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Iron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseases

Douglas B Kell

BMC Medical Genomics · 2009 · Review

doi:10.1186/1755-8794-2-2

Abstract

Background. The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular 'reactive oxygen species' (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation.

Review. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, since in some circumstances (especially the presence of poorly liganded iron) molecules that are nominally antioxidants can actually act as pro-oxidants. The reduction of redox stress thus requires suitable levels of both antioxidants and effective iron chelators. Some polyphenolic antioxidants may serve both roles. Understanding the exact speciation and liganding of iron in all its states is thus crucial to separating its various pro- and anti-inflammatory activities. Redox stress, innate immunity and pro- (and some anti-)inflammatory cytokines are linked in particular via signalling pathways involving NF-kappaB and p38, with the oxidative roles of iron here seemingly involved upstream of the IkappaB kinase (IKK) reaction. In a number of cases it is possible to identify mechanisms by which ROSs and poorly liganded iron act synergistically and autocatalytically, leading to 'runaway' reactions that are hard to control unless one tackles multiple sites of action simultaneously. Some molecules such as statins and erythropoietin, not traditionally associated with anti-inflammatory activity, do indeed have 'pleiotropic' anti-inflammatory effects that may be of benefit here.

Conclusion. Overall we argue, by synthesising a widely dispersed literature, that the role of poorly liganded iron has been rather underappreciated in the past, and that in combination with peroxide and superoxide its activity underpins the behaviour of a great many physiological processes that degrade over time. Understanding these requires an integrative, systems-level approach that may lead to novel therapeutic targets.

References 2469

  1. 1.

    Harnad S, Brody T, Vallieres F, Carr L, Hitchcock S, Gingras Y, Oppenheim C, Hajjem C, Hilf ER. The access/impact problem and the green and gold roads to open access: An update. Serials Review. 2008;34:36-40.

    Not in our library

  2. 2.

    Hull D, Pettifer SR, Kell DB. Defrosting the digital library: bibliographic tools for the next generation web. PLoS Comput Biol. 2008;4:e1000204.

    Not in our library10.1371/journal.pcbi.1000204

  3. 3.

    Ananiadou S, McNaught J. Text mining in biology and biomedicine. 2006.

    Not in our library

  4. 4.

    Ananiadou S, Kell DB, Tsujii Ji. Text Mining and its potential applications in Systems Biology. Trends Biotechnol. 2006;24:571-579.

    Not in our library10.1016/j.tibtech.2006.10.002

  5. 5.

    Jensen LJ, Saric J, Bork P. Literature mining for the biologist: from information retrieval to biological discovery. Nat Rev Genet. 2006;7:119-29.

    Not in our library10.1038/nrg1768

  6. 6.

    Smalheiser NR. The Arrowsmith project: 2005 status report. LNCS. 2005;3735:26-43.

    Not in our library

  7. 7.

    Hristovski D, Peterlin B, Mitchell JA, Humphrey SM. Using literature-based discovery to identify disease candidate genes. Int J Med Inform. 2005;74:289-98.

    Not in our library10.1016/j.ijmedinf.2004.04.024

  8. 8.

    Kostoff RN. Systematic acceleration of radical discovery and innovation in science and technology. Technol Forecasting Soc Change. 2006;73:923-936.

    Not in our library

  9. 9.

    Yetisgen-Yildiz M, Pratt W. Using statistical and knowledge-based approaches for literature-based discovery. J Biomed Informatics. 2006;39:600-611.

    Not in our library10.1016/j.jbi.2005.11.010

  10. 10.

    Kostoff RN. Validating discovery in literature-based discovery. J Biomed Inform. 2007;40:448-50.

    Not in our library10.1016/j.jbi.2007.05.001

  11. 11.

    Kostoff RN, Briggs MB, Solka JL, Rushenberg RL. Literature-related discovery (LRD): Methodology. Technol Forecast Soc Change. 2008.

    Not in our library

  12. 12.

    Cronin B. Bibliometrics and beyond: Some thoughts on web-based citation analysis. Journal of Information Science. 2001;27:1-7.

    Not in our library

  13. 13.

    Kasztler A, Leitner KH. Bibliometric analysis and visualisation of intellectual capital. J Universal Comp Sci. 2002;8:516-525.

    Not in our library

  14. 14.

    Tabah AN. Literature dynamics: Studies on growth, diffusion, and epidemics. Annu Rev Inf Sci Technol. 1999;34:249-286.

    Not in our library

  15. 15.

    Börner K, Chen CM, Boyack KW. Visualizing knowledge domains. Annual Review of Information Science and Technology. 2003;37:179-255.

    Not in our library

  16. 16.

    Errami M, Hicks JM, Fisher W, Trusty D, Wren JD, Long TC, Garner HR. Déjà vu: a study of duplicate citations in Medline. Bioinformatics. 2008;24:243-9.

    Not in our library10.1093/bioinformatics/btm574

  17. 17.
    Iron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseases · 2009
    No notice
  18. 18.

    Dobson PD, Kell DB. Carrier-mediated cellular uptake of pharmaceutical drugs: an exception or the rule? Nat Rev Drug Discov. 2008;7:205-220.

    Not in our library10.1038/nrd2438

  19. 19.

    Smalheiser NR, Torvik VI, Bischoff-Grethe A, Burhans LB, Gabriel M, Homayouni R, Kashef A, Martone ME, Perkins GA, Price DL, Talk AC, West R. Collaborative development of the Arrowsmith two node search interface designed for laboratory investigators. J Biomed Discov Collab. 2006;1:8.

    Not in our library10.1186/1747-5333-1-8

  20. 20.

    Smalheiser NR, Swanson DR. Using ARROWSMITH: a computer-assisted approach to formulating and assessing scientific hypotheses. Comput Methods Programs Biomed. 1998;57:149-53.

    Not in our library10.1016/s0169-2607(98)00033-9

  21. 21.

    Doms A, Schroeder M. GoPubMed: exploring PubMed with the Gene Ontology. Nucleic Acids Res. 2005;33:W783-6.

    Not in our library10.1093/nar/gki470

  22. 22.

    Oinn T, Addis M, Ferris J, Marvin D, Senger M, Greenwood M, Carver T, Glover K, Pocock MR, Wipat A, Li P. Taverna: a tool for the composition and enactment of bioinformatics workflows. Bioinformatics. 2004;20:3045-54.

    Not in our library10.1093/bioinformatics/bth361

  23. 23.

    Oinn T, Li P, Kell DB, Goble C, Goderis A, Greenwood M, Hull D, Stevens R, Turi D, Zhao J, Taylor IJ, Deelman E, Gannon DB, Shields M. Taverna/myGrid: aligning a workflow system with the life sciences community. Workflows for e-Science: scientific workflows for Grids. 2007;300-319.

    Not in our library

  24. 24.

    Hull D, Wolstencroft K, Stevens R, Goble C, Pocock MR, Li P, Oinn T. Taverna: a tool for building and running workflows of services. Nucleic Acids Res. 2006;34:W729-32.

    Not in our library10.1093/nar/gkl320

  25. 25.

    Oinn T, Greenwood M, Addis M, Alpdemir MN, Ferris J, Glover K, Goble C, Goderis A, Hull D, Marvin D, Li P, Lord P, Pocock MR, Senger M, Stevens R, Wipat A, Wroe C. Taverna: lessons in creating a workflow environment for the life sciences. Concurrency and Computation: Practice & Experience. 2006;18:1067-1100.

    Not in our library

  26. 26.

    Goble C, Wolstencroft K, Goderis A, Hull D, Zhao J, Alper P, Lord P, Wroe C, Belhajjame K, Turi D, Stevens R, Oinn T, De Roure D, Baker CJO, Cheung K-H. Knowledge discovery for biology with Taverna: producing and consuming semantics in the Web of Science. Semantic Web: revolutionising knowledge discovery in the life sciences. 2007.

    Not in our library

  27. 27.

    Chance B, Sies H, Boveris A. Hydroperoxide metabolism in mammalian organs. Physiol Rev. 1979;59:527-605.

    Not in our library10.1152/physrev.1979.59.3.527

  28. 28.

    Lenaz G. Role of mitochondria in oxidative stress and ageing. Biochim Biophys Acta. 1998;1366:53-67.

    Not in our library10.1016/s0005-2728(98)00120-0

  29. 29.

    Barja G. Mitochondrial oxygen radical generation and leak: sites of production in states 4 and 3, organ specificity, and relation to aging and longevity. J Bioenerg Biomembr. 1999;31:347-66.

    Not in our library10.1023/a:1005427919188

  30. 30.

    Kowaltowski AJ, Vercesi AE. Mitochondrial damage induced by conditions of oxidative stress. Free Radic Biol Med. 1999;26:463-71.

    Not in our library10.1016/s0891-5849(98)00216-0

  31. 31.

    Cadenas E, Davies KJ. Mitochondrial free radical generation, oxidative stress, and aging. Free Radic Biol Med. 2000;29:222-30.

    Not in our library10.1016/s0891-5849(00)00317-8

  32. 32.

    Lenaz G, D'Aurelio M, Merlo Pich M, Genova ML, Ventura B, Bovina C, Formiggini G, Parenti Castelli G. Mitochondrial bioenergetics in aging. Biochim Biophys Acta. 2000;1459:397-404.

    Not in our library10.1016/s0005-2728(00)00177-8

  33. 33.

    Raha S, Robinson BH. Mitochondria, oxygen free radicals, disease and ageing. Trends Biochem Sci. 2000;25:502-8.

    Not in our library10.1016/s0968-0004(00)01674-1

  34. 34.

    Lenaz G. The mitochondrial production of reactive oxygen species: mechanisms and implications in human pathology. IUBMB Life. 2001;52:159-64.

    Not in our library10.1080/15216540152845957

  35. 35.

    Raha S, Robinson BH. Mitochondria, oxygen free radicals, and apoptosis. Am J Med Genet. 2001;106:62-70.

    Not in our library10.1002/ajmg.1398

  36. 36.

    Dröge W. Free radicals in the physiological control of cell function. Physiol Rev. 2002;82:47-95.

    Not in our library10.1152/physrev.00018.2001

  37. 37.

    Taylor ER, Hurrell F, Shannon RJ, Lin TK, Hirst J, Murphy MP. Reversible glutathionylation of complex I increases mitochondrial superoxide formation. J Biol Chem. 2003;278:19603-10.

    Not in our library10.1074/jbc.m209359200

  38. 38.

    Turrens JF. Mitochondrial formation of reactive oxygen species. J Physiol. 2003;552:335-44.

    Not in our library10.1113/jphysiol.2003.049478

  39. 39.

    Adam-Vizi V. Production of reactive oxygen species in brain mitochondria: Contribution by electron transport chain and non-electron transport chain sources. Antioxidants & Redox Signaling. 2005;7:1140-1149.

    Not in our library10.1089/ars.2005.7.1140

  40. 40.

    Andreyev AY, Kushnareva YE, Starkov AA. Mitochondrial metabolism of reactive oxygen species. Biochemistry (Mosc). 2005;70:200-14.

    Not in our library10.1007/s10541-005-0102-7

All 2469 references

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