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Enrichment Analysis (enrichment + analysis)
Kinds of Enrichment Analysis Selected AbstractsHuman Variation in Alcohol Response Is Influenced by Variation in Neuronal Signaling GenesALCOHOLISM, Issue 5 2010Geoff Joslyn Background:, Alcohol use disorders (AUD) exhibit the properties shared by common conditions and diseases classified as genetically complex. The etiology of AUDs is heterogeneous involving mostly unknown interactions of environmental and heritable factors. A person's level of response (LR) to alcohol is inversely correlated with a family history and the development of AUDs. As an AUD endophenotype, alcohol LR is hypothesized to be less genetically complex and closer to the primary etiology of AUDs. Methods:, A genome wide association study (GWAS) was performed on subjects characterized for alcohol LR phenotypes. Gene Set Enrichment Analysis (GSEA) of the GWAS data was performed to determine whether, as a group, genes that participate in a common biological function (a gene set) demonstrate greater genetic association than would be randomly expected. Results:, The GSEA analysis implicated variation in neuronal signaling genes, especially glutamate signaling, as being involved in alcohol LR variability in the human population. Conclusions:, These data, coupled with cell and animal model data implicating neuronal signaling in alcohol response, support the conclusion that neuronal signaling is mechanistically involved in alcohol's cellular and behavioral effects. Further, these data suggest that genetic variation in these signaling pathways contribute to human variation in alcohol response. Finally, this concordance of the cell, animal, and human findings supports neuronal signaling, particularly glutamate signaling, as a prime target for translational studies to understand and eventually modulate alcohol's effects. [source] Identification of 2 putative critical segments of 17q gain in neuroblastoma through integrative genomicsINTERNATIONAL JOURNAL OF CANCER, Issue 5 2008Jo Vandesompele Abstract Partial gain of chromosome arm 17q is the most frequent genetic change in neuroblastoma (NB) and constitutes the strongest independent genetic factor for adverse prognosis. It is assumed that 1 or more genes on 17q contribute to NB pathogenesis by a gene dosage effect. In the present study, we applied chromosome 17 tiling path BAC arrays on a panel of 69 primary tumors and 28 NB cell lines in order to reduce the current smallest region of gain and facilitate identification of candidate dosage sensitive genes. In all tumors and cell lines with 17q gain, large distal segments were consistently present in extra copies and no interstitial gains were observed. In addition to these large regions of distal gain with breakpoints proximal to coordinate 44.3 Mb (17q21.32), smaller regions of gain (distal to coordinate 60 Mb at 17q24.1) were found superimposed on the larger region in a minority of cases. Positional gene enrichment analysis for 17q genes overexpressed in NB showed that dosage sensitive NB oncogenes are most likely located in the gained region immediately distal to the most distal breakpoint of the 2 breakpoint regions. Interestingly, comparison of gene expression profiles between primary tumors and normal fetal adrenal neuroblasts revealed 2 gene clusters on chromosome 17q that are overexpressed in NB, i.e. a region on 17q21.32 immediately distal to the most distal breakpoint (in cases with single regions of gain) and 17q24.1, a region coinciding with breakpoints leading to superimposed gain. © 2007 Wiley-Liss, Inc. [source] Transcriptional response to aging and caloric restriction in heart and adipose tissueAGING CELL, Issue 5 2007Nancy J. Linford Summary Sustained caloric restriction (CR) extends lifespan in animal models but the mechanism and primary tissue target(s) have not been identified. Gene expression changes with aging and CR were examined in both heart and white adipose tissue (WAT) of Fischer 344 (F344) male rats using Affymetrix® RAE 230 arrays and validated by quantitative reverse transcriptase,polymerase chain reaction (qRT-PCR) on 18 genes. As expected, age had a substantial effect on transcription on both tissues, although only 21% of cardiac age-associated genes were also altered in WAT. Gene set enrichment analysis revealed coordinated small magnitude changes in ribosomal, proteasomal, and mitochondrial genes with similarities in aging between heart and WAT. CR had very different effects on these two tissues at the transcriptional level. In heart, very few age-associated expression changes were affected by CR, while in WAT, CR suppressed a substantial subset of the age-associated changes. Genes unaltered by aging but altered by CR were identified in WAT but not heart. Most interestingly, we identified a gene expression signature associated with mammalian target of rapamycin (mTOR) activity that was down-regulated with age but preserved by CR in both WAT and heart. In addition, lipid metabolism genes, particularly those associated with peroxisome proliferator-activated receptor , (PPAR,)-mediated adipogenesis were reduced with age but preserved with CR in WAT. These results highlight tissue-specific differences in the gene expression response to CR and support a role for CR-mediated preservation of mTOR activity and adipogenesis in aging WAT. [source] Protein Kinase Target Discovery From Genome-Wide Messenger RNA Expression ProfilingMOUNT SINAI JOURNAL OF MEDICINE: A JOURNAL OF PERSONALIZED AND TRANSLATIONAL MEDICINE, Issue 4 2010Avi Ma'ayan Abstract Genome-wide messenger RNA profiling provides a snapshot of the global state of the cell under different experimental conditions such as diseased versus normal cellular states. However, because measurements are in the form of quantitative changes in messenger RNA levels, such experimental data does not provide direct understanding of the regulatory molecular mechanisms responsible for the observed changes. Identifying potential cell signaling regulatory mechanisms responsible for changes in gene expression under different experimental conditions or in different tissues has been the focus of many computational systems biology studies. Most popular approaches include promoter analysis, gene ontology, or pathway enrichment analysis, as well as reverse engineering of networks from messenger RNA expression data. Here we present a rational approach for identifying and ranking protein kinases that are likely responsible for observed changes in gene expression. By combining promoter analysis; data from various chromatin immunoprecipitation studies such as chromatin immunoprecipitation sequencing, chromatin immunoprecipitation coupled with paired-end ditag, and chromatin immunoprecipitation-on-chip; protein-protein interactions; and kinase-protein phosphorylation reactions collected from the literature, we can identify and rank candidate protein kinases for knock-down, or other types of functional validations, based on genome-wide changes in gene expression. We describe how protein kinase candidate identification and ranking can be made robust by cross-validation with phosphoproteomics data as well as through a literature-based text-mining approach. In conclusion, data integration can produce robust candidate rankings for understanding cell regulation through identification of protein kinases responsible for gene expression changes, and thus rapidly advancing drug target discovery and unraveling drug mechanisms of action. Mt Sinai J Med 77:345,349, 2010. © 2010 Mount Sinai School of Medicine [source] Genetic modifiers of the severity of sickle cell anemia identified through a genome-wide association study,AMERICAN JOURNAL OF HEMATOLOGY, Issue 1 2010Paola Sebastiani We conducted a genome-wide association study (GWAS) to discover single nucleotide polymorphisms (SNPs) associated with the severity of sickle cell anemia in 1,265 patients with either "severe" or "mild" disease based on a network model of disease severity. We analyzed data using single SNP analysis and a novel SNP set enrichment analysis (SSEA) developed to discover clusters of associated SNPs. Single SNP analysis discovered 40 SNPs that were strongly associated with sickle cell severity (odds for association >1,000); of the 32 that we could analyze in an independent set of 163 patients, five replicated, eight showed consistent effects although failed to reach statistical significance, whereas 19 did not show any convincing association. Among the replicated associations are SNPs in KCNK6 a K+ channel gene. SSEA identified 27 genes with a strong enrichment of significant SNPs (P < 10,6); 20 were replicated with varying degrees of confidence. Among the novel findings identified by SSEA is the telomere length regulator gene TNKS. These studies are the first to use GWAS to understand the genetic diversity that accounts the phenotypic heterogeneity sickle cell anemia as estimated by an integrated model of severity. Additional validation, resequencing, and functional studies to understand the biology and reveal mechanisms by which candidate genes might have their effects are the future goals of this work. Am. J. Hematol., 2010. © 2009 Wiley-Liss, Inc. [source] Transcription of proteinase 3 and related myelopoiesis genes in peripheral blood mononuclear cells of patients with active Wegener's granulomatosisARTHRITIS & RHEUMATISM, Issue 6 2010Chris Cheadle Objective Wegener's granulomatosis (WG) is a systemic inflammatory disease that is associated with substantial morbidity. The aim of this study was to understand the biology underlying WG and to discover markers of disease activity that would be useful for prognosis and treatment guidance. Methods Gene expression profiling was performed using total RNA from peripheral blood mononuclear cells (PBMCs) and granulocyte fractions from 41 patients with WG and 23 healthy control subjects. Gene set enrichment analysis (GSEA) was performed to search for candidate WG-associated molecular pathways and disease activity biomarkers. Principal components analysis was used to visualize relationships between subgroups of WG patients and controls. Longitudinal changes in proteinase 3 (PR3) gene expression were evaluated using reverse transcription,polymerase chain reaction, and clinical outcomes, including remission status and disease activity, were determined using the Birmingham Vasculitis Activity Score for WG (BVAS-WG). Results Eighty-six genes in WG PBMCs and 40 in WG polymorphonuclear neutrophils (PMNs) were significantly up-regulated relative to controls. Genes up-regulated in WG PBMCs were involved in myeloid differentiation, and these included the WG autoantigen PR3. The coordinated regulation of myeloid differentiation genes was confirmed by GSEA. The median expression values of the 86 up-regulated genes in WG PBMCs were associated with disease activity (P = 1.3 × 10,4), and WG patients with low-level expression of the WG signature genes showed expression profiles that were only modestly different from that in healthy controls (P = 0.07). PR3 transcription was significantly up-regulated in WG PBMCs (P = 1.3 × 10,5, false discovery rate [FDR] 0.002), but not in WG PMNs (P = 0.03, FDR 0.28), and a preliminary longitudinal analysis showed that the fold change in PR3 RNA levels in WG PBMCs corresponded to changes in the BVAS-WG score over time. Conclusion Transcription of PR3 and related myeloid differentiation genes in PBMCs may represent novel markers of disease activity in WG. [source] Computational identification of altered metabolism using gene expression and metabolic pathwaysBIOTECHNOLOGY & BIOENGINEERING, Issue 4 2009Hojung Nam Abstract Understanding altered metabolism is an important issue because altered metabolism is often revealed as a cause or an effect in pathogenesis. It has also been shown to be an important factor in the manipulation of an organism's metabolism in metabolic engineering. Unfortunately, it is not yet possible to measure the concentration levels of all metabolites in the genome-wide scale of a metabolic network; consequently, a method that infers the alteration of metabolism is beneficial. The present study proposes a computational method that identifies genome-wide altered metabolism by analyzing functional units of KEGG pathways. As control of a metabolic pathway is accomplished by altering the activity of at least one rate-determining step enzyme, not all gene expressions of enzymes in the pathway demonstrate significant changes even if the pathway is altered. Therefore, we measure the alteration levels of a metabolic pathway by selectively observing expression levels of significantly changed genes in a pathway. The proposed method was applied to two strains of Saccharomyces cerevisiae gene expression profiles measured in very high-gravity (VHG) fermentation. The method identified altered metabolic pathways whose properties are related to ethanol and osmotic stress responses which had been known to be observed in VHG fermentation because of the high sugar concentration in growth media and high ethanol concentration in fermentation products. With the identified altered pathways, the proposed method achieved best accuracy and sensitivity rates for the Red Star (RS) strain compared to other three related studies (gene-set enrichment analysis (GSEA), significance analysis of microarray to gene set (SAM-GS), reporter metabolite), and for the CEN.PK 113-7D (CEN) strain, the proposed method and the GSEA method showed comparably similar performances. Biotechnol. Bioeng. 2009;103: 835,843. © 2009 Wiley Periodicals, Inc. [source] | |||||||||||||