Development of a Multifaceted Program for Pharmacogenetics Adoption at an Academic Medical Center: Practical Considerations and Lessons Learned.

In 2019, Indiana University launched the Precision Health Initiative to enhance the institutional adoption of precision medicine, including pharmacogenetics (PGx) implementation, at university-affiliated practice sites across Indiana. The overarching goal of this PGx implementation program was to facilitate the sustainable adoption of genotype-guided prescribing into routine clinical care. To accomplish this goal, we pursued the following specific objectives: (i) to integrate PGx testing into existing healthcare system processes; (ii) to implement drug-gene pairs with high-level evidence and educate providers and pharmacists on established clinical management recommendations; (iii) to engage key stakeholders, including patients to optimize the return of results for PGx testing; (iv) to reduce health disparities through the targeted inclusion of underrepresented populations; (v) and to track third-party reimbursement. This tutorial details our multifaceted PGx implementation program, including descriptions of our interventions, the critical challenges faced, and the major program successes. By describing our experience, we aim to assist other clinical teams in achieving sustainable PGx implementation in their health systems.

Gene x environment interactions impact endometrial function and the menstrual cycle: PROGINS, life history, anthropometry, and physical activity.

OBJECTIVES: We assessed the impact of a high frequency, functionally significant allelic variant of the progesterone receptor gene (PROGINS) on endometrial function and menstrual cycle characteristics. Further we asked whether PROGINS moderates the impact of life history characteristics, anthropometric measures, and physical activity on endometrial function. METHODS: Fifty-two women were genotyped for the PROGINS variant, provided life history information, and had anthropometric measurements made. Women monitored their menstrual bleeding for three cycles, performed mid-cycle urinary ovulation tests, and recorded physical activity. A subset of women provided daily saliva samples and had mid-luteal endometrial thickness measurements taken during the third menstrual cycle. Salivary progesterone was assayed using ELISAs. The direct impact of PROGINS on endometrial and menstrual cycle characteristics was determined via independent t-tests with Bonferroni correction. Interactions between PROGINS and covariates were assessed by moderated regression. RESULTS: PROGINS did not directly impact any indicator of endometrial function. However, PROGINS caused an increase in menstrual cycle length with increasing mid-luteal progesterone levels; the opposite relationship was present in noncarriers (P < 0.05). Additionally, PROGINS interacted with four of six anthropometric measures (BMI, waist circumference, height, and waist-hip ratio) to impact endometrial function, however, interactions between PROGINS and life history variables, or physical activity was limited. CONCLUSIONS: The gene x environment interactions we report suggest that PROGINS alters endometrial sensitivity to maternal energetic condition. Thus, the possibility of genetically-based variation in sensitivity to energetic stress should be considered in future adaptive models of women's reproduction.

Computational pharmacogenotype extraction from clinical next-generation sequencing.

Background: Next-generation sequencing (NGS), including whole genome sequencing (WGS) and whole exome sequencing (WES), is increasingly being used for clinic care. While NGS data have the potential to be repurposed to support clinical pharmacogenomics (PGx), current computational approaches have not been widely validated using clinical data. In this study, we assessed the accuracy of the Aldy computational method to extract PGx genotypes from WGS and WES data for 14 and 13 major pharmacogenes, respectively. Methods: Germline DNA was isolated from whole blood samples collected for 264 patients seen at our institutional molecular solid tumor board. DNA was used for panel-based genotyping within our institutional Clinical Laboratory Improvement Amendments- (CLIA-) certified PGx laboratory. DNA was also sent to other CLIA-certified commercial laboratories for clinical WGS or WES. Aldy v3.3 and v4.4 were used to extract PGx genotypes from these NGS data, and results were compared to the panel-based genotyping reference standard that contained 45 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, TPMT, and VKORC1. Results: Mean WGS read depth was >30x for all variant regions except for G6PD (average read depth was 29 reads), and mean WES read depth was >30x for all variant regions. For 94 patients with WGS, Aldy v3.3 diplotype calls were concordant with those from the genotyping reference standard in 99.5% of cases when excluding diplotypes with additional major star alleles not tested by targeted genotyping, ambiguous phasing, and CYP2D6 hybrid alleles. Aldy v3.3 identified 15 additional clinically actionable star alleles not covered by genotyping within CYP2B6, CYP2C19, DPYD, SLCO1B1, and NUDT15. Within the WGS cohort, Aldy v4.4 diplotype calls were concordant with those from genotyping in 99.7% of cases. When excluding patients with CYP2D6 copy number variation, all Aldy v4.4 diplotype calls except for one CYP3A4 diplotype call were concordant with genotyping for 161 patients in the WES cohort. Conclusion: Aldy v3.3 and v4.4 called diplotypes for major pharmacogenes from clinical WES and WGS data with >99% accuracy. These findings support the use of Aldy to repurpose clinical NGS data to inform clinical PGx.

Worldwide distribution of allelic variation at the progesterone receptor locus and the incidence of female reproductive cancers.

OBJECTIVES: Global patterns of the incidence of cancer are often attributed to environmental and lifestyle differences between regions. Less attention has been given to global patterns of allelic variation of genes that may contribute to the risk of developing cancer. METHODS: We genotyped samples from 21 populations for four variants of the progesterone receptor (PR) gene. One is an Alu insertion in intron 7 which defines the PROGINS haplotype. The others include a promoter region SNP 331+ G/A (rs10895068), a haplotype defining T/C substitution in intron 6 (rs561650), and an A/T substitution (rs608995) in the 3' untranslated region of the gene. All variants have been investigated elsewhere in association with female reproductive cancers in western populations. RESULTS: We found population differences in the frequency of each of these alleles across study populations (P < 0.01, log-likelihood G statistic, computed in FSTAT) and therefore examined the correlation between the frequency of each genetic variant and the incidence of three female reproductive cancers (breast, uterine, and ovarian) obtained from the Globocan 2008 database. Breast and ovarian cancer incidence were significantly correlated with the frequency of the Alu insertion (r = 0.86 and 0.53) and the +331 A variant (r = 0.57 and 0.73). CONCLUSIONS: Our data expand the information on genetic variation at the PR locus in non-western populations and support an argument for more work on the genetic epidemiology of cancer among nonwestern populations.

Association of QT interval-prolonging drugs with clinical trial eligibility in patients with advanced cancer.

Introduction: Drug-induced prolongation of the heart rate-corrected QT interval (QTc) is associated with increased risk for the potentially fatal arrhythmia torsades de pointes. Due to arrhythmia risk, clinical trials with cancer therapeutics often exclude patients based on thresholds for QTc prolongation. Our objective was to assess associations between prescriptions for QT-prolonging drugs and the odds of meeting cancer trial exclusionary QTc thresholds in a cohort of adults with advanced cancer. Methods: Electronic health records were retrospectively reviewed for 271 patients seen at our institutional molecular solid tumor clinic. Collected data included demographics, QTc measurements, ventricular arrhythmia-related diagnoses, and all inpatient and outpatient prescriptions. Potential associations were assessed between demographic and clinical variables, including prescriptions for QT-prolonging drugs, and QTc measurements. Results: Women had longer median QTc measurements than men (p = 0.030) and were prescribed more QT-prolonging drugs during the study (p = 0.010). In all patients, prescriptions for QT-prolonging drugs were associated with longer median and maximum QTc measurements at multiple assessed time points (i.e., for QT-prolonging drugs prescribed within 10, 30, 60, and 90 days of QTc measurements). Similarly, the number of QT-prolonging drugs prescribed was correlated with longer median and maximum QTc measurements at multiple time points. Common QTc-related exclusionary criteria were collected from a review of ClinicalTrials.gov for recent cancer clinical trials. Based on common exclusion criteria, prescriptions for QT-prolonging drugs increased the odds of trial exclusion. Conclusion: This study demonstrates that prescriptions for QT-prolonging drugs were associated with longer QTc measurements and increased odds of being excluded from cancer clinical trials.

Clinical Opportunities for Germline Pharmacogenetics and Management of Drug-Drug Interactions in Patients With Advanced Solid Cancers.

PURPOSE: Precision medicine approaches, including germline pharmacogenetics (PGx) and management of drug-drug interactions (DDIs), are likely to benefit patients with advanced cancer who are frequently prescribed multiple concomitant medications to treat cancer and associated conditions. Our objective was to assess the potential opportunities for PGx and DDI management within a cohort of adults with advanced cancer. METHODS: Medication data were collected from the electronic health records for 481 subjects since their first cancer diagnosis. All subjects were genotyped for variants with clinically actionable recommendations in Clinical Pharmacogenetics Implementation Consortium guidelines for 13 pharmacogenes. DDIs were defined as concomitant prescription of strong inhibitors or inducers with sensitive substrates of the same drug-metabolizing enzyme and were assessed for six major cytochrome P450 (CYP) enzymes. RESULTS: Approximately 60% of subjects were prescribed at least one medication with Clinical Pharmacogenetics Implementation Consortium recommendations, and approximately 14% of subjects had an instance for actionable PGx, defined as a prescription for a drug in a subject with an actionable genotype. The overall subject-level prevalence of DDIs and serious DDIs were 50.3% and 34.8%, respectively. Serious DDIs were most common for CYP3A, CYP2D6, and CYP2C19, occurring in 24.9%, 16.8%, and 11.7% of subjects, respectively. When assessing PGx and DDIs together, approximately 40% of subjects had at least one opportunity for a precision medicine-based intervention and approximately 98% of subjects had an actionable phenotype for at least one CYP enzyme. CONCLUSION: Our findings demonstrate numerous clinical opportunities for germline PGx and DDI management in adults with advanced cancer.