Mining the Proliferative Diabetic Retinopathy-associated Genes and Pathways by Integrated Bioinformatic Analysis

Overview

Journal Int Ophthalmol

Specialty Ophthalmology

Date 2020 Jan 19

PMID 31953631

Citations 10

Authors

Haiyan Sun

Yahui Cheng

Zhipeng Yan

Xiaokun Liu

Jun Zhang

Affiliations

Soon will be listed here.

Abstract

Purpose: Diabetic retinopathy (DR) especially proliferative diabetic retinopathy (PDR) is a serious eye disease. We aimed to identify key pathway and hub genes associated with PDR by analyzing the expression of retinal fibrovascular tissue in PDR patients.

Methods: First raw data were downloaded from the Gene Expression Omnibus database. Median normalization was subsequently applied to preprocess. Differentially expressed genes (DEGs) analyzed with the Limma package. Weighted correlation network analysis (WGCNA) was utilized to build the co-expression network for all genes. Then, we compared the DEGs and modules filtered out by WGCNA. A protein-protein interaction network based on the STRING web site and the Cytoscape software was constructed by the overlapping DEGs. Next, the Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. Finally, we used the Comparative Toxicogenomics Database to identify some important pathways and hub genes tightly related to PDR.

Results: Functional enrichment analysis showed that the pathway of cytokine-cytokine receptor interaction was significantly related to PDR eight hub genes which were associated with pathway including tumor necrosis factor (TNF), tumor necrosis factor receptor superfamily member 12A (TNFRSF12A), C-C chemokine 20 (CCL20), chemokine (C-X-C motif) ligand 2 (CXCL2), oncostatin M (OSM) interleukin 10 (IL10), interleukin 15 (IL 15), and interleukin 1B (IL1B).

Conclusions: We identified one pathway and eight hub genes, which were associated with PDR. The pathway provided references that will advance the understanding of mechanisms of PDR. Moreover, the hub genes may serve as therapeutic targets for precise diagnosis and treatment of PDR in the future.

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References

Solomon S, Chew E, Duh E, Sobrin L, Sun J, VanderBeek B . Erratum. Diabetic Retinopathy: A Position Statement by the American Diabetes Association. Diabetes Care 2017;40:412-418. Diabetes Care. 2017; 40(9):1285. PMC: 5566277. DOI: 10.2337/dc17-er09. View

Wang L, Cao C, Ma Q, Zeng Q, Wang H, Cheng Z . RNA-seq analyses of multiple meristems of soybean: novel and alternative transcripts, evolutionary and functional implications. BMC Plant Biol. 2014; 14:169. PMC: 4070088. DOI: 10.1186/1471-2229-14-169. View

Huang D, Sherman B, Lempicki R . Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009; 4(1):44-57. DOI: 10.1038/nprot.2008.211. View

van Beijnum J, Buurman W, Griffioen A . Convergence and amplification of toll-like receptor (TLR) and receptor for advanced glycation end products (RAGE) signaling pathways via high mobility group B1 (HMGB1). Angiogenesis. 2008; 11(1):91-9. DOI: 10.1007/s10456-008-9093-5. View

Xia X, Wen R, Chou T, Li Y, Wang Z, Porciatti V . Protection of pattern electroretinogram and retinal ganglion cells by oncostatin M after optic nerve injury. PLoS One. 2014; 9(9):e108524. PMC: 4171539. DOI: 10.1371/journal.pone.0108524. View

Reverter A, McWilliam S, Barris W, Dalrymple B . A rapid method for computationally inferring transcriptome coverage and microarray sensitivity. Bioinformatics. 2004; 21(1):80-9. DOI: 10.1093/bioinformatics/bth472. View

Taboada B, Verde C, Merino E . High accuracy operon prediction method based on STRING database scores. Nucleic Acids Res. 2010; 38(12):e130. PMC: 2896540. DOI: 10.1093/nar/gkq254. View

Sziksz E, Pap D, Lippai R, Beres N, Fekete A, Szabo A . Fibrosis Related Inflammatory Mediators: Role of the IL-10 Cytokine Family. Mediators Inflamm. 2015; 2015:764641. PMC: 4495231. DOI: 10.1155/2015/764641. View

Ruta L, Magliano D, Lemesurier R, Taylor H, Zimmet P, Shaw J . Prevalence of diabetic retinopathy in Type 2 diabetes in developing and developed countries. Diabet Med. 2013; 30(4):387-98. DOI: 10.1111/dme.12119. View

10.

Huang D, Sherman B, Lempicki R . Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2008; 37(1):1-13. PMC: 2615629. DOI: 10.1093/nar/gkn923. View

11.

Wiley S, Cassiano L, Lofton T, Winkles J, Lindner V, Liu H . A novel TNF receptor family member binds TWEAK and is implicated in angiogenesis. Immunity. 2001; 15(5):837-46. DOI: 10.1016/s1074-7613(01)00232-1. View

12.

Bahrami B, Hong T, Gilles M, Chang A . Anti-VEGF Therapy for Diabetic Eye Diseases. Asia Pac J Ophthalmol (Phila). 2017; 6(6):535-545. DOI: 10.22608/APO.2017350. View

13.

Dimont E, Shi J, Kirchner R, Hide W . edgeRun: an R package for sensitive, functionally relevant differential expression discovery using an unconditional exact test. Bioinformatics. 2015; 31(15):2589-90. PMC: 4514933. DOI: 10.1093/bioinformatics/btv209. View

14.

Richards C . The enigmatic cytokine oncostatin m and roles in disease. ISRN Inflamm. 2014; 2013:512103. PMC: 3870656. DOI: 10.1155/2013/512103. View

15.

Tang J, Kern T . Inflammation in diabetic retinopathy. Prog Retin Eye Res. 2011; 30(5):343-58. PMC: 3433044. DOI: 10.1016/j.preteyeres.2011.05.002. View

16.

Williams R, Airey M, Baxter H, Forrester J, Kennedy-Martin T, Girach A . Epidemiology of diabetic retinopathy and macular oedema: a systematic review. Eye (Lond). 2004; 18(10):963-83. DOI: 10.1038/sj.eye.6701476. View

17.

Reimers M . Statistical analysis of microarray data. Addict Biol. 2005; 10(1):23-35. DOI: 10.1080/13556210412331327795. View

18.

Guariguata L, Whiting D, Hambleton I, Beagley J, Linnenkamp U, Shaw J . Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Res Clin Pract. 2014; 103(2):137-49. DOI: 10.1016/j.diabres.2013.11.002. View

19.

Burke S, Lu D, Sparer T, Masi T, Goff M, Karlstad M . NF-κB and STAT1 control CXCL1 and CXCL2 gene transcription. Am J Physiol Endocrinol Metab. 2013; 306(2):E131-49. PMC: 3920007. DOI: 10.1152/ajpendo.00347.2013. View

20.

Wang G, Semenza G . General involvement of hypoxia-inducible factor 1 in transcriptional response to hypoxia. Proc Natl Acad Sci U S A. 1993; 90(9):4304-8. PMC: 46495. DOI: 10.1073/pnas.90.9.4304. View