Rapid Engagement for Solutions to Population and Outcomes Through Networked Dialogue for Coronary Heart Disease

Rapid Engagement for Solutions to Population and Outcomes Through Networked Dialogue (RESPOND) to Coronary Heart Disease

Cardiometabolic diseases are major causes of morbidity and mortality in the state of Wisconsin and are expected to pose an increasing burden over the next few decades. A crucial initial step in preventing or delaying the onset of these diseases is to assess disease risk at the individual level. However, the accuracy of risk prediction of disease events based on conventional risk factors remains modest. Incorporating a polygenic risk score (PRS) into risk equations improves risk prediction but there is uncertainty about how best to integrate PRSs into primary care settings, given the lack of familiarity with PRSs among patients and providers. Probabilistic estimates for risks of cardiometabolic diseases may be misunderstood, and genetic risk assessment may not be trusted by those in low resource rural or inner-city settings. The potential for using PRSs to refine disease risk estimates has led to numerous studies to assess their clinical utility; however, the vast majority have been conducted in tertiary academic medical centers, raising concern that communities with diminished access to care could be left behind. The study team will investigate how the use of PRSs for such diseases influences health outcomes in rural and inner-city settings. The study team will leverage prior experience in conducting the MIGENES randomized clinical trial (RCT) of disclosing polygenic risk of CHD in a preventive cardiology setting of an academic center. In the proposed study, the investigators will conduct a pragmatic RCT to extend the investigation to 'real-world' settings of primary care clinics in a rural medical center and an urban Federally Qualified Health Center (FQHC). The investigators will engage a Community Advisory Board (CAB) through focus groups to gather feedback on implementing PRS-guided screening, related medical and lifestyle interventions, and public health strategies to reduce CHD risk. Feedback will inform provider education, targeted outreach to Wisconsin residents, and identification of barriers to adoption. The study team will also assess primary care physicians' and patients' familiarity with polygenic risk, their attitudes toward PRS testing, and intended actions based on results, comparing responses across rural and urban settings. The 10-yr risk of CHD will be estimated based on pooled cohort equations (PCE). Participants will view a video describing how cardiovascular risk was estimated and how lifestyle changes and drug therapy could reduce such risk and, in those randomized to receive PRS, the probabilistic nature of genetic risk. Patients will then see their PCP to review the 10-yr CHD risk estimate and engage in shared decision-making regarding statin therapy. Patient and clinician understanding of polygenic risk information will be assessed, as well as health-related and behavioral outcomes.

Description of study design:

The study team will conduct a pragmatic randomized, controlled trial at two sites (rural versus urban). At each site the team will enroll 100 adults aged 40-69 years without known CHD and who are not on a statin. The 10-yr risk of CHD will be estimated based on pooled cohort equations (PCE). Participants will view a video describing how cardiovascular risk was estimated and how lifestyle changes and drug therapy could reduce such risk and, in those randomized to receive PRS, the probabilistic nature of genetic risk. DNA will be obtained from saliva/blood and a PRS for CHD will be calculated in a CLIA-certified laboratory, using the global diversity array. Patients will then see their PCP to review the 10-yr CHD risk estimate and engage in shared decision-making regarding statin therapy. The study team will assess patient and clinician understanding of polygenic risk information, as well as health-related and behavioral outcomes.

Visit #1: In individuals who have consented for the study, height, weight, and blood pressure will be measured by the study coordinator at the baseline study visit. Demographic information, medication history, and family history (details above) will be collected. A 5ml blood draw will be performed by a trained individual for both a lipid panel and for genotyping. Participant fills out surveys for baseline qualitative assessments. (e.g. numeracy, genetic literacy, perceived heart disease risk, perceived personal control, intention to change, anxiety, impact of events, genetic determinism of understanding PRS results, smoking status, dietary fat, physical activity level, concerns about placing PRS in the HER, intent to pursue medical assistance or counseling in response to PRS, views regarding sharing results with family members, worries about future employability or insurance coverage)

Visit #2: Participants will return after 2 months to be randomized to disclosure of risk estimate based on conventional risk score (CRS) versus an integrated risk score (IRS). The study coordinator will disclose the 10-yr coronary heart disease risk and walk the subject through a 10 minute educational video. This will be followed by a visit with the primary care physician/provider. The patient and provider will then engage in shared decision-making regarding statin initiation. Participant fills out surveys to assess post-disclosure qualitative assessments. (e.g. perceived heart disease risk, perceived personal control, intention to change, impact of events, genetic determinism understanding PRS results, smoking status, dietary fat, physical activity, communication of results, comprehension of results, shared decision-making satisfaction, knowledge transfer, decisional conflict, recall, decisional regret, concerns about placing PRS in the HER, intent to pursue medical assistance or counseling in response to PRS, views regarding sharing results with family members, worries about future employability or insurance coverage)

Physician outcomes. A post-visit questionnaire will assess physicians' satisfaction with the risk communication tool and the decision-making process. The study team will address any bias related to interpretation of PRS. The survey will be completed immediately following the patient visit.

The discriminant ability of multivariable risk prediction equations for cardiometabolic diseases remains modest due to lack of sufficiently predictive biomarkers. Polygenic risk scores (PRSs) provide orthogonal risk information, thereby improving accuracy of risk prediction equations. The potential utility of PRS to increase accuracy of risk prediction and improve outcomes has been highlighted in multiple reports but has not been studied in low resource rural and inner-city settings. While there is optimism that PRS will empower patients to improve their health through preventive practices and early interventions, there is concern that the understanding that PRS tests offering probabilistic estimates for risks of common diseases among both the lay public and medical professionals is poor.

Study Procedures Study sites: The study will be conducted at two sites: The Outreach Community Health Center (OCHC) Primary Care clinic in Milwaukee and ThedaCare Medical Center (TCMC) - Shawano. OCHC - Milwaukee is a federally qualified health center that provides >8,000 primary care visits annually for adult (>18 years) patients. TCMC - Shawano provides approximately 12,000 to 15,000 primary care encounters on an annual basis.

Genotyping: Genotyping will be conducted in the Broad CLIA certified and CAP-accredited laboratory on the Global Diversity Array that includes ~1.8M SNPs and imputes over 25,000,000 SNPs. Broad's genotyping services for research include sample collection kits, arrays, reagents, DNA extraction, data processing, and a custom online dashboard to track study samples, manage enrollment, and access data. The dashboard tracks participants enrolled, percentage of kits received, progress of samples, and PRS results.

Baseline measures: The study team will obtain information about demographic factors including self-identified race and ethnicity (SIRE), personal medical history, social history, family history, educational attainment, home address-derived socioeconomic status and environmental information, social determinants of health (SDOH), primary language, and insurance status (i.e., commercial, Medicare, uninsured) from EHR and survey data. Participants will complete baseline surveys that assess smoking status, diet, physical activity, and perception of disease risk, conventional risk factors, and family history86,87. Height, weight, and BP will be measured by the study coordinator at the baseline study visit. Study data will be placed in a REDCap database105,106.

Family history: Family history is a valuable genomic tool107 and provides important contextual background for returning PRS. The study team will use a family history tool currently being used in the eMERGE phase IV study.94 Family history of early CHD will be defined as occurrence of a CHD event in a first-degree male relative before age 55 years or in a first degree female relative before age 65 years.

Calculation of a PRS: The study team will calculate a genome-wide PRS for CHD for each participant according to a weighted sum of their single nucleotide variant (SNV) genotypes, where each genotype codes the dose of the minor allele for a SNV, and the weights represent the effect size (log-odds-ratios) of the SNV on the phenotype. The investigative team will use the most current and best performing multi-ancestry PRSs that is portable to different ancestry groups.

Return of Results: Once results are ready, letter requesting that the participant set up an appointment with a study coordinator who will summarize results and lead the participant through a 10-min video about disease risk factors and potential means for risk reduction will be sent. A conventional risk score (CRS) for CHD will be calculated using the Pooled Cohort Equations (PCE). An Integrated Risk Score (IRS) will be computed by combining PRS with PCE. Clinical data will be extracted, normalized, and placed in REDCap. An appointment with a genetic counselor will be available to those participants who request it.

Randomization: Participants will be randomized to disclosure of risk based on CRS alone vs IRS, prior to their PCP visit. To ensure allocation concealment, the study coordinator will consult a central randomization line set up by the study statistician to randomize patients (1:1) to the two arms, one group receiving IRS derived by incorporating PRS into PCE, and the other (n= 100) CRS alone based on PCE. Participants will be randomized using a permuted block algorithm (block size 8), balancing age and sex in both arms. Blinding. Patients and clinicians will be aware that PRS may alter estimates of risk. Data analysts will be blinded to allocation. Intention-to-treat principle. Resources will be set aside to follow all patients to study completion and analyze them primarily as randomized. Fidelity. Participating clinicians will receive formal training in the use of a genomic decision-aid that incorporates the genotype-informed estimate of risk. This training will be performed by study investigators and mock sessions conducted so that they are fully familiar with the tool and the standard language to disclose risk.

Statistical Methods to analyze differences in primary and secondary endpoints between the two study groups. Initial evaluations of the data will include inspection of the raw data, descriptive statistics, examination of outliers and group distributions, and evaluation of missing data. Standard techniques will be used that are appropriate for patient randomized trials, with each outcome compared between study arms using t-tests for continuous outcomes and chi-square tests for dichotomous outcomes. If there are differences in baseline characteristics between the two study groups, these will be accounted for, using regression models which include an indicator for study arm. Exploratory analyses will be conducted to assess a) whether the presence of family history of CHD influences the study outcomes and b) whether outcomes differ by site (rural vs. urban).

Sample size and power calculations. Sample size was based on aiming for 90% power to detect an absolute difference in statin initiation from 20% in control arm to 40% in the intervention arm (PRS disclosure) at two-sided α = 0.05 using the normal-approximation formula for two independent proportions. The expected frequency of statin initiation is based on data from our prior MIGENES clinical trial.48 Even accounting for 15-20% loss to follow-up or missing outcome data, the study will have ~80% power to detect an absolute difference in statin initiation from 20% to 40%.

9. Potential Risks/ Risk Mitigation

1. Blood Draw: at baseline and after 2-3 months of result disclosure.
2. Loss of Confidentiality: Each participant will be assigned a code and the data will be filed according to code. Subject identity will be known only to the PIs and necessary research personnel. The information, including the consent forms, will be maintained in a location that is approved by the IRB.

Inclusion Criteria:

• Adults aged 40-69 years of age
• No prior history of coronary heart disease
• No prior use of statin medication
• Has primary care provider

Exclusion Criteria:

• Prior history of coronary heart disease
• current use of statin medication