scholarly journals Sampling Defective Pathways in Parkinson Disease

2019 ◽  
Vol 1 (1) ◽  
pp. 37-52
Author(s):  
Juan Luis Fernández-Martínez ◽  
Enrique J. deAndrés-Galiana ◽  
Enrique J. deAndrés-Galiana ◽  
Ana Cernea ◽  
Francisco Javier Fernández-Ovies ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prior Probability ◽  
Validation Dataset ◽  
P53 Signaling ◽  
Novel Algorithms ◽  
Fisher’S Ratio ◽  
Leave One Out ◽  
Prediction Problems ◽  
The Brain ◽  
Very High

Discrimination of case-control status based on gene expression differences has potential to identify novel pathways relevant to neurodegenerative diseases including Parkinson’s disease (PD). In this paper we applied two different novel algorithms to predict dysregulated pathways of gene expression across several different regions of the brain in PD and controls. The Fisher’s ratio sampler uses the Fisher’s ratio of the most discriminatory genes as prior probability distribution to sample the genetic networks and their likelihood (accuracy) was established via Leave-One-Out-Cross Validation (LOOCV). The holdout sampler finds the minimum-scale signatures corresponding to different random holdouts, establishing their likelihood using the validation dataset in each holdout. Phenotype prediction problems have by genesis a very high underdetermined character. We used both approaches to sample different lists of genes that optimally discriminate PD from controls and subsequently used gene ontology to identify pathways affected by disease. Both algorithms identified common pathways of Insulin signaling, FOXA1 Transcription Factor Network, HIF-1 Signaling, p53 Signaling and Chromatin Regulation/Acetylation. This analysis provides new therapeutic targets to treat PD.

scholarly journals Identification and validation of three core genes in p53 signaling pathway in hepatitis B virus-related hepatocellular carcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Mingxue Yu ◽  
Wenli Xu ◽  
Yusheng Jie ◽  
Jiahui Pang ◽  
Siqi Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Normal Liver ◽  
Validation Dataset ◽  
P53 Signaling ◽  
B Virus ◽  
P53 Signaling Pathway ◽  
Core Genes

Abstract Background Hepatocellular carcinoma (HCC) is a common cancer and the leading cause is persistent hepatitis B virus (HBV) infection. We aimed to identify some core genes and pathways for HBV-related HCC. Methods Gene expression profiles of GSE62232, GSE121248, and GSE94660 were available from Gene Expression Omnibus (GEO). The GSE62232 and GSE121248 profiles were the analysis datasets and GSE94660 was the validation dataset. The GEO2R online tool and Venn diagram software were applied to analyze commonly differentially expressed genes between HBV-related HCC tissues and normal tissues. Then, functional enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Gene and Genome (KEGG) as well as the protein-protein interaction (PPI) network was conducted. The overall survival rates and the expression levels were detected by Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA). Next, gene set enrichment analysis (GSEA) was performed to verify the KEGG pathway analysis. Furthermore, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed to validate the levels of these three core genes in tumor tissues and adjacent non-tumor liver tissues from 12 HBV related HCC patients, HBV-associated liver cancer cell lines and normal liver cell lines, and HepG2 with p53 knockdown or deletion, respectively. Results Fifteen highly expressed genes associated with significantly worse prognoses were selected and CCNB1, CDK1, and RRM2 in the p53 signaling pathway were identified as core genes. GSEA results showed that samples highly expressing three core genes were all enriched in the p53 signaling pathway in a validation dataset (P < 0.0001). The expression of these three core genes in tumor tissue samples was higher than that in relevant adjacent non-tumor liver tissues (P < 0.0001). Furthermore, we also found that the above genes were highly expressed in liver cancer cell lines compared with normal liver cells. In addition, we found that the expression of these three core genes in p53 knockdown or knockout HCC cell lines was lower than that in negative control HCC cell lines (P < 0.05). Conclusions CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway and could be potential biomarkers and therapeutic targets for HBV-related HCC.

1805-P: Insulin Regulates a Broad Network of Gene Expression in the Brain to Regulated Brain Metabolism and Neurotransmission

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1805-P
Author(s):  
WEIKANG CAI ◽  
THIAGO M. BATISTA ◽  
RUBEN GARCIA MARTIN ◽  
ALFRED RAMIREZ ◽  
MASAHIRO KONISHI ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brain Metabolism ◽  
The Brain

scholarly journals Alternative splicing during mammalian organ development

2021 ◽  
Author(s):  
Pavel V. Mazin ◽  
Philipp Khaitovich ◽  
Margarida Cardoso-Moreira ◽  
Henrik Kaessmann
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Regulatory Networks ◽  
Organ Development ◽  
Functional Diversification ◽  
Mammalian Genomes ◽  
Species Comparisons ◽  
Time Specific ◽  
The Brain ◽  
Gene Expression Levels

AbstractAlternative splicing (AS) is pervasive in mammalian genomes, yet cross-species comparisons have been largely restricted to adult tissues and the functionality of most AS events remains unclear. We assessed AS patterns across pre- and postnatal development of seven organs in six mammals and a bird. Our analyses revealed that developmentally dynamic AS events, which are especially prevalent in the brain, are substantially more conserved than nondynamic ones. Cassette exons with increasing inclusion frequencies during development show the strongest signals of conserved and regulated AS. Newly emerged cassette exons are typically incorporated late in testis development, but those retained during evolution are predominantly brain specific. Our work suggests that an intricate interplay of programs controlling gene expression levels and AS is fundamental to organ development, especially for the brain and heart. In these regulatory networks, AS affords substantial functional diversification of genes through the generation of tissue- and time-specific isoforms from broadly expressed genes.

On the limits of active module identification

2021 ◽  
Author(s):  
Olga Lazareva ◽  
Jan Baumbach ◽  
Markus List ◽  
David B Blumenthal
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Small Diameter ◽  
Extensive Study ◽  
Biological Knowledge ◽  
Expression Data ◽  
Module Identification ◽  
Ppi Networks ◽  
Novel Algorithms ◽  
Context Specific

Abstract In network and systems medicine, active module identification methods (AMIMs) are widely used for discovering candidate molecular disease mechanisms. To this end, AMIMs combine network analysis algorithms with molecular profiling data, most commonly, by projecting gene expression data onto generic protein–protein interaction (PPI) networks. Although active module identification has led to various novel insights into complex diseases, there is increasing awareness in the field that the combination of gene expression data and PPI network is problematic because up-to-date PPI networks have a very small diameter and are subject to both technical and literature bias. In this paper, we report the results of an extensive study where we analyzed for the first time whether widely used AMIMs really benefit from using PPI networks. Our results clearly show that, except for the recently proposed AMIM DOMINO, the tested AMIMs do not produce biologically more meaningful candidate disease modules on widely used PPI networks than on random networks with the same node degrees. AMIMs hence mainly learn from the node degrees and mostly fail to exploit the biological knowledge encoded in the edges of the PPI networks. This has far-reaching consequences for the field of active module identification. In particular, we suggest that novel algorithms are needed which overcome the degree bias of most existing AMIMs and/or work with customized, context-specific networks instead of generic PPI networks.

scholarly journals LSD1 enzyme inhibitor TAK-418 unlocks aberrant epigenetic machinery and improves autism symptoms in neurodevelopmental disorder models

2021 ◽  
Vol 7 (11) ◽  
pp. eaba1187
Author(s):  
Rina Baba ◽  
Satoru Matsuda ◽  
Yuuichi Arakawa ◽  
Ryuji Yamada ◽  
Noriko Suzuki ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enzyme Activity ◽  
Neurodevelopmental Disorders ◽  
Neurodevelopmental Disorder ◽  
Specific Inhibitor ◽  
Autism Spectrum ◽  
Poly I:C ◽  
Control Of Gene Expression ◽  
Epigenetic Machinery ◽  
The Brain

Persistent epigenetic dysregulation may underlie the pathophysiology of neurodevelopmental disorders, such as autism spectrum disorder (ASD). Here, we show that the inhibition of lysine-specific demethylase 1 (LSD1) enzyme activity normalizes aberrant epigenetic control of gene expression in neurodevelopmental disorders. Maternal exposure to valproate or poly I:C caused sustained dysregulation of gene expression in the brain and ASD-like social and cognitive deficits after birth in rodents. Unexpectedly, a specific inhibitor of LSD1 enzyme activity, 5-((1R,2R)-2-((cyclopropylmethyl)amino)cyclopropyl)-N-(tetrahydro-2H-pyran-4-yl)thiophene-3-carboxamide hydrochloride (TAK-418), almost completely normalized the dysregulated gene expression in the brain and ameliorated some ASD-like behaviors in these models. The genes modulated by TAK-418 were almost completely different across the models and their ages. These results suggest that LSD1 enzyme activity may stabilize the aberrant epigenetic machinery in neurodevelopmental disorders, and the inhibition of LSD1 enzyme activity may be the master key to recover gene expression homeostasis. TAK-418 may benefit patients with neurodevelopmental disorders.

scholarly journals Screening of gene markers related to the prognosis of metastatic skin cutaneous melanoma based on Logit regression and survival analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Guoliang Jia ◽  
Zheyu Song ◽  
Zhonghang Xu ◽  
Youmao Tao ◽  
Yuanyu Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cutaneous Melanoma ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Validation Dataset ◽  
Survival Prognosis ◽  
Gene Markers ◽  
Clinical Prognosis ◽  
Logit Regression

Abstract Background Bioinformatics was used to analyze the skin cutaneous melanoma (SKCM) gene expression profile to provide a theoretical basis for further studying the mechanism underlying metastatic SKCM and the clinical prognosis. Methods We downloaded the gene expression profiles of 358 metastatic and 102 primary (nonmetastatic) CM samples from The Cancer Genome Atlas (TCGA) database as a training dataset and the GSE65904 dataset from the National Center for Biotechnology Information database as a validation dataset. Differentially expressed genes (DEGs) were screened using the limma package of R3.4.1, and prognosis-related feature DEGs were screened using Logit regression (LR) and survival analyses. We also used the STRING online database, Cytoscape software, and Database for Annotation, Visualization and Integrated Discovery software for protein–protein interaction network, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses based on the screened DEGs. Results Of the 876 DEGs selected, 11 (ZNF750, NLRP6, TGM3, KRTDAP, CAMSAP3, KRT6C, CALML5, SPRR2E, CD3G, RTP5, and FAM83C) were screened using LR analysis. The survival prognosis of nonmetastatic group was better compared to the metastatic group between the TCGA training and validation datasets. The 11 DEGs were involved in 9 KEGG signaling pathways, and of these 11 DEGs, CALML5 was a feature DEG involved in the melanogenesis pathway, 12 targets of which were collected. Conclusion The feature DEGs screened, such as CALML5, are related to the prognosis of metastatic CM according to LR. Our results provide new ideas for exploring the molecular mechanism underlying CM metastasis and finding new diagnostic prognostic markers.

scholarly journals A gene expression atlas for different kinds of stress in the mouse brain

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Tiziano Flati ◽  
Silvia Gioiosa ◽  
Giovanni Chillemi ◽  
Andrea Mele ◽  
Alberto Oliverio ◽  
...  
Keyword(s):  
Gene Expression ◽  
Coping With Stress ◽  
Gene Expression Atlas ◽  
Sequence Read Archive ◽  
Brain Transcriptome ◽  
Expression Atlas ◽  
Differential Gene ◽  
Stress Related Genes ◽  
Public Repositories ◽  
The Brain

AbstractStressful experiences are part of everyday life and animals have evolved physiological and behavioral responses aimed at coping with stress and maintaining homeostasis. However, repeated or intense stress can induce maladaptive reactions leading to behavioral disorders. Adaptations in the brain, mediated by changes in gene expression, have a crucial role in the stress response. Recent years have seen a tremendous increase in studies on the transcriptional effects of stress. The input raw data are freely available from public repositories and represent a wealth of information for further global and integrative retrospective analyses. We downloaded from the Sequence Read Archive 751 samples (SRA-experiments), from 18 independent BioProjects studying the effects of different stressors on the brain transcriptome in mice. We performed a massive bioinformatics re-analysis applying a single, standardized pipeline for computing differential gene expression. This data mining allowed the identification of novel candidate stress-related genes and specific signatures associated with different stress conditions. The large amount of computational results produced was systematized in the interactive “Stress Mice Portal”.

scholarly journals The brain transcriptome of the wolf spider, Schizocosa ocreata

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Daniel Stribling ◽  
Peter L. Chang ◽  
Justin E. Dalton ◽  
Christopher A. Conow ◽  
Malcolm Rosenthal ◽  
...  
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Model Organisms ◽  
De Novo Transcriptome Assembly ◽  
De Novo Transcriptome ◽  
Wolf Spiders ◽  
Schizocosa Ocreata ◽  
Genomic Studies ◽  
The Brain

Abstract Objectives Arachnids have fascinating and unique biology, particularly for questions on sex differences and behavior, creating the potential for development of powerful emerging models in this group. Recent advances in genomic techniques have paved the way for a significant increase in the breadth of genomic studies in non-model organisms. One growing area of research is comparative transcriptomics. When phylogenetic relationships to model organisms are known, comparative genomic studies provide context for analysis of homologous genes and pathways. The goal of this study was to lay the groundwork for comparative transcriptomics of sex differences in the brain of wolf spiders, a non-model organism of the pyhlum Euarthropoda, by generating transcriptomes and analyzing gene expression. Data description To examine sex-differential gene expression, short read transcript sequencing and de novo transcriptome assembly were performed. Messenger RNA was isolated from brain tissue of male and female subadult and mature wolf spiders (Schizocosa ocreata). The raw data consist of sequences for the two different life stages in each sex. Computational analyses on these data include de novo transcriptome assembly and differential expression analyses. Sample-specific and combined transcriptomes, gene annotations, and differential expression results are described in this data note and are available from publicly-available databases.

scholarly journals Bile Acids in Dementia: Brain Amyloid, White Matter Lesions, and Atrophy

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 767-768
Author(s):  
Vijay Varma ◽  
Youjin Wang ◽  
Yang An ◽  
Sudhir Varma ◽  
Murat Bilgel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bile Acids ◽  
White Matter Lesions ◽  
Pharmacological Modulation ◽  
Dementia Risk ◽  
The Brain ◽  
Step Study ◽  
Brain Amyloid Deposition ◽  
Gene Expression Levels

Abstract While Alzheimer’s disease (AD) and vascular dementia (VaD) may be accelerated by hypercholesterolemia, the mechanisms underlying this association is unclear. Using a novel, 3-step study design we examined the role of cholesterol catabolism in dementia by testing whether 1) the synthesis of the primary cholesterol breakdown products (bile acids (BA)) were associated with neuroimaging markers of dementia; 2) pharmacological modulation of BAs alters dementia risk; and 3) brain BA concentrations and gene expression were associated with AD. We found that higher serum concentrations of BAs are associated with lower brain amyloid deposition, slower WML accumulation, and slower brain atrophy in males. Opposite effects were observed in females. Modulation of BA levels alters risk of incident VaD in males. Altered brain BA signaling at the metabolite and gene expression levels occurs in AD. Dysregulation of peripheral cholesterol catabolism and BA synthesis may impact dementia pathogenesis through signaling pathways in the brain.

scholarly journals Interaction of clozapine with metformin in a schizophrenia rat model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
G. Horvath ◽  
G. Kis ◽  
G. Kekesi ◽  
A. Büki ◽  
L. G. Adlan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cognitive Function ◽  
Negative Symptoms ◽  
Antipsychotic Drugs ◽  
D1 Receptor ◽  
Antidiabetic Drug ◽  
Beneficial Effects ◽  
Adjuvant Therapies ◽  
Behavioral Parameters ◽  
The Brain

AbstractThe low efficacy of antipsychotic drugs (e.g., clozapine) for negative symptoms and cognitive impairment has led to the introduction of adjuvant therapies. Because previous data suggest the procognitive potential of the antidiabetic drug metformin, this study aimed to assess the effects of chronic clozapine and metformin oral administration (alone and in combination) on locomotor and exploratory activities and cognitive function in a reward-based test in control and a schizophrenia-like animal model (Wisket rats). As impaired dopamine D1 receptor (D1R) function might play a role in the cognitive dysfunctions observed in patients with schizophrenia, the second goal of this study was to determine the brain-region-specific D1R-mediated signaling, ligand binding, and mRNA expression. None of the treatments affected the behavior of the control animals significantly; however, the combination treatment enhanced D1R binding and activation in the cerebral cortex. The Wisket rats exhibited impaired motivation, attention, and cognitive function, as well as a lower level of cortical D1R binding, signaling, and gene expression. Clozapine caused further deterioration of the behavioral parameters, without a significant effect on the D1R system. Metformin blunted the clozapine-induced impairments, and, similarly to that observed in the control animals, increased the functional activity of D1R. This study highlights the beneficial effects of metformin (at the behavioral and cellular levels) in blunting clozapine-induced adverse effects.

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