臺灣博碩士論文加值系統

阿茲海默症是少數無法治癒、預防、減緩的主要死因之一。隨著平均壽命增加，此疾病的盛行率也隨之增加。深腦電刺激藉由增強或阻斷不同腦區之前連結已被證實可治療多種神經疾病。穹窿因為與海馬迴之間的連結，因此有希望為深腦電刺激的目標腦區來治療阿茲海默症。儘管目前已經有研究及試驗，但尚未真正了解深腦電刺激穹窿使阿茲海默症病人有正向表現的原因。在此研究中，使用阿茲海默症基因轉殖老鼠模型及擴散磁振造影技術來了解白質在疾病中的長期變化。阿茲海默症老鼠模型在約年紀六個月時，減少非等向性指標及行為的表現。透過磁振相容探針及動物模型，觀察到深腦電刺激的時機使治療成果上有所差異。阿茲海默症老鼠模型在穹窿進行深腦電刺激對於非等向性指標及行為表現上有改善。

Alzheimer’s disease (AD) is one of the major causes of death that currently cannot be cured, prevented, or slowed. Due to the rising survival age, the upward trend of the disease prevalence will continue. Deep brain stimulation (DBS) has proven to be a viable therapy for various neurological disorders, by enhancing or interrupting different connections within the brain. Various brain structures have been considered as the target for DBS, including the fornix. DBS of the fornix, a major output tract of the hippocampus, has been shown to be a promising target for DBS therapy in AD patients. Even though these studies and trials are taking place, it is still not well understood what alterations are resulting in positive changes within AD patients. In this study, a triple-transgenic (3xTg) mouse model of AD was used in order to understand the longitudinal changes of white matter over the course of the disease through the use of diffusion tensor imaging (DTI). The 3xTg mouse model showed to have decreased FA values and behavioral performance around the age of 6 months. Through the integration of a MR compatible probe and the 3xTg model, it was observed that the timing of the implantation of DBS stimulation probes and stimulation therapy makes a difference in the effectiveness of the therapy. DBS of the fornix showed improvement in the behavior of 3xTg mice and FA values.

Table of Contents
Acknowledgements i
摘要 ii
Abstract iii
Table of Contents iv
List of Figures vii
List of Tables viii
Chapter 1. Introduction 1
1.1 Alzheimer’s Disease 1
1.2 Deep Brain Stimulation 4
1.3 Fornix, Papez Circuit, and Limbic System 5
1.4 Deep Brain Stimulation Targets Considered for Alzheimer’s Disease 6
1.5 Deep Brain Stimulation of the Fornix in Alzheimer’s Disease 6
1.6 Diffusion Tensor Imaging 7
1.7 Motivation and Objectives 8
Chapter 2. Materials and Methods 9
2.1 Experimental Design 9
2.2 Animal Models 9
2.3 Genotyping of 3xTg AD Mice 11
2.4 Immunohistochemistry 11
2.5 Surgical Techniques 12
2.6 Stimulation Parameters 13
2.7 Novel Object Recognition 13
2.8 Magnetic Resonance Imaging Procedures 15
2.9 Diffusion Tensor Imaging Analysis: Tractography Based Spatial Statistics 16
2.10 Selection of Regions of Interest and Analysis 17
Chapter 3. Results 20
3.1 Amyloid Beta in Alzheimer’s Triple Transgenic Mouse Model 20
3.2 Neural Probe MR Compatibility 20
3.3 Long-term Connectivity Progression Fractional Anistropy of Alzheimer’s Disease 3xTg Mouse Model 22
3.4 Fractional Anistropy Changes from Deep Brain Stimulation in the Fornix 23
3.5 Regions of Interest Fractional Anistropy Changes in 3xTg Mice without DBS Therapy 24
3.6 DTI Value Changes in 3xTg AD Mice after Fornix DBS 24
3.7 Deep Brain Stimulation in Different Alzheimer’s Disease Stages 26
3.8 Novel Object Recognition 26
Chapter 4. Discussion 29
4.1 Structural Changes Throughout Alzheimer’s 29
4.2 Applicability of Deep Brain Stimulation for Alzheimer’s Disease 29
4.3 Effectiveness of Fornix Deep Brain Stimulation on Different Disease Stages 30
4.4 Cognitive Enhancement in NOR Performance Post-DBS 31
4.5 Proposed Circuitry Change from Fornix Deep Brain Stimulation 32
4.6 Translating Mouse Model Studies to Human Clinical Applications 33
4.7 Future Works 33
Chapter 5. Conclusion 36
References 37
Appendix 41

•Acosta-Cabronero, J., Nestor, P.J. (2014). Diffusion tensor imaging in Alzheimer''s disease: insights into the limbic-diencephalic network and methodological considerations. Front Aging Neurosci.,6:266.

•Antunes, M., Biala, G. (2012). The novel object recognition memory: neurobiology, test procedure, and its modifications. Cogn Process. ,13(2):93-110.

•Arendash, G.W., Gordon, M.N., Diamond, D.M., et al. (2001). Behavioral assessment of Alzheimer''s transgenic mice following long-term Abeta vaccination: task specificity and correlations between Abeta deposition and spatial memory. DNA Cell Biol. ,20(11):737-44.

•Ashe, K.H., Zahs, K.R. (2010). Probing the biology of Alzheimer''s disease in mice. Neuron. ,66(5):631-45.

•Ballarini, T., Iaccarino, L., Magnani, G., et al. (2016). Neuropsychiatric subsyndromes and brain metabolic network dysfunctions in early onset Alzheimer''s disease. Hum Brain Mapp. ,37(12):4234-4247.

•Busche, M.A., Kekuš, M., Adelsberger, H., et al. (2015). Rescue of long-range circuit dysfunction in Alzheimer''s disease models. Nat Neurosci. ,18(11):1623-30.

•Calabrese, E., Badea, A., Cofer, G., et al. (2015). A Diffusion MRI Tractography Connectome of the Mouse Brain and Comparison with Neuronal Tracer Data. Cereb Cortex, 25(11):4628-37.

•Celone, K.A., Calhoun, V.D., Dickerson, B.C., et al. (2006). Alterations in memory networks in mild cognitive impairment and Alzheimer''s disease: an independent component analysis. J Neurosci, 26(40):10222-31.

•Cho, S., Wood, A., Bowlby, M.R. (2007). Brain slices as models for neurodegenerative disease and screening platforms to identify novel therapeutics. Curr Neuropharmacol. ,5(1):19-33.

•Claeysen, S., Bockaert, J., Giannoni, P. (2015). Serotonin: A New Hope in Alzheimer''s Disease?. ACS Chem Neurosci. ,6(7):940-3.

•Duran-Aniotz, C., Martínez, G., Hetz, C. (2014). Memory loss in Alzheimer''s disease: are the alterations in the UPR network involved in the cognitive impairment?. Front Aging Neurosci.,6:8.

•Ferreira, E., Shaw, D.M., Oddo, S. (2016). Identification of learning-induced changes in protein networks in the hippocampi of a mouse model of Alzheimer''s disease. Transl Psychiatry. ,6(7):e849.

•Foley, A.M., Ammar, Z.M., Lee, R.H., Mitchell, C.S. (2015). Systematic review of the relationship between amyloid-β levels and measures of transgenic mouse cognitive deficit in Alzheimer''s disease. J Alzheimers Dis. ,44(3):787-95.

•Frisch, S., Dukart, J., Vogt, B., et al. (2013). Dissociating memory networks in early Alzheimer''s disease and frontotemporal lobar degeneration - a combined study of hypometabolism and atrophy. PLoS ONE.,8(2):e55251.

•Gomez-Ramirez, J., Wu, J. (2014). Network-based biomarkers in Alzheimer''s disease: review and future directions. Front Aging Neurosci. ,6:12.

•Götz, J., Streffer, J.R., David, D., et al. (2004). Transgenic animal models of Alzheimer''s disease and related disorders: histopathology, behavior and therapy. Mol Psychiatry. ,9(7):664-83.

•Götz, J., Ittner, L.M. (2008). Animal models of Alzheimer''s disease and frontotemporal dementia. Nat Rev Neurosci., 9(7):532-44.

•Grayson, B., Leger, M., Piercy, C., Adamson, L., Harte, M., Neill, J.C. (2015). Assessment of disease-related cognitive impairments using the novel object recognition (NOR) task in rodents. Behav Brain Res., 285:176-93.

•Haines, D.C., Chattopadhyay, S., Ward, J.M. (2001). Pathology of aging B6;129 mice. Toxicol Pathol.,29(6):653-61.

•Hardenacke, K., Shubina, E., Bührle, C.P., et al. (2013). Deep brain stimulation as a tool for improving cognitive functioning in Alzheimer''s dementia: a systematic review. Front Psychiatry.,4:159.

•Hescham, S., Temel, Y., Schipper, S., et al. (2017). Fornix deep brain stimulation induced long-term spatial memory independent of hippocampal neurogenesis. Brain Struct Funct. ,;222(2):1069-1075.

•Huang, H., Zhang, J., Van Zijl, P.C., Mori, S. (2004). Analysis of noise effects on DTI based tractography using the brute-force and multi-ROI approach. Magn Reson Med, 52(3):559-65.

•Jin, Y., Huang, C., Daianu, M., Zhan, L., Dennis, E.L., et al. (2016). 3D Tract-Specific Local and Global Analysis of White Matter Integrity in Alzheimer''s Disease. Human Brain Mapping, 38(3): 1191-1207.

•Kantarci, K. (2014). Fractional anisotropy of the fornix and hippocampal atrophy in Alzheimer''s disease. Front Aging Neurosci.,6:316.

•Kastyak-Ibrahim, M.Z., Di Curzio, D.L., Buist, R., et al. (2013). Neurofibrillary tangles and plaques are not accompanied by white matter pathology in aged triple transgenic-Alzheimer disease mice. Magn Reson Imaging. ,31(9):1515-21.

•Le Bihan, D., Mangin, J.F., Poupon, C., et al. (2001). Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging.,13(4):534-46.

•Lozano, A.M., Fosdick, L., Chakravarty, M.M., et al. (2016). A Phase II Study of Fornix Deep Brain Stimulation in Mild Alzheimer''s Disease. J Alzheimers Dis, 54(2):777-87.

•Lyketsos, C.G., Targum, S.D., Pendergrass, J.C., Lozano, A.M. (2012). Deep brain stimulation: a novel strategy for treating Alzheimer''s disease. Innov Clin Neurosci.,9(11-12):10-7.

•Mastrangelo, M.A., Bowers, W.J. (2008). Detailed immunohistochemical characterization of temporal and spatial progression of Alzheimer''s disease-related pathologies in male triple-transgenic mice. BMC Neurosci.,9:81.

•Mattson, M.P. (2004). Pathways towards and away from Alzheimer''s disease. Nature. ,430(7000):631-9.

•Merrill, D.R., Bikson, M., Jefferys, J.G. (2005). Electrical stimulation of excitable tissue: design of efficacious and safe protocols. J Neurosci Methods. ,141(2):171-98.

•Mielke, M.M., Okonkwo, O.C., Oishi, K., et al. (2012). Fornix integrity and hippocampal volume predict memory decline and progression to Alzheimer''s disease. Alzheimers Dement.,8(2):105-13.

•Mirzadeh, Z., Bari, A., Lozano, A.M. (2016). The rationale for deep brain stimulation in Alzheimer''s disease. J Neural Transm (Vienna). ,123(7):775-83.

• Moldrich, R.X., Pannek, K., Hoch, R., Rubenstein, J.L., Kurniawan, N., et al. (2010). Comparative mouse brain tractography of diffusion magnetic resonance imaging. Neuroimage, 51(3): 1027-1036.

•Müller, H.P., Kassubek, J., Vernikouskaya, I., Ludolph, A.C., Stiller, D., Rasche, V. (2013). Diffusion tensor magnetic resonance imaging of the brain in APP transgenic mice: a cohort study. PLoS ONE.,8(6):e67630.

•O''Brien, R.J., Wong, P.C. (2011). Amyloid precursor protein processing and Alzheimer''s disease. Annu Rev Neurosci, 34:185-204.

•Oddo, S., Caccamo, A., Shepherd, J.D., et al. (2003). Triple-transgenic model of Alzheimer''s disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron, 39(3):409-21.

•Oishi, K., Mielke, M.M., Albert, M., Lyketsos, C.G., Mori, S. (2012). The fornix sign: a potential sign for Alzheimer''s disease based on diffusion tensor imaging. J Neuroimaging. ,22(4):365-74.

•Oishi, K., Lyketsos, C.G. (2014). Alzheimer''s disease and the fornix. Front Aging Neurosci, 6:241.

•Puzzo, D., Lee, L., Palmeri, A., Calabrese, G., Arancio, O. (2014). Behavioral assays with mouse models of Alzheimer''s disease: practical considerations and guidelines. Biochem Pharmacol,88(4):450-67.

•Rowland, N.C., Sammartino, F., Tomaszczyk, J.C., Lozano, A.M. (2016). Deep Brain Stimulation of the Fornix: Engaging Therapeutic Circuits and Networks in Alzheimer Disease. Neurosurgery.,63 Suppl 1:1-5.

•Sankar, T., Chakravarty, M.M., Bescos, A., et al. (2015). Deep Brain Stimulation Influences Brain Structure in Alzheimer''s Disease. Brain Stimul.,8(3):645-54.

•Sharma, M., Deogaonkar, M., Rezai, A. (2015). Assessment of potential targets for deep brain stimulation in patients with Alzheimer''s disease. J Clin Med Res.,7(7):501-5.

•Soares, J.M., Marques, P., Alves, V., et al. (2013). A hitchhiker''s guide to diffusion tensor imaging. Front Neurosci, 7:31.

•Sperling, R.A., Dickerson, B.C., Pihlajamaki, M., et al. (2010). Functional alterations in memory networks in early Alzheimer''s disease. Neuromolecular Med.,12(1):27-43.

•Behrens, T.E.J., Woolrich, M.W., Jenkinson, M., Johansen-Berg, H., Nunes, R.G., Clare, S., Matthews, P.S., Brady, J.M., and Smith, S.M. (2003). Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med, 50(5):1077-1088.

•Webster, S.J., Bachstetter, A.D., Nelson, P.T., Schmitt, F.A., Van Eldik, L.J. (2014). Using mice to model Alzheimer''s dementia: an overview of the clinical disease and the preclinical behavioral changes in 10 mouse models. Front Genet., 5:88.

•Wimo, A., Jonsoon, L., Bond, J., Prince, M., Winblad, B. (2013) The worldwide economic impact of dementia. Alzheimer Disease International 9;1-11.