Systematic untargeted UHPLC-Q-TOF-MS based lipidomics workflow for improved detection and annotation of lipid sub-classes in serum.

INTRODUCTION AND OBJECTIVE: Taking into consideration the challenges of lipid analytics, present study aims to design the best high-throughput workflow for detection and annotation of lipids. MATERIAL AND METHODS: Serum lipid profiling was performed on CSH-C18 and EVO-C18 columns using UHPLC Q-TOF-MS and generated lipid features were annotated based on m/z and fragment ion using different software. RESULT AND DISCUSSION: Better detection of features was observed in CSH-C18 than EVO-C18 with enhanced resolution except for Glycerolipids (triacylglycerols) and Sphingolipids (sphingomyelin). CONCLUSION: The study revealed an optimized untargeted Lipidomics-workflow with comprehensive lipid profiling (CSH-C18 column) and confirmatory annotation (LipidBlast).

Clinical predictors of treatment outcome in North Indian patients on antiepileptic drug therapy: A prospective observational study.

BACKGROUND: Nearly 40%-50% of the individuals fail to respond to first line antiepileptic drug (AED) monotherapy and 30% are refractory, which calls for the need to recognize predictive markers for treatment failure. This study aims to identify clinical factors predictive of a poor prognosis in patients on AED therapy. MATERIALS AND METHODS: A prospective follow-up study involving 1056 patients with epilepsy (PWE) aged 5-67 years from North India on phenytoin (PHT, n = 247), carbamazepine (CBZ, n = 369), valproate (VA, n = 271), phenobarbital (PB, n = 50), and multitherapy (MultiT, n = 119) was conducted between 2005 and 2015. Seizure and epilepsy types were diagnosed based on the classifications by the International League Against Epilepsy (ILAE). Patients remaining seizure-free during the past 1 year were assigned to the "no seizure" group and patients experiencing seizure recurrence were assigned to the "recurrent seizures" group. RESULTS: Of the total, 786 (74.4%) patients were successfully followed up with 60% achieving 1-year seizure remission. Seizure recurrence was observed in the remaining 40% of the patients with a high likelihood in patients with the disease onset at ≤5 years of age [55% vs. 38%, P = 0.0016, odds ratio (OR) = 2.02 (95% confidence interval (CI) = 1.31-3.13)], in patients with cryptogenic epilepsy than with idiopathic/symptomatic epilepsy (48% vs. 32%, P = 0.0049, OR = 1.61 [95% CI = 1.16-2.24]), and in patients with pretreatment seizure frequency ≥12/year (46% vs. 27%, P < 0.0001, OR = 2.21 [95% CI = 1.61-3.05]). Logistic regression analysis also revealed a significant association of seizure recurrence (P < 0.05) with the three variables. CONCLUSION: Our findings suggest that an early disease onset, cryptogenic epilepsy, and a higher pretreatment seizure frequency are related to a poor prognosis or poor remission in people with epilepsy (PWE) on AED therapy.

Critical appraisal of serum phenytoin variation with patient characteristics in a North Indian population.

CONTEXT: Phenytoin (PHT) is one of the frontrunner drugs used as monotherapy in the management of epilepsy. It is also one of the most common drugs causing adverse drug reactions (ADRs). The aim of this study was to study the relationship between serum PHT levels and the age, gender, dosage and genetic polymorphisms in a North Indian population. This knowledge will help in devising drug dosage schedules in various sub-groups of patients as well as in reducing its ADRs. MATERIALS AND METHODS: A retrospective analysis of data of 6224 patients from 1998 to 2009 receiving PHT alone for greater than (>) 4 weeks was performed. Patients suspected of being non-compliant, being overdosed or having a hepatic or renal disorder were excluded from the study. Two thousand eight hundred and eighty-eight patients fulfilling the inclusion criteria were divided into three groups: children (1-18 years), adults (19-60 years) and elderly (>60 years). RESULTS: There was a male preponderance (80%) in all the groups. A significant difference was found in the mean dose between children and adults as well as between children and elderly (P = 0.00). Also, there was a significant difference in the mean concentration and dose ratio between children and adults (P = 0.00). However, a negative correlation was observed between the daily dose and dose ratio (r = -0.36, P = 0.00) that was highest (r = -0.58, P = 0.00) in the elderly. There was a significant gender difference in the mean dose in both children (P = 0.03) and adults (P = 0.00), whereas the mean concentration differed in adults only. Every fifth patient was an intermediate metabolizer (IM) (CYP2C9FNx011/FNx013) and showed higher steady state drug levels (>17 mg/L) compared with extensive metabolizers (EMs) (<12 mg/L). The genetic difference between IM and EM was more prevalent in the dose ratio at maintenance dose, with a mean ± SD of 4.041 ± 1.288 mg/L/mg/kg in nine patients carrying the CYP2C9FNx011/FNx013 genotype compared with 2.145 ± 0.817 mg/L/mg/kg in 26 patients carrying the CYP2C9FNx011/FNx011 genotype (P = 0.00). CONCLUSION: North Indian female children and male adults frequently attain a higher serum concentration with the same dose when compared to the other groups. Absence of poor metabolizers may be responsible for a lower number of cases exhibiting toxicity in our population; however, this needs elucidation in a larger number of patients.

Synergistic association of PI4KA and GRM3 genetic polymorphisms with poor antipsychotic response in south Indian schizophrenia patients with low severity of illness.

Literature indicates key role of glutamatergic pathway genes in antipsychotic response among schizophrenia patients. However, molecular basis of their underlying role in antipsychotic response remained unexplained. Thus, to unravel their molecular underpinnings, we sought to investigate interactions amongst GRM3, SLC1A1, SLC1A2, SLC1A3, SLC1A4 gene polymorphisms with drug response in south Indian schizophrenia patients. We genotyped 48 SNPs from these genes in 423 schizophrenia patients stratified into low and high severity of illness groups. The SNPs and haplotypic combinations of associated SNPs were examined for their association with antipsychotic response. Multifactor-dimensionality-reduction was further used to explore gene-gene interaction among these SNPs and 53 SNPs from previously studied genes (BDNF, RGS4, SLC6A3, PI4KA, and PIP4K2A). Single SNP and haplotype analyses revealed no significant association with drug response irrespective of severity of illness. Gene-gene interaction analyses yielded promising leads, including an observed synergistic effect between PI4KA_rs165854 and GRM3_rs1468412 polymorphisms and incomplete antipsychotic response in schizophrenia patients with low severity of illness (OR = 12.4; 95%CI = 3.69-41.69). Further, this interaction was also observed in atypical monotherapy (n = 355) and risperidone (n = 260) treatment subgroups (OR = 11.21; 95%CI = 3.30-38.12 and OR = 13.5; 95%CI = 3.03-121.61 respectively). PI4KA is known to be involved in the biosynthesis of phosphatidylinositol-4, 5-bisphosphate which regulates exocytotic fusion of synaptic vesicles (glutamate, dopamine) with the plasma membrane and regulates duration of signal transduction of GPCRs. Whereas GRM3 regulates glutamate and dopamine transmission. Present findings indicate that PI4KA and GRM3 polymorphisms have potential to jointly modulate antipsychotic response. These results warrant additional replication studies to shed further light on these interactions.

Metabolomics and transcriptomics based multi-omics integration reveals radiation-induced altered pathway networking and underlying mechanism.

Recent advancement in integrated multi-omics has significantly contributed to many areas of the biomedical field. Radiation research has also grasped uprising omics technologies in biomarker identification to aid in triage management. Herein, we have used a combinatorial multi-omics approach based on transcriptomics together with metabolomics and lipidomics of blood from murine exposed to 1 Gy (LD) and 7.5 Gy (HD) of total-body irradiation (TBI) for a comprehensive understanding of biological processes through integrated pathways and networking. Both omics displayed demarcation of HD group from controls using multivariate analysis. Dysregulated amino acids, various PC, PE and carnitine were observed along with many dysregulated genes (Nos2, Hmgcs2, Oxct2a, etc.). Joint-Pathway Analysis and STITCH interaction showed radiation exposure resulted in changes in amino acid, carbohydrate, lipid, nucleotide, and fatty acid metabolism. Elicited immune response was also observed by Gene Ontology. BioPAN has predicted Elovl5, Elovl6 and Fads2 for fatty acid pathways, only in HD group. Collectively, the combined omics approach facilitated a better understanding of processes uncovering metabolic pathways. Presumably, this is the first in radiation metabolomics that utilized an integrated omics approach following TBI in mice. Our work showed that omics integration could be a valuable tool for better comprehending the mechanism as well as molecular interactions.

An integrative chemometric approach and correlative metabolite networking of LC-MS and 1H NMR based urine metabolomics for radiation signatures.

The increasing threat of nuclear terrorism or radiological accident has made high throughput radiation biodosimetry a requisite for the immediate response for triage. Owing to detection of subtle alterations in biological pathways before the onset of clinical conditions, metabolomics has become an important tool for studying biomarkers and the related mechanisms for radiation induced damage. Here, we have attempted to combine two detection techniques, LC-MS and 1H NMR spectroscopy, to obtain a comprehensive metabolite profile of urine at 24 h following lethal (7.5 Gy) and sub-lethal (5 Gy) irradiation in mice. Integrated data analytics using multiblock-OPLSDA (MB-OPLSDA), correlation networking and pathway analysis was used to identify metabolic disturbances associated with radiation exposure. MB-OPLSDA revealed better clustering and separation of irradiated groups compared with controls without overfitting (p-value of CV-ANOVA: 1.5 × 10-3). Metabolites identified through MB-OPLSDA, namely, taurine, creatine, citrate and 2-oxoglutarate, were found to be dose independent markers and further support and validate our earlier findings as potential radiation injury biomarkers. Integrated analysis resulted in the enhanced coverage of metabolites and better correlation networking in energy, taurine, gut flora, L-carnitine and nucleotide metabolism observed post irradiation in urine. Our study thus emphasizes the major advantage of using the two detection techniques along with integrated analysis for better detection and comprehensive understanding of disturbed metabolites in biological pathways.

Surveillance of adverse drug reactions at an adverse drug reaction monitoring centre in Central India: a 7-year surveillance study.

OBJECTIVES: To analyse and present the occurrence and severity of spontaneous adverse drug reaction (ADR) reports prospectively registered at an ADR monitoring centre (AMC) in Central India. SETTING AND DATA: The survey was conducted between 2013 and 2019 at an ADR Monitoring Centre in Central India. ADRs were recorded using the standard 'Suspected ADR Reporting form'. OUTCOME MEASURES: The causality of the ADRs were categorised using the WHO causality assessment scale to assess the relationship between a drug and the occurrence of an ADR. RESULTS: Totally 1980 spontaneous ADRs were reported involving 960 patients and 1316 drugs prescriptions. The occurrence of ADRs was common among male patients (64%) and patients of age between 19 and 65 years (81%). Antimicrobials caused 29% ADRs, followed by drugs of antiretroviral therapy (19%). Zidovudine caused most ADRs (88%) followed by ethambutol and ciprofloxacin. The ADRs of skin and subcutaneous tissue disorders (28%) were most common among all system organ classes followed by gastrointestinal systems (18%). Four per cent of all reported ADRs were severe. A peak of ADR reports was attained in 2016 with 224 reports, which decreased to 127 in 2019. CONCLUSION: A high number of ADRs caused by antimicrobials is an alarming situation, which adds up to antimicrobial resistance. Judicious use of antimicrobials is yet again proven as need of the hour. Under-reporting of ADRs is evident in our study and is a major factor for the delay in the withdrawal of drugs responsible for causing ADRs. Interventions in terms of training and feedback are suggested to encourage and improve ADR reporting.

Genetic variability in estrogen disposition: Potential clinical implications for neuropsychiatric disorders.

Variability in the physiological levels of neuroactive estrogens is widely believed to play a role in predisposition to several disorders of the central nervous system. Local biosynthesis of estrogens in the brain as well as their circulating serum levels are known to contribute to this pool of neuroactive steroids. It has been well accepted that estrogens modulate neuronal functions by affecting genesis, differentiation, excitability, and degeneration of nerve cells. These actions of estrogens appear to be more prominent in females with higher concentrations and marked variability of circulating serum levels occurring over a woman's lifetime. However, our knowledge regarding the variability of neuroactive steroid levels is very limited. Furthermore, several studies have recently reported differences in the synchronization of circulating and neuronal levels of estradiol. In the absence of reliable circulating steroid levels, knowledge of genetic variability in estrogen disposition may play a determining factor in predicting altered susceptibility or severity of neuropsychiatric disorders in women. Over the past decade, several genetic variants have been linked to both differential serum estrogen levels and predisposition to diverse types of neuropsychiatric disorders in women. Polymorphisms in genes encoding estrogen-metabolizing enzymes as well as estrogen receptors may account for this phenotypic variability. In this review, we attempt to show the contribution of genetics in determining estrogenicity in females with a particular emphasis on the central nervous system. This knowledge will further provide a driving force for unearthing the novel field of "Estrogen Pharmacogenomics." © 2010 Wiley-Liss, Inc.

Synergistic association of STX1A and VAMP2 with cryptogenic epilepsy in North Indian population.

INTRODUCTION: "Common epilepsies", merely explored for genetics are the most frequent, nonfamilial, sporadic cases in hospitals. Because of their much debated molecular pathology, there is a need to focus on other neuronal pathways including the existing ion channels. METHODS: For this study, a total of 214 epilepsy cases of North Indian ethnicity comprising 59.81% generalized, 40.19% focal seizures, and based on epilepsy types, 17.29% idiopathic, 37.38% cryptogenic, and 45.33% symptomatic were enrolled. Additionally, 170 unrelated healthy individuals were also enrolled. Here, we hypothesize the involvement of epilepsy pathophysiology genes, that is, synaptic vesicle cycle, SVC genes (presynapse), ion channels and their functionally related genes (postsynapse). An interactive analysis was initially performed in SVC genes using multifactor dimensionality reduction (MDR). Further, in order to understand the influence of ion channels and their functionally related genes, their interaction analysis with SVC genes was also performed. RESULTS: A significant interactive two-locus model of STX1A_rs4363087|VAMP2_rs2278637 (presynaptic genes) was observed among SVC variants in all epilepsy cases (P 1000-value = 0.054; CVC = 9/10; OR = 2.86, 95%CI = 1.88-4.35). Further, subgroup analysis revealed stronger interaction for the same model in cryptogenic epilepsy patients only (P 1000-value = 0.012; CVC = 10/10; OR = 4.59, 95%CI = 2.57-8.22). However, interactive analysis of presynaptic and postsynaptic genes did not show any significant association. CONCLUSIONS: Significant synergistic interaction of SVC genes revealed the possible functional relatedness of presynapse with pathophysiology of cryptogenic epilepsy. Further, to establish the clinical utility of the results, replication in a large and similar phenotypic group of patients is warranted.

Evaluating the Role of Genetic Variants on first-line antiepileptic drug response in North India: Significance of SCN1A and GABRA1 Gene Variants in Phenytoin Monotherapy and its Serum Drug Levels.

AIM: The present study aimed to evaluate association of genetic variants on drug response and therapy optimization parameters in patients treated with first-line antiepileptic drugs (AEDs). Genetic variants from ion channels, their functionally related genes, and synaptic vesicle cycle (SVC) genes with a potential role in epilepsy pathophysiology were thus prioritized. METHODS: A total of 12 genes from ion channels and related gene set and seven genes from SVC comprising 155 SNPs were genotyped and evaluated with drug response, dose levels, and drug levels in 408 patients with epilepsy. RESULTS: Both GABRA1 and SCN1A variants showed haplotypic and diplotypic associations in response to phenytoin (PHT). Diplotype analysis of GABRA1 variants revealed association of rs12658835|rs7735530 (AG/AG) (P-valuecorrected  = 0.034, OR = 3.75, 95% CI = 1.36-11.05) and rs12658835|rs7735530|rs7732641|rs2279020 (AGCA/AGCA) (P-valuecorrected  = 0.035, OR = 2.48, 95% CI = 0.96-6.41) with recurrent seizures. SCN1A haplotype rs6432860|rs3812718 (AC: P-valuecorrected  = 0.022, OR = 2.72, 95% CI = 1.39-5.35) and diplotype (AC/AC: P-valuecorrected  = 0.034, OR = 6.42, 95% CI = 1.10-65.76) were further observed to be associated with recurrent seizures. With respect to therapy optimization parameters, we observed significantly lower dose-adjusted drug levels at maximum dose of PHT in patients carrying AC/AC diplotype (P-value = 0.021). CONCLUSION: The results further substantiate the role of GABRA1 in PHT mode of action and contribution of SCN1A in response and therapy optimization with PHT monotherapy.

Evaluation of genetic association of neurodevelopment and neuroimmunological genes with antipsychotic treatment response in schizophrenia in Indian populations.

Neurodevelopmental and neuroimmunological genes critically regulate antipsychotic treatment outcome. We report genetic associations of antipsychotic response in 742 schizophrenia patients from Indian populations of Indo-European and Dravidian ancestry, segregated by disease severity. Meta-analysis comparing the two populations identified CCL2 [rs4795893: OR (95% CI) = 1.79 (1.27-2.52), P = 7.62 × 10(-4); rs4586: OR (95% CI) = 1.74 (1.24-2.43), P = 1.13 × 10(-3)] and GRIA4 [rs2513265: OR (95% CI) = 0.53 (0.36-0.78), P = 1.44 × 10(-3)] in low severity group; and, ADCY2 [rs1544938: OR (95% CI) = 0.36 (0.19-0.65), P = 7.68 × 10(-4)] and NRG1 [rs13250975, OR (95% CI) = 0.42 (0.23-0.79), P = 6.81 × 10(-3); rs17716295, OR (95% CI) = 1.78 (1.15-2.75), P = 8.71 × 10(-3)] in high severity group, with incomplete response toward antipsychotics. To our knowledge, this is the first study to identify genetic polymorphisms associated with the efficacy of antipsychotic treatment of schizophrenia patients from two major India populations.

Evidence for schizophrenia susceptibility alleles in the Indian population: An association of neurodevelopmental genes in case-control and familial samples.

Schizophrenia is a severe psychiatric disorder with lifetime prevalence of ~1% worldwide. A genotyping study was conducted using a custom panel of Illumina 1536 SNPs in 840 schizophrenia cases and 876 controls (351 patients and 385 controls from North India; and 436 patients, 401 controls and 143 familial samples with 53 probands containing 37 complete and 16 incomplete trios from South India). Meta-analysis of this population of Indo-European and Dravidian ancestry identified three strongly associated variants with schizophrenia: STT3A (rs548181, p=1.47×10(-5)), NRG1 (rs17603876, p=8.66×10(-5)) and GRM7 (rs3864075, p=4.06×10(-3)). Finally, a meta-analysis was conducted comparing our data with data from the Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ) that supported rs548181 (p=1.39×10(-7)). In addition, combined analysis of sporadic case-control association and a transmission disequilibrium test in familial samples from South Indian population identified three associations: rs1062613 (p=3.12×10(-3)), a functional promoter variant of HTR3A; rs6710782 (p=3.50×10(-3)), an intronic variant of ERBB4; and rs891903 (p=1.05×10(-2)), an intronic variant of EBF1. The results support the risk variants observed in the earlier published work and suggest a potential role of neurodevelopmental genes in the schizophrenia pathogenesis.

Pharmacogenomics of neuropsychiatric disorders: analysis of genetic variability in 162 identified neuroreceptors using 1000 Genomes Project data.

BACKGROUND: Neuroreceptors are considered to be primary drug targets and their abrupt signaling is a notable cause of interindividual drug response variability and treatment failure for complex neuropsychiatric diseases. In view of recent evidence, it is believed that common genetic risk factors mainly highly polymorphic neuroreceptors are being shared among neuropsychiatric disorders. MATERIALS & METHODS: We identified 162 neuroreceptors from the 639 known receptors in Homo sapiens and investigated 231,683 SNPs using 1000 Genomes Project data and evaluated their biological effect using in silico tools including RegulomeDB, SIFT, PolyPhen-2 and CAROL. Furthermore, data from the 1000 Genomes Project was utilized to retrieve minor allele frequency and calculate pairwise logartithm of the odds score among these SNPs for African, American, Asian and European populations separately as well as when combined together using Haploview v4.2. LRTag was used to identify tagSNPs in populations. RESULTS: A total of 52,381 (22.60%) SNPs were predicted as functionally important genetic variations. We identified sets of 603, 495, 450, 453 and 646 informative tagSNPs for African, American, Asian, European and combined populations, respectively. We propose construction of a 'neuroreceptor variants array' with these informative SNPs for future pharmacogenomic studies of neuropsychiatric disorders. CONCLUSION: Such an approach might improve genotype-phenotype correlation across different populations and lead to identification of reliable genetic markers and novel drug targets. Integration of these SNPs in literature would further provide evidence relevant to underlying mechanisms of genetics based nosology, pathophysiology and development of new drugs for the treatment of neuropsychiatric disorders.

Genetic variations of PIP4K2A confer vulnerability to poor antipsychotic response in severely ill schizophrenia patients.

Literature suggests that disease severity and neurotransmitter signaling pathway genes can accurately identify antipsychotic response in schizophrenia patients. However, putative role of signaling molecules has not been tested in schizophrenia patients based on severity of illness, despite its biological plausibility. In the present study we investigated the possible association of polymorphisms from five candidate genes RGS4, SLC6A3, PIP4K2A, BDNF, PI4KA with response to antipsychotic in variably ill schizophrenia patients. Thus in present study, a total 53 SNPs on the basis of previous reports and functional grounds were examined for their association with antipsychotic response in 423 schizophrenia patients segregated into low and high severity groups. Additionally, haplotype, diplotype, multivariate logistic regression and multifactor-dimensionality reduction (MDR) analyses were performed. Furthermore, observed associations were investigated in atypical monotherapy (n = 355) and risperidone (n = 260) treated subgroups. All associations were estimated as odds ratio (OR) and 95% confidence interval (CI) and test for multiple corrections was applied. Single locus analysis showed significant association of nine variants from SLC6A3, PIP4K2A and BDNF genes with incomplete antipsychotic response in schizophrenia patients with high severity. We identified significant association of six marker diplotype ATTGCT/ATTGCT (rs746203-rs10828317-rs7094131-rs2296624-rs11013052-rs1409396) of PIP4K2A gene in incomplete responders (corrected p-value = 0.001; adjusted-OR = 3.19, 95%-CI = 1.46-6.98) with high severity. These associations were further observed in atypical monotherapy and risperidone sub-groups. MDR approach identified gene-gene interaction among BDNF_rs7103411-BDNF_rs1491851-SLC6A3_rs40184 in severely ill incomplete responders (OR = 7.91, 95%-CI = 4.08-15.36). While RGS4_rs2842026-SLC6A3_rs2975226 interacted synergistically in incomplete responders with low severity (OR = 4.09, 95%-CI = 2.09-8.02). Our findings provide strong evidence that diplotype ATTGCT/ATTGCT of PIP4K2A gene conferred approximately three-times higher incomplete responsiveness towards antipsychotics in severely ill patients. These results are consistent with the known role of phosphatidyl-inositol-signaling elements in antipsychotic action and outcome. Findings have implication for future molecular genetic studies as well as personalized medicine. However more work is warranted to elucidate underlying causal biological pathway.

Genetic polymorphisms of drug-metabolizing phase I enzymes CYP2E1, CYP2A6 and CYP3A5 in South Indian population.

CYP2E1, CYP2A6 and CYP3A5 enzymes belong to phase I group of drug-metabolizing enzymes, which are involved in the metabolism of various compounds and xenobiotics. Presence of polymorphisms in the genes coding for these enzymes results in interindividual variations in drug metabolism, therapeutic response and susceptibility towards various diseases. The frequencies of these variants in genes differ considerably between ethnic groups. This study was carried out to estimate the allele and genotype frequencies of common variants in CYP2E1, CYP2A6 and CYP3A5 in South Indian population. Six hundred and fifty-two unrelated healthy volunteers of South Indian origin (Andhra Pradesh, Karnataka, Kerala and Tamil Nadu) were included in this study. Polymerase chain reaction-restriction fragment length polymorphism, allele-specific PCR, real-time PCR, SNaPshot and gene sequencing methods were used for the identification of gene polymorphisms. The frequencies of CYP2E1*1B, CYP2E1*5B and CYP2E1*6 alleles in South Indian population were 14.3, 1.3 and 22.4%, respectively. The frequencies of CYP2A6*2, CYP2A6*4A and CYP2A6*5 alleles were found to be 1, 8.9 and 0.7%, respectively. The distribution of CYP3A5*3 allele was 63.5%. There were no variant alleles of CYP3A5*2, CYP3A5*4 and CYP3A5*6 in South Indian population. The frequencies of CYP2E1, CYP2A6 and CYP3A5 in the South Indian population are distinct from Caucasians, Chinese, Japanese, African Americans and other compared populations. This is the first study conducted in the South Indian population with a larger sample size. The findings of our study provide the basic genetic information for further pharmacogenomic investigations in the population.

Absence of a general association between ABCB1 genetic variants and response to antiepileptic drugs in epilepsy patients.

Over-expression of efflux transporter P-glycoprotein (PgP) encoded by ABCB1 gene has been implicated in poor responsive epilepsy. Several genetic variants have been shown to influence the expression levels of P-glycoprotein. The aim of the present study was to investigate the role of ABCB1 polymorphisms: C1236T, G2677T/A and C3435T in determining drug response to first line antiepileptic drugs (AEDs) namely phenobarbitone, phenytoin, carbamazepine and valproate in North Indian cohort of epilepsy patients. DNA samples were obtained from 392 consecutive epilepsy patients, out of which 228 had completed follow-up evaluation at 12 months. After attaining steady state of the AEDs in the first two months of study, 133 patients showed complete freedom from seizures (no-seizure group) and 95 patients continued to have seizures (recurrent-seizures group) in the remaining period of study. Comparison of "no-seizure" and "recurrent-seizures" groups revealed no significant differences in allelic, genotypic and haplotypic frequencies for all the studied variants. In conclusion, our finding disproves a general association between ABCB1 polymorphisms and drug response in epilepsy patients.

Genetic polymorphisms in sex hormone metabolizing genes and drug response in women with epilepsy.

AIMS: It is hypothesized that functionally relevant polymorphisms in genes encoding metabolizing enzymes of sex steroids may influence drug response by directly predisposing women with epilepsy to seizure exacerbation. An alteration in estradiol:progesterone ratio is believed to play a role in seizure occurrence in women. CYP1A1 is a key enzyme involved in the metabolism of estradiol, with variants of the CYP1A1 gene having been reported to play a role in the alteration of sex hormone metabolism in women. The objective of the present study was to test for the association of genetic variants in CYP1A1 with seizure recurrence in patients diagnosed with epilepsy. MATERIALS & METHODS: In the study, the association of five variants in CYP1A1 with seizure control in 228 patients with epilepsy on first-line antiepileptic drug therapy for a minimum period of 12 months was investigated. RESULTS: A significant association of an intronic SNP, IVS1 +606C>A (rs2606345), with respect to seizure recurrence (genotypic: p = 3.3 × 10(-4); allelic: p = 7.2 × 10(-4); OR: 2.86; 95% CI: 1.5-5.3) in women with epilepsy from North India was observed. CONCLUSION: Since CYP1A1 is not involved in the metabolism of any of the first-line antiepileptic drugs, these results imply that variants from genes encoding sex hormone metabolizing enzymes might act as markers for predicting response to antiepileptic drug therapy in women with epilepsy.

Genetic profile of patients with epilepsy on first-line antiepileptic drugs and potential directions for personalized treatment.

BACKGROUND: The first-line antiepileptic drugs, although affordable and effective in the control of seizures, are associated with adverse drug effects, and there is large interindividual variability in the appropriate dose at which patients respond favorably. This variability may partly be explained by functional consequences of genetic polymorphisms in the drug-metabolizing enzymes, such as the CYP450 family, microsomal epoxide hydrolase and UDP-glucuronosyltransferases, drug transporters, mainly ATP-binding cassette transporters, and drug targets, including sodium channels. The purpose of this study was to determine the allele and genotype frequencies of such genetic variants in patients with epilepsy from North India administered first-line antiepileptic drugs, such as phenobarbitone, phenytoin, carbamazepine and valproic acid, and compare them with worldwide epilepsy populations. MATERIALS & METHODS: SNP screening of 19 functional variants from 12 genes in 392 patients with epilepsy was carried out, and the patients were classified with respect to the metabolizing rate of their drug-metabolizing enzymes, efflux rate of drug transporters and sensitivity of drug targets. RESULTS: A total of 16 SNPs were found to be polymorphic, and the allelic frequencies for these SNPs were in conformance with Hardy-Weinberg equilibrium. Among all the polymorphisms studied, functional variants from genes encoding CYP2C19, EPHX1, ABCB1 and SCN1A were highly polymorphic in North Indian epilepsy patients, and might account for differential drug response to first-line antiepileptic drugs. CONCLUSION: Interethnic differences were elucidated for several polymorphisms that might be responsible for differential serum drug levels and optimal dose requirement for efficacious treatment.