4.6
CiteScore
2.2
Impact Factor
- ISSN 1674-8301
- CN 32-1810/R
4.6
2.2
| Citation: |
Ruxu Sun, Hongjing Zhu, Ying Wang, Jianan Wang, Chao Jiang, Qiuchen Cao, Yeran Zhang, Yichen Zhang, Songtao Yuan, Qinghuai Liu. Circular RNA expression and the competitive endogenous RNA network in pathological, age-related macular degeneration events: A cross-platform normalization study[J]. The Journal of Biomedical Research, 2023, 37(5): 367-381. DOI: 10.7555/JBR.37.20230010
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Age-related macular degeneration (AMD) causes irreversible blindness in people aged over 50 worldwide. The dysfunction of the retinal pigment epithelium is the primary cause of atrophic AMD. In the current study, we used the ComBat and Training Distribution Matching method to integrate data obtained from the Gene Expression Omnibus database. We analyzed the integrated sequencing data by the Gene Set Enrichment Analysis. Peroxisome and tumor necrosis factor-α (TNF-α) signaling and nuclear factor kappa B (NF-κB) were among the top 10 pathways, and thus we selected them to construct AMD cell models to identify differentially expressed circular RNAs (circRNAs). We then constructed a competing endogenous RNA network, which is related to differentially expressed circRNAs. This network included seven circRNAs, 15 microRNAs, and 82 mRNAs. The Kyoto Encyclopedia of Genes and Genomes analysis of mRNAs in this network showed that the hypoxia-inducible factor-1 (HIF-1) signaling pathway was a common downstream event. The results of the current study may provide insights into the pathological processes of atrophic AMD.
We would like to thank the Core Facility of the First Affiliated Hospital of Nanjing Medical University for its help in the detection of experimental samples.
This research was funded by the National Natural Science Foundation of China (Grant No. 81970821); and the Postgraduate Research Innovation Program of Jiangsu Provinc (Grant No. SJCX21_0624). The funding organization had no role in the design or conduction of this research.
CLC number: R774.5, Document code: A
The authors reported no conflict of interests.
| [1] |
Mitchell P, Liew G, Gopinath B, et al. Age-related macular degeneration[J]. Lancet, 2018, 392(10153): 1147–1159. doi: 10.1016/S0140-6736(18)31550-2
|
| [2] |
Datta S, Cano M, Ebrahimi K, et al. The impact of oxidative stress and inflammation on RPE degeneration in non-neovascular AMD[J]. Prog Retin Eye Res, 2017, 60: 201–218. doi: 10.1016/j.preteyeres.2017.03.002
|
| [3] |
Persad PJ, Heid IM, Weeks DE, et al. Joint analysis of nuclear and mitochondrial variants in age-related macular degeneration identifies novel loci TRPM1 and ABHD2/RLBP1[J]. Invest Ophthalmol Vis Sci, 2017, 58(10): 4027–4038. doi: 10.1167/iovs.17-21734
|
| [4] |
SanGiovanni JP, Arking DE, Iyengar SK, et al. Mitochondrial DNA variants of respiratory complex I that uniquely characterize haplogroup T2 are associated with increased risk of age-related macular degeneration[J]. PLoS One, 2009, 4(5): e5508. doi: 10.1371/journal.pone.0005508
|
| [5] |
Liu B, Wei L, Meyerle C, et al. Complement component C5a promotes expression of IL-22 and IL-17 from human T cells and its implication in age-related macular degeneration[J]. J Transl Med, 2011, 9: 111. doi: 10.1186/1479-5876-9-111
|
| [6] |
Cousins SW, Espinosa-Heidmann DG, Csaky KG. Monocyte activation in patients with age-related macular degeneration: a biomarker of risk for choroidal neovascularization?[J]. Arch Ophthalmol, 2004, 122(7): 1013–1018. doi: 10.1001/archopht.122.7.1013
|
| [7] |
Yang L, Wilusz JE, Chen L. Biogenesis and regulatory roles of circular RNAs[J]. Annu Rev Cell Dev Biol, 2022, 38: 263–289. doi: 10.1146/annurev-cellbio-120420-125117
|
| [8] |
Chen X, Jiang C, Sun R, et al. Circular noncoding RNA NR3C1 acts as a miR-382–5p sponge to protect RPE functions via regulating PTEN/AKT/mTOR signaling pathway[J]. Mol Ther, 2020, 28(3): 929–945. doi: 10.1016/j.ymthe.2020.01.010
|
| [9] |
Dhirachaikulpanich D, Li X, Porter LF, et al. Integrated microarray and RNAseq transcriptomic analysis of retinal pigment epithelium/choroid in age-related macular degeneration[J]. Front Cell Dev Biol, 2020, 8: 808. doi: 10.3389/fcell.2020.00808
|
| [10] |
Thompson JA, Tan J, Greene CS. Cross-platform normalization of microarray and RNA-seq data for machine learning applications[J]. PeerJ, 2016, 4: e1621. doi: 10.7717/peerj.1621
|
| [11] |
Orozco LD, Chen HH, Cox C, et al. Integration of eQTL and a single-cell atlas in the human eye identifies causal genes for age-related macular degeneration[J]. Cell Rep, 2020, 30(4): 1246–1259.e6. doi: 10.1016/j.celrep.2019.12.082
|
| [12] |
Newman AM, Gallo NB, Hancox LS, et al. Systems-level analysis of age-related macular degeneration reveals global biomarkers and phenotype-specific functional networks[J]. Genome Med, 2012, 4(2): 16. doi: 10.1186/gm315
|
| [13] |
Gálvez JM, Castillo-Secilla D, Herrera LJ, et al. Towards improving skin cancer diagnosis by integrating microarray and RNA-Seq datasets[J]. IEEE J Biomed Health Inform, 2020, 24(7): 2119–2130. doi: 10.1109/JBHI.2019.2953978
|
| [14] |
Ritchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies[J]. Nucleic Acids Res, 2015, 43(7): e47. doi: 10.1093/nar/gkv007
|
| [15] |
Chen X, Sun R, Yang D, et al. LINC00167 regulates RPE differentiation by targeting the miR-203a-3p/SOCS3 axis[J]. Mol Ther Nucleic Acids, 2020, 19: 1015–1026. doi: 10.1016/j.omtn.2019.12.040
|
| [16] |
Zhang Y, Li J, Cui Q, et al. Circular RNA hsa_circ_0006091 as a novel biomarker for hepatocellular carcinoma[J]. Bioengineered, 2022, 13(2): 1988–2003. doi: 10.1080/21655979.2021.2006952
|
| [17] |
Kim KW, Kim K, Kim HJ, et al. Posttranscriptional modulation of KCNQ2 gene expression by the miR-106b microRNA family[J]. Proc Natl Acad Sci U S A, 2021, 118(47): e2110200118. doi: 10.1073/pnas.2110200118
|
| [18] |
Kanehisa M, Furumichi M, Tanabe M, et al. KEGG: new perspectives on genomes, pathways, diseases and drugs[J]. Nucleic Acids Res, 2017, 45(D1): D353–D361. doi: 10.1093/nar/gkw1092
|
| [19] |
Yu G, Wang LG, Han Y, et al. clusterProfiler: an R package for comparing biological themes among gene clusters[J]. OMICS, 2012, 16(5): 284–287. doi: 10.1089/omi.2011.0118
|
| [20] |
Müller C, Charniga C, Temple S, et al. Quantified F-actin morphology is predictive of phagocytic capacity of stem cell-derived retinal pigment epithelium[J]. Stem Cell Rep, 2018, 10(3): 1075–1087. doi: 10.1016/j.stemcr.2018.01.017
|
| [21] |
Foltz SM, Greene CS, Taroni JN. Cross-platform normalization enables machine learning model training on microarray and RNA-Seq data simultaneously[J]. Commun Biol, 2023, 6(1): 222. doi: 10.1038/s42003-023-04588-6
|
| [22] |
Saddala MS, Lennikov A, Mukwaya A, et al. Transcriptome-wide analysis of differentially expressed chemokine receptors, SNPs, and SSRs in the age-related macular degeneration[J]. Hum Genomics, 2019, 13(1): 15. doi: 10.1186/s40246-019-0199-1
|
| [23] |
Zhao C, Yasumura D, Li X, et al. mTOR-mediated dedifferentiation of the retinal pigment epithelium initiates photoreceptor degeneration in mice[J]. J Clin Invest, 2011, 121(1): 369–383. doi: 10.1172/JCI44303
|
| [24] |
Kurihara T, Westenskow PD, Gantner ML, et al. Hypoxia-induced metabolic stress in retinal pigment epithelial cells is sufficient to induce photoreceptor degeneration[J]. eLife, 2016, 5: e14319. doi: 10.7554/eLife.14319
|
| [25] |
Vogt SD, Curcio CA, Wang L, et al. Retinal pigment epithelial expression of complement regulator CD46 is altered early in the course of geographic atrophy[J]. Exp Eye Res, 2011, 93(4): 413–423. doi: 10.1016/j.exer.2011.06.002
|
| [26] |
Kozumi K, Kodama T, Murai H, et al. Transcriptomics identify thrombospondin-2 as a biomarker for NASH and advanced liver fibrosis[J]. Hepatology, 2021, 74(5): 2452–2466. doi: 10.1002/hep.31995
|
| [27] |
Baek JH, Lim D, Park KH, et al. Quantitative proteomic analysis of aqueous humor from patients with drusen and reticular pseudodrusen in age-related macular degeneration[J]. BMC Ophthalmol, 2018, 18(1): 289. doi: 10.1186/s12886-018-0941-9
|
| [28] |
Gadaleta RM, Garcia-Irigoyen O, Cariello M, et al. Fibroblast Growth Factor 19 modulates intestinal microbiota and inflammation in presence of Farnesoid X Receptor[J]. EBioMedicine, 2020, 54: 102719. doi: 10.1016/j.ebiom.2020.102719
|
| [29] |
Choudhary M, Ismail EN, Yao P, et al. LXRs regulate features of age-related macular degeneration and may be a potential therapeutic target[J]. JCI Insight, 2020, 5(1): e131928. doi: 10.1172/jci.insight.131928
|
| [30] |
Lu H, Yang Y, Kuang D, et al. Expression profile of circRNA in peripheral blood mononuclear cells of patients with rheumatoid arthritis[J]. BMC Med Genomics, 2022, 15(1): 77. doi: 10.1186/s12920-022-01225-9
|
| [31] |
Iparraguirre L, Muñoz-Culla M, Prada-Luengo I, et al. Circular RNA profiling reveals that circular RNAs from ANXA2 can be used as new biomarkers for multiple sclerosis[J]. Hum Mol Genetics, 2017, 26(18): 3564–3572. doi: 10.1093/hmg/ddx243
|
| [32] |
Duan X, Yu X, Li Z. Circular RNA hsa_circ_0001658 regulates apoptosis and autophagy in gastric cancer through microRNA-182/Ras-related protein Rab-10 signaling axis[J]. Bioengineered, 2022, 13(2): 2387–2397. doi: 10.1080/21655979.2021.2024637
|
| [33] |
Lei Q, Liang Z, Lei Q, et al. Analysis of circRNAs profile in TNF-α treated DPSC[J]. BMC Oral Health, 2022, 22(1): 269. doi: 10.1186/s12903-022-02267-2
|
| [34] |
Kuschel A, Simon P, Tug S. Functional regulation of HIF-1α under normoxia—is there more than post-translational regulation?[J]. J Cell Physiol, 2012, 227(2): 514–524. doi: 10.1002/jcp.22798
|
| [35] |
Dong S, Liang S, Cheng Z, et al. ROS/PI3K/Akt and Wnt/β-catenin signalings activate HIF-1α-induced metabolic reprogramming to impart 5-fluorouracil resistance in colorectal cancer[J]. J Exp Clin Cancer Res, 2022, 41(1): 15. doi: 10.1186/s13046-021-02229-6
|
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