Uncovering disease-disease relationships through the incomplete interactome

Science

Volumn 347, Issue 6224, 2015, Pages 841-

  Menche, Jörg ^a,b,c   Sharma, Amitabh ^a,b   Kitsak, Maksim ^a,b   Ghiassian, Susan Dina ^a,b   Vidal, Marc ^b,d   Loscalzo, Joseph ^e   Barabási, Albert László ^a,b,c,d,e  

^a NORTHEASTERN UNIVERSITY   (United States)

^b DANA FARBER CANCER INSTITUTE   (United States)

^c CENTRAL EUROPEAN UNIVERSITY   (Hungary)

^d HARVARD MEDICAL SCHOOL   (United States)

^e BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENZYME; REGULATOR PROTEIN; TRANSCRIPTION FACTOR;

HYPOTHESIS TESTING; MOLECULAR ANALYSIS; NUMERICAL MODEL; PHENOTYPE;

ARTICLE; CELL COMPONENT; CELL INTERACTION; COMORBIDITY; DISEASE ASSOCIATION; ENZYME METABOLISM; GENE EXPRESSION; GENE LOCATION; GENE MAPPING; GENE ONTOLOGY; GENETIC ASSOCIATION; GENETIC RISK; GENETIC VARIABILITY; HUMAN; INTERACTOME; METABOLISM; MOLECULAR GENETICS; MOLECULAR INTERACTION; MOLECULAR PATHOLOGY; MULTIPLE SCLEROSIS; NONSENSE MUTATION; OVERLAPPING GENE; PHENOTYPIC VARIATION; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN DNA INTERACTION; PROTEIN INTERACTION; PROTEIN PROTEIN INTERACTION; RISK FACTOR; DISEASE; GENETIC PREDISPOSITION; GENETICS; INFORMATION SERVICE;

COMORBIDITY; DISEASE; GENETIC PREDISPOSITION TO DISEASE; HUMANS; INFORMATION SERVICES; PROTEIN INTERACTION MAPS;

EID: 84923306828     PISSN: 00368075     EISSN: 10959203     Source Type: Journal    
DOI: 10.1126/science.1257601     Document Type: Article

References (50)

1. M. Buchanan, G. Caldarelli, P. De Los Rios, Networks in Cell Biology (Cambridge Univ. Press, Cambridge, 2010).
2. T. Pawson, R. Linding, Network medicine. FEBS Lett. 582, 1266-1270 (2008). doi: 10.1016/j.febslet.2008.02.011; pmid: 18282479
3. E. E. Schadt, Molecular networks as sensors and drivers of common human diseases. Nature 461, 218-223 (2009). doi: 10.1038/nature08454; pmid: 19741703
4. A. Califano, A. J. Butte, S. Friend, T. Ideker, E. Schadt, Leveraging models of cell regulation and GWAS data in integrative network-based association studies. Nat. Genet. 44, 841-847 (2012). doi: 10.1038/ng.2355; pmid: 22836096
5. A. Zanzoni, M. Soler-López, P. Aloy, A network medicine approach to human disease. FEBS Lett. 583, 1759-1765 (2009). doi: 10.1016/j.febslet.2009.03.001; pmid: 19269289
6. A.-L. Barabási, N. Gulbahce, J. Loscalzo, Network medicine: A network-based approach to human disease. Nat. Rev. Genet. 12, 56-68 (2011). doi: 10.1038/nrg2918; pmid: 21164525
7. K.-I. Goh et al., The human disease network. Proc. Natl. Acad. Sci. U. S. A. 104, 8685-8690 (2007). doi: 10.1073/pnas.0701361104; pmid: 17502601
8. M. Oti, B. Snel, M. A. Huynen, H. G. Brunner, Predicting disease genes using protein-protein interactions. J. Med. Genet. 43, 691-698 (2006). doi: 10.1136/jmg.2006.041376; pmid: 16611749
9. K. Lage et al., Dissecting spatio-temporal protein networks driving human heart development and related disorders. Mol. Syst. Biol. 6, 381 (2010). doi: 10.1038/msb.2010.36; pmid: 20571530
10. H.-Y. Chuang, E. Lee, Y.-T. Liu, D. Lee, T. Ideker, Network-based classification of breast cancer metastasis. Mol. Syst. Biol. 3, 140 (2007). doi: 10.1038/msb4100180; pmid: 17940530
11. R. Mosca, T. Pons, A. Céol, A. Valencia, P. Aloy, Towards a detailed atlas of protein-protein interactions. Curr. Opin. Struct. Biol. 23, 929-940 (2013). doi: 10.1016/j.sbi.2013.07.005; pmid: 23896349
12. T. Rolland et al., A proteome-scale map of the human interactome network. Cell 159, 1212-1226 (2014). doi: 10.1016/j.cell.2014.10.050; pmid: 25416956
13. G. T. Hart, A. K. Ramani, E. M. Marcotte, How complete are current yeast and human protein-interaction networks? Genome Biol. 7, 120 (2006). doi: 10.1186/gb-2006-7-11-120; pmid: 17147767
14. K. Venkatesan et al., An empirical framework for binary interactome mapping. Nat. Methods 6, 83-90 (2009). pmid: 19060904
15. M. P. Stumpf et al., Estimating the size of the human interactome. Proc. Natl. Acad. Sci. U. S. A. 105, 6959-6964 (2008). doi: 10.1073/pnas.0708078105; pmid: 18474861
16. M. N. Wass, A. David, M. J. Sternberg, Challenges for the prediction of macromolecular interactions. Curr. Opin. Struct. Biol. 21, 382-390 (2011). doi: 10.1016/j.sbi.2011.03.013; pmid: 21497504
17. J. Xu, Y. Li, Discovering disease-genes by topological features in human protein-protein interaction network. Bioinformatics 22, 2800-2805 (2006). doi: 10.1093/bioinformatics/btl467; pmid: 16954137
18. I. Feldman, A. Rzhetsky, D. Vitkup, Network properties of genes harboring inherited disease mutations. Proc. Natl. Acad. Sci. U. S. A. 105, 4323-4328 (2008). doi: 10.1073/pnas.0701722105; pmid: 18326631
19. M. Krauthammer, C. A. Kaufmann, T. C. Gilliam, A. Rzhetsky, Molecular triangulation: Bridging linkage and molecular-network information for identifying candidate genes in Alzheimer's disease. Proc. Natl. Acad. Sci. U. S. A. 101, 15148-15153 (2004). doi: 10.1073/pnas.0404315101; pmid: 15471992
20. L. Franke et al., Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. Am. J. Hum. Genet. 78, 1011-1025 (2006). doi: 10.1086/504300; pmid: 16685651
21. S. Köhler, S. Bauer, D. Horn, P. N. Robinson, Walking the interactome for prioritization of candidate disease genes. Am. J. Hum. Genet. 82, 949-958 (2008). doi: 10.1016/j.ajhg.2008.02.013; pmid: 18371930
22. Y. Chen et al., Variations in DNA elucidate molecular networks that cause disease. Nature 452, 429-435 (2008). doi: 10.1038/nature06757; pmid: 18344982
23. S. E. Baranzini et al., Pathway and network-based analysis of genome-wide association studies in multiple sclerosis. Hum. Mol. Genet. 18, 2078-2090 (2009). doi: 10.1093/hmg/ddp120; pmid: 19286671
24. C. E. Wheelock et al., Systems biology approaches and pathway tools for investigating cardiovascular disease. Mol. Biosyst. 5, 588-602 (2009). doi: 10.1039/b902356a; pmid: 19462016
25. A. S. Khalil, J. J. Collins, Synthetic biology: Applications come of age. Nat. Rev. Genet. 11, 367-379 (2010). doi: 10.1038/nrg2775; pmid: 20395970
26. S. Wuchty et al., Gene pathways and subnetworks distinguish between major glioma subtypes and elucidate potential underlying biology. J. Biomed. Inform. 43, 945-952 (2010). doi: 10.1016/j.jbi.2010.08.011; pmid: 20828632
27. I. Lee, U. M. Blom, P. I. Wang, J. E. Shim, E. M. Marcotte, Prioritizing candidate disease genes by network-based boosting of genome-wide association data. Genome Res. 21, 1109-1121 (2011). doi: 10.1101/gr.118992.110; pmid: 21536720
28. U. M. Singh-Blom et al., Prediction and validation of genedisease associations using methods inspired by social network analyses. PLOS ONE 8, e58977 (2013). doi: 10.1371/journal. pone.0058977; pmid: 23650495
29. A. Rzhetsky, D. Wajngurt, N. Park, T. Zheng, Probing genetic overlap among complex human phenotypes. Proc. Natl. Acad. Sci. U. S. A. 104, 11694-11699 (2007). doi: 10.1073/pnas.0704820104; pmid: 17609372
30. A. Mottaz, Y. L. Yip, P. Ruch, A.-L. Veuthey, Mapping proteins to disease terminologies: From UniProt to MeSH. BMC Bioinformatics 9(suppl. 5), S3 (2008). doi: 10.1186/1471-2105-9-S5-S3; pmid: 18460185
31. E. M. Ramos et al., Phenotype-Genotype Integrator (PheGenI): Synthesizing genome-wide association study (GWAS) data with existing genomic resources. Eur. J. Hum. Genet. 22, 144-147 (2014). doi: 10.1038/ejhg.2013.96; pmid: 23695286
32. L. Hakes, J. W. Pinney, D. L. Robertson, S. C. Lovell, Protein-protein interaction networks and biology-What's the connection? Nat. Biotechnol. 26, 69-72 (2008). doi: 10.1038/nbt0108-69
33. M. E. Cusick et al., Literature-curated protein interaction datasets. Nat. Methods 6, 39-46 (2009). doi: 10.1038/nmeth.1284; pmid: 19116613
34. R. Cohen, S. Havlin, Complex Networks. Structure, Robustness and Function (Cambridge Univ., Cambridge, 2010).
35. S. Bornholdt, H. G. Schuster, Eds., Handbook of Graphs and Networks (Wiley Online Library, 2003), vol. 2.
36. A. I. Su et al., A gene atlas of the mouse and human protein-encoding transcriptomes. Proc. Natl. Acad. Sci. U. S. A. 101, 6062-6067 (2004). doi: 10.1073/pnas.0400782101; pmid: 15075390
37. T. K. Gandhi et al., Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets. Nat. Genet. 38, 285-293 (2006). pmid: 16501559
38. X. Zhou, J. Menche, A.-L. Barabási, A. Sharma, Human symptoms-disease network. Nat. Commun. 5, 4212 (2014). doi: 10.1038/ncomms5212; pmid: 24967666
39. C. A. Hidalgo, N. Blumm, A.-L. Barabási, N. A. Christakis, A dynamic network approach for the study of human phenotypes. PLOS Comput. Biol. 5, e1000353 (2009). doi: 10.1371/journal.pcbi.1000353; pmid: 19360091
40. K. A. Hunt et al., Newly identified genetic risk variants for celiac disease related to the immune response. Nat. Genet. 40, 395-402 (2008). doi: 10.1038/ng.102; pmid: 18311140
41. D. A. van der Windt, P. Jellema, C. J. Mulder, C. M. Kneepkens, H. E. van der Horst, Diagnostic testing for celiac disease among patients with abdominal symptoms: A systematic review. JAMA 303, 1738-1746 (2010). doi: 10.1001/jama.2010.549; pmid: 20442390
42. C. Pilette, S. R. Durham, J.-P. Vaerman, Y. Sibille, Mucosal immunity in asthma and chronic obstructive pulmonary disease: A role for immunoglobulin A? Proc. Am. Thorac. Soc. 1, 125-135 (2004). doi: 10.1513/pats.2306032
43. J. Shi et al., Role of SWI/SNF in acute leukemia maintenance and enhancer-mediated Myc regulation. Genes Dev. 27, 2648-2662 (2013). doi: 10.1101/gad.232710.113; pmid: 24285714
44. A. Bauer, B. Perras, S. Sufke, H.-P. Horny, B. Kreft, Myocardial infarction as an uncommon clinical manifestation of intravascular large cell lymphoma. Acta Cardiol. 60, 551-555 (2005). doi: 10.2143/AC.60.5.2004979; pmid: 16261789
45. A. L. Hopkins, Network pharmacology: The next paradigm in drug discovery. Nat. Chem. Biol. 4, 682-690 (2008). doi: 10.1038/nchembio.118; pmid: 18936753
46. J. Mestres, E. Gregori-Puigjané, S. Valverde, R. V. Solé, The topology of drug-target interaction networks: Implicit dependence on drug properties and target families. Mol. Biosyst. 5, 1051-1057 (2009). doi: 10.1039/b905821b; pmid: 19668871
47. M. Kuhn et al., Systematic identification of proteins that elicit drug side effects. Mol. Syst. Biol. 9, 663 (2013). doi: 10.1038/msb.2013.10; pmid: 23632385
48. A. Hamosh, A. F. Scott, J. S. Amberger, C. A. Bocchini, V. A. McKusick, Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 33, D514-D517 (2005). doi: 10.1093/nar/gki033; pmid: 15608251
49. M. Ashburner et al. The Gene Ontology Consortium, Gene ontology: Tool for the unification of biology. Nat. Genet. 25, 25-29 (2000). doi: 10.1038/75556; pmid: 10802651
50. A. Subramanian et al., Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. U. S. A. 102, 15545-15550 (2005). doi: 10.1073/pnas.0506580102 pmid: 16199517