Facilitating family communication of familial hypercholesterolemia genetic risk: Assessing engagement with innovative chatbot technology from the IMPACT-FH study.

Objective: To assess use of two web-based conversational agents, the Family Sharing Chatbot (FSC) and One Month Chatbot (OMC), by individuals with familial hypercholesterolemia (FH). Methods: FSC and OMC were sent using an opt-out methodology to a cohort of individuals receiving a FH genetic result. Data from 7/1/2021 through 5/12/2022 was obtained from the electronic health record and the chatbots' HIPAA-secure web portal. Results: Of 175 subjects, 21 (12%) opted out of the chatbots. Older individuals were more likely to opt out. Most (91/154, 59%) preferred receiving chatbots via the patient EHR portal. Seventy-five individuals (49%) clicked the FSC link, 62 (40%) interacted, and 36 (23%) shared a chatbot about their FH result with at least one relative. Ninety-two of the subjects received OMC, 22 (23%) clicked the link and 20 (21%) interacted. Individuals who shared were majority female and younger on average than the overall cohort. Reminders tended to increase engagement. Conclusion: Results demonstrate characteristics relevant to chatbot engagement. Individuals may be more inclined to receive chatbots if integrated within the patient EHR portal. Frequent reminders can potentially improve chatbot utilization. Innovation: FSC and OMC employ innovative digital health technology that can facilitate family communication about hereditary conditions.

Optimizing communication strategies and designing a comprehensive program to facilitate cascade testing for familial hypercholesterolemia.

BACKGROUND: This project aimed to optimize communication strategies to support family communication about familial hypercholesterolemia (FH) and improve cascade testing uptake among at-risk relatives. Individuals and families with FH provided feedback on multiple strategies including: a family letter, digital tools, and direct contact. METHODS: Feedback from participants was collected via dyadic interviews (n = 11) and surveys (n = 98) on communication strategies and their proposed implementation to improve cascade testing uptake. We conducted a thematic analysis to identify how to optimize each strategy. We categorized optimizations and their implementation within the project's healthcare system using a Traffic Light approach. RESULTS: Thematic analysis resulted in four distinct suggested optimizations for each communication strategy and seven suggested optimizations that were suitable across all strategies. Four suggestions for developing a comprehensive cascade testing program, which would offer all optimized communication strategies also emerged. All optimized suggestions coded green (n = 21) were incorporated. Suggestions coded yellow (n = 12) were partially incorporated. Only two suggestions were coded red and could not be incorporated. CONCLUSIONS: This project demonstrates how to collect and analyze stakeholder feedback for program design. We identified feasible suggested optimizations, resulting in communication strategies that are patient-informed and patient-centered. Optimized strategies were implemented in a comprehensive cascade testing program.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Implementing comprehensive pharmacogenomics in a community hospital-associated primary care setting.

BACKGROUND: Pharmacogenomics (PGx) is an emerging field. Many drug-gene interactions are known but not yet routinely addressed in clinical practice. Therefore, there is a significant gap in care, necessitating development of implementation strategies. OBJECTIVE: The objective of the study was to assess the impact of implementing a PGx practice model which incorporates comprehensive pharmacogenomic risk evaluation, testing and medication optimization administered by 7 PGx-certified ambulatory care pharmacists embedded across 30 primary care clinic sites. METHODS: Pharmacogenomic services were implemented in 30 primary care clinics within the Cincinnati, Ohio area. Patients are identified for pharmacogenomic testing using a clinical decision support tool (CDST) that is fully integrated in the electronic medical record (EMR) or by provider designation (e.g., psychotropic drug failure). Pharmacogenomic testing is performed via buccal swab using standardized clinic processes. Discrete data results are returned directly into the EMR/CDST for review by PGx-certified ambulatory care pharmacists. Recommendations and prescriptive changes are then discussed and implemented as a collaborative effort between pharmacist, primary care provider, specialists, and patient. RESULTS: A total of 422 unique interactions were assessed by the embedded ambulatory care PGx pharmacists (N = 7) during this interim analysis. About half (213) were pharmacogenomic interactions, and of these, 124 were actionable. When an intervention was actionable, 82% of the time a change in medication was recommended. The underlying reasons for recommending therapy alterations were most commonly ineffective therapy (43%), adverse drug reaction prevented (34%), or adverse drug reaction observed (13%). CONCLUSION: Variations in drug metabolism, response, and tolerability can negatively impact patient outcomes across many disease states and treatment specialties. Incorporation of pharmacogenomic testing with accessible clinical decision support into the team-based care model allows for a truly comprehensive review and optimization of medications. Our initial analysis suggests that comprehensive PGx testing should be considered to enhance medication safety and efficacy in at-risk patients.

Validation of Pharmacogenomic Interaction Probability (PIP) Scores in Predicting Drug-Gene, Drug-Drug-Gene, and Drug-Gene-Gene Interaction Risks in a Large Patient Population.

Utilizing pharmacogenomic (PGx) testing and integrating evidence-based guidance in drug therapy enables an improved treatment response and decreases the occurrence of adverse drug events. We conducted a retrospective analysis to validate the YouScript® PGx interaction probability (PIP) algorithm, which predicts patients for whom PGx testing would identify one or more evidence-based, actionable drug-gene, drug-drug-gene, or drug-gene-gene interactions (EADGIs). PIP scores generated for 36,511 patients were assessed according to the results of PGx multigene panel testing. PIP scores versus the proportion of patients in whom at least one EADGI was found were 22.4% vs. 22.4% (p = 1.000), 23.5% vs. 23.4% (p = 0.6895), 30.9% vs. 29.4% (p = 0.0667), and 27.3% vs. 26.4% (p = 0.3583) for patients tested with a minimum of 3-, 5-, 14-, and 25-gene panels, respectively. These data suggest a striking concordance between the PIP scores and the EAGDIs found by gene panel testing. The ability to identify patients most likely to benefit from PGx testing has the potential to reduce health care costs, enable patient access to personalized medicine, and ultimately improve drug efficacy and safety.

The Impact of Proband Indication for Genetic Testing on the Uptake of Cascade Testing Among Relatives.

Although multiple factors can influence the uptake of cascade genetic testing, the impact of proband indication has not been studied. We performed a retrospective, cross-sectional study comparing cascade genetic testing rates among relatives of probands who received either diagnostic germline testing or non-indication-based proactive screening via next-generation sequencing (NGS)-based multigene panels for hereditary cancer syndromes (HCS) and/or familial hypercholesterolemia (FH). The proportion of probands with a medically actionable (positive) finding were calculated based on genes associated with Centers for Disease Control and Prevention (CDC) Tier 1 conditions, HCS genes, and FH genes. Among probands with a positive finding, cascade testing rates and influencing factors were assessed. A total of 270,715 probands were eligible for inclusion in the study (diagnostic n = 254,281,93.9%; proactive n = 16,434, 6.1%). A positive result in a gene associated with a CDC Tier 1 condition was identified in 10,520 diagnostic probands (4.1%) and 337 proactive probands (2.1%), leading to cascade testing among families of 3,305 diagnostic probands (31.4%) and 36 proactive probands (10.7%) (p < 0.0001). A positive result in an HCS gene was returned to 23,272 diagnostic probands (9.4%) and 970 proactive probands (6.1%), leading to cascade testing among families of 6,611 diagnostic probands (28.4%) and 89 proactive probands (9.2%) (p < 0.0001). Cascade testing due to a positive result in an HCS gene was more commonly pursued when the diagnostic proband was White, had a finding in a gene associated with a CDC Tier 1 condition, or had a personal history of cancer, or when the proactive proband was female. A positive result in an FH gene was returned to 1,647 diagnostic probands (25.3%) and 67 proactive probands (0.62%), leading to cascade testing among families of 360 diagnostic probands (21.9%) and 4 proactive probands (6.0%) (p < 0.01). Consistently higher rates of cascade testing among families of diagnostic probands may be due to a perceived urgency because of personal or family history of disease. Due to the proven clinical benefit of cascade testing, further research on obstacles to systematic implementation and uptake of testing for relatives of any proband with a medically actionable variant is warranted.

Use of a chatbot to increase uptake of cascade genetic testing.

Successful proband-mediated family communication and subsequent cascade genetic testing uptake requires interventions that present information clearly, in sufficient detail, and with medical authority. To facilitate family communication for patients receiving clinically actionable results via the MyCode® Community Health Initiative, a Family Sharing Tool (FST) and a cascade chatbot were developed. FST is an electronic mechanism allowing patients to share genetic test results with relatives via chatbot. The cascade chatbot describes the proband's result, associated disease risks, and recommended management and captures whether the user is a blood relative or caregiver, sex, and relationship to the proband. FST and cascade chatbot uptake among MyCode® probands and relatives was tracked from August 2018 through February 2020. Cascade genetic testing uptake was collected from testing laboratories as number of cascades per proband. Fifty-eight percent (316/543) of probands consented to FST; 42% (227/543) declined. Receipt preferences were patient electronic health record (EHR) portal (52%), email (29%), and text (19%). Patient EHR portal users (p < 0.001) and younger patients were more likely to consent (p < 0.001). FST was deployed to 308 probands. Fifty-nine percent (183/308) opened; of those, 56% (102/183) used FST to send a cascade chatbot to relatives. These 102 probands shared a cascade chatbot with 377 relatives. Sixty-two percent (235/377) of relatives opened; of these, 69% (161/235) started, and of these, 57% (92/161) completed the cascade chatbot. Cascade genetic testing uptake was significantly greater among relatives of probands who consented to the FST (M = 2.34 cascades, SD = 2.10) than relatives of probands who declined (M = 1.40 cascades, SD = 0.82, p < 0.001). Proband age was not a significant predictor of cascade genetic testing uptake. Further work is needed to better understand factors impacting proband use of FST and relative use of cascade chatbots.

Developing and Optimizing Innovative Tools to Address Familial Hypercholesterolemia Underdiagnosis: Identification Methods, Patient Activation, and Cascade Testing for Familial Hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is the most common cardiovascular genetic disorder and, if left untreated, is associated with increased risk of premature atherosclerotic cardiovascular disease, the leading cause of preventable death in the United States. Although FH is common, fatal, and treatable, it is underdiagnosed and undertreated due to a lack of systematic methods to identify individuals with FH and limited uptake of cascade testing. METHODS AND RESULTS: This mixed-method, multi-stage study will optimize, test, and implement innovative approaches for both FH identification and cascade testing in 3 aims. To improve identification of individuals with FH, in Aim 1, we will compare and refine automated phenotype-based and genomic approaches to identify individuals likely to have FH. To improve cascade testing uptake for at-risk individuals, in Aim 2, we will use a patient-centered design thinking process to optimize and develop novel, active family communication methods. Using a prospective, observational pragmatic trial, we will assess uptake and effectiveness of each family communication method on cascade testing. Guided by an implementation science framework, in Aim 3, we will develop a comprehensive guide to identify individuals with FH. Using the Conceptual Model for Implementation Research, we will evaluate implementation outcomes including feasibility, acceptability, and perceived sustainability as well as health outcomes related to the optimized methods and tools developed in Aims 1 and 2. CONCLUSIONS: Data generated from this study will address barriers and gaps in care related to underdiagnosis of FH by developing and optimizing tools to improve FH identification and cascade testing.

Testing a best practices risk result format to communicate genetic risks.

OBJECTIVE: To investigate the effect of a genetic report format using risk communication "best-practices" on risk perceptions, in part to reduce risk overestimates. METHODS: Adults (N = 470) from the Coriell Personalized Medicine Collaborative (CPMC) were randomized to a 2 × 2 experimental design to receive a hypothetical "personalized" genetic risk result for leukemia (relative risk = 1.5 or 2.5) through either the standard CPMC report (N = 232) or an enriched report informed by best practices (N = 238). A one-time, online survey assessed numeracy and risk perceptions including "feelings of risk" and a numerical estimate. RESULTS: Regardless of numeracy, participants who received the enriched report had fewer overestimates of their lifetime risk estimate (LRE; odds ratio = 0.19, p < .001) and lower feelings of risk on two of three measures (p < .001). Participants with higher numeracy scores had fewer overestimates of LRE (OR = 0.66, p < .001) and lower feelings of risk on two out of three measures (p ≤ .01); the interaction between numeracy and report format was non-significant. CONCLUSION: The enriched report produced more accurate LRE and lower risk perceptions regardless of numeracy level, suggesting the enriched format was helpful to individuals irrespective of numeracy ability. PRACTICE IMPLICATIONS: Best practice elements in risk reports may help individuals form more accurate risk perceptions.

Clinical outcomes of a genomic screening program for actionable genetic conditions.

PURPOSE: Three genetic conditions-hereditary breast and ovarian cancer syndrome, Lynch syndrome, and familial hypercholesterolemia-have tier 1 evidence for interventions that reduce morbidity and mortality, prompting proposals to screen unselected populations for these conditions. We examined the impact of genomic screening on risk management and early detection in an unselected population. METHODS: Observational study of electronic health records (EHR) among individuals in whom a pathogenic/likely pathogenic variant in a tier 1 gene was discovered through Geisinger's MyCode project. EHR of all eligible participants was evaluated for a prior genetic diagnosis and, among participants without such a diagnosis, relevant personal/family history, postdisclosure clinical diagnoses, and postdisclosure risk management. RESULTS: Eighty-seven percent of participants (305/351) did not have a prior genetic diagnosis of their tier 1 result. Of these, 65% had EHR evidence of relevant personal and/or family history of disease. Of 255 individuals eligible to have risk management, 70% (n = 179) had a recommended risk management procedure after results disclosure. Thirteen percent of participants (41/305) received a relevant clinical diagnosis after results disclosure. CONCLUSION: Genomic screening programs can identify previously unrecognized individuals at increased risk of cancer and heart disease and facilitate risk management and early cancer detection.

PARC report: a perspective on the state of clinical pharmacogenomics testing.

In this Perspective, the authors discuss the state of pharmacogenomics testing addressing a number of advances, challenges and barriers, including legal ramifications, changes to the regulatory landscape, coverage of testing and the implications of direct-to-consumer genetic testing on the provision of care to patients. Patient attitudes toward pharmacogenomics testing and associated costs will play an increasingly important role in test acquisition and subsequent utilization in a clinical setting. Additional key steps needed include: further research trials demonstrating clinical utility and cost-effectiveness of pharmacogenetic testing, evidence review to better integrate genomic information into clinical practice guidelines in target therapeutic areas to help providers identify patients that may benefit from pharmacogenetic testing and engagement with payers to create a path to reimbursement for pharmacogenetic tests that currently have sufficient evidence of clinical utility. Increased adoption of testing by payers and improved reimbursement practices will be needed to overcome barriers, especially as the healthcare landscape continues to shift toward a system of value-based care.

Positive impact of genetic counseling assistants on genetic counseling efficiency, patient volume, and cost in a cancer genetics clinic.

PURPOSE: Cancer genetics clinics have seen increasing demand, challenging genetic counselors (GCs) to increase efficiency and prompting some clinics to implement genetic counseling assistants (GCAs). To evaluate the impact of GCAs on Geisinger's cancer genetics clinic, we tracked GC time utilization, new patient volume, and clinic cost per patient before and after implementing a GCA program. METHODS: GCs used time-tracking software while completing preappointment activities. Electronic health records were reviewed for appointment length and number of patients per week. Internal salary data for GCs and GCAs were used to calculate clinic costs per patient. RESULTS: Time spent by GCs completing each preappointment activity (21.8 vs. 15.1 minutes) and appointment length (51.6 vs. 44.5 minutes) significantly decreased after GCA program implementation (p values < 0.001). New patients per week per GC significantly increased (7.9 vs. 11.4, p < 0.001). Weekly clinic cost per patient significantly decreased ($233 vs. $176, p = 0.03). CONCLUSION: Implementing a GCA program increased GC efficiency in preappointment activities and clinic appointments, increased patient volume, and decreased clinic cost per patient. Such a program can improve access to GC services and assist GCs in focusing on the direct patient care for which they are specially trained.

Pharmacogenomic (PGx) Counseling: Exploring Participant Questions about PGx Test Results.

As pharmacogenomic (PGx) use in healthcare increases, a better understanding of patient needs will be necessary to guide PGx result delivery. The Coriell Personalized Medicine Collaborative (CPMC) is a prospective study investigating the utility of personalized medicine. Participants received online genetic risk reports for 27 potentially actionable complex diseases and 7 drug-gene pairs and could request free, telephone-based genetic counseling (GC). To explore the needs of individuals receiving PGx results, we conducted a retrospective qualitative review of inquiries from CPMC participants who requested counseling from March 2009 to February 2017. Eighty out of 690 (12%) total GC inquiries were focused on the discussion of PGx results, and six salient themes emerged: "general help", "issues with drugs", "relevant disease experience", "what do I do now?", "sharing results", and "other drugs". The number of reported medications with a corresponding PGx result and participant engagement were significantly associated with PGx GC requests (p < 0.01 and p < 0.02, respectively). Our work illustrates a range of questions raised by study participants receiving PGx test results, most of which were addressed by a genetic counselor with few requiring referrals to prescribing providers or pharmacists. These results further support a role for genetic counselors in the team-based approach to optimal PGx result delivery.

Patient assessment of chatbots for the scalable delivery of genetic counseling.

A barrier to incorporating genomics more broadly is limited access to providers with genomics expertise. Chatbots are a technology-based simulated conversation used in scaling communications. Geisinger and Clear Genetics, Inc. have developed chatbots to facilitate communication with participants receiving clinically actionable genetic variants from the MyCode® Community Health Initiative (MyCode® ). The consent chatbot walks patients through the consent allowing them to opt to receive more or less detail on key topics (goals, benefits, risks, etc.). The follow-up chatbot reminds participants of suggested actions following result receipt and the cascade chatbot can be sent to at-risk relatives by participants to share their genetic test results and facilitate cascade testing. To explore the acceptability, usability, and understanding of the study consent, post-result follow-up and cascade testing chatbots, we conducted six focus groups with MyCode® participants. Sixty-two individuals participated in a focus group (n = 33 consent chatbot, n = 29 follow-up and cascade chatbot). Participants were mostly female (n = 42, 68%), Caucasian (n = 58, 94%), college-educated (n = 33,53%), retirees (n = 38, 61%), and of age 56 years or older (n = 52, 84%). Few participants reported that they knew what a chatbot was (n = 10, 16%), and a small number reported that they had used a chatbot (n = 5, 8%). Qualitative analysis of transcripts and notes from focus groups revealed four main themes: (a) overall impressions, (b) suggested improvements, (c) concerns and limitations, and (d) implementation. Participants supported using chatbots to consent for genomics research and to interact with healthcare providers for care coordination following receipt of genomic results. Most expressed willingness to use a chatbot to share genetic information with relatives. The consent chatbot presents an engaging alternative to deliver content challenging to comprehend in traditional paper or in-person consent. The cascade and follow-up chatbots may be acceptable, user-friendly, scalable approaches to manage ancillary genetic counseling tasks.

Generation and Implementation of a Patient-Centered and Patient-Facing Genomic Test Report in the EHR.

CONTEXT: Communication of genetic laboratory results to patients and providers is impeded by the complexity of results and reports. This can lead to misinterpretation of results, causing inappropriate care. Patients often do not receive a copy of the report leading to possible miscommunication. To address these problems, we conducted patient-centered research to inform design of interpretive reports. Here we describe the development and deployment of a specific patient-centered clinical decision support (CDS) tool, a multi-use patient-centered genomic test report (PGR) that interfaces with an electronic health record (EHR). IMPLEMENTATION PROCESS: A PGR with a companion provider report was configured for implementation within the EHR using locally developed software (COMPASS™) to manage secure data exchange and access. FINDINGS: We conducted semi-structured interviews with patients, family members, and clinicians that showed they sought clear information addressing findings, family implications, resources, prognosis and next steps relative to the genomic result. Providers requested access to applicable, available clinical guidelines. Initial results indicated patients and providers found the PGR contained helpful, valuable information and would provide a basis for result-related conversation between patients, providers and family. MAJOR THEMES: Direct patient involvement in the design and development of a PGR identified format and presentation preferences, and delivery of relevant information to patients and providers, prompting the creation of a CDS tool. CONCLUSIONS: Research and development of patient-centered CDS tools designed to support improved patient outcomes, are enhanced by early and substantial engagement of patients in contributing to all phases of tool design and development.

Early Outcome Data Assessing Utility of a Post-Test Genomic Counseling Framework for the Scalable Delivery of Precision Health.

Information on patients' preferences is essential to guide the development of more efficient genomic counseling service delivery models. We examined patient preferences in the context of use of a post-test genomic counseling framework on patients (n = 44) with chronic disease receiving online test reports for eight different diseases and one drug-response result. We also explored patients' disease risk awareness, recall of test report information, and confidence in knowing what to do with their test results. Prior to the post-test genomic counseling session, all participants viewed at least one test report; 81.6% of available test reports were reviewed in total. Participants requested more phone (36) than in-person counseling sessions (8), and phone sessions were shorter (mean 29.1 min; range 12⁻75 min) than in-person sessions (mean 52.8 min; range 23⁻85 min). A total of 182 test reports were discussed over the course of 44 counseling sessions (mean 4.13, range 1⁻9). Thirty-six (81.8%) participants requested assessment for additional medical/family history concerns. In exploring patient experiences of disease risk awareness and recall, no significant differences were identified in comparison to those of participants (n = 199) that had received in-person post-test genomic counseling in a parent study randomized controlled trial (RCT). In summary, a novel post-test genomic counseling framework allowed for a tailored approach to counseling based on the participants' predetermined choices.

Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

Precision Military Medicine: Conducting a multi-site clinical utility study of genomic and lifestyle risk factors in the United States Air Force.

Following several years enrolling disease-specific and otherwise healthy cohorts into the Coriell Personalized Medicine Collaborative, a prospective study aimed at evaluating the clinical utility of personal genomic information for common complex disease and pharmacogenomics, the Coriell Personalized Medicine Collaborative expanded to create a military cohort, specifically, the United States Air Force. Initial recruitment focused on Air Force Medical Service personnel and later expanded to include all Active Duty Air Force members and beneficiaries. Now in its 6th year, the study has produced a wide variety of insights, including optimal study design for military-sponsored genomic research, and discussion on genetic information sharing between and amongst Air Force study participants, civilian and military researchers, and the United States Department of Defense. Over the longer term, analyses will further contribute to the development of policies and processes relevant to clinical decision support and data sharing within the US military, and on-going work with the Air Force Medical Service sub-cohort will generate critical insights into how best to deploy useful genomic information in clinical care. Here we discuss challenges faced and critical success factors for military-civilian collaborations around genomic research.

Outcomes of a Randomized Controlled Trial of Genomic Counseling for Patients Receiving Personalized and Actionable Complex Disease Reports.

There has been very limited study of patients with chronic disease receiving potentially actionable genomic based results or the utilization of genetic counselors in the online result delivery process. We conducted a randomized controlled trial on 199 patients with chronic disease each receiving eight personalized and actionable complex disease reports online. Primary study aims were to assess the impact of in-person genomic counseling on 1) causal attribution of disease risk, 2) personal awareness of disease risk, and 3) perceived risk of developing a particular disease. Of 98 intervention arm participants (mean age = 57.8; 39% female) randomized for in-person genomic counseling, 76 (78%) were seen. In contrast, control arm participants (n = 101; mean age = 58.5; 54% female) were initially not offered genomic counseling as part of the study protocol but were able to access in-person genomic counseling, if they requested it, 3-months post viewing of at least one test report and post-completion of the study-specific follow-up survey. A total of 64 intervention arm and 59 control arm participants completed follow-up survey measures. We found that participants receiving in-person genomic counseling had enhanced objective understanding of the genetic variant risk contribution for multiple complex diseases. Genomic counseling was associated with lowered participant causal beliefs in genetic influence across all eight diseases, compared to control participants. Our findings also illustrate that for the majority of diseases under study, intervention arm participants believed they knew their genetic risk status better than control arm subjects. Disease risk was modified for the majority during genomic counseling, due to the assessment of more comprehensive family history. In conclusion, for patients receiving personalized and actionable genomic results through a web portal, genomic counseling enhanced their objective understanding of the genetic variant risk contribution to multiple common diseases. These results support the development of additional genomic counseling interventions to ensure a high level of patient comprehension and improve patient-centered health outcomes.

CYP2D6 Genetic Variation and Beta-Blocker Maintenance Dose in Patients with Heart Failure.

PURPOSE: This study examined whether a CYP2D6 polymorphism (CYP2D6*4) was related to beta-blocker maintenance dose in patients with heart failure. METHODS: Logistic regression modeling was utilized in a retrospective chart-review analysis of heart-failure patients (60% Male, 90% of European descent) to assess whether CYP2D6*4 (non-functional CYP2D6 allele present in 1 of 5 individuals of European descent) is associated with maintenance dose of carvedilol (n = 65) or metoprolol (n = 33). RESULTS: CYP2D6*4 was associated with lower maintenance dose of metoprolol (OR 0.13 [95% CI 0.02-0.75] p = 0.023), and a trend was observed between CYP2D6*4 and higher maintenance dose of carvedilol (OR 2.94 [95% CI 0.84-10.30] p = 0.093). None of the patients that carried CYP2D6*4 achieved the recommended target dose of metoprolol (200 mg/day). CONCLUSION: Consistent with the role of CYP2D6 in the metabolism of metoprolol, the tolerated maintenance dose of metoprolol was lower in CYP2D6*4 carriers compared to non-carriers. Consistent with the role of CYP2D6 in activation of carvedilol, tolerated maintenance dose of carvedilol was higher in CYP2D6*4 carriers compared to non-carriers. Further investigation is warranted to ascertain the potential of CYP2D6 as a potential predictive biomarker of beta-blocker maintenance dose in heart failure patients.