Table of Contents Author Guidelines Submit a Manuscript
Oxidative Medicine and Cellular Longevity
Volume 2016, Article ID 2370252, 9 pages
http://dx.doi.org/10.1155/2016/2370252
Review Article

Integrated Approaches to Drug Discovery for Oxidative Stress-Related Retinal Diseases

1Department of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, Tsu, Mie 514-8507, Japan
2Molecular Pharmacology, Department of Biofunctional Evaluation, Gifu Pharmaceutical University, Gifu 501-1196, Japan

Received 23 September 2016; Accepted 13 November 2016

Academic Editor: José Luís García-Giménez

Copyright © 2016 Yuhei Nishimura and Hideaki Hara. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Nita and A. Grzybowski, “The role of the reactive oxygen species and oxidative stress in the pathomechanism of the age-related ocular diseases and other pathologies of the anterior and posterior eye segments in adults,” Oxidative Medicine and Cellular Longevity, vol. 2016, Article ID 3164734, 23 pages, 2016. View at Publisher · View at Google Scholar
  2. M. D. Pinazo-Durán, R. Gallego-Pinazo, J. J. García-Medina et al., “Oxidative stress and its downstream signaling in aging eyes,” Clinical Interventions in Aging, vol. 9, pp. 637–652, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. V. Chrysostomou, F. Rezania, I. A. Trounce, and J. G. Crowston, “Oxidative stress and mitochondrial dysfunction in glaucoma,” Current Opinion in Pharmacology, vol. 13, no. 1, pp. 12–15, 2013. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Hong, Y. Iizuka, T. Lee, C. Y. Kim, and G. J. Seong, “Neuroprotective and neurite outgrowth effects of maltol on retinal ganglion cells under oxidative stress,” Molecular Vision, vol. 20, pp. 1456–1462, 2014. View at Google Scholar · View at Scopus
  5. M. Akane, M. Shimazawa, Y. Inokuchi, K. Tsuruma, and H. Hara, “SUN N8075, a novel radical scavenger, protects against retinal cell death in mice,” Neuroscience Letters, vol. 488, no. 1, pp. 87–91, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. J. Blasiak, G. Petrovski, Z. Veréb, A. Facskó, and K. Kaarniranta, “Oxidative stress, hypoxia, and autophagy in the neovascular processes of age-related macular degeneration,” BioMed Research International, vol. 2014, Article ID 768026, 7 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. K. Tsuruma, Y. Tanaka, M. Shimazawa, Y. Mashima, and H. Hara, “Unoprostone reduces oxidative stress- and light-induced retinal cell death, and phagocytotic dysfunction, by activating BK channels,” Molecular Vision, vol. 17, pp. 3556–3565, 2011. View at Google Scholar · View at Scopus
  8. R. A. Kowluru and M. Mishra, “Oxidative stress, mitochondrial damage and diabetic retinopathy,” Biochimica et Biophysica Acta—Molecular Basis of Disease, vol. 1852, no. 11, pp. 2474–2483, 2015. View at Publisher · View at Google Scholar · View at Scopus
  9. C. Martínez-Fernández de la Cámara, D. Salom, M. D. Sequedo et al., “Altered Antioxidant-Oxidant Status in the Aqueous Humor and Peripheral Blood of Patients with Retinitis Pigmentosa,” PLoS ONE, vol. 8, no. 9, Article ID e74223, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. K. Zhang, L. Zhang, and R. N. Weinreb, “Ophthalmic drug discovery: novel targets and mechanisms for retinal diseases and glaucoma,” Nature Reviews Drug Discovery, vol. 11, no. 7, pp. 541–559, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. R. K. Donegan and R. L. Lieberman, “Discovery of molecular therapeutics for glaucoma: challenges, successes, and promising directions,” Journal of Medicinal Chemistry, vol. 59, no. 3, pp. 788–809, 2016. View at Publisher · View at Google Scholar · View at Scopus
  12. S. D. Solomon, K. Lindsley, S. S. Vedula, M. G. Krzystolik, and B. S. Hawkins, “Anti-vascular endothelial growth factor for neovascular age-related macular degeneration,” The Cochrane database of systematic reviews, vol. 8, p. CD005139, 2014. View at Google Scholar · View at Scopus
  13. G. Virgili, M. Parravano, F. Menchini, and J. R. Evans, “Anti-vascular endothelial growth factor for diabetic macular oedema,” The Cochrane Database of Systematic Reviews, no. 10, Article ID CD007419, 2014. View at Publisher · View at Google Scholar
  14. N. J. D. Gower, R. J. Barry, M. R. Edmunds, L. C. Titcomb, and A. K. Denniston, “Drug discovery in ophthalmology: past success, present challenges, and future opportunities,” BMC Ophthalmology, vol. 16, article 11, 2016. View at Publisher · View at Google Scholar · View at Scopus
  15. M. Hay, D. W. Thomas, J. L. Craighead, C. Economides, and J. Rosenthal, “Clinical development success rates for investigational drugs,” Nature Biotechnology, vol. 32, no. 1, pp. 40–51, 2014. View at Publisher · View at Google Scholar · View at Scopus
  16. D. E. Bonds, M. Harrington, B. B. Worrall et al., “Effect of long-chain ω-3 fatty acids and lutein + zeaxanthin supplements on cardiovascular outcomes results of the age-related eye disease study 2 (AREDS2) randomized clinical trial,” JAMA Internal Medicine, vol. 174, no. 5, pp. 763–771, 2014. View at Publisher · View at Google Scholar · View at Scopus
  17. W. T. Wong, W. Kam, D. Cunningham et al., “Treatment of geographic atrophy by the topical administration of OT-551: results of a phase II clinical trial,” Investigative Ophthalmology and Visual Science, vol. 51, no. 12, pp. 6131–6139, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. R. M. Plenge, E. M. Scolnick, and D. Altshuler, “Validating therapeutic targets through human genetics,” Nature Reviews Drug Discovery, vol. 12, no. 8, pp. 581–594, 2013. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Dopazo, “Genomics and transcriptomics in drug discovery,” Drug Discovery Today, vol. 19, no. 2, pp. 126–132, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. H.-J. Yang, R. Ratnapriya, T. Cogliati, J.-W. Kim, and A. Swaroop, “Vision from next generation sequencing: multi-dimensional genome-wide analysis for producing gene regulatory networks underlying retinal development, aging and disease,” Progress in Retinal and Eye Research, vol. 46, pp. 1–30, 2015. View at Publisher · View at Google Scholar · View at Scopus
  21. B. Chen and A. J. Butte, “Leveraging big data to transform target selection and drug discovery,” Clinical Pharmacology and Therapeutics, vol. 99, no. 3, pp. 285–297, 2016. View at Publisher · View at Google Scholar · View at Scopus
  22. J. Bajorath, “Computer-aided drug discovery,” F1000Research, vol. 4, 2015. View at Publisher · View at Google Scholar
  23. Y. Chen and K. Palczewski, “Systems pharmacology links GPCRs with retinal degenerative disorders,” Annual Review of Pharmacology and Toxicology, vol. 56, pp. 273–298, 2016. View at Publisher · View at Google Scholar · View at Scopus
  24. M. Vidal, M. E. Cusick, and A.-L. Barabási, “Interactome networks and human disease,” Cell, vol. 144, no. 6, pp. 986–998, 2011. View at Publisher · View at Google Scholar · View at Scopus
  25. A. Segura-Cabrera, N. Singh, and K. Komurov, “An integrated network platform for contextual prioritization of drugs and pathways,” Molecular BioSystems, vol. 11, no. 11, pp. 2850–2859, 2015. View at Publisher · View at Google Scholar · View at Scopus
  26. M. Fillet and M. Frédérich, “The emergence of metabolomics as a key discipline in the drug discovery process,” Drug Discovery Today: Technologies, vol. 13, pp. 19–24, 2015. View at Publisher · View at Google Scholar · View at Scopus
  27. J. Dehairs, R. Derua, N. Rueda-Rincon, and J. V. Swinnen, “Lipidomics in drug development,” Drug Discovery Today: Technologies, vol. 13, pp. 33–38, 2015. View at Publisher · View at Google Scholar · View at Scopus
  28. J. Shi, E. Wang, J. P. Milazzo, Z. Wang, J. B. Kinney, and C. R. Vakoc, “Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains,” Nature Biotechnology, vol. 33, no. 6, pp. 661–667, 2015. View at Publisher · View at Google Scholar · View at Scopus
  29. A. N. Shah, C. F. Davey, A. C. Whitebirch, A. C. Miller, and C. B. Moens, “Rapid reverse genetic screening using CRISPR in zebrafish,” Nature Methods, vol. 12, no. 6, pp. 535–540, 2015. View at Publisher · View at Google Scholar · View at Scopus
  30. M. B. Gerstein, A. Kundaje, M. Hariharan et al., “Architecture of the human regulatory network derived from ENCODE data,” Nature, vol. 489, no. 7414, pp. 91–100, 2012. View at Publisher · View at Google Scholar · View at Scopus
  31. D. Szklarczyk, A. Franceschini, S. Wyder et al., “STRING v10: protein-protein interaction networks, integrated over the tree of life,” Nucleic Acids Research, vol. 43, no. 1, pp. D447–D452, 2015. View at Publisher · View at Google Scholar · View at Scopus
  32. G. O. Consortium, “Gene ontology consortium: going forward,” Nucleic Acids Research, vol. 43, pp. D1049–D1056, 2015. View at Google Scholar
  33. M. Kanehisa, Y. Sato, M. Kawashima, M. Furumichi, and M. Tanabe, “KEGG as a reference resource for gene and protein annotation,” Nucleic Acids Research, vol. 44, no. D1, pp. D457–D462, 2016. View at Publisher · View at Google Scholar
  34. J. S. Amberger, C. A. Bocchini, F. Schiettecatte, A. F. Scott, and A. Hamosh, “OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders,” Nucleic Acids Research, vol. 43, no. D1, pp. D789–D798, 2015. View at Publisher · View at Google Scholar · View at Scopus
  35. V. Law, C. Knox, Y. Djoumbou et al., “DrugBank 4.0: shedding new light on drug metabolism,” Nucleic Acids Research, vol. 42, no. 1, pp. D1091–D1097, 2014. View at Publisher · View at Google Scholar · View at Scopus
  36. A. Vailaya, P. Bluvas, R. Kincaid, A. Kuchinsky, M. Creech, and A. Adler, “An architecture for biological information extraction and representation,” Bioinformatics, vol. 21, no. 4, pp. 430–438, 2005. View at Publisher · View at Google Scholar · View at Scopus
  37. S. Mukhopadhyay, M. Palakal, and K. Maddu, “Multi-way association extraction and visualization from biological text documents using hyper-graphs: applications to genetic association studies for diseases,” Artificial Intelligence in Medicine, vol. 49, no. 3, pp. 145–154, 2010. View at Publisher · View at Google Scholar · View at Scopus
  38. Y. Okada, D. Wu, G. Trynka et al., “Genetics of rheumatoid arthritis contributes to biology and drug discovery,” Nature, vol. 506, no. 7488, pp. 376–381, 2014. View at Google Scholar
  39. J. Menche, A. Sharma, and M. Kitsak, “Disease networks. Uncovering disease-disease relationships through the incomplete interactome,” Science, vol. 347, no. 6224, p. 1257601, 2015. View at Publisher · View at Google Scholar · View at Scopus
  40. M. Eiraku, N. Takata, H. Ishibashi et al., “Self-organizing optic-cup morphogenesis in three-dimensional culture,” Nature, vol. 472, no. 7341, pp. 51–56, 2011. View at Publisher · View at Google Scholar · View at Scopus
  41. T. Nakano, S. Ando, N. Takata et al., “Self-formation of optic cups and storable stratified neural retina from human ESCs,” Cell Stem Cell, vol. 10, no. 6, pp. 771–785, 2012. View at Publisher · View at Google Scholar · View at Scopus
  42. S. Reichman, A. Terray, A. Slembrouck et al., “From confluent human iPS cells to self-forming neural retina and retinal pigmented epithelium,” Proceedings of the National Academy of Sciences of the United States of America, vol. 111, no. 23, pp. 8518–8523, 2014. View at Publisher · View at Google Scholar · View at Scopus
  43. Y. Nishimura, S. Okabe, S. Sasagawa et al., “Pharmacological profiling of zebrafish behavior using chemical and genetic classification of sleep-wake modifiers,” Frontiers in Pharmacology, vol. 6, article 257, 2015. View at Publisher · View at Google Scholar · View at Scopus
  44. S. Sasagawa, Y. Nishimura, H. Sawada et al., “Comparative transcriptome analysis identifies CCDC80 as a novel gene associated with pulmonary arterial hypertension,” Frontiers in Pharmacology, vol. 7, p. 142, 2016. View at Google Scholar
  45. S. Sasagawa, Y. Nishimura, S. Okabe et al., “Downregulation of GSTK1 is a common mechanism underlying hypertrophic cardiomyopathy,” Frontiers in Pharmacology, vol. 7, article 162, 2016. View at Publisher · View at Google Scholar
  46. Y. Nishimura, S. Murakami, Y. Ashikawa et al., “Zebrafish as a systems toxicology model for developmental neurotoxicity testing,” Congenital Anomalies, vol. 55, no. 1, pp. 1–16, 2015. View at Publisher · View at Google Scholar · View at Scopus
  47. Y. Nishimura, A. Inoue, S. Sasagawa et al., “Using zebrafish in systems toxicology for developmental toxicity testing,” Congenital Anomalies, vol. 56, no. 1, pp. 18–27, 2016. View at Publisher · View at Google Scholar · View at Scopus
  48. T. Nakao, M. Tsujikawa, S. Notomi, Y. Ikeda, and K. Nishida, “The role of mislocalized phototransduction in photoreceptor cell death of retinitis pigmentosa,” PLoS ONE, vol. 7, no. 4, Article ID e32472, 2012. View at Publisher · View at Google Scholar · View at Scopus
  49. K. Tsuruma, Y. Nishimura, S. Kishi, M. Shimazawa, T. Tanaka, and H. Hara, “SEMA4A mutations lead to susceptibility to light irradiation, oxidative stress, and ER stress in retinal pigment epithelial cells,” Investigative Ophthalmology and Visual Science, vol. 53, no. 10, pp. 6729–6737, 2012. View at Publisher · View at Google Scholar · View at Scopus
  50. J. Chhetri, G. Jacobson, and N. Gueven, “Zebrafish—on the move towards ophthalmological research,” Eye (London), vol. 28, no. 4, pp. 367–380, 2014. View at Publisher · View at Google Scholar · View at Scopus
  51. R. Richardson, D. Tracey-White, A. Webster, and M. Moosajee, “The zebrafish eye—a paradigm for investigating human ocular genetics,” Eye, 2016. View at Publisher · View at Google Scholar
  52. S. Sasagawa, Y. Nishimura, T. Kon et al., “DNA damage reesponse Is involved in the developmental toxicity of mebendazole in zebrafish retina,” Frontiers in Pharmacology, vol. 7, p. 57, 2016. View at Google Scholar
  53. R. Kawase, Y. Nishimura, Y. Ashikawa et al., “EP300 Protects from Light-Induced Retinopathy in Zebrafish,” Frontiers in Pharmacology, vol. 7, 2016. View at Publisher · View at Google Scholar
  54. Y. Saito, K. Tsuruma, M. Shimazawa, Y. Nishimura, T. Tanaka, and H. Hara, “Establishment of a drug evaluation model against light-induced retinal degeneration using adult pigmented zebrafish,” Journal of Pharmacological Sciences, vol. 131, no. 3, pp. 215–218, 2016. View at Publisher · View at Google Scholar
  55. H. Matsubara, T. Tanaka, Y. Nishimura, Y. Matsui, T. Yamamoto, and M. Kondo, “Circadian rhythm of electroretinograms in living zebrafish larvae,” Investigative Ophthalmology & Visual Science, vol. 54, no. 15, article 3419, 2013. View at Google Scholar
  56. B. W. Jones, M. Kondo, H. Terasaki et al., “Retinal remodeling in the Tg P347L rabbit, a large-eye model of retinal degeneration,” Journal of Comparative Neurology, vol. 519, no. 14, pp. 2713–2733, 2011. View at Publisher · View at Google Scholar · View at Scopus
  57. R. Hirota, M. Kondo, S. Ueno, T. Sakai, T. Koyasu, and H. Terasaki, “Photoreceptor and post-photoreceptoral contributions to photopic ERG a-wave in rhodopsin P347L transgenic rabbits,” Investigative Ophthalmology and Visual Science, vol. 53, no. 3, pp. 1467–1472, 2012. View at Publisher · View at Google Scholar · View at Scopus
  58. T. Hasegawa, Y. Muraoka, H. O. Ikeda et al., “Neuoroprotective efficacies by KUS121, a VCP modulator, on animal models of retinal degeneration,” Scientific Reports, vol. 6, article 31184, 2016. View at Publisher · View at Google Scholar
  59. Y. Nakagami, E. Hatano, T. Inoue, K. Yoshida, M. Kondo, and H. Terasaki, “Cytoprotective effects of a novel Nrf2 activator, RS9, in Rhodopsin Pro347Leu rabbits,” Current Eye Research, vol. 41, no. 8, pp. 1–4, 2015. View at Publisher · View at Google Scholar · View at Scopus
  60. M. Shimazawa, Y. Ito, Y. Inokuchi et al., “An alteration in the lateral geniculate nucleus of experimental glaucoma monkeys: in vivo positron emission tomography imaging of glial activation,” PLoS ONE, vol. 7, no. 1, Article ID e30526, 2012. View at Publisher · View at Google Scholar · View at Scopus
  61. M. Shimazawa, S. Nakamura, M. Miwa et al., “Establishment of the ocular hypertension model using the common marmoset,” Experimental Eye Research, vol. 111, pp. 1–8, 2013. View at Publisher · View at Google Scholar · View at Scopus
  62. M. Shimazawa, T. Masuda, S. Nakamura, M. Miwa, K. Nakamura, and H. Hara, “An experimental model for exudative age-related macular degeneration with choroidal neovascularization using the common marmoset,” Current Neurovascular Research, vol. 12, no. 2, pp. 128–134, 2015. View at Publisher · View at Google Scholar · View at Scopus
  63. K. Patrias, Citing Medicine: The NLM Style Guide for Authors, Editors, and Publishers, 2nd edition, 2007.
  64. P. Shannon, A. Markiel, O. Ozier et al., “Cytoscape: a software environment for integrated models of biomolecular interaction networks,” Genome Research, vol. 13, no. 11, pp. 2498–2504, 2003. View at Publisher · View at Google Scholar · View at Scopus
  65. K. Abu-Amero, A. A. Kondkar, and K. V. Chalam, “An updated review on the genetics of primary open angle glaucoma,” International Journal of Molecular Sciences, vol. 16, no. 12, pp. 28886–28911, 2015. View at Publisher · View at Google Scholar · View at Scopus
  66. J. N. C. Bailey, S. J. Loomis, J. H. Kang et al., “Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma,” Nature Genetics, vol. 48, no. 2, pp. 189–194, 2016. View at Publisher · View at Google Scholar · View at Scopus
  67. C. C. Khor, T. Do, H. Jia et al., “Genome-wide association study identifies five new susceptibility loci for primary angle closure glaucoma,” Nature Genetics, vol. 48, no. 5, pp. 556–562, 2016. View at Google Scholar
  68. D. W. Huang, B. T. Sherman, Q. Tan et al., “DAVID bioinformatics resources: expanded annotation database and novel algorithms to better extract biology from large gene lists,” Nucleic Acids Research, vol. 35, no. 2, pp. W169–W175, 2007. View at Publisher · View at Google Scholar · View at Scopus
  69. E. Favari, I. Zanotti, F. Zimetti, N. Ronda, F. Bernini, and G. H. Rothblat, “Probucol inhibits ABCA1-mediated cellular lipid efflux,” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 24, no. 12, pp. 2345–2350, 2004. View at Publisher · View at Google Scholar · View at Scopus
  70. M. J. Falk, E. Polyak, Z. Zhang et al., “Probucol ameliorates renal and metabolic sequelae of primary CoQ deficiency in Pdss2 mutant mice,” EMBO Molecular Medicine, vol. 3, no. 7, pp. 410–427, 2011. View at Publisher · View at Google Scholar · View at Scopus
  71. X.-Y. Bai, Y. Ma, R. Ding, B. Fu, S. Shi, and X.-M. Chen, “miR-335 and miR-34a promote renal senescence by suppressing mitochondrial antioxidative enzymes,” Journal of the American Society of Nephrology, vol. 22, no. 7, pp. 1252–1261, 2011. View at Publisher · View at Google Scholar · View at Scopus
  72. M. Naito, H. Umegaki, and A. Iguchi, “Protective effects of probucol against glutamate-induced cytotoxicity in neuronal cell line PC12,” Neuroscience Letters, vol. 186, no. 2-3, pp. 211–213, 1995. View at Publisher · View at Google Scholar · View at Scopus
  73. T. Harada, C. Harada, K. Nakamura et al., “The potential role of glutamate transporters in the pathogenesis of normal tension glaucoma,” The Journal of Clinical Investigation, vol. 117, no. 7, pp. 1763–1770, 2007. View at Publisher · View at Google Scholar · View at Scopus
  74. N. Bai, H. Hayashi, T. Aida et al., “Dock3 interaction with a glutamate-receptor NR2D subunit protects neurons from excitotoxicity,” Molecular Brain, vol. 6, no. 1, article no. 22, 2013. View at Publisher · View at Google Scholar · View at Scopus
  75. K. Namekata, A. Kimura, K. Kawamura et al., “Dock3 attenuates neural cell death due to NMDA neurotoxicity and oxidative stress in a mouse model of normal tension glaucoma,” Cell Death and Differentiation, vol. 20, no. 9, pp. 1250–1256, 2013. View at Publisher · View at Google Scholar · View at Scopus
  76. R. Mastropasqua, V. Fasanella, L. Agnifili et al., “Advance in the pathogenesis and treatment of normal-tension glaucoma,” Progress in Brain Research, vol. 221, pp. 213–232, 2015. View at Publisher · View at Google Scholar · View at Scopus
  77. Y. Ito, M. Shimazawa, K. Tsuruma et al., “Induction of amyloid-β1-42 in the retina and optic nerve head of chronic ocular hypertensive monkeys,” Molecular Vision, vol. 18, pp. 2647–2657, 2012. View at Google Scholar · View at Scopus
  78. V. Gupta, Y. You, J. Li et al., “BDNF impairment is associated with age-related changes in the inner retina and exacerbates experimental glaucoma,” Biochimica et Biophysica Acta (BBA)—Molecular Basis of Disease, vol. 1842, no. 9, pp. 1567–1578, 2014. View at Publisher · View at Google Scholar · View at Scopus
  79. T. E. Salt, S. Nizari, M. F. Cordeiro, H. Russ, and W. Danysz, “Effect of the Aβ aggregation modulator MRZ-99030 on retinal damage in an animal model of glaucoma,” Neurotoxicity Research, vol. 26, no. 4, pp. 440–446, 2014. View at Publisher · View at Google Scholar · View at Scopus
  80. V. Gupta, V. B. Gupta, N. Chitranshi et al., “One protein, multiple pathologies: multifaceted involvement of amyloid β in neurodegenerative disorders of the brain and retina,” Cellular and Molecular Life Sciences, vol. 73, no. 22, pp. 4279–4297, 2016. View at Publisher · View at Google Scholar
  81. J. Sevigny, P. Chiao, T. Bussière et al., “The antibody aducanumab reduces Aβ plaques in Alzheimer’s disease,” Nature, vol. 537, no. 7618, pp. 50–56, 2016. View at Publisher · View at Google Scholar
  82. C. R. Stewart, L. M. Stuart, K. Wilkinson et al., “CD36 ligands promote sterile inflammation through assembly of a Toll-like receptor 4 and 6 heterodimer,” Nature Immunology, vol. 11, no. 2, pp. 155–161, 2010. View at Publisher · View at Google Scholar · View at Scopus
  83. S. H. Choi, D. Sviridov, and Y. I. Miller, “Oxidized cholesteryl esters and inflammation,” Biochim Biophys Acta, 2016. View at Publisher · View at Google Scholar
  84. K. Semba, K. Namekata, X. Guo, C. Harada, T. Harada, and Y. Mitamura, “Renin-Angiotensin system regulates neurodegeneration in a mouse model of normal tension glaucoma,” Cell Death and Disease, vol. 5, no. 7, Article ID e1333, 2014. View at Publisher · View at Google Scholar · View at Scopus
  85. Y. Suzuki, K. Hattori, J. Hamanaka et al., “Pharmacological inhibition of TLR4-NOX4 signal protects against neuronal death in transient focal ischemia,” Scientific Reports, vol. 2, article no. 896, 2012. View at Publisher · View at Google Scholar · View at Scopus
  86. F. Peri and V. Calabrese, “Toll-like receptor 4 (TLR4) modulation by synthetic and natural compounds: an update,” Journal of Medicinal Chemistry, vol. 57, no. 9, pp. 3612–3622, 2014. View at Publisher · View at Google Scholar · View at Scopus
  87. L. G. Fritsche, R. N. Fariss, D. Stambolian, G. R. Abecasis, C. A. Curcio, and A. Swaroop, “Age-related macular degeneration: genetics and biology coming together,” Annual Review of Genomics and Human Genetics, vol. 15, pp. 151–171, 2014. View at Publisher · View at Google Scholar · View at Scopus
  88. L. G. Fritsche, W. Igl, J. N. Bailey et al., “A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants,” Nature Genetics, vol. 48, no. 2, pp. 134–143, 2016. View at Google Scholar
  89. J. Ambati and B. J. Fowler, “Mechanisms of age-related macular degeneration,” Neuron, vol. 75, no. 1, pp. 26–39, 2012. View at Publisher · View at Google Scholar · View at Scopus
  90. A. G. Marneros, “VEGF-A and the NLRP3 inflammasome in age-related macular degeneration,” Advances in Experimental Medicine and Biology, vol. 854, pp. 79–85, 2016. View at Publisher · View at Google Scholar · View at Scopus
  91. H.-L. Hsieh and C.-M. Yang, “Role of redox signaling in neuroinflammation and neurodegenerative diseases,” BioMed Research International, vol. 2013, Article ID 484613, 18 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  92. V. Lambert, B. Wielockx, C. Munaut et al., “MMP-2 and MMP-9 synergize in promoting choroidal neovascularization,” FASEB Journal, vol. 17, no. 15, pp. 2290–2292, 2003. View at Publisher · View at Google Scholar · View at Scopus
  93. S. Grisanti and O. Tatar, “The role of vascular endothelial growth factor and other endogenous interplayers in age-related macular degeneration,” Progress in Retinal and Eye Research, vol. 27, no. 4, pp. 372–390, 2008. View at Publisher · View at Google Scholar · View at Scopus
  94. W.-H. Zhu, X. Guo, S. Villaschi, and R. Francesco Nicosia, “Regulation of vascular growth and regression by matrix metalloproteinases in the rat aorta model of angiogenesis,” Laboratory Investigation, vol. 80, no. 4, pp. 545–555, 2000. View at Publisher · View at Google Scholar · View at Scopus
  95. M. Del V Cano and P. L. Gehlbach, “PPAR-α ligands as potential therapeutic agents for wet age-related macular degeneration,” PPAR Research, vol. 2008, Article ID 821592, 5 pages, 2008. View at Publisher · View at Google Scholar · View at Scopus
  96. A. A. Herzlich, J. Tuo, and C.-C. Chan, “Peroxisome proliferator-activated receptor and age-related macular degeneration,” PPAR Research, vol. 2008, Article ID 389507, 11 pages, 2008. View at Publisher · View at Google Scholar · View at Scopus
  97. A. Sur, S. Kesaraju, H. Prentice et al., “Pharmacological protection of retinal pigmented epithelial cells by sulindac involves PPAR-α,” Proceedings of the National Academy of Sciences of the United States of America, vol. 111, no. 47, pp. 16754–16759, 2014. View at Publisher · View at Google Scholar · View at Scopus
  98. J. E. Knickelbein, A. B. Abbott, and E. Y. Chew, “Fenofibrate and diabetic retinopathy,” Current Diabetes Reports, vol. 16, no. 10, 2016. View at Publisher · View at Google Scholar
  99. G. de Moraes and C. J. Layton, “Therapeutic targeting of diabetic retinal neuropathy as a strategy in preventing diabetic retinopathy,” Clinical & Experimental Ophthalmology, 2016. View at Publisher · View at Google Scholar
  100. X. Zhou, L. L. Wong, A. S. Karakoti, S. Seal, and J. F. McGinnis, “Nanoceria inhibit the development and promote the regression of pathologic retinal neovascularization in the Vldlr knockout mouse,” PLoS ONE, vol. 6, no. 2, Article ID e16733, 2011. View at Publisher · View at Google Scholar · View at Scopus
  101. X. Chen, S. S. Rong, Q. Xu et al., “Diabetes mellitus and risk of age-related macular degeneration: a systematic review and meta-analysis,” PLoS ONE, vol. 9, no. 9, Article ID e108196, 2014. View at Publisher · View at Google Scholar · View at Scopus
  102. J. L. Wilkinson-Berka, A. Agrotis, and D. Deliyanti, “The retinal renin-angiotensin system: roles of angiotensin II and aldosterone,” Peptides, vol. 36, no. 1, pp. 142–150, 2012. View at Publisher · View at Google Scholar · View at Scopus
  103. M. J. Giese and R. C. Speth, “The ocular renin-angiotensin system: a therapeutic target for the treatment of ocular disease,” Pharmacology and Therapeutics, vol. 142, no. 1, pp. 11–32, 2014. View at Publisher · View at Google Scholar · View at Scopus
  104. C. Hernández, M. Dal Monte, R. Simó, and G. Casini, “Neuroprotection as a therapeutic target for diabetic retinopathy,” Journal of Diabetes Research, vol. 2016, Article ID 9508541, 18 pages, 2016. View at Publisher · View at Google Scholar
  105. J. A. Phipps, A. I. Jobling, U. Greferath, E. L. Fletcher, and K. A. Vessey, “Alternative pathways in the development of diabetic retinopathy: the renin-angiotensin and kallikrein-kinin systems,” Clinical and Experimental Optometry, vol. 95, no. 3, pp. 282–289, 2012. View at Publisher · View at Google Scholar · View at Scopus