NGS

Next Generation Sequencing (NGS) is an interesting technology for PGx

A nice overview of the Requirements for comprehensive pharmacogenetic genotyping platforms was published by Volker Lauschke et al. They claim that rare variants account for 30-40% of functional variability in PGx. However they argue that pre-emptive PGx should only include validated variants, and rare variants should be investigated only when the patient experience unexpected drug response.

Challenges

• Bad coverage of pharmacogenes. This most seriously affects WES.
• Haplotype calling is challenging due to short read. NGS requires in silico haplotype estimation. There is support for basic haplotype estimation in the GATK haplotype caller since version 3.3. Haplotype calling can also be performed by various imputation methods Beagle or Eagle2 or SHAPEIT.
• Variants in homologous regions are hard to capture (regions with copy number variations (CNV)). Notably, the genes CYP2D6 and CYP2A6 are challenging. The CYP2D6 genotyping tool used by PharmCAT is Astrolabe.
• HLA-typing require special software. Yang et al. proposed to use Polysolver for whole exome sequencing (WES) or OptiType for whole genome sequencing (WGS). Reisberg et al. proposed SNP2HLA for WGS.
• New variants are discovered, and needs to be functionally assessed.

Solutions

Solutions for PGx on NGS data are given by Reisberg et al. in their article Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions.

Interesting publications

Institution	Article	Comments
St. Jude Children’s Research Hospital	Comparison of Genome Sequencing and Clinical Genotyping for Pharmacogenes	WES and WGS can be used for PGx with in silico CNV calling and HLA calling
National Human Genome Research Institute	Assessing the capability of massively parallel sequencing for opportunistic pharmacogenetic screening	Suggests developing tools for PGx based on WES and WGS
University of Washington	PGRNseq: A Targeted Capture Sequencing Panel for Pharmacogenetic Research and Implementation	Targeted PGx panel with 84 genes
University of Tartu	Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions	Well-described pipeline for PGx on biobank data. WES cannot be used for PGx (important variants missing, imputation and CNV calling difficult)