Identification of differentially expressed genes of blood leukocytes for Schizophrenia
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ABSTRACT:
SUBMITTER: Wang F
PROVIDER: S-EPMC11233772 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Schizophrenia (SCZ) is a severe neurodevelopmental disorder with brain dysfunction. This study aimed to use bioinformatic analysis to identify candidate blood biomarkers for SCZ. Our study identified 1205 statistically significant DEGs, of which 623 genes were upregulated and 582 genes were downregulated. Functional enrichment analysis showed that DEGs were mainly enriched in cell chemotaxis, cell surface, and serine peptidase activity, as well as involved in Natural killer cell-mediated cytotoxicity. WGCNA identified 16 gene co-expression modules, and 5 modules were significantly correlated with SCZ (P < 0.05). There were 106 upregulated genes and 90 downregulated genes in the 5 modules. The top ten genes sorted by the Degree algorithm were RPS28, BRD4, FUS, PABPC1, PCBP1, PCBP2, RPL27A, RPS21, RAG1, and RPL27. RAG1 and the other 9 genes belonged to the turquoise and pink module respectively. Pathway enrichment analysis indicated that these 10 genes were mainly involved in processes such as Ribosome, cytoplasmic translation, RNA binding, and protein binding.
2024-06-18 | GSE263180 | GEO
Project description:STUDY OBJECTIVE:A close association between the human leukocyte antigen (HLA)-DRB1*1501/DQB1*0602 and abnormalities in some inflammatory cytokines have been demonstrated in narcolepsy. Specific alterations in the immune system have been suggested to occur in this disorder. We attempted to identify alterations in gene expression underlying the abnormalities in the blood cells of narcoleptic patients. DESIGNS:Total RNA from 12 narcolepsy-cataplexy patients and from 12 age- and sex-matched healthy controls were pooled. The pooled samples were initially screened for candidate genes for narcolepsy by differential display analysis using annealing control primers (ACP). The second screening of the samples was carried out by semiquantitative PCR using gene-specific primers. Finally, the expression levels of the candidate genes were further confirmed by quantitative real-time PCR using a new set of samples (20 narcolepsy-cataplexy patients and 20 healthy controls). RESULTS:The second screening revealed differential expression of 4 candidate genes. Among them, MX2 was confirmed as a significantly down-regulated gene in the white blood cells of narcoleptic patients by quantitative real-time PCR. CONCLUSION:We found the MX2 gene to be significantly less expressed in comparison with normal subjects in the white blood cells of narcoleptic patients. This gene is relevant to the immune system. Although differential display analysis using ACP technology has a limitation in that it does not help in determining the functional mechanism underlying sleep/wakefulness dysregulation, it is useful for identifying novel genetic factors related to narcolepsy, such as HLA molecules. Further studies are required to explore the functional relationship between the MX2 gene and narcolepsy pathophysiology.
| S-EPMC1978392 | biostudies-literature
Project description:BackgroundOsteosarcoma (OS) is the most common primary bone tumors diagnosed in children and adolescents. Recent studies have shown a prognostic role of DNA methylation in various cancers, including OS. The aim of this study was to identify the aberrantly methylated genes that are prognostically relevant in OS.MethodsThe differentially expressed mRNAs, miRNAs and methylated genes (DEGs, DEMs and DMGs respectively) were screened from various GEO databases, and the potential target genes of the DEMs were predicted by the RNA22 program. The protein-protein interaction (PPI) networks were constructed using the STRING database and visualized by Cytoscape software. The functional enrichment and survival analyses of the screened genes was performed using the R software.ResultsForty-seven downregulated hypermethylated genes and three upregulated hypomethylated genes were identified that were enriched in cell activation, migration and proliferation functions, and were involved in cancer-related pathways like JAK-STAT and PI3K-AKT. Eight downregulated hypermethylated tumor suppressor genes (TSGs) were identified among the screened genes based on the TSGene database. These hub genes are likely involved in OS genesis, progression and metastasis, and are potential prognostic biomarkers and therapeutic targets.ConclusionsTSGs including PYCARD, STAT5A, CXCL12 and CXCL14 were aberrantly methylated in OS, and are potential prognostic biomarkers and therapeutic targets. Our findings provide new insights into the role of methylation in OS progression.
| S-EPMC7186728 | biostudies-literature
Project description:Identification of Differential Expression Genes of Blood Leukocytes for Schizophrenia
| PRJNA1096042 | ENA
Project description:Asthma has been the most common chronic disease in children that places a major burden for affected people and their families.An integrated analysis of microarrays studies was performed to identify differentially expressed genes (DEGs) in childhood asthma compared with normal control. We also obtained the differentially methylated genes (DMGs) in childhood asthma according to GEO. The genes that were both differentially expressed and differentially methylated were identified. Functional annotation and protein-protein interaction network construction were performed to interpret biological functions of DEGs. We performed q-RT-PCR to verify the expression of selected DEGs.One DNA methylation and 3 gene expression datasets were obtained. Four hundred forty-one DEGs and 1209 DMGs in childhood asthma were identified. Among which, 16 genes were both differentially expressed and differentially methylated in childhood asthma. Natural killer cell mediated cytotoxicity pathway, Jak-STAT signaling pathway, and Wnt signaling pathway were 3 significantly enriched pathways in childhood asthma according to our KEGG enrichment analysis. The PPI network of top 20 up- and downregulated DEGs consisted of 822 nodes and 904 edges and 2 hub proteins (UBQLN4 and MID2) were identified. The expression of 8 DEGs (GZMB, FGFBP2, CLC, TBX21, ALOX15, IL12RB2, UBQLN4) was verified by qRT-PCR and only the expression of GZMB and FGFBP2 was inconsistent with our integrated analysis.Our finding was helpful to elucidate the underlying mechanism of childhood asthma and develop new potential diagnostic biomarker and provide clues for drug design.
| S-EPMC6392650 | biostudies-literature
Project description:Owing to the remarkable heterogeneity of gastric cancer (GC), population-level differentially expressed genes (DEGs) identified using case-control comparison cannot indicate the dysregulated frequency of each DEG in GC. In this work, first, the individual-level DEGs were identified for 1,090 GC tissues without paired normal tissues using the RankComp method. Second, we directly compared the gene expression in a cancer tissue to that in paired normal tissue to identify individual-level DEGs among 448 paired cancer-normal gastric tissues. We found 25 DEGs to be dysregulated in more than 90% of 1,090 GC tissues and also in more than 90% of 448 GC tissues with paired normal tissues. The 25 genes were defined as universal DEGs for GC. Then, we measured 24 paired cancer-normal gastric tissues by RNA-seq to validate them further. Among the universal DEGs, 4 upregulated genes (BGN, E2F3, PLAU, and SPP1) and 1 downregulated gene (UBL3) were found to be cancer genes already documented in the COSMIC or F-Census databases. By analyzing protein-protein interaction networks, we found 12 universally upregulated genes, and we found that their 284 direct neighbor genes were significantly enriched with cancer genes and key biological pathways related to cancer, such as the MAPK signaling pathway, cell cycle, and focal adhesion. The 13 universally downregulated genes and 16 direct neighbor genes were also significantly enriched with cancer genes and pathways related to gastric acid secretion. These universal DEGs may be of special importance to GC diagnosis and treatment targets, and they may make it easier to study the molecular mechanisms underlying GC.
| S-EPMC7843176 | biostudies-literature
Project description:Rhizomania is one of the most devastating sugar beet diseases. It is caused by Beet necrotic yellow vein virus (BNYVV), which induces abnormal rootlet proliferation. To understand better the physiological and molecular basis of the disorder, transcriptome analysis was performed by restriction fragment differential display polymerase chain reaction (RFDD-PCR), which provided differential gene expression profiles between non-infected and infected sugar beet roots. Two distinct viral isolates were used to detect specific or general virus-induced genes. Differentially expressed genes were selected and identified by sequence analysis, followed by reverse Northern and reverse transcriptase PCR experiments. These latter analyses of different plants (Beta vulgaris and Beta macrocarpa) infected under distinct standardized conditions revealed specific and variable expressions. Candidate genes were linked to cell development, metabolism, defence signalling and oxidative stress. In addition, the expression of already characterized genes linked to defence response (pathogenesis-related protein genes), auxin signalling and cell elongation was also studied to further examine some aspects of the disease. Differential expression was retrieved in both B. vulgaris and B. macrocarpa. However, some candidate genes were found to be deregulated in only one plant species, suggesting differential response to BNYVV or specific responses to the BNYVV vector.
| S-EPMC6640463 | biostudies-literature
Project description:Osteocytes represent the most abundant cellular component of mammalian bones with important functions in bone mass maintenance and remodeling. To elucidate the differential gene expression between osteoblasts and osteocytes we completed a comprehensive analysis of their gene profiles. Selective identification of these two mature populations was achieved by utilization of visual markers of bone lineage cells. We have utilized dual GFP reporter mice in which osteocytes are expressing GFP (topaz) directed by the DMP1 promoter, while osteoblasts are identified by expression of GFP (cyan) driven by 2.3 kb of the Col1a1 promoter. Histological analysis of 7-day-old neonatal calvaria confirmed the expression pattern of DMP1GFP in osteocytes and Col2.3 in osteoblasts and osteocytes. To isolate distinct populations of cells we utilized fluorescent activated cell sorting (FACS). Cell suspensions were subjected to RNA extraction, in vitro transcription and labeling of cDNA and gene expression was analyzed using the Illumina WG-6v1 BeadChip. Following normalization of raw data from four biological replicates, 3444 genes were called present in all three sorted cell populations: GFP negative, Col2.3cyan(+) (osteoblasts), and DMP1topaz(+) (preosteocytes and osteocytes). We present the genes that showed in excess of a 2-fold change for gene expression between DMP1topaz(+) and Col2.3cyan(+) cells. The selected genes were classified and grouped according to their associated gene ontology terms. Genes clustered to osteogenesis and skeletal development such as Bmp4, Bmp8a, Dmp1, Enpp1, Phex and Ank were highly expressed in DMP1topaz(+)cells. Most of the genes encoding extracellular matrix components and secreted proteins had lower expression in DMP1topaz(+) cells, while most of the genes encoding plasma membrane proteins were increased. Interestingly a large number of genes associated with muscle development and function and with neuronal phenotype were increased in DMP1topaz(+) cells, indicating some new aspects of osteocyte biology. Although a large number of genes differentially expressed in DMP1topaz(+) and Col2.3cyan(+) cells in our study have already been assigned to bone development and physiology, for most of them we still lack any substantial data. Therefore, isolation of osteocyte and osteoblast cell populations and their subsequent microarray analysis allowed us to identify a number or genes and pathways with potential roles in regulation of bone mass.
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Project description:Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.
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Project description:Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. However, because of shared complications between DKD and chronic kidney disease (CKD), the description and characterization of DKD remain ambiguous in the clinic, hindering the diagnosis and treatment of early-stage DKD patients. Although estimated glomerular filtration rate and albuminuria are well-established biomarkers of DKD, early-stage DKD is rarely accompanied by a high estimated glomerular filtration rate, and thus there is a need for new sensitive biomarkers. Transcriptome profiling of kidney tissue has been reported previously, although RNA sequencing (RNA-Seq) analysis of the venous blood platelets in DKD patients has not yet been described. In the present study, we performed RNA-Seq analysis of venous blood platelets from three patients with CKD, five patients with DKD and 10 healthy controls, and compared the results with a CKD-related microarray dataset. In total, 2097 genes with differential transcript levels were identified in platelets of DKD patients and healthy controls, and 462 genes with differential transcript levels were identified in platelets of DKD patients and CKD patients. Through Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, we selected 11 pathways, from which nine potential biomarkers (IL-1B, CD-38, CSF1R, PPARG, NR1H3, DDO, HDC, DPYS and CAD) were identified. Furthermore, by comparing the RNA-Seq results with the GSE30566 dataset, we found that the biomarker KCND3 was the only up-regulated gene in DKD patients. These biomarkers may have potential application for the therapy and diagnosis of DKD, as well aid in determining the mechanisms underlying DKD.
| S-EPMC8329951 | biostudies-literature