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Microarrays in Inflammation pp 115–130Cite as

Gene expression profiling in neurological and neuroinflammatory diseases

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Part of the book series: Progress in Inflammation Research ((PIR))

Abstract

Neurological diseases arise when a sufficient number of neural cells cease to perform their normal functions, lose their ability to respond to the local environment, and die. In the last decade, a major technological leap led to the development of efficient and cost-effective high-throughput methods for determining gene expression. This in turn resulted in rapid accumulation of data describing gene expression patterns in human and experimental animal brains. In this chapter, I review several of the latest advances in large-scale gene expression in neurological and neuroinflammatory disorders, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and epilepsy. The need for integration of different sources of data is discussed in the context of systems biology, and I also address how such integration could result in improved diagnostics, therapies, and disease prevention.

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References

  1. Prentice T (2001) The World Health Report 2001. Mental health: new understanding, new hope. World Health Organization, Geneva

    Google Scholar 

  2. Higgins GA, Jacobsen H (2003) Transgenic mouse models of Alzheimer’s disease: phenotype and application. Behav Pharmacol 14, 419–438

    PubMed  CAS  Google Scholar 

  3. Hata R et al (2001) Up-regulation of calcineurin Abeta mRNA in the Alzheimer’s disease brain: assessment by cDNA microarray. Biochem Biophys Res Commun 284, 310–316

    Article  PubMed  CAS  Google Scholar 

  4. Colangelo V et al (2002) Gene expression profiling of 12633 genes in Alzheimer hippocampal CA1: transcription and neurotrophic factor down-regulation and up-regulation of apoptotic and pro-inflammatory signaling. J Neurosci Res 70, 462–473

    Article  PubMed  CAS  Google Scholar 

  5. Yao PJ et al (2003) Defects in expression of genes related to synaptic vesicle trafficking in frontal cortex of Alzheimer’s disease. Neurobiol Dis 12, 97–109

    Article  PubMed  CAS  Google Scholar 

  6. Reddy PH et al (2004) Gene expression profiles of transcripts in amyloid precursor protein transgenic mice: up-regulation of mitochondrial metabolism and apoptotic genes is an early cellular change in Alzheimer’s disease. Hum Mol Genet 13, 1225–1240

    Article  PubMed  CAS  Google Scholar 

  7. Blalock EM et al (2004) Incipient Alzheimer’s disease: microarray correlation analyses reveal major transcriptional and tumor suppressor responses. Proc Natl Acad Sci USA 101, 2173–2178

    Article  PubMed  CAS  Google Scholar 

  8. Parachikova A et al (2006) Inflammatory changes parallel the early stages of Alzheimer disease. Neurobiol Aging 28, 1821–1833

    Article  PubMed  Google Scholar 

  9. Ginsberg SD et al (2000) Expression profile of transcripts in Alzheimer’s disease tanglebearing CA1 neurons. Ann Neurol 48, 77–87

    Article  PubMed  CAS  Google Scholar 

  10. Cataldo AM et al (1995) Gene expression and cellular content of cathepsin D in Alzheimer’s disease brain: evidence for early up-regulation of the endosomal-lysosomal system. Neuron 14, 671–680

    Article  PubMed  CAS  Google Scholar 

  11. Cataldo AM et al (1996) Properties of the endosomal-lysosomal system in the human central nervous system: disturbances mark most neurons in populations at risk to degenerate in Alzheimer’s disease. J Neurosci 16, 186–199

    PubMed  CAS  Google Scholar 

  12. Nixon RA et al (2000) The endosomal-lysosomal system of neurons in Alzheimer’s disease pathogenesis: a review. Neurochem Res 25, 1161–1172

    Article  PubMed  CAS  Google Scholar 

  13. Weeraratna AT et al (2007) Alterations in immunological and neurological gene expression patterns in Alzheimer’s disease tissues. Exp Cell Res 313, 450–461

    Article  PubMed  CAS  Google Scholar 

  14. Cui JG et al (2007) Expression of inflammatory genes in the primary visual cortex of late-stage Alzheimer’s disease. Neuroreport 18, 115–119

    Article  PubMed  CAS  Google Scholar 

  15. Maes OC et al (2006) Transcriptional profiling of Alzheimer blood mononuclear cells by microarray. Neurobiol Aging 28, 1795–1809

    Article  PubMed  Google Scholar 

  16. Perese DA et al (1989) A 6-hydroxydopamine-induced selective parkinsonian rat model. Brain Res 494, 285–293

    Article  PubMed  CAS  Google Scholar 

  17. Grunblatt E et al (2001) Gene expression analysis in N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mice model of Parkinson’s disease using cDNA microarray: effect of R-apomorphine. J Neurochem 78, 1–12

    Article  PubMed  CAS  Google Scholar 

  18. Mandel S et al (2003) Genes and oxidative stress in parkinsonism: cDNA microarray studies. Adv Neurol 91, 123–132

    PubMed  CAS  Google Scholar 

  19. Hauser MA et al (2005) Expression profiling of substantia nigra in Parkinson disease, progressive supranuclear palsy, and frontotemporal dementia with parkinsonism. Arch Neurol 62, 917–921

    Article  PubMed  Google Scholar 

  20. Mandel S et al (2005) Gene expression profiling of sporadic Parkinson’s disease substantia nigra pars compacta reveals impairment of ubiquitin-proteasome subunits, SKP1A, aldehyde dehydrogenase, and chaperone HSC-70. Ann NY Acad Sci 1053, 356–375

    Article  PubMed  CAS  Google Scholar 

  21. Duke DC et al (2006) Transcriptome analysis reveals link between proteasomal and mitochondrial pathways in Parkinson’s disease. Neurogenetics 7, 139–148

    Article  PubMed  CAS  Google Scholar 

  22. Holtz WA, O’Malley KL (2003) Parkinsonian mimetics induce aspects of unfolded protein response in death of dopaminergic neurons. J Biol Chem 278, 19367–19377

    Article  PubMed  CAS  Google Scholar 

  23. Hauser SL, Goodin DS (2005) Multiple sclerosis and other demyelinating diseases. In: Braunwald et al (eds): Harrison’s Principles in Internal Medicine. McGraw-Hill, New York, 2461–2471

    Google Scholar 

  24. Compston A (1999) The genetic epidemiology of multiple sclerosis. Philos Trans R Soc Lond B Biol Sci 354, 1623–1634.

    Article  PubMed  CAS  Google Scholar 

  25. Oksenberg JR et al (2001) Multiple sclerosis: genomic rewards. J Neuroimmunol 113, 171–184

    Article  PubMed  CAS  Google Scholar 

  26. Becker KG et al (1997) Analysis of a sequenced cDNA library from multiple sclerosis lesions. J Neuroimmunol 77, 27–38

    Article  PubMed  CAS  Google Scholar 

  27. Whitney LW et al (1999) Analysis of gene expression in mutiple sclerosis lesions using cDNA microarrays. Ann Neurol 46, 425–428

    Article  PubMed  CAS  Google Scholar 

  28. Chabas D et al (2001) The influence of the proinflammatory cytokine, osteopontin, on autoimmune demyelinating disease. Science 294, 1731–1735

    Article  PubMed  CAS  Google Scholar 

  29. vanNoort JM et al (1995) The small heat-shock protein alpha B-crystallin as candidate autoantigen in multiple sclerosis. Nature 375, 798–801

    Article  PubMed  Google Scholar 

  30. Ramanathan M et al (2001) In vivo gene expression revealed by cDNA arrays: the pattern in relapsing-remitting multiple sclerosis patients compared with normal subjects. J Neuroimmunol 116, 213–219.

    Article  PubMed  CAS  Google Scholar 

  31. Mycko MP et al (2003) cDNA microarray analysis in multiple sclerosis lesions: detection of genes associated with disease activity. Brain 126, 1048–1057

    Article  PubMed  Google Scholar 

  32. Graumann U et al (2003) Molecular changes in normal appearing white matter in multiple sclerosis are characteristic of neuroprotective mechanisms against hypoxic insult. Brain Pathol 13, 554–573

    PubMed  CAS  Google Scholar 

  33. Mycko MP et al (2004) Microarray gene expression profiling of chronic active and inactive lesions in multiple sclerosis. Clin Neurol Neurosurg 106, 223–229

    Article  PubMed  Google Scholar 

  34. Lindberg RL et al (2004) Multiple sclerosis as a generalized CNS disease-comparative microarray analysis of normal appearing white matter and lesions in secondary progressive MS. J Neuroimmunol 152, 154–167

    Article  PubMed  CAS  Google Scholar 

  35. Lock C et al (2002) Gene-microarray analysis of multiple sclerosis lesions yields new targets validated in autoimmune encephalomyelitis. Nat Med 8, 500–508.

    Article  PubMed  CAS  Google Scholar 

  36. Matejuk A et al (2003) CNS gene expression pattern associated with spontaneous experimental autoimmune encephalomyelitis. J Neurosci Res 73, 667–678

    Article  PubMed  CAS  Google Scholar 

  37. Whitney LW et al (2001) Microarray analysis of gene expression in multiple sclerosis and EAE identifies 5-lipoxygenase as a component of inflammatory lesions. J Neuroimmunol 21, 40–48

    Article  Google Scholar 

  38. Carmody RJ et al (2002) Genomic scale profiling of autoimmune inflammation in the central nervous system: the nervous response to inflammation. J Neuroimmunol 133, 95–107

    Article  PubMed  CAS  Google Scholar 

  39. Mix E et al (2004) Gene-expression profiling of the early stages of MOG-induced EAE proves EAE-resistance as an active process. J Neuroimmunol 151, 158–170

    Article  Google Scholar 

  40. Baranzini SE et al (2005) Modular transcriptional activity characterizes the initiation and progression of autoimmune encephalomyelitis. J Immunol 174, 7412–7422

    PubMed  CAS  Google Scholar 

  41. Dutta R et al (2006) Mitochondrial dysfunction as a cause of axonal degeneration in multiple sclerosis patients. Ann Neurol 59, 478–489

    Article  PubMed  CAS  Google Scholar 

  42. Satoh J et al (2005) Microarray analysis identifies an aberrant expression of apoptosis and DNA damage-regulatory genes in multiple sclerosis. Neurobiol Dis 18, 537–550

    Article  PubMed  CAS  Google Scholar 

  43. Mirnics K et al (2000) Molecular characterization of schizophrenia viewed by microarray analysis of gene expression in prefrontal cortex. Neuron 28, 53–67

    Article  PubMed  CAS  Google Scholar 

  44. Hemby SE et al (2002) Gene expression profile for schizophrenia: discrete neuron transcription patterns in the entorhinal cortex. Arch Gen Psychiatry 59, 631–640

    Article  PubMed  CAS  Google Scholar 

  45. Middleton FA et al (2002) Gene expression profiling reveals alterations of specific metabolic pathways in schizophrenia. J Neurosci 22, 2718–2729

    PubMed  CAS  Google Scholar 

  46. Vawter MP et al (2002) Microarray analysis of gene expression in the prefrontal cortex in schizophrenia: a preliminary study. Schizophr Res 58, 11–20

    Article  PubMed  Google Scholar 

  47. Tkachev D et al (2003) Oligodendrocyte dysfunction in schizophrenia and bipolar disorder. Lancet 362, 798–805

    Article  PubMed  CAS  Google Scholar 

  48. Chowdari KV et al (2002) Association and linkage analyses of RGS4 polymorphisms in schizophrenia. Hum Mol Genet 11, 1373–1380

    Article  PubMed  CAS  Google Scholar 

  49. Williams NM et al (2004) Support for RGS4 as a susceptibility gene for schizophrenia. Biol Psychiatry 55, 192–195

    Article  PubMed  CAS  Google Scholar 

  50. Morris DW et al (2004) Confirming RGS4 as a susceptibility gene for schizophrenia. Am J Med Genet 125B, 50–53

    Article  Google Scholar 

  51. Hakak Y et al (2001) Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia. Proc Natl Acad Sci USA 98, 4746–4751

    Article  PubMed  CAS  Google Scholar 

  52. Pongrac J et al (2002) Gene expression profiling with DNA microarrays: advancing our understanding of psychiatric disorders. Neurochem Res 27, 1049–1063

    Article  PubMed  CAS  Google Scholar 

  53. Yeo CH et al (1985) Classical conditioning of the nictitating membrane response of the rabbit. I. Lesions of the cerebellar nuclei. Exp Brain Res 60, 87–98

    Article  PubMed  CAS  Google Scholar 

  54. Sweeney JA et al (1996) Positron emission tomography study of voluntary saccadic eye movements and spatial working memory. J Neurophysiol 75, 454–468

    PubMed  CAS  Google Scholar 

  55. Ohta M (1998) [Changes in spatio-temporal patterns after long-term potentiation (LTP) in mouse hippocampal slices and effects of trichloroethylene on LTP]. Hokkaido Igaku Zasshi 73, 365–378

    PubMed  CAS  Google Scholar 

  56. Cavallaro S et al (2001) Gene expression profiles during long-term memory consolidation. Eur J Neurosci 13, 1809–1815

    Article  PubMed  CAS  Google Scholar 

  57. Leil TA et al (2002) Finding new candidate genes for learning and memory. J Neurosci Res 68, 127–137

    Article  PubMed  CAS  Google Scholar 

  58. Bajorek JG et al (1986) Neuropeptides: anticonvulsant and convulsant mechanisms in epileptic model systems and in humans. Adv Neurol 44, 489–500

    PubMed  CAS  Google Scholar 

  59. White JD, Gall CM (1986) Increased enkephalin gene expression in the hippocampus following seizures. NIDA Res Monogr 75, 393–396

    PubMed  CAS  Google Scholar 

  60. White JD, Gall CM (1987) Differential regulation of neuropeptide and proto-oncogene mRNA content in the hippocampus following recurrent seizures. Brain Res 427, 21–29

    PubMed  CAS  Google Scholar 

  61. Morgan JI et al (1987) Mapping patterns of c-fos expression in the central nervous system after seizure. Science 237, 192–197

    Article  PubMed  CAS  Google Scholar 

  62. Sonnenberg JL et al (1989) Regulation of proenkephalin by Fos and Jun. Science 246, 1622–1625

    Article  PubMed  CAS  Google Scholar 

  63. French PJ et al (2001) Seizure-induced gene expression in area CA1 of the mouse hippocampus. Eur J Neurosci 14, 2037–2041

    Article  PubMed  CAS  Google Scholar 

  64. Yun J et al (2003) Gene expression profile of neurodegeneration induced by alpha1B-adrenergic receptor overactivity: NMDA/GABAA dysregulation and apoptosis. Brain 126, 2667–2681

    Article  PubMed  Google Scholar 

  65. Elliott RC et al (2003) Overlapping microarray profiles of dentate gyrus gene expression during development-and epilepsy-associated neurogenesis and axon outgrowth. J Neurosci 23, 2218–2227

    PubMed  CAS  Google Scholar 

  66. Lee TS et al (2007) Gene expression in temporal lobe epilepsy is consistent with increased release of glutamate by astrocytes. Mol Med 13, 1–13

    PubMed  CAS  Google Scholar 

  67. Jamali S et al (2006) Large-scale expression study of human mesial temporal lobe epilepsy: evidence for dysregulation of the neurotransmission and complement systems in the entorhinal cortex. Brain 129, 625–641

    Article  PubMed  Google Scholar 

  68. Arion D et al (2006) Correlation of transcriptome profile with electrical activity in temporal lobe epilepsy. Neurobiol Dis 22, 374–387

    Article  PubMed  CAS  Google Scholar 

  69. Marciano PG et al (2002) Expression profiling following traumatic brain injury: a review. Neurochem Res 27, 1147–1155

    Article  PubMed  CAS  Google Scholar 

  70. Matzilevich DA et al (2002) High-density microarray analysis of hippocampal gene expression following experimental brain injury. J Neurosci Res 67, 646–663

    Article  PubMed  CAS  Google Scholar 

  71. Dash PK et al (2004) A molecular description of brain trauma pathophysiology using microarray technology: an overview. Neurochem Res 29, 1275–1286

    Article  PubMed  CAS  Google Scholar 

  72. Moore DFet al (2005) Using peripheral blood mononuclear cells to determine a gene expression profile of acute ischemic stroke: a pilot investigation. Circulation 111, 212–221

    Article  PubMed  CAS  Google Scholar 

  73. Tang Yet al (2006) Gene expression in blood changes rapidly in neutrophils and monocytes after ischemic stroke in humans: a microarray study. J Cereb Blood Flow Metab 26, 1089–1102

    Article  PubMed  CAS  Google Scholar 

  74. Kitano H (2002) Systems biology: a brief overview. Science 295, 1662–1664

    Article  PubMed  CAS  Google Scholar 

  75. Morel NM et al (2004) Primer on medical genomics. Part XIV: Introduction to systems biology — a new approach to understanding disease and treatment. Mayo Clin Proc 79, 651–658

    Article  PubMed  CAS  Google Scholar 

  76. Somogyi R et al (2006) Advanced data mining and predictive modeling at the core of personalized medicine. In: Paton & McNamara (eds): Multidisciplinary Approaches to Theory in Medicine, Vol. 3 Elsevier, Amsterdam, 165–192

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Neurology, School of Medicine, University of California, San Francisco, Medical Sciences Building S-256, 513 Parnassus Ave., San Francisco, CA, 94143, USA

    Sergio E. Baranzini

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  1. Sergio E. Baranzini
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Editors and Affiliations

  1. Research & Development, Miltenyi Biotec GmbH, Friedrich-Ebert-Straße 68, 51429 Bergisch, Gladbach, Germany

    Andreas Bosio

  2. Miltenyi Biotec GmbH, Friedrich-Ebert-Straße 68, 51429 Bergisch, Gladbach, Germany

    Bernhard Gerstmayer

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© 2008 Birkhäuser Verlag Basel/Switzerland

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Baranzini, S.E. (2008). Gene expression profiling in neurological and neuroinflammatory diseases. In: Bosio, A., Gerstmayer, B. (eds) Microarrays in Inflammation. Progress in Inflammation Research. Birkhäuser Basel. https://doi.org/10.1007/978-3-7643-8334-3_11

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