Bland, Harris T.

Abstract Objectives To implementation an automated multi-institutional pipeline that delivers breast-cancer risk integrated with polygenic risk scores, monogenic variants, family history, and clinical factors, emphasizing operational challenges and their solutions. Materials and Methods A five-stage process was executed at ten sites. Data streams from REDCap surveys, PRS and monogenic reports, and MeTree pedigrees were normalized and forwarded through a REDCap plug-in to the CanRisk API. Results Integrated risk was returned to >10 000 women; 3.6% were ≥25 % lifetime risk and 0.9% carried pathogenic variants. Pipeline generated score aligns well with manual generated ones. Major barriers such as heterogeneous pedigree formats, missing data, edge-case handling, and evolving model versions were identified and resolved through mapping rules, imputations, and iterative testing. Discussion Cross-platform data harmonization and stakeholder alignment were decisive for success. Borderline-risk communication and model-version drift remain open issues. Conclusion Large-scale PRS-integrated breast-cancer risk reporting is feasible but requires robust interoperability standards and iterative governance.

Background: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. Methods: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record–derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. Results: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. Conclusions: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier; NCT03394859.

Background: Return of incidental genetic findings is recommended for pathogenic/likely pathogenic (P/LP) variants in Mendelian arrhythmia genes. The extent to which these variants are associated with arrhythmia phenotypes in unselected populations is unknown. Objective: Assess the impact of return of results (RoR) of P/LP variants in 4 arrhythmia genes in research participants not selected for cardiovascular disease. Methods: The cohort included 24,410 participants from the Electronic Medical Records and Genomics Network. Rare variants (minor allele frequency <1%) in KCNE1 , KCNH2 , KCNQ1 , and SCN5A were identified and classified according to ACMG guidelines. Arrhythmia phenotypes extracted from electronic health records (EHRs) included atrial fibrillation/flutter (AF/AFL), conduction system disease, long QT syndrome (LQTS), ventricular tachycardia/fibrillation (VT/VF), and premature ventricular contractions (PVCs). P/LP carriers’ phenotypes were compared to non-carriers using logistic regression adjusted for demographic covariates and site. Participants with P/LP variants were informed of their results and the impact of this RoR was assessed after 1 year of follow-up clinical care. Results: The participants included 53.7% females and 72.5% white individuals, with a median age of 57 years. 71 participants had a heterozygous P/LP variant in one of the 4 genes. LQTS diagnoses were associated with P/LP carrier status for all 4 genes ( KCNE1 OR 22.8, p=1.0e-4; KCNH2 OR 35.1, p=1.8e-7; KCNQ1 OR 27.3, p=3.6e-18; SCN5A OR 5.6, p=0.02). Carriers of SCN5A P/LP variants were also more likely to have PVCs (OR 4.3, p=0.003). Sensitivity analyses showed the associations predated the RoR. EHRs included a diagnosis of LQTS or Brugada Syndrome in 11/71 (16%) pre-RoR, and 16 more were diagnosed after RoR (27/71, 38%). A total of 47/71 (66%) participants had a documented arrhythmia phenotype 1 year after RoR, although 20 of these participants were not diagnosed with an inherited arrhythmia syndrome. Conclusion: Inherited arrhythmia diagnoses could be established in nearly half of participants with P/LP variants. These data indicate that return of incidental P/LP variants in these genes may facilitate the early diagnosis of arrhythmias.

AbstractPopulation‐based genomic screening has the potential to improve health outcomes by identifying genetic causes of disease before they occur. While much attention has been paid to supporting the needs of the small percentage of patients who will receive a life‐altering positive genomic screening result that requires medical attention, little attention has been given to the communication of negative screening results. As there are currently no best practices for returning negative genomic screening results, we drew on experiences across the electronic medical records and genomics (eMERGE) III Network to highlight the diversity of reporting methods employed, challenges encountered in reporting negative test results, and “lessons learned” across institutions. A 60‐item survey that consisted of both multiple choice and open‐ended questions was created to gather data across institutions. Even though institutions independently developed procedures for reporting negative results, and had very different study populations, we identified several similarities of approach, including but not limited to: returning results by mail, placing results in the electronic health record via an automated process, reporting results to participants' primary care provider, and providing genetic counseling to interested patients at no cost. Differences in procedures for reporting negative results included: differences in terminology used to describe negative results, definitions of negative results, guidance regarding the meaning of negative results for participants and their family members, and recommendations for clinical follow up. Our findings highlight emerging practices for reporting negative genomic screening results and highlight the need to create patient education and clinical support tools for reporting negative screening results.

A challenge in returning genomic test results to research participants is how best to communicate complex and clinically nuanced findings to participants in a manner that is scalable to the large numbers of participants enrolled. The purpose of this study was to examine the features of genetic results letters produced at each Electronic Medical Records and Genomics (eMERGE3) Network site to assess their readability and content. Letters were collected from each site, and a qualitative analysis of letter content and a quantitative analysis of readability statistics were performed. Because letters were produced independently at each eMERGE site, significant heterogeneity in readability and content was found. The content of letters varied widely from a baseline of notifying participants that results existed to more detailed information about positive or negative results, as well as materials for sharing with family members. Most letters were significantly above the Centers for Disease Control-suggested reading level for health communication. While continued effort should be applied to make letters easier to understand, the ongoing challenge of explaining complex genomic information, the implications of negative test results, and the uncertainty that comes with some types of test and result makes simplifying letter text challenging.

A goal of the 3rd phase of the Electronic Medical Records and Genomics (eMERGE3) Network was to examine the return of results (RoR) of actionable variants in more than 100 genes to consenting participants and their healthcare providers. Each of the 10 eMERGE sites developed plans for three essential elements of the RoR process: Disclosure to the participant, notification of the health care provider, and integration of results into the electronic health record (EHR). Procedures and protocols around these three elements were adapted as appropriate to individual site requirements and limitations. Detailed information about the RoR procedures at each site was obtained through structured telephone interviews and follow-up surveys with the clinical investigator leading or participating in the RoR process at each eMERGE3 institution. Because RoR processes at each of the 10 sites allowed for taking into account differences in population, disease focus and institutional requirements, significant heterogeneity of process was identified, including variability in the order in which patients and clinicians were notified and results were placed in the EHR. This heterogeneity in the process flow for eMERGE3 RoR reflects the “real world” of genomic medicine in which RoR procedures must be shaped by the needs of the patients and institutional environments.

Background: Coronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown. Methods: We performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus. Results: The meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35–1.86; P =2.6×10 − 10 ). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14–2.57; P =0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17–2.24; P =0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18–4.75; P =0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes. Conclusions: Genetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.