MMEASE: Online meta-analysis of metabolomic data by enhanced metabolite annotation, marker selection and enrichment analysis

2021 ◽  
Vol 232 ◽  
pp. 104023
Author(s):  
Qingxia Yang ◽  
Bo Li ◽  
Sijie Chen ◽  
Jing Tang ◽  
Yinghong Li ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Enrichment Analysis ◽  
Marker Selection ◽  
Metabolomic Data ◽  
Metabolite Annotation

scholarly journals Discovery and function exploration of microRNA-155 as a molecular biomarker for early detection of breast cancer

Breast Cancer ◽  
2021 ◽  
Author(s):  
Xuemin Liu ◽  
Qingyu Chang ◽  
Haiqiang Wang ◽  
Hairong Qian ◽  
Yikun Jiang
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Protein Interactions ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Diagnostic Value ◽  
Diagnostic Biomarker ◽  
Analysis Model ◽  
Sensitivity Specificity ◽  
Function Enrichment

Abstract Background MicroRNA-155 (miR-155) may function as a diagnostic biomarker of breast cancer (BC). Nevertheless, the available evidence is controversial. Therefore, we performed this study to summarize the global predicting role of miR-155 for early detection of BC and preliminarily explore the functional roles of miR-155 in BC. Methods We first collected published studies and applied the bivariate meta-analysis model to generate the pooled diagnostic parameters of miR-155 in diagnosing BC such as sensitivity, specificity and area under curve (AUC). Then, we applied function enrichment and protein–protein interactions (PPI) analyses to explore the potential mechanisms of miR-155. Results A total of 21 studies were finally included. The results indicated that miR-155 allowed for the discrimination between BC patients and healthy controls with a sensitivity of 0.87 (95% CI 0.78–0.93), specificity of 0.82 (0.72–0.89), and AUC of 0.91 (0.88–0.93). In addition, the overall sensitivity, specificity and AUC for circulating miR-155 were 0.88 (0.76–0.95), 0.83 (0.72–0.90), and 0.92 (0.89–0.94), respectively. Function enrichment analysis revealed several vital ontologies terms and pathways associated with BC occurrence and development. Furthermore, in the PPI network, ten hub genes and two significant modules were identified to be involved in some important pathways associated with the pathogenesis of BC. Conclusions We demonstrated that miR-155 has great potential to facilitate accurate BC detection and may serve as a promising diagnostic biomarker for BC. However, well-designed cohort studies and biological experiments should be implemented to confirm the diagnostic value of miR-155 before it can be applied to routine clinical procedures.

scholarly journals VEGF as a potential molecular target in periodontitis: a meta-analysis and microarray data validation

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Bo Ren ◽  
Que Feng ◽  
Shan He ◽  
Yanfeng Li ◽  
Jiadong Fan ◽  
...  
Keyword(s):  
Growth Factor ◽  
Clinical Sample ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Therapeutic Drug ◽  
Data Validation ◽  
Control Groups ◽  
Vegf Expression ◽  
Healthy Control

Abstract Background Anti-vascular endothelial growth factor (VEGF) has been used as a therapeutic drug for the treatment of some human diseases. However, no systematic evidence is performed for assessing the role of VEGF in periodontitis. We carried out a comprehensive analysis to explore the role of VEGF in patients with periodontitis. Methods Multiple databases were searched for eligible studies. The pooled standardized mean difference (SMD) and odds ratio (OR) with the corresponding 95% confidence interval (CI) were applied to evaluate the effect sizes. Clinical data validation from microarray analysis was used. Pathway and process enrichment analysis were also investigated. Results Finally, 16 studies were included in this analysis. Overall, there was a significantly higher level of VEGF expression in periodontitis than in healthy control groups (OR = 16.64, 95% CI = 6.01–46.06, P < 0.001; SMD = 2.25, 95% CI = 1.25–3.24, P < 0.001). Subgroup analysis of ethnicity showed that VEGF expression was still correlated with periodontitis in the Asian and European populations. No correlation was observed between VEGF expression and age, gender, and pathological type. A large clinical sample data (427 periodontitis patients and 136 healthy controls) further validated that VEGF expression was higher in periodontitis than in healthy control groups (P = 0.023). VEGF was involved in many functions such as blood vessel development, response to growth factor, cell proliferation, and cell adhesion. Conclusions High levels of VEGF were credible implications for the development of periodontitis. Anti-VEGF therapy may be valuable for the treatment of periodontitis in clinical management.

scholarly journals Meta-Analysis of Oxidative Transcriptomes in Insects

Antioxidants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 345
Author(s):  
Hidemasa Bono
Keyword(s):  
Oxidative Stress ◽  
Stress Response ◽  
Meta Analysis ◽  
Adherens Junction ◽  
Enrichment Analysis ◽  
Oxidative Stress Response ◽  
Insect Species ◽  
Rna Seq ◽  
Manual Curation ◽  
Analysis Workflow

Data accumulation in public databases has resulted in extensive use of meta-analysis, a statistical analysis that combines the results of multiple studies. Oxidative stress occurs when there is an imbalance between free radical activity and antioxidant activity, which can be studied in insects by transcriptome analysis. This study aimed to apply a meta-analysis approach to evaluate insect oxidative transcriptomes using publicly available data. We collected oxidative stress response-related RNA sequencing (RNA-seq) data for a wide variety of insect species, mainly from public gene expression databases, by manual curation. Only RNA-seq data of Drosophila melanogaster were found and were systematically analyzed using a newly developed RNA-seq analysis workflow for species without a reference genome sequence. The results were evaluated by two metric methods to construct a reference dataset for oxidative stress response studies. Many genes were found to be downregulated under oxidative stress and related to organ system process (GO:0003008) and adherens junction organization (GO:0034332) by gene enrichment analysis. A cross-species analysis was also performed. RNA-seq data of Caenorhabditis elegans were curated, since no RNA-seq data of insect species are currently available in public databases. This method, including the workflow developed, represents a powerful tool for deciphering conserved networks in oxidative stress response.

scholarly journals Meta-analysis of untargeted metabolomic data from multiple profiling experiments

2012 ◽  
Vol 7 (3) ◽  
pp. 508-516 ◽  
Author(s):  
Gary J Patti ◽  
Ralf Tautenhahn ◽  
Gary Siuzdak
Keyword(s):  
Meta Analysis ◽  
Metabolomic Data

scholarly journals Is There a Relationship Between Psoriasis and Hepatitis C?: a Meta-analysis and Bioinformatics Investigation

2021 ◽  
Author(s):  
Yong Liu ◽  
Sheng Nan Cui ◽  
Meng Yao Duan ◽  
Zhi Li Dou ◽  
Yi Zhen Li ◽  
...  
Keyword(s):  
Hepatitis C ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Case Control ◽  
Cochrane Library ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Overlapping Genes ◽  
Cross Sectional ◽  
Pathway Enrichment

Abstract Background: The relationship between psoriasis and hepatitis C was previously controversial, so our purpose is to investigate this connection.Methods: We conducted a systematic review of the case-control, cross-sectional and cohort studies examining the association between psoriasis and hepatitis C in PubMed, EMBASE and Cochrane library databases and investigated the overlapping genes between psoriasis targets and hepatitis C targets using bioinformatics analysis. Based on overlapping genes and hub nodes, we also constructed the protein-protein interaction (PPI) network and module respectively, followed by the pathway enrichment analysis. Results: We included 11 publications that reported a total of 11 studies (8 cross-sectional and 3 case-control). The case–control and cross-sectional studies included 25,047 psoriasis patients and 4,091,631 controls in total. Psoriasis was associated with a significant increase of prevalent hepatitis C (OR 1.72; 95% confidence interval [CI] (1.17-2.52)). A total of 389 significant genes were common to both hepatitis C and psoriasis, which mainly involved IL6, TNF, IL10, ALB, STAT3 and CXCL8. The module and pathway enrichment analyses showed that the common genes had the potential to influence varieties of biological pathways, including the inflammatory response, cytokine activity, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, which play an important role in the pathogenesis of hepatitis C and psoriasis.Conclusion: Patients with psoriasis display increased prevalence of hepatitis C and the basic related mechanisms between hepatitis C and psoriasis had been preliminarily clarified.

scholarly journals Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

2018 ◽  
Author(s):  
David M. Howard ◽  
Mark J. Adams ◽  
Toni-Kim Clarke ◽  
Jonathan D. Hafferty ◽  
Jude Gibson ◽  
...  
Keyword(s):  
Multiple Testing ◽  
Drug Repositioning ◽  
Association Studies ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Brain Regions ◽  
Genome Wide Association Studies ◽  
Multiple Testing Correction ◽  
Synaptic Structure ◽  
Genome Wide

AbstractMajor depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches.

scholarly journals Identification of Key Deregulated RNA-Binding Proteins in Pancreatic Cancer by Meta-Analysis and Prediction of Their Role as Modulators of Oncogenesis

2021 ◽  
Vol 9 ◽  
Author(s):  
Moumita Mukherjee ◽  
Srikanta Goswami
Keyword(s):  
Pancreatic Cancer ◽  
Cell Migration ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment

RNA-binding proteins (RBPs) play a significant role in multiple cellular processes with their deregulations strongly associated with cancer. However, there are not adequate evidences regarding global alteration and functions of RBPs in pancreatic cancer, interrogated in a systematic manner. In this study, we have prepared an exhaustive list of RBPs from multiple sources, downloaded gene expression microarray data from a total of 241 pancreatic tumors and 124 normal pancreatic tissues, performed a meta-analysis, and obtained differentially expressed RBPs (DE-RBPs) using the Limma package of R Bioconductor. The results were validated in microarray datasets and the Cancer Genome Atlas (TCGA) RNA sequencing dataset for pancreatic adenocarcinoma (PAAD). Pathway enrichment analysis was performed using DE-RBPs, and we also constructed the protein–protein interaction (PPI) network to detect key modules and hub-RBPs. Coding and noncoding targets for top altered and hub RBPs were identified, and altered pathways modulated by these targets were also investigated. Our meta-analysis identified 45 upregulated and 15 downregulated RBPs as differentially expressed in pancreatic cancer, and pathway enrichment analysis demonstrated their important contribution in tumor development. As a result of PPI network analysis, 26 hub RBPs were detected and coding and noncoding targets for all these RBPs were categorized. Functional exploration characterized the pathways related to epithelial-to-mesenchymal transition (EMT), cell migration, and metastasis to emerge as major pathways interfered by the targets of these RBPs. Our study identified a unique meta-signature of 26 hub-RBPs to primarily modulate pancreatic tumor cell migration and metastasis in pancreatic cancer. IGF2BP3, ISG20, NIP7, PRDX1, RCC2, RUVBL1, SNRPD1, PAIP2B, and SIDT2 were found to play the most prominent role in the regulation of EMT in the process. The findings not only contribute to understand the biology of RBPs in pancreatic cancer but also to evaluate their candidature as possible therapeutic targets.

scholarly journals Epigenome-wide meta-analysis of DNA methylation differences in prefrontal cortex implicates the immune processes in Alzheimer’s disease

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Lanyu Zhang ◽  
Tiago C. Silva ◽  
Juan I. Young ◽  
Lissette Gomez ◽  
Michael A. Schmidt ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Prefrontal Cortex ◽  
Biomarker Discovery ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Braak Stage ◽  
Polycomb Repressive Complex 2 ◽  
Differentially Methylated Genes

AbstractDNA methylation differences in Alzheimer’s disease (AD) have been reported. Here, we conducted a meta-analysis of more than 1000 prefrontal cortex brain samples to prioritize the most consistent methylation differences in multiple cohorts. Using a uniform analysis pipeline, we identified 3751 CpGs and 119 differentially methylated regions (DMRs) significantly associated with Braak stage. Our analysis identified differentially methylated genes such as MAMSTR, AGAP2, and AZU1. The most significant DMR identified is located on the MAMSTR gene, which encodes a cofactor that stimulates MEF2C. Notably, MEF2C cooperates with another transcription factor, PU.1, a central hub in the AD gene network. Our enrichment analysis highlighted the potential roles of the immune system and polycomb repressive complex 2 in pathological AD. These results may help facilitate future mechanistic and biomarker discovery studies in AD.

scholarly journals Host–Viral Interactions Revealed among Shared Transcriptomics Signatures of ARDS and Thrombosis: A Clue into COVID-19 Pathogenesis

TH Open ◽  
2020 ◽  
Vol 04 (04) ◽  
pp. e403-e412
Author(s):  
Aastha Mishra ◽  
Shankar Chanchal ◽  
Mohammad Z. Ashraf
Keyword(s):  
Gene Expression ◽  
Virus Disease ◽  
Meta Analysis ◽  
Random Effect ◽  
Enrichment Analysis ◽  
Coagulation Factors ◽  
Gene Expression Omnibus ◽  
Endothelial Damage ◽  
Pathway Enrichment Analysis ◽  
Hub Genes

AbstractSevere novel corona virus disease 2019 (COVID-19) infection is associated with a considerable activation of coagulation pathways, endothelial damage, and subsequent thrombotic microvascular injuries. These consistent observations may have serious implications for the treatment and management of this highly pathogenic disease. As a consequence, the anticoagulant therapeutic strategies, such as low molecular weight heparin, have shown some encouraging results. Cytokine burst leading to sepsis which is one of the primary reasons for acute respiratory distress syndrome (ARDS) drive that could be worsened with the accumulation of coagulation factors in the lungs of COVID-19 patients. However, the obscurity of this syndrome remains a hurdle in making decisive treatment choices. Therefore, an attempt to characterize shared biological mechanisms between ARDS and thrombosis using comprehensive transcriptomics meta-analysis is made. We conducted an integrated gene expression meta-analysis of two independently publicly available datasets of ARDS and venous thromboembolism (VTE). Datasets GSE76293 and GSE19151 derived from National Centre for Biotechnology Information–Gene Expression Omnibus (NCBI-GEO) database were used for ARDS and VTE, respectively. Integrative meta-analysis of expression data (INMEX) tool preprocessed the datasets and effect size combination with random effect modeling was used for obtaining differentially expressed genes (DEGs). Network construction was done for hub genes and pathway enrichment analysis. Our meta-analysis identified a total of 1,878 significant DEGs among the datasets, which when subjected to enrichment analysis suggested inflammation–coagulation–hypoxemia convolutions in COVID-19 pathogenesis. The top hub genes of our study such as tumor protein 53 (TP53), lysine acetyltransferase 2B (KAT2B), DExH-box helicase 9 (DHX9), REL-associated protein (RELA), RING-box protein 1 (RBX1), and proteasome 20S subunit beta 2 (PSMB2) gave insights into the genes known to be participating in the host–virus interactions that could pave the way to understand the various strategies deployed by the virus to improve its replication and spreading.

Sign in / Sign up

Export Citation Format

Share Document