scholarly journals Identification of Differentially Expressed Genes and Long Noncoding RNAs Associated with Parkinson’s Disease

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Lu-Mei Chi ◽  
Li-Ping Wang ◽  
Dan Jiao
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Noncoding Rnas ◽  
Gene Expression Omnibus ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Similar Treatment ◽  
Blood Samples

Objectives. This study aims to determine differentially expressed genes (DEGs) and long noncoding RNAs (lncRNAs) associated with Parkinson’s disease (PD) using a microarray. Methods. We downloaded the microarray data GSE6613 from the Gene Expression Omnibus, which included 105 samples. We selected 72 samples comprising 22 healthy control blood samples and 50 PD blood samples for further analysis. Later, we used Limma to screen DEGs and differentially expressed lncRNAs (DElncRNAs) and estimated their functions by the Gene Ontology (GO). Besides, the competing endogenous RNA (ceRNA) network, including microRNAs, lncRNAs, and mRNAs, was constructed to elucidate the regulatory mechanism. Furthermore, we performed the KEGG pathway enrichment with mRNAs in the ceRNA regulatory network and constructed a final network, including pathways, mRNAs, microRNAs, and lncRNAs. Results. Overall, we obtained 394 DEGs, including 207 upregulated DEGs and 187 downregulated DEGs, and 7 DElncRNAs, including 2 upregulated DElncRNAs and 5 downregulated DElncRNAs. Insulin-like growth factor-1 receptor (IGF1R) was considerably enriched in the endocytosis pathway. In the ceRNA regulation network, IGF1R was the target of hsa-miR-133b and lncRNAs of XIST, and PART1 could also be the target of hsa-miR-133b. While the upregulated DEGs were enriched in the GO terms of the cytoskeleton, cytoskeletal part, and microtubule cytoskeleton, the downregulated DEGs were enriched in the immune response. PRKACA was markedly enriched in numerous pathways, including the MAPK and insulin signaling pathways. Conclusions. IGF1R, PRKACA, and lncRNA-XIST could be potentially involved in PD, and these diverse molecular mechanisms could support the development of the similar treatment for PD.

DNA-methylation analysis of differentially expressed genes in fibroblast cell-lines, derived from monozygotic twins discordant for Parkinson’s disease

2020 ◽  
pp. 73-74
Author(s):  
И.Н. Рыболовлев ◽  
И.Н. Власов ◽  
А.Х. Алиева ◽  
П.А. Сломинский ◽  
М.И. Шадрина
Keyword(s):  
Parkinson’S Disease ◽  
Dna Methylation ◽  
Parkinson's Disease ◽  
Cell Lines ◽  
Differentially Expressed Genes ◽  
Regulation Of Gene Expression ◽  
Monozygotic Twins ◽  
Fibroblast Cell ◽  
Differentially Expressed ◽  
Pathogenesis Related

Болезнь Паркинсона (БП) является многофакторным гетерогенным нейродегенеративным заболеванием. Поскольку этиопатогенез БП недостаточно изучен, кроме поиска и анализа изменений на уровне ДНК, необходимо распространить фокус исследований на другие уровни: транскриптом и метилом. Изменения на уровне эпигенома можно исследовать у лиц с идентичной генетической конституцией, такой «моделью» являются дискордантные по этому заболеванию монозиготные близнецы. В исследовании приняло участие 3 пары фенотипически и генотипически монозиготных близнецов русского происхождения; В исследовании приняло участие 3 пары фенотипически и генотипически монозиготных близнецов русского происхождения. БП была уточнена у одного из каждой пары близнецов; длительность течения болезни у близнеца с БП составило по меньшей мере 7 лет.; длительность течения болезни у близнеца с БП составила по меньшей мере 7 лет. Были проанализированы метиломы крови и отобраны точки варьирующегося метилирования. Нами было найдено 8 дифференциально экспрессирующихся генов, которые могут быть дифференциально метилированы. Были выявлены различия между здоровым близнецом и близнецом с БП по уровню метилирования ДНК для ряда этих генов в клеточных линиях фибробластов. Полученные нами данные могут указывать на участие процесса ДНК-метилирования в регуляции транскрипции кандидатных генов-участников патогенеза БП. In recent years it has been convincingly demonstrated that genetic factors play an important role in progression of Parkinson’s disease (PD). Since the etiology of PD has not been elucidated completely yet, it is crucial to shift focus of the research to the broader areas - to dive into investigations of methylome and transcriptome. Epigenetic regulation of gene expression may take part in pathogenesis of PD. Changes in epigenome can be conveniently investigated in case of individuals with almost identical genetic makeup, and monozygotic twins discordant for PD may be such “model”. 3 pairs phenotypically and genotypically monozygous twins of Russian ancestry were enrolled in the study. PD was diagnosed in one of each pair. The disease duration was at least 7 years. Data on blood methylomes was analyzed. Points of variable methylation in blood methylomes were selected. With this approach, 8 differentially expressed genes were found that also may be differentially methylated. Changes in methylation level for some of this genes were found in monozygotic twins discordant for PD fibroblasts cell-lines between healthy and afflicted siblings. Acquired data might suggest participation of DNA-methylation in transcription regulation of PD pathogenesis-related candidate genes.

scholarly journals Transcriptomic profiles in Parkinson’s disease

2020 ◽  
pp. 153537022096732
Author(s):  
Lille Kurvits ◽  
Freddy Lättekivi ◽  
Ene Reimann ◽  
Liis Kadastik-Eerme ◽  
Kristjan M Kasterpalu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Brain Tissue ◽  
Differentially Expressed Genes ◽  
Meta Analysis ◽  
Rank Aggregation ◽  
Differentially Expressed ◽  
Peripheral Tissues

Transcriptomics in Parkinson’s disease offers insights into the pathogenesis of Parkinson’s disease but obtaining brain tissue has limitations. In order to bypass this issue, we profile and compare differentially expressed genes and enriched pathways (KEGG) in two peripheral tissues (blood and skin) of 12 Parkinson’s disease patients and 12 healthy controls using RNA-sequencing technique and validation with RT-qPCR. Furthermore, we compare our results to previous Parkinson’s disease post mortem brain tissue and blood results using the robust rank aggregation method. The results show no overlapping differentially expressed genes or enriched pathways in blood vs. skin in our sample sets (25 vs. 1068 differentially expressed genes with an FDR ≤ 0.05; 1 vs. 9 pathways in blood and skin, respectively). A meta-analysis from previous transcriptomic sample sets using either microarrays or RNA-Seq yields a robust rank aggregation list of cortical gene expression changes with 43 differentially expressed genes; a list of substantia nigra changes with 2 differentially expressed genes and a list of blood changes with 1 differentially expressed gene being statistically significant at FDR ≤ 0.05. In cortex 1, KEGG pathway was enriched, four in substantia nigra and two in blood. None of the differentially expressed genes or pathways overlap between these tissues. When comparing our previously published skin transcription analysis, two differentially expressed genes between the cortex robust rank aggregation and skin overlap. In this study, for the first time a meta-analysis is applied on transcriptomic sample sets in Parkinson’s disease. Simultaneously, it explores the notion that Parkinson’s disease is not just a neuronal tissue disease by exploring peripheral tissues. The comparison of different Parkinson’s disease tissues yields surprisingly few significant differentially expressed genes and pathways, suggesting that divergent gene expression profiles in distinct cell lineages, metabolic and possibly iatrogenic effects create too much transcriptomic noise for detecting significant signal. On the other hand, there are signs that point towards Parkinson’s disease-specific changes in non-neuronal peripheral tissues in Parkinson’s disease, indicating that Parkinson’s disease might be a multisystem disorder.

scholarly journals Expression Signatures of Long Noncoding RNAs in Left Ventricular Noncompaction

2021 ◽  
Vol 8 ◽  
Author(s):  
Qingshan Tian ◽  
Hanxiao Niu ◽  
Dingyang Liu ◽  
Na Ta ◽  
Qing Yang ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Noncoding Rnas ◽  
Enrichment Analysis ◽  
Left Ventricular ◽  
Long Noncoding Rnas ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Control Group ◽  
Left Ventricular Noncompaction ◽  
Ventricular Noncompaction

Long noncoding RNAs have gained widespread attention in recent years for their crucial role in biological regulation. They have been implicated in a range of developmental processes and diseases including cancer, cardiovascular, and neuronal diseases. However, the role of long noncoding RNAs (lncRNAs) in left ventricular noncompaction (LVNC) has not been explored. In this study, we investigated the expression levels of lncRNAs in the blood of LVNC patients and healthy subjects to identify differentially expressed lncRNA that develop LVNC specific biomarkers and targets for developing therapies using biological pathways. We used Agilent Human lncRNA array that contains both updated lncRNAs and mRNAs probes. We identified 1,568 upregulated and 1,141 downregulated (log fold-change > 2.0) lncRNAs that are differentially expressed between LVNC and the control group. Among them, RP11-1100L3.7 and XLOC_002730 are the most upregulated and downregulated lncRNAs. Using quantitative real-time reverse transcription polymerase chain reaction (RT-QPCR), we confirmed the differential expression of three top upregulated and downregulated lncRNAs along with two other randomly picked lncRNAs. Gene Ontology (GO) and KEGG pathways analysis with these differentially expressed lncRNAs provide insight into the cellular pathway leading to LVNC pathogenesis. We also identified 1,066 upregulated and 1,017 downregulated mRNAs. Gene set enrichment analysis (GSEA) showed that G2M, Estrogen, and inflammatory pathways are enriched in differentially expressed genes (DEG). We also identified miRNA targets for these differentially expressed genes. In this study, we first report the use of LncRNA microarray to understand the pathogenesis of LVNC and to identify several lncRNA and genes and their targets as potential biomarkers.

scholarly journals Non-invasive diagnostic tool for Parkinson’s disease by sebum RNA profile with machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuya Uehara ◽  
Shin-Ichi Ueno ◽  
Haruka Amano-Takeshige ◽  
Shuji Suzuki ◽  
Yoko Imamichi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Alpha Synuclein ◽  
Differentially Expressed ◽  
Healthy Controls ◽  
Non Invasive

AbstractParkinson's disease (PD) is a progressive neurodegenerative disease presenting with motor and non-motor symptoms, including skin disorders (seborrheic dermatitis, bullous pemphigoid, and rosacea), skin pathological changes (decreased nerve endings and alpha-synuclein deposition), and metabolic changes of sebum. Recently, a transcriptome method using RNA in skin surface lipids (SSL-RNAs) which can be obtained non-invasively with an oil-blotting film was reported as a novel analytic method of sebum. Here we report transcriptome analyses using SSL-RNAs and the potential of these expression profiles with machine learning as diagnostic biomarkers for PD in double cohorts (PD [n = 15, 50], controls [n = 15, 50]). Differential expression analysis between the patients with PD and healthy controls identified more than 100 differentially expressed genes in the two cohorts. In each cohort, several genes related to oxidative phosphorylation were upregulated, and gene ontology analysis using differentially expressed genes revealed functional processes associated with PD. Furthermore, machine learning using the expression information obtained from the SSL-RNAs was able to efficiently discriminate patients with PD from healthy controls, with an area under the receiver operating characteristic curve of 0.806. This non-invasive gene expression profile of SSL-RNAs may contribute to early PD diagnosis based on the neurodegeneration background.

scholarly journals Long Noncoding RNAs and Messenger RNAs Expression Profiles Potentially Regulated by ZBTB7A in Nasopharyngeal Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Fei Liu ◽  
Jiazhang Wei ◽  
Yanrong Hao ◽  
Fengzhu Tang ◽  
Wei Jiao ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Fatty Acid Synthase ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Messenger Rnas ◽  
Regulatory Pathways ◽  
Different Levels

Our previous studies showed that ZBTB7A played an important role in promoting nasopharyngeal carcinoma (NPC) progression. However, molecular mechanisms of different levels of ZBTB7A are still unclear. It is necessary to search molecular markers which are closely connected with ZBTB7A. We selected NPC sublines CNE2 with stably transfecting empty plasmid (negative control, NC) and short hair RNA (shRNA) plasmid targeting ZBTB7A as research objectives. Microarray was used to screen differentially expressed long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) via shRNA-CNE2 versus NC-CNE2. Quantitative PCR (qPCR) was used to validate lncRNAs and mRNAs from the sublines, chronic rhinitis, and NPC tissues. Bioinformatics was used to analyze regulatory pathways which were connected with ZBTB7A. The 1501 lncRNAs (long noncoding RNAs) and 1275 differentially expressed mRNAs were upregulated or downregulated over 2-fold. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the upregulated or downregulated carbohydrate and lipid metabolisms probably involved in carcinogenicity of shRNA-CNE2 (P-value cut-off was 0.05). In order to find the molecular mechanisms of ZBTB7A, we validated 12 differentially expressed lncRNAs and their nearby mRNAs by qPCR. Most of the differentially expressed mRNAs are closely connected with carbohydrate and lipid metabolisms in multiply cancers. Furthermore, part of them were validated in NPC and rhinitis tissues by qPCR. As a result, NR_047538, ENST00000442852, and fatty acid synthase (FASN) were closely associated with NPC. ZBTB7A had a positive association with NR_047538 and negative associations with ENST00000442852 and FASN. The results probably provide novel candidate biomarkers for NPC progression with different levels of ZBTB7A.

scholarly journals Identification and Interaction Analysis of Significant Genes and MicroRNAs in Pterygium

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Siying He ◽  
Hui Sun ◽  
Yifang Huang ◽  
Shiqi Dong ◽  
Chen Qiao ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas

Purpose. MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify the key genes and miRNAs in pterygium and to explore the underlying molecular mechanisms. Methods. MiRNA expression was initially extracted and pooled by published literature. Microarray data about differentially expressed genes was downloaded from Gene Expression Omnibus (GEO) database and analyzed with the R programming language. Functional and pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network was constructed with the STRING database. The associations between chemicals, differentially expressed miRNAs, and differentially expressed genes were predicted using the online resource. All the networks were constructed using Cytoscape. Results. We found that 35 miRNAs and 301 genes were significantly differentially expressed. Functional enrichment analysis showed that upregulated genes were significantly enriched in extracellular matrix (ECM) organization, while downregulated genes were mainly involved in cell death and apoptotic process. Finally, we concluded the chemical-gene affected network, miRNA-mRNA interacted networks, and significant pathway network. Conclusion. We identified lists of differentially expressed miRNAs and genes and their possible interaction in pterygium. The networks indicated that ECM breakdown and EMT might be two major pathophysiological mechanisms and showed the potential significance of PI3K-Akt signalling pathway. MiR-29b-3p and collagen family (COL4A1 and COL3A1) might be new treatment target in pterygium.

scholarly journals Human 45,X Fibroblast Transcriptome Reveals Distinct Differentially Expressed Genes Including Long Noncoding RNAs Potentially Associated with the Pathophysiology of Turner Syndrome

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e100076 ◽  
Author(s):  
Shriram N. Rajpathak ◽  
Shamsudheen Karuthedath Vellarikkal ◽  
Ashok Patowary ◽  
Vinod Scaria ◽  
Sridhar Sivasubbu ◽  
...  
Keyword(s):  
Turner Syndrome ◽  
Differentially Expressed Genes ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed

scholarly journals Transcriptome Analysis of Long Noncoding RNAs in Toll-Like Receptor 3-Activated Mesenchymal Stem Cells

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Shihua Wang ◽  
Xiaoxia Li ◽  
Robert Chunhua Zhao
Keyword(s):  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Length Distribution ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Therapeutic Effects ◽  
Wide Range

Mesenchymal stem cells (MSCs) possess great immunomodulatory capacity which lays the foundation for their therapeutic effects in a variety of diseases. Recently, toll-like receptors (TLR) have been shown to modulate MSC functions; however, the underlying molecular mechanisms are poorly understood. Emerging evidence suggests that long noncoding RNAs (lncRNAs) are an important class of regulators involved in a wide range of biological processes. To explore the potential involvement of lncRNAs in TLR stimulated MSCs, we performed a comprehensive lncRNA and mRNA profiling through microarray. 10.2% of lncRNAs (1733 out of 16967) and 15.1% of mRNA transcripts (1760 out of 11632) were significantly differentially expressed (absolute fold-change≥5 ,Pvalue≤0.05) in TLR3 stimulated MSCs. Furthermore, we characterized the differentially expressed lncRNAs through their classes and length distribution and correlated them with differentially expressed mRNA. Here, we are the first to determine genome-wide lncRNAs expression patterns in TLR3 stimulated MSCs by microarray and this work could provide a comprehensive framework of the transcriptome landscapes of TLR3 stimulated MSCs.

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