In vivo exploration of synaptic projections in frontotemporal dementia.

[en] The purpose of this exploratory research is to provide data on synaptopathy in the behavioral variant of frontotemporal dementia (bvFTD). Twelve patients with probable bvFTD were compared to 12 control participants and 12 patients with Alzheimer’s disease (AD). Loss of synaptic projections was assessed with [18F]UCBH-PET. Total distribution volume was obtained with Logan method using carotid artery derived input function. Neuroimages were analyzed with SPM12. Verbal fluency, episodic memory and awareness of cognitive impairment were equally impaired in patients groups. Compared to controls, [18F]UCBH uptake tended to decrease in the right anterior parahippocampal gyrus of bvFTD patients. Loss of synaptic projections was observed in the right hippocampus of AD participants, but there was no significant difference in [18F]UCBH brain uptake between patients groups. Anosognosia for clinical disorder was correlated with synaptic density in the caudate nucleus and the anteromedial prefrontal cortex. This study suggests that synaptopathy in bvFTD targets the temporal social brain and self-referential processes.

Research center :

GIGA CRC (Cyclotron Research Center) In vivo Imaging-Aging & Memory - ULiège

Disciplines :

Neurology

Author, co-author :

Salmon, Eric ; Université de Liège - ULiège > Département des sciences cliniques > Neuroimagerie des troubles de la mémoire et revalid. cogn.

Bahri, Mohamed Ali ; Université de Liège - ULiège > GIGA CRC In vivo Imaging - Aging & Memory

Plenevaux, Alain ; Université de Liège - ULiège > GIGA CRC In vivo Imaging - Preclinical Imaging

Becker, Guillaume ; Université de Liège - ULiège > Département de Psychologie > Département de Psychologie

Seret, Alain ; Université de Liège - ULiège > Département de physique > Imagerie médicale expérimentale

Delhaye, Emma ; Université de Liège - ULiège > GIGA CRC In vivo Imaging - Aging & Memory

Degueldre, Christian ; Université de Liège - ULiège > GIGA CRC In vivo Imaging - Aging & Memory

Balteau, Evelyne ; Université de Liège - ULiège > GIGA CRC In vivo Im. - Neuroimaging, data acquisi. & proces.

Lemaire, Christian ; Université de Liège - ULiège > CRC In vivo Imaging-Radiochemistry

Luxen, André ; Université de Liège - ULiège > Département de chimie (sciences) > Département de chimie (sciences)

Bastin, Christine ; Université de Liège - ULiège > GIGA CRC In vivo Imaging - Aging & Memory

Language :

English

Title :

In vivo exploration of synaptic projections in frontotemporal dementia.

Publication date :

09 August 2021

Journal title :

Scientific Reports

eISSN :

2045-2322

Publisher :

Nature Publishing Group, London, United Kingdom

Volume :

Pages :

16092

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.nature.com/articles/s41598-021-95499-1

Funders :

SAO-FRA
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
FRB - Fondation Roi Baudouin [BE]
FSR University of Liege

Available on ORBi :

since 09 November 2021

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Bibliography

Schroeter, M. L., Raczka, K., Neumann, J. & von Cramon, D. Y. Neural networks in frontotemporal dementia—A meta-analysis. Neurobiol. Aging 29, 418–426. 10.1016/j.neurobiolaging.2006.10.023 (2008). DOI: 10.1016/j.neurobiolaging.2006.10.023
Seeley, W. W. et al. Frontal paralimbic network atrophy in very mild behavioral variant frontotemporal dementia. Arch. Neurol. 65, 249–255. 10.1001/archneurol.2007.38 (2008). DOI: 10.1001/archneurol.2007.38
McMillan, C. T. et al. White matter imaging contributes to the multimodal diagnosis of frontotemporal lobar degeneration. Neurology 78, 1761–1768. 10.1212/WNL.0b013e31825830bd (2012). DOI: 10.1212/WNL.0b013e31825830bd
Zhou, J. et al. Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer’s disease. Brain J. Neurol. 133, 1352–1367. 10.1093/brain/awq075 (2010). DOI: 10.1093/brain/awq075
Borroni, B. et al. Biological, neuroimaging, and neurophysiological markers in frontotemporal dementia: Three faces of the same coin. J. Alzheimer’s Disease JAD 62, 1113–1123. 10.3233/JAD-170584 (2018). DOI: 10.3233/JAD-170584
Clare, R., King, V. G., Wirenfeldt, M. & Vinters, H. V. Synapse loss in dementias. J. Neurosci. Res. 88, 2083–2090. 10.1002/jnr.22392 (2010). DOI: 10.1002/jnr.22392
van der Ende, E. L. et al. Neuronal pentraxin 2: A synapse-derived CSF biomarker in genetic frontotemporal dementia. J. Neurol. Neurosurg. Psychiatry 91, 612–621. 10.1136/jnnp-2019-322493 (2020). DOI: 10.1136/jnnp-2019-322493
Ferrer, I. Neurons and their dendrites in frontotemporal dementia. Dement. Geriatr. Cogn. Disord. 10(Suppl 1), 55–60. 10.1159/000051214 (1999). DOI: 10.1159/000051214
Lipton, A. M. et al. Contribution of asymmetric synapse loss to lateralizing clinical deficits in frontotemporal dementias. Arch. Neurol. 58, 1233–1239. 10.1001/archneur.58.8.1233 (2001). DOI: 10.1001/archneur.58.8.1233
Liu, X., Erikson, C. & Brun, A. Cortical synaptic changes and gliosis in normal aging, Alzheimer’s disease and frontal lobe degeneration. Dementia 7, 128–134. 10.1159/000106867 (1996). DOI: 10.1159/000106867
Connelly, S. J. et al. Synaptic changes in frontotemporal lobar degeneration: Correlation with MAPT haplotype and APOE genotype. Neuropathol. Appl. Neurobiol. 37, 366–380. 10.1111/j.1365-2990.2010.01150.x (2011). DOI: 10.1111/j.1365-2990.2010.01150.x
Lippa, C. F. Synaptophysin immunoreactivity in Pick’s disease: Comparison with Alzheimer’s disease and dementia with Lewy bodies. Am. J. Alzheimers Dis. Other Demen. 19, 341–344. 10.1177/153331750401900606 (2004). DOI: 10.1177/153331750401900606
Chen, M. K. et al. Assessing synaptic density in Alzheimer disease with synaptic vesicle glycoprotein 2A positron emission tomographic imaging. JAMA Neurol. 75, 1215–1224. 10.1001/jamaneurol.2018.1836 (2018). DOI: 10.1001/jamaneurol.2018.1836
Holmes, S. E. et al. Lower synaptic density is associated with depression severity and network alterations. Nat. Commun. 10, 1529. 10.1038/s41467-019-09562-7 (2019). DOI: 10.1038/s41467-019-09562-7
Onwordi, E. C. et al. Synaptic density marker SV2A is reduced in schizophrenia patients and unaffected by antipsychotics in rats. Nat. Commun. 11, 246. 10.1038/s41467-019-14122-0 (2020). DOI: 10.1038/s41467-019-14122-0
Malpetti, M. et al. Synaptic density in carriers of C9orf72 mutations: a [(11) C]UCB-J PET study. Ann. Clin. Transl. Neurol. 10.1002/acn3.51407 (2021). DOI: 10.1002/acn3.51407
Salmon, E. et al. A comparison of unawareness in frontotemporal dementia and Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 79, 176–179 (2008). DOI: 10.1136/jnnp.2007.122853
Rascovsky, K. et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain J. Neurol. 134, 2456–2477. 10.1093/brain/awr179 (2011). DOI: 10.1093/brain/awr179
Munoz-Neira, C., Tedde, A., Coulthard, E., Thai, N. J. & Pennington, C. Neural correlates of altered insight in frontotemporal dementia: A systematic review. NeuroImage. Clin. 24, 102066. 10.1016/j.nicl.2019.102066 (2019). DOI: 10.1016/j.nicl.2019.102066
Whitfield-Gabrieli, S. & Nieto-Castanon, A. Conn: A functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect. 2, 125–141. 10.1089/brain.2012.0073 (2012). DOI: 10.1089/brain.2012.0073
Bastin, C. et al. In vivo imaging of synaptic loss in Alzheimer’s disease with [18F]UCB-H positron emission tomography. Eur. J. Nucl. Med. Mol. Imaging 47, 390–402. 10.1007/s00259-019-04461-x (2020). DOI: 10.1007/s00259-019-04461-x
Zhuo, J. et al. Connectivity profiles reveal a transition subarea in the Parahippocampal region that integrates the anterior temporal-posterior medial systems. J. Neurosci. Off. J. Soc. Neurosci. 36, 2782–2795. 10.1523/JNEUROSCI.1975-15.2016 (2016). DOI: 10.1523/JNEUROSCI.1975-15.2016
Thiebaut de Schotten, M., Dell’Acqua, F., Valabregue, R. & Catani, M. Monkey to human comparative anatomy of the frontal lobe association tracts. Cortex J. Devoted Study Nervous Syst. Behav. 48, 82–96. 10.1016/j.cortex.2011.10.001 (2012). DOI: 10.1016/j.cortex.2011.10.001
Bickart, K. C. et al. Atrophy in distinct corticolimbic networks in frontotemporal dementia relates to social impairments measured using the Social Impairment Rating Scale. J. Neurol. Neurosurg. Psychiatry 85, 438–448. 10.1136/jnnp-2012-304656 (2014). DOI: 10.1136/jnnp-2012-304656
Yeo, B. T. et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165. 10.1152/jn.00338.2011 (2011). DOI: 10.1152/jn.00338.2011
Salmon, E. et al. Decomposition of metabolic brain clusters in the frontal variant of frontotemporal dementia. Neuroimage 30, 871–878 (2006). DOI: 10.1016/j.neuroimage.2005.10.016
Bueno, A. P. A., Bertoux, M., de Souza, L. C. & Hornberger, M. How predictive are temporal lobe changes of underlying TDP-43 pathology in the ALS-FTD continuum? Ann. Clin. Neurophysiol. 19, 101–112. 10.14253/acn.2017.19.2.101 (2017). DOI: 10.14253/acn.2017.19.2.101
Brettschneider, J. et al. TDP-43 pathology and neuronal loss in amyotrophic lateral sclerosis spinal cord. Acta Neuropathol. 128, 423–437. 10.1007/s00401-014-1299-6 (2014). DOI: 10.1007/s00401-014-1299-6
Whitwell, J. L. et al. Does TDP-43 type confer a distinct pattern of atrophy in frontotemporal lobar degeneration?. Neurology 75, 2212–2220. 10.1212/WNL.0b013e31820203c2 (2010). DOI: 10.1212/WNL.0b013e31820203c2
Snowden, J. S. et al. Distinct clinical and pathological characteristics of frontotemporal dementia associated with C9ORF72 mutations. Brain J. Neurol. 135, 693–708. 10.1093/brain/awr355 (2012). DOI: 10.1093/brain/awr355
Whitwell, J. L. et al. MRI correlates of protein deposition and disease severity in postmortem frontotemporal lobar degeneration. Neurodegener. Dis. 6, 106–117. 10.1159/000209507 (2009). DOI: 10.1159/000209507
Cash, D. M. et al. Patterns of gray matter atrophy in genetic frontotemporal dementia: results from the GENFI study. Neurobiol. Aging 62, 191–196. 10.1016/j.neurobiolaging.2017.10.008 (2018). DOI: 10.1016/j.neurobiolaging.2017.10.008
Farb, N. A. et al. Abnormal network connectivity in frontotemporal dementia: Evidence for prefrontal isolation. Cortex J. Devoted Study Nervous Syst. Behav. 49, 1856–1873. 10.1016/j.cortex.2012.09.008 (2013). DOI: 10.1016/j.cortex.2012.09.008
Rytty, R. et al. GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia. Front. Hum. Neurosci. 7, 461. 10.3389/fnhum.2013.00461 (2013). DOI: 10.3389/fnhum.2013.00461
Tapia, L. et al. Progranulin deficiency decreases gross neural connectivity but enhances transmission at individual synapses. J. Neurosci. Off. J. Soc. Neurosci. 31, 11126–11132. 10.1523/JNEUROSCI.6244-10.2011 (2011). DOI: 10.1523/JNEUROSCI.6244-10.2011
Brun, A., Liu, X. & Erikson, C. Synapse loss and gliosis in the molecular layer of the cerebral cortex in Alzheimer’s disease and in frontal lobe degeneration. Neurodegenerat. J. Neurodegenerat. Disord. Neuroprotect. Neuroregenerat. 4, 171–177. 10.1006/neur.1995.0021 (1995). DOI: 10.1006/neur.1995.0021
Broe, M. et al. Staging disease severity in pathologically confirmed cases of frontotemporal dementia. Neurology 60, 1005–1011. 10.1212/01.wnl.0000052685.09194.39 (2003). DOI: 10.1212/01.wnl.0000052685.09194.39
Irwin, D. J. et al. Deep clinical and neuropathological phenotyping of Pick disease. Ann. Neurol. 79, 272–287. 10.1002/ana.24559 (2016). DOI: 10.1002/ana.24559
Kril, J. J. & Halliday, G. M. Pathological staging of frontotemporal lobar degeneration. J. Mol. Neurosci. MN 45, 379–383. 10.1007/s12031-011-9528-0 (2011). DOI: 10.1007/s12031-011-9528-0
Seeley, W. W. Selective functional, regional, and neuronal vulnerability in frontotemporal dementia. Curr. Opin. Neurol. 21, 701–707. 10.1097/WCO.0b013e3283168e2d (2008). DOI: 10.1097/WCO.0b013e3283168e2d
Massimo, L. et al. Self-appraisal in behavioural variant frontotemporal degeneration. J. Neurol. Neurosurg. Psychiatry 84, 148–153. 10.1136/jnnp-2012-303153 (2013). DOI: 10.1136/jnnp-2012-303153
Zamboni, G., Grafman, J., Krueger, F., Knutson, K. M. & Huey, E. D. Anosognosia for behavioral disturbances in frontotemporal dementia and corticobasal syndrome: A voxel-based morphometry study. Dement. Geriatr. Cogn. Disord. 29, 88–96. 10.1159/000255141 (2010). DOI: 10.1159/000255141
Ruby, P. et al. Social mind representation: Where does it fail in frontotemporal dementia? J. Cognit. Neurosci. 19, 671–683 (2007). DOI: 10.1162/jocn.2007.19.4.671
Rosen, H. J. et al. Neuroanatomical correlates of cognitive self-appraisal in neurodegenerative disease. Neuroimage 49, 3358–3364. 10.1016/j.neuroimage.2009.11.041 (2010). DOI: 10.1016/j.neuroimage.2009.11.041
Di Martino, A. et al. Functional connectivity of human striatum: A resting state FMRI study. Cereb. Cortex 18, 2735–2747. 10.1093/cercor/bhn041 (2008). DOI: 10.1093/cercor/bhn041
Cacciola, A. et al. A connectomic analysis of the human basal ganglia network. Front. Neuroanat. 11, 85. 10.3389/fnana.2017.00085 (2017). DOI: 10.3389/fnana.2017.00085
Lieberman, M. D., Straccia, M. A., Meyer, M. L., Du, M. & Tan, K. M. Social, self, (situational), and affective processes in medial prefrontal cortex (MPFC): Causal, multivariate, and reverse inference evidence. Neurosci. Biobehav. Rev. 99, 311–328. 10.1016/j.neubiorev.2018.12.021 (2019). DOI: 10.1016/j.neubiorev.2018.12.021
D’Argembeau, A. et al. Valuing one’s self: Medial prefrontal involvement in epistemic and emotive investments in self-views. Cereb. Cortex 22, 659–667. 10.1093/cercor/bhr144 (2012). DOI: 10.1093/cercor/bhr144
Delvecchio, G. et al. Structural and metabolic cerebral alterations between elderly bipolar disorder and behavioural variant frontotemporal dementia: A combined MRI-PET study. Aust. N. Z. J. Psychiatry 53, 413–423. 10.1177/0004867418815976 (2019). DOI: 10.1177/0004867418815976
Goetzl, E. J. et al. Decreased synaptic proteins in neuronal exosomes of frontotemporal dementia and Alzheimer’s disease. FASEB J. Off. Publ. Feder. Am. Soc. Exp. Biol. 30, 4141–4148. 10.1096/fj.201600816R (2016). DOI: 10.1096/fj.201600816R
Bahri, M. A. et al. Measuring brain synaptic vesicle protein 2A with positron emission tomography and [(18)F]UCB-H. Alzheimers Dement. 3, 481–486. 10.1016/j.trci.2017.08.004 (2017). DOI: 10.1016/j.trci.2017.08.004
Mecca, A. P. et al. In vivo measurement of widespread synaptic loss in Alzheimer’s disease with SV2A PET. Alzheimer’s Dementia 10.1002/alz.12097 (2020). DOI: 10.1002/alz.12097
Chen, Y., Kumfor, F., Landin-Romero, R., Irish, M. & Piguet, O. The cerebellum in frontotemporal dementia: A meta-analysis of neuroimaging studies. Neuropsychol. Rev. 29, 450–464. 10.1007/s11065-019-09414-7 (2019). DOI: 10.1007/s11065-019-09414-7
Hughes, C. P., Berg, L., Danziger, W. L., Coben, L. A. & Martin, R. L. A new clinical scale for the staging of dementia. Br. J. Psychiatry J. Mental Sci. 140, 566–572 (1982). DOI: 10.1192/bjp.140.6.566
McKhann, G. M. et al. The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dementia 7, 263–269. 10.1016/j.jalz.2011.03.005 (2011). DOI: 10.1016/j.jalz.2011.03.005
Folstein, M. F., Robins, L. N. & Helzer, J. E. The mini-mental state examination. Arch. Gen. Psychiatry 40, 812. 10.1001/archpsyc.1983.01790060110016 (1983). DOI: 10.1001/archpsyc.1983.01790060110016
Didic, M. et al. Impaired visual recognition memory in amnestic mild cognitive impairment is associated with mesiotemporal metabolic changes on magnetic resonance spectroscopic imaging. J. Alzheimer’s Disease JAD 22, 1269–1279. 10.3233/JAD-2010-101257 (2010). DOI: 10.3233/JAD-2010-101257
Migliorelli, R. et al. Anosognosia in Alzheimer’s disease: A study of associated factors. J. Neuropsychiatry Clin. Neurosci. 7, 338–344. 10.1176/jnp.7.3.338 (1995). DOI: 10.1176/jnp.7.3.338
Clare, L., Wilson, B. A., Carter, G., Roth, I. & Hodges, J. R. Assessing awarenes in early stage Alzheimer’s disease: development and piloting of the Memory Awareness Rating Scale. Neuropsychol. Rehabil. 12, 341–362 (2002). DOI: 10.1080/09602010244000129
Warnier, C. et al. Enabling efficient positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) with a robust and one-step radiosynthesis of a highly potent (18)F-labeled ligand ([(18)F]UCB-H). J. Med. Chem. 59, 8955–8966. 10.1021/acs.jmedchem.6b00905 (2016). DOI: 10.1021/acs.jmedchem.6b00905
Draganski, B. et al. Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ). Neuroimage 55, 1423–1434. 10.1016/j.neuroimage.2011.01.052 (2011). DOI: 10.1016/j.neuroimage.2011.01.052
Ashburner, J. & Friston, K. J. Unified segmentation. Neuroimage 26, 839–851. 10.1016/j.neuroimage.2005.02.018 (2005). DOI: 10.1016/j.neuroimage.2005.02.018
Thomas, B. A. et al. PETPVC: A toolbox for performing partial volume correction techniques in positron emission tomography. Phys. Med. Biol. 61, 7975–7993. 10.1088/0031-9155/61/22/7975 (2016). DOI: 10.1088/0031-9155/61/22/7975
Schain, M. et al. Arterial input function derived from pairwise correlations between PET-image voxels. J. Cerebral Blood Flow Metab. Off. J. Int. Soc. Cerebral Blood Flow Metab. 33, 1058–1065. 10.1038/jcbfm.2013.47 (2013). DOI: 10.1038/jcbfm.2013.47
Rousset, O. G., Ma, Y. & Evans, A. C. Correction for partial volume effects in PET: Principle and validation. J. Nuclear Med. Off. Publ. Soc. Nucl. Med. 39, 904–911 (1998).