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Background Clinical phenotype information greatly facilitates genetic diagnostic interpretations pipelines in disease. While post-hoc extraction using natural language processing on unstructured clinical notes continues to improve, there is a need to improve point-of-care collection of patient phenotypes. Therefore, we developed “PheNominal”, a point-of-care web application, embedded within Epic electronic health record (EHR) workflows, to permit capture of standardized phenotype data. Methods Using bi-directional web services available within commercial EHRs, we developed a lightweight web application that allows users to rapidly browse and identify relevant terms from the Human Phenotype Ontology (HPO). Selected terms are saved discretely within the patient’s EHR, permitting reuse both in clinical notes as well as in downstream diagnostic and research pipelines. Results In the 16 months since implementation, PheNominal was used to capture discrete phenotype data for over 1500 individuals and 11,000 HPO terms during clinic and inpatient encounters for a genetic diagnostic consultation service within a quaternary-care pediatric academic medical center. An average of 7 HPO terms were captured per patient. Compared to a manual workflow, the average time to enter terms for a patient was reduced from 15 to 5 min per patient, and there were fewer annotation errors. Conclusions Modern EHRs support integration of external applications using application programming interfaces. We describe a practical application of these interfaces to facilitate deep phenotype capture in a discrete, structured format within a busy clinical workflow. Future versions will include a vendor-agnostic implementation using FHIR. We describe pilot efforts to integrate structured phenotyping through controlled dictionaries into diagnostic and research pipelines, reducing manual effort for phenotype documentation and reducing errors in data entry.

Contains fulltext : 243959.pdf (Publisher’s version ) (Closed access) PURPOSE: The ClinGen Variant Curation Expert Panels (VCEPs) provide disease-specific rules for accurate variant interpretation. Using the hearing loss-specific American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines, the Hearing Loss VCEP (HL VCEP) illustrates the utility of expert specifications in variant interpretation. METHODS: A total of 157 variants across nine HL genes, previously submitted to ClinVar, were curated by the HL VCEP. The curation process involved collecting published and unpublished data for each variant by biocurators, followed by bimonthly meetings of an expert curation subgroup that reviewed all evidence and applied the HL-specific ACMG/AMP guidelines to reach a final classification. RESULTS: Before expert curation, 75% (117/157) of variants had single or multiple variants of uncertain significance (VUS) submissions (17/157) or had conflicting interpretations in ClinVar (100/157). After applying the HL-specific ACMG/AMP guidelines, 24% (4/17) of VUS and 69% (69/100) of discordant variants were resolved into benign (B), likely benign (LB), likely pathogenic (LP), or pathogenic (P). Overall, 70% (109/157) variants had unambiguous classifications (B, LB, LP, P). We quantify the contribution of the HL-specified ACMG/AMP codes to variant classification. CONCLUSION: Expert specification and application of the HL-specific ACMG/AMP guidelines effectively resolved discordant interpretations in ClinVar. This study highlights the utility of ClinGen VCEPs in supporting more consistent clinical variant interpretation.

While newborns and children with hearing loss are routinely offered genetic testing, adults are rarely clinically tested for a genetic etiology. One clinically actionable result from genetic testing in children is the discovery of variants in syndromic hearing loss genes. EYA4 is a known hearing loss gene which is also involved in important pathways in cardiac tissue. The pleiotropic effects of rare EYA4 variants are poorly understood and their prevalence in a large cohort has not been previously reported. We investigated cardio-auditory phenotypes in 11,451 individuals in a large biobank using a rare variant, genome-first approach to EYA4. We filtered 256 EYA4 variants carried by 6737 participants to 26 rare and predicted deleterious variants carried by 42 heterozygotes. We aggregated predicted deleterious EYA4 gene variants into a combined variable (i.e. "gene burden") and performed association studies across phenotypes compared to wildtype controls. We validated findings with replication in three independent cohorts and human tissue expression data. EYA4 gene burden was significantly associated with audiometric-proven HL (p = [Formula: see text], Mobitz Type II AV block (p = [Formula: see text]) and the syndromic presentation of HL and primary cardiomyopathy (p = 0.0194). Analyses on audiogram, echocardiogram, and electrocardiogram data validated these associations. Prior reports have focused on identifying variants in families with severe or syndromic phenotypes. In contrast, we found, using a genotype-first approach, that gene burden in EYA4 is associated with more subtle cardio-auditory phenotypes in an adult medical biobank population, including cardiac conduction disorders which have not been previously reported. We show the value of using a focused approach to uncover human disease related to pleiotropic gene variants and suggest a role for genetic testing in adults presenting with hearing loss.

In the published version of this article, the name of the 18th author was misspelled as Minjie Lou. The correct name is Minjie Luo. The authors regret the error.

As more research studies incorporate next-generation sequencing (including whole-genome or whole-exome sequencing), investigators and institutional review boards face difficult questions regarding which genomic results to return to research participants and how. An American College of Medical Genetics and Genomics 2013 policy paper suggesting that pathogenic mutations in 56 specified genes should be returned in the clinical setting has raised the question of whether comparable recommendations should be considered in research settings. The Clinical Sequencing Exploratory Research (CSER) Consortium and the Electronic Medical Records and Genomics (eMERGE) Network are multisite research programs that aim to develop practical strategies for addressing questions concerning the return of results in genomic research. CSER and eMERGE committees have identified areas of consensus regarding the return of genomic results to research participants. In most circumstances, if results meet an actionability threshold for return and the research participant has consented to return, genomic results, along with referral for appropriate clinical follow-up, should be offered to participants. However, participants have a right to decline the receipt of genomic results, even when doing so might be viewed as a threat to the participants’ health. Research investigators should be prepared to return research results and incidental findings discovered in the course of their research and meeting an actionability threshold, but they have no ethical obligation to actively search for such results. These positions are consistent with the recognition that clinical research is distinct from medical care in both its aims and its guiding moral principles.