Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network

Abstract

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE-PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of "precision medicine." The February 2015 eMERGE-PGx data release includes sequence-derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation-Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

Figure 1

Allelic spectrum of eMERGE‐PGx variants. Counts of genomic variants mapping to the canonical transcript of PGRNseq captured genes are plotted by frequency class (over all samples) by gene (x‐axis) in ascending order. Gold horizontal lines indicate the size of the canonical transcript in basepairs. The inset line plot is a percentile rank of genic intolerance (RVIS) scores computed using the ExAC dataset.

Figure 2

Boxplot of scaled (Phred) CADD score annotations for alleles by gene. Genes are ranked from top to bottom by ascending median CADD score.

Figure 3

Estimates of prescriptions impacted by rare missense variants within pharmacogenes impacting the metabolism of frequently prescribed drugs.

Figure 4

Screenshot of SPHINX website (http://emergesphinx.org).