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Periodontal disease, a multifactorial inflammatory condition affecting the supporting structures of the teeth, has been increasingly recognized for its association with various systemic diseases. Understanding the molecular comorbidities of periodontal disease is crucial for elucidating shared pathogenic mechanisms and potential therapeutic targets. In this study, we conducted comprehensive literature and biological database mining by utilizing DisGeNET2R for extracting gene-disease associations, Romin for integrating and modeling molecular interaction networks, and Rentrez R libraries for accessing and retrieving relevant information from NCBI databases. This integrative bioinformatics approach enabled us to systematically identify diseases sharing associated genes, proteins, or molecular pathways with periodontitis. Our analysis revealed significant molecular overlaps between periodontal disease and several systemic conditions, including cardiovascular diseases, diabetes mellitus, rheumatoid arthritis, and inflammatory bowel diseases. Shared molecular mechanisms implicated in the pathogenesis of these diseases and periodontitis encompassed dysregulation of inflammatory mediators, immune response pathways, oxidative stress pathways, and alterations in the extracellular matrix. Furthermore, network analysis unveiled the key hub genes and proteins (such as TNF, IL6, PTGS2, IL10, NOS3, IL1B, VEGFA, BCL2, STAT3, LEP and TP53) that play pivotal roles in the crosstalk between periodontal disease and its comorbidities, offering potential targets for therapeutic intervention. Insights gained from this integrative approach shed light on the intricate interplay between periodontal health and systemic well-being, emphasizing the importance of interdisciplinary collaboration in developing personalized treatment strategies for patients with periodontal disease and associated comorbidities.
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Comorbilidad , Redes Reguladoras de Genes , Enfermedades Periodontales , Humanos , Enfermedades Periodontales/genética , Enfermedades Periodontales/epidemiología , Mapas de Interacción de Proteínas/genética , Biología Computacional/métodos , Periodontitis/genética , Periodontitis/epidemiología , Enfermedades Cardiovasculares/genética , Enfermedades Cardiovasculares/epidemiología , Artritis Reumatoide/genética , Artritis Reumatoide/epidemiología , Enfermedades Inflamatorias del Intestino/genética , Enfermedades Inflamatorias del Intestino/epidemiologíaRESUMEN
Comprehension of the genetic basis of temperament has been improved by recent advances in the identification of genes and genetic variants. However, due to the complexity of the temperament traits, the elucidation of the genetic architecture of temperament is incomplete. A systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to analyze candidate genes related to bovine temperament, using bovine as the population, SNPs and genes as the exposure, and temperament test as the outcome, as principal search terms for population, exposure, and outcome (PEO) categories to define the scope of the search. The search results allowed the selection of 36 articles after removing duplicates and filtering by relevance. One hundred-two candidate genes associated with temperament traits were identified. The genes were further analyzed to construct an interaction network using the STRING database, resulting in 113 nodes and 346 interactions and the identification of 31 new candidate genes for temperament. Notably, the main genes identified were SST and members of the Kelch family. The candidate genes displayed interactions with pathways associated with different functions such as AMPA receptors, hormones, neuronal maintenance, protein signaling, neuronal regulation, serotonin synthesis, splicing, and ubiquitination activities. These new findings demonstrate the complexity of interconnected biological processes that regulate behavior and stress response in mammals. This insight now enables our targeted analysis of these newly identified temperament candidate genes in bovines.
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Redes Reguladoras de Genes , Polimorfismo de Nucleótido Simple , Temperamento , Bovinos/genética , Animales , Mapas de Interacción de Proteínas/genéticaRESUMEN
This study aimed to perform exhaustive bioinformatic analysis by using GSE29221 micro-array maps obtained from healthy controls and Type 2 Diabetes (T2DM) patients. Raw data are downloaded from the Gene Expression Omnibus database and processed by the limma package in R software to identify Differentially Expressed Genes (DEGs). Gene ontology functional analysis and Kyoto Gene Encyclopedia and Genome Pathway analysis are performed to determine the biological functions and pathways of DEGs. A protein interaction network is constructed using the STRING database and Cytoscape software to identify key genes. Finally, immune infiltration analysis is performed using the Cibersort method. This study has implications for understanding the underlying molecular mechanism of T2DM and provides potential targets for further research.
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Biología Computacional , Diabetes Mellitus Tipo 2 , Perfilación de la Expresión Génica , Humanos , Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/inmunología , Mapas de Interacción de Proteínas/genética , Redes Reguladoras de Genes/genética , Ontología de Genes , Bases de Datos Genéticas , Estudios de Casos y ControlesRESUMEN
Blood selenium (Se) concentrations differ substantially by population and could be influenced by genetic variants, increasing Se deficiency-related diseases. We conducted a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with serum Se deficiency in 382 adults with admixed ancestry. Genotyping arrays were combined to yield 90,937 SNPs. R packages were applied to quality control and imputation. We also performed the ancestral proportion analysis. The Search Tool for the Retrieval of Interacting Genes was used to interrogate known protein-protein interaction networks (PPIs). Our ancestral proportion analysis estimated 71% of the genome was from Caucasians, 22% was from Africans, and 8% was from East Asians. We identified the SNP rs1561573 in the TraB domain containing 2B (TRABD2B), rs425664 in MAF bZIP transcription factor (MAF), rs10444656 in spermatogenesis-associated 13 (SPATA13), and rs6592284 in heat shock protein nuclear import factor (HIKESHI) genes. The PPI analysis showed functional associations of Se deficiency, thyroid hormone metabolism, NRF2-ARE and the Wnt pathway, and heat stress. Our findings show evidence of a genetic association between Se deficiency and metabolic pathways indirectly linked to Se regulation, reinforcing the complex relationship between Se intake and the endogenous factors affecting the Se requirements for optimal health.
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Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple , Selenio , Adulto , Femenino , Humanos , Masculino , Persona de Mediana Edad , Brasil , Predisposición Genética a la Enfermedad , Genotipo , Mapas de Interacción de Proteínas/genética , Selenio/sangre , Selenio/deficiencia , Población Blanca/genética , Pueblo Africano , Pueblos del Este de AsiaRESUMEN
OBJECTIVE: Our aim in this study is to identify the core genes of chronic rhinosinusitis with nasal polyps and analyze the correlations between it and inflammation-related genes. METHODS: GSE72713 dataset containing gene expression data of ECRSwNP, nonECRSwNP and healthy samples was obtained from Gene Expression Omnibus (GEO) and filtered by limma to identify DEGs among three groups, then the functions and correlated pathways of DEGs were analyzed using GO and KEGG. The core DEGs were selected by the intersection of DEGs and the PPI network was constructed via STRING. The correlations between the expression levels of CRSwNP core gene and inflammation-related genes were analyzed via the Mann-Whitney U test. RESULTS: The DEGs among ECRSwNP, nonECRSwNP, and CTRL were filtered respectively, and enrichment analysis showed they were associated with olfaction and/or immune responses. The PPI network was constructed by 7 core DEGs obtained via the intersection among three groups, and ALOX15 was confirmed as the core gene in the network. Subsequently, the correlations between the expression levels of ALOX15 and inflammation-related genes were illustrated. CONCLUSION: In this study, the core gene ALOX15 was selected from the DEGs among ECRSwNP, nonECRSwNP, and CTRL. IL5, IL1RL1, and IL1RAP were found to exhibit a significant positive correlation with ALOX15. LEVEL OF EVIDENCE: Level 3.
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Inflamación , Pólipos Nasales , Rinitis , Sinusitis , Pólipos Nasales/genética , Humanos , Sinusitis/genética , Rinitis/genética , Enfermedad Crónica , Inflamación/genética , Araquidonato 15-Lipooxigenasa/genética , Perfilación de la Expresión Génica , Mapas de Interacción de Proteínas/genética , Estudios de Casos y Controles , RinosinusitisRESUMEN
Atypical parkinsonism (AP) is a group of complex neurodegenerative disorders with marked clinical and pathophysiological heterogeneity. The use of systems biology tools may contribute to the characterization of hub-bottleneck genes, and the identification of its biological pathways to broaden the understanding of the bases of these disorders. A systematic search was performed on the DisGeNET database, which integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. The tools STRING 11.0 and Cytoscape 3.8.2 were used for analysis of protein-protein interaction (PPI) network. The PPI network topography analyses were performed using the CytoHubba 0.1 plugin for Cytoscape. The hub and bottleneck genes were inserted into 4 different sets on the InteractiveVenn. Additional functional enrichment analyses were performed to identify Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology for a described set of genes. The systematic search in the DisGeNET database identified 485 genes involved with Atypical Parkinsonism. Superimposing these genes, we detected a total of 31 hub-bottleneck genes. Moreover, our functional enrichment analyses demonstrated the involvement of these hub-bottleneck genes in 3 major KEGG pathways. We identified 31 highly interconnected hub-bottleneck genes through a systems biology approach, which may play a key role in the pathogenesis of atypical parkinsonism. The functional enrichment analyses showed that these genes are involved in several biological processes and pathways, such as the glial cell development, glial cell activation and cognition, pathways were related to Alzheimer disease and Parkinson disease. As a hypothesis, we highlight as possible key genes for AP the MAPT (microtubule associated protein tau), APOE (apolipoprotein E), SNCA (synuclein alpha) and APP (amyloid beta precursor protein) genes.
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Redes y Vías Metabólicas , Trastornos Parkinsonianos , Mapas de Interacción de Proteínas , Biología de Sistemas , Humanos , Trastornos Parkinsonianos/genética , Trastornos Parkinsonianos/metabolismo , Redes y Vías Metabólicas/genética , Mapas de Interacción de Proteínas/genética , Redes Reguladoras de Genes/genética , AnimalesRESUMEN
Odontogenic keratocyst (OK) is a benign intraosseous cystic lesion characterized by a parakeratinized stratified squamous epithelial lining with palisade basal cells. It represents 10-12% of odontogenic cysts. The changes in its classification as a tumor or cyst have increased interest in its pathogenesis. OBJECTIVE: Identify key genes in the pathogenesis of sporadic OK through in silico analysis. MATERIALS AND METHODS: The GSE38494 technical sheet on OK was analyzed using GEOR2. Their functional and canonical signaling pathways were enriched in the NIH-DAVID bioinformatic platform. The protein-protein interaction network was constructed by STRING and analyzed with Cytoscape-MCODE software v 3.8.2 (score > 4). Post-enrichment analysis was performed by Cytoscape-ClueGO. RESULTS: A total of 768 differentially expressed genes (DEG) with a fold change (FC) greater than 2 and 469 DEG with an FC less than 2 were identified. In the post-enrichment analysis of upregulated genes, significance was observed in criteria related to the organization of the extracellular matrix, collagen fibers, and endodermal differentiation, while the downregulated genes were related to defensive response mechanisms against viruses and interferon-gamma activation. CONCLUSIONS: Our in silico analysis showed a significant relationship with mechanisms of extracellular matrix organization, interferon-gamma activation, and response to viral infections, which must be validated through molecular assays.
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Quistes Odontogénicos , Tumores Odontogénicos , Humanos , Interferón gamma , Quistes Odontogénicos/genética , Quistes Odontogénicos/patología , Tumores Odontogénicos/patología , Mapas de Interacción de Proteínas/genéticaRESUMEN
INTRODUCTION: Zika virus (ZIKV) is a human teratogen that causes congenital Zika syndrome (CZS). AXL, TLR3, and STAT2 are proteins involved in the ZIKV's entry into cells (AXL) and host's immune response (TLR3 and STAT2). In this study, we evaluated the role of genetic polymorphisms in these three genes as risk factors to CZS, and highlighted which proteins that interact with them could be important for ZIKV infection and teratogenesis. MATERIALS AND METHODS: We evaluate eighty-eight children exposed to ZIKV during the pregnancy, 40 with CZS and 48 without congenital anomalies. The evaluated polymorphisms in AXL (rs1051008), TLR3 (rs3775291), and STAT2 (rs2066811) were genotyped using TaqMan® Genotyping Assays. A protein-protein interaction network was created in STRING database and analyzed in Cytoscape software. RESULTS: We did not find any statistical significant association among the polymorphisms and the occurrence of CZS. Through the analyses of the network composed by AXL, TLR3, STAT2 and their interactions targets, we found that EGFR and SRC could be important proteins for the ZIKV infection and its teratogenesis. CONCLUSION: In summary, our results demonstrated that the evaluated polymorphisms do not seem to represent risk factors for CZS; however, EGFR and SRC appear to be important proteins that should be investigated in future studies.
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Teratogénesis , Infección por el Virus Zika , Virus Zika , Embarazo , Niño , Femenino , Humanos , Infección por el Virus Zika/genética , Virus Zika/fisiología , Tirosina Quinasa del Receptor Axl , Receptor Toll-Like 3/genética , Receptor Toll-Like 3/metabolismo , Proteínas Tirosina Quinasas Receptoras/genética , Proteínas Tirosina Quinasas Receptoras/metabolismo , Proteínas Proto-Oncogénicas/genética , Mapas de Interacción de Proteínas/genética , Receptores ErbB/metabolismo , Factor de Transcripción STAT2/genética , Factor de Transcripción STAT2/metabolismoRESUMEN
BACKGROUND: Childhood obesity is triggered by a complex interplay of environmental, genetic, and epigenetic factors; however, the molecular mechanisms behind this disease are not completely elucidated. Thus, the aim of this study was to investigate molecular mechanisms involved in childhood obesity by implementing a systems biology approach. METHODS: Experimentally validated and computationally predicted genes related to childhood obesity were downloaded from DisGeNET database. A protein-protein interaction (PPI) network was constructed using the STRING database and analyzed at Cytoscape web-tool. Hub-bottleneck genes and functional clusters were identified through CytoHubba and MCODE plugins, respectively. Functional enrichment analyses were performed based on Gene Ontology terms and KEGG Pathways. RESULTS: The DisGeNET search retrieved 191 childhood obesity-related genes. The resulting PPI network contained 12 hub-bottleneck genes (INS, LEP, STAT3, POMC, ALB, TNF, BDNF, CAT, GCG, PPARG, VEGFA, and ADIPOQ) and 4 functional clusters, with cluster 1 showing the highest interaction score. Genes at this cluster were enriched at inflammation, carbohydrate, and lipid metabolism pathways. With exception of POMC, all hub-bottleneck genes were found in cluster 1, which contains highly connected genes that possibly play key roles in obesity-related pathways. CONCLUSIONS: Our systems biology approach revealed a set of highly interconnected genes associated with childhood obesity, providing comprehensive information regarding genetic and molecular factors involved in the pathogenesis of this disease.
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Redes Reguladoras de Genes , Obesidad Infantil , Niño , Biología Computacional/métodos , Perfilación de la Expresión Génica , Humanos , Obesidad Infantil/genética , Proopiomelanocortina/genética , Mapas de Interacción de Proteínas/genética , Biología de SistemasRESUMEN
BACKGROUND: Gastric cancer (GC) is the third leading cause of cancer worldwide. According to the Lauren classification, gastric adenocarcinoma is divided into two subtypes: diffuse and intestinal. The development of intestinal gastric cancer (IGC) can take years and involves multiple factors. OBJECTIVE: To investigate the protein profile of tumor samples from patients with IGC in comparison with adjacent nontumor tissue samples. METHODS: We used label-free nano-LC-MS/MS to identify proteins from the tissues samples. The results were analyzed using MetaCore™ software to access functional enrichment information. Protein-protein interactions (PPI) were predicted using STRING analysis. Hub proteins were determined using the Cytoscape plugin, CytoHubba. Survival analysis was performed using KM plotter. We identified 429 differentially expressed proteins whose pathways and processes were related to protein folding, apoptosis, and immune response. RESULTS: The PPI network of these proteins showed enrichment modules related to the regulation of cell death, immune system, neutrophil degranulation, metabolism of RNA and chromatin DNA binding. From the PPI network, we identified 20 differentially expressed hub proteins, and assessed the prognostic value of the expression of genes that encode them. Among them, the expression of four hub genes was significantly associated with the overall survival of IGC patients. CONCLUSIONS: This study reveals important findings that affect IGC development based on specific biological alterations in IGC patients. Bioinformatics analysis showed that the pathogenesis of IGC patients is complex and involves different interconnected biological processes. These findings may be useful in research on new targets to develop novel therapies to improve the overall survival of patients with IGC.
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MicroARNs , Neoplasias Gástricas , Biología Computacional/métodos , Perfilación de la Expresión Génica/métodos , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Humanos , MicroARNs/genética , Pronóstico , Mapas de Interacción de Proteínas/genética , Neoplasias Gástricas/genética , Neoplasias Gástricas/patología , Espectrometría de Masas en TándemRESUMEN
Cystic fibrosis (CF) is an autosomal recessive disorder, caused by diverse genetic variants for the CF transmembrane conductance regulator (CFTR) protein. Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study is aimed at predicting cell signaling pathways present in different tissues of fibrocystic patients, homozygous for p.Phe508del. The study involved analysis of two microarray datasets, E-GEOD-15568 and E-MTAB-360 corresponding to the rectal and bronchial epithelium, respectively, obtained from the ArrayExpress repository. Particularly, differentially expressed genes (DEGs) were predicted, protein-protein interaction (PPI) networks were designed, and centrality and functional interaction networks were analyzed. The study reported that p.Phe508del-mutated CFTR-allele in homozygous state influenced the whole gene expression in each tissue differently. Interestingly, gene ontology (GO) term enrichment analysis revealed that only "neutrophil activation" was shared between both tissues; however, nonshared DEGs were grouped into the same GO term. For further verification, functional interaction networks were generated, wherein no shared nodes were reported between these tissues. These results suggested that the p.Phe508del-mutated CFTR-allele in homozygous state promoted tissue-specific pathways in fibrocystic patients. The generated data might further assist in prediction diagnosis to define biomarkers or devising therapeutic strategies.
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Fibrosis Quística/genética , Transducción de Señal/genética , Alelos , Biomarcadores/metabolismo , Epitelio/fisiología , Expresión Génica/genética , Homocigoto , Humanos , Mutación/genética , Mapas de Interacción de Proteínas/genética , Biología de Sistemas/métodosRESUMEN
BACKGROUND: Bacterial genomes are being deposited into online databases at an increasing rate. Genome annotation represents one of the first efforts to understand organisms and their diseases. Some evolutionary relationships capable of being annotated only from genomes are conserved gene neighbourhoods (CNs), phylogenetic profiles (PPs), and gene fusions. At present, there is no standalone software that enables networks of interactions among proteins to be created using these three evolutionary characteristics with efficient and effective results. RESULTS: We developed GENPPI software for the ab initio prediction of interaction networks using predicted proteins from a genome. In our case study, we employed 50 genomes of the genus Corynebacterium. Based on the PP relationship, GENPPI differentiated genomes between the ovis and equi biovars of the species Corynebacterium pseudotuberculosis and created groups among the other species analysed. If we inspected only the CN relationship, we could not entirely separate biovars, only species. Our software GENPPI was determined to be efficient because, for example, it creates interaction networks from the central genomes of 50 species/lineages with an average size of 2200 genes in less than 40 min on a conventional computer. Moreover, the interaction networks that our software creates reflect correct evolutionary relationships between species, which we confirmed with average nucleotide identity analyses. Additionally, this software enables the user to define how he or she intends to explore the PP and CN characteristics through various parameters, enabling the creation of customized interaction networks. For instance, users can set parameters regarding the genus, metagenome, or pangenome. In addition to the parameterization of GENPPI, it is also the user's choice regarding which set of genomes they are going to study. CONCLUSIONS: GENPPI can help fill the gap concerning the considerable number of novel genomes assembled monthly and our ability to process interaction networks considering the noncore genes for all completed genome versions. With GENPPI, a user dictates how many and how evolutionarily correlated the genomes answer a scientific query.
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Mapas de Interacción de Proteínas , Programas Informáticos , Animales , Filogenia , Mapas de Interacción de Proteínas/genética , OvinosRESUMEN
Transposable Elements (TEs) are ubiquitous genetic elements with the ability to move within a genome. TEs contribute to a large fraction of the repetitive elements of a genome, and because of their nature, they are not routinely analyzed in RNA-Seq gene expression studies. Amyotrophic Lateral Sclerosis (ALS) is a lethal neurodegenerative disease, and a well-accepted model for its study is the mouse harboring the human SOD1G93A mutant. In this model, landmark stages of the disease can be recapitulated at specific time points, making possible to understand changes in gene expression across time. While there are several works reporting TE activity in ALS models, they have not explored their activity through the disease progression. Moreover, they have done it at the expense of losing their locus of expression. Depending on their genomic location, TEs can regulate genes in cis and in trans, making locus-specific analysis of TEs of importance in order to understand their role in modulating gene expression. Particularly, the locus-specific role of TEs in ALS has not been fully elucidated. In this work, we analyzed publicly available RNA-Seq datasets of the SOD1G93A mouse model, to understand the locus-specific role of TEs. We show that TEs become up-regulated at the early stages of the disease, and via statistical associations, we speculate that they can regulate several genes, which in turn might be contributing to the genetic dysfunction observed in ALS.
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Esclerosis Amiotrófica Lateral/genética , Elementos Transponibles de ADN/genética , Progresión de la Enfermedad , Sitios Genéticos , Superóxido Dismutasa/genética , Animales , Simulación por Computador , Modelos Animales de Enfermedad , Perfilación de la Expresión Génica , Ratones Transgénicos , Mapas de Interacción de Proteínas/genética , RNA-Seq , Reproducibilidad de los Resultados , Programas InformáticosRESUMEN
Wound healing (WH) and cancer seem to share common cellular and molecular processes that could work in a tight balance to maintain tissue homeostasis or, when unregulated, drive tumor progression. The "Cancer Hallmarks" comprise crucial biological properties that mediate the advancement of the disease and affect patient prognosis. These hallmarks have been proposed to overlap with essential features of the WH process. However, common hallmarks and proteins actively participating in both processes have yet to be described. In this work we identify 21 WH proteins strongly linked with solid tumors by integrated TCGA Pan-Cancer and multi-omics analyses. These proteins were associated with eight of the ten described cancer hallmarks, especially avoiding immune destruction. These results show that WH and cancer's common proteins are involved in the microenvironment modification of solid tissues and immune system regulation. This set of proteins, between WH and cancer, could represent key targets for developing therapies.
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Neoplasias/metabolismo , Proteoma/metabolismo , Proteómica/métodos , Transducción de Señal/fisiología , Cicatrización de Heridas/fisiología , Perfilación de la Expresión Génica/métodos , Predisposición Genética a la Enfermedad/genética , Genómica/métodos , Homeostasis/genética , Homeostasis/fisiología , Humanos , Mutación , Neoplasias/genética , Fenotipo , Mapas de Interacción de Proteínas/genética , Proteoma/genética , Transducción de Señal/genética , Microambiente Tumoral/genética , Cicatrización de Heridas/genéticaRESUMEN
ABSTRACT Objective: Interstitial cystitis (IC)/bladder pain syndrome (BPS) is a chronic inflammatory disease that can cause bladder pain and accompanying symptoms, such as long-term urinary frequency and urgency. IC/BPS can be ulcerative or non-ulcerative. The aim of this study was to explore the core genes involved in the pathogenesis of ulcerative IC, and thus the potential biomarkers for clinical treatment. Materials and Methods: First, the gene expression dataset GSE11783 was downloaded using the Gene Expression Omnibus (GEO) database and analyzed using the limma package in R to identify differentially expressed genes (DEGs). Then, the Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for Gene Ontology (GO) functional analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for pathway enrichment analysis. Finally, the protein-protein interaction (PPI) network was constructed, and key modules and hub genes were determined using the STRING and Cytoscape software. The resulting key modules were then analyzed for tissue-specific gene expression using BioGPS. Results: A total of 216 up-regulated DEGs and 267 down-regulated genes were identified, and three key modules and nine hub genes were obtained. Conclusion: The core genes (CXCL8, CXCL1, IL6) obtained in this study may be potential biomarkers of interstitial cystitis with guiding significance for clinical treatment.
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Humanos , Cistitis Intersticial/genética , Programas Informáticos , Perfilación de la Expresión Génica , Mapas de Interacción de Proteínas/genética , Ontología de GenesRESUMEN
OBJECTIVE: Interstitial cystitis (IC)/bladder pain syndrome (BPS) is a chronic inflammatory disease that can cause bladder pain and accompanying symptoms, such as long-term urinary frequency and urgency. IC/BPS can be ulcerative or non-ulcerative. The aim of this study was to explore the core genes involved in the pathogenesis of ulcerative IC, and thus the potential biomarkers for clinical treatment. MATERIALS AND METHODS: First, the gene expression dataset GSE11783 was downloaded using the Gene Expression Omnibus (GEO) database and analyzed using the limma package in R to identify differentially expressed genes (DEGs). Then, the Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for Gene Ontology (GO) functional analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for pathway enrichment analysis. Finally, the protein-protein interaction (PPI) network was constructed, and key modules and hub genes were determined using the STRING and Cytoscape software. The resulting key modules were then analyzed for tissue-specific gene expression using BioGPS. RESULTS: A total of 216 up-regulated DEGs and 267 down-regulated genes were identified, and three key modules and nine hub genes were obtained. CONCLUSION: The core genes (CXCL8, CXCL1, IL6) obtained in this study may be potential biomarkers of interstitial cystitis with guiding significance for clinical treatment.
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Cistitis Intersticial , Cistitis Intersticial/genética , Perfilación de la Expresión Génica , Ontología de Genes , Humanos , Mapas de Interacción de Proteínas/genética , Programas InformáticosRESUMEN
PURPOSE: To study the use of in silica model to better understand and propose new markers of ovarian response to controlled ovarian stimulation before IVF. METHODS: A systematic review and in silica model using bioinformatics. After the selection of 103 papers from a systematic review process, we performed a GRADE qualification of all included papers for evidence-based quality evaluation. We included 57 genes in the silica model using a functional protein network interaction. Moreover, the construction of protein-protein interaction network was done importing these results to Cytoscape. Therefore, a cluster analysis using MCODE was done, which was exported to a plugin BINGO to determine Gene Ontology. A p value of < 0.05 was considered significant, using a Bonferroni correction test. RESULTS: In silica model was robust, presenting an ovulation-related gene network with 87 nodes (genes) and 348 edges (interactions between the genes). Related to the network centralities, the network has a betweenness mean value = 102.54; closeness mean = 0.007; and degree mean = 8.0. Moreover, the gene with a higher betweenness was PTPN1. Genes with the higher closeness were SRD5A1 and HSD17B3, and the gene with the lowest closeness was GDF9. Finally, the gene with a higher degree value was UBB; this gene participates in the regulation of TP53 activity pathway. CONCLUSIONS: This systematic review demonstrated that we cannot use any genetic marker before controlled ovarian stimulation for IVF. Moreover, in silica model is a useful tool for understanding and finding new markers for an IVF individualization. PROSPERO: CRD42020197185.
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Fertilización In Vitro , Ovario/metabolismo , Inducción de la Ovulación , Mapas de Interacción de Proteínas/genética , Biología Computacional , Simulación por Computador , Femenino , Redes Reguladoras de Genes/genética , Humanos , Ovario/crecimiento & desarrollo , PronósticoRESUMEN
BACKGROUND: Atrial fibrillation (AF) is a complex disease and affects millions of people around the world. The biological mechanisms that are involved with AF are complex and still need to be fully elucidated. Therefore, we performed a meta-analysis of transcriptome data related to AF to explore these mechanisms aiming at more sensitive and reliable results. METHODS: Ten public transcriptomic datasets were downloaded, analyzed for quality control, and individually pre-processed. Differential expression analysis was carried out for each dataset, and the results were meta-analytically aggregated using the rth ordered p value method. We analyzed the final list of differentially expressed genes through network analysis, namely topological and modularity analysis, and functional enrichment analysis. RESULTS: The meta-analysis of transcriptomes resulted in 1197 differentially expressed genes, whose protein-protein interaction network presented 39 hubs-bottlenecks and four main identified functional modules. These modules were enriched for 39, 20, 64, and 10 biological pathways involved with the pathophysiology of AF, especially with the disease's structural and electrical remodeling processes. The stress of the endoplasmic reticulum, protein catabolism, oxidative stress, and inflammation are some of the enriched processes. Among hub-bottlenecks genes, which are highly connected and probably have a key role in regulating these processes, HSPA5, ANK2, CTNNB1, and MAPK1 were identified. CONCLUSION: Our approach based on transcriptome meta-analysis revealed a set of key genes that demonstrated consistent overall changes in expression patterns associated with AF despite data heterogeneity related, among others, to type of tissue. Further experimental investigation of our findings may shed light on the pathophysiology of the disease and contribute to the identification of new therapeutic targets.
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Fibrilación Atrial/genética , Fibrilación Atrial/fisiopatología , Transcriptoma/genética , Chaperón BiP del Retículo Endoplásmico , Perfilación de la Expresión Génica , Regulación de la Expresión Génica , Redes Reguladoras de Genes , Humanos , Mapas de Interacción de Proteínas/genéticaRESUMEN
The utilization of different carbon sources in filamentous fungi underlies a complex regulatory network governed by signaling events of different protein kinase pathways, including the high osmolarity glycerol (HOG) and protein kinase A (PKA) pathways. This work unraveled cross-talk events between these pathways in governing the utilization of preferred (glucose) and non-preferred (xylan, xylose) carbon sources in the reference fungus Aspergillus nidulans. An initial screening of a library of 103 non-essential protein kinase (NPK) deletion strains identified several mitogen-activated protein kinases (MAPKs) to be important for carbon catabolite repression (CCR). We selected the MAPKs Ste7, MpkB, and PbsA for further characterization and show that they are pivotal for HOG pathway activation, PKA activity, CCR via regulation of CreA cellular localization and protein accumulation, as well as for hydrolytic enzyme secretion. Protein-protein interaction studies show that Ste7, MpkB, and PbsA are part of the same protein complex that regulates CreA cellular localization in the presence of xylan and that this complex dissociates upon the addition of glucose, thus allowing CCR to proceed. Glycogen synthase kinase (GSK) A was also identified as part of this protein complex and shown to potentially phosphorylate two serine residues of the HOG MAPKK PbsA. This work shows that carbon source utilization is subject to cross-talk regulation by protein kinases of different signaling pathways. Furthermore, this study provides a model where the correct integration of PKA, HOG, and GSK signaling events are required for the utilization of different carbon sources.
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Proteínas Quinasas Dependientes de AMP Cíclico/genética , Glucosa/metabolismo , Glucógeno Sintasa Quinasas/genética , Proteínas Quinasas Activadas por Mitógenos/genética , Aspergillus nidulans/enzimología , Represión Catabólica/genética , Hongos/genética , Hongos/metabolismo , Glicerol/metabolismo , Concentración Osmolar , Fosforilación/genética , Mapas de Interacción de Proteínas/genética , Proteínas Represoras/genética , Xilosa/metabolismoRESUMEN
Endometrial cancer (EC) is the sixth most common cancer in women worldwide. Early diagnosis is critical in recurrent EC management. The present study aimed to identify biomarkers of EC early recurrence using a workflow that combined text and data mining databases (DisGeNET, Gene Expression Omnibus), a prioritization algorithm to select a set of putative candidates (ToppGene), proteinprotein interaction network analyses (Search Tool for the Retrieval of Interacting Genes, cytoHubba), association analysis of selected genes with clinicopathological parameters, and survival analysis (KaplanMeier and Cox proportional hazard ratio analyses) using a The Cancer Genome Atlas cohort. A total of 10 genes were identified, among which the targeting protein for Xklp2 (TPX2) was the most promising independent prognostic biomarker in stage I EC. TPX2 expression (mRNA and protein) was higher (P<0.0001 and P<0.001, respectively) in ETS variant transcription factor 5overexpressing Hec1a and Ishikawa cells, a previously reported cell model of aggressive stage I EC. In EC biopsies, TPX2 mRNA expression levels were higher (P<0.05) in high grade tumors (grade 3) compared with grade 12 tumors (P<0.05), in tumors with deep myometrial invasion (>50% compared with <50%; P<0.01), and in intermediatehigh recurrence risk tumors compared with lowrisk tumors (P<0.05). Further validation studies in larger and independent EC cohorts will contribute to confirm the prognostic value of TPX2.