Genome-wide methylation profiles in coronary artery ectasia

2017 ◽  
Vol 131 (7) ◽  
pp. 583-594 ◽  
Author(s):  
Tzu-Pin Lu ◽  
Nai-Chen Chuang ◽  
Chin-Yu Cheng ◽  
Cheng-An Hsu ◽  
Yi-Chih Wang ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Coronary Arteries ◽  
Inflammatory Responses ◽  
Functional Characterization ◽  
Enrichment Analysis ◽  
Systematic Investigation ◽  
Gene Set Enrichment Analysis ◽  
Coronary Artery Ectasia ◽  
Protein Levels ◽  
Genome Wide

Coronary artery ectasia (CAE) is a disease characterized by abnormally dilated coronary arteries. The mechanism of CAE remains unclear, and its treatment is limited. Previous studies have shown that risk factors for CAE were related to changes in DNA methylation. However, no systematic investigation of methylation profiles has been performed. Therefore, we compared methylation profiles between 12 CAE patients and 12 propensity-matched individuals with normal coronary arteries using microarrays. Wilcoxon's rank sum tests revealed 89 genes with significantly different methylation levels (P<0.05 and Δβ > |0.1|). Functional characterization using the DAVID database and gene set enrichment analysis indicated that these genes were involved in immune and inflammatory responses. Of these genes 6 were validated in 29 CAE patients and 87 matched individuals with CAE, using pyro-sequencing. TLR6 and NOTCH4 showed significant differences in methylation between the two groups, and lower protein levels of toll-like receptor 6 (TLR6) were detected in CAE patients. In conclusion, this genome-wide analysis of methylation profiles in CAE patients showed that significant changes in both methylation and expression of TLR6 deserve further study to elucidate their roles in CAE.

scholarly journals Gene set enrichment analysis for genome-wide DNA methylation data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jovana Maksimovic ◽  
Alicia Oshlack ◽  
Belinda Phipson
Keyword(s):  
Dna Methylation ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Methylation Array ◽  
Gene Set ◽  
Genome Wide ◽  
Genome Methylation ◽  
Unbiased Gene ◽  
Gene Set Testing

AbstractDNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.

scholarly journals Identification of long noncoding RNAs reveals the effects of dinotefuran on the brain in Apis mellifera (Hymenopptera: Apidae)

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Minjie Huang ◽  
Jie Dong ◽  
Haikun Guo ◽  
Minghui Xiao ◽  
Deqian Wang
Keyword(s):  
Immune Response ◽  
Honey Bee ◽  
Honey Bees ◽  
Transforming Growth Factor ◽  
Sublethal Effects ◽  
Inflammatory Responses ◽  
Noncoding Rnas ◽  
Enrichment Analysis ◽  
Long Noncoding Rnas ◽  
Gene Set Enrichment Analysis

Abstract Background Dinotefuran (CAS No. 165252–70-0), a neonicotinoid insecticide, has been used to protect various crops against invertebrate pests and has been associated with numerous negative sublethal effects on honey bees. Long noncoding RNAs (lncRNAs) play important roles in mediating various biological and pathological processes, involving transcriptional and gene regulation. The effects of dinotefuran on lncRNA expression and lncRNA function in the honey bee brain are still obscure. Results Through RNA sequencing, a comprehensive analysis of lncRNAs and mRNAs was performed following exposure to 0.01 mg/L dinotefuran for 1, 5, and 10 d. In total, 312 lncRNAs and 1341 mRNAs, 347 lncRNAs and 1458 mRNAs, and 345 lncRNAs and 1155 mRNAs were found to be differentially expressed (DE) on days 1, 5 and 10, respectively. Gene set enrichment analysis (GSEA) indicated that the dinotefuran-treated group showed enrichment in carbohydrate and protein metabolism and immune-inflammatory responses such as glycine, serine and threonine metabolism, pentose and glucuronate interconversion, and Hippo and transforming growth factor-β (TGF-β) signaling pathways. Moreover, the DE lncRNA TCONS_00086519 was shown by fluorescence in situ hybridization (FISH) to be distributed mainly in the cytoplasm, suggesting that it may serve as a competing endogenous RNA and a regulatory factor in the immune response to dinotefuran. Conclusion This study characterized the expression profile of lncRNAs upon exposure to neonicotinoid insecticides in young adult honey bees and provided a framework for further study of the role of lncRNAs in honey bee growth and the immune response.

scholarly journals Novel Anti-inflammatory Effects of Canagliflozin Involving Hexokinase II in Lipopolysaccharide-Stimulated Human Coronary Artery Endothelial Cells

2020 ◽  
Author(s):  
Laween Uthman ◽  
Marius Kuschma ◽  
Gregor Römer ◽  
Marleen Boomsma ◽  
Jens Kessler ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Coronary Artery ◽  
Inflammatory Responses ◽  
Vascular Inflammation ◽  
Glycolytic Enzyme ◽  
Human Coronary Artery ◽  
Hexokinase Ii ◽  
Protein Levels ◽  
Inflammatory Mechanism ◽  
Anti Inflammatory

Abstract Purpose Vascular inflammation and disturbed metabolism are observed in heart failure and type 2 diabetes mellitus. Glycolytic enzyme hexokinase II (HKII) is upregulated by inflammation. We hypothesized that SGLT2 inhibitors Canagliflozin (Cana), Empagliflozin (Empa) or Dapagliflozin (Dapa) reduces inflammation via HKII in endothelial cells, and that HKII-dependent inflammation is determined by ERK1/2, NF-κB. and/or AMPK activity in lipopolysaccharide (LPS)-stimulated human coronary artery endothelial cells (HCAECs). Methods HCAECs were pre-incubated with 3 μM or 10 μM Cana, 1 μM, 3 μM or 10 μM Empa or 0.5 μM, 3 μM or 10 μM Dapa (16 h) and subjected to 3 h LPS (1 μg/mL). HKII was silenced via siRNA transfection. Interleukin-6 (IL-6) release was measured by ELISA. Protein levels of HK I and II, ERK1/2, AMPK and NF-κB were detected using infra-red western blot. Results LPS increased IL-6 release and ERK1/2 phosphorylation; Cana prevented these pro-inflammatory responses (IL-6: pg/ml, control 46 ± 2, LPS 280 ± 154 p < 0.01 vs. control, LPS + Cana 96 ± 40, p < 0.05 vs. LPS). Cana reduced HKII expression (HKII/GAPDH, control 0.91 ± 0.16, Cana 0.71 ± 0.13 p < 0.05 vs. control, LPS 1.02 ± 0.25, LPS + Cana 0.82 ± 0.24 p < 0.05 vs. LPS). Empa and Dapa were without effect on IL-6 release and HKII expression in the model used. Knockdown of HKII by 37% resulted caused partial loss of Cana-mediated IL-6 reduction (pg/ml, control 35 ± 5, LPS 188 ± 115 p < 0.05 vs. control, LPS + Cana 124 ± 75) and ERK1/2 activation by LPS. In LPS-stimulated HCAECs, Cana, but not Empa or Dapa, activated AMPK. AMPK activator A769662 reduced IL-6 release. Conclusion Cana conveys anti-inflammatory actions in LPS-treated HCAECs through 1) reductions in HKII and ERK1/2 phosphorylation and 2) AMPK activation. These data suggest a novel anti-inflammatory mechanism of Cana through HKII.

scholarly journals TMEA: A Thermodynamically Motivated Framework for Functional Characterization of Biological Responses to System Acclimation

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 1030
Author(s):  
Kevin Schneider ◽  
Benedikt Venn ◽  
Timo Mühlhaus
Keyword(s):  
Free Energy ◽  
Functional Characterization ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Energy Investment ◽  
Biological Responses ◽  
Novel Approach ◽  
Biological Studies

The objective of gene set enrichment analysis (GSEA) in modern biological studies is to identify functional profiles in huge sets of biomolecules generated by high-throughput measurements of genes, transcripts, metabolites, and proteins. GSEA is based on a two-stage process using classical statistical analysis to score the input data and subsequent testing for overrepresentation of the enrichment score within a given functional coherent set. However, enrichment scores computed by different methods are merely statistically motivated and often elusive to direct biological interpretation. Here, we propose a novel approach, called Thermodynamically Motivated Enrichment Analysis (TMEA), to account for the energy investment in biological relevant processes. Therefore, TMEA is based on surprisal analysis, which offers a thermodynamic-free energy-based representation of the biological steady state and of the biological change. The contribution of each biomolecule underlying the changes in free energy is used in a Monte Carlo resampling procedure resulting in a functional characterization directly coupled to the thermodynamic characterization of biological responses to system perturbations. To illustrate the utility of our method on real experimental data, we benchmark our approach on plant acclimation to high light and compare the performance of TMEA with the most frequently used method for GSEA.

scholarly journals Genome-wide association analysis of hippocampal volume identifies enrichment of neurogenesis-related pathways

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Emrin Horgusluoglu-Moloch ◽  
◽  
Shannon L. Risacher ◽  
Paul K. Crane ◽  
Derrek Hibar ◽  
...  
Keyword(s):  
Association Analysis ◽  
Adult Neurogenesis ◽  
Enrichment Analysis ◽  
Hippocampal Volume ◽  
Imaging Genetics ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide Association ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Genome Wide

Abstract Adult neurogenesis occurs in the dentate gyrus of the hippocampus during adulthood and contributes to sustaining the hippocampal formation. To investigate whether neurogenesis-related pathways are associated with hippocampal volume, we performed gene-set enrichment analysis using summary statistics from a large-scale genome-wide association study (N = 13,163) of hippocampal volume from the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium and two year hippocampal volume changes from baseline in cognitively normal individuals from Alzheimer’s Disease Neuroimaging Initiative Cohort (ADNI). Gene-set enrichment analysis of hippocampal volume identified 44 significantly enriched biological pathways (FDR corrected p-value < 0.05), of which 38 pathways were related to neurogenesis-related processes including neurogenesis, generation of new neurons, neuronal development, and neuronal migration and differentiation. For genes highly represented in the significantly enriched neurogenesis-related pathways, gene-based association analysis identified TESC, ACVR1, MSRB3, and DPP4 as significantly associated with hippocampal volume. Furthermore, co-expression network-based functional analysis of gene expression data in the hippocampal subfields, CA1 and CA3, from 32 normal controls showed that distinct co-expression modules were mostly enriched in neurogenesis related pathways. Our results suggest that neurogenesis-related pathways may be enriched for hippocampal volume and that hippocampal volume may serve as a potential phenotype for the investigation of human adult neurogenesis.

scholarly journals Genome-Wide Association Study of Postoperative Cognitive Dysfunction in Older Surgical Patients

2020 ◽  
Author(s):  
Marc Rickenbacher ◽  
Céline S Reinbold ◽  
Stefan Herms ◽  
Per Hoffmann ◽  
Sven Cichon ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Cognitive Dysfunction ◽  
Genome Wide Association Study ◽  
Postoperative Cognitive Dysfunction ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

Abstract Background: Postoperative cognitive dysfunction (POCD) is a common neurocognitive complication after surgery and anesthesia, particularly in elderly patients. Various studies have suggested genetic risk factors for POCD. The study aimed to detect genome-wide associations of POCD in older patients.Methods: In this prospective observational cohort study, participants aged ≥65 years completed a set of neuropsychological tests before, at 1 week, and 3 months after major noncardiac surgery. Test variables were converted into standard scores (z-scores) based on demographic characteristics. POCD was diagnosed if the decline was >1 standard deviation in ≥2 of the 15 variables in the assessment battery. A genome-wide association study (GWAS) was performed to determine potential alleles that are linked to the POCD phenotype. In addition, candidate genes for POCD were identified in a literature search for further analysis.Results: Sixty-three patients with blood samples were included in the study. POCD was diagnosed in 47.6% of patients at 1 week and in 34.2% of patients at 3 months after surgery. Insufficient sample quality led to exclusion of 26 patients. In the remaining 37 patients, a GWAS was performed, but no association (P < 5*10-8) with POCD was found. The subsequent gene set enrichment analysis of 34 candidate genes did not reveal any significant associations.Conclusion: In this patient cohort, a GWAS did not reveal an association between specific genetic alleles and POCD at 1 week and 3 months after surgery. Future genetic analysis should focus on specific candidate genes for POCD.Trial registration: ClinicalTrials.gov (NCT02864173)

scholarly journals Importance of SNP Dependency Correction and Association Integration for Gene Set Analysis in Genome-Wide Association Studies

2021 ◽  
Vol 12 ◽  
Author(s):  
Michal Marczyk ◽  
Agnieszka Macioszek ◽  
Joanna Tobiasz ◽  
Joanna Polanska ◽  
Joanna Zyla
Keyword(s):  
Association Studies ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide Association ◽  
Gene Set Analysis ◽  
Genome Wide Association Studies ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Genome Wide ◽  
The Impact

A typical genome-wide association study (GWAS) analyzes millions of single-nucleotide polymorphisms (SNPs), several of which are in a region of the same gene. To conduct gene set analysis (GSA), information from SNPs needs to be unified at the gene level. A widely used practice is to use only the most relevant SNP per gene; however, there are other methods of integration that could be applied here. Also, the problem of nonrandom association of alleles at two or more loci is often neglected. Here, we tested the impact of incorporation of different integrations and linkage disequilibrium (LD) correction on the performance of several GSA methods. Matched normal and breast cancer samples from The Cancer Genome Atlas database were used to evaluate the performance of six GSA algorithms: Coincident Extreme Ranks in Numerical Observations (CERNO), Gene Set Enrichment Analysis (GSEA), GSEA-SNP, improved GSEA for GWAS (i-GSEA4GWAS), Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA), and Over-Representation Analysis (ORA). Association of SNPs to phenotype was calculated using modified McNemar’s test. Results for SNPs mapped to the same gene were integrated using Fisher and Stouffer methods and compared with the minimum p-value method. Four common measures were used to quantify the performance of all combinations of methods. Results of GSA analysis on GWAS were compared to the one performed on gene expression data. Comparing all evaluation metrics across different GSA algorithms, integrations, and LD correction, we highlighted CERNO, and MAGENTA with Stouffer as the most efficient. Applying LD correction increased prioritization and specificity of enrichment outcomes for all tested algorithms. When Fisher or Stouffer were used with LD, sensitivity and reproducibility were also better. Using any integration method was beneficial in comparison with a minimum p-value method in specific combinations. The correlation between GSA results from genomic and transcriptomic level was the highest when Stouffer integration was combined with LD correction. We thoroughly evaluated different approaches to GSA in GWAS in terms of performance to guide others to select the most effective combinations. We showed that LD correction and Stouffer integration could increase the performance of enrichment analysis and encourage the usage of these techniques.

scholarly journals In vivo CRISPR/Cas9 knockout screen: TCEAL1 silencing enhances docetaxel efficacy in prostate cancer

2020 ◽  
Vol 3 (12) ◽  
pp. e202000770 ◽  
Author(s):  
Linda K Rushworth ◽  
Victoria Harle ◽  
Peter Repiscak ◽  
William Clark ◽  
Robin Shaw ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Elongation Factor ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Genome Wide ◽  
A Genome ◽  
Docetaxel Treatment ◽  
Crispr Screen ◽  
Altered Cell

Docetaxel chemotherapy in metastatic prostate cancer offers only a modest survival benefit because of emerging resistance. To identify candidate therapeutic gene targets, we applied a murine prostate cancer orthograft model that recapitulates clinical invasive prostate cancer in a genome-wide CRISPR/Cas9 screen under docetaxel treatment pressure. We identified 17 candidate genes whose suppression may enhance the efficacy of docetaxel, with transcription elongation factor A–like 1 (Tceal1) as the top candidate. TCEAL1 function is not fully characterised; it may modulate transcription in a promoter dependent fashion. Suppressed TCEAL1 expression in multiple human prostate cancer cell lines enhanced therapeutic response to docetaxel. Based on gene set enrichment analysis from transcriptomic data and flow cytometry, we confirmed that loss of TCEAL1 in combination with docetaxel leads to an altered cell cycle profile compared with docetaxel alone, with increased subG1 cell death and increased polyploidy. Here, we report the first in vivo genome-wide treatment sensitisation CRISPR screen in prostate cancer, and present proof of concept data on TCEAL1 as a candidate for a combinational strategy with the use of docetaxel.

scholarly journals Identification of key genes and pathways affected in epicardial adipose tissue from patients with coronary artery disease by integrated bioinformatics analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8763
Author(s):  
Liao Tan ◽  
Qian Xu ◽  
Qianchen Wang ◽  
Ruizheng Shi ◽  
Guogang Zhang
Keyword(s):  
Coronary Artery Disease ◽  
Adipose Tissue ◽  
Coronary Artery ◽  
Epicardial Adipose Tissue ◽  
Enrichment Analysis ◽  
Pathological Process ◽  
Gene Set Enrichment Analysis ◽  
Rt Pcr ◽  
Key Genes ◽  
Artery Disease

Background Coronary artery disease (CAD) is a common disease with high cost and mortality. Here, we studied the differentially expressed genes (DEGs) between epicardial adipose tissue (EAT) and subcutaneous adipose tissue (SAT) from patients with CAD to explore the possible pathways and mechanisms through which EAT participates in the CAD pathological process. Methods Microarray data for EAT and SAT were obtained from the Gene Expression Omnibus database, including three separate expression datasets: GSE24425, GSE64554 and GSE120774. The DEGs between EAT samples and SAT control samples were screened out using the limma package in the R language. Next, we conducted bioinformatic analysis of gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways to discover the enriched gene sets and pathways associated with DEGs. Simultaneously, gene set enrichment analysis was carried out to discover enriched gene functions and pathways from all expression data rather than DEGs. The PPI network was constructed to reveal the possible protein interactions consistent with CAD. Mcode and Cytohubba in Cytoscape revealed the possible key CAD genes. In the next step, the corresponding predicted microRNAs (miRNAs) were analysed using miRNA Data Integration Portal. RT-PCR was used to validate the bioinformatic results. Results The three datasets had a total of 89 DEGs (FC log2 > 1 and P value < 0.05). By comparing EAT and SAT, ten common key genes (HOXA5, HOXB5, HOXC6, HOXC8, HOXB7, COL1A1, CCND1, CCL2, HP and TWIST1) were identified. In enrichment analysis, pro-inflammatory and immunological genes and pathways were up-regulated. This could help elucidate the molecular expression mechanism underlying the involvement of EAT in CAD development. Several miRNAs were predicted to regulate these DEGs. In particular, hsa-miR-196a-5p and hsa-miR-196b-5p may be more reliably associated with CAD. Finally, RT-PCR validated the significant difference of OXA5, HOXC6, HOXC8, HOXB7, COL1A1, CCL2 between EAT and SAT (P value < 0.05). Conclusions Between EAT and SAT in CAD patients, a total of 89 DEGs, and 10 key genes, including HOXA5, HOXB5, HOXC6, HOXC8, HOXB7, COL1A1, CCND1, CCL2, HP and TWIST1, and miRNAs hsa-miR-196a-5p and hsa-miR-196b-5p were predicted to play essential roles in CAD pathogenesis. Pro-inflammatory and immunological pathways could act as key EAT regulators by participating in the CAD pathological process.

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