Detection of CYP2C19 Genetic Variants in Malaysian Orang Asli from Massively Parallel Sequencing Data.

The human cytochrome P450 (CYP) is a superfamily of enzymes that have been a focus in research for decades due to their prominent role in drug metabolism. CYP2C is one of the major subfamilies which metabolize more than 10% of all clinically used drugs. In the context of CYP2C19, several key genetic variations that alter the enzyme's activity have been identified and catalogued in the CYP allele nomenclature database. In this study, we investigated the presence of well-established variants as well as novel polymorphisms in the CYP2C19 gene of 62 Orang Asli from the Peninsular Malaysia. A total of 449 genetic variants were detected including 70 novel polymorphisms; 417 SNPs were located in introns, 23 in upstream, 7 in exons, and 2 in downstream regions. Five alleles and seven genotypes were inferred based on the polymorphisms that were found. Null alleles that were observed include CYP2C19*3 (6.5%), *2 (5.7%) and *35 (2.4%) whereas allele with increased function *17 was detected at a frequency of 4.8%. The normal metabolizer genotype was the most predominant (66.1%), followed by intermediate metabolizer (19.4%), rapid metabolizer (9.7%) and poor metabolizer (4.8%) genotypes. Findings from this study provide further insights into the CYP2C19 genetic profile of the Orang Asli as previously unreported variant alleles were detected through the use of massively parallel sequencing technology platform. The systematic and comprehensive analysis of CYP2C19 will allow uncharacterized variants that are present in the Orang Asli to be included in the genotyping panel in the future.

Systematic characterization and comparison of the CYP2C9 variability of the Orang Asli in Malaysia with 12 populations.

We conducted a systematic characterization of CYP2C9 variants in 61 Orang Asli and 96 Singaporean Malays using the whole genome sequences data and compared the variants with the other 11 HapMap populations. The frequency of rs1057910 (CYP2C9*3) is the highest in the Orang Asli compared to other populations. Three alleles with clinical implication were detected in the Orang Asli while 2 were found in the Singaporean Malays. Large numbers of the Orang Asli are predicted to have reduced metabolic capacity and therefore they would require a lower dose of drugs which are metabolized by CYP2C9. They are also at increased risks of adverse effects and therapeutic failures. A large number of CYP2C9 variants in the Orang Asli were not in the Hardy Weinberg Equilibrium which could be due to small sample size or mutations that disrupt the equilibrium of allele frequencies. In conclusion, different polymorphism patterns, allele frequencies, genotype frequencies and LD blocks are observed between the Orang Asli, the Singaporean Malays and the other populations. The study provided new information on the genetic polymorphism of CYP2C9 which is important for the implementation of precision medicine for the Orang Asli.

Metabolomics and partial least square discriminant analysis to predict history of myocardial infarction of self-claimed healthy subjects: validity and feasibility for clinical practice.

BACKGROUND: The dynamics of metabolomics in establishing a prediction model using partial least square discriminant analysis have enabled better disease diagnosis; with emphasis on early detection of diseases. We attempted to translate the metabolomics model to predict the health status of the Orang Asli community whom we have little information. The metabolite expressions of the healthy vs. diseased patients (cardiovascular) were compared. A metabotype model was developed and validated using partial least square discriminant analysis (PLSDA). Cardiovascular risks of the Orang Asli were predicted and confirmed by biochemistry profiles conducted concurrently. RESULTS: Fourteen (14) metabolites were determined as potential biomarkers for cardiovascular risks with receiver operating characteristic of more than 0.7. They include 15S-HETE (AUC = 0.997) and phosphorylcholine (AUC = 0.995). Seven Orang Asli were clustered with the patients' group and may have ongoing cardiovascular risks and problems. This is supported by biochemistry tests results that showed abnormalities in cholesterol, triglyceride, HDL and LDL levels. CONCLUSIONS: The disease prediction model based on metabolites is a useful diagnostic alternative as compared to the current single biomarker assays. The former is believed to be more cost effective since a single sample run is able to provide a more comprehensive disease profile, whilst the latter require different types of sampling tubes and blood volumes.