Postmortem toxicology findings from the Camden Opioid Research Initiative.

The United States continues to be impacted by decades of an opioid misuse epidemic, worsened by the COVID-19 pandemic and by the growing prevalence of highly potent synthetic opioids (HPSO) such as fentanyl. In instances of a toxicity event, first-response administration of reversal medications such as naloxone can be insufficient to fully counteract the effects of HPSO, particularly when there is co-occurring substance use. In an effort to characterize and study this multi-faceted problem, the Camden Opioid Research Initiative (CORI) has been formed. The CORI study has collected and analyzed post-mortem toxicology data from 42 cases of decedents who expired from opioid-related toxicity in the South New Jersey region to characterize substance use profiles. Co-occurring substance use, whether by intent or through possible contamination of the illicit opioid supply, is pervasive among deaths due to opioid toxicity, and evidence of medication-assisted treatment is scarce. Nearly all (98%) of the toxicology cases show the presence of the HPSO, fentanyl, and very few (7%) results detected evidence of medication-assisted treatment for opioid use disorder, such as buprenorphine or methadone, at the time of death. The opioid toxicity reversal drug, naloxone, was detected in 19% of cases, but 100% of cases expressed one or more stimulants, and sedatives including xylazine were detected in 48% of cases. These results showing complex substance use profiles indicate that efforts at mitigating the opioid misuse epidemic must address the complications presented by co-occurring stimulant and other substance use, and reduce barriers to and stigmas of seeking effective medication-assisted treatments.

Yield of Familial Hypercholesterolemia Genetic and Phenotypic Diagnoses After Electronic Health Record and Genomic Data Screening.

Background Data mining of electronic health records to identify patients suspected of familial hypercholesterolemia (FH) has been limited by absence of both phenotypic and genomic data in the same cohort. Methods and Results Using the Geisinger MyCode Community Health Initiative cohort (n=130 257), we ran 2 screening algorithms (Mayo Clinic [Mayo] and flag, identify, network, deliver [FIND] FH) to determine FH genetic and phenotypic diagnostic yields. With 29 243 excluded by Mayo (for secondary causes of hypercholesterolemia, no lipid value in electronic health records), 52 034 excluded by FIND FH (insufficient data to run the model), and 187 excluded for prior FH diagnosis, a final cohort of 59 729 participants was created. Genetic diagnosis was based on presence of a pathogenic or likely pathogenic variant in FH genes. Charts from 180 variant-negative participants (60 controls, 120 identified by FIND FH and Mayo) were reviewed to calculate Dutch Lipid Clinic Network scores; a score ≥5 defined probable phenotypic FH. Mayo flagged 10 415 subjects; 194 (1.9%) had a pathogenic or likely pathogenic FH variant. FIND FH flagged 573; 34 (5.9%) had a pathogenic or likely pathogenic variant, giving a net yield from both of 197 out of 280 (70%). Confirmation of a phenotypic diagnosis was constrained by lack of electronic health record data on physical findings or family history. Phenotypic FH by chart review was present by Mayo and/or FIND FH in 13 out of 120 versus 2 out of 60 not flagged by either (P<0.09). Conclusions Applying 2 recognized FH screening algorithms to the Geisinger MyCode Community Health Initiative identified 70% of those with a pathogenic or likely pathogenic FH variant. Phenotypic diagnosis was rarely achievable due to missing data.

Designing implementation strategies to improve identification, cascade testing, and management of families with familial hypercholesterolemia: An intervention mapping approach.

Introduction: Familial hypercholesterolemia (FH) is a common inherited cholesterol disorder that, without early intervention, leads to premature cardiovascular disease. Multilevel strategies that target all components of FH care including identification, cascade testing, and management are needed to address gaps that exist in FH care. We utilized intervention mapping, a systematic implementation science approach, to identify and match strategies to existing barriers and develop programs to improve FH care. Methods: Data were collected utilizing two methods: a scoping review of published literature, related to any component of FH care, and a parallel mixed method study using interviews and surveys. The scientific literature was searched using key words including "barriers" or "facilitators" and "familial hypercholesterolemia" from inception to December 1, 2021. The parallel mixed method study recruited individuals and families with FH to participate in either dyadic interviews (N = 11 dyads/22 individuals) or online surveys (N = 98 respondents). Data generated from the scoping review, dyadic interviews, and online surveys were used in the 6-step intervention mapping process. Steps 1-3 included a needs assessment, development of program outcomes and creation of evidence-based implementation strategies. Steps 4-6 included program development, implementation, and evaluation of implementation strategies. Results: In steps 1-3, a needs assessment found barriers to FH care included underdiagnosis of the condition which led to suboptimal management due to a myriad of determinants including knowledge gaps, negative attitudes, and risk misperceptions by individuals with FH and clinicians. Literature review highlighted barriers to FH care at the health system level, notably the relative lack of genetic testing resources and infrastructure needed to support FH diagnosis and treatment. Examples of strategies to overcome identified barriers included development of multidisciplinary care teams and educational programs. In steps 4-6, an NHLBI-funded study, the Collaborative Approach to Reach Everyone with FH (CARE-FH), deployed strategies that focused on improving identification of FH in primary care settings. The CARE-FH study is used as an example to describe program development, implementation, and evaluation techniques of implementation strategies. Conclusion: The development and deployment of evidence-based implementation strategies that address barriers to FH care are important next steps to improve identification, cascade testing, and management.

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.

Patient Perceptions and Potential Utility of Pharmacogenetic Testing in Chronic Pain Management and Opioid Use Disorder in the Camden Opioid Research Initiative.

Pharmacogenetics (PGx) has the potential to improve opioid medication management. Here, we present patient perception data, pharmacogenetic data and medication management trends in patients with chronic pain (arm 1) and opioid use disorder (arm 2) treated at Cooper University Health Care in Camden City, NJ. Our results demonstrate that the majority of patients in both arms of the study (55% and 65%, respectively) are open to pharmacogenetic testing, and most (66% and 69%, respectively) believe that genetic testing has the potential to improve their medical care. Our results further support the potential for CYP2D6 PGx testing to inform chronic pain medication management for poor metabolizers (PMs) and ultrarapid metabolizers (UMs). Future efforts to implement PGx testing in chronic pain management, however, must address patient concerns about genetic test result access and genetic discrimination.

Patient experiences align with the familial hypercholesterolemia global call to action.

Objective: To explore alignment of perspectives from individuals and families with familial hypercholesterolemia (FH) to the FH Global Call to Action recommendations. Methods: Interviews and focus groups were conducted with individuals and families with FH from multiple U.S. health systems and the Family Heart Foundation community to capture lived experiences and to identify barriers to diagnosis, cascade testing, and treatment. Participant perspectives were examined and classified, according to their alignment to recommendations of the FH Global Call to Action. Results: A total of 75 lived experiences were analyzed. Participants were majority female, mostly white, older, and well-educated. Participants most frequently mentioned recommendations were family-based care (84%) and screening, testing, & diagnosis (84%), followed by treatment (69%), advocacy (60%), cost & value (59%), awareness (56%), research & registries (43%), and severe & homozygous FH (11%). An average of 4.65 (SD 1.76) recommendations were mentioned. Conclusions: The FH Global Call to Action was driven by the persistent unmet needs of those living with FH in receiving a timely diagnosis, appropriate care, and support to prevent early morbidity and mortality. Patient- and family-centric perspectives suggest the FH Global Call to Action captures these concerns. Acting on recommendations, particularly improvements in screening and family-based care, will address patient, and public health, concerns.

Motivating cascade testing for familial hypercholesterolemia: applying the extended parallel process model for clinician communication.

Motivating at-risk relatives to undergo cascade testing for familial hypercholesterolemia (FH) is critical for diagnosis and lifesaving treatment. As credible sources of information, clinicians can assist in family communication about FH and motivate cascade testing uptake. However, there are no guidelines regarding how clinicians should effectively communicate with probands (the first person diagnosed in the family) and at-risk relatives. Individuals and families with FH can inform our understanding of the most effective communications to promote cascade testing. Guided by the extended parallel process model (EPPM), we analyzed the perspectives of individuals and families with FH for effective messaging clinicians can use to promote cascade testing uptake. We analyzed narrative data from interviews and surveys collected as part of a larger mixed-methods study. The EPPM was used to identify message features recommended by individuals and families with FH that focus on four key constructs (severity, susceptibility, response efficacy, self-efficacy) to promote cascade testing. Participants included 22 individuals from 11 dyadic interviews and 98 survey respondents. Participants described prioritizing multiple messages that address each EPPM construct to alert relatives about their risk. They illustrated strategies clinicians could use within each EPPM construct to communicate to at-risk relatives about the importance of pursuing diagnosis via cascade testing and subsequent treatment for high cholesterol due to FH. Findings provide guidance on effective messaging to motivate cascade testing uptake for FH and demonstrates how the EPPM may guide communication with at-risk relatives about genetic risk and motivate cascade testing broadly.

Acceptability, Appropriateness, and Feasibility of Automated Screening Approaches and Family Communication Methods for Identification of Familial Hypercholesterolemia: Stakeholder Engagement Results from the IMPACT-FH Study.

Guided by the Conceptual Model of Implementation Research, we explored the acceptability, appropriateness, and feasibility of: (1) automated screening approaches utilizing existing health data to identify those who require subsequent diagnostic evaluation for familial hypercholesterolemia (FH) and (2) family communication methods including chatbots and direct contact to communicate information about inherited risk for FH. Focus groups were conducted with 22 individuals with FH (2 groups) and 20 clinicians (3 groups). These were recorded, transcribed, and analyzed using deductive (coded to implementation outcomes) and inductive (themes based on focus group discussions) methods. All stakeholders described these initiatives as: (1) acceptable and appropriate to identify individuals with FH and communicate risk with at-risk relatives; and (2) feasible to implement in current practice. Stakeholders cited current initiatives, outside of FH (e.g., pneumonia protocols, colon cancer and breast cancer screenings), that gave them confidence for successful implementation. Stakeholders described perceived obstacles, such as nonfamiliarity with FH, that could hinder implementation and potential solutions to improve systematic uptake of these initiatives. Automated health data screening, chatbots, and direct contact approaches may be useful for patients and clinicians to improve FH diagnosis and cascade screening.

Common Treatment, Common Variant: Evolutionary Prediction of Functional Pharmacogenomic Variants.

Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new 'common treatment, common variant' perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX's in silico predictions.

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.

The Genomics of Opioid Addiction Longitudinal Study (GOALS): study design for a prospective evaluation of genetic and non-genetic factors for development of and recovery from opioid use disorder.

BACKGROUND: The opioid use disorder and overdose crisis in the United States affects public health as well as social and economic welfare. While several genetic and non-genetic risk factors for opioid use disorder have been identified, many of the genetic associations have not been independently replicated, and it is not well understood how these factors interact. This study is designed to evaluate relationships among these factors prospectively to develop future interventions to help prevent or treat opioid use disorder. METHODS: The Genomics of Opioid Addiction Longitudinal Study (GOALS) is a prospective observational study assessing the interplay of genetic and non-genetic by collecting comprehensive genetic and non-genetic information on 400 participants receiving medication for opioid use disorder. Participants will be assessed at four time points over 1 year. A saliva sample will be collected for large-scale genetic data analyses. Non-genetic assessments include validated surveys measuring addiction severity, depression, anxiety, and adverse childhood experiences, as well as treatment outcomes such as urine toxicology results, visit frequency, and number of pre and post-treatment overdoses extracted from electronic medical records. DISCUSSION: We will use these complex data to investigate the relative contributions of genetic and non-genetic risk factors to opioid use disorder and related treatment outcomes.

Individuals with CYP2C8 and CYP2C9 reduced metabolism haplotypes self-adjusted ibuprofen dose in the Coriell Personalized Medicine Collaborative.

OBJECTIVES: The objectives of this study were to determine whether differences in CYP2C8 and CYP2C9 haplotype influence the dose of ibuprofen self-administered by individuals, and to examine the potential relationship between CYP2C8 and CYP2C9 reduced metabolism haplotypes and adverse events. PARTICIPANTS AND METHODS: We investigated relationships between genetic variations in CYP2C8 and CYP2C9 and ibuprofen use, dose, and side effects (reported by questionnaire) in 445 participants from the Coriell Personalized Medicine Collaborative. RESULTS: Carriers of reduced metabolism haplotypes for CYP2C8 (*2, *3, *4) and CYP2C9 (*2, *3) were significantly (P=0.0171) more likely than those lacking these variants to take less than the recommended dose of ibuprofen, after controlling for sex, age, race, and cohort. In contrast to ibuprofen dose, there were no differences in ibuprofen use frequency or reported side effects based on haplotype. However, there are often no early signs of acute kidney injury, the most serious side effect of elevated ibuprofen exposure. CONCLUSION: These results suggest a subset of individuals with genetic variation in CYP2C8 and CYP2C9 recognize that they obtain adequate drug efficacy with lower ibuprofen doses, or take lower doses due to prior side effects. However, most (82.6%) individuals with reduced metabolism haplotypes nonetheless took recommended or higher doses, potentially putting them at increased risk for side effects.