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Integrated Bioinformatics Analysis of Aberrantly-Methylated Shen et al. BMC Ophthalmology (2020) 20:119 https://doi.org/10.1186/s12886-020-01392-2 RESEARCH ARTICLE Open Access Integrated bioinformatics analysis of aberrantly-methylated differentially- expressed genes and pathways in age- related macular degeneration Yinchen Shen1,2†,MoLi3†, Kun Liu1,2, Xiaoyin Xu1,2, Shaopin Zhu1,2, Ning Wang1,2, Wenke Guo4, Qianqian Zhao4, Ping Lu4, Fudong Yu4 and Xun Xu1,2* Abstract Background: Age-related macular degeneration (AMD) represents the leading cause of visual impairment in the aging population. The goal of this study was to identify aberrantly-methylated, differentially-expressed genes (MDEGs) in AMD and explore the involved pathways via integrated bioinformatics analysis. Methods: Data from expression profile GSE29801 and methylation profile GSE102952 were obtained from the Gene Expression Omnibus database. We analyzed differentially-methylated genes and differentially-expressed genes using R software. Functional enrichment and protein–protein interaction (PPI) network analysis were performed using the R package and Search Tool for the Retrieval of Interacting Genes online database. Hub genes were identified using Cytoscape. Results: In total, 827 and 592 genes showed high and low expression, respectively, in GSE29801; 4117 hyper-methylated genes and 511 hypo-methylated genes were detected in GSE102952. Based on overlap, we categorized 153 genes as hyper-methylated, low-expression genes (Hyper-LGs) and 24 genes as hypo-methylated, high-expression genes (Hypo-HGs). Four Hyper-LGs (CKB, PPP3CA, TGFB2, SOCS2) overlapped with AMD risk genes in the Public Health Genomics and Precision Health Knowledge Base. KEGG pathway enrichment analysis indicated that Hypo-HGs were enriched in the calcium signaling pathway, whereas Hyper-LGs were enriched in sphingolipid metabolism. In GO analysis, Hypo-HGs were enriched in fibroblast migration, membrane raft, and coenzyme binding, among others. Hyper-LGs were enriched in mRNA transport, nuclear speck, and DNA binding, among others. In PPI network analysis, 23 nodes and two edges were established from Hypo-HGs, and 151 nodes and 73 edges were established from Hyper-LGs. Hub genes (DHX9, MAPT, PAX6) showed the greatest overlap. (Continued on next page) * Correspondence: [email protected] †Yinchen Shen and Mo Li are co-first authors. 1Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, People’s Republic of China 2National Clinical Research Center for Eye Diseases, Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases, Shanghai, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Shen et al. BMC Ophthalmology (2020) 20:119 Page 2 of 12 (Continued from previous page) Conclusion: This study revealed potentially aberrantly MDEGs and pathways in AMD, which might improve the understanding of this disease. Keywords: Methylation, Gene expression, Age-related macular degeneration, Choroidal neovascularization, Bioinformatics analysis Background gene deletions, gene mutations, and gene insertions, Age-related macular degeneration (AMD) is the leading among other changes. Microarrays based on high- cause of adult blindness in developed countries, particu- throughput platforms are useful and efficient tools to larly in those over 55 years of age. Worldwide, this con- search for meaningful genes and epigenetic alterations dition accounts for 7% of cases of blindness [1, 2] and is for the identification of diagnostic or prognostic bio- expected to affect 288 million people by the year 2040 markers [22]. To better explore the molecular mechan- [3]. AMD first appears as drusen (dry AMD) and ism underlying AMD, it is necessary to conduct full advances to late AMD (wet AMD) characterized by transcriptome analysis at the tissue level; however, as choroidal neovascularization (CNV) [4]. Drusen is com- mentioned previously herein, obtaining ocular tissue posed of lipoproteinaceous deposits and acellular debris samples is difficult. Compared to retina or choroid tis- [5]. CNV involves the growth of new abnormal blood sue, blood samples are relatively easy to obtain from pa- vessels originating from the choroid through a break in tients with AMD. Therefore, it would be helpful to the Bruch’s membrane, which then invade the subretinal evaluate gene expression in the ocular tissue of patients pigment epithelium or sub-retinal space, resulting in se- with AMD as biomarkers in the blood. In the present vere vision loss [6, 7]. AMD affects central fine vision, study, data from gene expression profiling microarrays significantly impairs a patient’s ability to drive, read, and of human retinal and choroidal samples from the Iowa recognize faces, and greatly affects quality of life [8]. As and Oregon cohort AMD and control donors (GSE29801: for wet-AMD (i.e. advanced stages), anti-vascular endo- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE2 thelial growth factor (anti-VEGF) therapy was shown to 9801)[23], as well as gene methylation profiling microar- be effective and has become the first choice for the treat- rays of the peripheral blood of subjects with AMD ment of CNV [9]. However, anti-VEGF therapy requires (GSE102952: https://www.ncbi.nlm.nih.gov/geo/query/acc. repeated intra-vitreal injections, which are associated cgi?acc=GSE102952), were integrated and analyzed using a with a risk of infection and treatment burden for both series of bioinformatics tools. More precise screening re- the patients and the ophthalmologists [10]. Moreover, sults were obtained by overlapping these two AMD data some patients have poor response to the drugs after a sets. Few studies have attempted to combine gene expres- long-term treatment [11]. Apart from anti-VEGF drugs, sion profile microarrays and gene methylation profile some other therapies have also impacted macular disease microarrays to understand the development of AMD. The treatment and showed their effectiveness, such as dexa- introduction of DNA methylation characteristics in the methasone implant [12–14]. blood is useful to understand the characteristics of AMD Previous studies indicated that many environmental disease at the tissue level. factors are associated with an increased risk of AMD, In the present study, data from gene expression profiling such as age, race, smoking, obesity, and hypertension microarrays and gene methylation profiling microarrays [15, 16]. Additionally, genetic factors are regarded as were integrated and analyzed. Functional enrichment and important for the initiation and progression of AMD protein–protein interaction (PPI) network analyses of [17, 18]. Comparing to tumor tissue samples, ocular fun- screened genes were performed using the R package “clus- dus tissue samples (i.e. retina and choroid) of patients terProfiler” and Search Tool for the Retrieval of Interact- with AMD are quite difficult to obtain in real world. ing Genes (STRING) online database. We identified The difficulties to obtain human fundus tissues re- methylated genes in the peripheral blood, which might be stricted our understanding of this blinding disease. Over useful as biomarkers for the precise diagnosis and treat- the past few years, most genetic studies on AMD were ment of AMD. case-control genome-wide association studies (GWASs) of single-nucleotide polymorphisms in the patients’ per- ipheral blood [19–21], which were valuable but provided Methods limited information. The need for ethics approval was waived by the ethics With the rapid development of gene assay technology, committee of Shanghai General Hospital, Shanghai Jiao studies of disease pathogenesis are no longer limited to Tong University School of Medicine, Shanghai, China (the document is attached as an additional file). Shen et al. BMC Ophthalmology (2020) 20:119 Page 3 of 12 Microarray data information (GSE102952: https://www.ncbi.nlm.nih.gov/geo/query/ We identified methylated, differentially-expressed genes acc.cgi?acc=GSE102952). The methylation profile data of (MDEGs) between AMD and control samples by analyz- all nine patients with AMD and nine normal controls ing mRNA microarray and methylation profiling data- were included in this analysis. sets. In this study, a gene expression profiling dataset (GSE29801: https://www.ncbi.nlm.nih.gov/geo/query/
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