69 research outputs found

    Oxidative Stress: Role and Response of Short Guanine Tracts at Genomic Locations

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    Over the decades, oxidative stress has emerged as a major concern to biological researchers. It is involved in the pathogenesis of various lifestyle-related diseases such as hypertension, diabetes, atherosclerosis, and neurodegenerative diseases. The connection between oxidative stress and telomere shortening via oxidative guanine lesion is well documented. Telomeres are confined to guanine rich ends of chromosomes. Owing to its self-association properties, it adopts G-quadruplex structures and hampers the overexpression of telomerase in the cancer cells. Guanine, being the most oxidation prone nucleobase, when structured in G-quadruplex entity, is found to respond peculiarly towards oxidative stress. Interestingly, this non-Watson-Crick structural feature exists abundantly in promoters of various oncogenes, exons and other genomic locations. The involvement of G-quadruplex architecture in oncogene promoters is well recognized in gene regulation processes. Development of small molecules aimed to target G-quadruplex structures, have found to alter the overexpression of oncogenes. The interaction may lead to the obstruction of diseased cell having elevated level of reactive oxygen species (ROS). Thus, presence of short guanine tracts (Gn) forming G-quadruplexes suggests its critical role in oxidative genome damage. Present review is a modest attempt to gain insight on the association of oxidative stress and G-quadruplexes, in various biological processes

    Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease

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    BACKGROUND: Alzheimer’s disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling. RESULTS: Our approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (S(R)) based method followed by prioritization using clusters derived from PPI network. S(R) for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes. CONCLUSIONS: With the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers than candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-199) contains supplementary material, which is available to authorized users

    Calendario para el Reyno de Valencia...: Año 1902

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    Microfilme. Valencia : BV, ca. 1990Recurso electrĂłnico. Valencia : BVNP, 20141902_A_95667

    Downregulation of peripheral PTGS2/COX-2 in response to valproate treatment in patients with epilepsy

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    Antiepileptic drug therapy has significant inter-patient variability in response towards it. The current study aims to understand this variability at the molecular level using microarray-based analysis of peripheral blood gene expression profiles of patients receiving valproate (VA) monotherapy. Only 10 unique genes were found to be differentially expressed in VA responders (n = 15) and 6 genes in the non-responders (n = 8) (fold-change >2, p < 0.05). PTGS2 which encodes cyclooxygenase-2, COX-2, showed downregulation in the responders compared to the non-responders. PTGS2/COX-2 mRNA profiles in the two groups corresponded to their plasma profiles of the COX-2 product, prostaglandin E(2) (PGE(2)). Since COX-2 is believed to regulate P-glycoprotein (P-gp), a multidrug efflux transporter over-expressed at the blood-brain barrier (BBB) in drug-resistant epilepsy, the pathway connecting COX-2 and P-gp was further explored in vitro. Investigation of the effect of VA upon the brain endothelial cells (hCMEC/D3) in hyperexcitatory conditions confirmed suppression of COX-2-dependent P-gp upregulation by VA. Our findings suggest that COX-2 downregulation by VA may suppress seizure-mediated P-gp upregulation at the BBB leading to enhanced drug delivery to the brain in the responders. Our work provides insight into the association of peripheral PTGS2/COX-2 expression with VA efficacy and the role of COX-2 as a potential therapeutic target for developing efficacious antiepileptic treatment

    Global text mining and development of pharmacogenomic knowledge resource for precision medicine

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    Understanding patients' genomic variations and their effect in protecting or predisposing them to drug response phenotypes is important for providing personalized healthcare. Several studies have manually curated such genotype-phenotype relationships into organized databases from clinical trial data or published literature. However, there are no text mining tools available to extract high-accuracy information from such existing knowledge. In this work, we used a semiautomated text mining approach to retrieve a complete pharmacogenomic (PGx) resource integrating disease-drug-gene-polymorphism relationships to derive a global perspective for ease in therapeutic approaches. We used an R package, pubmed.mineR, to automatically retrieve PGx-related literature. We identified 1,753 disease types, and 666 drugs, associated with 4,132 genes and 33,942 polymorphisms collated from 180,088 publications. With further manual curation, we obtained a total of 2,304 PGx relationships. We evaluated our approach by performance (precision = 0.806) with benchmark datasets like Pharmacogenomic Knowledgebase (PharmGKB) (0.904), Online Mendelian Inheritance in Man (OMIM) (0.600), and The Comparative Toxicogenomics Database (CTD) (0.729). We validated our study by comparing our results with 362 commercially used the US- Food and drug administration (FDA)-approved drug labeling biomarkers. Of the 2,304 PGx relationships identified, 127 belonged to the FDA list of 362 approved pharmacogenomic markers, indicating that our semiautomated text mining approach may reveal significant PGx information with markers for drug response prediction. In addition, it is a scalable and state-of-art approach in curation for PGx clinical utility

    Genetic landscape of common epilepsies: advancing towards precision in treatment

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    Epilepsy, a neurological disease characterized by recurrent seizures, is highly heterogeneous in nature. Based on the prevalence, epilepsy is classified into two types: common and rare epilepsies. Common epilepsies affecting nearly 95% people with epilepsy, comprise generalized epilepsy which encompass idiopathic generalized epilepsy like childhood absence epilepsy, juvenile myoclonic epilepsy, juvenile absence epilepsy and epilepsy with generalized tonic-clonic seizure on awakening and focal epilepsy like temporal lobe epilepsy and cryptogenic focal epilepsy. In 70% of the epilepsy cases, genetic factors are responsible either as single genetic variant in rare epilepsies or multiple genetic variants acting along with different environmental factors as in common epilepsies. Genetic testing and precision treatment have been developed for a few rare epilepsies and is lacking for common epilepsies due to their complex nature of inheritance. Precision medicine for common epilepsies require a panoramic approach that incorporates polygenic background and other non-genetic factors like microbiome, diet, age at disease onset, optimal time for treatment and other lifestyle factors which influence seizure threshold. This review aims to comprehensively present a state-of-art review of all the genes and their genetic variants that are associated with all common epilepsy subtypes. It also encompasses the basis of these genes in the epileptogenesis. Here, we discussed the current status of the common epilepsy genetics and address the clinical application so far on evidence-based markers in prognosis, diagnosis, and treatment management. In addition, we assessed the diagnostic predictability of a few genetic markers used for disease risk prediction in individuals. A combination of deeper endo-phenotyping including pharmaco-response data, electro-clinical imaging, and other clinical measurements along with genetics may be used to diagnose common epilepsies and this marks a step ahead in precision medicine in common epilepsies management

    Study of the single nucleotide polymorphism (SNP) at the palindromic sequence of hypersensitive site (HS)4 of the human β-globin locus control region (LCR) in Indian population

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    LCR, a genetic regulatory element, was examined in β-thalassemia patients who do not show any mutation in the β-globin genes. We sequenced LCR-HS2, HS3, and HS4 in samples from 16 such patients from the Indian population and found only one SNP A-G in the inverted repeat in HS4. A significant association was observed between the G allele and occurrence of β-thalassemia by Fisher's exact test. The AG and GG genotypes showed higher relative risk as compared to the AA genotype. We also observed linkage disequilibrium between the A/G polymorphism and the AT-rich motif of the LCR HS2 region, suggesting that the G allele could be an evolutionarily new mutation in the study population

    Catechol-O-Methyltransferase Val158Met Polymorphism and Clinical Response to Antipsychotic Treatment in Schizophrenia and Schizo-Affective Disorder Patients: a Meta-Analysis

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    BACKGROUND: The catechol-O-methyltransferase (COMT) enzyme plays a crucial role in dopamine degradation, and the COMT Val158Met polymorphism (rs4680) is associated with significant differences in enzymatic activity and consequently dopamine concentrations in the prefrontal cortex. Multiple studies have analyzed the COMT Val158Met variant in relation to antipsychotic response. Here, we conducted a meta-analysis examining the relationship between COMT Val158Met and antipsychotic response. METHODS: Searches using PubMed, Web of Science, and PsycInfo databases (03/01/2015) yielded 23 studies investigating COMT Val158Met variation and antipsychotic response in schizophrenia and schizo-affective disorder. Responders/nonresponders were defined using each study's original criteria. If no binary response definition was used, authors were asked to define response according to at least 30% Positive and Negative Syndrome Scale score reduction (or equivalent in other scales). Analysis was conducted under a fixed-effects model. RESULTS: Ten studies met inclusion criteria for the meta-analysis. Five additional antipsychotic-treated samples were analyzed for Val158Met and response and included in the meta-analysis (ntotal=1416). Met/Met individuals were significantly more likely to respond than Val-carriers (P=.039, ORMet/Met=1.37, 95% CI: 1.02-1.85). Met/Met patients also experienced significantly greater improvement in positive symptoms relative to Val-carriers (P=.030, SMD=0.24, 95% CI: 0.024-0.46). Posthoc analyses on patients treated with atypical antipsychotics (n=1207) showed that Met/Met patients were significantly more likely to respond relative to Val-carriers (P=.0098, ORMet/Met=1.54, 95% CI: 1.11-2.14), while no difference was observed for typical-antipsychotic-treated patients (n=155) (P=.65). CONCLUSIONS: Our findings suggest that the COMT Val158Met polymorphism is associated with response to antipsychotics in schizophrenia and schizo-affective disorder patients. This effect may be more pronounced for atypical antipsychotics.C.C.Z. is supported by the Brain and Behavior Research Foundation, American Foundation for Suicide Prevention and Eli Lilly. D.F. is supported by the Vanier Canada Graduate Scholarship. D.J.M. has been or is supported by the Canadian Institute of Health Research (CIHR) Operating Grant: “Genetics of antipsychotic-induced metabolic syndrome,” Michael Smith New Investigator Salary Prize for Research in Schizophrenia, NARSAD Independent Investigator Award by the Brain & Behavior Research Foundation, and Early Researcher Award from Ministry of Research and Innovation of Ontario. E.H. is supported by the Canada Graduate Scholarship. H.Y.M. has grant support from Sumitomo Dainippon, Sunovion, Boehringer Ingelheim, Eli Lilly, Janssen, Reviva, Alkermes, Auspex, and FORUM. J.A.L. has received research funding from Alkermes, Biomarin, EnVivo/Forum, Genentech, and Novartis. J.L.K. is supported the CIHR grant “Strategies for gene discovery in schizophrenia: subphenotypes, deep sequencing and interaction.” J.R.B. is supported by NIH grant MH083888. A.K.T. is supported by a NARSAD Young Investigator Award. J.S. is supported by a Pfizer independent grant. P.M. receives salary from Clinica Universidad de Navarra and has received research grants from the Ministry of Education (Spain), the Government of Navarra (Spain), the Spanish Foundation of Psychiatry and Mental Health, and Astrazeneca. S.G. is supported by the Ningbo Medical Technology Project Fund (No. 2004050), the Natural Science Foundation of Ningbo (No. 2009A610186, No. 2013A610249), and the Zhejiang Provincial Medical and Health Project Fund (No. 2015127713). S.G.P. has received research support from Otsuka, Lundbeck, FORUM, and Alkermes
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