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1. An Automated Toolbox to Predict Single Subject Atrophy in Presymptomatic Granulin Mutation Carriers

Author

Premi, Enrico, Costa, Tommaso, Moreno, Fermin, Panman, Jessica, Papma, Janne, Pievani, Michela, Pijnenburg, Yolande, Polito, Cristina, Prioni, Sara, Prix, Catharina, Rademakers As London Ontario Geneticist, Rosa, Redaelli, Veronica, Rittman, Tim, Santana, Isabel, Rogaeva, Ekaterina, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Scarpini, Elio, Schönecker, Sonja, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Laforce, Robert, Tábuas-Pereira, Miguel, Tainta, Mikel, Taipa, Ricardo, Tang-Wai, David, L Thomas, David, Thompson, Paul, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Van Damme, Philip, Ducharme, Simon, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Woollacott, Ione, Wlasich, Elisabeth, Zetterberg, Henrik, Zulaica, Miren, Graff, Caroline, Galimberti, Daniela, Masellis, Mario, Tartaglia, Carmela, Rowe, James B, Finger, Elizabeth, Gazzina, Stefano, Tagliavini, Fabrizio, de Mendonça, Alexandre, Vandenberghe, Rik, Gerhard, Alexander, Butler, Chris R, Danek, Adrian, Synofzik, Matthis, Levin, Johannes, Otto, Markus, Ghidoni, Roberta, Benussi, Alberto, Frisoni, Giovanni B, Sorbi, Sandro, Peakman, Georgia, Todd, Emily, Bocchetta, Martina, Rohrer, Johnathan D, Borroni, Barbara, Members, GENFI Consortium, Afonso, Sónia, Rosario Almeida, Maria, Cauda, Franco, Anderl-Straub, Sarah, Andersson, Christin, Antonell, Anna, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Luisa, Gasparotti, Roberto, Bessi, Valentina, Binetti, Giuliano, Black, Sandra, Borrego-Ecija, Sergi, Bras, Jose, Bruffaerts, Rose, Caroppo, Paola, Cash, David, Castelo-Branco, Miguel, Convery, Rhian, Archetti, Silvana, Cope, Thomas, de Arriba, María, Di Fede, Giuseppe, Díaz, Zigor, Duro, Diana, Fenoglio, Chiara, Ferrari, Camilla, B Ferreira, Catarina, Fox, Nick, Freedman, Morris, Alberici, Antonella, Fumagalli, Giorgio, Gabilondo, Alazne, Gauthier, Serge, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, van Swieten, John C, Jelic, Vesna, Jiskoot, Lize, Karnath, Hans Otto, Keren, Ron, Langheinrich, Tobias, João Leitão, Maria, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, Sanchez-Valle, Raquel, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Moore, Katrina, Nacmias, Benedetta, Nicholas, Jennifer, Öijerstedt, Linn, Olives, Jaume, GENFI Consortium Members, Neurology, Rowe, James [0000-0001-7216-8679], and Apollo - University of Cambridge Repository

Subjects
genetics [Granulins], Frontotemporal dementia, granulin, magnetic resonance imaging, mutation, preclinical, presymptomatic, Atrophy, Brain, Granulins, Humans, Magnetic Resonance Imaging, Mutation, Progranulins, Frontotemporal Dementia, Medizin, genetics [Mutation], diagnostic imaging [Frontotemporal Dementia], frontotemporal dementia, genetics [Progranulins], methods [Magnetic Resonance Imaging], SDG 3 - Good Health and Well-being, pathology [Brain], Settore BIO/13 - Biologia Applicata, ddc:610, diagnostic imaging [Brain], genetics [Frontotemporal Dementia], pathology [Atrophy], Frontotemporal dementia, granulin, magnetic resonance imaging, mutation, preclinical, presymptomatic, General Neuroscience, General Medicine, Psychiatry and Mental health, Clinical Psychology, pathology [Frontotemporal Dementia], Geriatrics and Gerontology
Abstract

Background:Magnetic resonance imaging (MRI) measures may be used as outcome markers in frontotemporal dementia (FTD). Objectives:To predict MRI cortical thickness (CT) at follow-up at the single subject level, using brain MRI acquired at baseline in preclinical FTD. Methods:84 presymptomatic subjects carrying Granulin mutations underwent MRI scans at baseline and at follow-up (31.2±16.5 months). Multivariate nonlinear mixed-effects model was used for estimating individualized CT at follow-up based on baseline MRI data. The automated user-friendly preGRN-MRI script was coded. Results:Prediction accuracy was high for each considered brain region (i.e., prefrontal region, real CT at follow-up versus predicted CT at follow-up, mean error ≤1.87%). The sample size required to detect a reduction in decline in a 1-year clinical trial was equal to 52 subjects (power = 0.80, alpha = 0.05). Conclusion:The preGRN-MRI tool, using baseline MRI measures, was able to predict the expected MRI atrophy at follow-up in presymptomatic subjects carrying GRN mutations with good performances. This tool could be useful in clinical trials, where deviation of CT from the predicted model may be considered an effect of the intervention itself. Swedish Frontotemporal Dementia Initiative Schörling Foundation; Swedish Research Council: JPND Prefrontals, 2015-02926 ,2018-02754; Swedish Alzheimer foundation; Swedish Brain Foundation; Karolinska Institutet Doctoral Funding; KI StratNeuro; Swedish Dementia foundation and Stockholm County Council ALF/Region Stockholm.

Published
2022
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2. MRI data-driven algorithm for the diagnosis of behavioural variant frontotemporal dementia

Author

Manera, Ana L, Dadar, Mahsa, Van Swieten, John Cornelis, Borroni, Barbara, Sanchez-Valle, Raquel, Moreno, Fermin, Laforce Jr, Robert, Graff, Caroline, Synofzik, Matthis, Galimberti, Daniela, Rowe, James Benedict, Masellis, Mario, Tartaglia, Maria Carmela, Finger, Elizabeth, Vandenberghe, Rik, De Mendonca, Alexandre, Tagliavini, Fabrizio, Santana, Isabel, Butler, Christopher R, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Frisoni, Giovanni, Ghidoni, Roberta, Sorbi, Sandro, Rohrer, Jonathan Daniel, Ducharme, Simon, Collins, D Louis, FTLDNI Investigators, Rosen, Howard, Dickerson, Bradford C., Domoto-Reilly, Kimoko, Knopman, David, Boeve, Bradley F., Boxer, Adam L., Kornak, John, Miller, Bruce L., Seeley, William W., Gorno-Tempini, Maria-Luisa, McGinnis, Scott, Mandelli, Maria Luisa, GENFI Consortium, Afonso, Sónia, Almeida, Maria Rosario, Anderl-Straub, Sarah, Andersson, Christin, Antonell, Anna, Archetti, Silvana, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Alberto, Benussi, Luisa, Bessi, Valentina, Binetti, Giuliano, Black, Sandra, Bocchetta, Martina, Borrego-Ecija, Sergi, Bras, Jose, Bruffaerts, Rose, Caroppo, Paola, Cash, David, Castelo-Branco, Miguel, Convery, Rhian, Cope, Thomas, Cosseddu, Maura, Arriba, María De, Fede, Giuseppe Di, Díaz, Zigor, Duro, Diana, Fenoglio, Chiara, Ferrari, Camilla, Ferreira, Carlos, Ferreira, Catarina B., Flanagan, Toby, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gabilondo, Alazne, Gasparotti, Roberto, Gauthier, Serge, Gazzina, Stefano, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Jiskoot, Lize, Karnath, Hans-Otto, Keren, Ron, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, Minkelen, Rick Van, Mitchell, Sara, Moore, Katrina M, Nacmias, Benedetta, Neason, Mollie, Nicholas, Jennifer, Öijerstedt, Linn, Olives, Jaume, Ourselin, Sebastien, Padovani, Alessandro, Panman, Jessica, Papma, Janne, Peakman, Georgia, Piaceri, Irene, Pievani, Michela, Pijnenburg, Yolande, Polito, Cristina, Premi, Enrico, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rittman, Tim, Rogaeva, Ekaterina, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Scarpini, Elio, Schönecker, Sonja, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Tábuas-Pereira, Miguel, Tainta, Mikel, Taipa, Ricardo, Tang-Wai, David, Thomas, David L, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Todd, Emily, Vandamme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Woollacott, Ione, Wlasich, Elisabeth, Zetterberg, Henrik, Zulaica, Miren, Neurology, Amsterdam Neuroscience - Neurodegeneration, Repositório da Universidade de Lisboa, Manera, Ana L [0000-0003-1639-6858], Dadar, Mahsa [0000-0003-4008-2672], Van Swieten, John Cornelis [0000-0001-6278-6844], Borroni, Barbara [0000-0001-9340-9814], Galimberti, Daniela [0000-0002-9284-5953], Rowe, James Benedict [0000-0001-7216-8679], Finger, Elizabeth [0000-0003-4461-7427], Otto, Markus [0000-0002-6647-5944], Rohrer, Jonathan Daniel [0000-0002-6155-8417], Ducharme, Simon [0000-0002-7309-1113], Apollo - University of Cambridge Repository, and Clinical Genetics

Subjects
medicine.medical_specialty, Audiology, Cross-validation, 03 medical and health sciences, 0302 clinical medicine, Text mining, Cognitive neurology, Neuroimaging, SDG 3 - Good Health and Well-being, Medicine, ddc:610, 030304 developmental biology, 0303 health sciences, business.industry, Semantic fluency, medicine.disease, 3. Good health, Random forest, Psychiatry and Mental health, Cohort, Surgery, Neurology (clinical), Differential diagnosis, business, 030217 neurology & neurosurgery, Frontotemporal dementia
Abstract

© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ., Introduction: Structural brain imaging is paramount for the diagnosis of behavioural variant of frontotemporal dementia (bvFTD), but it has low sensitivity leading to erroneous or late diagnosis. Methods: A total of 515 subjects from two different bvFTD cohorts (training and independent validation cohorts) were used to perform voxel-wise morphometric analysis to identify regions with significant differences between bvFTD and controls. A random forest classifier was used to individually predict bvFTD from deformation-based morphometry differences in isolation and together with semantic fluency. Tenfold cross validation was used to assess the performance of the classifier within the training cohort. A second held-out cohort of genetically confirmed bvFTD cases was used for additional validation. Results: Average 10-fold cross-validation accuracy was 89% (82% sensitivity, 93% specificity) using only MRI and 94% (89% sensitivity, 98% specificity) with the addition of semantic fluency. In the separate validation cohort of definite bvFTD, accuracy was 88% (81% sensitivity, 92% specificity) with MRI and 91% (79% sensitivity, 96% specificity) with added semantic fluency scores. Conclusion: Our results show that structural MRI and semantic fluency can accurately predict bvFTD at the individual subject level within a completely independent validation cohort coming from a different and independent database., Data collection and sharing for this project was funded by the Frontotemporal Lobar Degeneration Neuroimaging Initiative (National Institutes of Health Grant R01 AG032306). The study is coordinated through the University of California, San Francisco, Memory and Aging Center. FTLDNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. Brain scan acquisition at the McConnell Brain Imaging was supported by the Brain Canada Foundation with support from Health Canada and the Canada Foundation for Innovation (CFI Project 34874). This work was supported by Italian Ministry of Health (CoEN015 and Ricerca Corrente).

Published
2021
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3. MRI data-driven algorithm for the diagnosis of behavioural variant frontotemporal dementia

Author

Manera, Ana L, Dadar, Mahsa, Van Swieten, John Cornelis, Borroni, Barbara, Sanchez-Valle, Raquel, Moreno, Fermin, Laforce, Robert, Graff, Caroline, Synofzik, Matthis, Galimberti, Daniela, Rowe, James Benedict, Masellis, Mario, Tartaglia, Maria Carmela, Finger, Elizabeth, Vandenberghe, Rik, De Mendonca, Alexandre, Tagliavini, Fabrizio, Santana, Isabel, Butler, Christopher R, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Frisoni, Giovanni, Ghidoni, Roberta, Sorbi, Sandro, Rohrer, Jonathan Daniel, Ducharme, Simon, Collins, D Louis, FTLDNI Investigators, GENFI Consortium, Manera, Ana L [0000-0003-1639-6858], Dadar, Mahsa [0000-0003-4008-2672], Van Swieten, John Cornelis [0000-0001-6278-6844], Borroni, Barbara [0000-0001-9340-9814], Galimberti, Daniela [0000-0002-9284-5953], Rowe, James Benedict [0000-0001-7216-8679], Finger, Elizabeth [0000-0003-4461-7427], Otto, Markus [0000-0002-6647-5944], Rohrer, Jonathan Daniel [0000-0002-6155-8417], Ducharme, Simon [0000-0002-7309-1113], and Apollo - University of Cambridge Repository

Subjects
GENFI Consortium, FTLDNI investigators
Abstract

INTRODUCTION: Structural brain imaging is paramount for the diagnosis of behavioural variant of frontotemporal dementia (bvFTD), but it has low sensitivity leading to erroneous or late diagnosis. METHODS: A total of 515 subjects from two different bvFTD cohorts (training and independent validation cohorts) were used to perform voxel-wise morphometric analysis to identify regions with significant differences between bvFTD and controls. A random forest classifier was used to individually predict bvFTD from deformation-based morphometry differences in isolation and together with semantic fluency. Tenfold cross validation was used to assess the performance of the classifier within the training cohort. A second held-out cohort of genetically confirmed bvFTD cases was used for additional validation. RESULTS: Average 10-fold cross-validation accuracy was 89% (82% sensitivity, 93% specificity) using only MRI and 94% (89% sensitivity, 98% specificity) with the addition of semantic fluency. In the separate validation cohort of definite bvFTD, accuracy was 88% (81% sensitivity, 92% specificity) with MRI and 91% (79% sensitivity, 96% specificity) with added semantic fluency scores. CONCLUSION: Our results show that structural MRI and semantic fluency can accurately predict bvFTD at the individual subject level within a completely independent validation cohort coming from a different and independent database.

Published
2021
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4. Temporal dynamics predict symptom onset and cognitive decline in familial frontotemporal dementia

Author

Whiteside, David J, Malpetti, Maura, Jones, P Simon, Ghosh, Boyd CP, Coyle‐Gilchrist, Ian, van Swieten, John C, Seelaar, Harro, Jiskoot, Lize, Borroni, Barbara, Sanchez‐Valle, Raquel, Moreno, Fermin, Laforce, Robert, Graff, Caroline, Synofzik, Matthis, Galimberti, Daniela, Masellis, Mario, Tartaglia, Maria Carmela, Finger, Elizabeth, Vandenberghe, Rik, de Mendonça, Alexandre, Tagliavini, Fabrizio, Butler, Chris R, Santana, Isabel, Ber, Isabelle Le, Gerhard, Alexander, Ducharme, Simon, Levin, Johannes, Danek, Adrian, Otto, Markus, Sorbi, Sandro, Pasquier, Florence, Bouzigues, Arabella, Russell, Lucy L, Rohrer, Jonathan D, Rowe, James B, Rittman, Timothy, Esteve, Aitana Sogorb, Nelson, Annabel, Heller, Carolin, Greaves, Caroline V, Cash, David, Thomas, David L, Todd, Emily, Benotmane, Hanya, Zetterberg, Henrik, Swift, Imogen J, Nicholas, Jennifer, Samra, Kiran, Bocchetta, Martina, Shafei, Rachelle, Convery, Rhian S, Timberlake, Carolyn, Cope, Thomas, Benussi, Alberto, Premi, Enrico, Gasparotti, Roberto, Archetti, Silvana, Gazzina, Stefano, Cantoni, Valentina, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Borracci, Vittoria, Rossi, Giacomina, Giaccone, Giorgio, Di Fede, Giuseppe, Caroppo, Paola, Tiraboschi, Pietro, Prioni, Sara, Redaelli, Veronica, Tang‐Wai, David, Rogaeva, Ekaterina, Castelo‐Branco, Miguel, Freedman, Morris, Keren, Ron, Black, Sandra, Mitchell, Sara, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Poos, Jackie, Papma, Janne M, Giannini, Lucia, van Minkelen, Rick, Pijnenburg, Yolande, Ferrari, Camilla, Polito, Cristina, Lombardi, Gemma, Bessi, Valentina, Veldsman, Michele, Andersson, Christin, Thonberg, Hakan, Öijerstedt, Linn, Jelic, Vesna, Thompson, Paul, Langheinrich, Tobias, Lladó, Albert, Antonell, Anna, Olives, Jaume, Balasa, Mircea, Bargalló, Nuria, Borrego‐Ecija, Sergi, Verdelho, Ana, Maruta, Carolina, Ferreira, Catarina B, Miltenberger, Gabriel, Simões do Couto, Frederico, Gabilondo, Alazne, Gorostidi, Ana, Villanua, Jorge, Cañada, Marta, Tainta, Mikel, Zulaica, Miren, Barandiaran, Myriam, Alves, Patricia, Bender, Benjamin, Wilke, Carlo, Graf, Lisa, Vogels, Annick, Vandenbulcke, Mathieu, Van Damme, Philip, Bruffaerts, Rose, Poesen, Koen, Rosa‐Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Colliot, Olivier, Sayah, Sabrina, Prix, Catharina, Wlasich, Elisabeth, Wagemann, Olivia, Loosli, Sandra, Schönecker, Sonja, Hoegen, Tobias, Lombardi, Jolina, Anderl‐Straub, Sarah, Rollin, Adeline, Kuchcinski, Gregory, Bertoux, Maxime, Lebouvier, Thibaud, Deramecourt, Vincent, Santiago, Beatriz, Duro, Diana, Leitão, Maria João, Almeida, Maria Rosario, Tábuas‐Pereira, Miguel, Afonso, Sónia, Engel, Annerose, Polyakova, Maryna, Whiteside, David [0000-0002-5890-9220], Apollo - University of Cambridge Repository, GENFI Consortium, Repositório da Universidade de Lisboa, Langheinrich, Tobias, Lladó, Albert, Antonell, Anna, Olives, Jaume, Balasa, Mircea, Bargalló, Nuria, Borrego-Ecija, Sergi, Verdelho, Ana, Maruta, Carolina, Ferreira, Catarina B, Miltenberger, Gabriel, Simões do Couto, Frederico, Gabilondo, Alazne, Gorostidi, Ana, Villanua, Jorge, Cañada, Marta, Tainta, Mikel, Zulaica, Miren, Barandiaran, Myriam, Alves, Patricia, Bender, Benjamin, Wilke, Carlo, Graf, Lisa, Vogels, Annick, Vandenbulcke, Mathieu, Van Damme, Philip, Bruffaerts, Rose, Poesen, Koen, Rosa-Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Colliot, Olivier, Sayah, Sabrina, Prix, Catharina, Wlasich, Elisabeth, Wagemann, Olivia, Loosli, Sandra, Schönecker, Sonja, Hoegen, Tobias, Lombardi, Jolina, Anderl-Straub, Sarah, Rollin, Adeline, Kuchcinski, Gregory, Bertoux, Maxime, Lebouvier, Thibaud, Deramecourt, Vincent, Santiago, Beatriz, Duro, Diana, Leitão, Maria João, Almeida, Maria Rosario, Tábuas-Pereira, Miguel, Afonso, Sónia, Engel, Annerose, Polyakova, Maryna, Esteve, Aitana Sogorb, Nelson, Annabel, Bouzigues, Arabella, Heller, Carolin, Greaves, Caroline V, Cash, David, Thomas, David L, Todd, Emily, Benotmane, Hanya, Zetterberg, Henrik, Swift, Imogen J, Nicholas, Jennifer, Samra, Kiran, Russell, Lucy L, Bocchetta, Martina, Shafei, Rachelle, Convery, Rhian S, Timberlake, Carolyn, Cope, Thomas, Rittman, Timothy, Benussi, Alberto, Premi, Enrico, Gasparotti, Roberto, Archetti, Silvana, Gazzina, Stefano, Cantoni, Valentina, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Borracci, Vittoria, Rossi, Giacomina, Giaccone, Giorgio, Di Fede, Giuseppe, Caroppo, Paola, Tiraboschi, Pietro, Prioni, Sara, Redaelli, Veronica, Tang-Wai, David, Rogaeva, Ekaterina, Castelo-Branco, Miguel, Freedman, Morris, Keren, Ron, Black, Sandra, Mitchell, Sara, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Poos, Jackie, Papma, Janne M, Giannini, Lucia, van Minkelen, Rick, Pijnenburg, Yolande, Ferrari, Camilla, Polito, Cristina, Lombardi, Gemma, Bessi, Valentina, Veldsman, Michele, Andersson, Christin, Thonberg, Hakan, Öijerstedt, Linn, Jelic, Vesna, Thompson, Paul, and Neurology

Subjects
Epidemiology, FEATURED ARTICLE, Medizin, Clinical Neurology, NETWORK CONNECTIVITY, frontotemporal dementia, disease progression, functional magnetic resonance imaging (fMRI), network dynamics, presymptomatic, DISEASE, Cellular and Molecular Neuroscience, Developmental Neuroscience, SDG 3 - Good Health and Well-being, Humans, Cognitive Dysfunction, ddc:610, BRAIN, BATTERY, Science & Technology, Health Policy, Brain, FUNCTIONAL CONNECTIVITY, Magnetic Resonance Imaging, STATE, TIME, Psychiatry and Mental health, COMPENSATION, Frontotemporal Dementia, Mutation, FEATURED ARTICLES, Neurology (clinical), Human medicine, Neurosciences & Neurology, Geriatrics and Gerontology, Life Sciences & Biomedicine
Abstract

© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited., Introduction: We tested whether changes in functional networks predict cognitive decline and conversion from the presymptomatic prodrome to symptomatic disease in familial frontotemporal dementia (FTD). Methods: For hypothesis generation, 36 participants with behavioral variant FTD (bvFTD) and 34 controls were recruited from one site. For hypothesis testing, we studied 198 symptomatic FTD mutation carriers, 341 presymptomatic mutation carriers, and 329 family members without mutations. We compared functional network dynamics between groups, with clinical severity and with longitudinal clinical progression. Results: We identified a characteristic pattern of dynamic network changes in FTD, which correlated with neuropsychological impairment. Among presymptomatic mutation carriers, this pattern of network dynamics was found to a greater extent in those who subsequently converted to the symptomatic phase. Baseline network dynamic changes predicted future cognitive decline in symptomatic participants and older presymptomatic participants. Discussion: Dynamic network abnormalities in FTD predict cognitive decline and symptomatic conversion. Highlights: We investigated brain network predictors of dementia symptom onset Frontotemporal dementia results in characteristic dynamic network patterns Alterations in network dynamics are associated with neuropsychological impairment Network dynamic changes predict symptomatic conversion in presymptomatic carriers Network dynamic changes are associated with longitudinal cognitive decline., GENFI was funded by the Medical Research Council UK (MR/M023664/1), the Bluefield Project, the JPND GENFI-PROX grant (by DLR/BMBF 2019-02248) and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy – ID 390857198). The study was co-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge (BRC-1215-20014), the Cambridge Centre for Parkinson-plus (RG95450); the Wellcome Trust (220258); the Evelyn Trust (17/09) and Medical Research Council (SUAG/092 116768).

Published
2022
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5. Conceptual framework for the definition of preclinical and prodromal frontotemporal dementia

Author

Benussi, Alberto, Alberici, Antonella, Jiskoot, Lize C, Olives, Jaume, Otto, Markus, Ourselin, Sebastien, Panman, Jessica, Papma, Janne M, Pasquier, Florence, Pijnenburg, Yolande, Polito, Cristina, Premi, Enrico, Prioni, Sara, Le Ber, Isabelle, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rinaldi, Daisy, Rittman, Tim, Rogaeva, Ekaterina, Rollin, Adeline, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Masellis, Mario, Santana, Isabel, Santiago, Beatriz, Saracino, Dario, Sayah, Sabrina, Scarpini, Elio, Schönecker, Sonja, Schroeter, Matthias, Shafei, Rachelle, Shoesmith, Christen, Sorbi, Sandro, Nacmias, Benedetta, Swift, Imogen, Tábuas-Pereira, Miguel, Tagliavini, Fabrizio, Tainta, Mikel, Taipa, Ricardo, Tang-Wai, David, Tartaglia, Carmela, Thomas, David L, Thompson, Paul, Rowe, James B, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Todd, Emily, Van Damme, Philip, Vandenberghe, Rik, Vandenbulcke, Mathieu, van Swieten, John C, Veldsman, Michele, Verdelho, Ana, Sanchez-Valle, Raquel, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Woollacott, Ione, Wlasich, Elisabeth, Zetterberg, Henrik, Zulaica, Miren, Seelaar, Harro, Synofzik, Matthis, Consortium, GENFI, Rohrer, Jonathan D, Samra, Kiran, Borroni, Barbara, Afonso, Sónia, Almeida, Maria Rosario, Anderl-Straub, Sarah, Andersson, Christin, Antonell, Anna, Archetti, Silvana, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Russell, Lucy L, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Bertoux, Maxime, Bertrand, Anne, Bessi, Valentina, Black, Sandra, Borrego-Ecija, Sergi, Bouzigues, Arabella, Bras, Jose, Greaves, Caroline V, Brice, Alexis, Bruffaerts, Rose, Butler, Chris R, Camuzat, Agnès, Cañada, Marta, Cantoni, Valentina, Caroppo, Paola, Cash, David, Castelo-Branco, Miguel, Colliot, Olivier, Bocchetta, Martina, Convery, Rhian, Cope, Thomas, Danek, Adrian, de Mendonça, Alexandre, Deramecourt, Vincent, Di Fede, Giuseppe, Díez, Alina, Duro, Diana, Fenoglio, Chiara, Ferrari, Camilla, Ducharme, Simon, Ferreira, Catarina B, Fox, Nick, Freedman, Morris, Funkiewiez, Aurélie, Gabilondo, Alazne, Gauthier, Serge, Gazzina, Stefano, Gerhard, Alexander, Giaccone, Giorgio, Gorostidi, Ana, Finger, Elizabeth, Graff, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Karnath, Hans Otto, Keren, Ron, Kuchcinski, Gregory, Laforce, Robert, Fumagalli, Giorgio, Waldo, Maria Landqvist, Langheinrich, Tobias, Lebouvier, Thibaud, Leitão, Maria João, Levin, Johannes, Lladó, Albert, Lombardi, Gemma, Lombardi, Jolina, Loosli, Sandra, Maruta, Carolina, Galimberti, Daniela, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Moore, Katrina, Moreno, Fermin, Nelson, Annabel, Nicholas, Jennifer, Öijerstedt, Linn, Erasmus MC other, Neurology, Clinical Genetics, Clinical Psychology, Rowe, James [0000-0001-7216-8679], Apollo - University of Cambridge Repository, and GENFI Consortium

Subjects
Epidemiology, Health Policy, prodromal, Prodromal Symptoms, frontotemporal dementia, Psychiatry and Mental health, Cellular and Molecular Neuroscience, presymptomatic, diagnosis [Frontotemporal Dementia], mild cognitive impairment, Developmental Neuroscience, SDG 3 - Good Health and Well-being, frontotemporal lobar degeneration, mental disorders, preclinical, Humans, definition, Neurology (clinical), ddc:610, Geriatrics and Gerontology, mild cognitive and/or behavioral and/or motor impairment, genetics [Frontotemporal Dementia]
Abstract

Funder: EU Joint Programme – Neurodegenerative Disease Research; Id: http://dx.doi.org/10.13039/100013278, Funder: UK Dementia Research Institute; Id: http://dx.doi.org/10.13039/501100017510, The presymptomatic stages of frontotemporal dementia (FTD) are still poorly defined and encompass a long accrual of progressive biological (preclinical) and then clinical (prodromal) changes, antedating the onset of dementia. The heterogeneity of clinical presentations and the different neuropathological phenotypes have prevented a prior clear description of either preclinical or prodromal FTD. Recent advances in therapeutic approaches, at least in monogenic disease, demand a proper definition of these predementia stages. It has become clear that a consensus lexicon is needed to comprehensively describe the stages that anticipate dementia. The goal of the present work is to review existing literature on the preclinical and prodromal phases of FTD, providing recommendations to address the unmet questions, therefore laying out a strategy for operationalizing and better characterizing these presymptomatic disease stages.

Published
2022
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6. Plasma Neurofilament Light for Prediction of Disease Progression in Familial Frontotemporal Lobar Degeneration

Author

Rojas, Julio C, Wang, Ping, Taylor, Joanne B, Veras, Eliseo, Song, Linan, Jeromin, Andreas, Hanlon, David, Yu, Lili, Khinikar, Arvind, Sivasankaran, Rajeev, Kieloch, Agnieszka, Valentin, Marie-Anne, Staffaroni, Adam M, Karydas, Anna M, Mitic, Laura L, Pearlman, Rodney, Kornak, John, Kramer, Joel H, Miller, Bruce L, Kantarci, Kejal, Knopman, David S, Graff-Radford, Neill, Petrucelli, Leonard, Heller, Carolin, Rademakers, Rosa, Irwin, David J, Grossman, Murray, Ramos, Eliana Marisa, Coppola, Giovanni, Mendez, Mario F, Bordelon, Yvette, Dickerson, Bradford C, Ghoshal, Nupur, Huey, Edward D, Cobigo, Yann, Mackenzie, Ian R, Appleby, Brian S, Domoto-Reilly, Kimiko, Hsiung, Ging-Yuek R, Toga, Arthur W, Weintraub, Sandra, Kaufer, Daniel I, Kerwin, Diana, Litvan, Irene, Onyike, Chiadikaobi U, Wolf, Amy, Pantelyat, Alexander, Roberson, Erik D, Tartaglia, Maria C, Foroud, Tatiana, Chen, Weiping, Czerkowicz, Julie, Graham, Danielle L, van Swieten, John C, Borroni, Barbara, Sanchez-Valle, Raquel, Goh, Sheng-Yang M, Moreno, Fermin, Laforce, Robert, Graff, Caroline, Synofzik, Matthis, Galimberti, Daniela, Rowe, James B, Masellis, Mario, Finger, Elizabeth, Vandenberghe, Rik, de Mendonça, Alexandre, Ljubenkov, Peter A, Tagliavini, Fabrizio, Santana, Isabel, Ducharme, Simon, Butler, Chris R, Gerhard, Alexander, Levin, Johannes, Danek, Adrian, Otto, Markus, Sorbi, Sandro, Cash, David M, Heuer, Hilary W, Convery, Rhian S, Bocchetta, Martina, Foiani, Martha, Greaves, Caroline V, Peakman, Georgia, Russell, Lucy, Swift, Imogen, Todd, Emily, Rohrer, Jonathan D, Boeve, Bradley F, Fong, Jamie C, Rosen, Howard J, Boxer, Adam L, ALLFTD, consortia, GENFI, Rojas, Julio C [0000-0002-1308-646X], Cobigo, Yann [0000-0002-0354-4092], Fong, Jamie C [0000-0003-3637-8526], Coppola, Giovanni [0000-0003-2105-1061], Dickerson, Bradford C [0000-0002-5958-3445], Ghoshal, Nupur [0000-0002-6680-6731], Hsiung, Ging-Yuek R [0000-0002-8017-0856], Onyike, Chiadikaobi U [0000-0003-2255-4437], Pantelyat, Alexander [0000-0002-6427-7485], Roberson, Erik D [0000-0002-1810-9763], Laforce, Robert [0000-0002-2031-490X], Galimberti, Daniela [0000-0002-9284-5953], Vandenberghe, Rik [0000-0001-6237-2502], Danek, Adrian [0000-0001-8857-5383], Otto, Markus [0000-0003-4273-4267], Cash, David M [0000-0001-7833-616X], Peakman, Georgia [0000-0002-3319-138X], Todd, Emily [0000-0003-1551-5691], Apollo - University of Cambridge Repository, ARTFL LEFFTDS Longitudinal Frontotemporal Dementia (ALLFTD) Consortium, and Genetic Frontotemporal Dementia Initiative (GENFI) Consortium

Subjects
0301 basic medicine, Male, Aging, 1702 Cognitive Sciences, Medizin, blood [Neurofilament Proteins], Neurodegenerative, Alzheimer's Disease, Cohort Studies, 0302 clinical medicine, Neurofilament Proteins, 80 and over, 2.1 Biological and endogenous factors, Aetiology, Aged, 80 and over, blood [Biomarkers], Philosophy, Frontotemporal lobar degeneration, Middle Aged, Magnetic Resonance Imaging, Frontotemporal Dementia (FTD), Disease Progression, Cognitive Sciences, Female, medicine.symptom, ALLFTD and GENFI consortia, Adult, Neuropsychological function, Neurofilament light, trends [Magnetic Resonance Imaging], Clinical Trials and Supportive Activities, Clinical Sciences, Asymptomatic, Article, 03 medical and health sciences, Young Adult, Disease severity, Clinical Research, Predictive Value of Tests, mental disorders, medicine, Acquired Cognitive Impairment, Genetics, diagnostic imaging [Frontotemporal Lobar Degeneration], Humans, ddc:610, blood [Frontotemporal Lobar Degeneration], neurofilament protein L, Aged, Neurology & Neurosurgery, Prevention, Disease progression, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 1103 Clinical Sciences, medicine.disease, Brain Disorders, 030104 developmental biology, Dementia, Neurology (clinical), Frontotemporal Lobar Degeneration, 1109 Neurosciences, Asymptomatic carrier, Humanities, 030217 neurology & neurosurgery, Clinical progression, Biomarkers
Abstract

Data Availability: Joint ARTFL and LEFFTDS data and biospecimens and GENFI data are available to qualified investigators for replication of the present study results or further projects. Copyright © 2021 The Author(s). OBJECTIVE: We tested the hypothesis that plasma neurofilament light chain (NfL) identifies asymptomatic carriers of familial frontotemporal lobar degeneration (FTLD)-causing mutations at risk of disease progression. METHODS: Baseline plasma NfL concentrations were measured with single-molecule array in original (n = 277) and validation (n = 297) cohorts. C9orf72, GRN, and MAPT mutation carriers and noncarriers from the same families were classified by disease severity (asymptomatic, prodromal, and full phenotype) using the CDR Dementia Staging Instrument plus behavior and language domains from the National Alzheimer's Disease Coordinating Center FTLD module (CDR+NACC-FTLD). Linear mixed-effect models related NfL to clinical variables. RESULTS: In both cohorts, baseline NfL was higher in asymptomatic mutation carriers who showed phenoconversion or disease progression compared to nonprogressors (original: 11.4 ± 7 pg/mL vs 6.7 ± 5 pg/mL, p = 0.002; validation: 14.1 ± 12 pg/mL vs 8.7 ± 6 pg/mL, p = 0.035). Plasma NfL discriminated symptomatic from asymptomatic mutation carriers or those with prodromal disease (original cutoff: 13.6 pg/mL, 87.5% sensitivity, 82.7% specificity; validation cutoff: 19.8 pg/mL, 87.4% sensitivity, 84.3% specificity). Higher baseline NfL correlated with worse longitudinal CDR+NACC-FTLD sum of boxes scores, neuropsychological function, and atrophy, regardless of genotype or disease severity, including asymptomatic mutation carriers. CONCLUSIONS: Plasma NfL identifies asymptomatic carriers of FTLD-causing mutations at short-term risk of disease progression and is a potential tool to select participants for prevention clinical trials. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier: NCT02372773 and NCT02365922. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that in carriers of FTLD-causing mutations, elevation of plasma NfL predicts short-term risk of clinical progression. ALLFTD Consortium (LEFFTDS: U01 AG045390; ARTFL: U54 NS092089; ALLFTD: U19AG063911). J.C.R. is supported by National Institute on Aging–NIH: K23AG059888. AMS is supported by National Institute on Aging–NIH: K23AG061253 and Larry L. Hillblom Foundation: 2018-A-025-FEL. Work was also supported by grants U24 AG021886 and U01 AG016976 and the Bluefield Project to Cure FTD. Samples from the National Centralized Repository for Alzheimer’s Disease and Related Dementias, which receives government support under a cooperative agreement grant (U24 AG21886), were used in this study. The Dementia Research Centre is supported by Alzheimer's Research UK, Alzheimer's Society, Brain Research UK, and The Wolfson Foundation. This work was supported by the National Institute for Health Research UCL/H Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre Clinical Research Facility, and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society, and Alzheimer's Research UK. J.D.R. is supported by a Medical Research Council Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the National Institute for Health Research Rare Disease Translational Research Collaboration (BRC149/NS/MH). R.C. and C.G. are supported by Frontotemporal Dementia Research Studentships in Memory of David Blechner funded through The National Brain Appeal (RCN 290173). M.B. is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517) and by the UK Dementia Research Institute, which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society, and Alzheimer’s Research UK. R.L. is supported by the Canadian Institutes of Health Research and the Chaire de Recherche sur les Aphasies Primaires Progressives Fondation Famille Lemaire. C.G. is supported by the Swedish Frontotemporal Dementia Initiative Schörling Foundation, Swedish Research Council, JPND Prefrontals, 2015–02926, 2018–02754, Swedish Alzheimer Foundation, Swedish Brain Foundation, Karolinska Institutet Doctoral Funding, KI StratNeuro, Swedish Dementia Foundation, and Stockholm County Council ALF/Region Stockholm. J.L. is supported by Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (German Research Foundation, EXC 2145 SyNergy 390857198). This work was also supported by the Medical Research Council UK GENFI grant (MR/M023664/1), the Bluefield Project, the National Institute for Health Research including awards to Cambridge and UCL Biomedical Research Centres, and the JPND GENFI-PROX grant (2019–02248). Several authors of this publication are members of the European Reference Network for Rare Neurologic Diseases, project No. 739510. J.B.R. is supported by NIHR Cambridge Biomedical Research Centre (BRC-1215-20014).

Published
2021
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