4.6 Article

Expression profiles and potential functions of long noncoding RNAs and mRNAs in autoimmune pulmonary alveolar proteinosis patients

期刊

AGING-US
卷 13, 期 7, 页码 10535-10554

出版社

IMPACT JOURNALS LLC
DOI: 10.18632/aging.202818

关键词

autoimmune pulmonary alveolar proteinosis; long noncoding RNAs; microarray; network

资金

  1. CAMS Innovation Fund for Medical Sciences [CIFMS 2018-I2M-1-003, CIFMS 2017-12M-2-001]
  2. National Key Research and Development Program of China [2016YFC0901502]

向作者/读者索取更多资源

Autoimmune pulmonary alveolar proteinosis (APAP) is a rare lung disease. Long noncoding RNAs (lncRNAs) play a role in the pathogenesis of APAP. Differentially expressed lncRNAs and mRNAs were identified in APAP patient samples, providing insights for future functional research.
Autoimmune pulmonary alveolar proteinosis (APAP) is a rare lung disease that may be associated with surfactant overaccumulation. To assess the function of long noncoding RNAs (lncRNAs) in APAP, we performed microarray analyses to identify differentially expressed (DE) lncRNAs and mRNAs between peripheral blood samples from five APAP patients and five healthy volunteers. In total, 12459 DE lncRNAs and 9331 DE mRNAs were identified in APAP patient samples. A qRT-PCR validation of 20 DE lncRNAs and 20 mRNAs indicated that 12 DE lncRNAs may be involved in the pathogenesis of APAP. Coding and noncoding co-expression (CNC) and competing endogenous RNA (ceRNA) regulatory networks were constructed with these 12 DE lncRNAs. Gene Ontology analysis of the downregulated mRNAs and the CNC network revealed that ubiquitin-like protein transferase activity was suppressed in APAP patient samples. Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that the MAPK signaling pathway was enriched in the ceRNA network. Gene Ontology analysis also indicated that mRNAs involved in many transmembrane ion transport processes were upregulated in APAP patients. The DE lncRNAs and mRNAs discovered in this study have elucidated the pathogenesis of APAP, and the CNC and ceRNA networks have provided novel insights for future functional research.

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