Hyper BOLD Activation in Dorsal Raphe Nucleus of APP/PS1 Alzheimer's Disease Mouse during Reward-Oriented Drinking Test under Thirsty Conditions.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
03 03 2020
03 03 2020
Historique:
received:
15
09
2019
accepted:
18
02
2020
entrez:
5
3
2020
pubmed:
5
3
2020
medline:
26
11
2020
Statut:
epublish
Résumé
Alzheimer's disease (AD), a neurodegenerative disease, causes behavioural abnormalities such as disinhibition, impulsivity, and hyperphagia. Preclinical studies using AD model mice have investigated these phenotypes by measuring brain activity in awake, behaving mice. In this study, we monitored the behavioural alterations of impulsivity and hyperphagia in middle-aged AD model mice. As a behavioural readout, we trained the mice to accept a water-reward under thirsty conditions. To analyse brain activity, we developed a measure for licking behaviour combined with visualisation of whole brain activity using awake fMRI. In a water-reward learning task, the AD model mice showed significant hyperactivity of the dorsal raphe nucleus in thirsty conditions. In summary, we successfully visualised altered brain activity in AD model mice during reward-oriented behaviour for the first time using awake fMRI. This may help in understanding the causes of behavioural alterations in AD patients.
Identifiants
pubmed: 32127559
doi: 10.1038/s41598-020-60894-7
pii: 10.1038/s41598-020-60894-7
pmc: PMC7054396
doi:
Substances chimiques
Oxygen
S88TT14065
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
3915Références
Ritchie, K. & Lovestone, S. The dementias. Lancet 360, 1759–1766 (2002).
pubmed: 12480441
doi: 10.1016/S0140-6736(02)11667-9
pmcid: 12480441
Bidzan, L., Bidzan, M. & Pąchalska, M. Aggressive and impulsive behavior in Alzheimer’s disease and progression of dementia. Med. Sci. Monit. 18, 182–189 (2012).
doi: 10.12659/MSM.882523
Rochat, L., Billieux, J., Gagnon, J. & Van der Linden, M. A multifactorial and integrative approach to impulsivity in neuropsychology: insights from the UPPS model of impulsivity. J. Clin. Exp. Neuropsychol. 40, 45–61 (2018).
pubmed: 28398126
doi: 10.1080/13803395.2017.1313393
pmcid: 28398126
Keene, J. & Hope, T. Natural history of hyperphagia and other eating changes in dementia. Int. J. Geriatr. Psychiatry 13, 700–706 (1996).
doi: 10.1002/(SICI)1099-1166(1998100)13:10<700::AID-GPS855>3.0.CO;2-D
Shea, Y., Lee, C. & Chu, W. Prevalence of hyperphagia in Alzheimer’s disease: a meta-analysis. Psychogeriatrics. 18, 243–251 (2018).
pubmed: 29409159
doi: 10.1111/psyg.12316
pmcid: 29409159
Adebakin, A., Bradley, J., Gümüsgöz, S., Waters, J. & Lawrence, B. Impaired satiation and increased feeding behaviour in the triple-transgenic Alzheimer’s disease mouse model. Plos One 7, e45179, https://doi.org/10.1371/journal.pone.0045179. (2012).
doi: 10.1371/journal.pone.0045179.
pubmed: 23056194
pmcid: 3464300
Shepherd, A. et al. Evaluation of attention in APP/PS1 mice shows impulsive and compulsive behaviours. Genes Brain Behav., https://doi.org/10.1111/gbb.12594. (2019).
Vakalopoulos, C. Alzheimer’s Disease: The Alternative Serotonergic Hypothesis of Cognitive Decline. J. Alzheimer Dis. 60, 859–866 (2017).
doi: 10.3233/JAD-170364
Athanasios, M. et al. Reduced Serotonin Transporter Levels and Inflammation in the Midbrain Raphe of 12 Month Old APPswe/PSEN1dE9 Mice. Curr. Alzheimer Res. 15, 420–428 (2018).
doi: 10.2174/1567205014666171004113537
Asaad, M. & Lee, J. H. A guide to using functional magnetic resonance imaging to study Alzheimer’s disease in animal models. Dis. Model Mech. 11, dmm031724, https://doi.org/10.1242/dmm.031724. (2018).
doi: 10.1242/dmm.031724.
pubmed: 29784664
pmcid: 5992611
Chhatwal, J. P. & Sperling, R. A. Functional MRI of mnemonic networks across the spectrum of normal aging, mild cognitive impairment and Alzheimer’s disease. J. Alzheimers Dis. 31, 155–167 (2013).
doi: 10.3233/JAD-2012-120730
Dickerson, B. C. & Sperling, R. A. Functional abnormalities of the medial temporal lobe memory system in mild cognitive impairment and Alzheimer’s disease: Insights from functional MRI studies. Neuropsychologia 46, 1624–1635 (2008).
pubmed: 18206188
doi: 10.1016/j.neuropsychologia.2007.11.030
Li, H. J. et al. Toward systems neuroscience in mild cognitive impairment and Alzheimer’s disease: a meta-analysis of 75 fMRI studies. Hum. Brain Mapp. 36, 1217–1232 (2015).
pubmed: 25411150
doi: 10.1002/hbm.22689
Sugarman, M. A. et al. Functional magnetic resonance imaging of semantic memory as a presymptomatic biomarker of Alzheimer’s disease risk. Biochim. Biophys. Acta 1822, 442–456 (2012).
pubmed: 21996618
doi: 10.1016/j.bbadis.2011.09.016
Vanhoutte, L. et al. MRI Assessment of Cardiomyopathy Induced by β1-Adrenoreceptor Autoantibodies and Protection Through β3-Adrenoreceptor Overexpression. Sci. Rep. 7, 43951, https://doi.org/10.1038/srep43951 (2017).
Braak, H., Thal, R., Ghebremedhin, E. & Del Tredici, K. Stages of the pathologic process in Alzheimer disease: age categories from 1 to 100 years. J. Neuropathol. Exp. Neurol. 70, 960–969 (2011).
pubmed: 22002422
doi: 10.1097/NEN.0b013e318232a379
Bookheimer, Y. et al. Patterns of brain activation in people at risk for Alzheimer’s disease. N. Engl. J. Med. 343, 450–456 (2000).
pubmed: 10944562
pmcid: 2831477
doi: 10.1056/NEJM200008173430701
Trivedi, A. et al. fMRI activation during episodic encoding and metacognitive appraisal across the lifespan: risk factors for Alzheimer’s disease. Neuropsychologia 46, 1667–1678 (2008).
pubmed: 18241895
doi: 10.1016/j.neuropsychologia.2007.11.035
Filippini, N. et al. Distinct patterns of brain activity in young carriers of the APOE-ε4 allele. Proc. Natl. Acad. Sci. USA 106, 7209–7214 (2009).
pubmed: 19357304
doi: 10.1073/pnas.0811879106
Quiroz, T. et al. Hippocampal hyperactivation in presymptomatic familial Alzheimer’s disease. Ann. Neurol. 68, 865–875 (2010).
pubmed: 21194156
pmcid: 3175143
doi: 10.1002/ana.22105
Celone, A. et al. Alterations in memory networks in mild cognitive impairment and Alzheimer’s disease: and independent component analysis. J. Neurosci. 26, 10222–10231 (2006).
pubmed: 17021177
pmcid: 6674636
doi: 10.1523/JNEUROSCI.2250-06.2006
Hämäläinen, A. et al. Increased fMRI responses during encoding in mild cognitive impairment. Neurobiol. Aging. 28, 1889–1903 (2007).
pubmed: 16997428
doi: 10.1016/j.neurobiolaging.2006.08.008
Miller, L. et al. Age-related memory impairment associated with loss of parietal deactivation but preserved hippocampal activation. Proc. Natl. Acad. Sci. USA 105, 2181–2186 (2008).
pubmed: 18238903
doi: 10.1073/pnas.0706818105
O’Brien, L. et al. Longitudinal fMRI in elderly reveals loss of hippocampal activation with clinical decline. Neurology 74, 1969–1976 (2010).
pubmed: 20463288
pmcid: 2905893
doi: 10.1212/WNL.0b013e3181e3966e
Bakker, A. et al. Reduction of hippocampal hyperactivity improves cognition in amnestic mild cognitive impairment. Neuron 74, 467–474 (2012).
pubmed: 22578498
pmcid: 3351697
doi: 10.1016/j.neuron.2012.03.023
Wogar, M. A., Bradshaw, C. M. & Szabadi, E. Effect of lesions of the ascending 5-hydroxytryptaminergic pathways on choice between delayed reinforcers. Psychopharmacology 111, 239–243 (1993).
pubmed: 7870958
doi: 10.1007/BF02245530
Bizot, J., Le Bihan, C., Puech, A. J., Hamon, M. & Thiebot, M. Serotonin and tolerance to delay of reward in rats. Psychopharmacology 146, 400–412 (1999).
pubmed: 10550490
doi: 10.1007/PL00005485
Mobini, S., Chiang, T. J., Ho, M. Y., Bradshaw, C. M. & Szabadi, E. Effects of central 5-hydroxytryptamine depletion on sensitivity to delayed and probabilistic reinforcement. Psychopharmacology 152, 390–397 (2000).
pubmed: 11140331
doi: 10.1007/s002130000542
Denk, F. et al. Differential involvement of serotonin and dopamine systems in cost-benefit decisions about delay or effort. Psychopharmacology 179, 587–596 (2005).
pubmed: 15864561
doi: 10.1007/s00213-004-2059-4
Miyazaki, K. W., Miyazaki, K. & Doya, K. Activation of dorsal raphe serotonin neurons is necessary for waiting for delayed rewards. J. Neurosci. 32, 10451–10457 (2012).
pubmed: 22855794
pmcid: 6621383
doi: 10.1523/JNEUROSCI.0915-12.2012
Xu, S., Das, G., Hueske, E. & Tonegawa, S. Dorsal Raphe Serotonergic Neurons Control Intertemporal Choice under Trade-off. Curr. Biol. 27, 3111–3119 (2017).
pubmed: 28988863
pmcid: 5691357
doi: 10.1016/j.cub.2017.09.008
Ehrenberg, A. J. et al. Quantifying the accretion of hyperphosphorylated tau in the locus coeruleus and dorsal raphe nucleus: the pathological building blocks of early Alzheimer’s disease. Neuropathol. Appl. Neurobiol. 43, 393–408 (2017).
pubmed: 28117917
pmcid: 5642282
doi: 10.1111/nan.12387
Metaxas, A. et al. Reduced Serotonin Transporter Levels and Inflammation in the Midbrain Raphe of 12 Month Old APPswe/PSEN1dE9 Mice. Curr. Alzheimer Res. 15, 420–428 (2018).
pubmed: 28982335
doi: 10.2174/1567205014666171004113537
pmcid: 28982335
Perles-Barbacaru, T. A. et al. Quantitative pharmacologic MRI: mapping the cerebral blood volume response to cocaine in dopamine transporter knockout mice. Neuroimage 55, 622–628 (2011).
pubmed: 21185387
doi: 10.1016/j.neuroimage.2010.12.048
pmcid: 21185387
Abe, Y. et al. Opto-fMRI analysis for exploring the functional connectivity of the hippocampal formation in rats. Neurosci. Res. 74, 248–255 (2012).
pubmed: 22982343
doi: 10.1016/j.neures.2012.08.007
pmcid: 22982343
Grandjean, J. et al. A brain-wide functional map of the serotonergic responses to acute stress and fluoxetine. Nat Commun. 10, 350, https://doi.org/10.1038/s41467-018-08256-w (2019).
doi: 10.1038/s41467-018-08256-w
pubmed: 30664643
pmcid: 6341094
Zhang, N. et al. Mapping resting-state brain networks in conscious animals. J. Neurosci. Methods 189, 186–196 (2010).
pubmed: 20382183
pmcid: 2896018
doi: 10.1016/j.jneumeth.2010.04.001
Johnson, T. R., Smerkers, B., Moulder, J. K., Stellar, J. R. & Febo, M. Neural processing of a cocaine-associated odor cue revealed by functional MRI in awake rats. Neurosci. 534, 160–165 (2013).
Jonckers, E. et al. Different anesthesia regimes modulate the functional connectivity outcome in mice. Magn. Reson. Med. 72, 1103–1112 (2014).
pubmed: 24285608
doi: 10.1002/mrm.24990
Martin, C., Martindale, J., Berwick, J. & Mayhew, J. Investigating neural-hemodynamic coupling and the hemodynamic response function in the awake rat. Neuroimage 32, 33–48 (2006).
pubmed: 16725349
doi: 10.1016/j.neuroimage.2006.02.021
Desai, M. et al. Mapping brain networks in awake mice using combined optical neural control and fMRI. J. Neurophysiol. 105, 1393–1405 (2011).
pubmed: 21160013
doi: 10.1152/jn.00828.2010
Nasrallah, F. A., Yeow, L. Y., Biswal, B. & Chuang, K. H. Dependence of BOLD signal fluctuation on arterial blood CO2 and O2: implication for resting-state functional connectivity. Neuroimage 117, 29–39 (2015).
pubmed: 26003858
doi: 10.1016/j.neuroimage.2015.05.035
Shim, H. J. et al. Mouse fMRI under ketamine and xylazine anesthesia: Robust contralateral somatosensory cortex activation in response to forepaw stimulation. Neuroimage 177, 30–44 (2018).
pubmed: 29730495
doi: 10.1016/j.neuroimage.2018.04.062
Brydges, N. M. et al. Imaging conditioned fear circuitry using awake rodent fMRI. Plos One 8, e54197 (2013).
pubmed: 23349824
pmcid: 3551953
doi: 10.1371/journal.pone.0054197
Harris, A. P. et al. Imaging learned fear circuitry in awake mice using fMRI. Eur. J. Neurosci. 42, 2125–2134 (2015).
pubmed: 25943794
pmcid: 4744695
doi: 10.1111/ejn.12939
Jomura, N., Shintani, T., Sakurai, K., Kaneko, J. & Hisatsune, T. Mouse BOLD fMRI imaging during operant learning at ultra-high field (14 T). Proc. Intl. Soc. Mag. Reson. Med. 25, 5365 (2017).
Han, Z. et al. Awake and behaving mouse fMRI during Go/No-Go task. Neuroimage 188, 733–742 (2019).
pubmed: 30611875
doi: 10.1016/j.neuroimage.2019.01.002
pmcid: 30611875
Jankowsky, J. L. et al. Co-expression of multiple transgenes in mouse CNS: a comparison of strategies. Biomol. Eng. 17, 157–165 (2001).
pubmed: 11337275
doi: 10.1016/S1389-0344(01)00067-3
pmcid: 11337275
Herculano, B. et al. β-Alanyl-L-histidine rescues cognitive deficits caused by feeding a high fat diet in a transgenic mouse model of Alzheimer’s Disease. J. Alzheimer Dis. 33, 983–997 (2013).
doi: 10.3233/JAD-2012-121324
Kaneko, J., Enya, A., Enomoto, K., Ding, Q. & Hisatsune, T. Anserine (beta-alanyl-3-methyl-L-histidine) improves neurovascular-unit dysfunction and spatial memory in aged AβPPswe/PSEN1dE9 Alzheimer’s-model mice. Sci. Rep. 7, 12571, https://doi.org/10.1038/s41598-017-12785-7. (2017).
doi: 10.1038/s41598-017-12785-7.
pubmed: 28974740
pmcid: 5626714
Kao, K.-C. & Hisatsune, T. Differential effects of dopamine D1-like and D2-like receptor agonists on water drinking behavior under thirsty conditions in mice with reduced dopamine secretion. Eur. J. Neurosci. (online after 2019.8.31), https://doi.org/10.1111/ejn.14568 . (2019).
pubmed: 31472080
doi: 10.1111/ejn.14568
Tsurugizawa, T., Uematsu, A., Uneyama, H. & Torii, K. Functional brain mapping of conscious rats during reward anticipation. J. Neurosci. Meth. 206, 132–137 (2012).
doi: 10.1016/j.jneumeth.2012.02.014
Ciobanu, L. et al. fMRI contrast at high and ultrahigh magnetic fields: insight from complementary methods. Neuroimage 113, 37–43 (2015).
pubmed: 25795340
doi: 10.1016/j.neuroimage.2015.03.018
Turner, R. et al. Functional mapping of the human visual cortex at 4 Tesla and 1.5 Tesla using deoxygenation contrast EPI. Magn. Reson. Med. 29, 277–279 (1993).
pubmed: 8429797
doi: 10.1002/mrm.1910290221
Duong, T. Q. et al. Microvascular BOLD contribution at 4 and 7 T in the human brain: gradient-echo and spin-echo fMRI with suppression of blood effects. Magn. Reson. Med. 49, 1019–1027 (2003).
pubmed: 12768579
doi: 10.1002/mrm.10472
Blazquez Freches, G., Chavarrias, C. & Shemesh, N. BOLD-fMRI in the mouse auditory pathway. Neuroimage 165, 265–277 (2018).
pubmed: 29050909
doi: 10.1016/j.neuroimage.2017.10.027
Han, S., Son, J. P., Cho, H., Park, J. Y. & Kim, S. G. Gradient-echo and spin-echo blood oxygenation level-dependent functional MRI at ultrahigh fields of 9.4 and 15.2 Tesla. Magn. Reson. Med. 81, 1237–1246 (2019).
pubmed: 30183108
doi: 10.1002/mrm.27457
Avants, B. et al. A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage. 54, 2033–2044 (2010).
pubmed: 20851191
pmcid: 3065962
doi: 10.1016/j.neuroimage.2010.09.025
Yushkevich, A. & Gerig, G. ITK-SNAP: An Intractive Medical Image Segmentation Tool to Meet the Need for Expert-Guided Segmentation of Complex Medical Images. IEEE Pulse 8, 854–857 (2017).
doi: 10.1109/MPUL.2017.2701493
Hikishima, K. et al. In vivo microscopic voxel-based morphometry with a brain template to characterize strain specific structures in the mouse brain. Sci. Rep. 7, 85, https://doi.org/10.1038/s41598-017-00148-1 (2017).
doi: 10.1038/s41598-017-00148-1
pubmed: 28273899
pmcid: 5427914
Franklin, K. B. J. & Paxinos, G. The mouse brain in stereotaxic coordinates, third edition. Elsevier Academic Press, New York. ISBN 978-0-12-374244-5 (2008).
Ma, Y. et al. A three-dimensional digital atlas database of the adult C57BL/6J mouse brain by magnetic resonance microscopy. Neuroscience 135, 1203–1215 (2005).
pubmed: 16165303
doi: 10.1016/j.neuroscience.2005.07.014
Stanford, S. C. The Open Field Test: reinventing the wheel. J Psychopharmacol. 21, 134–5 (2007).
pubmed: 17329288
doi: 10.1177/0269881107073199
Ennaceur, A. Tests of unconditioned anxiety - pitfalls and disappointments. Physiol Behav. 135, 55–71 (2014).
pubmed: 24910138
doi: 10.1016/j.physbeh.2014.05.032