Predicting the potential ankylosing spondylitis-related genes utilizing bioinformatics approaches

Rheumatology International

Volumn 35, Issue 6, 2015, Pages 973-979

  Zhao, Hao ^a,b   Wang, Dan ^c   Fu, Deyu ^c   Xue, Luan ^c  

^a Guanghua Integrative Medicine Hospital   (China)

^b Institute of Arthritis Research Shanghai Academy of Chinese Medical Sciences   (China)

^c SHANGHAI UNIVERSITY OF TRADITIONAL CHINESE MEDICINE   (China)

Author keywords

Ankylosing spondylitis; Differentially expressed gene; Functional analysis; MicroRNA; Protein protein interaction network

Indexed keywords

ADENOSYLMETHIONINE DECARBOXYLASE 1; AP2 ASSOCIATED KINASE 1; B CELL CLL LYMPHOMA 11B; BIOLOGICAL MARKER; C TYPE LECTIN DOMAIN FAMILY 4, MEMBER D; CDGSH IRON SULFUR DOMAIN 2; CHEMOKINE RECEPTOR CX3CR1; COILED COIL DOMAIN CONTAINING 72; COMM DOMAIN CONTAINING 6; E1A ASSOCIATED P300 PROTEIN; G PROTEIN COUPLED RECEPTOR 56; INTERLEUKIN 17 RECEPTOR; INTERLEUKIN 17 RECEPTOR C; INTERLEUKIN 17 RECEPTOR D; INTERLEUKIN 2 RECEPTOR BETA; IRON SULFUR PROTEIN; MICRORNA; MITOCHONDRIAL RIBOSOMAL PROTEIN L22; PROTEASOME SUBUNIT ALPHA TYPE 6; REDUCED NICOTINAMIDE ADENINE DINUCLEOTIDE DEHYDROGENASE; RIBOSOME PROTEIN; RIBOSOME PROTEIN 17; TUMOR NECROSIS FACTOR RELATED APOPTOSIS INDUCING LIGAND; UNCLASSIFIED DRUG; GENETIC MARKER;

ANKYLOSING SPONDYLITIS; ARTICLE; BIOINFORMATICS; CLINICAL ARTICLE; CLUSTER ANALYSIS; CONTROLLED STUDY; DOWN REGULATION; GENE EXPRESSION; GENE EXPRESSION REGULATION; GENE IDENTIFICATION; HUMAN; OXIDATIVE PHOSPHORYLATION; PRIORITY JOURNAL; PROTEIN DOMAIN; PROTEIN PHOSPHORYLATION; PROTEIN PROTEIN INTERACTION; UPREGULATION; BIOLOGY; CASE CONTROL STUDY; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETIC ASSOCIATION STUDY; GENETIC DATABASE; GENETIC MARKER; GENETIC PREDISPOSITION; GENETIC SCREENING; GENETICS; PHENOTYPE; PREDICTIVE VALUE; PROCEDURES; PROGNOSIS; SIGNAL TRANSDUCTION; SPONDYLITIS, ANKYLOSING;

CASE-CONTROL STUDIES; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORKS; GENETIC ASSOCIATION STUDIES; GENETIC MARKERS; GENETIC PREDISPOSITION TO DISEASE; GENETIC TESTING; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PHENOTYPE; PREDICTIVE VALUE OF TESTS; PROGNOSIS; SIGNAL TRANSDUCTION; SPONDYLITIS, ANKYLOSING;

EID: 84939418064     PISSN: 01728172     EISSN: 1437160X     Source Type: Journal    
DOI: 10.1007/s00296-014-3178-9     Document Type: Article

References (41)

1. Braun J, Sieper J (2007) Ankylosing spondylitis. Lancet 369(9570):1379–1390
2. Reveille JD, Sims A-M, Danoy P, Evans DM, Leo P, Pointon JJ, Jin R, Zhou X, Bradbury LA, Appleton LH (2010) Genome-wide association study of ankylosing spondylitis identifies non-MHC susceptibility loci. Nat Genet 42(2):123
3. Machado P, Landewé R, Lie E, Kvien TK, Braun J, Baker D, van der Heijde D (2011) Ankylosing spondylitis disease activity score (ASDAS): defining cut-off values for disease activity states and improvement scores. Ann Rheum Dis 70(1):47–53
4. Yekta S, I-h Shih, Bartel DP (2004) MicroRNA-directed cleavage of HOXB8 mRNA. Science 304(5670):594–596
5. Chatzikyriakidou A, Voulgari P, Georgiou I, Drosos A (2010) The role of microRNA-146a (miR-146a) and its target IL-1R-associated kinase (IRAK1) in psoriatic arthritis susceptibility. Scand J Immunol 71(5):382–385
6. Thomas GP, Brown MA (2010) Genetics and genomics of ankylosing spondylitis. Immunol Rev 233(1):162–180
7. Taurog JD (2009) Animal models of spondyloarthritis. Molecular mechanisms of spondyloarthropathies. Springer, Heidelberg, pp 245–254
8. Díaz-Peña R, Aransay AM, Bruges-Armas J, López-Vázquez A, Rodríguez-Ezpeleta N, Mendibil I, Sánchez A, Torre-Alonso JC, Bettencourt BF, Mulero J (2011) Fine mapping of a major histocompatibility complex in ankylosing spondylitis: association of the HLA-DPA1 and HLA-DPB1 regions. Arthritis Rheum 63(11):3305–3312
9. Haroon N, Tsui FW, Uchanska-Ziegler B, Ziegler A, Inman RD (2012) Endoplasmic reticulum aminopeptidase 1 (ERAP1) exhibits functionally significant interaction with HLA-B27 and relates to subtype specificity in ankylosing spondylitis. Ann Rheum Dis 71(4):589–595
10. Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C, Kim IF, Soboleva A, Tomashevsky M, Edgar R (2007) NCBI GEO: mining tens of millions of expression profiles—database and tools update. Nucleic Acids Res 35(Suppl 1):D760–D765
11. Pimentel-Santos FM, Ligeiro D, Matos M, Mourão AF, Costa J, Santos H, Barcelos A, Godinho F, Pinto P, Cruz M (2011) Whole blood transcriptional profiling in ankylosing spondylitis identifies novel candidate genes that might contribute to the inflammatory and tissue-destructive disease aspects. Arthritis Res Ther 13(2):R57
12. Diboun I, Wernisch L, Orengo C, Koltzenburg M (2006) Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma. BMC Genom 7(1):252
13. Efron B, Tibshirani R (2002) Empirical Bayes methods and false discovery rates for microarrays. Genet Epidemiol 23(1):70–86
14. Alvord G, Roayaei J, Stephens R, Baseler MW, Lane HC, Lempicki RA (2007) The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol 8:R183
15. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT (2000) Gene ontology: tool for the unification of biology. Nat Genet 25(1):25–29
16. John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS (2004) Human microRNA targets. PLoS Biol 2(11):e363
17. Wang X (2008) miRDB: a microRNA target prediction and functional annotation database with a wiki interface. RNA 14(6):1012–1017
18. Dweep H, Sticht C, Pandey P, Gretz N (2011) miRWalk–database: prediction of possible miRNA binding sites by “walking” the genes of three genomes. J Biomed Inform 44(5):839–847
19. Loher P, Rigoutsos I (2012) Interactive exploration of RNA22 microRNA target predictions. Bioinformatics 28(24):3322–3323
20. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120(1):15–20
21. Von Mering C, Huynen M, Jaeggi D, Schmidt S, Bork P, Snel B (2003) STRING: a database of predicted functional associations between proteins. Nucleic Acids Res 31(1):258–261
22. Smoot ME, Ono K, Ruscheinski J, Wang P-L, Ideker T (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27(3):431–432
23. Nepusz T, Yu H, Paccanaro A (2012) Detecting overlapping protein complexes in protein–protein interaction networks. Nat Methods 9(5):471–472
24. Apweiler R, Attwood TK, Bairoch A, Bateman A, Birney E, Biswas M, Bucher P, Cerutti L, Corpet F, Croning MDR (2001) The InterPro database, an integrated documentation resource for protein families, domains and functional sites. Nucleic Acids Res 29(1):37–40
25. Anderson JJ, Baron G, Van Der Heijde D, Felson DT, Dougados M (2001) Ankylosing spondylitis assessment group preliminary definition of short-term improvement in ankylosing spondylitis. Arthritis Rheum 44(8):1876–1886
26. Zai-Xing Y, Yan L, Hao W, Ye Z, Chang L, Ren-Qian Z (2008) Preliminary clinical measurement of the expression of TNF-related apoptosis inducing ligand in patients with ankylosing spondylitis. J Clin Lab Anal 22(2):138–145
27. Ciccia F, Accardo-Palumbo A, Giardina A, Di Maggio P, Principato A, Bombardieri M, Rizzo A, Alessandro R, Ferrante A, Principe S (2010) Expansion of intestinal CD4+ CD25 high Treg cells in patients with ankylosing spondylitis: a putative role for interleukin-10 in preventing intestinal Th17 response. Arthritis Rheum 62(12):3625–3634
28. Shaw J, Kollnberger S (2012) New perspectives on the ligands and function of the killer cell immunoglobulin-like receptor KIR3DL2 in health and disease. Front Immunol 3:339
29. DiMauro S, Schon EA (2008) Mitochondrial disorders in the nervous system. Annu Rev Neurosci 31:91–123
30. Wendling D, Didier J, Vuitton D (1991) The phagocyte oxidative metabolism function in ankylosing spondylitis. Rheumatol Int 11(4–5):187–189
31. Smolock EM, Korshunov VA, Glazko G, Qiu X, Gerloff J, Berk BC (2012) Ribosomal protein L17, RpL17, is an inhibitor of vascular smooth muscle growth and carotid intima formation. Circulation 126(20):2418–2427
32. Cmejla R, Cmejlova J, Handrkova H, Petrak J, Pospisilova D (2007) Ribosomal protein S17 gene (RPS17) is mutated in Diamond–Blackfan anemia. Hum Mutat 28(12):1178–1182
33. Mees ST, Mardin WA, Wendel C, Baeumer N, Willscher E, Senninger N, Schleicher C, Colombo-Benkmann M, Haier J (2010) EP300—A miRNA-regulated metastasis suppressor gene in ductal adenocarcinomas of the pancreas. Int J Cancer 126(1):114–124
34. Yu F, Cui Y, Zhou X, Zhang X, Han J (2011) Osteogenic differentiation of human ligament fibroblasts induced by conditioned medium of osteoclast-like cells. Biosci Trends 5(2):46
35. Graham LM, Gupta V, Schafer G, Reid DM, Kimberg M, Dennehy KM, Hornsell WG, Guler R, Campanero-Rhodes MA, Palma AS (2012) The C-type lectin receptor CLECSF8 (CLEC4D) is expressed by myeloid cells and triggers cellular activation through Syk kinase. J Biol Chem 287(31):25964–25974
36. Cismasiu VB, Ghanta S, Duque J, Albu DI, Chen H-M, Kasturi R, Avram D (2006) BCL11B participates in the activation of IL2 gene expression in CD4+ T lymphocytes. Blood 108(8):2695–2702
37. Wright C, Edelmann M, Kollnberger S, Kramer H, McGowan S, McHugh K, Taylor S, Kessler B, Bowness P (2009) Ankylosing spondylitis monocytes show upregulation of proteins involved in inflammation and the ubiquitin proteasome pathway. Ann Rheum Dis 68(10):1626–1632
38. Aldea G, Výprachtický D, Cimrová V (2004) Modification of poly (styrene-alt-maleic anhydride) with 1,3,4-oxadiazole units for electroluminescent devices. Macromolecular symposia. Wiley, Hoboken, pp 523–528
39. Haroon N, Maksymowych WP, Rahman P, Tsui FW, O’Shea FD, Inman RD (2012) Radiographic severity of ankylosing spondylitis is associated with polymorphism of the large multifunctional peptidase 2 gene in the spondyloarthritis research consortium of Canada cohort. Arthritis Rheum 64(4):1119–1126
40. van Endert P (2011) Post-proteasomal and proteasome-independent generation of MHC class I ligands. Cell Mol Life Sci 68(9):1553–1567
41. Parkes M, Cortes A, van Heel DA, Brown MA (2013) Genetic insights into common pathways and complex relationships among immune-mediated diseases. Nat Rev Genet 14(9):661–673