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. 2018 Dec;16(6):5103-5111.
doi: 10.3892/etm.2018.6875. Epub 2018 Oct 17.

Transcriptional profiling analysis predicts potential biomarkers for glaucoma: HGF, AKR1B10 and AKR1C3

Affiliations

Transcriptional profiling analysis predicts potential biomarkers for glaucoma: HGF, AKR1B10 and AKR1C3

Qiaoli Nie et al. Exp Ther Med. 2018 Dec.

Abstract

Glaucoma results in damage to the optic nerve and vision loss. The aim of this study was to screen more accurate biomarkers and targets for glaucoma. The datasets E-GEOD-7144 and E-MEXP-3427 were screened for differently expressed genes (DEGs) by significance analysis of microarrays. Functional and pathway enrichment analysis were processed. Pathway relationship networks and gene co-expression networks were constructed. DEGs of disease and treatment with the same symbols were of interest. RT-qPCR was processed to verify the expression of key DEGs. A total of 1,019 DEGs of glaucoma were identified and 93 DEGs in transforming growth factor-β1 (TGF-β1) and TGF-β1-2 treatment cases compared with the normal control group. Pathway relationship network of glaucoma was constructed with 25 nodes. The pathway relationship network of TGF-β1 and -2 treatment groups was constructed with 11 nodes. Glaucoma-related DEGs in GO terms and pathways were inserted and 180 common DEGs were obtained. Then, gene co-expression network of glaucoma-related DEGs was constructed with 91 nodes. Furthermore, DEGs of TGF-β1 and -2 treated glaucoma in GO terms and pathways were inserted, and 29 common DEGs were identified. Based on these DEGs, gene co-expression network was constructed with 12 nodes and 16 edges. Finally, a total of 6 important DEGs of disease and treatment were inserted and obtained. They were HGF, AKR1B10, AKR1C3, PPAP2B, INHBA and BCAT1. The expression of HGF, AKR1B10 and AKR1C3 was decreased in glaucoma samples and treatment samples. In conclusion, HGF, AKR1B10 and AKR1C3 may be key genes for glaucoma diagnosis and treatment.

Keywords: TGF-β1 and −2; biomarker; glaucoma; pathway.

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Figures

Figure 1.
Figure 1.
Pathway relationship network of glaucoma-related DEGs. The blue nodes represent pathways involving downregulated DEGs, and the yellow nodes represent pathways involving both up- and downregulated DEGs. The arrows represent regulatory direction. DEG, differently expressed gene.
Figure 2.
Figure 2.
Pathway relationship network of TGF-β1 and −2 treatment-related DEGs. The red nodes represent pathways involving upregulated DEGs, and the yellow nodes represent pathways involving both up- and downregulated DEGs. The arrows represent regulatory direction. DEG, differently expressed gene; TGF-β1, transforming growth factor-β1.
Figure 3.
Figure 3.
Gene co-expression network of important glaucoma-related DEGs. The solid lines represent DEGs with positive correlation, and the dotted lines represent DEGs with negative correlation. DEG, differently expressed gene.
Figure 4.
Figure 4.
Important gene co-expression network TGF-β1 and −2 treatment-related DEGs. The solid lines represent DEGs with positive correlation, and the dotted lines represent DEGs with negative correlation. DEG, differently expressed gene; TGF-β1, transforming growth factor-β1.
Figure 5.
Figure 5.
The expression level of HGF, AKR1B10, AKR1C3 and PPAP2B. HGF, hepatocyte growth factor; AKR1B10, aldo-ketoreductase family 1, member B10; AKR1C3, aldo-ketoreductase family 1, member C3; PPAP2B, phosphatidic acid phosphatase type 2B. *p<0.05, **p<0.01.

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