The Identification of Novel Variants in US Hmong: Results From Genome Sequencing and Clinical Genotyping.

Hmong individuals represent a unique East Asian subpopulation in whom limited information concerning pharmacogenetic variation exists. The objectives of this study were to comprehensively characterize the highly polymorphic gene in Hmong, estimate allele and phenotype frequencies and to compare results between two testing platforms. DNA from 48 self-identified Hmong participants were sequenced using a targeted next-generation sequencing (NGS) panel. Star allele calls were made using Astrolabe, manual inspection of NGS variant calls and confirmatory Sanger sequencing. Structural variation was determined by long-range (XL)-PCR and digital droplet PCR (ddPCR). The consensus diplotypes were subsequently translated into phenotype utilizing the activity score system. Clinical grade pharmacogenetic testing was obtained for 12 of the 48 samples enabling an assessment of concordance between the consensus calls and those determined by clinical testing platforms. A total of 13 alleles were identified. The most common alleles were and its structural arrangements (37.5%, 36/96) and the gene deletion (13.5%, 13/96). Three novel suballeles (, , and ) were also identified. Phenotype frequencies were as follows: ultrarapid metabolizers (4.2%, 2/48), normal metabolizers (41.7%, 20/48) and intermediate metabolizers (52.1%, 25/48); none of the 48 participants were predicted to be poor metabolizers. Concordance of diplotype and phenotype calls between the consensus and clinical testing were 66.7 and 50%, respectively. Our study to explore genotypes in the Hmong population suggests that this subpopulation is unique regarding allelic variants; also, a higher portion of Hmong participants (50%) are predicted to have an intermediate metabolizer phenotype for CYP2D6 compared to other East Asians which range between 27 and 44%. Results from different testing methods varied considerably. These preliminary findings underscore the importance of thoroughly interrogating unique subpopulations to accurately predict a patient's metabolizer status.