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Byline: Chitra. Rawat, Debleena. Guin, Puneet. Talwar, Sandeep. Grover, Ruchi. Baghel, Suman. Kushwaha, Sangeeta. Sharma, Rachna. Agarwal, Kiran. Bala, Achal. Srivastava, Ritushree. Kukreti Background: Nearly 40%-50% of the individuals fail [...]

Byline: Sangeeta. Sharma, Fauzia. Tabassum, Pradeep. Dwivedi, Rachna. Agarwal, Suman. Kushwaha, Kiran. Bala, Sandeep. Grover, Ruchi. Baghel, Ritushree. Kukreti, Chandra. Tripathi Context: Phenytoin (PHT) is one of the frontrunner drugs [...]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Radiation exposures (accidental or terrorist attack) are heterogeneous in dose distribution and may lead to an unpredictable level of partial-body irradiation. Earlier studies have shown differential response of whole body or partial body irradiation with few common observations. Further, it would also be worthwhile to observe response to single or fractionated dose of same radiation. Therefore, present study performed comparative account of single and fractionated dose of partial radiation exposure using NMR metabolomics. C57BL6 mice were exposed to 60Co gamma radiation in abdominal region only. Animals were divided in 3 groups i.e., SD group (single dose of radiation, 15Gy), FD group (15Gy in fractions 3Gy x 5 days) and sham controls. Post-irradiation, urine samples were collected on day1 and day3. NMR spectroscopy was performed on 600MHz spectrometer using NOESYPR sequence. After post-processing, univariate and multivariate statistical analysis was performed using metaboanalyst. Multivariate analysis (PCA, PLS-DA) showed separation of irradiated groups. FD cluster displayed some overlap with controls whereas; SD clusters were distinctly located at both the time intervals. The univariate analysis highlighted significant changes in identified metabolites. Metabolic changes more prominent in SD than FD group were as follows: Energy (Citrate, alpha-ketoglutarate, and succinate), gut microbial (phenylalanine and hippurate), membrane (choline, TMA), and citrulline in general. Taurine, a well-known biomarker of radiation exposure was significantly increased only in SD group indicating different metabolic response in the groups. The results further reflected better recovery of FD group over SD group and highlighted the severity of single dose over fractionated dose. [ABSTRACT FROM AUTHOR]

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 1 H 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.

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.