Genetic forms of frontotemporal dementia are most commonly due to mutations in three genes, C9orf72, GRN or MAPT, with presymptomatic carriers from families representing those at risk. While cerebral blood flow shows differences between frontotemporal dementia and other forms of dementia, there is limited evidence of its utility in presymptomatic stages of frontotemporal dementia. This study aimed to delineate the cerebral blood flow signature of presymptomatic, genetic frontotemporal dementia using a voxel-based approach. In the multicentre GENetic Frontotemporal dementia Initiative (GENFI) study, we investigated cross-sectional differences in arterial spin labelling MRI-based cerebral blood flow between presymptomatic C9orf72, GRN or MAPT mutation carriers (n = 107) and non-carriers (n = 113), using general linear mixed-effects models and voxel-based analyses. Cerebral blood flow within regions of interest derived from this model was then explored to identify differences between individual gene carrier groups and to estimate a timeframe for the expression of these differences. The voxel-based analysis revealed a significant inverse association between cerebral blood flow and the expected age of symptom onset in carriers, but not non-carriers. Regions included the bilateral insulae/orbitofrontal cortices, anterior cingulate/paracingulate gyri, and inferior parietal cortices, as well as the left middle temporal gyrus. For all bilateral regions, associations were greater on the right side. After correction for partial volume effects in a region of interest analysis, the results were found to be largely driven by the C9orf72 genetic subgroup. These cerebral blood flow differences first appeared approximately 12.5 years before the expected symptom onset determined on an individual basis. Cerebral blood flow was lower in presymptomatic mutation carriers closer to and beyond their expected age of symptom onset in key frontotemporal dementia signature regions. These results suggest that arterial spin labelling MRI may be a promising non-invasive imaging biomarker for the presymptomatic stages of genetic frontotemporal dementia.

Cerebral perfusion changes in presymptomatic genetic frontotemporal dementia: A GENFI study / Mutsaerts, H. J. M. M.; Mirza, S. S.; Petr, J.; Thomas, D. L.; Cash, D. M.; Bocchetta, M.; De Vita, E.; Metcalfe, A. W. S.; Shirzadi, Z.; Robertson, A. D.; Tartaglia, M. C.; Mitchell, S. B.; Black, S. E.; Freedman, M.; Tang-Wai, D.; Keren, R.; Rogaeva, E.; Van Swieten, J.; Laforce, R.; Tagliavini, F.; Borroni, B.; Galimberti, D.; Rowe, J. B.; Graff, C.; Frisoni, G. B.; Finger, E.; Sorbi, S.; De Mendonca, A.; Rohrer, J. D.; Macintosh, B. J.; Masellis, M.; Andersson, C.; Archetti, S.; Arighi, A.; Benussi, L.; Binetti, G.; Cosseddu, M.; Dick, K. M.; Fallstrom, M.; Ferreira, C.; Fenoglio, C.; Fox, N. C.; Fumagalli, G.; Gazzina, S.; Ghidoni, R.; Grisoli, M.; Jelic, V.; Jiskoot, L.; Lombardi, G.; Maruta, C.; Mead, S.; Meeter, L.; Van Minkelen, R.; Nacmias, B.; Oijerstedt, L.; Ourselin, S.; Padovani, A.; Panman, J.; Pievani, M.; Polito, C.; Premi, E.; Prioni, S.; Rademakers, R.; Redaelli, V.; Rossi, G.; Rossor, M. N.; Scarpini, E.; Thonberg, H.; Tiraboschi, P.; Verdelho, A.; Warren, J. D.. - In: BRAIN. - ISSN 0006-8950. - 142:4(2019), pp. 1108-1120. [10.1093/brain/awz039]

Cerebral perfusion changes in presymptomatic genetic frontotemporal dementia: A GENFI study

Fumagalli G.;
2019-01-01

Abstract

Genetic forms of frontotemporal dementia are most commonly due to mutations in three genes, C9orf72, GRN or MAPT, with presymptomatic carriers from families representing those at risk. While cerebral blood flow shows differences between frontotemporal dementia and other forms of dementia, there is limited evidence of its utility in presymptomatic stages of frontotemporal dementia. This study aimed to delineate the cerebral blood flow signature of presymptomatic, genetic frontotemporal dementia using a voxel-based approach. In the multicentre GENetic Frontotemporal dementia Initiative (GENFI) study, we investigated cross-sectional differences in arterial spin labelling MRI-based cerebral blood flow between presymptomatic C9orf72, GRN or MAPT mutation carriers (n = 107) and non-carriers (n = 113), using general linear mixed-effects models and voxel-based analyses. Cerebral blood flow within regions of interest derived from this model was then explored to identify differences between individual gene carrier groups and to estimate a timeframe for the expression of these differences. The voxel-based analysis revealed a significant inverse association between cerebral blood flow and the expected age of symptom onset in carriers, but not non-carriers. Regions included the bilateral insulae/orbitofrontal cortices, anterior cingulate/paracingulate gyri, and inferior parietal cortices, as well as the left middle temporal gyrus. For all bilateral regions, associations were greater on the right side. After correction for partial volume effects in a region of interest analysis, the results were found to be largely driven by the C9orf72 genetic subgroup. These cerebral blood flow differences first appeared approximately 12.5 years before the expected symptom onset determined on an individual basis. Cerebral blood flow was lower in presymptomatic mutation carriers closer to and beyond their expected age of symptom onset in key frontotemporal dementia signature regions. These results suggest that arterial spin labelling MRI may be a promising non-invasive imaging biomarker for the presymptomatic stages of genetic frontotemporal dementia.
2019
4
Mutsaerts, H. J. M. M.; Mirza, S. S.; Petr, J.; Thomas, D. L.; Cash, D. M.; Bocchetta, M.; De Vita, E.; Metcalfe, A. W. S.; Shirzadi, Z.; Robertson, A...espandi
Cerebral perfusion changes in presymptomatic genetic frontotemporal dementia: A GENFI study / Mutsaerts, H. J. M. M.; Mirza, S. S.; Petr, J.; Thomas, D. L.; Cash, D. M.; Bocchetta, M.; De Vita, E.; Metcalfe, A. W. S.; Shirzadi, Z.; Robertson, A. D.; Tartaglia, M. C.; Mitchell, S. B.; Black, S. E.; Freedman, M.; Tang-Wai, D.; Keren, R.; Rogaeva, E.; Van Swieten, J.; Laforce, R.; Tagliavini, F.; Borroni, B.; Galimberti, D.; Rowe, J. B.; Graff, C.; Frisoni, G. B.; Finger, E.; Sorbi, S.; De Mendonca, A.; Rohrer, J. D.; Macintosh, B. J.; Masellis, M.; Andersson, C.; Archetti, S.; Arighi, A.; Benussi, L.; Binetti, G.; Cosseddu, M.; Dick, K. M.; Fallstrom, M.; Ferreira, C.; Fenoglio, C.; Fox, N. C.; Fumagalli, G.; Gazzina, S.; Ghidoni, R.; Grisoli, M.; Jelic, V.; Jiskoot, L.; Lombardi, G.; Maruta, C.; Mead, S.; Meeter, L.; Van Minkelen, R.; Nacmias, B.; Oijerstedt, L.; Ourselin, S.; Padovani, A.; Panman, J.; Pievani, M.; Polito, C.; Premi, E.; Prioni, S.; Rademakers, R.; Redaelli, V.; Rossi, G.; Rossor, M. N.; Scarpini, E.; Thonberg, H.; Tiraboschi, P.; Verdelho, A.; Warren, J. D.. - In: BRAIN. - ISSN 0006-8950. - 142:4(2019), pp. 1108-1120. [10.1093/brain/awz039]
File in questo prodotto:
File Dimensione Formato  
2019 Mutsaerts et al.pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Creative commons
Dimensione 646.68 kB
Formato Adobe PDF
646.68 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/355509
Citazioni
  • ???jsp.display-item.citation.pmc??? 23
  • Scopus 35
  • ???jsp.display-item.citation.isi??? 36
  • OpenAlex ND
social impact