Biomedical subjects

Shama C Buch

Publications and source records attributed to Shama C Buch.

4 recordsLinked to original sources

PubMed2005

Strategies for measurement of biotransformation enzyme gene expression.

The analysis of gene expression is an integral part of any research characterizing gene function. A wide variety of techniques have been developed for this purpose, each with their own advantages and limitations. This chapter seeks to provide an overview of some of the most recent as well as conventional methods to quantitate gene expression. These approaches include Northern blot analysis, ribonuclease protection assay (RPA), reverse transcription polymerase chain reaction, expressed sequence tag (EST) sequencing, differential display, cDNA arrays, and the serial analysis of gene expression (SAGE). Current applications of the information derived from gene expression studies require assays to be adaptable for the quantitative analysis of a large number of samples and end points within a short period coupled with cost effectiveness. A comparison of some of these features of each analytical approach as well as their advantages and disadvantages has also been provided.

Animals↗

PubMed2005

Genotyping technologies: application to biotransformation enzyme genetic polymorphism screening.

Pharmacogenomics encompasses several major areas: the study of polymorphic variations in drug response and disease susceptibility, identification of the effects of drugs/xenobiotics at the genomic level, and genotype/phenotype associations. The most common type of human genetic variations is single-nucleotide polymorphisms (SNPs). Several novel approaches to detection of SNPs are currently available. The range of new methods includes modifications of several conventional techniques, such as PCR, mass spectrometry (ms), and sequencing, as well as more innovative technologies such as fluorescence resonance energy transfer (FRET) and microarrays. The application of each of these techniques is largely dependent on the number of SNPs to be screened and sample size. The current chapter presents an overview of the general concepts of a variety of genotyping technologies, with an emphasis on the recently developed methodologies, including a comparison of the advantages, applicability, cost efficiency, and limitations of these methods.

Biotransformation↗

PubMed2004

Bioequivalence revisited: influence of age and sex on CYP enzymes.

BACKGROUND AND OBJECTIVE: The activity of cytochrome P450 (CYP) enzymes, which determine the rate of elimination of lipid-soluble drugs, demonstrates considerable interindividual variability. The extent to which age and sex influence CYP activity remains unclear in humans. Our objectives were to determine whether in vivo activity of selected CYP enzymes is affected by age or sex and to evaluate sex bioequivalence in a large sample size. METHODS: We have assessed in vivo activity of the CYP1A2, 2C19, 2D6, 2E1, and 3A4 enzymes in 161 normal subjects (51% female subjects and 40% aged >50 years). After simultaneous administration of a cocktail of selective probes (caffeine, mephenytoin, debrisoquin [INN, debrisoquine], chlorzoxazone, and dapsone, respectively), phenotypic indices for metabolism of these drugs were used as measures of individual CYP activity. Sex bioequivalence analysis used the bootstrap method. RESULTS: There were no sex differences associated with CYP1A2 activity. A significant negative correlation (r = -0.572, P < .01) between enzyme activity and age was observed for CYP2C19, but there were no sex differences. CYP2D6 activity showed no dependence on age or sex. In contrast, CYP2E1 activity showed an age-associated increase (r = 0.393, P < .01), which developed earlier in life in male subjects compared with female subjects. These results were further supported by the sex bioequivalence analysis of CYP phenotypic activity, which revealed that sexes were equivalent with respect to CYP2C19 (90% confidence interval [CI], 0.874-1.04), CYP3A4 (90% CI, 0.95-1.176), and CYP2D6 (90% CI, 0.928-1.09) phenotype and just exceeded the 0.8 to 1.25 limits to be equivalent with respect to CYP2E1 (90% CI, 0.785-1.08) and CYP1A2 (90% CI, 0.736-1.03) phenotype. CONCLUSION: These observations suggest that the presence of selective mechanisms of regulation for individual CYP enzymes can be influenced by age and sex. However, we suggest that sex has a limited ability to explain intersubject variation of activity for these phenotypic measures of CYP enzyme activity.

Adolescent↗

PubMed2002

Polymorphism at GSTM1, GSTM3 and GSTT1 gene loci and susceptibility to oral cancer in an Indian population.

This study evaluates the influence of genetic polymorphism at GSTM1, GSTM3 and GSTT1 gene loci on oral cancer risk among Indians habituated to the use of, smokeless tobacco, bidi or cigarette. DNA extracted from white blood cells of 297 cancer patients and 450 healthy controls by the proteinase K phenol-chloroform extraction procedure were analyzed by the polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism (RFLP) analyses. Lifetime tobacco exposure was evaluated as a risk factor in relation to the polymorphism at the GST gene loci using logistic regression analysis. There was no significant difference in the distribution of the GSTM3 and GSTT1 genotypes between oral cancer patients and controls. In contrast, a significant 3-fold increase in risk was seen for patients with the GSTM1 null genotype (age adjusted OR = 3.2, 95% CI 2.4-4.3). The impact of the GSTM1 null genotype on oral cancer risk was also analyzed in separate groups of individuals with different tobacco habits. The odds ratio associated with the GSTM1 null genotype was 3.7 (95% CI 2.0-7.1) in tobacco chewers, 3.7 (5% CI 1.3-7.9) in bidi smokers and 5.7 (95% CI 2.0-16.3) in cigarette smokers. Furthermore, increased lifetime exposure to chewing tobacco appeared to be associated with a 2-fold increase in oral cancer risk in GSTM1 null individuals. The results suggest that the GSTM1 null genotype is a risk factor for development of oral cancer among Indian tobacco habitues.

Case-Control Studies↗