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Clinical laboratories offering genome sequencing have the opportunity to return pharmacogenomic findings to patients, providing the added benefit of preemptive testing that could help inform medication selection or dosing throughout the lifespan. Implementation of pharmacogenomic reporting must address several challenges, including inherent limitations in short-read genome sequencing methods, gene and variant selection, standardization of genotype and phenotype nomenclature, and choice of guidelines and drugs to report. An automated pipeline, lmPGX, was developed as an end-to-end solution that produces two versions of a pharmacogenomic report, presenting either Clinical Pharmacogenetics Implementation Consortium or US Food and Drug Administration guidelines for 12 genes. The pipeline was validated for performance using reference samples and pharmacogenetic data from the Genetic Testing Reference Materials Coordination Program. To determine performance and limitations, lmPGX was compared with three additional publicly available pharmacogenomic pipelines. The lmPGX pipeline offers clinical laboratories an opportunity for seamless integration of pharmacogenomic results with genome reporting.

Variant interpretation depends on accurate annotations using biologically relevant transcripts. We have developed a systematic strategy for designating primary transcripts and have applied it to 109 hearing loss–associated genes that were divided into three categories. Category 1 genes (n = 38) had a single transcript; category 2 genes (n = 33) had multiple transcripts, but a single transcript was sufficient to represent all exons; and category 3 genes (n = 38) had multiple transcripts with unique exons. Transcripts were curated with respect to gene expression reported in the literature and the Genotype-Tissue Expression Project. In addition, high-frequency loss-of-function variants in the Genome Aggregation Database and disease-causing variants in ClinVar and the Human Gene Mutation Database across the 109 genes were queried. These data were used to classify exons as clinically significant, insignificant, or of uncertain significance. Interestingly, 6% of all exons, containing 124 reportedly disease-causing variants, were of uncertain significance. Finally, we used exon-level next-generation sequencing quality metrics generated at two clinical laboratories and identified a total of 43 technically challenging exons in 20 different genes that had inadequate coverage and/or homology issues that might lead to false-variant calls. We have demonstrated that transcript analysis plays a critical role in accurate clinical variant interpretation.

Diagnostic next-generation sequencing (NGS)-based gene panels are increasingly used for prevalent disorders with genetic and clinical heterogeneity. Clinical development, validation, and quality management of these panels ideally includes reference samples containing prevalent pathogenic variants; however, clinical domain expertise to select appropriate variants may not be present, samples are often not publicly available, and their inclusion is associated with added cost. Expert-designed, multiplexed controls can remedy some of these challenges. One approach relies on spiking biosynthetic fragments carrying desired variants into human genomic DNA. We piloted the utility of this approach for hypertrophic cardiomyopathy. Data from3000 previously sequenced probands were used to select 10 common pathogenic and/or technically challenging variants in the top hypertrophic cardiomyopathy genes. Multiplexed controls were constructed across a range of ideal and realistic allelic fractions for heterozygous germline variants. NGS was performed in quadruplicate, and results were compared with diagnostic NGS data for the source patient samples. Overall, results were indistinguishable from patient-derived data with variants being detected at or reasonably close to the targeted allelic fraction ratios. The exception was a common 25-bp deletion in MYBPC3, underscoring the importance of including such variants in test development. These controls may be an attractive addition to the repertoire of materials for development, validation, and quality monitoring of clinical NGS assays.