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.

Systematic pharmacogenomics analysis of a Malay whole genome: proof of concept for personalized medicine.

BACKGROUND: With a higher throughput and lower cost in sequencing, second generation sequencing technology has immense potential for translation into clinical practice and in the realization of pharmacogenomics based patient care. The systematic analysis of whole genome sequences to assess patient to patient variability in pharmacokinetics and pharmacodynamics responses towards drugs would be the next step in future medicine in line with the vision of personalizing medicine. METHODS: Genomic DNA obtained from a 55 years old, self-declared healthy, anonymous male of Malay descent was sequenced. The subject's mother died of lung cancer and the father had a history of schizophrenia and deceased at the age of 65 years old. A systematic, intuitive computational workflow/pipeline integrating custom algorithm in tandem with large datasets of variant annotations and gene functions for genetic variations with pharmacogenomics impact was developed. A comprehensive pathway map of drug transport, metabolism and action was used as a template to map non-synonymous variations with potential functional consequences. PRINCIPAL FINDINGS: Over 3 million known variations and 100,898 novel variations in the Malay genome were identified. Further in-depth pharmacogenetics analysis revealed a total of 607 unique variants in 563 proteins, with the eventual identification of 4 drug transport genes, 2 drug metabolizing enzyme genes and 33 target genes harboring deleterious SNVs involved in pharmacological pathways, which could have a potential role in clinical settings. CONCLUSIONS: The current study successfully unravels the potential of personal genome sequencing in understanding the functionally relevant variations with potential influence on drug transport, metabolism and differential therapeutic outcomes. These will be essential for realizing personalized medicine through the use of comprehensive computational pipeline for systematic data mining and analysis.