The Panomics Approach in Neurodegenerative Disorders

Page: [1712 - 1720] Pages: 9

  • * (Excluding Mailing and Handling)

Abstract

Background: The molecular genetic technologies revolutionized the diagnostics of many disorders. Thanks to the new molecular techniques and the rapid improvement of the information technologies the number of mendelien inherited disorders has increased rapidly in the last five years. The omics era brought radical changes in the understanding of complex disorders and the underlying pathomechanisms. However, in most complex disorders the genome wide association studies could not clarify the genetic background even for disorders where a very strong heritability had been observed.

Objective: In this paper the changing concept of the neurodegenerative disorders is discussed. The traditional classification of these disorders was purely based on clinical symptoms and morphological signs in the last century. Identifying the signature lesions of various neurodegenerative disorders may reveal a common pathological pathway in these disorders. New neuroimaging methods provided additional tools to assess pathological pathways in vivo already in the early stages of the diseases. Visualizing in vivo amyloid deposits and neuroinflammation improved our understanding of their role in various neurodegenerative disorders. Genetics may be the most precise way to identify the background of these disorders. However, there is only limited number of cases where true association can be proved between the disorder and the genetic mutations. Most of the neurodegenerative disorders seem to be multifactorial and cannot be traced back to one single cause.

Conclusion: In conclusion, shifting from a classification based on symptomatology only to a modern multidisciplinary approach, based on the constantly evolving panomics findings, would improve our understanding of neurodegenerative diseases and could be the basis of novel therapeutic research.

Keywords: Omics, classification, neurodegenerative disorders, multidisciplinary approach, genetics, imaging.

[1]
Gorman, A.M. Neuronal cell death in neurodegenerative diseases: recurring themes around protein handling. J. Cell. Mol. Med., 2008, 12(6a), 2263-2280.
[2]
Ferrer, I.; Lopez-Gonzalez, I.; Carmona, M.; Arregui, L.; Dalfo, E.; Torrejon-Escribano, B.; Diehl, R.; Kovacs, G.G. Glial and neuronal tau pathology in tauopathies: characterization of disease-specific phenotypes and tau pathology progression. J. Neuropathol. Exp. Neurol., 2014, 73(1), 81-97.
[3]
Cheng, L.; Alexander, R.E.; Maclennan, G.T.; Cummings, O.W.; Montironi, R.; Lopez-Beltran, A.; Cramer, H.M.; Davidson, D.D.; Zhang, S. Molecular pathology of lung cancer: key to personalized medicine. Mod. Pathol., 2012, 25(3), 347-369.
[4]
Korpanty, G.J.; Graham, D.M.; Vincent, M.D.; Leighl, N.B. Biomarkers that currently affect clinical practice in lung cancer: EGFR, ALK, MET, ROS-1, and KRAS. Front. Oncol., 2014, 4, 204.
[5]
Mall, M.A.; Galietta, L.J. Targeting ion channels in cystic fibrosis. J. Cyst. Fibros., 2015, 14(5), 561-570.
[6]
Hoffman, L.R.; Ramsey, B.W. Cystic fibrosis therapeutics: the road ahead. Chest, 2013, 143(1), 207-213.
[7]
Welsh, M.J.; Smith, A.E. Molecular mechanisms of CFTR chloride channel dysfunction in cystic fibrosis. Cell, 1993, 73(7), 1251-1254.
[8]
Bompadre, S.G.; Sohma, Y.; Li, M.; Hwang, T.C. G551D and G1349D, two CF-associated mutations in the signature sequences of CFTR, exhibit distinct gating defects. J. Gen. Physiol., 2007, 129(4), 285-298.
[9]
Armstrong, R.A. On the ‘classification’ of neurodegenerative disorders: discrete entities, overlap or continuum? Folia neuropathologica / association of polish neuropathologists and medical research centre. Polish Acad. Sci., 2012, 50(3), 201-208.
[10]
Williams-Gray, C.H.; Foltynie, T.; Lewis, S.J.; Barker, R.A. Cognitive deficits and psychosis in Parkinson’s disease: a review of pathophysiology and therapeutic options. CNS Drugs, 2006, 20(6), 477-505.
[11]
Paulsen, J.S. Cognitive impairment in Huntington disease: diagnosis and treatment. Curr. Neurol. Neurosci. Rep., 2011, 11(5), 474-483.
[12]
Cairns, N.J.; Bigio, E.H.; Mackenzie, I.R.; Neumann, M.; Lee, V.M.; Hatanpaa, K.J.; White, C.L., III; Schneider, J.A.; Grinberg, L.T.; Halliday, G.; Duyckaerts, C.; Lowe, J.S.; Holm, I.E.; Tolnay, M.; Okamoto, K.; Yokoo, H.; Murayama, S.; Woulfe, J.; Munoz, D.G.; Dickson, D.W.; Ince, P.G.; Trojanowski, J.Q.; Mann, D.M. Neuropathologic diagnostic and nosologic criteria for frontotemporal lobar degeneration: consensus of the consortium for frontotemporal lobar degeneration. Acta Neuropathol., 2007, 114(1), 5-22.
[13]
Mackenzie, I.R.; Rademakers, R.; Neumann, M. TDP-43 and FUS in amyotrophic lateral sclerosis and frontotemporal dementia. Lancet Neurol., 2010, 9(10), 995-1007.
[14]
Lei, P.; Ayton, S.; Finkelstein, D.I.; Adlard, P.A.; Masters, C.L.; Bush, A.I. Tau protein: relevance to Parkinson’s disease. Int. J. Biochem. Cell Biol., 2010, 42(11), 1775-1778.
[15]
Klunemann, H.H.; Fronhofer, W.; Wurster, H.; Fischer, W.; Ibach, B.; Klein, H.E. Alzheimer’s second patient: Johann F. and his family. Ann. Neurol., 2002, 52(4), 520-523.
[16]
Villemagne, V.L.; Pike, K.E.; Chetelat, G.; Ellis, K.A.; Mulligan, R.S.; Bourgeat, P.; Ackermann, U.; Jones, G.; Szoeke, C.; Salvado, O.; Martins, R.; O’Keefe, G.; Mathis, C.A.; Klunk, W.E.; Ames, D.; Masters, C.L.; Rowe, C.C. Longitudinal assessment of Abeta and cognition in aging and Alzheimer disease. Ann. Neurol., 2011, 69(1), 181-192.
[17]
Johnson, K.A.; Minoshima, S.; Bohnen, N.I.; Donohoe, K.J.; Foster, N.L.; Herscovitch, P.; Karlawish, J.H.; Rowe, C.C.; Carrillo, M.C.; Hartley, D.M.; Hedrick, S.; Pappas, V.; Thies, W.H. Appropriate use criteria for amyloid PET: a report of the Amyloid Imaging Task Force, the Society of Nuclear Medicine and Molecular Imaging, and the Alzheimer’s Association. Alzheimers Dement., 2013, 9(1), e-1-e-16.
[18]
Ching, A.S.C.; Kuhnast, B.; Damont, A.; Roeda, D.; Tavitian, B.; Dollé, F. Current paradigm of the 18-kDa translocator protein (TSPO) as a molecular target for PET imaging in neuroinflammation and neurodegenerative diseases. Insights Imaging, 2012, 3(1), 111-119.
[19]
Cagnin, A.; Brooks, D.J.; Kennedy, A.M.; Gunn, R.N.; Myers, R.; Turkheimer, F.E.; Jones, T.; Banati, R.B. In-vivo measurement of activated microglia in dementia. Lancet (London, England), 2001, 358(9280), 461-467.
[20]
Politis, M.; Su, P.; Piccini, P. Imaging of microglia in patients with neurodegenerative disorders. Front. Pharmacol., 2012, 3, 96.
[21]
Imamura, K.; Hishikawa, N.; Sawada, M.; Nagatsu, T.; Yoshida, M.; Hashizume, Y. Distribution of major histocompatibility complex class II-positive microglia and cytokine profile of Parkinson’s disease brains. Acta Neuropathol., 2003, 106(6), 518-526.
[22]
Sanchez-Guajardo, V.; Febbraro, F.; Kirik, D.; Romero-Ramos, M. Microglia acquire distinct activation profiles depending on the degree of alpha-synuclein neuropathology in a rAAV based model of Parkinson’s disease. PLoS One, 2010, 5(1)e8784
[23]
Bartels, A.L.; Willemsen, A.T.; Doorduin, J.; de Vries, E.F.; Dierckx, R.A.; Leenders, K.L. [11C]-PK11195 PET: quantification of neuroinflammation and a monitor of anti-inflammatory treatment in Parkinson’s disease? Parkinsonism Relat. Disord., 2010, 16(1), 57-59.
[24]
Gerhard, A.; Trender-Gerhard, I.; Turkheimer, F.; Quinn, N.P.; Bhatia, K.P.; Brooks, D.J. In vivo imaging of microglial activation with [11C](R)-PK11195 PET in progressive supranuclear palsy. Mov. Disord., 2006, 21(1), 89-93.
[25]
Politis, M.; Pavese, N.; Tai, Y.F.; Tabrizi, S.J.; Barker, R.A.; Piccini, P. Hypothalamic involvement in Huntington’s disease: an in vivo PET study. Brain, 2008, 131(Pt 11), 2860-2869.
[26]
Politis, M.; Pavese, N.; Tai, Y.F.; Kiferle, L.; Mason, S.L.; Brooks, D.J.; Tabrizi, S.J.; Barker, R.A.; Piccini, P. Microglial activation in regions related to cognitive function predicts disease onset in Huntington’s disease: a multimodal imaging study. Hum. Brain Mapp., 2011, 32(2), 258-270.
[27]
Gerhard, A.; Banati, R.B.; Goerres, G.B.; Cagnin, A.; Myers, R.; Gunn, R.N.; Turkheimer, F.; Good, C.D.; Mathias, C.J.; Quinn, N.; Schwarz, J.; Brooks, D.J. [11C](R)-PK11195 PET imaging of microglial activation in multiple system atrophy. Neurology, 2003, 61(5), 686-689.
[28]
Gerhard, A.; Watts, J.; Trender-Gerhard, I.; Turkheimer, F.; Banati, R.B.; Bhatia, K.; Brooks, D.J. In vivo imaging of microglial activation with [11C](R)-PK11195 PET in corticobasal degeneration. Mov. Disord., 2004, 19(10), 1221-1226.
[29]
Banati, R.B.; Newcombe, J.; Gunn, R.N.; Cagnin, A.; Turkheimer, F.; Heppner, F.; Price, G.; Wegner, F.; Giovannoni, G.; Miller, D.H.; Perkin, G.D.; Smith, T.; Hewson, A.K.; Bydder, G.; Kreutzberg, G.W.; Jones, T.; Cuzner, M.L.; Myers, R. The peripheral benzodiazepine binding site in the brain in multiple sclerosis: quantitative in vivo imaging of microglia as a measure of disease activity. Brain, 2000, 123(Pt 11), 2321-2337.
[30]
Hardy, J.; Orr, H. The genetics of neurodegenerative diseases. J. Neurochem., 2006, 97(6), 1690-1699.
[31]
Bettens, K.; Sleegers, K.; Van Broeckhoven, C. Genetic insights in Alzheimer’s disease. Lancet Neurol., 2013, 12(1), 92-104.
[32]
Farrer, L.A.; Cupples, L.; Haines, J.L. Effects of age, sex, and ethnicity on the association between apolipoprotein e genotype and alzheimer disease: A meta-analysis. JAMA, 1997, 278(16), 1349-1356.
[33]
Lambert, J-C.; Ibrahim-Verbaas, C.A.; Harold, D.; Naj, A.C.; Sims, R.; Bellenguez, C.; Jun, G.; DeStefano, A.L.; Bis, J.C.; Beecham, G.W.; Grenier-Boley, B.; Russo, G.; Thornton-Wells, T.A.; Jones, N.; Smith, A.V.; Chouraki, V.; Thomas, C.; Ikram, M.A.; Zelenika, D.; Vardarajan, B.N.; Kamatani, Y.; Lin, C-F.; Gerrish, A.; Schmidt, H.; Kunkle, B.; Dunstan, M.L.; Ruiz, A.; Bihoreau, M-T.; Choi, S-H.; Reitz, C.; Pasquier, F.; Hollingworth, P.; Ramirez, A.; Hanon, O.; Fitzpatrick, A.L.; Buxbaum, J.D.; Campion, D.; Crane, P.K.; Baldwin, C.; Becker, T.; Gudnason, V.; Cruchaga, C.; Craig, D.; Amin, N.; Berr, C.; Lopez, O.L.; De Jager, P.L.; Deramecourt, V.; Johnston, J.A.; Evans, D.; Lovestone, S.; Letenneur, L.; Moron, F.J.; Rubinsztein, D.C.; Eiriksdottir, G.; Sleegers, K.; Goate, A.M.; Fievet, N.; Huentelman, M.J.; Gill, M.; Brown, K.; Kamboh, M.I.; Keller, L.; Barberger-Gateau, P.; McGuinness, B.; Larson, E.B.; Green, R.; Myers, A.J.; Dufouil, C.; Todd, S.; Wallon, D.; Love, S.; Rogaeva, E.; Gallacher, J.; St George-Hyslop, P.; Clarimon, J.; Lleo, A.; Bayer, A.; Tsuang, D.W.; Yu, L.; Tsolaki, M.; Bossu, P.; Spalletta, G.; Proitsi, P.; Collinge, J.; Sorbi, S.; Sanchez-Garcia, F.; Fox, N.C.; Hardy, J.; Naranjo, M.C.D.; Bosco, P.; Clarke, R.; Brayne, C.; Galimberti, D.; Mancuso, M.; Matthews, F. European Alzheimer’s Disease, I.; Genetic; Environmental Risk in Alzheimer’s, D.; Alzheimer’s Disease Genetic, C.; Cohorts for, H.; Aging Research in Genomic, E.; Moebus, S.; Mecocci, P.; Del Zompo, M.; Maier, W.; Hampel, H.; Pilotto, A.; Bullido, M.; Panza, F.; Caffarra, P.; Nacmias, B.; Gilbert, J.R.; Mayhaus, M.; Lannfelt, L.; Hakonarson, H.; Pichler, S.; Carrasquillo, M.M.; Ingelsson, M.; Beekly, D.; Alvarez, V.; Zou, F.; Valladares, O.; Younkin, S.G.; Coto, E.; Hamilton-Nelson, K.L.; Gu, W.; Razquin, C.; Pastor, P.; Mateo, I.; Owen, M.J.; Faber, K.M.; Jonsson, P.V.; Combarros, O.; O’Donovan, M.C.; Cantwell, L.B.; Soininen, H.; Blacker, D.; Mead, S.; Mosley Jr, T.H.; Bennett, D.A.; Harris, T.B.; Fratiglioni, L.; Holmes, C.; de Bruijn, R.F.A.G.; Passmore, P.; Montine, T.J.; Bettens, K.; Rotter, J.I.; Brice, A.; Morgan, K.; Foroud, T.M.; Kukull, W.A.; Hannequin, D.; Powell, J.F.; Nalls, M.A.; Ritchie, K.; Lunetta, K.L.; Kauwe, J.S.K.; Boerwinkle, E.; Riemenschneider, M.; Boada, M.; Hiltunen, M.; Martin, E.R.; Schmidt, R.; Rujescu, D.; Wang, L.-S.; Dartigues, J.-F.; Mayeux, R.; Tzourio, C.; Hofman, A.; Nothen, M.M.; Graff, C.; Psaty, B.M.; Jones, L.; Haines, J.L.; Holmans, P.A.; Lathrop, M.; Pericak-Vance, M.A.; Launer, L.J.; Farrer, L.A.; van Duijn, C.M.; Van Broeckhoven, C.; Moskvina, V.; Seshadri, S.; Williams, J.; Schellenberg, G.D.; Amouyel, P., Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat. Genet., 2013, 45(12), 1452-1458.
[34]
Guerreiro, R.; Wojtas, A.; Bras, J.; Carrasquillo, M.; Rogaeva, E.; Majounie, E.; Cruchaga, C.; Sassi, C.; Kauwe, J.S.K.; Younkin, S.; Hazrati, L.; Collinge, J.; Pocock, J.; Lashley, T.; Williams, J.; Lambert, J.C.; Amouyel, P.; Goate, A.; Rademakers, R.; Morgan, K.; Powell, J.; St George-Hyslop, P.; Singleton, A.; Hardy, J. Alzheimer genetic anal, G., TREM2 variants in Alzheimer’s disease. N. Engl. J. Med., 2013, 368(2), 117-127.
[35]
Jonsson, T.; Stefansson, H.; Steinberg, S.; Jonsdottir, I.; Jonsson, P.V.; Snaedal, J.; Bjornsson, S.; Huttenlocher, J.; Levey, A.I.; Lah, J.J.; Rujescu, D.; Hampel, H.; Giegling, I.; Andreassen, O.A.; Engedal, K.; Ulstein, I.; Djurovic, S.; Ibrahim-Verbaas, C.; Hofman, A.; Ikram, M.A.; van Duijn, C.M.; Thorsteinsdottir, U.; Kong, A.; Stefansson, K. Variant of TREM2 associated with the risk of Alzheimer’s disease. N. Engl. J. Med., 2013, 368(2), 107-116.
[36]
Finelli, D.; Rollinson, S.; Harris, J.; Jones, M.; Richardson, A.; Gerhard, A.; Snowden, J.; Mann, D.; Pickering-Brown, S. TREM2 analysis and increased risk of Alzheimer’s disease. Neurobiol. Aging, 2015, 36(1), 546.e549-546.e513.
[37]
Lu, Y.; Liu, W.; Wang, X. TREM2 variants and risk of Alzheimer’s disease: a meta-analysis. Neurol. Sci., 2015, 36(10), 1881-1888.
[38]
Jin, S.C.; Carrasquillo, M.M.; Benitez, B.A.; Skorupa, T.; Carrell, D.; Patel, D.; Lincoln, S.; Krishnan, S.; Kachadoorian, M.; Reitz, C.; Mayeux, R.; Wingo, T.S.; Lah, J.J.; Levey, A.I.; Murrell, J.; Hendrie, H.; Foroud, T.; Graff-Radford, N.R.; Goate, A.M.; Cruchaga, C.; Ertekin-Taner, N. TREM2 is associated with increased risk for Alzheimer’s disease in African Americans. Mol. Neurodegener., 2015, 10, 19.
[39]
Lill, C.M.; Rengmark, A.; Pihlstrøm, L.; Fogh, I.; Shatunov, A.; Sleiman, P.M.; Wang, L.S.; Liu, T.; Lassen, C.F.; Meissner, E.; Alexopoulos, P.; Calvo, A.; Chio, A.; Dizdar, N.; Faltraco, F.; Forsgren, L.; Kirchheiner, J.; Kurz, A.; Larsen, J.P.; Liebsch, M.; Linder, J.; Morrison, K.E.; Nissbrandt, H.; Otto, M.; Pahnke, J.; Partch, A.; Restagno, G.; Rujescu, D.; Schnack, C.; Shaw, C.E.; Shaw, P.J.; Tumani, H.; Tysnes, O.B.; Valladares, O.; Silani, V.; van den Berg, L.H.; van Rheenen, W.; Veldink, J.H.; Lindenberger, U.; Steinhagen-Thiessen, E.; Teipel, S.; Perneczky, R.; Hakonarson, H.; Hampel, H.; von Arnim, C.A.F.; Olsen, J.H.; Van Deerlin, V.M.; Al-Chalabi, A.; Toft, M.; Ritz, B.; Bertram, L. The role of TREM2 R47H as a risk factor for Alzheimer’s disease, frontotemporal lobar degeneration, amyotrophic lateral sclerosis, and Parkinson’s disease. Alzheimers Dement., 2015, 11(12), 1407-1416.
[40]
Jonsson, T.; Atwal, J.K.; Steinberg, S.; Snaedal, J.; Jonsson, P.V.; Bjornsson, S.; Stefansson, H.; Sulem, P.; Gudbjartsson, D.; Maloney, J.; Hoyte, K.; Gustafson, A.; Liu, Y.; Lu, Y.; Bhangale, T.; Graham, R.R.; Huttenlocher, J.; Bjornsdottir, G.; Andreassen, O.A.; Jonsson, E.G.; Palotie, A.; Behrens, T.W.; Magnusson, O.T.; Kong, A.; Thorsteinsdottir, U.; Watts, R.J.; Stefansson, K. A mutation in APP protects against Alzheimer’s disease and age-related cognitive decline. Nature, 2012, 488(7409), 96-99.
[41]
Carrell, R.W.; Lomas, D.A. Conformational disease. Lancet, 1997, 350(9071), 134-138.
[42]
Kovacs, G.G. Molecular pathological classification of neurodegenerative diseases: Turning towards precision medicine. Int. J. Mol. Sci., 2016, 17(2), 189.
[43]
Kovacs, G.G. Current concepts of neurodegenerative diseases. Eur. Med. J. Neurol., 2014, 1, 78-86.
[44]
Neumann, M.; Bentmann, E.; Dormann, D.; Jawaid, A.; DeJesus-Hernandez, M.; Ansorge, O.; Roeber, S.; Kretzschmar, H.A.; Munoz, D.G.; Kusaka, H.; Yokota, O.; Ang, L.C.; Bilbao, J.; Rademakers, R.; Haass, C.; Mackenzie, I.R. FET proteins TAF15 and EWS are selective markers that distinguish FTLD with FUS pathology from amyotrophic lateral sclerosis with FUS mutations. Brain, 2011, 134(Pt 9), 2595-2609.
[45]
Valera, E.; Spencer, B.; Masliah, E. Immunotherapeutic approaches targeting amyloid-β, α-synuclein, and tau for the treatment of neurodegenerative disorders. Neurotherapeutics, 2016, 13(1), 179-189.
[46]
Panza, F.; Solfrizzi, V.; Imbimbo, B.P.; Giannini, M.; Santamato, A.; Seripa, D.; Logroscino, G. Efficacy and safety studies of gantenerumab in patients with Alzheimer’s disease. Expert Rev. Neurother., 2014, 14(9), 973-986.
[47]
Farlow, M.; Arnold, S.E.; van Dyck, C.H.; Aisen, P.S.; Snider, B.J.; Porsteinsson, A.P.; Friedrich, S.; Dean, R.A.; Gonzales, C.; Sethuraman, G.; DeMattos, R.B.; Mohs, R.; Paul, S.M.; Siemers, E.R. Safety and biomarker effects of solanezumab in patients with Alzheimer’s disease. Alzheimers Dement., 2012, 8(4), 261-271.
[48]
Giuliani, D.; Zaffe, D.; Ottani, A.; Spaccapelo, L.; Galantucci, M.; Minutoli, L.; Bitto, A.; Irrera, N.; Contri, M.; Altavilla, D.; Botticelli, A.R.; Squadrito, F.; Guarini, S. Treatment of cerebral ischemia with melanocortins acting at MC4 receptors induces marked neurogenesis and long-lasting functional recovery. Acta Neuropathol., 2011, 122(4), 443-453.
[49]
Giuliani, D.; Bitto, A.; Galantucci, M.; Zaffe, D.; Ottani, A.; Irrera, N.; Neri, L.; Cavallini, G.M.; Altavilla, D.; Botticelli, A.R.; Squadrito, F.; Guarini, S. Melanocortins protect against progression of Alzheimer’s disease in triple-transgenic mice by targeting multiple pathophysiological pathways. Neurobiol. Aging, 2014, 35(3), 537-547.
[50]
Giuliani, D.; Ottani, A.; Minutoli, L.; Stefano, V.D.; Galantucci, M.; Bitto, A.; Zaffe, D.; Altavilla, D.; Botticelli, A.R.; Squadrito, F.; Guarini, S. Functional recovery after delayed treatment of ischemic stroke with melanocortins is associated with overexpression of the activity-dependent gene Zif268. Brain Behav. Immun., 2009, 23(6), 844-850.
[51]
Giuliani, D.; Ottani, A.; Neri, L.; Zaffe, D.; Grieco, P.; Jochem, J.; Cavallini, G.M.; Catania, A.; Guarini, S. Multiple beneficial effects of melanocortin MC4 receptor agonists in experimental neurodegenerative disorders: therapeutic perspectives. Prog. Neurobiol., 2017, 148, 40-56.