Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine.

Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.

Biomarkers Correspond with Echocardiographic Phenotypes in Heart Failure with Preserved Ejection Fraction: A Secondary Analysis of the RELAX Trial.

Background: Little is known about the relationship between structural phenotypes in in heart failure with preserved ejection fraction (HFpEF) and cardiac biomarkers. We used cluster analysis to identify cardiac structural phenotypes and their relationships to biomarkers in HFpEF. Methods and results: Latent class analysis (LCA) was applied to echocardiographic data including left atrial enlargement (LAE), diastolic dysfunction (DD), E/e', EF≤55%, and right ventricular dysfunction from 216 patients enrolled in the RELAX trial. Three structural phenotypes were identified. Phenotype A had the most grade II DD. Phenotype B had the most grade III DD, worst LAE, elevated E/e' and right ventricular dysfunction. Phenotype C had the least DD and moderate LAE. Phenotypes B and C had prevalent atrial fibrillation (AF). Phenotype B patients had increased carboxy-terminal telopeptide of collagen type I (CITP), cystatin-c (CYSTC), endothelin-1 (ET1), NT-proBNP, and high-sensitivity troponin I (TNI). Type A had the next highest CITP and CYSTC levels while Type C had next highest NT-proBNP. Conclusions: Structural HFpEF phenotypes demonstrated different characteristics including cardiac biomarkers. These findings may help explain phenotype-specific differences in natural history and prognosis, and they may represent phenotype-specific pathophysiology that could be amenable to targeted therapy.

Implementation of clopidogrel pharmacogenetic clinical decision support for a preemptive return of results program.

PURPOSE: To describe our experiences implementing and iterating CYP2C19 genotype-guided clopidogrel pharmacogenetic clinical decision support (CDS) tools over time in the setting of a large health system-wide, preemptive pharmacogenomics program. SUMMARY: Clopidogrel-treated patients who are genetically predicted cytochrome P450 isozyme 2C19 (CYP2C19) intermediate or poor metabolizers have an increased risk of atherothrombotic events, some of which can be life-threatening. The Clinical Pharmacogenetics Implementation Consortium provides guidance for the use of clopidogrel based on CYP2C19 genotype in patients with cardiovascular and cerebrovascular diseases. Our multidisciplinary team implemented an automated, interruptive alert that fires when clopidogrel is ordered or refilled for biobank participants with structured CYP2C19 intermediate or poor metabolizer genomic indicators in the electronic health record. The implementation began with a narrow cardiovascular indication and setting and was then scaled in 4 primary dimensions: (1) clinical indication; (2) availability across health-system locations; (3) care venue (e.g., inpatient vs outpatient); and (4) provider groups (eg, cardiology and neurology). We iterated our approach over time based on evolving clinical evidence and proactive strategies to optimize CDS maintenance and sustainability. A key facilitator of expansion was socialization of the broader pharmacogenomics initiative among our academic medical center community, accompanied by clinician acceptance of pharmacogenetic alerts in practice. CONCLUSION: A multidisciplinary collaboration is recommended to facilitate the use of CYP2C19 genotype-guided antiplatelet therapy in patients with cardiovascular and cerebrovascular diseases. Evolving clopidogrel pharmacogenetic evidence necessitates thoughtful iteration of implementation efforts and strategies to optimize long-term maintenance and sustainability.