Das visuelle System als Modell in der translationalen Forschung

Zusammenfassung

Das visuelle System bietet einzigartige Einblicke in die komplexen Mechanismen neurologischer Erkrankungen und stellt daher ein zentrales Modell in der translationalen Forschung dar. Die Netzhaut, als Teil des zentralen Nervensystems, dient als präzises Fenster, das es ermöglicht, neurodegenerative und neuroinflammatorische Prozesse zu untersuchen. Dieser Artikel beleuchtet die Anwendung des visuellen Systems in der translationalen Erforschung neurologischer Erkrankungen durch verschiedene experimentelle Modelle und Analysemethoden. Besonderes Augenmerk liegt auf der Untersuchung entzündlicher Modelle wie der Experimentellen Autoimmunen Enzephalomyelitis Optikusneuritis (EAEON), nicht-entzündlichen degenerativen Modellen wie dem Optic Nerve Crush und dem lichtinduzierten Photorezeptorverlust sowie demyelinisierenden Modellen wie dem Cuprizone-Modell sowie neurodegenerative Erkrankungen wie Demenz vom Alzheimer-Typ und idiopathisches Parkinson-Syndrom. Der Artikel stellt zudem diagnostische und funktionelle Evaluierungsmethoden wie die Optische Kohärenztomographie (OCT), konfokale Scanning Laser Ophthalmoskopie (cSLO), optomotorische Reaktions-Messung (OMR) und die Messung Visuell Evozierter Potentiale (VEP) vor. Abschließend werden ein kurzer Ausblick gegeben und die Limitationen, insbesondere bezüglich der Übertragbarkeit der Ergebnisse zwischen Tiermodellen und dem Menschen, erläutert.

Abstract

The visual system provides unique insights into the complex mechanisms of neurological diseases, thus serving as a central model in translational research. The retina, as part of the central nervous system, acts as a precise window that enables the study of neurodegenerative and neuroinflammatory processes. This article highlights the application of the visual system in the translational research of neurological diseases through various experimental models and analytical methods. Special emphasis is placed on the examination of inflammatory models such as Experimental Autoimmune Encephalomyelitis Optic Neuritis (EAEON), non-inflammatory degenerative models like Optic Nerve Crush and light-induced photoreceptor loss, as well as demyelinating models like the Cuprizone model, in addition to neurodegenerative diseases such as Alzheimer's type dementia and idiopathic Parkinson's syndrome. The article also presents diagnostic and functional evaluation methods such as Optical Coherence Tomography (OCT), confocal Scanning Laser Ophthalmoscopy (cSLO), optomotor response (OMR) measurements, and the measurement of Visually Evoked Potentials (VEP). Furthermore, a brief outlook is provided, as well as the limitations, especially regarding the extrapolatability of results from animal models to humans and vice versa.

Schlüsselwörter

OCT - VEP - Visuelles System - Retina - Translationale Evaluierungsmethoden

Keywords

OCT - VEP - visual system - retina - translational evaluation methods

Publication History

Article published online:
09 September 2024

• Literatur

• 1 Oertel FC, Hastermann M, Paul F. Delimiting MOGAD as a disease entity using translational imaging. Front Neurol 2023; 14: 1216477
• 2 Dietrich M, Koska V, Hecker C. et al. Protective effects of 4-aminopyridine in experimental optic neuritis and multiple sclerosis. Brain 2020; 143: 1127-1142
• 3 Ingwersen J, De Santi L, Wingerath B. et al. Nimodipine confers clinical improvement in two models of experimental autoimmune encephalomyelitis. J Neurochem 2018;
• 4 Levy H, Assaf Y, Frenkel D. Characterization of brain lesions in a mouse model of progressive multiple sclerosis. Exp Neurol 2010; 226: 148-158
• 5 Rothhammer V, Kenison JE, Tjon E. et al. Sphingosine 1-phosphate receptor modulation suppresses pathogenic astrocyte activation and chronic progressive CNS inflammation. Proc Natl Acad Sci USA 2017; 114: 2012-2017
• 6 Dietrich M, Hecker C, Nasiri M. et al. Neuroprotective Properties of Dimethyl Fumarate Measured by Optical Coherence Tomography in Non-inflammatory Animal Models. Front Neurol 2020; 11: 601628
• 7 Hilla AM, Diekmann H, Fischer D. Microglia Are Irrelevant for Neuronal Degeneration and Axon Regeneration after Acute Injury. J Neurosci 2017; 37: 6113-6124
• 8 Meyer R, Weissert R, Diem R. et al. Acute neuronal apoptosis in a rat model of multiple sclerosis. J Neurosci 2001; 21: 6214-6220
• 9 Sindi M, Hecker C, Issberner A. et al. S1PR-1/5 modulator RP-101074 shows beneficial effects in a model of central nervous system degeneration. Front Immunol 2023; 14: 1234984
• 10 Cordano C, Sin JH, Timmons G. et al. Validating visual evoked potentials as a preclinical, quantitative biomarker for remyelination efficacy. Brain 2022; 145: 3943-3952
• 11 Marenna S, Huang S-C, Dalla Costa G. et al. Visual Evoked Potentials to Monitor Myelin Cuprizone-Induced Functional Changes. Front Neurosci 2022; 16: 820155
• 12 Parisi V, Restuccia R, Fattapposta F. et al. Morphological and functional retinal impairment in Alzheimer’s disease patients. Clin Neurophysiol 2001; 112: 1860-1867
• 13 Loh EH-T, Ong Y-T, Venketasubramanian N. et al. Repeatability and Reproducibility of Retinal Neuronal and Axonal Measures on Spectral-Domain Optical Coherence Tomography in Patients with Cognitive Impairment. Front Neurol 2017; 8: 359
• 14 Garcia-Martin E, Larrosa JM, Polo V. et al. Distribution of retinal layer atrophy in patients with Parkinson disease and association with disease severity and duration. Am J Ophthalmol 2014; 157: 470-478.e2
• 15 Satue M, Obis J, Alarcia R. et al. Retinal and Choroidal Changes in Patients with Parkinson’s Disease Detected by Swept-Source Optical Coherence Tomography. Curr Eye Res 2018; 43: 109-115
• 16 Simonett J, Chou J, Siddique N. et al. Ocular Manifestations and Optic Nerve Changes in Patients with Amyotrophic Lateral Sclerosis (ALS). Investigative Ophthalmology & Visual Science 2013; 54: 4382-4382
• 17 Mukherjee N, McBurney-Lin S, Kuo A. et al. Retinal thinning in amyotrophic lateral sclerosis patients without ophthalmic disease. PLoS One 2017; 12: e0185242
• 18 Kersten HM, Danesh-Meyer HV, Kilfoyle DH. et al. Optical coherence tomography findings in Huntington’s disease: a potential biomarker of disease progression. J Neurol 2015; 262: 2457-2465
• 19 Gatto E, Parisi V, Persi G. et al. Optical coherence tomography (OCT) study in Argentinean Huntington’s disease patients. Int J Neurosci 2018; 128: 1157-1162
• 20 Tsokolas G, Tsaousis KT, Diakonis VF. et al. Optical Coherence Tomography Angiography in Neurodegenerative Diseases: A Review. Eye Brain 2020; 12: 73-87
• 21 Albrecht P, Müller A-K, Südmeyer M. et al. Optical coherence tomography in parkinsonian syndromes. PLoS One 2012; 7: e34891
• 22 Wagner SK, Romero-Bascones D, Cortina-Borja M. et al. Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease. Neurology 2023; 101: e1581-e1593
• 23 Tran KKN, Wong VHY, Lim JKH. et al. Characterization of retinal function and structure in the MPTP murine model of Parkinson’s disease. Sci Rep 2022; 12: 7610
• 24 Harper DJ, Augustin M, Lichtenegger A. et al. Retinal analysis of a mouse model of Alzheimer’s disease with multicontrast optical coherence tomography. Neurophotonics 2020; 7: 015006
• 25 Groh J, Stadler D, Buttmann M. et al. Non-invasive assessment of retinal alterations in mouse models of infantile and juvenile neuronal ceroid lipofuscinosis by spectral domain optical coherence tomography. Acta Neuropathol Commun 2014; 2: 54
• 26 Huang D, Swanson EA, Lin CP. et al. Optical coherence tomography. Science 1991; 254: 1178-1181
• 27 Parisi V, Manni G, Spadaro M. et al. Correlation between morphological and functional retinal impairment in multiple sclerosis patients. Invest Ophthalmol Vis Sci 1999; 40: 2520-2527
• 28 Albrecht P, Fröhlich R, Hartung H-P. et al. Optical coherence tomography measures axonal loss in multiple sclerosis independently of optic neuritis. J Neurol 2007; 254: 1595-1596
• 29 Costello F, Hodge W, Pan YI. et al. Differences in retinal nerve fiber layer atrophy between multiple sclerosis subtypes. J Neurol Sci 2009; 281: 74-79
• 30 Albrecht P, Müller A-K, Ringelstein M. et al. Retinal neurodegeneration in Wilson’s disease revealed by spectral domain optical coherence tomography. PLoS One 2012; 7: e49825
• 31 Albrecht P, Ringelstein M, Müller AK. et al. Degeneration of retinal layers in multiple sclerosis subtypes quantified by optical coherence tomography. Mult Scler 2012; 18: 1422-1429
• 32 Saidha S, Sotirchos ES, Ibrahim MA. et al. Microcystic macular oedema, thickness of the inner nuclear layer of the retina, and disease characteristics in multiple sclerosis: a retrospective study. Lancet Neurol 2012; 11: 963-972
• 33 Dietrich M, Hecker C, Hilla A. et al. Using Optical Coherence Tomography and Optokinetic Response As Structural and Functional Visual System Readouts in Mice and Rats. J Vis Exp 2019;
• 34 Fischer MD, Huber G, Beck SC. et al. Noninvasive, in vivo assessment of mouse retinal structure using optical coherence tomography. PLoS One 2009; 4: e7507
• 35 Sotirchos ES, Saidha S. OCT is an alternative to MRI for monitoring MS – YES. Mult Scler 2018; 24: 701-703
• 36 Saidha S, Calabresi PA. Optical coherence tomography should be part of the routine monitoring of patients with multiple sclerosis: yes. Mult Scler 2014; 20: 1296-1298
• 37 Castonguay A, Lefebvre J, Lesage F. et al. Comparing three-dimensional serial optical coherence tomography histology to MRI imaging in the entire mouse brain. J Biomed Opt 2018; 23: 1-9
• 38 Manogaran P, Hanson JVM, Olbert ED. et al. Optical Coherence Tomography and Magnetic Resonance Imaging in Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorder. Int J Mol Sci 2016; 17: 1894
• 39 Brandt AU, Martinez-Lapiscina EH, Nolan R. et al. Monitoring the Course of MS With Optical Coherence Tomography. Curr Treat Options Neurol 2017; 19: 15
• 40 Oh J, Sotirchos ES, Saidha S. et al. Relationships between quantitative spinal cord MRI and retinal layers in multiple sclerosis. Neurology 2015; 84: 720-728
• 41 Frenger MJ, Hecker C, Sindi M. et al. Semi-Automated Live Tracking of Microglial Activation in CX3CR1GFP Mice During Experimental Autoimmune Encephalomyelitis by Confocal Scanning Laser Ophthalmoscopy. Front Immunol 2021; 12: 761776
• 42 Hecker C, Dietrich M, Issberner A. et al. Comparison of different optomotor response readouts for visual testing in experimental autoimmune encephalomyelitis-optic neuritis. J Neuroinflammation 2020; 17: 216
• 43 Marenna S, Rossi E, Huang S-C. et al. Visual evoked potentials waveform analysis to measure intracortical damage in a preclinical model of multiple sclerosis. Front Cell Neurosci 2023; 17: 1186110
• 44 Li M, Wan C. The use of deep learning technology for the detection of optic neuropathy. Quant Imaging Med Surg 2022; 12: 2129-2143
• 45 Ortiz M, Mallen V, Boquete L. et al. Diagnosis of multiple sclerosis using optical coherence tomography supported by artificial intelligence. Mult Scler Relat Disord 2023; 74: 104725
• 46 Przybyszewski AW, Śledzianowski A, Chudzik A. et al. Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms. Sensors (Basel) 2023; 23: 2145
• 47 Volland S, Esteve-Rudd J, Hoo J. et al. A comparison of some organizational characteristics of the mouse central retina and the human macula. PLoS One 2015; 10: e0125631
• 48 Lama J, Buhidma Y, Fletcher EJR. et al. Animal models of Parkinson’s disease: a guide to selecting the optimal model for your research. Neuronal Signal 2021; 5: NS20210026