Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study.

PURPOSE: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.

Concordance between predicted HLA type using next generation sequencing data generated for non-HLA purposes and clinical HLA type.

We explored the feasibility of obtaining accurate HLA type using pre-existing NGS data not generated for HLA purposes. 83 exomes and 500 targeted NGS pharmacogenomic panels were analyzed using Omixon HLA Explore, OptiType, and/or HLA-Genotyper software. Results were compared against clinical HLA genotyping. 765 (94.2%) Omixon and 769 (94.7%) HLA-Genotyper of 812 germline allele calls across class I/II loci and 402 (99.5%) of 404 OptiType class I calls were concordant to the second field (i.e. HLA-A*02:01). An additional 19 (2.3%) Omixon, 39 (4.8%) HLA-Genotyper, and 2 (0.5%) OptiType allele calls were first field concordant (i.e. HLA-A*02). Using Omixon, four alleles (0.4%) were discordant and 24 (3.0%) failed to call, while 4 alleles (0.4%) were discordant using HLA-Genotyper. Tumor exomes were also evaluated and were 85.4%, 91.6%, and 100% concordant (Omixon and HLA-Genotyper with 96 alleles tested, and Optitype with 48 class I alleles, respectively). The 15 exomes and 500 pharmacogenomic panels were 100% concordant for each pharmacogenomic allele tested. This work has broad implications spanning future clinical care (pharmacogenomics, tumor response to immunotherapy, autoimmunity, etc.) and research applications.

Clinical UGT1A1 Genetic Analysis in Pediatric Patients: Experience of a Reference Laboratory.

BACKGROUND: Neonatal hyperbilirubinemia can be severe or prolonged and warrant exploration into the underlying etiology, which may include genetic assessment of UGT1A1 for inherited disorders (i.e. Crigler-Najjar syndrome or Gilbert syndrome). METHODS: In our reference laboratory, we performed UGT1A1 gene sequencing analysis on 346 pediatric patients referred for a clinical indication of hyperbilirubinemia. RESULTS: Males (n = 241) had significantly higher mean total bilirubin concentration compared to females (n = 105) (9.7 and 7.3 mg/dL, respectively, p = 0.042); however, no sex-based difference was observed in frequency of known or suspected reduced function UGT1A1 variants. The presence of two UGT1A1 variants (consistent with Gilbert or Crigler-Najjar syndrome) occurred less frequently in neonates (aged ≤28 days) than older children (aged 1-18 years) (31.3% in neonates vs. 85.1%, p < 0.0001), and among neonates there was no significant difference in mean total bilirubin between those with two UGT1A1 variants and those without (p = 0.47). Three novel variants, including c.337T>G (p.Y113D), c.1037C>A (p.A346E), and c.1469A>C (p.D490A) were identified. Among older children, the most common reason for referral was Gilbert syndrome (83.8%) and UGT1A1 genetic analysis confirmed a diagnosis of Gilbert syndrome in 79.0% of those children. CONCLUSIONS: Among neonates, a population in which hyperbilirubinemia is common and often of multifactorial etiology, UGT1A1 genetic testing served as a useful clinical tool in ruling in or ruling out inherited hyperbilirubinemia. Here we describe our experience as a reference laboratory in clinical UGT1A1 full gene sequencing. Our results highlight the challenges in predicting the contribution of genetic variation in UGT1A1 to hyperbilirubinemia based on clinical parameters alone, particularly in neonates, and the utility of UGT1A1 full gene sequencing in the evaluation of neonatal and pediatric hyperbilirubinemia.

Preemptive Pharmacogenomic Testing for Precision Medicine: A Comprehensive Analysis of Five Actionable Pharmacogenomic Genes Using Next-Generation DNA Sequencing and a Customized CYP2D6 Genotyping Cascade.

Significant barriers, such as lack of professional guidelines, specialized training for interpretation of pharmacogenomics (PGx) data, and insufficient evidence to support clinical utility, prevent preemptive PGx testing from being widely clinically implemented. The current study, as a pilot project for the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment Protocol, was designed to evaluate the impact of preemptive PGx and to optimize the workflow in the clinic setting. We used an 84-gene next-generation sequencing panel that included SLCO1B1, CYP2C19, CYP2C9, and VKORC1 together with a custom-designed CYP2D6 testing cascade to genotype the 1013 subjects in laboratories approved by the Clinical Laboratory Improvement Act. Actionable PGx variants were placed in patient's electronic medical records where integrated clinical decision support rules alert providers when a relevant medication is ordered. The fraction of this cohort carrying actionable PGx variant(s) in individual genes ranged from 30% (SLCO1B1) to 79% (CYP2D6). When considering all five genes together, 99% of the subjects carried an actionable PGx variant(s) in at least one gene. Our study provides evidence in favor of preemptive PGx testing by identifying the risk of a variant being present in the population we studied.

Analysis of compound heterozygous CYP2C19 genotypes to determine cis and trans configurations.

BACKGROUND: Through allele specific PCR we studied 220 CYP2C19 compound heterozygous samples, of unknown ethnicity, to determine the haplotype for each of the variations within a sample. MATERIALS & METHODS: The genotypes assessed were: 180 *2 and *17 samples (100% in trans); 20 *2 and *11 samples (100% in cis); ten *4 and *17 samples (50% of the samples were *1/*4B and 50% *4A/*17); six *2, *11 and *17 samples (100% showed *2 and *11 in cis, and *17 in trans); two *2, *4 and *17 samples (100% *4B with *2 in trans); one sample with *17 and *34 (these were in trans); and one sample that contained *2, *17, c.463G>T (p.E155X; *17 and c.463G>T were in cis, with *2 in trans). RESULTS & CONCLUSION: In our study, we observed a different frequency for the *4B allele (when a sample contains both *4 and *17); and identified *17 occurring in cis with a novel nonsense allele. Accurately assessing a patient's genotype, including assignment of a haplotype, can be important when making a phenotype prediction.

Preemptive genotyping for personalized medicine: design of the right drug, right dose, right time-using genomic data to individualize treatment protocol.

OBJECTIVE: To report the design and implementation of the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment protocol that was developed to test the concept that prescribers can deliver genome-guided therapy at the point of care by using preemptive pharmacogenomics (PGx) data and clinical decision support (CDS) integrated into the electronic medical record (EMR). PATIENTS AND METHODS: We used a multivariate prediction model to identify patients with a high risk of initiating statin therapy within 3 years. The model was used to target a study cohort most likely to benefit from preemptive PGx testing among the Mayo Clinic Biobank participants, with a recruitment goal of 1000 patients. We used a Cox proportional hazards model with variables selected through the Lasso shrinkage method. An operational CDS model was adapted to implement PGx rules within the EMR. RESULTS: The prediction model included age, sex, race, and 6 chronic diseases categorized by the Clinical Classifications Software for International Classification of Diseases, Ninth Revision codes (dyslipidemia, diabetes, peripheral atherosclerosis, disease of the blood-forming organs, coronary atherosclerosis and other heart diseases, and hypertension). Of the 2000 Biobank participants invited, 1013 (51%) provided blood samples, 256 (13%) declined participation, 555 (28%) did not respond, and 176 (9%) consented but did not provide a blood sample within the recruitment window (October 4, 2012, through March 20, 2013). Preemptive PGx testing included CYP2D6 genotyping and targeted sequencing of 84 PGx genes. Synchronous real-time CDS was integrated into the EMR and flagged potential patient-specific drug-gene interactions and provided therapeutic guidance. CONCLUSION: This translational project provides an opportunity to begin to evaluate the impact of preemptive sequencing and EMR-driven genome-guided therapy. These interventions will improve understanding and implementation of genomic data in clinical practice.

UGT1A1 genetic analysis as a diagnostic aid for individuals with unconjugated hyperbilirubinemia.

OBJECTIVE: To assess the clinical utility of UGT1A1 genetic testing and describe the spectrum and prevalence of UGT1A1 variations identified in pediatric unconjugated hyperbilirubinemia (UCH), and to characterize specific genotype-phenotype relationships in suspected Gilbert and Crigler-Najjar syndromes. STUDY DESIGN: A retrospective study was conducted to review clinical information and UGT1A1 genotyping data from 181 pediatric patients referred for UCH. In silico analyses were performed to aid in the assessment of novel UGT1A1 variants. RESULTS: Overall, 146/181 pediatric patients had at least one heterozygous UGT1A1 functional variant. Identified UGT1A1 variants included 17 novel variants, 7 rare star alleles, and 1 rare variant. There were 129 individuals who possessed the TA7 (*28) promoter repeat and 15 individuals who possessed the *6 (c.211G > A) variation. Out of the 104 individuals with accompanying bilirubin levels, 41 individuals did not have identifiable UGT1A1 variants that explained their UCH, although glucose-6-phosphate dehydrogenase deficiency and other causes of UCH could not be ruled out. CONCLUSION: Much of the observed UCH could be attributed to variation at the UGT1A1 locus, and UGT1A1 testing helped to substantiate a genetic diagnosis, thereby aiding in individual and family disease management. Although UGT1A1 variation plays a large role in UCH, genetic assessment of UGT1A1 alone may not be comprehensive. Assessment of additional genes may also be useful to evaluate genetic causes for UCH.

CYP2D6*11 and challenges in clinical genotyping of the highly polymorphic CYP2D6 gene.

CYP2D6 is genotyped clinically for prediction of response to tamoxifen, psychotropic drugs and other medications. Phenotype prediction is dependent upon accurate genotyping. The CYP Allele Nomenclature Committee maintains the allelic nomenclature for CYP2D6; however, in some cases, the list of polymorphisms associated with a given allele is incomplete. Clinical laboratories and in vitro diagnostic manufacturers rely upon this nomenclature, in addition to the literature, to infer allelic function and haplotypes and when they design CYP2D6-testing platforms. This article provides more complete sequencing data for the CYP2D6*11 allele and describes the difficulties encountered in genotyping CYP2D6 when incomplete data are available. The CYP Allele Nomenclature Committee should provide clear information about the completeness of the original data used to define each allele.