Genetic polymorphisms of CYP2C9, VKORC1, CYP4F2 and GGCX are important predictive factors of warfarin maintenance dose, and the developed algorithm will be useful to predict the required maintenance and/or starting warfarin dose in South Indian populations.

SUMMARYWhat is known and Objective: CYP2C19*17 allele increases the metabolic activity of CYP2C19 resulting in decreased therapeutic levels of CYP2C19 substrates. There exist inter-ethnic differences in the distribution of this allele. The present study was aimed at establishing the allele and genotype frequencies of CYP2C19*17 in a South Indian Tamilian population. Furthermore, we describe the haplotype structure of the three common variant alleles of CYP2C19 in the Tamilian population. Methods: Two hundred and six subjects of South Indian Tamilian origin were genotyped for CYP2C19*17 allele by nested polymerase chain reaction and restriction fragment length polymorphism. A subset of 87 subjects were also genotyped for CYP2C19*2 and CYP2C19*3 alleles. After ascertaining linkage disequilibrium (LD), haplotypes were constructed. Allele and genotype frequencies, LD pattern and haplotype frequency were compared with those of the HapMap populations. Results and Discussion: The CYP2C19*17 allele frequency in the Tamilian population (n = 206) was found to be 19AE2 (95 CI: 15AE4 -20AE3). The CYP2C19*2 allele frequency (n = 87) was found to be 40AE2 (95 CI: 32AE9 -47AE5), whereas the CYP2C19*3 allele was not detected in the study subjects (n = 97). The high frequency of the CYP2C19*17 allele in the study population has resulted in a revision of frequencies for CYP2C19*1/*2 (31AE0) and CYP2C19*1/*1 (16AE1) genotypes in the Tamilian population. We also observed significant differences in haplotype structure and frequencies of these variant alleles in the HapMap population compared to Tamilian population. What is new and conclusion: CYP2C19*17 allele is present at high frequency in the Tamilian population. This study also demonstrates the need for reassessment of wild-type allele frequencies in view of CYP2C19*17 allele. The estimated high frequency of CYP2C19*17 allele will aid in genotype-phenotype association studies in the Tamilian population. Further genotype-phenotype association studies are required to evaluate the clinical utility of this allele in South Indians. WHAT IS KNOWN AND OBJECTIVECYP2C19 is a clinically important enzyme that metabolizes a wide range of drugs such as omeprazole, fluoxetine, lansoprazole, S-mephenytoin, tolbutamide, voriconazole, diazepam and proguanil. 1 Variability in the metabolism and the therapeutic effect of CYP2C19 substrates can be attributed to the genetic polymorphisms of CYP2C19 gene. About 25 variant alleles have been reported (http://www.imm.ki.se/CYPalleles, access date: 20 February 2010), of which CYP2C19*2 (681G>A in exon 5, rs4244285) and CYP2C19*3 (636G>A in exon 4, rs4986893) are the most common alleles associated with decreased metabolism of CYP2C19 substrates. 2,3 Recently, a novel variant allele (CYP2C19*17, )806C>T and )3402C>T that are in linkage disequilibrium (LD) with each other) in the 5¢-flanking region has been found to be associated with increased CYP2C19 activity, resulting in ultra-rapid metabolism of CYP2C19 substrates. 4 Thus, subjects can be classified as...

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To refer to metabolomics as a new field is injustice to ancient doctors who used ants to diagnose the patients of diabetes having glycosuria. Measuring the levels of molecules in biological fluids believing them to be the representatives of biochemical pathways of carbohydrates, fats, proteins, nucleic acids or xenobiotic metabolism and deciphering meaningful data from it is what can be called as metabolomics, just as high glucose in urine suggests diabetes mellitus. Genomics, epigenetics, proteomics, transcriptomics finally converge to metabolomics, which are the signatures of mechanisms of bodily processes which is why understanding this science can have many applications. Just as a heap of stones does not make a house, having data of metabolite levels does not make it a science. Analyzing this data would help us in constructing biochemical pathways and their interactions. Analyzing the changes caused by a drug in the metabolite levels would help us in deriving the mechanisms by which the drug acts. Comparing metabolite levels in diseased with non-diseased, good-responders with poor-responders to a particular drug can help in identifying new markers of a disease or response to a drug respectively. Also, metabolite levels of an endogenous substrate can tell us the status of a person's metabolizing enzymes and help in drug dose titration. Generating hypothesis by identifying the new molecular markers and testing their utility in clinics seems to be the most promising approach in future. This review narrates the modes of quantifying and identifying metabolome, its proposed applications in diagnosis, monitoring and understanding the diseases and drug responses. We also intend to identify hindrances in using metabolomics in clinical studies or experiments.

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