage sensitivity). ClinGen actively applies these frameworks across multiple disease domains, and makes this information publicly available via its website (https://www.clinicalgenome.org/) for use in multiple applications, including clinical variant classification. Here, we describe how the results of these curation processes can be utilized to inform the appropriate application of pathogenicity criteria for both sequence and copy number variants, as well as to guide test development and inform genomic filtering pipelines.

Diagnostic testing laboratories are valuable partners for disease gene discovery: 5-year experience with GeneMatcher.

Although the rates of disease gene discovery have steadily increased with the expanding use of genome and exome sequencing by clinical and research laboratories, only ~16% of genes in the genome have confirmed disease associations. Here we describe our clinical laboratory's experience utilizing GeneMatcher, an online portal designed to promote disease gene discovery and data sharing. Since 2016, we submitted 246 candidates from 243 unique genes to GeneMatcher, of which 111 (45%) are now clinically characterized. Submissions meeting our candidate gene-reporting criteria based on a scoring system using patient and molecular-weighted evidence were significantly more likely to be characterized as of October 2021 versus genes that did not meet our clinical-reporting criteria (p = 0.025). We reported relevant findings related to these newly characterized gene-disease associations in 477 probands. In 218 (46%) instances, we issued reclassifications after an initial negative or candidate gene (uncertain) report. We coauthored 104 publications delineating gene-disease relationships, including descriptions of new associations (60%), additional supportive evidence (13%), subsequent descriptive cohorts (23%), and phenotypic expansions (4%). Clinical laboratories are pivotal for disease gene discovery efforts and can screen phenotypes based on genotype matches, contact clinicians of relevant cases, and issue proactive reclassification reports.

Clinical validity assessment of genes frequently tested on intellectual disability/autism sequencing panels.

PURPOSE: Neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and autism spectrum disorder (ASD), exhibit genetic and phenotypic heterogeneity, making them difficult to differentiate without a molecular diagnosis. The Clinical Genome Resource Intellectual Disability/Autism Gene Curation Expert Panel (GCEP) uses systematic curation to distinguish ID/ASD genes that are appropriate for clinical testing (ie, with substantial evidence supporting their relationship to disease) from those that are not. METHODS: Using the Clinical Genome Resource gene-disease validity curation framework, the ID/Autism GCEP classified genes frequently included on clinical ID/ASD testing panels as Definitive, Strong, Moderate, Limited, Disputed, Refuted, or No Known Disease Relationship. RESULTS: As of September 2021, 156 gene-disease pairs have been evaluated. Although most (75%) were determined to have definitive roles in NDDs, 22 (14%) genes evaluated had either Limited or Disputed evidence. Such genes are currently not recommended for use in clinical testing owing to the limited ability to assess the effect of identified variants. CONCLUSION: Our understanding of gene-disease relationships evolves over time; new relationships are discovered and previously-held conclusions may be questioned. Without periodic re-examination, inaccurate gene-disease claims may be perpetuated. The ID/Autism GCEP will continue to evaluate these claims to improve diagnosis and clinical care for NDDs.

Expert Panel Curation of 31 Genes in Relation to Limb Girdle Muscular Dystrophy.

Introduction: Limb girdle muscular dystrophies (LGMDs) are a group of genetically heterogeneous autosomal conditions with some degree of phenotypic homogeneity. LGMD is defined as having onset >2 years of age with progressive proximal weakness, elevated serum creatine kinase levels and dystrophic features on muscle biopsy. Advances in massively parallel sequencing have led to a surge in genes linked to LGMD. Methods: The ClinGen Muscular Dystrophies and Myopathies gene curation expert panel (MDM GCEP, formerly Limb Girdle Muscular Dystrophy GCEP) convened to evaluate the strength of evidence supporting gene-disease relationships (GDR) using the ClinGen gene-disease clinical validity framework to evaluate 31 genes implicated in LGMD. Results: The GDR was exclusively LGMD for 17 genes, whereas an additional 14 genes were related to a broader phenotype encompassing congenital weakness. Four genes (CAPN3, COL6A1, COL6A2, COL6A3) were split into two separate disease entities, based on each displaying both dominant and recessive inheritance patterns, resulting in curation of 35 GDRs. Of these, 30 (86%) were classified as Definitive, 4 (11%) as Moderate and 1 (3%) as Limited. Two genes, POMGNT1 and DAG1, though definitively related to myopathy, currently have insufficient evidence to support a relationship specifically with LGMD. Conclusions: The expert-reviewed assertions on the clinical validity of genes implicated in LGMDs form an invaluable resource for clinicians and molecular geneticists. We encourage the global neuromuscular community to publish case-level data that help clarify disputed or novel LGMD associations.

Using whole genome sequence findings to assess gene-disease causality in cardiomyopathy and arrhythmia patients.

Aim: The genetic etiologies of cardiomyopathies and arrhythmias have not been fully elucidated. Materials & methods: Research findings from genome analyses in a cardiomyopathy and arrhythmia cohort were gathered. Gene-disease relationships from two databases were compared with patient phenotypes. A literature review was conducted for genes with limited evidence. Results: Of 43 genes with candidate findings from 18 cases, 23.3% of genes had never been curated, 15.0% were curated for cardiomyopathies, 16.7% for arrhythmias and 31.3% for other conditions. 25.5% of candidate findings were curated for the patient's specific phenotype with 11.8% having definitive evidence. MYH6 and TPCN1 were flagged for recuration. Conclusion: Findings from genome sequencing in disease cohorts may be useful to guide gene-curation efforts.