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Cancer Informatics
Published in Trevor F. Cox, Medical Statistics for Cancer Studies, 2022
The top ten genes, in terms of p-values are PIK3C2G, C16orf11, PVT1, GABRD, CA10, BSND, PAK6, SLC9A4, ACPP and NDUFA4L2. It seems almost pointless listing the first few genes like this, as the order is somewhat arbitrary since we are ordering many p-values of order to . Instead we will carry out an Enrichment Analysis (EA) of the 3,382 differentially expressed genes, using the function TCGAanalyze_EAcomplete().
Animal models of major depressive disorder and the implications for drug discovery and development
Published in Expert Opinion on Drug Discovery, 2019
Konstantin A. Demin, Maxim Sysoev, Maria V. Chernysh, Anna K. Savva, Mamiko Koshiba, Edina A. Wappler-Guzzetta, Cai Song, Murilo S. De Abreu, Brian Leonard, Matthew O. Parker, Brian H. Harvey, Li Tian, Eero Vasar, Tatyana Strekalova, Tamara G. Amstislavskaya, Andrey D. Volgin, Erik T. Alpyshov, Dongmei Wang, Allan V. Kalueff
Aberrant GABA-ergic system is strongly associated with depression. Indeed, GABRA1, GABRA5, GABRA6 and GABRG2 genes are linked to MDD, and a male-specific polymorphism of GABRD to childhood mood disorders [158]. MDD is generally accompanied by lower GABA levels, restored by conventional antidepressant treatments [158]. Interestingly, the glutamate decarboxylase (GAD65) or GABA-B1 knockout display high anxiety-like but low depression-like behaviors [9,79], thereby providing a potentially valuable tool to dissect these two commonly comorbid and clinically overlapping conditions.
Developing precision treatments for epilepsy using patient and animal models
Published in Expert Review of Neurotherapeutics, 2021
Krzysztof Łukawski, Stanisław J. Czuczwar
It is commonly accepted that genetic factors play a crucial role in the pathophysiology of many types of epilepsies. It has been recently reported that 977 genes are associated with epilepsy, among which 84 genes are primary epilepsy genes (genes that cause epilepsies or syndromes with epilepsy as the core symptom), 73 genes are classified as neurodevelopment-associated genes (genes associated with both brain-development malformations and epilepsy) and 536 epilepsy-related genes (genes associated with both systemic and other neurological diseases and epilepsy or seizures) [43]. Genetic-related epilepsies involve a monogenic or polygenic model of inheritance and basically, in monogenic epilepsies, mutated genes encode ion channel subunits that mediate neuronal excitability and whose gain or loss of function result in abnormal generation and propagation of action potentials [44]. Numerous genetic mouse models that contain mutations in the genes encoding voltage-gated channels, e.g. Na+ channels (SCN1A, SCN1B, SCN2A, or SCN8A), K+ channels (KCNQ2, KCNQ3), and Ca2+ channels (CACNA1H, CACNB4) have been developed in recent years, which recapitulate many of the features of different genetic epilepsy types or syndromes (depending on the model) such as, e.g. GEFS+ (generalized epilepsy with febrile seizures plus), severe myoclonic epilepsy of infancy, benign familial infantile convulsions or juvenile myoclonic epilepsy [15,45]. Also, various genetic mouse models of epilepsy that possess mutations of epilepsy-associated GABAA receptor genes (GABRA1, GABRG2, GABRD), N-methyl-D-aspartate receptor (NMDAR) genes (GRIN2A) or neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNB2, CHRNA4) have been introduced [15,46]. Recently tuberous sclerosis complex (TSC) has been recognized as a model of genetic epilepsies [47]. TSC is an autosomal dominant neurocutaneous disorder that represents one of the most common genetic causes of epilepsy [47] and astrocyte-specific Tsc1 conditional knockout mice exhibit abnormal neuronal organization and seizures [48]. The above-mentioned models offer valuable opportunities to isolate and experimentally reproduce gene mutations for human epilepsies, to perform studies on the molecular mechanisms of epileptogenesis, and investigate strategies for correcting early hyperactivity defects in the developing brain [49]. It has been discussed that some existing medications can target functional consequences in genetic epilepsies, such as, e.g. AEDs being Na+ channel blockers in the sodium channelopathies or quinidine in KCNT1-related epilepsies as examples of epilepsy precision medicine [50]. However, clinical evaluation of such treatments is complicated by genetic and phenotypic heterogeneity, as well as by various neurological and non-neurological comorbidities [50].
Association of drinking behaviors with TXNIP DNA methylation levels in leukocytes among the general Japanese population
Published in The American Journal of Drug and Alcohol Abuse, 2022
Keisuke Maeda, Hiroya Yamada, Eiji Munetsuna, Ryosuke Fujii, Mirai Yamazaki, Yoshitaka Ando, Genki Mizuno, Hiroaki Ishikawa, Koji Ohashi, Yoshiki Tsuboi, Yuji Hattori, Yuya Ishihara, Shuji Hashimoto, Nobuyuki Hamajima, Koji Suzuki
This study has several limitations. First, since this is a cross-sectional study, causal relationships could not be examined. Longitudinal studies are required to prove a true causal relationship. Second, the possibility of residual confounding cannot be completely excluded, although confounding was appropriately adjusted for in our multivariable analyses, e.g., smoking. We adjusted our multivariable analyses for smoking habits, and the conclusions of all analyses were not different than the non-adjusted analysis. Moreover, we examined the association between drinking behaviors and TXNIP DNA methylation among the subject with non-smokers. These results also showed that heavy drinking was associated with TXNIP DNA hypomethylation (Figure S3 and Table S1), and daily and cumulative alcohol consumption levels were associated with decreased TXNIP DNA methylation levels (Figure S4 and Table S2). For other possible confounders, we found higher the E values, indicating that it is unlikely that an unmeasured variable explained the observed association between TXNIP DNA hypomethylation and heavy drinkers. Third, the type of white blood cells (WBCs) used in our analysis must be considered, as the type of WBC may affect TXNIP DNA methylation levels. Therefore, the type of WBC from each blood sample was determined using an automated hematology analyzer LH755 (Beckman Coulter, Brea, CA, USA), and the percentage of neutrophils was adjusted for in our multivariable analysis. Fourth, the data on alcohol consumption was based on a self-administered questionnaire. Although this data was obtained by trained public health nurses during the health examination, a typical systematic bias, i.e., recall bias, might have occurred in our analyses. Fifth, our study participants were all Japanese. Therefore, this relationship may not be generalizable to racially different populations with diverse drinking behaviors and lifestyles. Further studies using a larger population are required to evaluate whether the present findings can be replicated in non-Japanese populations. Sixth, east Asian has a different alcohol metabolism compared with other ancestry groups due to SNPs within two key alcohol-related genes; alcohol dehydrogenase 1B (ADH1B) and aldehyde dehydrogenase 2 (ALDH2) (19,34,35). Although we did not genotype for these genes, our literature review did not find any interactions between two genes and TXNIP genotype and methylation levels. In addition, we speculate that there is much less direct interaction between the TXNIP gene and these alcohol-related genes because ADH1B and ALDH2 are located in chromosome 4 and 12 (TXNIP within chromosome 1). However, other alcohol-related genes (e.g. γ-aminobutyric acid A receptor delta (GABRD), and γ-aminobutyric acid B receptor subunit 1 (GABBR1)) have possibility to influence on our results. Further studies are expected to explore the complex gene-gene interactions underlying alcohol metabolism.