We examined the Institutional Review Board (IRB) process at 9 academic institutions in the electronic Medical Records and Genomics (eMERGE) Network, for proposed electronic health record-based genomic medicine studies, to identify common questions and concerns. Sequencing of 109 disease related genes and genotyping of 14 actionable variants is being performed in ~28,100 participants from the 9 sites. Pathogenic/likely pathogenic variants in actionable genes are being returned to study participants. We examined each site’s research protocols, informed-consent materials, and interactions with IRB staff. Research staff at each site completed questionnaires regarding their IRB interactions. The time to prepare protocols for IRB submission, number of revisions and time to approval ranged from 10–261 days, 0–11, and 11–90 days, respectively. IRB recommendations related to the readability of informed consent materials, specifying the full range of potential risks, providing options for receiving limited results or withdrawal, sharing of information with family members, and establishing the mechanisms to answer participant questions. IRBs reviewing studies that involve the return of results from genomic sequencing have a diverse array of concerns, and anticipating these concerns can help investigators to more effectively engage IRBs.

Health benefits to relatives of people at known genetic risk for hereditary cancer syndromes is key to realizing the promise of precision medicine. We conducted a qualitative study to design a patient- and family-centered program for direct contact of relatives to recommend cascade genetic testing. We conducted two rounds of data collection using focus groups followed by individual interviews with patients with HBOC or Lynch syndrome and a separate sample of people with a family history of hereditary cancers. Results indicate that U.S.-based health system-led direct contact of relatives is acceptable to patients and families, should take a programmatic approach, include consent of relatives before proband testing, complement to existing patient-mediated disclosure, and allow for relative control of information. Our findings suggest a set of requirements for U.S.-based direct contact programs that could ultimately benefit more relatives than current approaches.

Background: O’Donnell-Luria-Rodan syndrome (ODLURO) is an autosomal-dominant neurodevelopmental disorder caused by pathogenic, mostly truncating variants in KMT2E. It was first described by O’Donnell-Luria et al in 2019 in a cohort of 38 patients. Clinical features encompass macrocephaly, mild intellectual disability (ID), autism spectrum disorder (ASD) susceptibility and seizure susceptibility. Methods: Affected individuals were ascertained at paediatric and genetic centres in various countries by diagnostic chromosome microarray or exome/genome sequencing. Patients were collected into a case cohort and were systematically phenotyped where possible. Results: We report 18 additional patients from 17 families with genetically confirmed ODLURO. We identified 15 different heterozygous likely pathogenic or pathogenic sequence variants (14 novel) and two partial microdeletions of KMT2E. We confirm and refine the phenotypic spectrum of the KMT2E-related neurodevelopmental disorder, especially concerning cognitive development, with rather mild ID and macrocephaly with subtle facial features in most patients. We observe a high prevalence of ASD in our cohort (41%), while seizures are present in only two patients. We extend the phenotypic spectrum by sleep disturbances. Conclusion: Our study, bringing the total of known patients with ODLURO to more than 60 within 2 years of the first publication, suggests an unexpectedly high relative frequency of this syndrome worldwide. It seems likely that ODLURO, although just recently described, is among the more common single-gene aetiologies of neurodevelopmental delay and ASD. We present the second systematic case series of patients with ODLURO, further refining the mutational and phenotypic spectrum of this not-so-rare syndrome.

Background: In an effort to return actionable results from variant data to electronic health records (EHRs), participants in the Electronic Medical Records and Genomics (eMERGE) Network are being sequenced with the targeted Pharmacogenomics Research Network sequence platform (PGRNseq). This cost-effective, highly-scalable, and highly-accurate platform was created to explore rare variation in 84 key pharmacogenetic genes with strong drug phenotype associations. Methods: To return Clinical Laboratory Improvement Amendments (CLIA) results to our participants at the Group Health Cooperative, we sequenced the DNA of 900 participants (61 % female) with non-CLIA biobanked samples. We then selected 450 of those to be re-consented, to redraw blood, and ultimately to validate CLIA variants in anticipation of returning the results to the participant and EHR. These 450 were selected using an algorithm we designed to harness data from self-reported race, diagnosis and procedure codes, medical notes, laboratory results, and variant-level bioinformatics to ensure selection of an informative sample. We annotated the multi-sample variant call format by a combination of SeattleSeq and SnpEff tools, with additional custom variables including evidence from ClinVar, OMIM, HGMD, and prior clinical associations. Results: We focused our analyses on 27 actionable genes, largely driven by the Clinical Pharmacogenetics Implementation Consortium. We derived a ranking system based on the total number of coding variants per participant (75.2±14.7), and the number of coding variants with high or moderate impact (11.5±3.9). Notably, we identified 11 stop-gained (1 %) and 519 missense (20 %) variants out of a total of 1785 in these 27 genes. Finally, we prioritized variants to be returned to the EHR with prior clinical evidence of pathogenicity or annotated as stop-gain for the following genes: CACNA1S and RYR1 (malignant hyperthermia); SCN5A, KCNH2, and RYR2 (arrhythmia); and LDLR (high cholesterol). Conclusions: The incorporation of genetics into the EHR for clinical decision support is a complex undertaking for many reasons including lack of prior consent for return of results, lack of biospecimens collected in a CLIA environment, and EHR integration. Our study design accounts for these hurdles and is an example of a pilot system that can be utilized before expanding to an entire health system.