Mathew W. Wright

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.

This commentary is written in response to the recent article from Herring et al., discussing the eradication of the offensive term “retardation” from gene nomenclature. We discuss the work of the HUGO (Human Genome Organisation) Gene Nomenclature Committee (HGNC) and outline the steps already taken to remove this term from our gene names. We also highlight the latest nomenclature changes made as a result of discussions with the authors and agreement with the European Fragile X Network.

Background The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) clinical variant interpretation guidelines established criteria (PS3/BS3) for functional assays that specified a “strong” level of evidence. However, they did not provide detailed guidance on how functional evidence should be evaluated, and differences in the application of the PS3/BS3 codes is a contributor to variant interpretation discordance between laboratories. This recommendation seeks to provide a more structured approach to the assessment of functional assays for variant interpretation and guidance on the use of various levels of strength based on assay validation. Methods The Clinical Genome Resource (ClinGen) Sequence Variant Interpretation (SVI) Working Group used curated functional evidence from ClinGen Variant Curation Expert Panel-developed rule specifications and expert opinions to refine the PS3/BS3 criteria over multiple in-person and virtual meetings. We estimated odds of pathogenicity for assays using various numbers of variant controls to determine the minimum controls required to reach moderate level evidence. Feedback from the ClinGen Steering Committee and outside experts were incorporated into the recommendations at multiple stages of development. Results The SVI Working Group developed recommendations for evaluators regarding the assessment of the clinical validity of functional data and a four-step provisional framework to determine the appropriate strength of evidence that can be applied in clinical variant interpretation. These steps are: 1. Define the disease mechanism; 2. Evaluate applicability of general classes of assays used in the field; 3. Evaluate validity of specific instances of assays; 4. Apply evidence to individual variant interpretation. We found that a minimum of eleven total pathogenic and benign variant controls are required to reach moderate-level evidence in the absence of rigorous statistical analysis. Conclusions The recommendations and approach to functional evidence evaluation described here should help clarify the clinical variant interpretation process for functional assays. Further, we hope that these recommendations will help develop productive partnerships with basic scientists who have developed functional assays that are useful for interrogating the function of a variety of genes.

The Clinical Genome Resource (ClinGen) Ancestry and Diversity Working Group highlights the need to develop guidance on race, ethnicity, and ancestry (REA) data collection and use in clinical genomics. We present quantitative and qualitative evidence to characterize: (1) acquisition of REA data via clinical laboratory requisition forms, and (2) information disparity across populations in the Genome Aggregation Database (gnomAD) at clinically relevant sites ascertained from annotations in ClinVar. Our requisition form analysis showed substantial heterogeneity in clinical laboratory ascertainment of REA, as well as marked incongruity among terms used to define REA categories. There was also striking disparity across REA populations in the amount of information available about clinically relevant variants in gnomAD. European ancestral populations constituted the majority of observations (55.8%), allele counts (59.7%), and private alleles (56.1%) in gnomAD at 550 loci with “pathogenic” and “likely pathogenic” expert‐reviewed variants in ClinVar. Our findings highlight the importance of implementing and supporting programs to increase diversity in genome sequencing and clinical genomics, as well as measuring uncertainty around population‐level datasets that are used in variant interpretation. Finally, we suggest the need for a standardized REA data collection framework to be developed through partnerships and collaborations and adopted across clinical genomics.

The ClinGen Inborn Errors of Metabolism Working Group was tasked with creating a comprehensive, standardized knowledge base of genes and variants for metabolic diseases. Phenylalanine hydroxylase (PAH) deficiency was chosen to pilot development of the Working Group's standards and guidelines. A PAH variant curation expert panel (VCEP) was created to facilitate this process. Following ACMG‐AMP variant interpretation guidelines, we present the development of these standards in the context of PAH variant curation and interpretation. Existing ACMG‐AMP rules were adjusted based on disease (6) or strength (5) or both (2). Disease adjustments include allele frequency thresholds, functional assay thresholds, and phenotype‐specific guidelines. Our validation of PAH‐specific variant interpretation guidelines is presented using 85 variants. The PAH VCEP interpretations were concordant with existing interpretations in ClinVar for 69 variants (81%). Development of biocurator tools and standards are also described. Using the PAH‐specific ACMG‐AMP guidelines, 714 PAH variants have been curated and will be submitted to ClinVar. We also discuss strategies and challenges in applying ACMG‐AMP guidelines to autosomal recessive metabolic disease, and the curation of variants in these genes.

Effective exchange of information about genetic variants is currently hampered by the lack of readily available globally unique variant identifiers that would enable aggregation of information from different sources. The ClinGen Allele Registry addresses this problem by providing (1) globally unique “canonical” variant identifiers (CAids) on demand, either individually or in large batches; (2) access to variant‐identifying information in a searchable Registry; (3) links to allele‐related records in many commonly used databases; and (4) services for adding links to information about registered variants in external sources. A core element of the Registry is a canonicalization service, implemented using in‐memory sequence alignment‐based index, which groups variant identifiers denoting the same nucleotide variant and assigns unique and dereferenceable CAids. More than 650 million distinct variants are currently registered, including those from gnomAD, ExAC, dbSNP, and ClinVar, including a small number of variants registered by Registry users. The Registry is accessible both via a web interface and programmatically via well‐documented Hypertext Transfer Protocol (HTTP) Representational State Transfer Application Programming Interface (REST‐APIs). For programmatic interoperability, the Registry content is accessible in the JavaScript Object Notation for Linked Data (JSON‐LD) format. We present several use cases and demonstrate how the linked information may provide raw material for reasoning about variant's pathogenicity.