BACKGROUND/AIMS: Long non-coding RNAs (lncRNAs) are potential biomarkers of tumors, cardiac disease, and cerebral disease because of their interaction with coding RNAs. This work focused on ischemic stroke (IS) and aimed to identify novel lncRNA biomarkers and construct lncRNA-related networks in IS. METHODS: Differentially expressed lncRNAs were identified using Arraystar Human LncRNA Microarray v4.0, and validated with qRT-PCR. A lncRNA-mRNA co-expression network and a lncRNA-miRNA-mRNA regulatory network were constructed. Functional and pathway analyses were then performed. RESULTS: In total, 560 up-regulated and 690 down-regulated differentially expressed lncRNAs were found (P < 0.05, false discovery rate < 0.05, absolute fold change ≥ 2). qRT-PCR results confirmed that lncRNA-ENST00000568297, lncRNA-ENST00000568243, and lncRNA-NR_046084 exhibited significant differential expression between IS and controls (all P < 0.05). Areas under the curves (AUCs) for these lncRNAs were 0.733, 0.743, and 0.690, respectively, and the combined AUC was 0.843. A coding-noncoding co-expression (CNC) network was constructed based on Pearson's correlation coefficient. A specific lncRNA-miRNA-mRNA regulatory network of ENST00000568297, ENST00000568243, and NR_046084 was also constructed. Functional annotation of the up- and down-regulated mRNAs was performed. Pathway analysis enriched IS-related pathways with mRNAs in the lncRNA-miRNA-mRNA regulatory network. CONCLUSION: LncRNA and mRNA expression profiles in human peripheral blood were altered after IS. ENST00000568297, ENST00000568243, and NR_046084 were identified as novel potential diagnostic biomarkers of IS. Analysis of the CNC network and lncRNA-miRNA-mRNA regulatory network suggested that lncRNAs may participate in IS pathophysiology by regulating pivotal miRNAs, mRNAs, or IS-related pathways.
BACKGROUND/AIMS: Long non-coding RNAs (lncRNAs) are potential biomarkers of tumors, cardiac disease, and cerebral disease because of their interaction with coding RNAs. This work focused on ischemic stroke (IS) and aimed to identify novel lncRNA biomarkers and construct lncRNA-related networks in IS. METHODS: Differentially expressed lncRNAs were identified using Arraystar Human LncRNA Microarray v4.0, and validated with qRT-PCR. A lncRNA-mRNA co-expression network and a lncRNA-miRNA-mRNA regulatory network were constructed. Functional and pathway analyses were then performed. RESULTS: In total, 560 up-regulated and 690 down-regulated differentially expressed lncRNAs were found (P < 0.05, false discovery rate < 0.05, absolute fold change ≥ 2). qRT-PCR results confirmed that lncRNA-ENST00000568297, lncRNA-ENST00000568243, and lncRNA-NR_046084 exhibited significant differential expression between IS and controls (all P < 0.05). Areas under the curves (AUCs) for these lncRNAs were 0.733, 0.743, and 0.690, respectively, and the combined AUC was 0.843. A coding-noncoding co-expression (CNC) network was constructed based on Pearson's correlation coefficient. A specific lncRNA-miRNA-mRNA regulatory network of ENST00000568297, ENST00000568243, and NR_046084 was also constructed. Functional annotation of the up- and down-regulated mRNAs was performed. Pathway analysis enriched IS-related pathways with mRNAs in the lncRNA-miRNA-mRNA regulatory network. CONCLUSION: LncRNA and mRNA expression profiles in human peripheral blood were altered after IS. ENST00000568297, ENST00000568243, and NR_046084 were identified as novel potential diagnostic biomarkers of IS. Analysis of the CNC network and lncRNA-miRNA-mRNA regulatory network suggested that lncRNAs may participate in IS pathophysiology by regulating pivotal miRNAs, mRNAs, or IS-related pathways.
Authors: Junfen Fan; Madeline Saft; Nadia Sadanandan; Bella Gonzales-Portillo; You Jeong Park; Paul R Sanberg; Cesario V Borlongan; Yumin Luo Journal: Front Aging Neurosci Date: 2020-10-19 Impact factor: 5.750