Human symptoms-disease network

Nature Communications

Volumn 5, Issue , 2014, Pages

  Zhou, Xuezhong ^a,b,c   Menche, Jörg ^b,c,d   Barabási, Albert László ^b,c,d,e,f   Sharma, Amitabh ^b,c,f  

^a BEIJING JIAOTONG UNIVERSITY   (China)

^b NORTHEASTERN UNIVERSITY   (United States)

^c DANA FARBER CANCER INSTITUTE   (United States)

^d BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

^e CENTRAL EUROPEAN UNIVERSITY   (Hungary)

^f HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE; DISEASE INCIDENCE; DRUG DEVELOPMENT; ETIOLOGY; GENETIC ANALYSIS; GENOME; MAPPING; MEDICINE; PROTEIN; SYMPTOM;

ARTICLE; CLINICAL FEATURE; CONTROLLED STUDY; DATA BASE; GENETIC ASSOCIATION; HUMAN; MOLECULAR INTERACTION; PROTEIN PROTEIN INTERACTION; SYMPTOM; DISEASES; GENETIC PREDISPOSITION; GENETICS; PHENOTYPE; SYSTEMS THEORY; THEORETICAL MODEL;

PROTEIN;

DISEASE; GENETIC PREDISPOSITION TO DISEASE; HUMANS; MODELS, THEORETICAL; PHENOTYPE; PROTEINS; SYSTEMS THEORY;

EID: 84903639346     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms5212     Document Type: Article

References (69)

1. Botstein, D. & Risch, N. Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat. Genet. 33 Suppl 228-237 (2003 (Pubitemid 36278833)
2. Vidal, M., Cusick, M. E. & Barabasi, A. L. Interactome networks and human disease. Cell 144, 986-998 (2011
3. McKusick, V. A. The growth and development of human genetics as a clinical discipline. Am. J. Hum. Genet. 27, 261-273 (1975
4. McKusick, V. A. On lumpers and splitters, or the nosology of genetic disease. Perspect. Biol. Med. 12, 298-312 (1969
5. Loscalzo, J., Kohane, I. & Barabasi, A. L. Human disease classification in the postgenomic era: a complex systems approach to human pathobiology. Mol. Syst. Biol. 3, 124 (2007
6. Barabasi, A. L., Gulbahce, N. & Loscalzo, J. Network medicine: a network-based approach to human disease. Nat. Rev. Genet. 12, 56-68 (2011
7. Wang, Q. et al. Community of protein complexes impacts disease association. Eur. J. Hum. Genet. 20, 1162-1167 (2012
8. Park, J., Lee, D. S., Christakis, N. A. & Barabasi, A. L. The impact of cellular networks on disease comorbidity. Mol. Syst. Biol. 5, 262 (2009
9. Hidalgo, C. A., Blumm, N., Barabasi, A. L. & Christakis, N. A. A dynamic network approach for the study of human phenotypes. PLoS. Comput. Biol. 5, e1000353 (2009
10. Lee, D. S. et al. The implications of human metabolic network topology for disease comorbidity. Proc. Natl Acad. Sci. USA 105, 9880-9885 (2008
11. Brunner, H. G. & van Driel, M. A. From syndrome families to functional genomics. Nat. Rev. Genet. 5, 545-551 (2004 (Pubitemid 38868510)
12. Rzhetsky, A., Wajngurt, D., Park, N. & Zheng, T. Probing genetic overlap among complex human phenotypes. Proc. Natl Acad. Sci. USA 104, 11694-11699 (2007 (Pubitemid 47175075)
13. Goh, K. I. et al. The human disease network. Proc. Natl Acad. Sci. USA 104, 8685-8690 (2007
14. Giot, L. et al. A protein interaction map of Drosophila melanogaster. Science 302, 1727-1736 (2003 (Pubitemid 37505730)
15. Li, S. et al. A map of the interactome network of the metazoan C. elegans. Science 303, 540-543 (2004 (Pubitemid 38120855)
16. Dudley, A. M., Janse, D. M., Tanay, A., Shamir, R. & Church, G. M. A global view of pleiotropy and phenotypically derived gene function in yeast. Mol. Syst. Biol. 1, 2005 0001 (2005
17. Gavin, A. C. et al. Proteome survey reveals modularity of the yeast cell machinery. Nature 440, 631-636 (2006
18. Freudenberg, J. & Propping, P. A similarity-based method for genome-wide prediction of disease-relevant human genes. Bioinformatics 18(Suppl 2): S110-S115 (2002 (Pubitemid 41073225)
19. van Driel, M. A., Bruggeman, J., Vriend, G., Brunner, H. G. & Leunissen, J. A. A text-mining analysis of the human phenome. Eur. J. Hum. Genet. 14, 535-542 (2006
20. Gandhi, T. K. et al. Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets. Nat. Genet. 38, 285-293 (2006
21. Wu, X., Jiang, R., Zhang, M. Q. & Li, S. Network-based global inference of human disease genes. Mol. Syst. Biol. 4, 189 (2008
22. Vanunu, O., Magger, O., Ruppin, E., Shlomi, T. & Sharan, R. Associating genes and protein complexes with disease via network propagation. PLoS. Comput. Biol. 6, e1000641 (2010
23. Wang, X., Gulbahce, N. & Yu, H. Network-based methods for human disease gene prediction. Brief. Funct. Genomics 10, 280-293 (2011
24. Moreau, Y. & Tranchevent, L. C. Computational tools for prioritizing candidate genes: boosting disease gene discovery. Nat. Rev. Genet. 13, 523-536 (2012
25. Robinson, P. N. et al. The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Am. J. Hum. Genet. 83, 610-615 (2008
26. Smith, C. L., Goldsmith, C. A. & Eppig, J. T. The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information. Genome Biol. 6, R7 (2005
27. Doelken, S. C. et al. Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish. Dis. Model. Mech. 6, 358-372 (2013
28. Robinson, P. N. et al. Improved exome prioritization of disease genes through cross-species phenotype comparison. Genome Res. 24, 340-348 (2014
29. Little, R. A. et al. Plasma catecholamines in the acute phase of the response to myocardial infarction. Arch. Emerg. Med. 3, 20-27 (1986 (Pubitemid 16110517)
30. Knottnerus, J. A. The effects of disease verification and referral on the relationship between symptoms and diseases. Med. Decis. Making 7, 139-148 (1987 (Pubitemid 17112779)
31. Lowe, H. J. & Barnett, G. O. Understanding and using the medical subject headings (MeSH) vocabulary to perform literature searches. JAMA 271, 1103-1108 (1994 (Pubitemid 24106508)
32. Wheeler, D. L. et al. Database resources of the National Center for Biotechnology Information. Nucleic. Acids. Res. 35, D5-D12 (2007 (Pubitemid 46056160)
33. Fisher, R. A. S. & Yates, F. Statistical Tables for Biological, Agricultural and Medical Research 2nd edn revised and enlarged (Oliver & Boyd, 1943
34. The-Cancer-Genome-Atlas-Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487, 330-337 (2012
35. Oti, M., Snel, B., Huynen, M. A. & Brunner, H. G. Predicting disease genes using protein-protein interactions. J. Med. Genet. 43, 691-698 (2006 (Pubitemid 44214908)
36. Warner, T. T. & Schapira, A. H. Genetic and environmental factors in the cause of Parkinson's disease. Ann. Neurol. 53(Suppl 3): S16-S23 (2003
37. Duty, S. & Jenner, P. Animal models of Parkinson's disease: a source of novel treatments and clues to the cause of the disease. Br. J. Pharmacol. 164, 1357-1391 (2011
38. Sanchez-Betancourt, J. et al. Manganese mixture inhalation is a reliable Parkinson disease model in rats. Neurotoxicology 33, 1346-1355 (2012
39. Vanduyn, N., Settivari, R., Wong, G. & Nass, R. SKN-1/Nrf2 inhibits dopamine neuron degeneration in a Caenorhabditis elegans model of methylmercury toxicity. Toxicol. Sci. 118, 613-624 (2010
40. Serrano, M. A., Boguna, M. & Vespignani, A. Extracting the multiscale backbone of complex weighted networks. Proc. Natl Acad. Sci. USA 106, 6483-6488 (2009
41. Grivennikov, S. I., Greten, F. R. & Karin, M. Immunity, inflammation, and cancer. Cell 140, 883-899 (2010
42. Chapman, S. J. & Hill, A. V. Human genetic susceptibility to infectious disease. Nat. Rev. Genet. 13, 175-188 (2012
43. Loscalzo, J. & Barabasi, A. L. Systems biology and the future of medicine. Wiley interdisciplinary reviews. Syst. Biol. Med. 3, 619-627 (2011
44. Molodecky, N. A. et al. Increasing incidence and prevalence of the inflammatory bowel diseases with time, based on systematic review. Gastroenterology 142, 46-54 (2012
45. Khor, B., Gardet, A. & Xavier, R. J. Genetics and pathogenesis of inflammatory bowel disease. Nature 474, 307-317 (2011
46. Jostins, L. et al. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119-124 (2012
47. Gulbahce, N. et al. Viral perturbations of host networks reflect disease etiology. PLoS. Comput. Biol. 8, e1002531 (2012
48. Yildirim, M. A., Goh, K. I., Cusick, M. E., Barabasi, A. L. & Vidal, M. Drugtarget network. Nat. Biotechnol. 25, 1119-1126 (2007
49. Campillos, M., Kuhn, M., Gavin, A. C., Jensen, L. J. & Bork, P. Drug target identification using side-effect similarity. Science 321, 263-266 (2008 (Pubitemid 351989100)
50. Kuhn, M., Campillos, M., Letunic, I., Jensen, L. J. & Bork, P. A side effect resource to capture phenotypic effects of drugs. Mol. Syst. Biol. 6, 343 (2010
51. Imfeld, P., Bodmer, M., Schuerch, M., Jick, S. S. & Meier, C. R. Seizures in patients with Alzheimer's disease or vascular dementia: a population-based nested case-control analysis. Epilepsia 54, 700-707 (2013
52. Sanchez, P. E. et al. Levetiracetam suppresses neuronal network dysfunction and reverses synaptic and cognitive deficits in an Alzheimer's disease model. Proc. Natl Acad. Sci. USA 109, E2895-E2903 (2012
53. Cote, R. A. & Robboy, S. Progress in medical information management. Systematized nomenclature of medicine (SNOMED). JAMA 243, 756-762 (1980 (Pubitemid 10169321)
54. Kohane, I. S. Using electronic health records to drive discovery in disease genomics. Nat. Rev. Genet. 12, 417-428 (2011
55. Hripcsak, G. & Albers, D. J. Next-generation phenotyping of electronic health records. J. Am. Med. Inform. Assoc. 20, 117-121 (2013
56. Jensen, P. B., Jensen, L. J. & Brunak, S. Mining electronic health records: towards better research applications and clinical care. Nat. Rev. Genet. 13, 395-405 (2012
57. Pathak, J., Kho, A. N. & Denny, J. C. Electronic health records-driven phenotyping: challenges, recent advances, and perspectives. J. Am. Med. Inform. Assoc. 20, e206-e211 (2013
58. Coletti, M. H. & Bleich, H. L. Medical subject headings used to search the biomedical literature. J. Am. Med. Inform. Assoc. 8, 317-323 (2001 (Pubitemid 32641634)
59. Jensen, L. J., Saric, J. & Bork, P. Literature mining for the biologist: from information retrieval to biological discovery. Nat. Rev. Genet. 7, 119-129 (2006 (Pubitemid 43128897)
60. Salton, G., Wong, A. & Yang, C. S. A vector space model for automatic indexing. Commun. ACM 18, 613-620 (1975
61. Cao, H., Hripcsak, G. & Markatou, M. A statistical methodology for analyzing co-occurrence data from a large sample. J. Biomed. Inform. 40, 343-352 (2007 (Pubitemid 46729709)
62. Schweder, T. & Spjotvoll, E. Plots of p-values to evaluate many tests simultaneously. Biometrika 69, 493-502 (1982
63. Girvan, M. & Newman, M. E. Community structure in social and biological networks. Proc. Natl Acad. Sci. USA 99, 7821-7826 (2002 (Pubitemid 34650963)
64. Watts, D. J. & Strogatz, S. H. Collective dynamics of 'small-world' networks. Nature 393, 440-442 (1998 (Pubitemid 28292183)
65. Cormen, T. H. & Cormen, T.H.I.t.a. Introduction to Algorithms (MIT Press, 2001
66. Newman, M. E. J. Networks: an introduction (Oxford University Press, 2010
67. Liu, Lu. et al. Mining Diversity on Networks. Database Systems for Advanced Applications 5981, 384-398 (2010
68. Freeman, L. C. A set of measures of centrality based on betweenness. Sociometry 40, 35-41 (1977
69. Hwang, W., Kim, T., Ramanathan, M. & Zhang, A. in Proceedings of the 14th ACM SIGKDD Internat Conf on Knowledge Discovery and Data Mining, 336-344 (ACM, 2008).