Analysis of lncRNA Expression in Patients With Eosinophilic and Neutrophilic Asthma Focusing on LNC_000127

Yujin Zhu, Dan Mao, Wei Gao, Guojing Han, Hong Hu, Yujin Zhu, Dan Mao, Wei Gao, Guojing Han, Hong Hu

Abstract

Long non-coding RNA (lncRNA) is important in many diseases. Some studies have shown that lncRNA affects the pathogenesis of systemic inflammation of asthma. lncRNA regulates gene transcription, protein expression, and epigenetic regulation. However, lncRNAs associated with different airway phenotypes, such as eosinophilic (Eos) and neutrophilic (Neu) asthma have not been identified. The goal of this study was to determine the differences in circulating lncRNA signatures in Eos and Neu samples. Using RNA-sequencing (RNA-seq), lncRNA expression was evaluated in peripheral whole blood samples among Eos patients, Neu patients, and healthy individuals (Control). Bioinformatic analysis was used to predict relevant biological pathways. Quantitative PCR (qPCR) was used to measure gene expression in whole blood samples, Jurkat cells, and human CD4+ T cells. Finally, a novel lncRNA, LNC_000127, was inhibited by transfection of Jurkat cells with a lentiviral vector, and the effect was examined by Human Asthma RT2 Profiler™ PCR Array and western blotting. Compared to control samples, Eos samples contained 190 unique lncRNAs and Neu samples had 166 unique lncRNAs (difference ≥2-fold). KEGG pathway annotation data and GO terms revealed that different lncRNAs are involved in different mechanisms. LNC_000127, was highly expressed in Eos samples before treatment; its expression was increased in Jurkat cells and human CD4+ T cells following stimulation with PMA/CD28. Subsequent analyses revealed that LNC_000127 functions in the Th2 inflammation pathway. The results suggest that lncRNAs are involved in different phenotypes of asthma. Whether the different phenotypes of asthma can be recognized based on these lncRNAs (as biomarkers) requires further analysis. Targeting LNC_000127 may be effective for reducing Th2 inflammation in Eos asthma.

Keywords: RNA-sequencing; eosinophilic asthma; long non-coding RNA; neutrophilic asthma; peripheral whole blood.

Figures

Figure 1
Figure 1
(A) Volcano plot assessment of lncRNA expression between asthma and control groups. Red spots indicate a >2.0-fold change in lncRNA expression between asthma and control groups. Green spots indicate a <0.5-fold change between asthma and control groups. (B) Heat map analysis of differentially expressed lncRNAs between asthma and control group. Blue indicates low lncRNA expression and red indicates high lncRNA expression. (C) Volcano plot assessment of mRNA expression between asthma and control groups. Red spots indicate a >2.0-fold change in mRNA expression between asthma and control groups. Green spots indicate a <0.5-fold change between asthma and control groups. (D) Heat map analysis of differentially expressed mRNAs between asthma and control group. Blue indicates low lncRNA expression and red indicates high lncRNA expression. (E) Venn diagram showing differential expression of mRNAs between asthma and control groups. (F) Venn diagram showing differential expression of lncRNA between asthma and control groups. (G) Gene Ontology (GO) analysis of differentially expressed lncRNAs between asthma and control groups. The most enriched GO terms targeted by dysregulated transcripts were involved in a variety of functions, such as immune response, immune system process, cellular response to stress, and response to stress. (H) Gene Ontology (GO) analysis of differentially expressed lncRNAs between Eos and Neu groups. The enriched GO term targeted by dysregulated transcripts was involved in multiple metabolic processes.
Figure 2
Figure 2
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of T cell receptor signaling pathway in asthma.
Figure 3
Figure 3
(A) Three selected lncRNA expression levels were validated in vivo. The expression of the selected three lncRNAs was validated by qPCR in three groups in vivo. LNC_000127 was upregulated in Eos samples (p < 0.05). (B) Before and after treatment, the expression of LNC_000127 was validated by qPCR in Eos samples in vivo. LNC_000127 was downregulated after treatment in Eos samples (p < 0.05). (C) lncRNA expression in response to PMA/CD28 stimulation. Jurkat cells were treated without (control) or with 10 ng/mL PMA, and 1 μg/mL CD28 for 8 and 24 h. Levels of selected lncRNAs and GATA3 were determined by qPCR, using the housekeeping gene GAPDH as a reference. Data are shown as the mean ± SD (n = 3) and are representative of one of three independent experiments. p < 0.05 compared to the control group, as analyzed by one-way ANOVA and post-hoc Bonferroni test. (D) Human CD4+ T cells were divided into three groups. One group was treated with 10 ng/mL PMA, and 1 μg/mL CD28 for 8 and 24 h. One group was treated with 10 ng/mL PMA, and 1 μg/mL CD3 for 8 and 24 h. The last group was used as a control. Gene expression results were validated by qPCR. Levels of selected genes (GATA3, LNC_000127, and INF-r) were determined by real-time PCR using the housekeeping gene GAPDH as a reference. Data are shown as the mean ± SD (n = 3) and are representative of one of three independent experiments. A p-value <0.05 compared to the control group, as analyzed by one-way ANOVA and post-hoc Bonferroni test. (E) Expression of LNC_000127 was validated by qPCR. Data are shown as the mean ± SD (n = 3) and are representative of one of three independent experiments. p-Value <0.05 compared to the control group, as analyzed by one-way ANOVA and post-hoc Bonferroni test. (F) Expression of the genes was validated by western blotting. Gene expression in response to PMA/CD28 stimulation. Jurkat cells were treated without (control) or with 10 ng/mL PMA, and 1 μg/mL CD28 for 8 h. β-Actin was used as a reference. The relative abundance of genes was calculated as the ratio of the normalized densitometric values between three samples. Intergroup differences (of the densitometry data) were calculated by the Mann-Whitney U test using SPSS version 11.6 software. p-Value <0.05 was considered to indicate a statistically significant difference.

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