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Extracellular RNA profiles with human age.

ABSTRACT: Circulating extracellular RNAs (exRNAs) are potential biomarkers of disease. We thus hypothesized that age-related changes in exRNAs can identify age-related processes. We profiled both large and small RNAs in human serum to investigate changes associated with normal aging. exRNA was sequenced in 13 young (30-32 years) and 10 old (80-85 years) African American women to identify all RNA transcripts present in serum. We identified age-related differences in several RNA biotypes, including mitochondrial transfer RNAs, mitochondrial ribosomal RNA, and unprocessed pseudogenes. Age-related differences in unique RNA transcripts were further validated in an expanded cohort. Pathway analysis revealed that EIF2 signaling, oxidative phosphorylation, and mitochondrial dysfunction were among the top pathways shared between young and old. Protein interaction networks revealed distinct clusters of functionally-related protein-coding genes in both age groups. These data provide timely and relevant insight into the exRNA repertoire in serum and its change with aging.

SUBMITTER: Dluzen DF

PROVIDER: S-EPMC6052399 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Extracellular RNA profiles with human age.

Dluzen Douglas F DF Noren Hooten Nicole N De Supriyo S Wood William H WH Zhang Yongqing Y Becker Kevin G KG Zonderman Alan B AB Tanaka Toshiko T Ferrucci Luigi L Evans Michele K MK

Aging cell 20180524 4

Circulating extracellular RNAs (exRNAs) are potential biomarkers of disease. We thus hypothesized that age-related changes in exRNAs can identify age-related processes. We profiled both large and small RNAs in human serum to investigate changes associated with normal aging. exRNA was sequenced in 13 young (30-32 years) and 10 old (80-85 years) African American women to identify all RNA transcripts present in serum. We identified age-related differences in several RNA biotypes, including mitochon ...[more]

PMID: 29797538

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Project description:BackgroundNon-small cell lung cancer (NSCLC) has a high mortality rate and poor prognosis. The early detection of high-risk patients is essential to improve patient prognosis. Thus, the identification of a non-invasive, non-radiative, convenient, and fast diagnostic approach should be a top priority in NSCLC research. Circulating extracellular RNAs (exRNAs) in the plasma are potential biomarkers for NSCLC.MethodsWe used RNA-sequencing (RNA-seq) technology to explore the NSCLC-related RNAs, especially the circular RNAs (circRNAs). The circRNA-targeted micro RNAs (miRNAs) were predicted using 3 circRNA databases [i.e., the Cancer-Specific CircRNA Database (CSCD), circBank, and Circular RNA Interactome]. The circRNA-miRNA-messenger RNA (mRNA) network was constructed using Cytoscape V3.8.0 (Cytoscape Consortium, San Diego, CA, USA). The expression levels of some differentially expressed genes were validated by a quantitative real-time polymerase chain reaction (qRT-PCR) analysis.ResultsThe results showed that the RNA biotypes of the mitochondrial ribosomal RNAs (mt-rRNAs) and mitochondrial transfer RNAs (mt-tRNAs) were upregulated in the NSCLC plasma. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms of the differentially expressed transcripts of NSCLC included oxidative phosphorylation, proton transmembrane transport, and the response to oxidative stress. Additionally, the qRT-PCR validation indicated that hsa_circ_0000722 had significantly higher expression in the NSCLC plasma than the control plasma, but hsa_circ_0006156 did not differ between the NSCLC plasma and the control plasma. The expression levels of miR-324-5p and miR-326 were higher in the NSCLC plasma than the control plasma.ConclusionsIn this study, an exRNA-sequencing strategy was used to identify the expression of NSCLC-specific transcription factors in clinical plasma samples, and hsa_circ_0000722 and hsa-miR-324-5p were identified as potential biomarkers in NSCLC.

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Extracellular RNA profiles with human age.

Publications

Extracellular RNA profiles with human age.

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