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. 2023 Apr 11;24(8):7088.
doi: 10.3390/ijms24087088.

Plasma Exosomal Non-Coding RNA Profile Associated with Renal Damage Reveals Potential Therapeutic Targets in Lupus Nephritis

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Plasma Exosomal Non-Coding RNA Profile Associated with Renal Damage Reveals Potential Therapeutic Targets in Lupus Nephritis

Ana Flores-Chova et al. Int J Mol Sci. .

Abstract

Despite considerable progress in our understanding of systemic lupus erythematosus (SLE) pathophysiology, patient diagnosis is often deficient and late, and this has an impact on disease progression. The aim of this study was to analyze non-coding RNA (ncRNA) packaged into exosomes by next-generation sequencing to assess the molecular profile associated with renal damage, one of the most serious complications of SLE, to identify new potential targets to improve disease diagnosis and management using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The plasma exosomes had a specific ncRNA profile associated with lupus nephritis (LN). The three ncRNA types with the highest number of differentially expressed transcripts were microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and piwi-interacting RNAs (piRNAs). We identified an exosomal 29-ncRNA molecular signature, of which 15 were associated only with LN presence; piRNAs were the most representative, followed by lncRNAs and miRNAs. The transcriptional regulatory network showed a significant role for four lncRNAs (LINC01015, LINC01986, AC087257.1 and AC022596.1) and two miRNAs (miR-16-5p and miR-101-3p) in network organization, targeting critical pathways implicated in inflammation, fibrosis, epithelial-mesenchymal transition and actin cytoskeleton. From these, a handful of potential targets, such as transforming growth factor-β (TGF-β) superfamily binding proteins (activin-A, TGFB receptors, etc.), WNT/β-catenin and fibroblast growth factors (FGFs) have been identified for use as therapeutic targets of renal damage in SLE.

Keywords: RNA sequencing; bioinformatics enrichment analysis; exosomes; non-coding RNA; systemic lupus erythematosus.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Differentially expressed RNAs in SLE patients with or without renal damage in each biological fraction compared to control subjects. (A) Volcano plot depicts significantly altered RNAs found in LN or nLN. Each dot represents an RNA; non-significant false discovery rate (FDR > 0.05) and log2 fold-change ≥−1.5 or ≤1.5) in black, log2 fold-change ≤−1.5 or ≥1.5 in brown, significant FDR in blue and significant FDR and log2 fold-change ≥1.5, green (up-regulated) or ≤−1.5 in red (downregulated). The threshold dotted line for −log10(FDR) it was <0.05 and for log2 fold-change was ≤1.5 or ≥−1.5, and; (B) Bar graph of RNA subtype percentages according to the two biofluids in LN and nLN. DE: differentially expressed; Exo-P: plasma exosomes; LN: lupus nephritis; nLN: non lupus nephritis. lncRNA: long non-coding RNA; miRNA: microRNA; mRNA: messenger RNA; piRNA: PIWI-interacting RNA.
Figure 2
Figure 2
Differentially expressed ncRNAs profiles in plasma exosome fraction of SLE patients with or without LN compared to control subjects. (A) Venn diagram shows the overlap among biological fractions. (B) Diverging bar charts show the fold-change expression of the exosomal non-coding RNAs signature in both groups: upregulated are in green and downregulated in red. Common NcRNAs in both signatures are in bold. logFC: logarithm 2 base fold-change; (C) Proportions of DE ncRNA biotypes in plasma exosomes from SLE patients with LN or without (nLN). Exo-P: plasma exosomes; LN, lupus nephritis; lncRNA: long non-coding RNA; miRNA: microRNA; piRNA: PIWI-interacting RNA; nLN: non lupus nephritis.
Figure 3
Figure 3
Functional enrichment analysis of the DE exosomal miRNA targets in SLE patients with LN. (A) GO analysis of the DE targeted genes. The vertical axis indicates the number of targeted genes in a particular hierarchical cluster in biological process, cellular component and molecular function. (B) Volcano plot of GO terms enrichment analysis, according to the enrichment ratio (horizontal axis) and –log10(FDR) (vertical axis). The top 20 significant GO terms are described. (C) Volcano plot of the KEGG pathway enrichment analysis. The top 20 significant KEGG pathways are described. The size and color of the dot (enriched gene set) is proportional to the size of the category.
Figure 4
Figure 4
Regulatory networks of miRNAs–mRNAs for exosomal fraction in LN. (A) The two miRNAs (miR-16-5p and miR-101-3p) blue circles and their predicted targeted genes (yellow triangles) are shown together with the top 20 GO terms whose color is proportional to the FDR value, and (B) the top 20 KEGG pathways.
Figure 5
Figure 5
Regulatory network of lncRNAs–mRNAs for exosomal fraction in LN. The four lncRNAs (LINC01986, AC087257.1, AC022596.1 and LINC01015) represented as blue circles and their predicted targeted genes (yellow triangles) are shown, together with the top GO terms (parallelogram) and KEGG pathways (rectangle) whose color is proportional to the p value. Yellow triangles with bold border are lncRNAs as targets.

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