Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

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.

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GSEA-SNP: applying gene set enrichment analysis to SNP data from genome-wide association studies

Bioinformatics ◽

10.1093/bioinformatics/btn516 ◽

2008 ◽

Vol 24 (23) ◽

pp. 2784-2785 ◽

Cited By ~ 119

Author(s):

Marit Holden ◽

Shiwei Deng ◽

Leszek Wojnowski ◽

Bettina Kulle

Keyword(s):

Association Studies ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Gene Set Enrichment ◽

Gene Set ◽

Snp Data ◽

Genome Wide

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

Frontiers in Genetics ◽

10.3389/fgene.2021.767358 ◽

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.

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Expression Profiles and Prognostic Values of BOLA Family members in Ovarian Cancer

10.21203/rs.3.rs-95044/v1 ◽

2020 ◽

Author(s):

Mingyang Zhu ◽

Shiqi Xiao

Keyword(s):

Ovarian Cancer ◽

Metal Ion ◽

Expression Profiles ◽

Family Members ◽

Enrichment Analysis ◽

Genetic Alterations ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Protein Disulfide Oxidoreductase

Abstract Background: The BOLA gene family, comprising 3 members, is mainly involved in the regulation of intracellular iron homeostasis. Emerging evidence suggests that BOLA family member 2 play vital roles in tumorigenesis and progression of hepatic cellular carcinoma. However, little known about its roles in ovarian cancer. Methods: In present study, we investigated the expression profiles, prognostic roles, and genetic alterations of three BOLA family members in patients with ovarian cancer through several public databases, containing Oncomine and Gene Expression Profiling Interactive Analysis, Human Protein Atlas, Kaplan–Meier plotter and cBioPortal. Then, we constructed the protein–protein interaction networks of BOLA proteins and their interactors by using String database and Cytoscape software. In addition, we performed the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment by the Annotation, Visualization, and Integrated Discovery database. Finally, we explored the mechanisms underlying the involvement of BOLA family members in OC by using gene set enrichment analysis. Results: The mRNA and protein expression levels of BOLA2 and BOLA3 were heavily higher in ovarian cancer tissues than that in normal ovarian tissues. Dysregulated mRNA expressions of three BOLA family members were significantly associated with prognosis in overall or subgroup analysis. Moreover, genetic alterations also occurred in three BOLA family members in ovarian cancer. Network analysis and enrichment analysis indicated that three BOLA family members and their 20 interactors were mainly associated with metal-ion binding and protein disulfide oxidoreductase activity. Gene set enrichment analysis indicated that BOLA family members were mainly associated with oxidative phosphorylation, proteasome, protein export and glutathione metabolism in ovarian cancer. Conclusions: In brief, the present comprehensive bioinformatics analysis revealed that BOLA1, 2, and 3 may be new prognostic biomarkers, and BOLA2 and BOLA3 may be a potential therapeutic target of precision therapy for patients with ovarian cancer, but further studies are demanded to certify this notion.

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Dysregulation of post-transcriptional modification by copy number variable microRNAs in schizophrenia with enhanced glycation stress

Translational Psychiatry ◽

10.1038/s41398-021-01460-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Akane Yoshikawa ◽

Itaru Kushima ◽

Mitsuhiro Miyashita ◽

Kazuya Toriumi ◽

Kazuhiro Suzuki ◽

...

Keyword(s):

Oxidative Stress ◽

Copy Number ◽

Mirna Target ◽

Target Genes ◽

Enrichment Analysis ◽

Synaptic Function ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Genome Wide

AbstractPreviously, we identified a subpopulation of schizophrenia (SCZ) showing increased levels of plasma pentosidine, a marker of glycation and oxidative stress. However, its causative genetic factors remain largely unknown. Recently, it has been suggested that dysregulated posttranslational modification by copy number variable microRNAs (CNV-miRNAs) may contribute to the etiology of SCZ. Here, an integrative genome-wide CNV-miRNA analysis was performed to investigate the etiology of SCZ with accumulated plasma pentosidine (PEN-SCZ). The number of CNV-miRNAs and the gene ontology (GO) in the context of miRNAs within CNVs were compared between PEN-SCZ and non-PEN-SCZ groups. Gene set enrichment analysis of miRNA target genes was further performed to evaluate the pathways affected in PEN-SCZ. We show that miRNAs were significantly enriched within CNVs in the PEN-SCZ versus non-PEN-SCZ groups (p = 0.032). Of note, as per GO analysis, the dysregulated neurodevelopmental events in the two groups may have different origins. Additionally, gene set enrichment analysis of miRNA target genes revealed that miRNAs involved in glycation/oxidative stress and synaptic neurotransmission, especially glutamate/GABA receptor signaling, were possibly affected in PEN-SCZ. To the best of our knowledge, this is the first genome-wide CNV-miRNA study suggesting the role of CNV-miRNAs in the etiology of PEN-SCZ, through effects on genes related to glycation/oxidative stress and synaptic function. Our findings provide supportive evidence that glycation/oxidative stress possibly caused by genetic defects related to the posttranscriptional modification may lead to synaptic dysfunction. Therefore, targeting miRNAs may be one of the promising approaches for the treatment of PEN-SCZ.

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Expression profiles and prognostic values of BolA family members in ovarian cancer

Journal of Ovarian Research ◽

10.1186/s13048-021-00821-0 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Mingyang Zhu ◽

Shiqi Xiao

Keyword(s):

Ovarian Cancer ◽

Metal Ion ◽

Expression Profiles ◽

Family Members ◽

Enrichment Analysis ◽

Genetic Alterations ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Protein Disulfide Oxidoreductase

Abstract Background The BOLA gene family, comprising three members, is mainly involved in regulating intracellular iron homeostasis. Emerging evidence suggests that BolA family member 2 plays a vital role in tumorigenesis and hepatic cellular carcinoma progression. However, there was less known about its role in ovarian cancer. Methods In the present study, we investigated the expression profiles, prognostic roles, and genetic alterations of three BolA family members in patients with ovarian cancer through several public databases, containing Oncomine and Gene Expression Profiling Interactive Analysis, Human Protein Atlas, Kaplan–Meier plotter and cBioPortal. Then, we constructed the protein-protein interaction networks of BOLA proteins and their interactors by using the String database and Cytoscape software. In addition, we performed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment by the Annotation, Visualization, and Integrated Discovery database. Finally, we explored the mechanisms underlying BolA family members’ involvement in OC by using gene set enrichment analysis. Results The mRNA and protein expression levels of BOLA2 and BOLA3 were heavily higher in ovarian cancer tissues than in normal ovarian tissues. Dysregulated mRNA expressions of three BolA family members were significantly associated with prognosis in overall or subgroup analysis. Moreover, genetic alterations also occurred in three BolA family members in ovarian cancer. GO analysis indicated that BolA family members might regulate the function of metal ion binding and protein disulfide oxidoreductase activity. Gene set enrichment analysis indicated that BolA family members were mainly associated with oxidative phosphorylation, proteasome, protein export, and glutathione metabolism in ovarian cancer. Conclusion In brief, our finding may contribute to increasing currently limited prognostic biomarkers and treatment options for ovarian cancer.

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Gene set enrichment analysis: A genome-wide expression profile-based strategy for discovering functional microRNA–disease relationships

Journal of International Medical Research ◽

10.1177/0300060517693719 ◽

2017 ◽

Vol 46 (2) ◽

pp. 596-611 ◽

Cited By ~ 3

Author(s):

Yin Ni ◽

Caiyun Song ◽

Shuqing Jin ◽

Zhoufeng Chen ◽

Ming Ni ◽

...

Keyword(s):

Colorectal Cancer ◽

Pattern Matching ◽

Expression Profile ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Genome Wide ◽

A Genome ◽

Matching Strategy ◽

Genome Wide Expression

Objective To explore stable and functional microRNA (miRNA)–disease relationships using a genome-wide expression profile pattern matching strategy. Methods We applied the ranked microarray pattern matching strategy Gene Set Enrichment Analysis to identify miRNA permutations with similar expression patterns to diseases. We also used quantitative reverse transcription PCR to validate the predicted expression levels of miRNAs in three diseases: inflammatory bowel disease (IBD), oesophageal cancer, and colorectal cancer. Results We found that hsa-miR-200 c was upregulated more than 40-fold in oesophageal cancer. The expression of miR-16 and miR-124 was not consistently upregulated in IBD or colorectal cancer. Conclusions Our results suggest that this expression profile matching strategy can be used to identify functional miRNA–disease relationships.

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CENPN Acts as a Novel Biomarker that Correlates With the Malignant Phenotypes of Glioma Cells

Frontiers in Genetics ◽

10.3389/fgene.2021.732376 ◽

2021 ◽

Vol 12 ◽

Author(s):

Hailong Wu ◽

Yan Zhou ◽

Haiyang Wu ◽

Lixia Xu ◽

Yan Yan ◽

...

Keyword(s):

Expression Profiles ◽

Glioma Cells ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Migration And Invasion ◽

Malignant Neoplasms ◽

Gene Set Enrichment ◽

Gene Set ◽

Genome Atlas

Background: Gliomas are the most common intracranial malignant neoplasms and have high recurrence and mortality rates. Recent literatures have reported that centromere protein N (CENPN) participates in tumor development. However, the clinicopathologic significance and biological functions of CENPN in glioma are still unclear.Methods: Clinicopathologic data and gene expression profiles of glioma cases downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases were utilized to determine the associations between the expression of CENPN and clinical features of glioma. Kaplan-Meier and ROC curves were plotted for prognostic analysis. Gene set enrichment analysis (GSEA) and single sample gene set enrichment analysis (ssGSEA) were applied to identify immune-related functions and pathways associated with CENPN’ differential expression. In vitro experiments were conducted to investigate the impacts of CENPN on human glioma cells.Results: Elevated CENPN expression was associated with unfavorable clinical variables of glioma patients, which was validated in clinical specimens obtained from our institution by immunohistochemical staining (IHC). The GSEA and ssGSEA results revealed that CENPN expression was strongly correlated with inflammatory activities, immune-related signaling pathways and the infiltration of immune cells. Cell experiments showed that CENPN deficiency impaired cell proliferation, migration and invasion ability and increased glioma apoptosis.Conclusion: CENPN could be a promising therapeutic target for glioma.

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