Investigating perturbed pathway modules from gene expression data via structural equation models

BMC Bioinformatics

Volumn 15, Issue 1, 2014, Pages

  Pepe, Daniele ^a   Grassi, Mario ^a  

^a UNIVERSITY OF PAVIA   (Italy)

Author keywords

Model generation; Pathway analysis; Perturbed edges; Perturbed models; Structural equation modeling (SEM)

Indexed keywords

COMPLEX NETWORKS; GENES; STRUCTURAL ANALYSIS;

DIFFERENTIAL EXPRESSIONS; DIFFERENTIAL GENE EXPRESSIONS; DIFFERENTIALLY EXPRESSED GENE; MODEL GENERATION; PATHWAY ANALYSIS; PERTURBED EDGES; STRUCTURAL EQUATION MODELING; STRUCTURAL EQUATION MODELS;

GENE EXPRESSION;

ARTICLE; BIOLOGICAL MODEL; GENE EXPRESSION; GENE EXPRESSION PROFILING; HUMAN; METHODOLOGY; MUTATION; PHENOTYPE; SIGNAL TRANSDUCTION; UBIQUITINATION;

GENE EXPRESSION; GENE EXPRESSION PROFILING; HUMANS; MODELS, GENETIC; MUTATION; PHENOTYPE; SIGNAL TRANSDUCTION; UBIQUITINATION;

EID: 84902274191     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-15-132     Document Type: Article

References (66)

1. Barabási AL, Oltvai ZN. Network biology: understanding the cell's functional organization. Nat Rev Genet 2004, 5:101-113. 10.1038/nrg1272, 14735121.
2. Hartemink AJ. Reverse engineering gene regulatory networks. Nat biotech 2005, 23:554-555.
3. Shipley B. Cause and Correlation in Biology. A User's Guide to Path Analysis, Structural Equations, and Causal Inference 2000, New York: Cambridge University Press.
4. Rosa GJ, Valente BD, de los Campo G, Wu XL, Gianola D, Silva MA. Inferring causal phenotype networks using structural equation models. Gen Select Evol 2011, 43:6.
5. Kim J, Namkung J, Lee S, Park T. Application of structural equation models to genome-wide association analysis. Genomics & Informatics 2010, 8:150-158.
6. Mi X, Eskridge KM, George V, Wang D. Structural equation modeling of gene-environment interactions in coronary heart disease. Ann Hum Genet 2011, 75:255-265.
7. Rao DC, Province MA. The future of path analysis, segregation analysis, and combined models for genetic dissection of complex traits. Hum Hered 1999, 50(1):34-42.
8. Province MA, Rice TK, Borecki IB, Gu C, Kraja A, Rao DC. Multivariate and multilocus variance components method, based on structural relationships to assess quantitative trait linkage via SEGPATH. Genet Epidemiol 2003, 24(2):128-138. 10.1002/gepi.10208, 12548674.
9. Li R, Tsaih SW, Shockley K, Stylianou IM, Wergedal J, Paigen B, Churchill GA. Structural model analysis of multiple quantitative traits. PLoS Genet 2006, 2(7):e114. 10.1371/journal.pgen.0020114, 1513264, 16848643.
10. Xie J, Bentler PM. Covariance structure models for gene expression microarray data. Struct Equ Model 2003, 10:566-582.
11. Xiong M, Li J, Fang X. Identification of genetic networks. Genetics 2004, 166(2):1037-1052. 10.1534/genetics.166.2.1037, 1470757, 15020486.
12. Wu X, Sharpe K, Zhang T, Chen H, Zhu W, Li E, Taghavi S, Van Der Lelie D. Comparative genetic pathway analysis using structural equation modeling. Proceeding of IEEE First International Conference on Computational Advances in Bio and Medical Sciences (ICCABS 2011): 3-5 February 2011; Orlando 2011, 190-195. Washington, DC, USA: IEEE Computer Society.
13. Khatri P, Sirota M, Butte A. Ten years of pathway analysis: current approaches and outstanding challenges. Plos Comp Bio 2012, 8:15-22.
14. Barabási AL, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet 2011, 12:56-68. 10.1038/nrg2918, 3140052, 21164525.
15. Nikolskaya AN, Arighi CN, Huang H, Barker WC, Wu CH. PIRSF family classification system for protein functional and evolutionary analysis. Evol Bioinform Online 2006, 2:197-209.
16. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 2001, 98:5116-5121. 10.1073/pnas.091062498, 33173, 11309499.
17. Tarca AL, Draghici S, Khatri P, Hassan S, Mital P, Kim J, Kim C, Kusanovic JP, Romero R. A novel signaling pathway impact analysis for microarray experiments. Bioinformatics 2009, 25:75-82. 10.1093/bioinformatics/btn577, 2732297, 18990722.
18. Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000, 28(1):27-30. 10.1093/nar/28.1.27, 102409, 10592173.
19. Tibshirani R, Chu G, Balasubramanian N, Jun L. samr: SAM: Significance Analysis of Microarrays. R reference manual: August 29, 2013 [http://cran.r-project.org/web/packages/samr/samr.pdf].
20. Tarca AL, Kathri P, Draghici S. SPIA: Signaling Pathway Impact Analysis (SPIA) using combined evidence of pathway over-representation and unusual signaling perturbations. R reference manual: May 27, 2014 [http://www.bioconductor.org/packages/release/bioc/manuals/SPIA/man/SPIA.pdf].
21. Wright SS. Correlation and causation. J Agric Res 1921, 20:557-585.
22. Bollen KA. Structural Equations with Latent Variables 1989, New York: Wiley.
23. Pearl J. Graphs, causality, and structural equation models. Socio Meth Res 1998, 27:226-284.
24. Csardi G, Nepusz T. igraph: network analysis and visualization. R reference manual: April 22, 2014 [http://cran.r-project.org/web/packages/igraph/igraph.pdf].
25. Rigdon E. A necessary and sufficient identification rule for structural models estimated in practice. Multivar Behav Res 1995, 30:359-383.
26. Brito C, Pearl J. A new identification condition for recursive models with correlated errors. Struct Equ Model 2002, 9:459-474.
27. Grace JB, Bollen KA. Representing general theoretical concepts in structural equation models: the role of composite variables. Environ Ecol Stat 2008, 15:191-213.
28. Sales G, Calura E, Romualdi C. Graphite: GRAPH Interaction from pathway Topological Environment. R reference manual: May 27, 2014, [http://www.bioconductor.org/packages/release/bioc/manuals/graphite/man/graphite.pdf].
29. R Development Core Team: The R Stats package In A Language and Environment for Statistical Computing 2012, Vienna, Austria: R Foundation for Statistical Computing, http://cran.r-project.org/, R Development Core Team: The R Stats package.
30. Bollen KA, Stine RA. Bootstrapping goodness-of-fit measures in structural equation models. Sociol Methods Res 1992, 21:205-229.
31. Browne MW, Cudeck R. Alternative ways of assessing model fit. Sage Focus Editions 1993, 154:136.
32. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling 1999, 6:1-55.
33. Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, Jensen LJ. STRING v9. 1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res 2013, 41(D1):D808-D815. 10.1093/nar/gks1094, 3531103, 23203871.
34. Rosseel Y. lavaan: An R Package for Structural Equation Modeling. J Stat Softw 2012, 48(2):1-36. http://www.jstatsoft.org/v48/i02/.
35. Chen-Plotkin AS, Geser F, Plotkin JB, Clark CM, Kwong LK, Yuan W, Lee VMY. Variations in the progranulin gene affect global gene expression in frontotemporal lobar degeneration. Hum Mol Genet 2008, 17:1349-1362. 10.1093/hmg/ddn023, 2900863, 18223198.
36. Meldrum BS. Glutamate as a neurotransmitter in the brain: review of physiology and pathology. J Nutr 2000, 130(Suppl 4):1007S-1015S.
37. Sheldon AL, Robinson MB. The role of glutamate transporters in neurodegenerative diseases and potential opportunities for intervention. Neurochem Int 2007, 51:333-355. 10.1016/j.neuint.2007.03.012, 2075474, 17517448.
38. Hynd MR, Scott HL, Dodd PR. Glutamate-mediated excitotoxicity and neurodegeneration in Alzheimer's disease. Neurochem Int 2004, 45:583-595. 10.1016/j.neuint.2004.03.007, 15234100.
39. Ferrer I. Neurons and their dendrites in frontotemporal dementia. Dement Geriatr Cogn Disord 1999, 10(Suppl 1):55-60.
40. Ferrer I, Tunon T, Serrano MT, Casas R, Alcantara S, Zujar MJ, Rivera RM. D-28 k and parvalbumin immunoreactivity in the frontal cortex in patients with frontal lobe dementia of non-Alzheimer type associated with amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 1993, 56:257-261. 10.1136/jnnp.56.3.257, 1014857, 8459241.
41. Adriaens ME, Jaillard M, Waagmeester A, Coort SL, Pico AR, Evelo CT. The public road to high-quality curated biological pathways. Drug Discov Today 2008, 13:856-862. 10.1016/j.drudis.2008.06.013, 3646620, 18652912.
42. Gong Y, Lippa CF. Review: disruption of the postsynaptic density in Alzheimer's disease and other neurodegenerative dementias. Am J Alzheimers Dis Other Demen 2010, 25:547-555. 10.1177/1533317510382893, 2976708, 20858652.
43. Rosen EY, Wexler EM, Versano R, Coppola G, Gao F, Winden KD, Geschwind DH. Functional genomic analyses identify pathways dysregulated by progranulin deficiency, implicating Wnt signaling. Neuron 2011, 71:1030-1042. 10.1016/j.neuron.2011.07.021, 3633414, 21943601.
44. Kim E, Sheng M. PDZ domain proteins of synapses. Nat Rev Neurosci 2004, 5:771-781. 10.1038/nrn1517, 15378037.
45. Gong Y, Lippa CF, Zhu J, Lin Q, Rosso AL. Disruption of glutamate receptors at Shank-postsynaptic platform in Alzheimer's disease. Brain Res 2009, 1292:191-198. 2745956, 19635471.
46. van de Leemput J, Chandran J, Knight MA, Holtzclaw LA, Scholz S, Cookson MR, Houlden H, Gwinn-Hardy K, Fung HC, Lin X, Hernandez D, Simon-Sanchez J, Wood NW, Giunti P, Rafferty I, Hardy J, Storey E, Gardner RJ, Forrest SM, Fisher EM, Russell JT, Cai H, Singleton AB. Deletion at ITPR1 underlies ataxia in mice and spinocerebellar ataxia 15 in humans. PLoS Genet 2007, 3:e108. 10.1371/journal.pgen.0030108, 1892049, 17590087.
47. Owens GP, Bennett JL, Gilden DH, Burgoon MP. The B cell response in multiple sclerosis. Neurol Res 2006, 28:236-244. 10.1179/016164106X98099, 16687047.
48. von Büdingen HC, Kuo TC, Sirota M, van Belle CJ, Apeltsin L, Glanville J, Cree BA, Gourraud PA, Schwartzburg A, Huerta G, Telman D, Sundar PD, Casey T, Cox DR, Hauser SL. B cell exchange across the blood-brain barrier in multiple sclerosis. J Clin Investig 2012, 122:4533. 10.1172/JCI63842, 3533544, 23160197.
49. Nimmerjahn F, Ravetch JV. Fcgamma receptors as regulators of immune responses. Nat Rev Immunol 2008, 8:34-47. 10.1038/nri2206, 18064051.
50. Mackay M, Stanevsky A, Wang T, Aranow C, Li M, Koenig S, Diamond B. Selective dysregulation of the FcγIIB receptor on memory B cells in SLE. J Exp Med 2006, 203:2157-2164. 10.1084/jem.20051503, 2118390, 16923849.
51. Tackenberg B, Jelčić I, Baerenwaldt A, Oertel WH, Sommer N, Nimmerjahn F, Lünemann JD. Impaired inhibitory Fcγ receptor IIB expression on B cells in chronic inflammatory demyelinating polyneuropathy. Proc Natl Acad Sci 2009, 106:4788-4792. 10.1073/pnas.0807319106, 2660764, 19261857.
52. Zhu W, London NR, Gibson CC, Davis CT, Tong Z, Sorensen LK, Shi DS, Guo J, Smith MC, Grossmann AH, Thomas KR, Li DY. Interleukin receptor activates a MYD88-ARNO-ARF6 cascade to disrupt vascular stability. Nature 2012, 492:252-255. 10.1038/nature11603, 3521847, 23143332.
53. Mori F, Nisticò R, Mandolesi G, Piccinin S, Mango D, Kusayanagi H, Berretta N, Bergami A, Gentile A, Musella A, Nicoletti CG, Nicoletti F, Buttari F, Mercuri NB, Martino G, Furlan R, Centonze D. Interleukin-1β promotes long-term potentiation in patients with multiple sclerosis. NeuroMolecular Med 2013, Epub ahead of print.
54. Iglesias AH, Camelo S, Hwang D, Villanueva R, Stephanopoulos G, Dangond F. Microarray detection of E2F pathway activation and other targets in multiple sclerosis peripheral blood mononuclear cells. J Neuroimmunol 2004, 150:163-177. 10.1016/j.jneuroim.2004.01.017, 15081262.
55. Gilli F. Role of differential expression of interferon receptor isoforms on the response of multiple sclerosis patients to therapy with interferon beta. J Interf Cytokine Res 2010, 30:733-741.
56. Lamorte L, Rodrigues S, Sangwan V, Turner CE, Park M. Crk associates with a multimolecular Paxillin/GIT2/β-PIX complex and promotes Rac-dependent relocalization of Paxillin to focal contacts. Mol Biol Cell 2003, 14:2818-2831. 10.1091/mbc.E02-08-0497, 165679, 12857867.
57. Di Paolo G, Moskowitz HS, Gipson K, Wenk MR, Voronov S, Obayashi M, Flavell R, Fitzsimonds RM, Ryan TA, De Camilli P. Impaired PtdIns(4,5)P(2) synthesis in nerve terminals produces defects in synaptic vesicle trafficking. Nature 2004, 431:415-422. 10.1038/nature02896, 15386003.
58. Terao C, Ohmura K, Kawaguchi Y, Nishimoto T, Kawasaki A, Takehara K, Mimori T. PLD4 as a novel susceptibility gene for systemic sclerosis in a Japanese population. Arthritis Rheum 2013, 65:472-480. 10.1002/art.37777, 23124809.
59. Wu MC, Zhang L, Wang Z, Christiani DC, Lin X. Sparse linear discriminant analysis for simultaneous testing for the significance of a gene set/pathway and gene selection. Bioinformatics 2009, 25:1145-1151. 10.1093/bioinformatics/btp019, 2732305, 19168911.
60. Kiiveri HT. Multivariate analysis of microarray data: differential expression and differential connection. BMC Bioinforma 2011, 12:42.
61. Edwards D, Wang L, Sørensen P. Network-enabled gene expression analysis. BMC Bioinforma 2012, 13:167.
62. Martini P, Sales G, Massa MS, Chiogna M, Romualdi C. Along signal paths: an empirical gene set approach exploiting pathway topology. Nucl Acids Res 2013, 41:e19. 10.1093/nar/gks866, 3592432, 23002139.
63. Gill R, Datta S, Datta S. A statistical framework for differential network analysis from microarray data. BMC Bioinforma 2010, 11:95.
64. Aburatani S. Application of structure equation modeling for inferring a serial transcriptional regulation in yeast. Gene Regul Syst Bio 2011, 5:75-88. 3236004, 22272062.
65. Kalisch M, Mächler M, Colombo D, Maathuis MH, Bühlmann P. Causal inference using graphical models with the R package pcalg. J Stat Softw 2011, 47:1-26.
66. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. JR Stat Soc Ser B(Methodological) 1995, 57:289-300.