Inter-tissue coexpression network analysis reveals DPP4 as an important gene in heart to blood communication

Genome Medicine

Volumn 8, Issue 1, 2016, Pages

  Long, Quan ^a   Argmann, Carmen ^a   Houten, Sander M ^a   Huang, Tao ^a   Peng, Siwu ^a   Zhao, Yong ^a   Tu, Zhidong ^a   Zhu, Jun ^a  

^a MOUNT SINAI SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIPEPTIDYL PEPTIDASE IV; FOCAL ADHESION KINASE; DPP4 PROTEIN, HUMAN; FOCAD PROTEIN, HUMAN; TUMOR SUPPRESSOR PROTEIN;

ARTICLE; BLOOD; CONTROLLED STUDY; DPP4 GENE; FOCAD GENE; GENE ACTIVITY; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE FUNCTION; GENETIC ANALYSIS; HEART; HUMAN; HUMAN TISSUE; MOLECULAR INTERACTION; PRIORITY JOURNAL; PROTEIN SYNTHESIS; QUANTITATIVE TRAIT LOCUS; RNA SEQUENCE; SIGNAL TRANSDUCTION; TISSUE DISTRIBUTION; TISSUE INTERACTION; ALGORITHM; ANTIBODY SPECIFICITY; BIOLOGY; BLOOD CELL; CARDIAC MUSCLE; CELL PROLIFERATION; CYTOLOGY; GENE EXPRESSION REGULATION; GENETICS; LUNG; METABOLISM; PROCEDURES; SEQUENCE ANALYSIS;

ALGORITHMS; BLOOD CELLS; CELL PROLIFERATION; COMPUTATIONAL BIOLOGY; DIPEPTIDYL PEPTIDASE 4; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; HUMANS; LUNG; MYOCARDIUM; ORGAN SPECIFICITY; SEQUENCE ANALYSIS, RNA; TISSUE DISTRIBUTION; TUMOR SUPPRESSOR PROTEINS;

EID: 84958110601     PISSN: None     EISSN: 1756994X     Source Type: Journal    
DOI: 10.1186/s13073-016-0268-1     Document Type: Article

References (57)

1. Zhu J, Zhang B, Smith EN, Drees B, Brem RB, Kruglyak L, et al. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nat Genet. 2008;40(7):854-61.
2. Gerstein MB, Kundaje A, Hariharan M, Landt SG, Yan KK, Cheng C, et al. Architecture of the human regulatory network derived from ENCODE data. Nature. 2012;489(7414):91-100.
3. Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A. Reverse engineering of regulatory networks in human B cells. Nat Genet. 2005;37(4):382-90.
4. Dobrin R, Zhu J, Molony C, Argman C, Parrish ML, Carlson S, et al. Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease. Genome Biol. 2009;10(5):R55.
5. GTEX consortium. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348(6235):648-60.
6. The GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45(6):580-5.
7. Gagneur J, Stegle O, Zhu C, Jakob P, Tekkedil MM, Aiyar RS, et al. Genotype-environment interactions reveal causal pathways that mediate genetic effects on phenotype. PLoS Genet. 2013;9(9):e1003803.
8. Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol. 2005;4:Article17.
9. Chen Y, Zhu J, Lum PY, Yang X, Pinto S, MacNeil DJ, et al. Variations in DNA elucidate molecular networks that cause disease. Nature. 2008;452(7186):429-35.
10. Emilsson V, Thorleifsson G, Zhang B, Leonardson AS, Zink F, Zhu J, et al. Genetics of gene expression and its effect on disease. Nature. 2008;452(7186):423-8.
11. Mele M, Ferreira PG, Reverter F, DeLuca DS, Monlong J, Sammeth M, et al. Human genomics. The human transcriptome across tissues and individuals. Science. 2015;348(6235):660-5.
12. Kang HM, Ye C, Eskin E. Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots. Genetics. 2008;180(4):1909-25.
13. Stegle O, Parts L, Piipari M, Winn J, Durbin R. Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses. Nat Protoc. 2012;7(3):500-7.
14. Lippert C, Listgarten J, Liu Y, Kadie CM, Davidson RI, Heckerman D. FaST linear mixed models for genome-wide association studies. Nat Methods. 2011;8(10):833-5.
15. Long Q, Zhang Q, Vilhjalmsson BJ, Forai P, Seren U, Nordborg M. JAWAMix5: an out-of-core HDF5-based java implementation of whole-genome association studies using mixed models. Bioinformatics. 2013;29(9):1220-2.
16. Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, et al. Variance component model to account for sample structure in genome-wide association studies. Nat Genet. 2010;42(4):348-54.
17. Dhillon IS. Coclustering documents and words using Bipartite Spectral Graph Partitioning. In: Kdd-2001: Proceedings of the seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining: San Francisco, Ca, USA. August 26-29, 2001:269-274.
18. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5(10):R80.
19. Liberzon A, Subramanian A, Pinchback R, Thorvaldsdottir H, Tamayo P, Mesirov JP. Molecular signatures database (MSigDB) 3.0. Bioinformatics. 2011;27(12):1739-40.
20. Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, et al. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A. 2004;101(16):6062-7.
21. Korte A, Farlow A. The advantages and limitations of trait analysis with GWAS: a review. Plant Methods. 2013;9:29.
22. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42(7):565-9.
23. Yang J, Zaitlen NA, Goddard ME, Visscher PM, Price AL. Advantages and pitfalls in the application of mixed-model association methods. Nat Genet. 2014;46(2):100-6.
24. Segura V, Vilhjalmsson BJ, Platt A, Korte A, Seren U, Long Q, et al. An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations. Nat Genet. 2012;44(7):825-30.
25. Szigeti A, Bellyei S, Gasz B, Boronkai A, Hocsak E, Minik O, et al. Induction of necrotic cell death and mitochondrial permeabilization by heme binding protein 2/SOUL. FEBS Lett. 2006;580(27):6447-54.
26. Miljkovic-Licina M, Hammel P, Garrido-Urbani S, Bradfield PF, Szepetowski P, Imhof BA. Sushi repeat protein X-linked 2, a novel mediator of angiogenesis. FASEB J. 2009;23(12):4105-16.
27. Roll P, Rudolf G, Pereira S, Royer B, Scheffer IE, Massacrier A, et al. SRPX2 mutations in disorders of language cortex and cognition. Hum Mol Genet. 2006;15(7):1195-207.
28. Sia GM, Clem RL, Huganir RL. The human language-associated gene SRPX2 regulates synapse formation and vocalization in mice. Science. 2013;342(6161):987-91.
29. Benita Y, Cao Z, Giallourakis C, Li C, Gardet A, Xavier RJ. Gene enrichment profiles reveal T-cell development, differentiation, and lineage-specific transcription factors including ZBTB25 as a novel NF-AT repressor. Blood. 2010;115(26):5376-84.
30. Zhong J, Rao X, Rajagopalan S. An emerging role of dipeptidyl peptidase 4 (DPP4) beyond glucose control: potential implications in cardiovascular disease. Atherosclerosis. 2013;226(2):305-14.
31. Röhrborn D, Eckel J, Sell H. Shedding of dipeptidyl peptidase 4 is mediated by metalloproteases and up-regulated by hypoxia in human adipocytes and smooth muscle cells. FEBS Lett. 2014;588(21):3870-7.
32. Durinx C, Lambeir AM, Bosmans E, Falmagne JB, Berghmans R, Haemers A, et al. Molecular characterization of dipeptidyl peptidase activity in serum: soluble CD26/dipeptidyl peptidase IV is responsible for the release of X-Pro dipeptides. Eur J Biochem. 2000;267(17):5608-13.
33. Zhong J, Rajagopalan S. Dipeptidyl peptidase-4 regulation of SDF-1/CXCR4 axis: implications for cardiovascular disease. Front Immunol. 2015;6:477.
34. Fadini GP, Avogaro A. Dipeptidyl peptidase-4 inhibition and vascular repair by mobilization of endogenous stem cells in diabetes and beyond. Atherosclerosis. 2013;229(1):23-9.
35. Pala L, Rotella CM. The role of DPP4 activity in cardiovascular districts: in vivo and in vitro evidence. J Diabetes Res. 2013;2013:590456.
36. Ou X, O'Leary HA, Broxmeyer HE. Implications of DPP4 modification of proteins that regulate stem/progenitor and more mature cell types. Blood. 2013;122(2):161-9.
37. Christopherson 2nd KW, Hangoc G, Mantel CR, Broxmeyer HE. Modulation of hematopoietic stem cell homing and engraftment by CD26. Science. 2004;305(5686):1000-3.
38. Berahovich RD, Zabel BA, Lewen S, Walters MJ, Ebsworth K, Wang Y, et al. Endothelial expression of CXCR7 and the regulation of systemic CXCL12 levels. Immunology. 2013;141(1):111-22.
39. Shigeta T, Aoyama M, Bando YK, Monji A, Mitsui T, Takatsu M, et al. Dipeptidyl peptidase-4 modulates left ventricular dysfunction in chronic heart failure via angiogenesis-dependent and -independent actions. Circulation. 2012;126(15):1838-51.
40. Chen Q, Zhang M, Li Y, Xu D, Wang Y, Song A, et al. CXCR7 mediates neural progenitor cells migration to CXCL12 independent of CXCR4. Stem Cells. 2015;33(8):2574-85.
41. Brockschmidt A, Trost D, Peterziel H, Zimmermann K, Ehrler M, Grassmann H, et al. KIAA1797/FOCAD encodes a novel focal adhesion protein with tumour suppressor function in gliomas. Brain. 2012;135(Pt 4):1027-41.
42. Weren RD, Venkatachalam R, Cazier JB, Farin HF, Kets CM, de Voer RM, et al. Germline deletions in the tumour suppressor gene FOCAD are associated with polyposis and colorectal cancer development. J Pathol. 2015;236(2):155-64.
43. Horpaopan S, Spier I, Zink AM, Altmuller J, Holzapfel S, Laner A, et al. Genome-wide CNV analysis in 221 unrelated patients and targeted high-throughput sequencing reveal novel causative candidate genes for colorectal adenomatous polyposis. Int J Cancer. 2015;136(6):E578-89.
44. de Hoog CL, Foster LJ, Mann M. RNA and RNA binding proteins participate in early stages of cell spreading through spreading initiation centers. Cell. 2004;117(5):649-62.
45. Manso AM, Kang SM, Ross RS. Integrins, focal adhesions, and cardiac fibroblasts. J Investig Med. 2009;57(8):856-60.
46. Shattil SJ, Kim C, Ginsberg MH. The final steps of integrin activation: the end game. Nat Rev Mol Cell Biol. 2010;11(4):288-300.
47. Malenfant S, Neyron AS, Paulin R, Potus F, Meloche J, Provencher S, et al. Signal transduction in the development of pulmonary arterial hypertension. Pulm Circ. 2013;3(2):278-93.
48. Olson TP, Beck KC, Johnson BD. Pulmonary function changes associated with cardiomegaly in chronic heart failure. J Card Fail. 2007;13(2):100-7.
49. Melton PE, Rutherford S, Voruganti VS, Goring HH, Laston S, Haack K, et al. Bivariate genetic association of KIAA1797 with heart rate in American Indians: the Strong Heart Family Study. Hum Mol Genet. 2010;19(18):3662-71.
50. STAMPEED: http://www.ncbi.nlm.nih.gov/gap/phegeni?tab=1&gene=54914#pgGAP. Accessed date: April 20,2015.
51. Wilk JB, Walter RE, Laramie JM, Gottlieb DJ, O'Connor GT. Framingham Heart Study genome-wide association: results for pulmonary function measures. BMC Med Genet. 2007;8 Suppl 1:S8.
52. Krackhardt AM, Witzens M, Harig S, Hodi FS, Zauls AJ, Chessia M, et al. Identification of tumor-associated antigens in chronic lymphocytic leukemia by SEREX. Blood. 2002;100(6):2123-31.
53. Choy FY, Campbell TN. Gaucher disease and cancer: concept and controversy. Int J Cell Biol. 2011;2011:150450.
54. Dick DM, Aliev F, Krueger RF, Edwards A, Agrawal A, Lynskey M, et al. Genome-wide association study of conduct disorder symptomatology. Mol Psychiatry. 2011;16(8):800-8.
55. Glynn D, Gibson HE, Harte MK, Reim K, Jones S, Reynolds GP, et al. Clorgyline-mediated reversal of neurological deficits in a Complexin 2 knockout mouse. Hum Mol Genet. 2010;19(17):3402-12.
56. Lionel AC, Crosbie J, Barbosa N, Goodale T, Thiruvahindrapuram B, Rickaby J, et al. Rare copy number variation discovery and cross-disorder comparisons identify risk genes for ADHD. Sci Transl Med. 2011;3(95):95ra75.
57. Hass J, Walton E, Kirsten H, Turner J, Wolthusen R, Roessner V, et al. Complexin2 modulates working memory-related neural activity in patients with schizophrenia. Eur Arch Psychiatry Clin Neurosci. 2015;265(2):137-45.