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.

Father's care uniquely influences male neurodevelopment.

Mammalian infants depend on parental care for survival, with numerous consequences for their behavioral development. We investigated the epigenetic and neurodevelopmental mechanisms mediating the impact of early biparental care on development of alloparenting behavior, or caring for offspring that are not one's own. We find that receiving high parental care early in life leads to slower epigenetic aging of both sexes and widespread male-specific differential expression of genes related to synaptic transmission and autism in the nucleus accumbens. Examination of parental care composition indicates that high-care fathers promote a male-specific increase in excitatory synapses and increases in pup retrieval behavior as juveniles. Interestingly, females raised by high-care fathers have the opposite behavioral response and display fewer pup retrievals. These results support the concept that neurodevelopmental trajectories are programmed by different features of early-life parental care and reveal that male neurodevelopmental processes are uniquely sensitive to care by fathers.

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 PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health.

INTRODUCTION: Social determinants are structures and conditions in the biological, physical, built, and social environments that affect health, social and physical functioning, health risk, quality of life, and health outcomes. The adoption of recommended, standard measurement protocols for social determinants of health will advance the science of minority health and health disparities research and provide standard social determinants of health protocols for inclusion in all studies with human participants. METHODS: A PhenX (consensus measures for Phenotypes and eXposures) Working Group of social determinants of health experts was convened from October 2018 to May 2020 and followed a well-established consensus process to identify and recommend social determinants of health measurement protocols. The PhenX Toolkit contains data collection protocols suitable for inclusion in a wide range of research studies. The recommended social determinants of health protocols were shared with the broader scientific community to invite review and feedback before being added to the Toolkit. RESULTS: Nineteen social determinants of health protocols were released in the PhenX Toolkit (https://www.phenxtoolkit.org) in May 2020 to provide measures at the individual and structural levels for built and natural environments, structural racism, economic resources, employment status, occupational health and safety, education, environmental exposures, food environment, health and health care, and sociocultural community context. CONCLUSIONS: Promoting the adoption of well-established social determinants of health protocols can enable consistent data collection and facilitate comparing and combining studies, with the potential to increase their scientific impact.

Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX.

Identifying relevant studies and harmonizing datasets are major hurdles for data reuse. Common Data Elements (CDEs) can help identify comparable study datasets and reduce the burden of retrospective data harmonization, but they have not been required, historically. The collaborative team at PhenX and dbGaP developed an approach to use PhenX variables as a set of CDEs to link phenotypic data and identify comparable studies in dbGaP. Variables were identified as either comparable or related, based on the data collection mode used to harmonize data across mapped datasets. We further added a CDE data field in the dbGaP data submission packet to indicate use of PhenX and annotate linkages in the future. Some 13,653 dbGaP variables from 521 studies were linked through PhenX variable mapping. These variable linkages have been made accessible for browsing and searching in the repository through dbGaP CDE-faceted search filter and the PhenX variable search tool. New features in dbGaP and PhenX enable investigators to identify variable linkages among dbGaP studies and reveal opportunities for cross-study analysis.

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.

A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources.

OBJECTIVE: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled "Developing a Clinical Genomic Informatics Research Agenda". The meeting's goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. MATERIALS AND METHODS: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. RESULTS: Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. DISCUSSION: Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.

ClinGen's Pediatric Actionability Working Group: Clinical actionability of secondary findings from genome-scale sequencing in children and adolescents.

PURPOSE: Synthesis and curation of evidence regarding the clinical actionability of secondary findings (SFs) from genome-scale sequencing are needed to support decision-making on reporting of these findings. To assess actionability of SFs in children and adolescents, the Clinical Genome Resource established the Pediatric Actionability Working Group (AWG). METHODS: The Pediatric AWG modified the framework of the existing Adult AWG, which included production of summary reports of actionability for genes and associated conditions and consensus actionability scores for specific outcome-intervention pairs. Modification of the adult framework for the pediatric setting included accounting for special considerations for reporting presymptomatic or predictive genetic findings in the pediatric context, such as maintaining future autonomy by not disclosing conditions not actionable until adulthood. The Pediatric AWG then applied this new framework to genes and associated conditions with putative actionability. RESULTS: As of September 2021, the Pediatric AWG applied the new framework to 70 actionability topics representing 143 genes. Reports and scores are publicly available at www.clinicalgenome.org. CONCLUSION: The Pediatric AWG continues to curate gene-condition topics and build an evidence-based resource, supporting clinical communities and decision-makers with policy development on the return of SFs in pediatric populations.

Using the PhenX Toolkit to Select Standard Measurement Protocols for Your Research Study.

The goals of PhenX (consensus measures for Phenotypes and eXposures) are to promote the use of standard measurement protocols and to help investigators identify opportunities for collaborative research and cross-study analysis, thus increasing the impact of individual studies. The PhenX Toolkit (https://www.phenxtoolkit.org/) offers high-quality, well-established measurement protocols to assess phenotypes and exposures in studies with human participants. The Toolkit contains protocols representing 29 research domains and 6 specialty collections of protocols that add depth to the Toolkit in specific research areas (e.g., COVID-19, Social Determinants of Health [SDoH], Blood Sciences Research [BSR], Mental Health Research [MHR], Tobacco Regulatory Research [TRR], and Substance Abuse and Addiction [SAA]). Protocols are recommended for inclusion in the PhenX Toolkit by Working Groups of domain experts using a consensus process that includes input from the scientific community. For each PhenX protocol, the Toolkit provides a detailed description, the rationale for inclusion, and supporting documentation. Users can browse protocols in the Toolkit, search the Toolkit using keywords, or use Browse Protocols Tree to identify protocols of interest. The PhenX Toolkit provides data dictionaries compatible with the database of Genotypes and Phenotypes (dbGaP), Research Electronic Data Capture (REDCap) data submission compatibility, and data collection worksheets to help investigators incorporate PhenX protocols into their study design. The PhenX Toolkit provides resources to help users identify published studies that used PhenX protocols. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Using the PhenX Toolkit to support or extend study design.

Genomic medicine implementation protocols in the PhenX Toolkit: tools for standardized data collection.

PURPOSE: The PhenX Toolkit ( www.phenxtoolkit.org ), an online catalog of recommended measurement protocols, facilitates cross-study analyses for research with human participants. The PhenX Steering Committee recommended genomic medicine implementation as a new research domain, with the following scope: genomic knowledge and education (both patients and providers); implementation science; changes in management and treatment; return of results; patient outcomes; and ethical, legal, and social issues (ELSI) associated with genomic research. METHODS: A seven-member expert Working Group convened in October 2019 to identify well-established measurement protocols for a new genomic medicine implementation domain and used the established PhenX consensus process to select measurement protocols for inclusion in the PhenX Toolkit. RESULTS: The Working Group recommended 15 measurement protocols for inclusion in the PhenX Toolkit, with priority given to those with empirical evidence supporting validity. Consortia funded by the National Institutes of Health, and particularly the National Human Genome Research Institute, proved critical in identifying protocols with established utility in this research domain, and identified protocols that were developed through a rigorous process for scope elements that lacked formally validated protocols. CONCLUSION: Use of these protocols, which were released in September 2020, can facilitate standard data collection for genomic medicine implementation research.

Improving reporting standards for polygenic scores in risk prediction studies.

Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

Clinical Genetics Lacks Standard Definitions and Protocols for the Collection and Use of Diversity Measures.

Genetics researchers and clinical professionals rely on diversity measures such as race, ethnicity, and ancestry (REA) to stratify study participants and patients for a variety of applications in research and precision medicine. However, there are no comprehensive, widely accepted standards or guidelines for collecting and using such data in clinical genetics practice. Two NIH-funded research consortia, the Clinical Genome Resource (ClinGen) and Clinical Sequencing Evidence-generating Research (CSER), have partnered to address this issue and report how REA are currently collected, conceptualized, and used. Surveying clinical genetics professionals and researchers (n = 448), we found heterogeneity in the way REA are perceived, defined, and measured, with variation in the perceived importance of REA in both clinical and research settings. The majority of respondents (>55%) felt that REA are at least somewhat important for clinical variant interpretation, ordering genetic tests, and communicating results to patients. However, there was no consensus on the relevance of REA, including how each of these measures should be used in different scenarios and what information they can convey in the context of human genetics. A lack of common definitions and applications of REA across the precision medicine pipeline may contribute to inconsistencies in data collection, missing or inaccurate classifications, and misleading or inconclusive results. Thus, our findings support the need for standardization and harmonization of REA data collection and use in clinical genetics and precision health research.

Development of a consent resource for genomic data sharing in the clinical setting.

PURPOSE: Data sharing between clinicians, laboratories, and patients is essential for improvements in genomic medicine, but obtaining consent for individual-level data sharing is often hindered by a lack of time and resources. To address this issue, the Clinical Genome Resource (ClinGen) developed tools to facilitate consent, including a one-page consent form and online supplemental video with information on key topics, such as risks and benefits of data sharing. METHODS: To determine whether the consent form and video accurately conveyed key data sharing concepts, we surveyed 5,162 members of the general public. We measured comprehension at baseline, after reading the form and watching the video. Additionally, we assessed participants' attitudes toward genomic data sharing. RESULTS: Participants' performance on comprehension questions significantly improved over baseline after reading the form and continued to improve after watching the video. CONCLUSION: Results suggest reading the form alone provided participants with important knowledge regarding broad data sharing, and watching the video allowed for broader comprehension. These materials are now available at http://www.clinicalgenome.org/share . These resources will provide patients a straightforward way to share their genetic and health information, and improve the scientific community's access to data generated through routine healthcare.

Development of Clinical Domain Working Groups for the Clinical Genome Resource (ClinGen): lessons learned and plans for the future.

The Clinical Genome Resource (ClinGen) is supported by the National Institutes of Health (NIH) to develop expertly curated and freely accessible resources defining the clinical relevance of genes and variants for use in precision medicine and research. To facilitate expert input, ClinGen has formed Clinical Domain Working Groups (CDWGs) to leverage the collective knowledge of clinicians, laboratory diagnosticians, and researchers. In the initial phase of ClinGen, CDWGs were launched in the cardiovascular, hereditary cancer, and inborn errors of metabolism clinical fields. These early CDWGs established the infrastructure necessary to implement standardized processes developed or adopted by ClinGen working groups for the interpretation of gene-disease associations and variant pathogenicity, and provided a sustainable model for the formation of future disease-focused curation groups. The establishment of CDWGs requires recruitment of international experts to broadly represent the interests of their field and ensure that assertions made are reliable and widely accepted. Building on the successes, challenges, and trade-offs made in establishing the original CDWGs, ClinGen has developed standard operating procedures for the development of CDWGs in new clinical domains, while maximizing efforts to scale up curation and facilitate involvement of external groups who wish to utilize ClinGen methods and infrastructure for expert curation.

The clinical imperative for inclusivity: Race, ethnicity, and ancestry (REA) in genomics.

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.

Evidence-based assessments of clinical actionability in the context of secondary findings: Updates from ClinGen's Actionability Working Group.

The use of genome-scale sequencing allows for identification of genetic findings beyond the original indication for testing (secondary findings). The ClinGen Actionability Working Group's (AWG) protocol for evidence synthesis and semi-quantitative metric scoring evaluates four domains of clinical actionability for potential secondary findings: severity and likelihood of the outcome, and effectiveness and nature of the intervention. As of February 2018, the AWG has scored 127 genes associated with 78 disorders (up-to-date topics/scores are available at www.clinicalgenome.org). Scores across these disorders were assessed to compare genes/disorders recommended for return as secondary findings by the American College of Medical Genetics and Genomics (ACMG) with those not currently recommended. Disorders recommended by the ACMG scored higher on outcome-related domains (severity and likelihood), but not on intervention-related domains (effectiveness and nature of the intervention). Current practices indicate that return of secondary findings will expand beyond those currently recommended by the ACMG. The ClinGen AWG evidence reports and summary scores are not intended as classifications of actionability, rather they provide a resource to aid decision makers as they determine best practices regarding secondary findings. The ClinGen AWG is working with the ACMG Secondary Findings Committee to update future iterations of their secondary findings list.

ClinGen Variant Curation Expert Panel experiences and standardized processes for disease and gene-level specification of the ACMG/AMP guidelines for sequence variant interpretation.

Genome-scale sequencing creates vast amounts of genomic data, increasing the challenge of clinical sequence variant interpretation. The demand for high-quality interpretation requires multiple specialties to join forces to accelerate the interpretation of sequence variant pathogenicity. With over 600 international members including clinicians, researchers, and laboratory diagnosticians, the Clinical Genome Resource (ClinGen), funded by the National Institutes of Health, is forming expert groups to systematically evaluate variants in clinically relevant genes. Here, we describe the first ClinGen variant curation expert panels (VCEPs), development of consistent and streamlined processes for establishing new VCEPs, and creation of standard operating procedures for VCEPs to define application of the ACMG/AMP guidelines for sequence variant interpretation in specific genes or diseases. Additionally, ClinGen has created user interfaces to enhance reliability of curation and a Sequence Variant Interpretation Working Group (SVI WG) to harmonize guideline specifications and ensure consistency between groups. The expansion of VCEPs represents the primary mechanism by which curation of a substantial fraction of genomic variants can be accelerated and ultimately undertaken systematically and comprehensively. We welcome groups to utilize our resources and become involved in our effort to create a publicly accessible, centralized resource for clinically relevant genes and variants.