Analytical Validation of a Computational Method for Pharmacogenetic Genotyping from Clinical Whole Exome Sequencing

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.

The Potential Impact of Preemptive Pharmacogenetic Genotyping in the Neonatal Intensive Care Unit

OBJECTIVE

To evaluate the use of drugs with pharmacogenomic (PGx) guidelines from the Clinical Pharmacogenetics Implementation Consortium in early childhood.

STUDY DESIGN

A retrospective observational study of patients admitted to the neonatal intensive care (NICU) between 2005 and 2018 with at least 1 subsequent hospitalization at or after 5 years of age was performed to determine PGx drug exposure. Data regarding hospitalizations, drug exposures, gestational age, birth weight, and congenital anomalies and/or a primary genetic diagnosis were collected. Incidence of PGx drug and drug class exposures was determined and patient specific factors predictive of exposure were investigated.

RESULTS

During the study, 19 195 patients received NICU care and 4196 (22%) met study inclusion; 67% received 1-2, 28% 3-4, and 5% 5 or more PGx-drugs in early childhood. Preterm gestation, low birth weight (<2500 g), and the presence of any congenital anomalies and/or a primary genetic diagnosis were statistically significant predictors of Clinical Pharmacogenetics Implementation Consortium drug exposures (P < .01, P < .01, P < .01, respectively).

CONCLUSIONS

Preemptive PGx testing in patients in the NICU could have a significant impact on medical management during the NICU stay and throughout early childhood.

Implementation of Clinical Cytochrome P450 3A Genotyping for Tacrolimus Dosing in a Large Kidney Transplant Program

Tacrolimus is a calcineurin inhibitor with a narrow therapeutic range and is metabolized by cytochrome P450 (CYP) isoenzymes CYP3A4 and CYP3A5. The Clinical Pharmacogenetic Implementation Consortium published evidence-based guidelines for CYP3A5 normal/intermediate metabolizers prescribed tacrolimus, yet few transplant centers have implemented routine testing. The objective of this study was to implement preemptive CYP3A genotyping into clinical practice in a large kidney transplant program and to evaluate workflow feasibility, potential clinical benefit, and reimbursement to identify barriers and determine sustainability. Preemptive pharmacogenetic testing for CYP3A5 and CYP3A4 was implemented in all patients listed for a kidney transplant as part of standard clinical care. Genotyping was performed at the listing appointment, results were reported as discrete data in the electronic medical record, and education and clinical decision support alerts were developed to provide pharmacogenetic-recommended tacrolimus dosing. During this initial phase, all patients were administered standard tacrolimus dosing, and clinical and reimbursement outcomes were collected. Greater than 99.5% of genotyping claims were reimbursed by third-party payers. CYP3A5 normal/intermediate metabolizers had significantly fewer tacrolimus trough concentrations within the target range and a significantly longer time to their first therapeutic trough compared to poor metabolizers. The challenge of tacrolimus dosing is magnified in the African American population. The US Food and Drug Administration drug label recommends increased starting doses in African ancestry, yet only ≈66% of African Americans in our cohort were normal/intermediate metabolizers who required higher doses. Routine CYP3A5 genotyping may overcome this issue by using genotype over race as a more accurate predictor of drug response.

Cytochrome P450 Oxidoreductase (POR) Associated with Severe Paclitaxel-Induced Peripheral Neuropathy in Patients of European Ancestry from ECOG-ACRIN E5103

PURPOSE

Paclitaxel is a widely used anticancer therapeutic. Peripheral neuropathy is the dose-limiting toxicity and negatively impacts quality of life. Rare germline gene markers were evaluated for predicting severe taxane-induced peripheral neuropathy (TIPN) in the patients of European ancestry. In addition, the impact of Cytochrome P450 (CYP) 2C8, CYP3A4, and CYP3A5 metabolizer status on likelihood of severe TIPN was also assessed.

EXPERIMENTAL DESIGN

Whole-exome sequencing analyses were performed in 340 patients of European ancestry who received a standard dose and schedule of paclitaxel in the adjuvant, randomized phase III breast cancer trial, E5103. Patients who experienced grade 3-4 (n = 168) TIPN were compared to controls (n = 172) who did not experience TIPN. For the analyses, rare variants with a minor allele frequency ≤ 3% and predicted to be deleterious by protein prediction programs were retained. A gene-based, case-control analysis using SKAT was performed to identify genes that harbored an imbalance of deleterious variants associated with increased risk of severe TIPN. CYP star alleles for CYP2C8, CYP3A4, and CYP3A5 were called. An additive logistic regression model was performed to test the association of CYP2C8, CYP3A4, and CYP3A5 metabolizer status with severe TIPN.

RESULTS

Cytochrome P450 oxidoreductase (POR) was significantly associated with severe TIPN (P value = 1.8 ×10-6). Six variants were predicted to be deleterious in POR. There were no associations between CYP2C8, CYP3A4, or CYP3A5 metabolizer status with severe TIPN.

CONCLUSIONS

Rare variants in POR predict an increased risk of severe TIPN in patients of European ancestry who receive paclitaxel.

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.

An efficient genotyper and star-allele caller for pharmacogenomics

High-throughput sequencing provides sufficient means for determining genotypes of clinically important pharmacogenes that can be used to tailor medical decisions to individual patients. However, pharmacogene genotyping, also known as star-allele calling, is a challenging problem that requires accurate copy number calling, structural variation identification, variant calling, and phasing within each pharmacogene copy present in the sample. Here we introduce Aldy 4, a fast and efficient tool for genotyping pharmacogenes that uses combinatorial optimization for accurate star-allele calling across different sequencing technologies. Aldy 4 adds support for long reads and uses a novel phasing model and improved copy number and variant calling models. We compare Aldy 4 against the current state-of-the-art star-allele callers on a large and diverse set of samples and genes sequenced by various sequencing technologies, such as whole-genome and targeted Illumina sequencing, barcoded 10x Genomics, and Pacific Biosciences (PacBio) HiFi. We show that Aldy 4 is the most accurate star-allele caller with near-perfect accuracy in all evaluated contexts, and hope that Aldy remains an invaluable tool in the clinical toolbox even with the advent of long-read sequencing technologies.

Development of an extensive workflow for comprehensive clinical pharmacogenomic profiling: lessons from a pilot study on 100 whole exome sequencing data

This pilot study is aimed at implementing an approach for comprehensive clinical pharmacogenomics (PGx) profiling. Fifty patients with cardiovascular diseases and 50 healthy individuals underwent whole-exome sequencing. Data on 1800 PGx genes were extracted and analyzed through deep filtration separately. Theoretical drug induced phenoconversion was assessed for the patients, using sequence2script. In total, 4539 rare variants (including 115 damaging non-synonymous) were identified. Four publicly available PGx bioinformatics algorithms to assign PGx haplotypes were applied to nine selected very important pharmacogenes (VIP) and revealed a 45-70% concordance rate. To ensure availability of the results at point-of-care, actionable variants were stored in a web-hosted database and PGx-cards were developed for quick access and handed to the study subjects. While a comprehensive clinical PGx profile could be successfully extracted from WES data, available tools to interpret these data demonstrated inconsistencies that complicate clinical application.