Implementation of a dyadic nomenclature for monogenic diseases.

A core task when establishing the strength of evidence for a gene's role in a monogenic disorder is determining the appropriate disease entity to curate. Establishing this concept determines which evidence can be applied and quantified toward the final gene-disease validity, variant pathogenicity, or actionability classification. Genes with implications in more than one phenotype can necessitate a process of lumping and splitting, disease reorganization, and updates to disease nomenclature. Reappraisal of the names that are used as labels for disease entities is therefore a necessary and perpetual process. The Clinical Genome Resource (ClinGen), in collaboration with representatives from Monarch Disease Ontology (Mondo) and Online Inheritance in Man (OMIM), formed the Disease Naming Advisory Committee (DNAC) to develop guidance for groups faced with the need to establish the "curated disease entity" for gene-phenotype validity and variant pathogenicity and to update disease names for clinical use when necessary. The objective of this group was to harmonize guidance for disease naming across these nosologic entities and among ClinGen curation groups in collaboration with other disease-related professional groups. Here, we present the initial guidance developed by the DNAC with representative examples provided by the ClinGen expert panels and working groups that warranted nomenclature updates. We also discuss the broader implications of these efforts and their benefits for harmonization of gene-disease validity curation. Overall, this work sheds light on current inconsistencies and/or discrepancies and is designed to engage the broader community on how ClinGen defines monogenic disorders using a consistent approach for disease naming.

Operational description of rare diseases: a reference to improve the recognition and visibility of rare diseases.

Improving health and social equity for persons living with a rare disease (PLWRD) is increasingly recognized as a global policy priority. However, there is currently no international alignment on how to define and describe rare diseases. A global reference is needed to establish a mutual understanding to inform a wide range of stakeholders for actions. A multi-stakeholder, global panel of rare disease experts, came together and developed an Operational Description of Rare Diseases. This reference describes which diseases are considered rare, how many persons are affected and why the rare disease population demands specific attention. The operational description of rare diseases is framed in two parts: a core definition of rare diseases, complemented by a descriptive framework of rare diseases. The core definition includes parameters that permit the identification of which diseases are considered rare, and how many persons are affected. The descriptive framework elaborates on the impact and burden of rare diseases on patients, their caregivers and families, healthcare systems, and society overall. The Operational Description of Rare Diseases establishes a common point of reference for decision-makers across the world who strive to understand and address the unmet needs of persons living with a rare disease. Adoption of this reference is essential to improving the visibility of rare conditions in health systems across the world. Greater recognition of the burden of rare diseases will motivate new actions and policies to address the unmet needs of the rare disease community.

Lipodystrophy in methylmalonic acidemia associated with elevated FGF21 and abnormal methylmalonylation.

A distinct adipose tissue distribution pattern was observed in patients with methylmalonyl-CoA mutase deficiency, an inborn error of branched-chain amino acid (BCAA) metabolism, characterized by centripetal obesity with proximal upper and lower extremity fat deposition and paucity of visceral fat, that resembles familial multiple lipomatosis syndrome. To explore brown and white fat physiology in methylmalonic acidemia (MMA), body composition, adipokines, and inflammatory markers were assessed in 46 patients with MMA and 99 matched controls. Fibroblast growth factor 21 levels were associated with acyl-CoA accretion, aberrant methylmalonylation in adipose tissue, and an attenuated inflammatory cytokine profile. In parallel, brown and white fat were examined in a liver-specific transgenic MMA mouse model (Mmut-/- TgINS-Alb-Mmut). The MMA mice exhibited abnormal nonshivering thermogenesis with whitened brown fat and had an ineffective transcriptional response to cold stress. Treatment of the MMA mice with bezafibrates led to clinical improvement with beiging of subcutaneous fat depots, which resembled the distribution seen in the patients. These studies defined what we believe to be a novel lipodystrophy phenotype in patients with defects in the terminal steps of BCAA oxidation and demonstrated that beiging of subcutaneous adipose tissue in MMA could readily be induced with small molecules.

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.

The remarkable journey of one female individual with ornithine transcarbamylase deficiency diagnosed post-mortem.

Urea cycle disorders (UCDs) comprise a group of inborn errors of metabolism with impaired ammonia clearance and an incidence of ~1:35 000 individuals. First described in the 1970s, the diagnosis and management of these disorders has evolved dramatically. We report on a 59-year-old woman with a UCD who contributed to advances in the understanding and treatment of this group of disorders. This individual was diagnosed with carbamoyl phosphate synthetase 1 deficiency based on a biochemical assay under a research context predating genetic sequencing, treated longitudinally as having this metabolic disorder, and was among the first participants to trial UCD pharmaceutical therapies. She ultimately succumbed to a SARS-CoV-2 infection while maintaining unexpectedly normal ammonium levels. Postmortem genetic testing revealed ornithine transcarbamylase deficiency. This individual's contributions to the field of UCDs is discussed herein.

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.

Exploring Genes and Phenotypes Within Chromosomal Regions Using OMIM's GeneScout.

Structural variation in genomes, such as copy number variants (CNVs), is under scrutiny for its contribution to phenotypic expression and evolution. Regions of homozygosity (ROH) are ripe for phenotype-gene discovery. Determining the genes and related phenotypes within genomic regions is key to studying potential functional and phenotypic consequences. Because individuals have multiple CNVs and ROHs in their genome, identifying genomic regions that are phenotypically significant is challenging. GeneScout is a web-based tool that can be used to search genomic regions to display and filter the genes and their associated phenotypes within regions of interest. Phenotypes and their associated gene(s) can then be filtered to show only the genes with phenotypes that have a particular inheritance pattern and/or specific clinical feature(s). Phenotypes can then be selected to compare the clinical synopses side-by-side in Online Mendelian Inheritance in Man (OMIM® ). Additionally, two coordinate sets can be compared to determine either the regions of overlap or the unique regions (subtraction). The resulting coordinate ranges are displayed on the results page, and the results table displays only the genes and phenotypes present within the coordinate ranges. The interactive table includes gene-specific links to external resources such as ClinVar, ClinGen validity, ClinGen dosage, and gnomAD, and a diamond symbol next to the gene name indicates a gene that spans the start or end of a coordinate range. Searches and comparisons may be performed for coordinates in assemblies GRCh37 (hg19) and GRCh38 (hg38). The results page offers the option to liftover coordinates entered in GRCh37 to GRCh38 and updates the results table to display the gene content based on assembly GRCh38. The search coordinates and results table can be downloaded in a tab-delimited or Excel file. © 2022 Wiley Periodicals LLC. Basic Protocol: Searching GeneScout.

Monochorionic twins with 15q26.3 duplication presenting with selective intrauterine growth restriction and discordant cardiac anomalies: A case report.

BACKGROUND: Duplication of the distal end of chromosome 15q has been previously implicated in a characteristic overgrowth syndrome. Additionally, many patients have other congenital malformations, including cardiac, renal, genital, and musculoskeletal anomalies. However, some patients may present with intrauterine growth restriction and short stature. Different breakpoints within 15q, as well as different environmental factors, may underlie these varied presentations. CASE PRESENTATION: We discuss monochorionic-diamniotic twins with a ~345 kb maternally inherited duplication in 15q26.3. The twins presented with discordant pathology-one twin with a single umbilical artery, selective intrauterine growth restriction, and multiple cardiac defects including aortic coarctation, aortic valve stenosis, and ventricular septal defect, whereas the other twin was unaffected. To our knowledge, this case represents the smallest reported duplication of distal 15q. CONCLUSION: The discordant phenotype seen in the twins is likely due to a complex interplay between genetic and environmental causes. The affected infant presented prenatally with growth restriction and a single umbilical artery rather than overgrowth, potentially due to a unique breakpoint within 15q. This, in turn, may have produced hemodynamic perturbations between the twins, leading to discordant cardiac disease. Our report thus highlights the importance of genetic and nongenetic mechanisms underlying discordant anomalies in monochorionic twins.

Lumping versus splitting: How to approach defining a disease to enable accurate genomic curation.

The dilemma of how to categorize and classify diseases has been debated for centuries. The field of medical genetics has historically approached nosology based on clinical phenotypes observed in patients and families. Advances in genomic sequencing and understanding of genetic contributions to disease often provoke a need to reassess these classifications. The Clinical Genome Resource (ClinGen) has developed frameworks to classify the strength of evidence underlying monogenic gene-disease relationships, variant pathogenicity, and clinical actionability. It is therefore necessary to define the disease entity being evaluated, which can be challenging for genes associated with multiple conditions and/or a broad phenotypic spectrum. We therefore developed criteria to guide "lumping and splitting" decisions and improve consistency in defining monogenic gene-disease relationships. Here, we outline the precuration process, the lumping and splitting guidelines with examples, and describe the implications for clinical diagnosis, informatics, and care management.

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.

Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking.

The Matchmaker Exchange (MME) was launched in 2015 to provide a robust mechanism to discover novel disease-gene relationships. It operates as a federated network connecting databases holding relevant data using a common application programming interface, where two or more users are looking for a match for the same gene (two-sided matchmaking). Seven years from its launch, it is clear that the MME is making outstanding contributions to understanding the morbid anatomy of the genome. The number of unique genes present across the MME has steadily increased over time; there are currently >13,520 unique genes (~68% of all protein-coding genes) connected across the MME's eight genomic matchmaking nodes, GeneMatcher, DECIPHER, PhenomeCentral, MyGene2, seqr, Initiative on Rare and Undiagnosed Disease, PatientMatcher, and the RD-Connect Genome-Phenome Analysis Platform. The collective data set accessible across the MME currently includes more than 120,000 cases from over 12,000 contributors in 98 countries. The discovery of potential new disease-gene relationships is happening daily and international collaborative teams are moving these advances forward to publication, now numbering well over 500. Expansion of data sharing into routine clinical practice by clinicians, genetic counselors, and clinical laboratories has ensured access to discovery for even more individuals with undiagnosed rare genetic diseases. Tens of thousands of patients and their family members have been directly or indirectly impacted by the discoveries facilitated by two-sided genomic matchmaking. MME supports further connections to the literature (PubCaseFinder) and to human and model organism resources (Monarch Initiative) and scientists (ModelMatcher). Efforts are now underway to explore additional approaches to matchmaking at the gene or variant level where there is only one querier (one-sided matchmaking). Genomic matchmaking has proven its utility over the past 7 years and will continue to facilitate discoveries in the years to come.

The impact of GeneMatcher on international data sharing and collaboration.

GeneMatcher (genematcher.org) is a tool designed to connect individuals with an interest in the same gene. Now used around the world to create collaborations and generate the evidence needed to support novel disease gene identification, GeneMatcher is a founding member of the Matchmaker Exchange (MME; matchmakerexchange.org) and strongest possible advocate for global data sharing including those in resource-limited environments. As of October 1, 2021, there are 12,531 submitters from 94 countries who have submitted 58,134 submissions with 13,498 unique genes in the database. Among these genes, 8970 (64%) have matched at least once and the total number of matches is 378,806, growing by about 10,000 per month. GeneMatcher submitters increase by 80-120 each month and submissions grow by >800 per month, while unique genes and gene matches continue to grow steadily at rate of about 80 per month. The number of genes without a match peaked at 4371 in February of 2019 and despite the increase in the number of new submissions, the number of unique genes without a match continues to slowly decline, currently standing at 4,016. All submissions in GeneMatcher are available for matching across the MME.

Variant-level matching for diagnosis and discovery: Challenges and opportunities.

Here we describe MyGene2, Geno2MP, VariantMatcher, and Franklin; databases that provide variant-level information and phenotypic features to researchers, clinicians, healthcare providers and patients. Following the footsteps of the Matchmaker Exchange project that connects exome, genome, and phenotype databases at the gene level, these databases have as one goal to facilitate connection to one another using Data Connect, a standard for discovery and search of biomedical data from the Global Alliance for Genomics and Health (GA4GH).

Centers for Mendelian Genomics: A decade of facilitating gene discovery.

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

Three decades of the Human Genome Organization.

The Human Genome Organization (HUGO) was initially established in 1988 to help integrate international scientific genomic activity and to accelerate the diffusion of knowledge from the efforts of the human genome project. Its founding President was Victor McKusick. During the late 1980s and 1990s, HUGO organized lively gene mapping meetings to accurately place genes on the genome as chromosomes were being sequenced. With the completion of the Human Genome Project, HUGO went through some transitions and self-reflection. In 2020, HUGO (which hosts a large annual scientific meeting and comprises the renowned HUGO Gene Nomenclature Committee [HGNC], responsible for naming genes, and an outstanding Ethics Committee) was merged with the Human Genome Variation Society (HGVS; which defines the correct nomenclature for variation description) and the Human Variome Project (HVP; championed by the late Richard Cotton) into a single organization that is committed to assembling human genomic variation from all over the world. This consolidated effort, under a new Executive Board and seven focused committees, will facilitate efficient and effective communication and action to bring the benefits of increasing knowledge of genome diversity and biology to people all over the world.

PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data.

BACKGROUND: With the advent of whole exome (ES) and genome sequencing (GS) as tools for disease gene discovery, rare variant filtering, prioritization and data sharing have become essential components of the search for disease genes and variants potentially contributing to disease phenotypes. The computational storage, data manipulation, and bioinformatic interpretation of thousands to millions of variants identified in ES and GS, respectively, is a challenging task. To aid in that endeavor, we constructed PhenoDB, GeneMatcher and VariantMatcher. RESULTS: PhenoDB is an accessible, freely available, web-based platform that allows users to store, share, analyze and interpret their patients' phenotypes and variants from ES/GS data. GeneMatcher is accessible to all stakeholders as a web-based tool developed to connect individuals (researchers, clinicians, health care providers and patients) around the globe with interest in the same gene(s), variant(s) or phenotype(s). Finally, VariantMatcher was developed to enable public sharing of variant-level data and phenotypic information from individuals sequenced as part of multiple disease gene discovery projects. Here we provide updates on PhenoDB and GeneMatcher applications and implementation and introduce VariantMatcher. CONCLUSION: Each of these tools has facilitated worldwide data sharing and data analysis and improved our ability to connect genes to phenotypic traits. Further development of these platforms will expand variant analysis, interpretation, novel disease-gene discovery and facilitate functional annotation of the human genome for clinical genomics implementation and the precision medicine initiative.