Effect of Polymorphisms in the FCN1, FCN2, and FCN3 Genes on the Susceptibility to Develop Rheumatoid Arthritis: A Systematic Review

Gil‐Quiñones, Sebastian Ramiro; Castañeda, Luz Dary Gutiérrez; Larios-Salazar, Lorena; Mejia-Mesa, Susana; Motta, Adriana; Tovar-Parra, David

doi:10.1155/2022/1730996

Cited by 2 publications

(3 citation statements)

References 27 publications

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“…CX3CR1 [666], CD177 [690], PF4 [691], FFAR2 [692], MPO (myeloperoxidase) [693], F11 [694], S100A8 [695], VEGFD (vascular endothelial growth factor D) [674], IL1A [696], BPI (bactericidal permeability increasing protein) [697], AQP4 [698], BDNF (brain derived neurotrophic factor) [699], CXCL10 [700], RNASE2 [701], FCGR3B [702], S100A9 [703], IL1B [704], CXCR2 [705], GPIHBP1 [294], CD36 [706], TRIB3 [707], PCSK9 [708], FGF2 [709], FASN (fatty acid synthase) [710], PNPLA3 [711], HSPA6 [712], VIP (vasoactive intestinal peptide) [713], TLR3 [683], ADRB1 [328], SPOCK2 [714], TLR8 [715], CCR2 [716], IFIT3 [717], NEK7 [718], TLR7 [687], EFNB2 [719], CAV1 [720], CR1 [721] and AQP5 [722] plays essential roles in viral respiratory diseases. Previous study confirmed that CX3CR1 [723], S100A12 [724], CD177 [725], PF4 [726], MPO (myeloperoxidase) [727], CD5L [728], F11 [729], S100A8 [730], PGLYRP1 [731], GPR15 [732], BPI (bactericidal permeability increasing protein) [733], AQP4 [734], BDNF (brain derived neurotrophic factor) [735], CXCL10 [736], FCGR3B [737], S100A9 [738], IL1B [739], CXCR1 [740], CXCR2 [741], AFF3 [742], WNT3A [743], FCN3 [744], AZGP1 [745], CD36 [746], PCSK9 [747], GPX3 [748], FGF2 [749], SHH (sonic hedgehog signaling molecule) [750], SLC7A11 [751], VIP (vasoactive intestinal peptide) [752], KL (klotho) [753], APOA1 [754], RASGRF1 [75...…”

Section: Discussionmentioning

confidence: 99%

Study on potential differentially expressed genes in idiopathic pulmonary fibrosis by bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2023

Preprint

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Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analysis of DEGs were performed. Then, a protein protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst database was used to construct the targeted microRNAs (miRNAs) and transcription factors (TFs) of the hub genes. Finally receiver operating characteristic (ROC) curve analysis was used to validates the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8 and EFHC2 were selected. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

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Section: Discussionmentioning

confidence: 99%

Study on potential differentially expressed genes in idiopathic pulmonary fibrosis by bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2023

Preprint

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“…1 The prevalence of RA has been observed to range between 0.5% and 1%, with a female-to-male ratio of 3:1. 2 Poor sleep quality is frequent in the chronic rheumatic disease population. 3 RA patients have a significant prevalence of obstructive sleep apnoea (OSA) 4 and insomnia, 5 among other main sleep disorders.…”

Section: Introductionmentioning

confidence: 99%

“… 1 The prevalence of RA has been observed to range between 0.5% and 1%, with a female-to-male ratio of 3:1. 2 …”

Section: Introductionmentioning

confidence: 99%

Sleep disorders in patients with rheumatoid arthritis: association with quality of life, fatigue, depression levels, functional disability, disease duration, and activity: a multicentre cross-sectional study

Gouda,

Mokhtar,

Elazab

et al. 2023

J Int Med Res

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Objective To investigate the correlations between pain, quality of life, fatigue, levels of depression, disability and activity, and sleep quality and common sleep disorders in patients with rheumatoid arthritis (RA). Methods This multicentre, cross-sectional study enrolled patients with RA and sex- and age-matched control subjects. Clinical, sociodemographic, serological and therapeutic data were collected. Data from the Disease Activity Score (DAS28-CRP), the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Berlin questionnaire, a visual analogue scale to evaluate fatigue severity (VAS-F), health assessment questionnaire disability index (HAQ-DI) and the Center for Epidemiological Studies-depression (CES-D) score were analysed. Results The study enrolled 247 patients with RA (190 females and 57 males) and 60 control subjects (50 females and 10 males). The PSQI for patients with RA was significantly associated with the DAS28-CRP, HAQ-DI and VAS-F. There was a significant correlation between the CES-D score, the Berlin questionnaire and the HAQ-DI and the age of control subjects. Multiple linear regression analysis demonstrated that HAQ-DI (coefficient β = 0.103) and VAS-F (coefficient β = 0.028) significantly predicted the risk of sleep apnoea. Conclusion Patients with RA may suffer from poor sleep quality, which is attributed to depression, fatiguability, disability and disease activity.

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Effect of Polymorphisms in the FCN1, FCN2, and FCN3 Genes on the Susceptibility to Develop Rheumatoid Arthritis: A Systematic Review

Cited by 2 publications

References 27 publications

Study on potential differentially expressed genes in idiopathic pulmonary fibrosis by bioinformatics and next generation sequencing data analysis

Study on potential differentially expressed genes in idiopathic pulmonary fibrosis by bioinformatics and next generation sequencing data analysis

Sleep disorders in patients with rheumatoid arthritis: association with quality of life, fatigue, depression levels, functional disability, disease duration, and activity: a multicentre cross-sectional study

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