Skip to content
2000
Volume 28, Issue 19
  • ISSN: 1386-2073
  • E-ISSN: 1875-5402

Abstract

Introduction

Age-related Macular Degeneration (AMD) is a predominant cause of blindness in the elderly. The present study is the first to investigate the alteration of lncRNAs and mRNAs in neovascular AMD.

Methods

Nine patients with neovascular AMD were included in the study. The control group comprised seven patients with epiretinal membranes. RNA sequencing was performed to obtain the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs). Then, the DElncRNA-DEmRNA co-expression network, ceRNA network, and immune-related ceRNA subnetwork were constructed. Functional annotation of DEmRNAs between the two groups and DEmRNAs in networks was conducted. The immune cell distribution in neovascular AMD was also evaluated. Real-time qPCR (RT-qPCR) was used to validate the expression levels of key markers.

Results

A total of 342 DEmRNAs and 157 DElncRNAs were obtained in neovascular AMD. Functional annotation indicated that these DEmRNAs significantly enriched immune system-related processes, such as positive regulation of B cell activation, immunoglobulin receptor binding, complement activation, and classical pathway. The DElncRNA-DEmRNA co-expression network, including 185 DElncRNA-DEmRNA co-expression pairs, and the ceRNA (DElncRNA-miRNA-DEmRNA) network, containing 45 lncRNA-miRNA pairs and 73 miRNA-mRNA pairs, were constructed. The immune-related ceRNA subnetwork, including 2 lncRNAs, 5 miRNAs, and 3 mRNAs, was constructed. In addition, the distribution of immune cells was slightly different between the neovascular AMD group and the control group. RT-qPCR validation indicated the consistency between the RT-qPCR results and RNA sequencing results.

Conclusion

In conclusion, STC1, S100A1, MEG3, MEG3-hsa-miR-608-S100A1, and MEG3-hsa-miR-130b-3p/hsa-miR-149-3p-STC1 may be related to the occurrence and development of neovascular AMD.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cchts/10.2174/0113862073342212250102042734
2025-02-12
2025-12-16

  • From This Site

    /content/journals/cchts/10.2174/0113862073342212250102042734
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. PenningtonK.L. DeAngelisM.M. Epidemiology of age-related macular degeneration (AMD): Associations with cardiovascular disease phenotypes and lipid factors.Eye Vis. (Lond.)2016313410.1186/s40662‑016‑0063‑5 28032115
     [Google Scholar]
  2. BhuttoI. LuttyG. Understanding age-related macular degeneration (AMD): Relationships between the photoreceptor/retinal pigment epithelium/Bruch’s membrane/choriocapillaris complex.Mol. Aspects Med.201233429531710.1016/j.mam.2012.04.005 22542780
     [Google Scholar]
  3. MuraliA. KrishnakumarS. SubramanianA. ParameswaranS. Bruch’s membrane pathology: A mechanistic perspective.Eur. J. Ophthalmol.20203061195120610.1177/1120672120919337 32345040
     [Google Scholar]
  4. TisiA. FeligioniM. PassacantandoM. CiancagliniM. MaccaroneR. The impact of oxidative stress on blood-retinal barrier physiology in age-related macular degeneration.Cells20211016410.3390/cells10010064 33406612
     [Google Scholar]
  5. MitchellP. LiewG. GopinathB. WongT.Y. Age-related macular degeneration.Lancet2018392101531147115910.1016/S0140‑6736(18)31550‑2 30303083
     [Google Scholar]
  6. ThomasC.J. MirzaR.G. GillM.K. Age-related macular degeneration.Med. Clin. North Am.2021105347349110.1016/j.mcna.2021.01.003 33926642
     [Google Scholar]
  7. JiaY. BaileyS.T. WilsonD.J. TanO. KleinM.L. FlaxelC.J. PotsaidB. LiuJ.J. LuC.D. KrausM.F. FujimotoJ.G. HuangD. Quantitative optical coherence tomography angiography of choroidal neovascularization in age-related macular degeneration.Ophthalmology201412171435144410.1016/j.ophtha.2014.01.034 24679442
     [Google Scholar]
  8. KokotasH. GrigoriadouM. PetersenM.B. Age-related macular degeneration: Genetic and clinical findings.cclm201149460161610.1515/CCLM.2011.09121175380
     [Google Scholar]
  9. LeeS. KimS. JeonJ.S. Microfluidic outer blood–retinal barrier model for inducing wet age-related macular degeneration by hypoxic stress.Lab Chip202222224359436810.1039/D2LC00672C 36254466
     [Google Scholar]
  10. MurphyC. JohnsonA.P. KoenekoopR.K. SeipleW. OverburyO. The relationship between cognitive status and known single nucleotide polymorphisms in age-related macular degeneration.Front. Aging Neurosci.20201258669110.3389/fnagi.2020.586691 33178008
     [Google Scholar]
  11. ChenX. JiangC. QinB. LiuG. JiJ. SunX. XuM. DingS. ZhuM. HuangG. YanB. ZhaoC. LncRNA ZNF503-AS1 promotes RPE differentiation by downregulating ZNF503 expression.Cell Death Dis.201789e304610.1038/cddis.2017.382 28880276
     [Google Scholar]
  12. MeolaN. PizzoM. AlfanoG. SuraceE.M. BanfiS. The long noncoding RNA Vax2os1 controls the cell cycle progression of photoreceptor progenitors in the mouse retina.RNA201218111112310.1261/rna.029454.111 22128341
     [Google Scholar]
  13. XuX.D. LiK.R. LiX.M. YaoJ. QinJ. YanB. Long non-coding RNAs: New players in ocular neovascularization.Mol. Biol. Rep.20144174493450510.1007/s11033‑014‑3320‑5 24623407
     [Google Scholar]
  14. ZhuW. MengY.F. XingQ. TaoJ.J. LuJ. WuY. Identification of lncRNAs involved in biological regulation in early age-related macular degeneration.Int. J. Nanomedicine2017127589760210.2147/IJN.S140275 29089757
     [Google Scholar]
  15. ChenX. SunR. YangD. JiangC. LiuQ. LINC00167 regulates RPE differentiation by targeting the miR-203a-3p/SOCS3 axis.Mol. Ther. Nucleic Acids2020191015102610.1016/j.omtn.2019.12.040 32044724
     [Google Scholar]
  16. AllinghamM.J. LoksztejnA. CousinsS.W. MettuP.S. Immunological aspects of age-related macular degeneration.Adv. Exp. Med. Biol.2021125614318910.1007/978‑3‑030‑66014‑7_6 33848001
     [Google Scholar]
  17. LiberzonA. SubramanianA. PinchbackR. ThorvaldsdóttirH. TamayoP. MesirovJ.P. Molecular signatures database (MSigDB) 3.0.Bioinformatics201127121739174010.1093/bioinformatics/btr260 21546393
     [Google Scholar]
  18. LoveM.I. HuberW. AndersS. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.Genome Biol.2014151255010.1186/s13059‑014‑0550‑8 25516281
     [Google Scholar]
  19. Garcia-MorenoA. López-DomínguezR. Villatoro-GarcíaJ.A. Ramirez-MenaA. Aparicio-PuertaE. HackenbergM. Pascual-MontanoA. Carmona-SaezP. Functional enrichment analysis of regulatory elements.Biomedicines202210359010.3390/biomedicines10030590 35327392
     [Google Scholar]
  20. SubramanianA. TamayoP. MoothaV.K. MukherjeeS. EbertB.L. GilletteM.A. PaulovichA. PomeroyS.L. GolubT.R. LanderE.S. MesirovJ.P. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles.Proc. Natl. Acad. Sci. USA200510243155451555010.1073/pnas.0506580102 16199517
     [Google Scholar]
  21. ZhaoS. ZhongY. ShenF. ChengX. QingX. LiuJ. Comprehensive exosomal microRNA profile and construction of competing endogenous RNA network in autism spectrum disorder: A pilot study.Biomol. Biomed.202424229230110.17305/bb.2023.9552 37865919
     [Google Scholar]
  22. ShannonP. MarkielA. OzierO. BaligaN.S. WangJ.T. RamageD. AminN. SchwikowskiB. IdekerT. Cytoscape: A software environment for integrated models of biomolecular interaction networks.Genome Res.200313112498250410.1101/gr.1239303 14597658
     [Google Scholar]
  23. StichtC. De La TorreC. ParveenA. GretzN. miRWalk: An online resource for prediction of microRNA binding sites.PLoS One20181310e020623910.1371/journal.pone.0206239 30335862
     [Google Scholar]
  24. LiJ.H. LiuS. ZhouH. QuL.H. YangJ.H. starBase v2.0: Decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data.Nucleic Acids Res.201442D1D92D9710.1093/nar/gkt1248 24297251
     [Google Scholar]
  25. BhattacharyaS. DunnP. ThomasC.G. SmithB. SchaeferH. ChenJ. HuZ. ZalocuskyK.A. ShankarR.D. Shen-OrrS.S. ThomsonE. WiserJ. ButteA.J. ImmPort, toward repurposing of open access immunological assay data for translational and clinical research.Sci. Data20185118001510.1038/sdata.2018.15 29485622
     [Google Scholar]
  26. NewmanA.M. LiuC.L. GreenM.R. GentlesA.J. FengW. XuY. HoangC.D. DiehnM. AlizadehA.A. Robust enumeration of cell subsets from tissue expression profiles.Nat. Methods201512545345710.1038/nmeth.3337 25822800
     [Google Scholar]
  27. AgarwalV. BellG.W. NamJ.W. BartelD.P. Predicting effective microRNA target sites in mammalian mRNAs.eLife20154e0500510.7554/eLife.05005 26267216
     [Google Scholar]
  28. BlasiakJ. HyttinenJ.M.T. SzczepanskaJ. PawlowskaE. KaarnirantaK. Potential of long non-coding RNAs in age-related macular degeneration.Int. J. Mol. Sci.20212217917810.3390/ijms22179178 34502084
     [Google Scholar]
  29. WangZ. GersteinM. SnyderM. RNA-Seq: A revolutionary tool for transcriptomics.Nat. Rev. Genet.2009101576310.1038/nrg2484 19015660
     [Google Scholar]
  30. MortazaviA. WilliamsB.A. McCueK. SchaefferL. WoldB. Mapping and quantifying mammalian transcriptomes by RNA-Seq.Nat. Methods20085762162810.1038/nmeth.1226 18516045
     [Google Scholar]
  31. NagalakshmiU. WangZ. WaernK. ShouC. RahaD. GersteinM. SnyderM. The transcriptional landscape of the yeast genome defined by RNA sequencing.Science200832058811344134910.1126/science.1158441 18451266
     [Google Scholar]
  32. CloonanN. ForrestA.R.R. KolleG. GardinerB.B.A. FaulknerG.J. BrownM.K. TaylorD.F. SteptoeA.L. WaniS. BethelG. RobertsonA.J. PerkinsA.C. BruceS.J. LeeC.C. RanadeS.S. PeckhamH.E. ManningJ.M. McKernanK.J. GrimmondS.M. Stem cell transcriptome profiling via massive-scale mRNA sequencing.Nat. Methods20085761361910.1038/nmeth.1223 18516046
     [Google Scholar]
  33. BehnkeV. WolfA. LangmannT. The role of lymphocytes and phagocytes in age-related macular degeneration (AMD).Cell. Mol. Life Sci.202077578178810.1007/s00018‑019‑03419‑4 31897541
     [Google Scholar]
  34. PenfoldiP.L. ProvisJ.M. FurbyJ.H. GatenbyP.A. BillsonF.A. Autoantibodies to retinal astrocytes associated with age-related macular degeneration.Graefes Arch. Clin. Exp. Ophthalmol.1990228327027410.1007/BF00920033 2193850
     [Google Scholar]
  35. PatelN. OhbayashiM. NugentA.K. RamchandK. TodaM. ChauK.Y. BunceC. WebsterA. BirdA.C. OnoS.J. ChongV. Circulating anti‐retinal antibodies as immune markers in age‐related macular degeneration.Immunology2005115342243010.1111/j.1365‑2567.2005.02173.x 15946260
     [Google Scholar]
  36. ReynoldsR. HartnettM.E. AtkinsonJ.P. GiclasP.C. RosnerB. SeddonJ.M. Plasma complement components and activation fragments: Associations with age-related macular degeneration genotypes and phenotypes.Invest. Ophthalmol. Vis. Sci.200950125818582710.1167/iovs.09‑3928 19661236
     [Google Scholar]
  37. ParkY.G. ParkY.S. KimI.B. Complement system and potential therapeutics in age-related macular degeneration.Int. J. Mol. Sci.20212213685110.3390/ijms22136851 34202223
     [Google Scholar]
  38. WestbergJ.A. SerlachiusM. LankilaP. PenkowaM. HidalgoJ. AnderssonL.C. Hypoxic preconditioning induces neuroprotective stanniocalcin-1 in brain via IL-6 signaling.Stroke20073831025103010.1161/01.STR.0000258113.67252.fa 17272771
     [Google Scholar]
  39. WangY. HuangL. AbdelrahimM. CaiQ. TruongA. BickR. PoindexterB. Sheikh-HamadD. Stanniocalcin-1 suppresses superoxide generation in macrophages through induction of mitochondrial UCP2.J. Leukoc. Biol.200986498198810.1189/jlb.0708454 19602668
     [Google Scholar]
  40. BishopA. CartwrightJ.E. WhitleyG.S. Stanniocalcin-1 in the female reproductive system and pregnancy.Hum. Reprod. Update20212761098111410.1093/humupd/dmab028 34432025
     [Google Scholar]
  41. WangK. LiuY. LiS. ZhaoN. QinF. TaoY. SongZ. Unveiling the therapeutic potential and mechanisms of stanniocalcin-1 in retinal degeneration.Surv. Ophthalmol.2024 39270826
     [Google Scholar]
  42. KimS.J. KoJ.H. YunJ.H. KimJ.A. KimT.E. LeeH.J. KimS.H. ParkK.H. OhJ.Y. Stanniocalcin-1 protects retinal ganglion cells by inhibiting apoptosis and oxidative damage.PLoS One201385e6374910.1371/journal.pone.0063749 23667669
     [Google Scholar]
  43. RoddyG.W. RosaR.H.Jr OhJ.Y. YlostaloJ.H. BartoshT.J.Jr ChoiH. LeeR.H. YasumuraD. AhernK. NielsenG. MatthesM.T. LaVailM.M. ProckopD.J. Stanniocalcin-1 rescued photoreceptor degeneration in two rat models of inherited retinal degeneration.Mol. Ther.201220478879710.1038/mt.2011.308 22294148
     [Google Scholar]
  44. RoddyG.W. YasumuraD. MatthesM.T. AlaviM.V. BoyeS.L. RosaR.H.Jr FautschM.P. HauswirthW.W. LaVailM.M. Long-term photoreceptor rescue in two rodent models of retinitis pigmentosa by adeno-associated virus delivery of Stanniocalcin-1.Exp. Eye Res.201716517518110.1016/j.exer.2017.09.011 28974356
     [Google Scholar]
  45. RosaR.H.Jr XieW. ZhaoM. TsaiS.H. RoddyG.W. SuM.G. PottsL.B. HeinT.W. KuoL. Intravitreal administration of stanniocalcin-1 rescues photoreceptor degeneration with reduced oxidative stress and inflammation in a porcine model of retinitis pigmentosa.Am. J. Ophthalmol.202223923024310.1016/j.ajo.2022.03.014 35307380
     [Google Scholar]
  46. HongG. LiT. ZhaoH. ZengZ. ZhaiJ. LiX. LuoX. Diagnostic value and mechanism of plasma S100A1 protein in acute ischemic stroke: A prospective and observational study.PeerJ202311e1444010.7717/peerj.14440 36643631
     [Google Scholar]
  47. YuJ. LuY. LiY. XiaoL. XingY. LiY. WuL. Role of S100A1 in hypoxia-induced inflammatory response in cardiomyocytes via TLR4/ROS/NF-κB pathway.J. Pharm. Pharmacol.20156791240125010.1111/jphp.12415 25880347
     [Google Scholar]
  48. BaiY. GuoN. XuZ. ChenY. ZhangW. ChenQ. BiZ. S100A1 expression is increased in spinal cord injury and promotes inflammation, oxidative stress and apoptosis of PC12 cells induced by LPS via ERK signaling.Mol. Med. Rep.20222723010.3892/mmr.2022.12917 36524376
     [Google Scholar]
  49. MostP. LerchenmüllerC. RengoG. MahlmannA. RitterhoffJ. RohdeD. GoodmanC. BuschC.J. LaubeF. HeissenbergJ. PlegerS.T. WeissN. KatusH.A. KochW.J. PeppelK. S100A1 deficiency impairs postischemic angiogenesis via compromised proangiogenic endothelial cell function and nitric oxide synthase regulation.Circ. Res.20131121667810.1161/CIRCRESAHA.112.275156 23048072
     [Google Scholar]
  50. QiuG.Z. TianW. FuH.T. LiC.P. LiuB. Long noncoding RNA-MEG3 is involved in diabetes mellitus-related microvascular dysfunction.Biochem. Biophys. Res. Commun.2016471113514110.1016/j.bbrc.2016.01.164 26845358
     [Google Scholar]
  51. TongP. PengQ.H. GuL.M. XieW.W. LiW.J. LncRNA-MEG3 alleviates high glucose induced inflammation and apoptosis of retina epithelial cells via regulating miR-34a/SIRT1 axis.Exp. Mol. Pathol.201910710210910.1016/j.yexmp.2018.12.003 30529346
     [Google Scholar]
  52. LuoR. JinH. LiL. HuY.X. XiaoF. Long noncoding RNA MEG3 inhibits apoptosis of retinal pigment epithelium cells induced by high glucose via the miR-93/Nrf2 axis.Am. J. Pathol.202019091813182210.1016/j.ajpath.2020.05.008 32473920
     [Google Scholar]
  53. ChenG. QianH.M. ChenJ. WangJ. GuanJ.T. ChiZ.L. Whole transcriptome sequencing identifies key circRNAs, lncRNAs, and miRNAs regulating neurogenesis in developing mouse retina.BMC Genomics202122177910.1186/s12864‑021‑08078‑z 34717547
     [Google Scholar]
  54. HeY. DanY. GaoX. HuangL. LvH. ChenJ. DNMT1-mediated lncRNA MEG3 methylation accelerates endothelial-mesenchymal transition in diabetic retinopathy through the PI3K/Akt/mTOR signaling pathway.Am. J. Physiol. Endocrinol. Metab.20213203E598E60810.1152/ajpendo.00089.2020 33284093
     [Google Scholar]
  55. SunH.J. ZhangF.F. XiaoQ. XuJ. ZhuL.J. lncRNA MEG3, acting as a ceRNA, modulates RPE differentiation through the miR-7-5p/Pax6 axis.Biochem. Genet.20215961617163010.1007/s10528‑021‑10072‑9 34018078
     [Google Scholar]
/content/journals/cchts/10.2174/0113862073342212250102042734
Loading
Investigation of LncRNA Expression Profiles and Analysis of Immune-Related lncRNA-miRNA-mRNA Networks in Neovascular Age-Related Macular Degeneration
Comb Chem High Throughput Screen 28, 3397 (2025); https://doi.org/10.2174/0113862073342212250102042734
/content/journals/cchts/10.2174/0113862073342212250102042734
/content/journals/cchts/10.2174/0113862073342212250102042734
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): Age-related macular degeneration; ceRNA; immune; lncRNA; neovascular

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test