OBJECTIVE: The goal of this study was to determine the frequencies of SNPs rs1042114, rs702764, rs1997794, rs1022563 and rs910080 in the Malaysian population and to study their association with opioid dependence in Malaysian Malays.
METHODS: A total of 459 Malay male with opioid dependence and 543 healthy male (controls) subjects were included in this study. SNPs were genotyped using the TaqMan SNP genotyping assay. Statistical analysis was performed using Golden Helix SVS software suite to identify the distribution of allele and genotype frequencies, and SNP-SNP interactions were also analysed in this study.
RESULTS AND DISCUSSION: SNP rs1042114 in the OPRD1 gene is strongly associated with opiate addiction (P=.0001). In individuals homozygous for this risk allele, the likelihood of opiate addiction is increased by a factor 1.62 (95% confidence interval (CI) 1.412-1.875). Polymorphic alleles at SNP rs702764 of OPRK1 were not associated with opioid dependence. A significant association between opioid dependence and SNP rs910080 of PDYN (P=.0217) was detected, but there was no association for SNPs rs199774 and rs1022563. A significant interaction was also identified between homozygous wild-type genotype TT of rs702764 with the risk genotypes TG/GG of rs1042114 (odds ratio (OR)=2.111 (95% CI 1.227-3.631), P=.0069) and with the risk genotypes GA/AA of rs910080 (OR=1.415 (95% CI 1.04-1.912), P=.0239).
WHAT IS NEW AND CONCLUSION: The results indicate that SNPs rs1042114 and rs910080 contribute to vulnerability to opioid dependence in the Malaysian Malay population. These results will help us to understand the effect of the SNPs and the SNP-SNP interaction on opioid dependence and may assist in efforts to screen vulnerable individuals and match them with individually tailored prevention and treatment strategies.
METHODS: We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow.
RESULTS: We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population.
CONCLUSION: Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.
METHODS: Two-hundred unrelated Emirati parents of patients selected for bone marrow transplantation were genotyped for HLA class I (A, B, C) and class II (DRB1, DQB1) genes using reverse sequence specific oligonucleotide bead-based multiplexing. HLA haplotypes were assigned with certainty by segregation (pedigree) analysis, and haplotype frequencies were obtained by direct counting. HLA class I and class II frequencies in Emiratis were compared to data from other populations using standard genetic distances (SGD), Neighbor-Joining (NJ) phylogenetic dendrograms, and correspondence analysis.
RESULTS: The studied HLA loci were in Hardy-Weinberg Equilibrium. We identified 17 HLA-A, 28 HLA-B, 14 HLA-C, 13 HLA-DRB1, and 5 HLA-DQB1 alleles, of which HLA-A*02 (22.2%), -B*51 (19.5%), -C*07 (20.0%), -DRB1*03 (22.2%), and -DQB1*02 (32.8%) were the most frequent allele lineages. DRB1*03~DQB1*02 (21.2%), DRB1*16~DQB1*05 (17.3%), B*35~C*04 (11.7%), B*08~DRB1*03 (9.7%), A*02~B*51 (7.5%), and A*26~C*07~B*08~DRB1*03~DQB1*02 (4.2%) were the most frequent two- and five-locus HLA haplotypes. Correspondence analysis and dendrograms showed that Emiratis were clustered with the Arabian Peninsula populations (Saudis, Omanis and Kuwaitis), West Mediterranean populations (North Africans, Iberians) and Pakistanis, but were distant from East Mediterranean (Turks, Albanians, Greek), Levantine (Syrians, Palestinians, Lebanese), Iranian, Iraqi Kurdish, and Sub-Saharan populations.
CONCLUSIONS: Emiratis were closely related to Arabian Peninsula populations, West Mediterranean populations and Pakistanis. However, the contribution of East Mediterranean, Levantine Arab, Iranian, and Sub-Saharan populations to the Emiratis' gene pool appears to be minor.