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. 2017 Aug 17;7(1):8576.
doi: 10.1038/s41598-017-08492-y.

Transcriptome-based Network Analysis Reveals Renal Cell Type-Specific Dysregulation of Hypoxia-Associated Transcripts

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Free PMC article

Transcriptome-based Network Analysis Reveals Renal Cell Type-Specific Dysregulation of Hypoxia-Associated Transcripts

Natallia Shved et al. Sci Rep. .
Free PMC article

Abstract

Accumulating evidence suggests that dysregulation of hypoxia-regulated transcriptional mechanisms is involved in development of chronic kidney diseases (CKD). However, it remains unclear how hypoxia-induced transcription factors (HIFs) and subsequent biological processes contribute to CKD development and progression. In our study, genome-wide expression profiles of more than 200 renal biopsies from patients with different CKD stages revealed significant correlation of HIF-target genes with eGFR in glomeruli and tubulointerstitium. These correlations were positive and negative and in part compartment-specific. Microarrays of proximal tubular cells and podocytes with stable HIF1α and/or HIF2α suppression displayed cell type-specific HIF1/HIF2-dependencies as well as dysregulation of several pathways. WGCNA analysis identified gene sets that were highly coregulated within modules. Characterization of the modules revealed common as well as cell group- and condition-specific pathways, GO-Terms and transcription factors. Gene expression analysis of the hypoxia-interconnected pathways in patients with different CKD stages revealed an increased dysregulation with loss of renal function. In conclusion, our data clearly point to a compartment- and cell type-specific dysregulation of hypoxia-associated gene transcripts and might help to improve the understanding of hypoxia, HIF dysregulation, and transcriptional program response in CKD.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Immunohistochemistry of HIF1α, VEGFA and ABCG2. Sections from paraffin embedded kidney biopsies with chronic kidney disease (normal (left) and reduced eGFR (right)) were stained with antibodies against HIF1α (A), ATP binding cassette subfamily G member 2 (ABCG2) (B), and vascular endothelial growth factor A (VEGFA) (C). (A) No specific HIF1α staining could be detected in kidney sections with normal eGFR, score negative (0). Only some unspecific intravascular background staining is seen (left). In kidneys from patients with severely reduced eGFR, some nuclear (→) and cytoplasmic (►) tubular staining is detected, score weak (1) (right). (B) ABCG2 showing strong (score 2) expression in the tubulointerstitial compartment of kidneys with normal eGFR (left) in contrast to weak (score 1) staining in samples with reduced eGFR (right). (C) Similar stainig pattern for VEGFA, strong (score 2) expression in the tubulointerstitial compartment of kidneys with normal eGFR (left) in contrast to weak (score 1) staining in samples with reduced eGFR (right).
Figure 2
Figure 2
Scheme describing the workflow of microarray analysis.
Figure 3
Figure 3
GO enrichment analysis: network visualization for the common and exclusively enriched GOs in the different cell lines using the Cytoscape plugins BinGO and EnrichmentMap. Red nodes represent enriched GO-terms, node size corresponds to negative logarithm of FDR-corrected p-value. Edge thickness shows overlap of genes between neighbor nodes. Figures (A) and (B) represent networks of GO-Terms which are exclusively associated with AB81 (A) and HK-2 (B) under hypoxic condition, figure (C) displays the network of common GO-Terms in AB81 and HK-2 under hypoxia. Figures (DE) show the exlusive AB81 (D), HK-2 (E) GO-Terms under normoxic conditions. There were no common GO-Terms under normoxic conditions.
Figure 4
Figure 4
Transcription factor (TF) - gene regulatory networks (under hypoxic conditions). The podocyte TF-gene network (A) consists of 1837 nodes, 53175 edges. The tubular network (B) is compiled of 775 nodes and 24799 edges. Figure (C) shows the intersection of the podocyte and tubular network. Red nodes represent transcription factors, white nodes correspond to regulated genes. Edges connect TFs with their target genes.
Figure 5
Figure 5
Transcription factor (TF) - gene regulatory networks (under normoxic conditions). The podocyte TF-gene network (A) consists of 2275 nodes, 63209 edges. The tubular network (B) is compiled of 1255 nodes and 21204 edges. Figure (C) shows the intersection of the podocyte and tubular network. Red nodes represent transcription factors, white nodes correspond to regulated genes. Edges connect TFs with their target genes.
Figure 6
Figure 6
Visualization of the interplay of the significantly enriched pathways in CKD development progression. Increased dysregulation of the hypoxia-interconnected pathways with loss of renal function in glomerular (A) and tubulointerstitial (B) samples. Color represents the log2 expression foldchange, node size the absolute value of the log2 foldchange, edge color represents the pathway. Directionality is based on pathway information and represented by arrows. Red means upregulated, blue downregulated compared to CKD1.

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References

    1. Covic A, et al. Systematic review of the evidence underlying the association between mineral metabolism disturbances and risk of all-cause mortality, cardiovascular mortality and cardiovascular events in chronic kidney disease. Nephrol Dial Transplant. 2009;24:1506–1523. doi: 10.1093/ndt/gfn613. - DOI - PubMed
    1. USRDS. United States Renal Data System. 2016 USRDS annual data report: Epidemiology of kidney disease in the United States., http://www.usrds.org/atlas.aspx (2016).
    1. Levey AS, Coresh J. Chronic kidney disease. Lancet. 2012;379:165–180. doi: 10.1016/S0140-6736(11)60178-5. - DOI - PubMed
    1. Theilig F. Spread of glomerular to tubulointerstitial disease with a focus on proteinuria. Ann Anat. 2010;192:125–132. doi: 10.1016/j.aanat.2010.03.003. - DOI - PubMed
    1. Gilbert RE, Cooper ME. The tubulointerstitium in progressive diabetic kidney disease: more than an aftermath of glomerular injury? Kidney international. 1999;56:1627–1637. doi: 10.1046/j.1523-1755.1999.00721.x. - DOI - PubMed

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