Alberto Benussi1, Valentina Dell'Era1, Valentina Cantoni2, Maria Sofia Cotelli3, Maura Cosseddu4, Marco Spallazzi5, Anna Micheli6, Rosanna Turrone4, Antonella Alberici4, Barbara Borroni7. 1. Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy. 2. Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Italy. 3. Neurology Unit, Valle Camonica Hospital, Brescia, Italy. 4. Neurology Unit, Spedali Civili di Brescia, Brescia, Italy. 5. Department of Medicine and Surgery, Section of Neurology, Azienda Ospedaliero-Universitaria, Parma, Italy. 6. Casa di Cura San Francesco, Bergamo, Italy. 7. Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy. Electronic address: bborroni@inwind.it.
Abstract
OBJECTIVE: To evaluate if transcranial magnetic stimulation (TMS) measures correlate with disease severity and predict functional decline in frontotemporal dementia (FTD) phenotypes. METHODS: Paired-pulse TMS was used to investigate the activity of different intracortical circuits in 171 FTD patients (122 bvFTD, 31 avPPA, 18 svPPA) and 74 healthy controls. Pearson's correlations were used to analyze the association between TMS measures and disease severity, while multiple regression analysis was used to identify the best clinical or neurophysiological measure to predict functional decline at 12 months. RESULTS: We observed significant strong correlations between TMS measures [short interval intracortical inhibition-facilitation (SICI-ICF) and long interval intracortical inhibition (LICI)], and disease severity (evaluated with the FTLD-CDR) (all r > 0.5, p < 0.005). SICI-ICF, short interval intracortical facilitation (SICF) and LICI were also significant predictors of functional decline, evaluated as the change in FTLD-CDR scores at 12 months (all p < 0.005), while at the stepwise multiple regression analysis, SICI was the best predictor of disease progression, accounting for 72.5% of the variation in FTLD-CDR scores at 12 months (adjusted R2 = 0.72, p < 0.001). CONCLUSIONS: The present study has shown that the dysfunction of inhibitory and facilitatory intracortical circuits, evaluated with TMS, correlates with disease severity and progression, accurately predicting functional decline at 12 months, better than any other investigated marker.
OBJECTIVE: To evaluate if transcranial magnetic stimulation (TMS) measures correlate with disease severity and predict functional decline in frontotemporal dementia (FTD) phenotypes. METHODS: Paired-pulse TMS was used to investigate the activity of different intracortical circuits in 171 FTDpatients (122 bvFTD, 31 avPPA, 18 svPPA) and 74 healthy controls. Pearson's correlations were used to analyze the association between TMS measures and disease severity, while multiple regression analysis was used to identify the best clinical or neurophysiological measure to predict functional decline at 12 months. RESULTS: We observed significant strong correlations between TMS measures [short interval intracortical inhibition-facilitation (SICI-ICF) and long interval intracortical inhibition (LICI)], and disease severity (evaluated with the FTLD-CDR) (all r > 0.5, p < 0.005). SICI-ICF, short interval intracortical facilitation (SICF) and LICI were also significant predictors of functional decline, evaluated as the change in FTLD-CDR scores at 12 months (all p < 0.005), while at the stepwise multiple regression analysis, SICI was the best predictor of disease progression, accounting for 72.5% of the variation in FTLD-CDR scores at 12 months (adjusted R2 = 0.72, p < 0.001). CONCLUSIONS: The present study has shown that the dysfunction of inhibitory and facilitatory intracortical circuits, evaluated with TMS, correlates with disease severity and progression, accurately predicting functional decline at 12 months, better than any other investigated marker.
Authors: Alberto Benussi; Valentina Cantoni; Mario Grassi; Lucie Brechet; Christoph M Michel; Abhishek Datta; Chris Thomas; Stefano Gazzina; Maria Sofia Cotelli; Marta Bianchi; Enrico Premi; Yasmine Gadola; Maria Cotelli; Marta Pengo; Federica Perrone; Maria Scolaro; Silvana Archetti; Eino Solje; Alessandro Padovani; Alvaro Pascual-Leone; Barbara Borroni Journal: Ann Neurol Date: 2022-06-06 Impact factor: 11.274
Authors: Alberto Benussi; Valentina Cantoni; Jasmine Rivolta; Silvana Archetti; Anna Micheli; Nicholas Ashton; Henrik Zetterberg; Kaj Blennow; Barbara Borroni Journal: Alzheimers Res Ther Date: 2022-10-13 Impact factor: 8.823
Authors: Parmis Fatih; M Utku Kucuker; Jennifer L Vande Voort; Deniz Doruk Camsari; Faranak Farzan; Paul E Croarkin Journal: Front Psychiatry Date: 2021-06-02 Impact factor: 4.157