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Network Medicine-Based Unbiased Disease Modules for Drug and Diagnostic Target Identification in ROSopathies

Chapter
Part of the Handbook of Experimental Pharmacology book series (HEP, volume 264)

Abstract

Most diseases are defined by a symptom, not a mechanism. Consequently, therapies remain symptomatic. In reverse, many potential disease mechanisms remain in arbitrary search for clinical relevance. Reactive oxygen species (ROS) are such an example. It is an attractive hypothesis that dysregulation of ROS can become a disease trigger. Indeed, elevated ROS levels of various biomarkers have been correlated with almost every disease, yet after decades of research without any therapeutic application. We here present a first systematic, non-hypothesis-based approach to transform this field as a proof of concept for biomedical research in general. We selected as seed proteins 9 families with 42 members of clinically researched ROS-generating enzymes, ROS-metabolizing enzymes or ROS targets. Applying an unbiased network medicine approach, their first neighbours were connected, and, based on a stringent subnet participation degree (SPD) of 0.4, hub nodes excluded. This resulted in 12 distinct human interactome-based ROS signalling modules, while 8 proteins remaining unconnected. This ROSome is in sharp contrast to commonly used highly curated and integrated KEGG, HMDB or WikiPathways. These latter serve more as mind maps of possible ROS signalling events but may lack important interactions and often do not take different cellular and subcellular localization into account. Moreover, novel non-ROS-related proteins were part of these forming functional hybrids, such as the NOX5/sGC, NOX1,2/NOS2, NRF2/ENC-1 and MPO/SP-A modules. Thus, ROS sources are not interchangeable but associated with distinct disease processes or not at all. Module members represent leads for precision diagnostics to stratify patients with specific ROSopathies for precision intervention.

Graphical Abstract

The upper panel shows the classical approach to generate hypotheses for a role of ROS in a given disease by focusing on ROS levels and to some degree the ROS type or metabolite. Low levels are considered physiological; higher amounts are thought to cause a redox imbalance, oxidative stress and eventually disease. The source of ROS is less relevant; there is also ROS-induced ROS formation, i.e. by secondary sources (see upwards arrow). The non-hypothesis-based network medicine approach uses genetically or otherwise validated risk genes to construct disease-relevant signalling modules, which will contain also ROS targets. Not all ROS sources will be relevant for a given disease; some may not be disease relevant at all. The three examples show (from left to right) the disease-relevant appearance of an unphysiological ROS modifier/toxifier protein, ROS target or ROS source.

Keywords

ROS Systems medicine Network pharmacology Precision medicine Precision diagnostics 

References

  1. Alanis-Lobato G, Andrade-Navarro MA (2017) A reliable and unbiased human protein network with the disparity filter. BioRxiv.  https://doi.org/10.1101/207761
  2. Altenhöfer S, Kleikers PWM, Radermacher KA, Peter S, Rob Hermans JJ, Schiffers P, Ho H, Wingler K, Schmidt HHHW (2012) The NOX toolbox: validating the role of NADPH oxidases in physiology and disease. Cell Mol Life Sci 69:2327.  https://doi.org/10.1007/s00018-012-1010-9CrossRefPubMedPubMedCentralGoogle Scholar
  3. Alvarez-Ponce D, Feyertag F, Chakraborty S (2017) Position matters: network centrality considerably impacts rates of protein evolution in the human protein-protein interaction network. Genome Biol Evol 9:1742.  https://doi.org/10.1093/gbe/evx117CrossRefPubMedPubMedCentralGoogle Scholar
  4. Aviello G, Knaus UG (2018) NADPH oxidases and ROS signaling in the gastrointestinal tract review-article. Mucosal Immunol 11:1011.  https://doi.org/10.1038/s41385-018-0021-8CrossRefPubMedGoogle Scholar
  5. Bickers DR, Athar M (2006) Oxidative stress in the pathogenesis of skin disease. J Investig Dermatol 126:2565.  https://doi.org/10.1038/sj.jid.5700340CrossRefPubMedGoogle Scholar
  6. Bigarella CL, Liang R, Ghaffari S (2014) Stem cells and the impact of ROS signaling. Development (Cambridge) 141:4206.  https://doi.org/10.1242/dev.107086CrossRefGoogle Scholar
  7. Björklund ÅK, Light S, Hedin L, Elofsson A (2008) Quantitative assessment of the structural Bias in protein-protein interaction assays. Proteomics 8:4657.  https://doi.org/10.1002/pmic.200800150CrossRefPubMedGoogle Scholar
  8. Casas AI, Dao VTV, Daiber A, Maghzal GJ, Di Lisa F, Kaludercic N, Leach S et al (2015) Reactive oxygen-related diseases: therapeutic targets and emerging clinical indications. Antioxid Redox Signal 23:1171.  https://doi.org/10.1089/ars.2015.6433CrossRefPubMedPubMedCentralGoogle Scholar
  9. Casas AI, Geuss E, Kleikers PWM, Mencl S, Herrmann AM, Buendia I, Egea J et al (2017) NOX4-dependent neuronal autotoxicity and BBB breakdown explain the superior sensitivity of the brain to ischemic damage. Proc Natl Acad Sci U S A 114:12315.  https://doi.org/10.1073/pnas.1705034114CrossRefPubMedPubMedCentralGoogle Scholar
  10. Casas AI, Hassan AA, Larsen SJ, Gomez-Rangel V, Elbatreek M, Kleikers PWM, Guney E et al (2019a) From single drug targets to synergistic network pharmacology in ischemic stroke. Proc Natl Acad Sci U S A 116:7129.  https://doi.org/10.1073/pnas.1820799116CrossRefPubMedPubMedCentralGoogle Scholar
  11. Casas AI, Kleikers PWM, Geuss E, Langhauser F, Adler T, Busch DH, Gailus-Durner V et al (2019b) Calcium-dependent blood-brain barrier breakdown by NOX5 limits postreperfusion benefit in stroke. J Clin Investig 129:1772.  https://doi.org/10.1172/JCI124283CrossRefPubMedGoogle Scholar
  12. Cuadrado A, Manda G, Hassan A, Alcaraz MJ, Barbas C, Daiber A, Ghezzi P et al (2018) Transcription factor NRF2 as a therapeutic target for chronic diseases: a systems medicine approach. Pharmacol Rev 70:348.  https://doi.org/10.1124/pr.117.014753CrossRefPubMedGoogle Scholar
  13. Cuadrado, Antonio, Ana I. Rojo, Geoffrey Wells, John D. Hayes, Sharon P. Cousin, William L. Rumsey, Otis C. Attucks, et al. 2019. “Therapeutic targeting of the NRF2 and KEAP1 partnership in chronic diseases.” Nat Rev Drug Discov Doi:  https://doi.org/10.1038/s41573-018-0008-x, 18, 295
  14. Dröge W (2002) Free radicals in the physiological control of cell function. Physiol Rev 82:47.  https://doi.org/10.1152/physrev.00018.2001CrossRefPubMedGoogle Scholar
  15. Edmondson D (2014) Hydrogen peroxide produced by mitochondrial monoamine oxidase catalysis: biological implications. Curr Pharm Des 20:155.  https://doi.org/10.2174/13816128113190990406CrossRefPubMedGoogle Scholar
  16. Frijhoff J, Winyard PG, Zarkovic N, Davies SS, Stocker R, Cheng D, Knight AR et al (2015) Clinical relevance of biomarkers of oxidative stress. Antioxid Redox Signal 23(14):1144–1170.  https://doi.org/10.1089/ars.2015.6317CrossRefPubMedPubMedCentralGoogle Scholar
  17. Gracia C, Karla DL-C, Husi H (2017) CVD and oxidative stress. J Clin Med 6.  https://doi.org/10.3390/jcm6020022
  18. Gray SP, Di Marco E, Okabe J, Szyndralewiez C, Heitz F, Montezano AC, De Haan JB et al (2013) NADPH oxidase 1 plays a key role in diabetes mellitus-accelerated atherosclerosis. Circulation 127:1888.  https://doi.org/10.1161/CIRCULATIONAHA.112.132159CrossRefPubMedGoogle Scholar
  19. Gray SP, Di Marco E, Kennedy K, Chew P, Okabe J, El-Osta A, Calkin AC et al (2016) Reactive oxygen species can provide atheroprotection via NOX4-dependent inhibition of inflammation and vascular remodeling. Arterioscler Thromb Vasc Biol 36:295.  https://doi.org/10.1161/ATVBAHA.115.307012CrossRefPubMedGoogle Scholar
  20. He FJ, MacGregor GA (2007) Blood pressure is the most important cause of death and disability in the world. Eur Heart J Suppl 9(B):23–28.  https://doi.org/10.1093/eurheartj/sum005CrossRefGoogle Scholar
  21. Hilenski LL, Clempus RE, Quinn MT, David Lambeth J, Griendling KK (2004) Distinct subcellular localizations of Nox1 and Nox4 in vascular smooth muscle cells. Arterioscler Thromb Vasc Biol 24:677.  https://doi.org/10.1161/01.ATV.0000112024.13727.2cCrossRefPubMedGoogle Scholar
  22. Hochman JS, Alexander JH, Reynolds HR, Stebbins AL, Dzavik V, Harrington RA, Van De Werf F (2007) Effect of Tilarginine acetate in patients with acute myocardial infarction and cardiogenic shock: the TRIUMPH randomized controlled trial. J Am Med Assoc 297:1657.  https://doi.org/10.1001/jama.297.15.joc70035CrossRefGoogle Scholar
  23. Ivanic J, Yu X, Wallqvist A, Reifman J (2009) Influence of protein abundance on high-throughput protein-protein interaction detection. PLoS One 4:e5815.  https://doi.org/10.1371/journal.pone.0005815CrossRefPubMedPubMedCentralGoogle Scholar
  24. Jäkel A, Clark H, Reid KBM, Sim RB (2010) Surface-bound myeloperoxidase is a ligand for recognition of late apoptotic neutrophils by human lung surfactant proteins A and D. Protein Cell 1:563.  https://doi.org/10.1007/s13238-010-0076-0CrossRefPubMedPubMedCentralGoogle Scholar
  25. Jensen LJ, Bork P (2008) Biochemistry: not comparable, but complementary. Science 322:56.  https://doi.org/10.1126/science.1164801CrossRefPubMedGoogle Scholar
  26. Jha JC, Gray SP, Barit D, Okabe J, El-Osta A, Namikoshi T, Thallas-Bonke V et al (2014) Genetic targeting or pharmacologic inhibition of NADPH oxidase Nox4 provides renoprotection in long-term diabetic nephropathy. J Am Soc Nephrol 25:1237.  https://doi.org/10.1681/asn.2013070810CrossRefPubMedPubMedCentralGoogle Scholar
  27. Kleinschnitz C, Mencl S, Kleikers PWM, Schuhmann MK, López MG, Casas AI, Sürün B, Reif A, Schmidt HHHW (2016) NOS knockout or inhibition but not disrupting PSD-95-NOS interaction protect against ischemic brain damage. J Cereb Blood Flow Metab 36:1508.  https://doi.org/10.1177/0271678X16657094CrossRefPubMedPubMedCentralGoogle Scholar
  28. Knowles RG, Moncada S (1994) Nitric oxide synthases in mammals. Biochem J 298:249.  https://doi.org/10.1042/bj2980249CrossRefPubMedPubMedCentralGoogle Scholar
  29. Kotlyar M, Pastrello C, Malik Z, Jurisica I (2019) IID 2018 update: context-specific physical protein-protein interactions in human, model organisms and domesticated species. Nucleic Acids Res 47:D581.  https://doi.org/10.1093/nar/gky1037CrossRefPubMedGoogle Scholar
  30. Lane AE, Tan JTM, Hawkins CL, Heather AK, Davies MJ (2010) The myeloperoxidase-derived oxidant HOSCN inhibits protein tyrosine phosphatases and modulates cell Signalling via the mitogen-activated protein kinase (MAPK) pathway in macrophages. Biochem J 430:161.  https://doi.org/10.1042/BJ20100082CrossRefPubMedPubMedCentralGoogle Scholar
  31. Langhauser F, Casas AI, Dao VTV, Guney E, Menche J, Geuss E, Kleikers PWM et al (2018) A diseasome cluster-based drug repurposing of soluble guanylate cyclase activators from smooth muscle relaxation to direct neuroprotection. NPJ Syst Biol Appl 4:8.  https://doi.org/10.1038/s41540-017-0039-7CrossRefPubMedPubMedCentralGoogle Scholar
  32. Lapchak PA (2010) A critical assessment of Edaravone acute ischemic stroke efficacy trials: is Edaravone an effective neuroprotective therapy? Expert Opin Pharmacother 11:1753.  https://doi.org/10.1517/14656566.2010.493558CrossRefPubMedPubMedCentralGoogle Scholar
  33. Matziouridou C, Rocha SDC, Haabeth OA, Rudi K, Carlsen H, Kielland A (2018) INOS- and NOX1-dependent ROS production maintains bacterial homeostasis in the ileum of mice. Mucosal Immunol 11:774.  https://doi.org/10.1038/mi.2017.106CrossRefPubMedGoogle Scholar
  34. Menche J, Sharma A, Kitsak M, Ghiassian SD, Vidal M, Loscalzo J, Barabási AL (2015) Uncovering disease-disease relationships through the incomplete Interactome. Science 347(6224):841.  https://doi.org/10.1126/science.1257601CrossRefGoogle Scholar
  35. Moloney JN, Cotter TG (2018) ROS Signalling in the biology of cancer. Semin Cell Dev Biol 80:50.  https://doi.org/10.1016/j.semcdb.2017.05.023CrossRefPubMedGoogle Scholar
  36. Nisimoto Y, Diebold BA, Constentino-Gomes D, David Lambeth J (2014) Nox4: a hydrogen peroxide-generating oxygen sensor. Biochemistry 53:5111.  https://doi.org/10.1021/bi500331yCrossRefPubMedPubMedCentralGoogle Scholar
  37. Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M (1999) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 27:29.  https://doi.org/10.1093/nar/27.1.29CrossRefPubMedPubMedCentralGoogle Scholar
  38. Ogden LG, He J, Lydick E, Whelton PK (2000) Long-term absolute benefit of lowering blood pressure in hypertensive patients according to the JNC VI risk stratification. Hypertension 35(2):539–543.  https://doi.org/10.1161/01.HYP.35.2.539CrossRefPubMedGoogle Scholar
  39. Ogedegbe G, Shah NR, Phillips C, Goldfeld K, Roy J, Yu G, Gyamfi J, Torgersen C, Capponi L, Bangalore S (2015) Comparative effectiveness of angiotensin-converting enzyme inhibitor-based treatment on cardiovascular outcomes in hypertensive blacks versus whites. J Am Coll Cardiol 66(11):1224–1233.  https://doi.org/10.1016/j.jacc.2015.07.021CrossRefPubMedPubMedCentralGoogle Scholar
  40. Pajares M, Cuadrado A, Rojo AI (2017) Modulation of Proteostasis by transcription factor NRF2 and impact in neurodegenerative diseases. Redox Biol 11:543.  https://doi.org/10.1016/j.redox.2017.01.006CrossRefPubMedPubMedCentralGoogle Scholar
  41. Paulus WJ, Tschöpe C (2013) A novel paradigm for heart failure with preserved ejection fraction: comorbidities drive myocardial dysfunction and remodeling through coronary microvascular endothelial inflammation. J Am Coll Cardiol 62:263.  https://doi.org/10.1016/j.jacc.2013.02.092CrossRefPubMedGoogle Scholar
  42. Schaefer MH, Serrano L, Andrade-Navarro MA (2015) Correcting for the study Bias associated with protein-protein interaction measurements reveals differences between protein degree distributions from different Cancer types. Front Genet 6.  https://doi.org/10.3389/fgene.2015.00260
  43. Schmidt HHHW, Stocker R, Vollbracht C, Paulsen G, Riley D, Daiber A, Cuadrado A (2015) Antioxidants in translational medicine. Antioxid Redox Signal 23:1130.  https://doi.org/10.1089/ars.2015.6393CrossRefPubMedPubMedCentralGoogle Scholar
  44. Schork NJ (2015) Personalized medicine: time for one-person trials. Nature 520:609.  https://doi.org/10.1038/520609aCrossRefPubMedGoogle Scholar
  45. Schwerd T, Bryant RV, Pandey S, Capitani M, Meran L, Cazier JB, Jung J et al (2018) NOX1 loss-of-function genetic variants in patients with inflammatory bowel disease. Mucosal Immunol 11:562.  https://doi.org/10.1038/mi.2017.74CrossRefPubMedGoogle Scholar
  46. Slenter DN, Kutmon M, Hanspers K, Riutta A, Windsor J, Nunes N, Mélius J et al (2018) WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res 46:D661.  https://doi.org/10.1093/nar/gkx1064CrossRefPubMedGoogle Scholar
  47. Takimoto E, Champion HC, Li M, Belardi D, Shuxun R, Rene Rodriguez E, Bedja D, Gabrielson KL, Wang Y, Kass DA (2005) Chronic inhibition of cyclic GMP phosphodiesterase 5A prevents and reverses cardiac hypertrophy. Nat Med 11:214.  https://doi.org/10.1038/nm1175CrossRefPubMedGoogle Scholar
  48. Thanan R, Oikawa S, Hiraku Y, Ohnishi S, Ma N, Pinlaor S, Yongvanit P, Kawanishi S, Murata M (2014) Oxidative stress and its significant roles in neurodegenerative diseases and Cancer. Int J Mol Sci 16:193.  https://doi.org/10.3390/ijms16010193CrossRefPubMedPubMedCentralGoogle Scholar
  49. Villanueva C, Giulivi C (2010) Subcellular and cellular locations of nitric oxide synthase isoforms as determinants of health and disease. Free Radic Biol Med 49:307.  https://doi.org/10.1016/j.freeradbiomed.2010.04.004CrossRefPubMedPubMedCentralGoogle Scholar
  50. von Mering C, Krause R, Snel B, Cornell M, Oliver SG, Fields S, Bork P (2002) Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417:399.  https://doi.org/10.1038/nature750CrossRefGoogle Scholar
  51. Wang XJ, Zhang DD (2009) Ectodermal-neural cortex 1 down-regulates Nrf2 at the translational level. PLoS One 4:e5492.  https://doi.org/10.1371/journal.pone.0005492CrossRefPubMedPubMedCentralGoogle Scholar
  52. Wilkinson-Berka JL, Deliyanti D, Rana I, Miller AG, Agrotis A, Armani R, Szyndralewiez C et al (2014) NADPH oxidase, NOX1, mediates vascular injury in ischemic retinopathy. Antioxid Redox Signal 20:2726.  https://doi.org/10.1089/ars.2013.5357CrossRefPubMedPubMedCentralGoogle Scholar
  53. Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, Cheng D et al (2007) HMDB: the human metabolome database. Nucleic Acids Res 35:D521.  https://doi.org/10.1093/nar/gkl923CrossRefPubMedPubMedCentralGoogle Scholar
  54. Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Vázquez-Fresno R, Sajed T et al (2018) HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res.  https://doi.org/10.1093/nar/gkx1089
  55. Yang JL, Mukda S, Der Chen S (2018) Diverse roles of mitochondria in ischemic stroke. Redox Biol 16:263.  https://doi.org/10.1016/j.redox.2018.03.002CrossRefPubMedPubMedCentralGoogle Scholar
  56. Zhao Y, Hu X, Liu Y, Dong S, Wen Z, He W, Zhang S, Huang Q, Shi M (2017) ROS signaling under metabolic stress: cross-talk between AMPK and AKT pathway. Mol Cancer 16:79.  https://doi.org/10.1186/s12943-017-0648-1CrossRefPubMedPubMedCentralGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Pharmacology and Personalised MedicineMaastricht UniversityMaastrichtThe Netherlands
  2. 2.Department of Mathematics and Computer ScienceUniversity of Southern DenmarkOdenseDenmark
  3. 3.Chair of Experimental Bioinformatics, TUM School of Life SciencesTechnical University of MunichFreisingGermany

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