The Brain Gene Registry: a data snapshot.

Monogenic disorders account for a large proportion of population-attributable risk for neurodevelopmental disabilities. However, the data necessary to infer a causal relationship between a given genetic variant and a particular neurodevelopmental disorder is often lacking. Recognizing this scientific roadblock, 13 Intellectual and Developmental Disabilities Research Centers (IDDRCs) formed a consortium to create the Brain Gene Registry (BGR), a repository pairing clinical genetic data with phenotypic data from participants with variants in putative brain genes. Phenotypic profiles are assembled from the electronic health record (EHR) and a battery of remotely administered standardized assessments collectively referred to as the Rapid Neurobehavioral Assessment Protocol (RNAP), which include cognitive, neurologic, and neuropsychiatric assessments, as well as assessments for attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Co-enrollment of BGR participants in the Clinical Genome Resource's (ClinGen's) GenomeConnect enables display of variant information in ClinVar. The BGR currently contains data on 479 participants who are 55% male, 6% Asian, 6% Black or African American, 76% white, and 12% Hispanic/Latine. Over 200 genes are represented in the BGR, with 12 or more participants harboring variants in each of these genes: CACNA1A, DNMT3A, SLC6A1, SETD5, and MYT1L. More than 30% of variants are de novo and 43% are classified as variants of uncertain significance (VUSs). Mean standard scores on cognitive or developmental screens are below average for the BGR cohort. EHR data reveal developmental delay as the earliest and most common diagnosis in this sample, followed by speech and language disorders, ASD, and ADHD. BGR data has already been used to accelerate gene-disease validity curation of 36 genes evaluated by ClinGen's BGR Intellectual Disability (ID)-Autism (ASD) Gene Curation Expert Panel. In summary, the BGR is a resource for use by stakeholders interested in advancing translational research for brain genes and continues to recruit participants with clinically reported variants to establish a rich and well-characterized national resource to promote research on neurodevelopmental disorders.

Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms.

Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.

Expansion of the Genotypic and Phenotypic Spectrum of ASH1L-Related Syndromic Neurodevelopmental Disorder.

Pathogenic ASH1L variants have been reported in probands with broad phenotypic presentations, including intellectual disability, autism spectrum disorder, attention deficit hyperactivity disorder, seizures, congenital anomalies, and other skeletal, muscular, and sleep differences. Here, we review previously published individuals with pathogenic ASH1L variants and report three further probands with novel ASH1L variants and previously unreported phenotypic features, including mixed receptive language disorder and gait disturbances. These novel data from the Brain Gene Registry, an accessible repository of clinically derived genotypic and phenotypic data, have allowed for the expansion of the phenotypic and genotypic spectrum of this condition.

Detection of Beet curly top virus in Solanum jamesii, Artemisia tridentata, Helianthus annuus, and Cannabis sativa in Utah.

Historically, beet curly top virus (BCTV; Geminiviridae, Curtovirus) is known for destroying the sugar beet industry in Utah and has been a persistent problem in the state since then (Ball, 1917). Starting in June of 2022, we began identifying plants in San Juan County, Utah with chlorosis and leaf curling. Of note, Solanum jamesii, the Four Corners potato, Artemisia tridentata, big sagebrush, and Helianthus annuus, common sunflower, were found with general chlorosis, severe leaf curling and in the case of the sage brush, completely lacking in smell whereas nearby sage plants without the yellowing were intensely fragrant. In August 2023, Cannabis sativa plants for hemp production were found with severe leaf curling in Juab County, Utah. Samples were collected and stored at -80°C for future work. DNA was extracted using the IBI Genomic Plant DNA kit (IBI Scientific, Dubuque, IA) and subjected to rolling circle amplification using Phi29 polymerase (NEB, Ipswich, MA). The primer set BCTV2 (Strausbaugh et al. 2008) for BCTV detection was then used on a subset of the RCA-positive samples for either one (A. tridentata, H. annus, and S. jamesii) or two (C. sativa) plants displaying classic BCTV symptoms, to amplify a 518 bp region. This amplicon was then sequenced by the Sanger method to a 4x coverage. The resulting sequences (accession nos. OR698900 to OR698904) share 98.94 to 99.80% nucleotide identity to the Worland strain (accession no. KU892789.1) for all samples. To confirm the detection, a triple antibody sandwich ELISA kit from Nano Diagnostics (San Jose, CA) was used on these, and other plants of similar species and symptoms from across the state. Samples that tested positive include 3/3 symptomatic H. annuus plants, 1/1 symptomatic S. jamesii, 3/3 symptomatic A. tridentata. The A. tridentata samples were collected from Juab, San Juan, and Utah Counties. None of three asymptomatic A. tridentata plants tested were ELISA positive. Of the C. sativa plants tested by ELISA, 9/9 of the plants displaying classic BCTV symptoms in that host were positive and 6/6 of the plants without classic BCTV symptoms were ELISA positive. The findings of these novel hosts indicate the need for increased testing and analysis of economically relevant crops and native flora across the state. These findings represent a concern for conservation in the case of S. jamesii and a potential threat to the growing hemp industry in the state due to the severity of BCTV symptoms on these plants. Additionally, the finding of A. tridentata as a host may represent a significant finding for the epidemiology of BCTV in the Mountain West region as A. tridentata is distributed from Mexico to Canada along the Rocky Mountain range and is found in much of the Western US in arid regions. This is the first report, to our knowledge, of S. jamesii and A. tridentata as hosts for BCTV and the first peer reviewed reports for H. annuus and C. sativa as hosts for BCTV in Utah.

Recommendations for risk allele evidence curation, classification, and reporting from the ClinGen Low Penetrance/Risk Allele Working Group.

PURPOSE: Genetic variants at the low end of the penetrance spectrum have historically been challenging to interpret because their high population frequencies exceed the disease prevalence of the associated condition, leading to a lack of clear segregation between the variant and disease. There is currently substantial variation in the classification of these variants, and no formal classification framework has been widely adopted. The Clinical Genome Resource Low Penetrance/Risk Allele Working Group was formed to address these challenges and promote harmonization within the clinical community. METHODS: The work presented here is the product of internal and community Likert-scaled surveys in combination with expert consensus within the Working Group. RESULTS: We formally recognize risk alleles and low-penetrance variants as distinct variant classes from those causing highly penetrant disease that require special considerations regarding their clinical classification and reporting. First, we provide a preferred terminology for these variants. Second, we focus on risk alleles and detail considerations for reviewing relevant studies and present a framework for the classification these variants. Finally, we discuss considerations for clinical reporting of risk alleles. CONCLUSION: These recommendations support harmonized interpretation, classification, and reporting of variants at the low end of the penetrance spectrum.

Toward robust clinical genome interpretation: Developing a consistent terminology to characterize Mendelian disease-gene relationships-allelic requirement, inheritance modes, and disease mechanisms.

PURPOSE: The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here, we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation and to support variant classification within the ACMG/AMP framework. METHODS: Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated. RESULTS: We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both Sequence Ontology (SO) and Human Phenotype Ontology (HPO) ontologies. Gene Curation Coalition member groups intend to use or map to these terms in their respective resources. CONCLUSION: The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

Clinical variants paired with phenotype: A rich resource for brain gene curation.

PURPOSE: Clinically ascertained variants are under-utilized in neurodevelopmental disorder research. We established the Brain Gene Registry (BGR) to coregister clinically identified variants in putative brain genes with participant phenotypes. Here, we report 179 genetic variants in the first 179 BGR registrants and analyze the proportion that were novel to ClinVar at the time of entry and those that were absent in other disease databases. METHODS: From 10 academically affiliated institutions, 179 individuals with 179 variants were enrolled into the BGR. Variants were cross-referenced for previous presence in ClinVar and for presence in 6 other genetic databases. RESULTS: Of 179 variants in 76 genes, 76 (42.5%) were novel to ClinVar, and 62 (34.6%) were absent from all databases analyzed. Of the 103 variants present in ClinVar, 37 (35.9%) were uncertain (ClinVar aggregate classification of variant of uncertain significance or conflicting classifications). For 5 variants, the aggregate ClinVar classification was inconsistent with the interpretation from the BGR site-provided classification. CONCLUSION: A significant proportion of clinical variants that are novel or uncertain are not shared, limiting the evidence base for new gene-disease relationships. Registration of paired clinical genetic test results with phenotype has the potential to advance knowledge of the relationships between genes and neurodevelopmental disorders.

Towards robust clinical genome interpretation: developing a consistent terminology to characterize disease-gene relationships - allelic requirement, inheritance modes and disease mechanisms.

PURPOSE: The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation, and to support variant classification within the ACMG/AMP framework. METHODS: Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition (GenCC) members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated. RESULTS: We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both sequence ontology (SO) and human phenotype ontology (HPO) ontologies. GenCC member groups intend to use or map to these terms in their respective resources. CONCLUSION: The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

The Gene Curation Coalition: A global effort to harmonize gene-disease evidence resources.

PURPOSE: Several groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed. METHODS: The GenCC drafted harmonized definitions for differing levels of gene-disease validity on the basis of existing resources, and performed a modified Delphi survey with 3 rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene-disease validity assertions from its members. RESULTS: On the basis of 241 survey responses from the genetics community, a consensus term set was chosen for grading gene-disease validity and database submissions. As of December 2021, the database contained 15,241 gene-disease assertions on 4569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene-disease validity ranged from 5.3% to 13.4%. CONCLUSION: Terminology standardization, sharing of gene-disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.

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.

ClinGen Variant Curation Interface: a variant classification platform for the application of evidence criteria from ACMG/AMP guidelines.

BACKGROUND: Identification of clinically significant genetic alterations involved in human disease has been dramatically accelerated by developments in next-generation sequencing technologies. However, the infrastructure and accessible comprehensive curation tools necessary for analyzing an individual patient genome and interpreting genetic variants to inform healthcare management have been lacking. RESULTS: Here we present the ClinGen Variant Curation Interface (VCI), a global open-source variant classification platform for supporting the application of evidence criteria and classification of variants based on the ACMG/AMP variant classification guidelines. The VCI is among a suite of tools developed by the NIH-funded Clinical Genome Resource (ClinGen) Consortium and supports an FDA-recognized human variant curation process. Essential to this is the ability to enable collaboration and peer review across ClinGen Expert Panels supporting users in comprehensively identifying, annotating, and sharing relevant evidence while making variant pathogenicity assertions. To facilitate evidence-based improvements in human variant classification, the VCI is publicly available to the genomics community. Navigation workflows support users providing guidance to comprehensively apply the ACMG/AMP evidence criteria and document provenance for asserting variant classifications. CONCLUSIONS: The VCI offers a central platform for clinical variant classification that fills a gap in the learning healthcare system, facilitates widespread adoption of standards for clinical curation, and is available at https://curation.clinicalgenome.org.

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.

Recontacting registry participants with genetic updates through GenomeConnect, the ClinGen patient registry.

PURPOSE: Variant classifications and gene-disease relationships may evolve. Professional societies have suggested patients share the responsibility to remain up-to-date on the implications genetic results have on their health, and that novel methods of recontact are needed. GenomeConnect, the ClinGen patient registry, has implemented a process to provide variant classification and gene-disease relationship updates to participants. Here, we report on our experience with this recontacting process. METHODS: GenomeConnect shares data with ClinVar and Matchmaker Exchange enabling the identification of updates to variant classifications and gene-disease relationships. For any updates identified, the reporting laboratory is contacted, and updates are shared with participants opting to receive them. RESULTS: Of 1,419 variants shared with ClinVar by GenomeConnect, 49 (3.4%) variant reclassifications were identified and 34 were shared with participants. Of 97 candidate genes submitted to Matchmaker Exchange, 10 (10.3%) gene-disease relationships have been confirmed and 9 were shared with participants. Details available from a subset of participants highlight that updated information is not always shared with the patient by testing laboratories. CONCLUSION: Patient registries can provide a mechanism for patients and their providers to remain informed about changes to the interpretation and clinical significance of their genetic results, leading to important implications for care.

Ensuring best practice in genomics education and evaluation: reporting item standards for education and its evaluation in genomics (RISE2 Genomics).

PURPOSE: Widespread, quality genomics education for health professionals is required to create a competent genomic workforce. A lack of standards for reporting genomics education and evaluation limits the evidence base for replication and comparison. We therefore undertook a consensus process to develop a recommended minimum set of information to support consistent reporting of design, development, delivery, and evaluation of genomics education interventions. METHODS: Draft standards were derived from literature (25 items from 21 publications). Thirty-six international experts were purposively recruited for three rounds of a modified Delphi process to reach consensus on relevance, clarity, comprehensiveness, utility, and design. RESULTS: The final standards include 18 items relating to development and delivery of genomics education interventions, 12 relating to evaluation, and 1 on stakeholder engagement. CONCLUSION: These Reporting Item Standards for Education and its Evaluation in Genomics (RISE2 Genomics) are intended to be widely applicable across settings and health professions. Their use by those involved in reporting genomics education interventions and evaluation, as well as adoption by journals and policy makers as the expected standard, will support greater transparency, consistency, and comprehensiveness of reporting. Consequently, the genomics education evidence base will be more robust, enabling high-quality education and evaluation across diverse settings.

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven't been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

Variant interpretation is a component of clinical practice among genetic counselors in multiple specialties.

PURPOSE: Genomic testing is routinely utilized across clinical settings and can have significant variant interpretation challenges. The extent of genetic counselor (GC) engagement in variant interpretation in clinical practice is unknown. This study aimed to explore clinical GCs' variant interpretation practice across specialties, understand outcomes of this practice, and identify resource and educational needs. METHODS: An online survey was administered to National Society of Genetic Counselors members providing clinical counseling. RESULTS: Respondents (n = 239) represented all major clinical specialties. The majority (68%) reported reviewing evidence documented by the laboratory for most (>60%) variants reported; 45.5% report seeking additional evidence. Prenatal GCs were less likely to independently assess reported evidence. Most respondents (67%) report having reached a different conclusion about a variant's classification than the testing laboratory, though infrequently. Time was the most commonly reported barrier (72%) to performing variant interpretation, though the majority (97%) indicated that this practice had an important impact on patient care. When presented with three hypothetical scenarios, evidence typically used for variant interpretation was generally applied correctly. CONCLUSION: This study is the first to document variant interpretation practice broadly across clinical GC specialties. Our results suggest that variant interpretation should be considered a practice-based competency for GCs.