Genomics

Dataset Information

0

Identification and functional prediction of long noncoding RNA and mRNA related to connective tissue disease-associated interstitial lung diseases


ABSTRACT: LncRNA microarray analysis was used to identify the pattern of lncRNA and mRNA dysregulation between connective tissue disease-associated interstitial lung diseases (CTD-ILD) and connective tissue disease without associated interstitial lung disease (CTD-NILD). Differential genes were identified by bioinformatic analysis. Relative expression levels of five differentially expressed lncRNAs and one mRNA in 120 CTD patients with or without ILD were detected by quantitative reverse-transcription PCR (qRT-PCR). The differential gene expression analysis revealed 46 lncRNAs and 133 mRNAs were upregulated while 194 lncRNAs and 85 mRNAs were downregulated in the CTD-ILD group compared to the CTD-NILD group. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses identified several significant biological processes and signaling pathways, including NF-kappa B signaling pathway, IL-17 signaling pathway, Toll-like receptor signaling pathway, B cell receptor signaling pathway. QRT-PCR confirmed that the selected target genes were differentially expressed in different groups. In particular, the ENST00000604692 expression level was significantly higher in the ILD than the NILD group. This research has demonstrated, for the first time, the specific profile of lncRNA in PBMCs of CTD-ILD patients and the potential signal pathways related to the pathogenesis of CTD-ILD, which may provide newfound insights for the diagnosis and treatment of CTD-ILD patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE192985 | GEO | 2022/01/05

REPOSITORIES: GEO

Similar Datasets

| EGAD00001011334 | EGA
2021-02-22 | PXD024113 | Pride
2021-02-22 | PXD024123 | Pride
2011-04-19 | E-GEOD-21411 | biostudies-arrayexpress
2013-07-12 | GSE47162 | GEO
2020-12-03 | GSE162229 | GEO
2013-07-12 | E-GEOD-47162 | biostudies-arrayexpress
2023-03-30 | GSE188501 | GEO
2015-12-12 | E-GEOD-75940 | biostudies-arrayexpress
2021-06-02 | GSE171896 | GEO