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BioMed Research International
Volume 2013, Article ID 523415, 8 pages
http://dx.doi.org/10.1155/2013/523415
Research Article

Identification of Age-Related Macular Degeneration Related Genes by Applying Shortest Path Algorithm in Protein-Protein Interaction Network

1Department of Ophthalmology, Shanghai First People’s Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200080, China
2State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiaotong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200025, China
3Beijing Genomics Institute, Shenzhen Beishan Industrial Zone, Shenzhen 518083, China
4Institute of Systems Biology, Shanghai University, Shanghai 200444, China
5College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China

Received 22 October 2013; Accepted 27 November 2013

Academic Editor: Tao Huang

Copyright © 2013 Jian Zhang et al. 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. K. M. Gehrs, D. H. Anderson, L. V. Johnson, and G. S. Hageman, “Age-related macular degeneration—emerging pathogenetic and therapeutic concepts,” Annals of Medicine, vol. 38, no. 7, pp. 450–471, 2006. View at Publisher · View at Google Scholar · View at Scopus
  2. R. Klein, C.-F. Chou, B. E. K. Klein, X. Zhang, S. M. Meuer, and J. B. Saaddine, “Prevalence of age-related macular degeneration in the US population,” Archives of Ophthalmology, vol. 129, no. 1, pp. 75–80, 2011. View at Publisher · View at Google Scholar · View at Scopus
  3. X. Tong, Macular Degeneration, Baidu Baike, 2013.
  4. C. M. Cheung and T. Y. Wong, “Treatment of age-related macular degeneration,” The Lancet, vol. 382, no. 9900, pp. 1230–1232, 2013. View at Publisher · View at Google Scholar
  5. R. Sarangarajan and S. P. Apte, “Melanin aggregation and polymerization: possible implications in age-related macular degeneration,” Ophthalmic Research, vol. 37, no. 3, pp. 136–141, 2005. View at Publisher · View at Google Scholar · View at Scopus
  6. C. Glazer-Hockstein and J. L. Dunaief, “Could blue light-blocking lenses decrease the risk of age-related macular degeneration?” Retina, vol. 26, no. 1, pp. 1–4, 2006. View at Publisher · View at Google Scholar · View at Scopus
  7. T. H. Margrain, M. Boulton, J. Marshall, and D. H. Sliney, “Do blue light filters confer protection against age-related macular degeneration?” Progress in Retinal and Eye Research, vol. 23, no. 5, pp. 523–531, 2004. View at Publisher · View at Google Scholar · View at Scopus
  8. M. B. Gorin, “Genetic insights into age-related macular degeneration: controversies addressing risk, causality, and therapeutics,” Molecular Aspects of Medicine, vol. 33, pp. 467–486, 2012. View at Google Scholar
  9. U. Chakravarthy, T. Y. Wong, A. Fletcher et al., “Clinical risk factors for age-related macular degeneration: a systematic review and meta-analysis,” BMC Ophthalmology, vol. 10, no. 1, article 31, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. A. Y. C. Ting, T. K. M. Lee, and I. M. MacDonald, “Genetics of age-related macular degeneration,” Current Opinion in Ophthalmology, vol. 20, no. 5, pp. 369–376, 2009. View at Publisher · View at Google Scholar · View at Scopus
  11. K. Antoniak, W. Bienias, and J. Z. Nowak, “Age-related macular degeneration—A complex genetic disease,” Klinika Oczna, vol. 110, no. 4–6, pp. 211–218, 2008. View at Google Scholar · View at Scopus
  12. Y. Yu, T. R. Bhangale, J. Fagerness et al., “Common variants near FRK/COL10A1 and VEGFA are associated with advanced age-related macular degeneration,” Human Molecular Genetics, vol. 20, no. 18, pp. 3699–3709, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. B. Niu, Y. D. Cai, W. C. Lu, G.-Z. Li, and K.-C. Chou, “Predicting protein structural class with AdaBoost Learner,” Protein and Peptide Letters, vol. 13, no. 5, pp. 489–492, 2006. View at Publisher · View at Google Scholar · View at Scopus
  14. P. Gao, Q. P. Wang, L. Chen, and T. Huang, “Prediction of human genes regulatory functions based on proteinprotein interaction network,” Protein and Peptide Letters, vol. 19, pp. 910–916, 2012. View at Google Scholar
  15. L. Hu, T. Huang, X. Shi, W.-C. Lu, Y. D. Cai, and K.-C. Chou, “Predicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid properties,” PLoS ONE, vol. 6, no. 1, Article ID e14556, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. L. Hu, T. Huang, X.-J. Liu, and Y. D. Cai, “Predicting protein phenotypes based on protein-protein interaction network,” PLoS ONE, vol. 6, no. 3, Article ID e17668, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. J. Cheng, J. Li, Z. Wang, J. Eickholt, and X. Deng, “The MULTICOM toolbox for protein structure prediction,” BMC Bioinformatics, vol. 13, article 65, 2012. View at Publisher · View at Google Scholar
  18. L. Chen, W. M. Zeng, Y.D. Cai, K.-Y. Feng, and K.-C. Chou, “Predicting anatomical therapeutic chemical (ATC) classification of drugs by integrating chemical-chemical interactions and similarities,” PLoS ONE, vol. 7, no. 4, Article ID e35254, 2012. View at Publisher · View at Google Scholar · View at Scopus
  19. Y. Yamanishi, M. Araki, A. Gutteridge, W. Honda, and M. Kanehisa, “Prediction of drug-target interaction networks from the integration of chemical and genomic spaces,” Bioinformatics, vol. 24, no. 13, pp. i232–i240, 2008. View at Publisher · View at Google Scholar · View at Scopus
  20. Y. Yamanishi, M. Kotera, M. Kanehisa, and S. Goto, “Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework,” Bioinformatics, vol. 26, no. 12, pp. i246–i254, 2010. View at Publisher · View at Google Scholar · View at Scopus
  21. L. Chen, T. Huang, J. Zhang et al., “Predicting drugs side effects based on chemical-chemical interactions and protein-chemical interactions,” BioMed Research International, vol. 2013, Article ID 485034, 8 pages, 2013. View at Publisher · View at Google Scholar
  22. L. Chen, J. Lu, X. Luo, and K.-Y. Feng, “Prediction of drug target groups based on chemical-chemical similarities and chemical-chemical/protein connections,” Biochimica et Biophysica Acta, 2013. View at Publisher · View at Google Scholar
  23. L. Chen, W. M. Zeng, Y. D. Cai, and T. Huang, “Prediction of metabolic pathway using graph property, chemical functional group and chemical structural set,” Current Bioinformatics, vol. 8, pp. 200–207, 2013. View at Google Scholar
  24. T. H. Gormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Eds., Introduction to Algorithms, MIT Press, Cambridge, Mass, USA, 1990.
  25. Z. Yang, N. J. Camp, H. Sun et al., “A variant of the HTRA1 gene increases susceptibility to age-related macular degeneration,” Science, vol. 314, no. 5801, pp. 992–993, 2006. View at Publisher · View at Google Scholar · View at Scopus
  26. A. DeWan, M. Liu, S. Hartman et al., “HTRA1 promoter polymorphism in wet age-related macular degeneration,” Science, vol. 314, no. 5801, pp. 989–992, 2006. View at Publisher · View at Google Scholar · View at Scopus
  27. T. P. Dryja, C. E. Briggs, E. L. Berson, P. J. Rosenfeld, and M. Abitbol, “ABCR gene and age-related macular degeneration,” Science, vol. 279, pp. 1107–1107, 1998. View at Google Scholar
  28. A. E. Hughes, N. Orr, H. Esfandiary, M. Diaz-Torres, T. Goodship, and U. Chakravarthy, “A common CFH haplotype, with deletion of CFHR1 and CFHR3, is associated with lower risk of age-related macular degeneration,” Nature Genetics, vol. 38, no. 10, pp. 1173–1177, 2006. View at Publisher · View at Google Scholar · View at Scopus
  29. L. G. Fritsche, N. Lauer, A. Hartmann et al., “An imbalance of human complement regulatory proteins CFHR1, CFHR3 and factor H influences risk for age-related macular degeneration (AMD),” Human Molecular Genetics, vol. 19, no. 23, pp. 4694–4704, 2010. View at Publisher · View at Google Scholar · View at Scopus
  30. L. G. Fritsche, W. Chen, M. Schu et al., “Seven new loci associated with age-related macular degeneration,” Nature Genetics, vol. 45, pp. 433–439, 2013. View at Google Scholar
  31. L. J. Jensen, M. Kuhn, M. Stark et al., “STRING 8—a global view on proteins and their functional interactions in 630 organisms,” Nucleic Acids Research, vol. 37, no. 1, pp. D412–D416, 2009. View at Publisher · View at Google Scholar · View at Scopus
  32. Y. F. Gao, L. Chen, Y. D. Cai et al., “Predicting metabolic pathways of small molecules and enzymes based on interaction information of chemicals and proteins,” PLoS ONE, vol. 7, Article ID e45944, 2012. View at Google Scholar
  33. J. Davis and M. Goadrich, “The relationship between precision-recall and ROC curves,” in Proceedings of the 23rd International Conference on Machine Learning (ICML '06), pp. 233–240, New York, NY, USA, June 2006. View at Publisher · View at Google Scholar · View at Scopus
  34. J. B. M. Craven, Markov Networks for Detecting Overlapping Elements in Sequence Data, The MIT Press, Cambridge, Mass, USA, 2005.
  35. R. Bunescu, R. Ge, R. J. Kate et al., “Comparative experiments on learning information extractors for proteins and their interactions,” Artificial Intelligence in Medicine, vol. 33, no. 2, pp. 139–155, 2005. View at Publisher · View at Google Scholar · View at Scopus
  36. D. E. Johnson and G. H. I. Wolfgang, “Predicting human safety: screening and computational approaches,” Drug Discovery Today, vol. 5, no. 10, pp. 445–454, 2000. View at Publisher · View at Google Scholar · View at Scopus
  37. B. Q. Li, B. Niu, L. Chen et al., “Identifying chemicals with potential therapy of HIV based on protein-protein and protein-chemical interaction network,” PLoS ONE, vol. 8, Article ID e65207, 2013. View at Google Scholar
  38. M. Jiang, Y. Chen, Y. Zhang et al., “Identification of hepatocellular carcinoma related genes with k-th shortest paths in a protein-protein interaction network,” Molecular BioSystems, vol. 9, pp. 2720–2728, 2013. View at Google Scholar
  39. D. W. Huang, B. T. Sherman, and R. A. Lempicki, “Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources,” Nature Protocols, vol. 4, no. 1, pp. 44–57, 2009. View at Publisher · View at Google Scholar · View at Scopus
  40. Y. Benjamini and D. Yekutieli, “The control of the false discovery rate in multiple testing under dependency,” Annals of Statistics, vol. 29, no. 4, pp. 1165–1188, 2001. View at Publisher · View at Google Scholar · View at Scopus
  41. G. S. Hageman, P. J. Luthert, N. H. Victor Chong, L. V. Johnson, D. H. Anderson, and R. F. Mullins, “An integrated hypothesis that considers drusen as biomarkers of immune-mediated processes at the RPE-Bruch's membrane interface in aging and age-related macular degeneration,” Progress in Retinal and Eye Research, vol. 20, no. 6, pp. 705–732, 2001. View at Publisher · View at Google Scholar · View at Scopus
  42. A. L. Wang, T. J. Lukas, M. Yuan, N. Du, M. O. Tso, and A. H. Neufeld, “Autophagy and exomoses in the aged retinal pigment epithelium: possible relevance to drusen formation and age-related macular degeneration,” PLoS ONE, vol. 4, no. 1, Article ID e4160, 2009. View at Publisher · View at Google Scholar · View at Scopus
  43. D. H. Anderson, R. F. Mullins, G. S. Hageman, and L. V. Johnson, “A role for local inflammation in the formation of drusen in the aging eye,” The American Journal of Ophthalmology, vol. 134, no. 3, pp. 411–431, 2002. View at Publisher · View at Google Scholar · View at Scopus
  44. Y. Murakami, H. Matsumoto, M. Roh et al., “Programmed necrosis, not apoptosis, is a key mediator of cell loss and DAMP-mediated inflammation in dsRNA-induced retinal degeneration,” Cell Death and Differentiation, 2013. View at Publisher · View at Google Scholar
  45. M. Chen, J. V. Forrester, and H. Xu, “Dysregulation in retinal para-inflammation and age-related retinal degeneration in CCL2 or CCR2 deficient mice,” PLoS ONE, vol. 6, no. 8, Article ID e22818, 2011. View at Publisher · View at Google Scholar · View at Scopus
  46. J. Ambati, J. P. Atkinson, and B. D. Gelfand, “Immunology of age-related macular degeneration,” Nature Reviews Immunology, vol. 13, pp. 438–451, 2013. View at Google Scholar
  47. S. M. Whitcup, A. Sodhi, J. P. Atkinson et al., “The role of the immune response in age-related macular degeneration,” International Journal of Inflammation, vol. 2013, Article ID 348092, 10 pages, 2013. View at Publisher · View at Google Scholar
  48. P. L. Penfold, M. C. Madigan, M. C. Gillies, and J. M. Provis, “Immunological and aetiological aspects of macular degeneration,” Progress in Retinal and Eye Research, vol. 20, no. 3, pp. 385–414, 2001. View at Publisher · View at Google Scholar · View at Scopus
  49. J. Ambati, A. Anand, S. Fernandez et al., “An animal model of age-related macular degeneration in senescent Ccl-2- or Ccr-2-deficient mice,” Nature Medicine, vol. 9, no. 11, pp. 1390–1397, 2003. View at Publisher · View at Google Scholar · View at Scopus
  50. R. J. Ross, M. Zhou, D. Shen et al., “Immunological protein expression profile in Ccl2/Cx3cr1 deficient mice with lesions similar to age-related macular degeneration,” Experimental Eye Research, vol. 86, no. 4, pp. 675–683, 2008. View at Publisher · View at Google Scholar · View at Scopus
  51. W. A. Tseng, T. Thein, K. Kinnunen et al., “NLRP3 inflammasome activation in retinal pigment epithelial cells by lysosomal destabilization: implications for age-related macular degeneration,” Investigative Ophthalmology and Visual Science, vol. 54, pp. 110–120, 2013. View at Google Scholar
  52. A. Kauppinen, H. Niskanen, T. Suuronen et al., “Oxidative stress activates NLRP3 inflammasomes in ARPE-19 cells—implications for age-related macular degeneration (AMD),” Immunology Letters, vol. 147, pp. 29–33, 2012. View at Google Scholar
  53. R. T. Liu, J. Gao, S. Cao et al., “Inflammatory mediators induced by amyloid-beta in the retina and RPE in vivo: implications for inflammasome activation in age-related macular degeneration,” Investigative Ophthalmology and Visual Science, vol. 54, pp. 2225–2237, 2013. View at Google Scholar
  54. M. E. Kleinman, K. Yamada, A. Takeda et al., “Sequence-and target-independent angiogenesis suppression by siRNA via TLR3,” Nature, vol. 452, no. 7187, pp. 591–597, 2008. View at Publisher · View at Google Scholar · View at Scopus
  55. M. E. Kleinman, H. Kaneko, W. G. Cho et al., “Short-interfering RNAs induce retinal degeneration via TLR3 and IRF3,” Molecular Therapy, vol. 20, no. 1, pp. 101–108, 2012. View at Publisher · View at Google Scholar · View at Scopus
  56. S. Lavalette, W. Raoul, M. Houssier et al., “Interleukin-1β inhibition prevents choroidal neovascularization and does not exacerbate photoreceptor degeneration,” The American Journal of Pathology, vol. 178, no. 5, pp. 2416–2423, 2011. View at Publisher · View at Google Scholar · View at Scopus
  57. A. Lambiase, M. Coassin, P. Tirassa, F. Mantelli, and L. Aloe, “Nerve growth factor eye drops improve visual acuity and electrofunctional activity in Age-related macular degeneration: a case report,” Annali dell'Istituto Superiore di Sanita, vol. 45, no. 4, pp. 439–442, 2009. View at Google Scholar · View at Scopus
  58. C. Baudouin, G. A. Peyman, D. Fredj-Reygrobellet et al., “Immunohistological study of subretinal membranes in age-related macular degeneration,” Japanese Journal of Ophthalmology, vol. 36, no. 4, pp. 443–451, 1992. View at Google Scholar · View at Scopus
  59. D. H. Anderson, M. J. Radeke, N. B. Gallo et al., “The pivotal role of the complement system in aging and age-related macular degeneration: hypothesis re-visited,” Progress in Retinal and Eye Research, vol. 29, no. 2, pp. 95–112, 2010. View at Publisher · View at Google Scholar · View at Scopus
  60. N. Kondo, H. Bessho, S. Honda, and A. Negi, “Complement factor H Y402H variant and risk of age-related macular degeneration in Asians: a systematic review and meta-analysis,” Ophthalmology, vol. 118, no. 2, pp. 339–344, 2011. View at Publisher · View at Google Scholar · View at Scopus
  61. J. Hoh Kam, E. Lenassi, T. H. Malik, M. C. Pickering, and G. Jeffery, “Complement component c3 plays a critical role in protecting the aging retina in a murine model of age-related macular degeneration,” The American Journal of Pathology, vol. 183, pp. 480–492, 2013. View at Google Scholar
  62. S. Sugita, S. Horie, Y. Yamada, and M. Mochizuki, “Inhibition of B-Cell activation by retinal pigment epithelium,” Investigative Ophthalmology and Visual Science, vol. 51, no. 11, pp. 5783–5788, 2010. View at Publisher · View at Google Scholar · View at Scopus
  63. Z. Dong, J. Li, Y. Leng et al., “Cyclic intensive light exposure induces retinal lesions similar to age-related macular degeneration in APPswe/PS1 bigenic mice,” BMC Neuroscience, vol. 13, article 34, 2012. View at Publisher · View at Google Scholar · View at Scopus
  64. Y. Sano, A. Furuta, R. Setsuie et al., “Photoreceptor cell apoptosis in the retinal degeneration of Uchl3-deficient mice,” The American Journal of Pathology, vol. 169, no. 1, pp. 132–141, 2006. View at Publisher · View at Google Scholar · View at Scopus
  65. J. Wan, R. Ramachandran, and D. Goldman, “HB-EGF is necessary and sufficient for Müller glia dedifferentiation and retina regeneration,” Developmental Cell, vol. 22, no. 2, pp. 334–347, 2012. View at Publisher · View at Google Scholar · View at Scopus
  66. L. Vuong, D. E. Brobst, I. Ivanovic, D. M. Sherry, and M. R. Al-Ubaidi, “p53 selectively regulates developmental apoptosis of rod photoreceptors,” PLoS ONE, vol. 8, Article ID e67381, 2013. View at Google Scholar
  67. H. Meisner, A. Daga, J. Buxton et al., “Interactions of Drosophila Cbl with epidermal growth factor receptors and role of Cbl in R7 photoreceptor cell development,” Molecular and Cellular Biology, vol. 17, no. 4, pp. 2217–2225, 1997. View at Google Scholar · View at Scopus
  68. B. M. Braunger, A. Ohlmann, M. Koch et al., “Constitutive overexpression of Norrin activates Wnt/beta-catenin and endothelin-2 signaling to protect photoreceptors from light damage,” Neurobiology of Disease, vol. 50, pp. 1–12, 2013. View at Google Scholar
  69. D. Sanges, N. Romo, G. Simonte, U. di Vicino, A. D. Tahoces et al., “Wnt/beta-catenin signaling triggers neuron reprogramming and regeneration in the mouse retina,” Cell Reports, vol. 4, pp. 271–286, 2013. View at Google Scholar