Introduction: Behavioural dysfunction is a key feature of genetic frontotemporal dementia (FTD) but validated clinical scales measuring behaviour are lacking at present. Methods: We assessed behaviour using the revised version of the Cambridge Behavioural Inventory (CBI-R) in 733 participants from the Genetic FTD Initiative study: 466 mutation carriers (195 C9orf72, 76 MAPT, 195 GRN) and 267 non-mutation carriers (controls). All mutation carriers were stratified according to their global CDR plus NACC FTLD score into three groups: asymptomatic (CDR = 0), prodromal (CDR = 0.5) and symptomatic (CDR = 1+). Mixed-effects models adjusted for age, education, sex and family clustering were used to compare between the groups. Neuroanatomical correlates of the individual domains were assessed within each genetic group. Results: CBI-R total scores were significantly higher in all CDR 1+ mutation carrier groups compared with controls [C9orf72 mean 70.5 (standard deviation 27.8), GRN 56.2 (33.5), MAPT 62.1 (36.9)] as well as their respective CDR 0.5 groups [C9orf72 13.5 (14.4), GRN 13.3 (13.5), MAPT 9.4 (10.4)] and CDR 0 groups [C9orf72 6.0 (7.9), GRN 3.6 (6.0), MAPT 8.5 (13.3)]. The C9orf72 and GRN 0.5 groups scored significantly higher than the controls. The greatest impairment was seen in the Motivation domain for the C9orf72 and GRN symptomatic groups, whilst in the symptomatic MAPTgroup, the highest-scoring domains were Stereotypic and Motor Behaviours and Memory and Orientation. Neural correlates of each CBI-R domain largely overlapped across the different mutation carrier groups. Conclusions: The CBI-R detects early behavioural change in genetic FTD, suggesting that it could be a useful measure within future clinical trials.
The CBI-R detects early behavioural impairment in genetic frontotemporal dementia / Nelson, A.; Russell, L. L.; Peakman, G.; Convery, R. S.; Bouzigues, A.; Greaves, C. V.; Bocchetta, M.; Cash, D. M.; van Swieten, J. C.; Jiskoot, L.; Moreno, F.; Sanchez-Valle, R.; Laforce, R.; Graff, C.; Masellis, M.; Tartaglia, M. C.; Rowe, J. B.; Borroni, B.; Finger, E.; Synofzik, M.; Galimberti, D.; Vandenberghe, R.; de Mendonca, A.; Butler, C. R.; Gerhard, A.; Ducharme, S.; Le Ber, I.; Santana, I.; Pasquier, F.; Levin, J.; Otto, M.; Sorbi, S.; Rohrer, J. D.; Afonso, S.; Almeida, M. R.; Anderl-Straub, S.; Andersson, C.; Antonell, A.; Archetti, S.; Arighi, A.; Balasa, M.; Barandiaran, M.; Bargallo, N.; Bartha, R.; Bender, B.; Benussi, A.; Bertoux, M.; Bertrand, A.; Bessi, V.; Black, S.; Borrego-Ecija, S.; Bras, J.; Brice, A.; Bruffaerts, R.; Camuzat, A.; Canada, M.; Cantoni, V.; Caroppo, P.; Cash, D.; Castelo-Branco, M.; Colliot, O.; Cope, T.; Deramecourt, V.; de Arriba, M.; Di Fede, G.; Diez, A.; Duro, D.; Fenoglio, C.; Ferrari, C.; Ferreira, C. B.; Fox, N.; Freedman, M.; Fumagalli, G.; Funkiewiez, A.; Gabilondo, A.; Gasparotti, R.; Gauthier, S.; Gazzina, S.; Giaccone, G.; Gorostidi, A.; Greaves, C.; Guerreiro, R.; Heller, C.; Hoegen, T.; Indakoetxea, B.; Jelic, V.; Karnath, H. -O.; Keren, R.; Kuchcinski, G.; Langheinrich, T.; Lebouvier, T.; Leitao, M. J.; Llado, A.; Lombardi, G.; Loosli, S.; Maruta, C.; Mead, S.; Meeter, L.; Miltenberger, G.; van Minkelen, R.; Mitchell, S.; Moore, K.; Nacmias, B.; Nelson, A.; Oijerstedt, L.; Olives, J.; Ourselin, S.; Padovani, A.; Panman, J.; Papma, J. M.; Pijnenburg, Y.; Polito, C.; Premi, E.; Prioni, S.; Prix, C.; Rademakers, R.; Redaelli, V.; Rinaldi, D.; Rittman, T.; Rogaeva, E.; Rollin, A.; Rosa-Neto, P.; Rossi, G.; Rossor, M.; Santiago, B.; Saracino, D.; Sayah, S.; Scarpini, E.; Schonecker, S.; Seelaar, H.; Semler, E.; Shafei, R.; Shoesmith, C.; Swift, I.; Tabuas-Pereira, M.; Tainta, M.; Taipa, R.; Tang-Wai, D.; Thomas, D. L.; Thompson, P.; Thonberg, H.; Timberlake, C.; Tiraboschi, P.; Todd, E.; Van Damme, P.; Vandenbulcke, M.; Veldsman, M.; Verdelho, A.; Villanua, J.; Warren, J.; Wilke, C.; Wlasich, E.; Zetterberg, H.; Zulaica, M.. - In: ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY. - ISSN 2328-9503. - 9:5(2022), pp. 644-658. [10.1002/acn3.51544]
The CBI-R detects early behavioural impairment in genetic frontotemporal dementia
Fumagalli G.;
2022-01-01
Abstract
Introduction: Behavioural dysfunction is a key feature of genetic frontotemporal dementia (FTD) but validated clinical scales measuring behaviour are lacking at present. Methods: We assessed behaviour using the revised version of the Cambridge Behavioural Inventory (CBI-R) in 733 participants from the Genetic FTD Initiative study: 466 mutation carriers (195 C9orf72, 76 MAPT, 195 GRN) and 267 non-mutation carriers (controls). All mutation carriers were stratified according to their global CDR plus NACC FTLD score into three groups: asymptomatic (CDR = 0), prodromal (CDR = 0.5) and symptomatic (CDR = 1+). Mixed-effects models adjusted for age, education, sex and family clustering were used to compare between the groups. Neuroanatomical correlates of the individual domains were assessed within each genetic group. Results: CBI-R total scores were significantly higher in all CDR 1+ mutation carrier groups compared with controls [C9orf72 mean 70.5 (standard deviation 27.8), GRN 56.2 (33.5), MAPT 62.1 (36.9)] as well as their respective CDR 0.5 groups [C9orf72 13.5 (14.4), GRN 13.3 (13.5), MAPT 9.4 (10.4)] and CDR 0 groups [C9orf72 6.0 (7.9), GRN 3.6 (6.0), MAPT 8.5 (13.3)]. The C9orf72 and GRN 0.5 groups scored significantly higher than the controls. The greatest impairment was seen in the Motivation domain for the C9orf72 and GRN symptomatic groups, whilst in the symptomatic MAPTgroup, the highest-scoring domains were Stereotypic and Motor Behaviours and Memory and Orientation. Neural correlates of each CBI-R domain largely overlapped across the different mutation carrier groups. Conclusions: The CBI-R detects early behavioural change in genetic FTD, suggesting that it could be a useful measure within future clinical trials.| File | Dimensione | Formato | |
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