Phenome-driven disease genetics prediction toward drug discovery

Bioinformatics

Volumn 31, Issue 12, 2015, Pages i276-i283

  Chen, Yang ^a   Li, Li ^b   Zhang, Guo Qiang ^a   Xu, Rong ^b  

^a Case Western Reserve University   (United States)

^b CASE WESTERN RESERVE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CROHN DISEASE; DISEASES; DRUG DEVELOPMENT; GENE; GENETIC DATABASE; GENETICS; GENOMICS; HUMAN; PHENOTYPE; PROCEDURES; PROTEIN ANALYSIS;

CROHN DISEASE; DATABASES, GENETIC; DISEASE; DRUG DISCOVERY; GENES; GENOMICS; HUMANS; PHENOTYPE; PROTEIN INTERACTION MAPPING;

EID: 84931089568     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv245     Document Type: Conference Paper

References (63)

1. Aerts S., et al. (2006). Gene prioritization through genomic data fusion. Nat. Biotechnol., 24, 537-544
2. Antonarakis E.S. and Beckmann S.J. (2006). Mendelian disorders deserve more attention. Nat. Rev. Genet., 7, 277-282
3. Atreya R., et al. (2014). In vivo imaging using fluorescent antibodies to tumor necrosis factor predicts therapeutic response in Crohn's disease. Nat. Med., 20, 313-318
4. Barabási A.L., et al. (2011). Network medicine: a network-based approach to human disease. Nat. Rev. Genet., 12, 56-68
5. Baumgart C.D. and Sandborn J.W. (2007). Inflammatory bowel disease: clinical aspects and established and evolving therapies. Lancet, 369, 1641-1657
6. Berger I.S., et al. (2010). Systems pharmacology of arrhythmias. Sci. Signal, 3, ra30
7. Borthakur A., et al. (2007). Carrageenan induces interleukin-8 production through distinct Bcl10 pathway in normal human colonic epithelial cells. Am. J. Physiol. Gastrointest. Liver Physiol., 292, G829-G838
8. Brunner H.G. and Van Driel A.M. (2004). From syndrome families to functional genomics. Nat. Rev. Genet., 5, 545-551
9. Chen Y. and Xu R. (2014a) Network analysis of human disease comorbidity patterns based on large-scale data mining. In: Proceedings of the International Symposium on Bioinformatics Research and Applications, Zhangjiajie, China, June 28-30, 2014. pp. 243-254
10. Chen Y. and Xu R. (2014b) Mining cancer-specific disease comorbidities from a large observational database. Cancer Inform., 13 (Suppl. 1) , 37-44
11. Chen Y., et al. (2011). Uncover disease genes by maximizing information flow in the phenome-interactome network. Bioinformatics, 27, i167-i176
12. Chen Y., et al. (2015). Comparative analysis of a novel disease phenotype network based on clinical manifestations. J. Biomed. Inform., 53, 113-120
13. Cosnes J., et al. (2011). Epidemiology and natural history of inflammatory bowel diseases. Gastroenterology, 140, 1785-1794
14. Franke L., et al. (2006). Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. Am. J. Hum. Genet., 78, 1011-1025
15. Gerard R., et al. (2013). An immunological link between Candida albicans colonization and Crohn's disease. Crit. Rev. Microbiol., doi: 10.3109/1040841X.2013.810587
16. Gergis U., et al. (2010). Effectiveness and safety of tocilizumab, an antiinterleukin- 6 receptor monoclonal antibody, in a patient with refractory GI graft-versus-host disease. J. Clin. Oncol., 28, e602-e604
17. Hindorff A.L., et al. (2009). Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA, 106, 9362-9367
18. Hirota A.S., et al. (2011). NLRP3 inflammasome plays a key role in the regulation of intestinal homeostasis. Inflamm. Bowel Dis., 17, 1359-1372
19. Hoehndorf R., et al. (2011). PhenomeNET: a whole-phenome approach to disease gene discovery. Nucleic Acids Res., 39, e119
20. Houle D., et al. (2010). Phenomics: the next challenge. Nat. Rev. Genet., 11, 855-866
21. Hurle R.M., et al. (2013). Computational drug repositioning: from data to therapeutics. Clin. Pharmacol. Ther., 93, 335-341
22. Hwang T., et al. (2012). Co-clustering phenome-genome for phenotype classification and disease gene discovery. Nucleic Acids Res., 40, e146
23. Jostins L., et al. (2012). Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature, 491, 119-124
24. Kann G.M. (2010). Advances in translational bioinformatics: computational approaches for the hunting of disease genes. Brief Bioinform., 11, 96-110
25. Köhler S., et al. (2008). Walking the interactome for prioritization of candidate disease genes. Am. J. Hum. Genet., 82, 949-958
26. Korbel O.J., et al. (2005). Systematic association of genes to phenotypes by genome and literature mining. PLoS Biol., 3, e134
27. Korzenik R.J., et al. (2005). Sargramostim for active Crohn's disease. N. Engl. J. Med., 352, 2193-2201
28. Kufer A.T., et al. (2006). Role for erbin in bacterial activation of Nod2. Infect. Immun., 74, 3115-3124
29. Lage K., et al. (2007). A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat. Biotechnol., 25, 309-316
30. Law V., et al. (2014). DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res., 42, D1091-D1097
31. Lazzerini M., et al. (2013). Effect of thalidomide on clinical remission in children and adolescents with refractory Crohn disease: a randomized clinical trial. J. Am. Med. Assoc., 310, 2164-2173
32. Li Y. and Patra C.J. (2010). Genome-wide inferring gene-phenotype relationship by walking on the heterogeneous network. Bioinformatics, 26, 1219-1224
33. Lupfer C., et al. (2013). Receptor interacting protein kinase 2-mediated mitophagy regulates inflammasome activation during virus infection. Nat. Immunol., 14, 480-488
34. Margolis J.D., et al. (2010). Potential association between the oral tetracycline class of antimicrobials used to treat acne and inflammatory bowel disease. Am. J. Gastroenterol., 105, 2610-2616
35. Molodecky A.N., et al. (2012). Increasing incidence and prevalence of the inflammatory bowel diseases with time, based on systematic review. Gastroenterology, 142, 46-54
36. Moreau Y. and Tranchevent C.L. (2012). Computational tools for prioritizing candidate genes: boosting disease gene discovery. Nat. Rev. Genet., 13, 523-536
37. Natarajan N. and Dhillon S.I. (2014). Inductive matrix completion for predicting gene-disease associations. Bioinformatics, 30, i60-i68
38. Netea G.M., et al. (2010). IL-1b processing in host defense: beyond the inflammasomes. PLoS Pathog., 6, e1000661
39. Nishimoto N. and Kishimoto T. (2008). Humanized antihuman IL-6 receptor antibody, tocilizumab. Handb. Exp. Pharmacol., 181, 151-160
40. Oti M., et al. (2008). Phenome connections. Trends Genet., 24, 103-106
41. Oti M., et al. (2009). The biological coherence of human phenome databases. Am. J. Hum. Genet., 85, 801-808
42. Philpott J.D., et al. (2014). NOD proteins: regulators of inflammation in health and disease. Nat. Rev. Immunol., 14, 9-23
43. Piro R.M. and Di Cunto F. (2012). Computational approaches to diseasegene prediction: rationale, classification and successes. FEBS J., 279, 678-696
44. Plenge M.R., et al. (2013). Validating therapeutic targets through human genetics. Nat. Rev. Drug Discov., 12, 581-594
45. Prasad K.T., et al. (2009). Human protein reference database-2009 update. Nucleic Acids Res., 37 (Suppl. 1) , D767-D772
46. Puche E.J. and Castilla-Cortzar I. (2012). Human conditions of insulin-like growth factor-I (IGF-I) deficiency. J. Transl. Med., 10, 224
47. Rahimi R., et al. (2009). Efficacy of tricyclic antidepressants in irritable bowel syndrome: a meta-analysis.World J. Gastroenterol., 15, 1548-1553
48. Rahimi R.H., et al. (2012). Antidepressants can treat inflammatory bowel disease through regulation of the nuclear factor-B/nitric oxide pathway and inhibition of cytokine production: a hypothesis. World J. Gastrointest. Pharmacol. Ther., 3, 83
49. Robinson P.N., et al. (2008). The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Am. J. Hum. Genet., 83, 610-615
50. Rosenbloom L.A. (2009). Mecasermin (recombinant human insulin-like growth factor I) . Adv. Ther., 26, 40-54
51. Roth L., et al. (2011). Sargramostim (GM-CSF) for induction of remission in Crohn's disease. Cochrane Database Syst. Rev., CD008538
52. Sartor B.R. (2006). Mechanisms of disease: pathogenesis of Crohn's disease and ulcerative colitis. Nat. Clin. Pract.Gastroenterol.Hepatol., 3, 390-407
53. Standaert-Vitse A., et al. (2009). Candida albicans colonization and ASCA in familial Crohn's disease. Am. J. Gastroenterol., 104, 1745-1753
54. Tiffin N., et al. (2009). Linking genes to diseases: it's all in the data. Genome Med., 1, 77
55. Tomalka J., et al. (2011). A novel role for the NLRC4 inflammasome in mucosal defenses against the fungal pathogen Candida albicans. PLoS Pathog., 7, e1002379
56. Tranchevent L.C., et al. (2011). A guide to web tools to prioritize candidate genes. Brief Bioinform., 12, 22-32
57. Van Driel A.M., et al. (2006). A text-mining analysis of the human phenome. Eur. J. Hum. Genet., 14, 535-542
58. Vanunu O., et al. (2010). Associating genes and protein complexes with disease via network propagation. PLoS Comput. Biol., 6, e1000641
59. Villani C.A., et al. (2008). Common variants in the NLRP3 region contribute to Crohn's disease susceptibility. Nat. Genet., 41, 71-76
60. Wang X., et al. (2011). Network-based methods for human disease gene prediction. Brief Funct. Genomics, 10, 280-293
61. Wu X., et al. (2008). Network-based global inference of human disease genes. Mol. Syst. Biol., 4, 189
62. Wu X., et al. (2009). Align human interactome with phenome to identify causative genes and networks underlying disease families. Bioinformatics, 25, 98-104
63. Xu J. and Li Y. (2006). Discovering disease-genes by topological features in human protein-protein interaction network. Bioinformatics, 22, 2800-2805