ObjectivesTo develop a population specific pharmacogenetic acenocoumarol dosing algorithm for north Indian patients and show its efficiency in dosage prediction.MethodsMultiple and linear stepwise regression analyses were used to include age, sex, height, weight, body surface area, smoking status, VKORC1 -1639 G>A, CYP4F2 1347 G>A, CYP2C9*2,*3 and GGCX 12970 C>G polymorphisms as variables to generate dosing algorithms. The new dosing models were compared with already reported algorithms and also with the clinical data for various performance measures. Odds ratios for association of genotypes with drug sensitive and resistant groups were calculated.ResultsThe pharmacogenetic dosing algorithm generated by multiple regression analysis explains 41.4% (p-value <0.001) of dosage variation. Validation of the new algorithm showed its predictive ability to be better than the already established algorithms based on similar variables. Its validity in our population is reflected by increased sensitivity, specificity, accuracy and decreased rates of over- and under- estimation in comparison to clinical data. The VKORC1-1639 G>A polymorphism was found to be strongly associated with acenocoumarol sensitivity according to recessive model.ConclusionsWe have proposed an efficient north India specific pharmacogenetic acenocoumarol dosing algorithm which might become a baseline for personalised medicine approach for treatment of patients in future.
Rheumatic heart disease (RHD) is one of the most severe consequences of rheumatic fever. It has been suggested that angiotensin I-converting enzyme (ACE) may be involved in the increased valvular fibrosis and calcification in the pathogenesis of RHD. We conducted a case-control study to look for association of ACE I/D polymorphism with RHD in Indian population. The study incorporated 300 patients (170 males and 130 females) with RHD, and 200 controls (118 males and 82 females). We also subgrouped RHD patients into mitral valve lesion (MVL) and combined valve lesion (CVL). ACE I/D polymorphism was identified using polymerase chain reaction method. We also performed a meta-analysis of three published studies and the present study (636 RHD cases and 533 controls) to evaluate the association between the ACE I/D polymorphisms and RHD risk. A significant difference in ACE ID and DD genotypes distribution between RHD cases (OR = 1.62, 95% CI = 1.11-2.36 and OR = 2.08, 95% CI = 1.02-4.15, respectively) and corresponding controls was observed. On comparing the ACE genotypes of MVL and CVL subgroups with controls, ID and DD genotypes were also significantly associated with CVL (FDR Pcorr = 0.009, OR = 2.19 and FDR Pcorr = 0.014, OR = 3.29, respectively). Meta-analysis also suggested association of the ACE D allele (FDR Pcorr = 0.036, OR-1.22, 95% CI 1.02-1.45) with RHD. In conclusion, ACE ID and DD genotypes are associated with an increased risk of RHD, particularly CVL. This suggests that the ACE I/D gene polymorphism may play an important role in the pathogenesis of RHD.
The cytochrome P450 (CYP)4F2 gene is known to influence mean coumarin dose. The aim of the present study was to undertake a meta-analysis at the individual patients level to capture the possible effect of ethnicity, gene-gene interaction, or other drugs on the association and to verify if inclusion of CYP4F2*3 variant into dosing algorithms improves the prediction of mean coumarin dose. We asked the authors of our previous meta-analysis (30 articles) and of 38 new articles retrieved by a systematic review to send us individual patients' data. The final collection consists of 15,754 patients split into a derivation and validation cohort. The CYP4F2*3 polymorphism was consistently associated with an increase in mean coumarin dose (+9% (95% confidence interval (CI) 7-10%), with a higher effect in women, in patients taking acenocoumarol, and in white patients. The inclusion of the CYP4F2*3 in dosing algorithms slightly improved the prediction of stable coumarin dose. New pharmacogenetic equations potentially useful for clinical practice were derived.
Psittacula cyanocephala is an endemic parakeet from the Indian sub-continent that is widespread in the illegal bird trade. Previous studies on Psittacula parakeets have highlighted taxonomic ambiguities, warranting studies to resolve the issues. Since the mitochondrial genome provides useful information concerning the species evolution and phylogenetics, we sequenced the complete mitogenome of P. cyanocephala using NGS, validated 38.86% of the mitogenome using Sanger Sequencing and compared it with other available whole mitogenomes of Psittacula. The complete mitogenome of the species was 16814 bp in length with 54.08% AT composition. P. cyanocephala mitogenome comprises of 13 protein-coding genes, 2 rRNAs and 22 tRNAs. P. cyanocephala mitogenome organization was consistent with other Psittacula mitogenomes. Comparative codon usage analysis indicated the role of natural selection on Psittacula mitogenomes. Strong purifying selection pressure was observed maximum on nad1 and nad4l genes. The mitochondrial control region of all Psittacula species displayed the ancestral avian CR gene order. Phylogenetic analyses revealed the Psittacula genus as paraphyletic nature, containing at least 4 groups of species within the same genus, suggesting its taxonomic reconsideration. Our results provide useful information for developing forensic tests to control the illegal trade of the species and scientific basis for phylogenetic revision of the genus Psittacula.
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