A Bayesian gene network reveals insight into the JAK-STAT pathway in systemic lupus erythematosus
Autoři:
Yupeng Li aff001; Richard E. Higgs aff001; Robert W. Hoffman aff001; Ernst R. Dow aff001; Xiong Liu aff001; Michelle Petri aff002; Daniel J. Wallace aff003; Thomas Dörner aff004; Brian J. Eastwood aff001; Bradley B. Miller aff001; Yushi Liu aff001
Působiště autorů:
Eli Lilly and Company, Indianapolis, Indiana, United States of America
aff001; Hopkins Lupus Center, John Hopkins University, Baltimore, Maryland, United States of America
aff002; David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America
aff003; Charité University Hospitals, Berlin, Germany
aff004
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0225651
Souhrn
Systemic lupus erythematosus (SLE) is a chronic, remitting, and relapsing, inflammatory disease involving multiple organs, which exhibits abnormalities of both the innate and adaptive immune responses. A limited number of transcriptomic studies have characterized the gene pathways involved in SLE in an attempt to identify the key pathogenic drivers of the disease. In order to further advance our understanding of the pathogenesis of SLE, we used a novel Bayesian network algorithm to hybridize knowledge- and data-driven methods, and then applied the algorithm to build an SLE gene network using transcriptomic data from 1,760 SLE patients’ RNA from the two tabalumab Phase III trials (ILLUMINATE-I & -II), the largest SLE RNA dataset to date. Further, based on the gene network, we carried out hub- and key driver-gene analyses for gene prioritization. Our analyses identified that the JAK-STAT pathway genes, including JAK2, STAT1, and STAT2, played essential roles in SLE pathogenesis, and reaffirmed the recent discovery of pathogenic relevance of JAK-STAT signaling in SLE. Additionally, we showed that other genes, such as IRF1, IRF7, PDIA4, FAM72C, TNFSF10, DHX58, SIGLEC1, and PML, may be also important in SLE and serve as potential therapeutic targets for SLE. In summary, using a hybridized network construction approach, we systematically investigated gene-gene interactions based on their transcriptomic profiles, prioritized genes based on their importance in the network structure, and revealed new insights into SLE activity.
Klíčová slova:
Gene expression – Gene regulation – Genetic networks – Interferons – Transcriptome analysis – Gene regulatory networks – JAK-STAT signaling cascade
Zdroje
1. Chen L, Morris DL, Vyse TJ. Genetic advances in systemic lupus erythematosus: an update. Curr Opin Rheumatol. 2017;29(5):423–33. doi: 10.1097/BOR.0000000000000411 28509669.
2. Furie R, Khamashta M, Merrill JT, Werth VP, Kalunian K, Brohawn P, et al. Anifrolumab, an Anti-Interferon-alpha Receptor Monoclonal Antibody, in Moderate-to-Severe Systemic Lupus Erythematosus. Arthritis Rheumatol. 2017;69(2):376–86. Epub 2017/01/29. doi: 10.1002/art.39962 28130918; PubMed Central PMCID: PMC5299497.
3. van Vollenhoven RF, Hahn BH, Tsokos GC, Wagner CL, Lipsky P, Touma Z, et al. Efficacy and safety of ustekinumab, an IL-12 and IL-23 inhibitor, in patients with active systemic lupus erythematosus: results of a multicentre, double-blind, phase 2, randomised, controlled study. Lancet. 2018;392(10155):1330–9. Epub 2018/09/27. doi: 10.1016/S0140-6736(18)32167-6 30249507.
4. Wallace DJ, Furie RA, Tanaka Y, Kalunian KC, Mosca M, Petri MA, et al. Baricitinib for systemic lupus erythematosus: a double-blind, randomised, placebo-controlled, phase 2 trial. Lancet. 2018;392(10143):222–31. doi: 10.1016/S0140-6736(18)31363-1 30043749.
5. A Study of Ustekinumab in Participants With Active Systemic Lupus Erythematosus [cited 2019 06-17-2019]. Available from: https://clinicaltrials.gov/ct2/show/NCT03517722.
6. Mahieu MA, Strand V, Simon LS, Lipsky PE, Ramsey-Goldman R. A critical review of clinical trials in systemic lupus erythematosus. Lupus. 2016;25(10):1122–40. Epub 2016/08/09. doi: 10.1177/0961203316652492 27497257; PubMed Central PMCID: PMC4978143.
7. Hoffman RW, Merrill JT, Alarcon-Riquelme MM, Petri M, Dow ER, Nantz E, et al. Gene Expression and Pharmacodynamic Changes in 1,760 Systemic Lupus Erythematosus Patients From Two Phase III Trials of BAFF Blockade With Tabalumab. Arthritis Rheumatol. 2017;69(3):643–54. doi: 10.1002/art.39950 27723281.
8. Bennett L, Palucka AK, Arce E, Cantrell V, Borvak J, Banchereau J, et al. Interferon and granulopoiesis signatures in systemic lupus erythematosus blood. J Exp Med. 2003;197(6):711–23. Epub 2003/03/19. doi: 10.1084/jem.20021553 12642603; PubMed Central PMCID: PMC2193846.
9. Kirou KA, Lee C, George S, Louca K, Peterson MG, Crow MK. Activation of the interferon-alpha pathway identifies a subgroup of systemic lupus erythematosus patients with distinct serologic features and active disease. Arthritis Rheum. 2005;52(5):1491–503. Epub 2005/05/10. doi: 10.1002/art.21031 15880830.
10. Lauwerys BR, Ducreux J, Houssiau FA. Type I interferon blockade in systemic lupus erythematosus: where do we stand? Rheumatology (Oxford). 2014;53(8):1369–76. Epub 2013/12/18. doi: 10.1093/rheumatology/ket403 24344319.
11. Marbach D, Costello JC, Kuffner R, Vega NM, Prill RJ, Camacho DM, et al. Wisdom of crowds for robust gene network inference. Nat Methods. 2012;9(8):796–804. doi: 10.1038/nmeth.2016 22796662; PubMed Central PMCID: PMC3512113.
12. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559. doi: 10.1186/1471-2105-9-559 19114008; PubMed Central PMCID: PMC2631488.
13. Pearl J. Causality: Models, Reasoning, and Inference: Cambridge University Press; 2000.
14. Mok CC. The Jakinibs in systemic lupus erythematosus: progress and prospects. Expert Opin Investig Drugs. 2019;28(1):85–92. doi: 10.1080/13543784.2019.1551358 30462559.
15. Alunno A, Padjen I, Fanouriakis A, Boumpas DT. Pathogenic and Therapeutic Relevance of JAK/STAT Signaling in Systemic Lupus Erythematosus: Integration of Distinct Inflammatory Pathways and the Prospect of Their Inhibition with an Oral Agent. Cells. 2019;8(8):898. doi: 10.3390/cells8080898 31443172
16. Isenberg DA, Petri M, Kalunian K, Tanaka Y, Urowitz MB, Hoffman RW, et al. Efficacy and safety of subcutaneous tabalumab in patients with systemic lupus erythematosus: results from ILLUMINATE-1, a 52-week, phase III, multicentre, randomised, double-blind, placebo-controlled study. Ann Rheum Dis. 2016;75(2):323–31. doi: 10.1136/annrheumdis-2015-207653 26338095.
17. Merrill JT, van Vollenhoven RF, Buyon JP, Furie RA, Stohl W, Morgan-Cox M, et al. Efficacy and safety of subcutaneous tabalumab, a monoclonal antibody to B-cell activating factor, in patients with systemic lupus erythematosus: results from ILLUMINATE-2, a 52-week, phase III, multicentre, randomised, double-blind, placebo-controlled study. Ann Rheum Dis. 2016;75(2):332–40. Epub 2015/08/22. doi: 10.1136/annrheumdis-2015-207654 26293163.
18. Bandy J, Milward D, McQuay S. Mining protein-protein interactions from published literature using Linguamatics I2E. Methods Mol Biol. 2009;563:3–13. doi: 10.1007/978-1-60761-175-2_1 19597777.
19. Zhang B, Gaiteri C, Bodea LG, Wang Z, McElwee J, Podtelezhnikov AA, et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease. Cell. 2013;153(3):707–20. doi: 10.1016/j.cell.2013.03.030 23622250; PubMed Central PMCID: PMC3677161.
20. Csardi G, Nepusz T. The igraph software package for complex network research. InterJournal, Complex Systems. 2006;1695(5):1–9.
21. Scutari M. Learning Bayesian networks with the bnlearn R package. Journal of Statistical Software. 2010;35(3):1–22. Epub 2010-07-16.
22. Margaritis D. Learning Bayesian network model structure from data: Carnegie Mellon University; 2003.
23. Barabasi AL. Scale-free networks: a decade and beyond. Science. 2009;325(5939):412–3. doi: 10.1126/science.1173299 19628854.
24. Friedman J, Hastie T, Tibshirani R. The elements of statistical learning: Springer series in statistics New York; 2001.
25. Tamura T, Yanai H, Savitsky D, Taniguchi T. The IRF family transcription factors in immunity and oncogenesis. Annu Rev Immunol. 2008;26:535–84. doi: 10.1146/annurev.immunol.26.021607.090400 18303999.
26. Kochupurakkal BS, Wang ZC, Hua T, Culhane AC, Rodig SJ, Rajkovic-Molek K, et al. RelA-Induced Interferon Response Negatively Regulates Proliferation. PLoS One. 2015;10(10):e0140243. Epub 2015/10/16. doi: 10.1371/journal.pone.0140243 26460486; PubMed Central PMCID: PMC4604146.
27. Wang F, Gao X, Barrett JW, Shao Q, Bartee E, Mohamed MR, et al. RIG-I mediates the co-induction of tumor necrosis factor and type I interferon elicited by myxoma virus in primary human macrophages. PLoS Pathog. 2008;4(7):e1000099. Epub 2008/07/12. doi: 10.1371/journal.ppat.1000099 18617992; PubMed Central PMCID: PMC2438611.
28. Mistry P, Kaplan MJ. Cell death in the pathogenesis of systemic lupus erythematosus and lupus nephritis. Clin Immunol. 2017;185:59–73. Epub 2016/10/25. doi: 10.1016/j.clim.2016.08.010 27519955; PubMed Central PMCID: PMC5299061.
29. Cousens LP, Goulette FA, Darnowski JW. JAK-mediated signaling inhibits Fas ligand-induced apoptosis independent of de novo protein synthesis. J Immunol. 2005;174(1):320–7. Epub 2004/12/22. doi: 10.4049/jimmunol.174.1.320 15611255.
30. Li X, Leung S, Qureshi S, Darnell JE Jr., Stark GR. Formation of STAT1-STAT2 heterodimers and their role in the activation of IRF-1 gene transcription by interferon-alpha. J Biol Chem. 1996;271(10):5790–4. Epub 1996/03/08. doi: 10.1074/jbc.271.10.5790 8621447.
31. Santer DM, Wiedeman AE, Teal TH, Ghosh P, Elkon KB. Plasmacytoid dendritic cells and C1q differentially regulate inflammatory gene induction by lupus immune complexes. J Immunol. 2012;188(2):902–15. doi: 10.4049/jimmunol.1102797 22147767; PubMed Central PMCID: PMC3238790.
32. Kutzner A, Pramanik S, Kim PS, Heese K. All-or-(N)One—an epistemological characterization of the human tumorigenic neuronal paralogous FAM72 gene loci. Genomics. 2015;106(5):278–85. Epub 2015/07/25. doi: 10.1016/j.ygeno.2015.07.003 26206078.
33. Hara M, Kitani A, Harigai M, Hirose T, Norioka K, Hirose W, et al. Differential abnormality in cell-cycle stage of peripheral B cells from patients with systemic lupus erythematosus. Rheumatol Int. 1987;7(2):83–7. Epub 1987/01/01. doi: 10.1007/bf00270312 3497423.
34. Liu YP, Zeng L, Tian A, Bomkamp A, Rivera D, Gutman D, et al. Endoplasmic reticulum stress regulates the innate immunity critical transcription factor IRF3. J Immunol. 2012;189(9):4630–9. Epub 2012/10/03. doi: 10.4049/jimmunol.1102737 23028052; PubMed Central PMCID: PMC3478468.
35. Meares GP, Liu Y, Rajbhandari R, Qin H, Nozell SE, Mobley JA, et al. PERK-dependent activation of JAK1 and STAT3 contributes to endoplasmic reticulum stress-induced inflammation. Mol Cell Biol. 2014;34(20):3911–25. Epub 2014/08/13. doi: 10.1128/MCB.00980-14 25113558; PubMed Central PMCID: PMC4187715.
36. Bradshaw RAD, Edward A. Handbook of Cell Signaling2009.
37. Papageorgiou A, Dinney CP, McConkey DJ. Interferon-alpha induces TRAIL expression and cell death via an IRF-1-dependent mechanism in human bladder cancer cells. Cancer Biol Ther. 2007;6(6):872–9. Epub 2007/07/10. doi: 10.4161/cbt.6.6.4088 17617740.
38. Shi L, Perin JC, Leipzig J, Zhang Z, Sullivan KE. Genome-wide analysis of interferon regulatory factor I binding in primary human monocytes. Gene. 2011;487(1):21–8. Epub 2011/08/02. doi: 10.1016/j.gene.2011.07.004 21803131; PubMed Central PMCID: PMC3167955.
39. Tsokos GC, Lo MS, Costa Reis P, Sullivan KE. New insights into the immunopathogenesis of systemic lupus erythematosus. Nat Rev Rheumatol. 2016;12(12):716–30. Epub 2016/11/23. doi: 10.1038/nrrheum.2016.186 27872476.
40. Oon S, Wilson NJ, Wicks I. Targeted therapeutics in SLE: emerging strategies to modulate the interferon pathway. Clin Transl Immunology. 2016;5(5):e79. Epub 2016/06/29. doi: 10.1038/cti.2016.26 27350879; PubMed Central PMCID: PMC4910120.
41. Biesen R, Demir C, Barkhudarova F, Grun JR, Steinbrich-Zollner M, Backhaus M, et al. Sialic acid-binding Ig-like lectin 1 expression in inflammatory and resident monocytes is a potential biomarker for monitoring disease activity and success of therapy in systemic lupus erythematosus. Arthritis Rheum. 2008;58(4):1136–45. Epub 2008/04/03. doi: 10.1002/art.23404 18383365.
42. Rose T, Grutzkau A, Hirseland H, Huscher D, Dahnrich C, Dzionek A, et al. IFNalpha and its response proteins, IP-10 and SIGLEC-1, are biomarkers of disease activity in systemic lupus erythematosus. Ann Rheum Dis. 2013;72(10):1639–45. Epub 2012/11/03. doi: 10.1136/annrheumdis-2012-201586 23117242.
43. Regad T, Chelbi-Alix MK. Role and fate of PML nuclear bodies in response to interferon and viral infections. Oncogene. 2001;20(49):7274–86. doi: 10.1038/sj.onc.1204854 11704856.
44. Zhou W, Bao S. PML-mediated signaling and its role in cancer stem cells. Oncogene. 2014;33(12):1475–84. doi: 10.1038/onc.2013.111 23563177.
45. Liu ZP, Wu C, Miao H, Wu H. RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse. Database (Oxford). 2015;2015. Epub 2015/10/02. doi: 10.1093/database/bav095 26424082; PubMed Central PMCID: PMC4589691.
46. Han H, Cho JW, Lee S, Yun A, Kim H, Bae D, et al. TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Res. 2018;46(D1):D380–D6. Epub 2017/11/01. doi: 10.1093/nar/gkx1013 29087512; PubMed Central PMCID: PMC5753191.
47. Becker AM, Dao KH, Han BK, Kornu R, Lakhanpal S, Mobley AB, et al. SLE peripheral blood B cell, T cell and myeloid cell transcriptomes display unique profiles and each subset contributes to the interferon signature. PloS one. 2013;8(6):e67003. doi: 10.1371/journal.pone.0067003 23826184
Článok vyšiel v časopise
PLOS One
2019 Číslo 12
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Úspěšná resuscitativní thorakotomie v přednemocniční neodkladné péči
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Methylsulfonylmethane increases osteogenesis and regulates the mineralization of the matrix by transglutaminase 2 in SHED cells
- Oregano powder reduces Streptococcus and increases SCFA concentration in a mixed bacterial culture assay
- The characteristic of patulous eustachian tube patients diagnosed by the JOS diagnostic criteria
- Parametric CAD modeling for open source scientific hardware: Comparing OpenSCAD and FreeCAD Python scripts