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29 results on '"Papma, Janne"'

1. Enhancing cognitive performance prediction by white matter hyperintensity connectivity assessment.

Author

Petersen M, Coenen M, DeCarli C, De Luca A, van der Lelij E, Barkhof F, Benke T, Chen CPLH, Dal-Bianco P, Dewenter A, Duering M, Enzinger C, Ewers M, Exalto LG, Fletcher EM, Franzmeier N, Hilal S, Hofer E, Koek HL, Maier AB, Maillard PM, McCreary CR, Papma JM, Pijnenburg YAL, Schmidt R, Smith EE, Steketee RME, van den Berg E, van der Flier WM, Venkatraghavan V, Venketasubramanian N, Vernooij MW, Wolters FJ, Xu X, Horn A, Patil KR, Eickhoff SB, Thomalla G, Biesbroek JM, Biessels GJ, and Cheng B

Subjects
Humans, Male, Female, Aged, Middle Aged, Cross-Sectional Studies, Cognitive Dysfunction diagnostic imaging, Cognitive Dysfunction physiopathology, Cognition physiology, Neuropsychological Tests, Connectome methods, Brain diagnostic imaging, Brain pathology, White Matter diagnostic imaging, White Matter pathology, Magnetic Resonance Imaging methods
Abstract

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables us to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (i) LNM-informed markers surpass WMH volumes in predicting cognitive performance; and (ii) WMH contributing to cognitive impairment map to specific brain networks. We analysed cross-sectional data of 3485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in four cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based grey and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in grey and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Published
2024
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2. Automatic normative quantification of brain tissue volume to support the diagnosis of dementia: A clinical evaluation of diagnostic accuracy.

Author

Vernooij MW, Jasperse B, Steketee R, Koek M, Vrooman H, Ikram MA, Papma J, van der Lugt A, Smits M, and Niessen WJ

Subjects
Aged, Brain pathology, Dementia pathology, Diagnosis, Differential, Female, Humans, Magnetic Resonance Imaging methods, Male, Middle Aged, Organ Size, Retrospective Studies, Brain diagnostic imaging, Dementia diagnostic imaging, Magnetic Resonance Imaging standards
Abstract

Objectives: To assesses whether automated brain image analysis with quantification of structural brain changes improves diagnostic accuracy in a memory clinic setting., Methods: In 42 memory clinic patients, we evaluated whether automated quantification of brain tissue volumes, hippocampal volume and white matter lesion volume improves diagnostic accuracy for Alzheimer's disease (AD) and frontotemporal dementia (FTD), compared to visual interpretation. Reference data were derived from a dementia-free aging population ( n  = 4915, aged >45 years), and were expressed as age- and sex-specific percentiles. Experienced radiologists determined the most likely imaging-based diagnosis based on structural brain MRI using three strategies (visual assessment of MRI only, quantitative normative information only, or a combination of both). Diagnostic accuracy of each strategy was calculated with the clinical diagnosis as the reference standard., Results: Providing radiologists with only quantitative data decreased diagnostic accuracy both for AD and FTD compared to conventional visual rating. The combination of quantitative with visual information, however, led to better diagnostic accuracy compared to only visual ratings for AD. This was not the case for FTD., Conclusion: Quantitative assessment of structural brain MRI combined with a reference standard in addition to standard visual assessment may improve diagnostic accuracy in a memory clinic setting.

Published
2018
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3. The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment.

Author

Papma JM, Smits M, de Groot M, Mattace Raso FU, van der Lugt A, Vrooman HA, Niessen WJ, Koudstaal PJ, van Swieten JC, van der Veen FM, and Prins ND

Subjects
Aged, Aged, 80 and over, Atrophy pathology, Case-Control Studies, Cognitive Dysfunction diagnostic imaging, Female, Humans, Male, Middle Aged, Neuropsychological Tests, Regression Analysis, Temporal Lobe physiopathology, Cognitive Dysfunction physiopathology, Gyrus Cinguli physiopathology, Hippocampus pathology, Hippocampus physiopathology, Magnetic Resonance Imaging methods, Memory, Episodic, Nerve Net physiopathology
Abstract

Objectives: Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI)., Method: MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus., Results: We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors., Conclusions: Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI., Key Points: • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI.

Published
2017
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4. Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge.

Author

Bron EE, Smits M, van der Flier WM, Vrenken H, Barkhof F, Scheltens P, Papma JM, Steketee RM, Méndez Orellana C, Meijboom R, Pinto M, Meireles JR, Garrett C, Bastos-Leite AJ, Abdulkadir A, Ronneberger O, Amoroso N, Bellotti R, Cárdenas-Peña D, Álvarez-Meza AM, Dolph CV, Iftekharuddin KM, Eskildsen SF, Coupé P, Fonov VS, Franke K, Gaser C, Ledig C, Guerrero R, Tong T, Gray KR, Moradi E, Tohka J, Routier A, Durrleman S, Sarica A, Di Fatta G, Sensi F, Chincarini A, Smith GM, Stoyanov ZV, Sørensen L, Nielsen M, Tangaro S, Inglese P, Wachinger C, Reuter M, van Swieten JC, Niessen WJ, and Klein S

Subjects
Aged, Aged, 80 and over, Alzheimer Disease classification, Cognitive Dysfunction classification, Diagnosis, Computer-Assisted standards, Female, Humans, Image Interpretation, Computer-Assisted standards, Magnetic Resonance Imaging standards, Male, Middle Aged, Sensitivity and Specificity, Algorithms, Alzheimer Disease diagnosis, Cognitive Dysfunction diagnosis, Diagnosis, Computer-Assisted methods, Image Interpretation, Computer-Assisted methods, Magnetic Resonance Imaging methods
Abstract

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n=30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Published
2015
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5. Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients

Author

Biesbroek, J Matthijs, Coenen, Mirthe, DeCarli, Charles, Fletcher, Evan M, Maillard, Pauline M, Initiative, Alzheimer's Disease Neuroimaging, Barkhof, Frederik, Barnes, Josephine, Benke, Thomas, Chen, Christopher PLH, Dal‐Bianco, Peter, Dewenter, Anna, Duering, Marco, Enzinger, Christian, Ewers, Michael, Exalto, Lieza G, Franzmeier, Nicolai, Hilal, Saima, Hofer, Edith, Koek, Huiberdina L, Maier, Andrea B, McCreary, Cheryl R, Papma, Janne M, Paterson, Ross W, Pijnenburg, Yolande AL, Rubinski, Anna, Schmidt, Reinhold, Schott, Jonathan M, Slattery, Catherine F, Smith, Eric E, Sudre, Carole H, Steketee, Rebecca ME, Teunissen, Charlotte E, van den Berg, Esther, van der Flier, Wiesje M, Venketasubramanian, Narayanaswamy, Venkatraghavan, Vikram, Vernooij, Meike W, Wolters, Frank J, Xin, Xu, Kuijf, Hugo J, and Biessels, Geert Jan

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Vascular Cognitive Impairment/Dementia, Dementia, Cerebrovascular, Aging, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease Related Dementias (ADRD), Acquired Cognitive Impairment, Alzheimer's Disease, Clinical Research, Neurodegenerative, Neurological, Humans, Female, Middle Aged, Aged, Aged, 80 and over, Male, White Matter, Arteriolosclerosis, Amyloid beta-Peptides, Magnetic Resonance Imaging, amyloid pathology, arteriolosclerosis, dementia, lesion pattern, white matter hyperintensities, Alzheimer's Disease Neuroimaging Initiative, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionWhite matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status.MethodsIndividual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.ResultsVRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p

Published
2024

6. Network structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia

Author

Shafiei, Golia, Bazinet, Vincent, Dadar, Mahsa, Manera, Ana L, Collins, D Louis, Dagher, Alain, Borroni, Barbara, Sanchez-Valle, Raquel, Moreno, Fermin, Laforce, Robert, Graff, Caroline, Synofzik, Matthis, Galimberti, Daniela, Rowe, James B, Masellis, Mario, Tartaglia, Maria Carmela, Finger, Elizabeth, Vandenberghe, Rik, de Mendonça, Alexandre, Tagliavini, Fabrizio, Santana, Isabel, Butler, Chris, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Sorbi, Sandro, Jiskoot, Lize C, Seelaar, Harro, van Swieten, John C, Rohrer, Jonathan D, Misic, Bratislav, Ducharme, Simon, Initiative, Frontotemporal Lobar Degeneration Neuroimaging, 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, Initiative, GENetic Frontotemporal dementia, 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, van der Ende, Emma, Poos, Jackie, Papma, Janne M, Giannini, Lucia, and van Minkelen, Rick

Subjects
Biomedical and Clinical Sciences, Health Sciences, Psychology, Acquired Cognitive Impairment, Dementia, Aging, Neurodegenerative, Frontotemporal Dementia (FTD), Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Alzheimer's Disease, Aetiology, 2.1 Biological and endogenous factors, Neurological, Humans, Frontotemporal Dementia, Transcriptome, Brain, Pick Disease of the Brain, Atrophy, Connectome, Magnetic Resonance Imaging, Neuropsychological Tests, Frontotemporal Lobar Degeneration Neuroimaging Initiative, GENetic Frontotemporal dementia Initiative, connectome, disease epicentre, frontotemporal dementia, gene expression, network spreading, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioural variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). First, we identified distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbours, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicentre of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and antero-medial temporal areas. We found that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability, providing an explanation as to how heterogenous pathological entities can lead to the same clinical syndrome.

Published
2023

7. Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts

Author

Coenen, Mirthe, Biessels, Geert Jan, DeCarli, Charles, Fletcher, Evan F, Maillard, Pauline M, Initiative, Alzheimer's Disease Neuroimaging, Barkhof, Frederik, Barnes, Josephine, Benke, Thomas, Boomsma, Jooske MF, Chen, Christopher PLH, Dal-Bianco, Peter, Dewenter, Anna, Duering, Marco, Enzinger, Christian, Ewers, Michael, Exalto, Lieza G, Franzmeier, Nicolai, Groeneveld, Onno, Hilal, Saima, Hofer, Edith, Koek, Huiberdina L, Maier, Andrea B, McCreary, Cheryl R, Papma, Janne M, Paterson, Ross W, Pijnenburg, Yolande AL, Rubinski, Anna, Schmidt, Reinhold, Schott, Jonathan M, Slattery, Catherine F, Smith, Eric E, Sudre, Carole H, Steketee, Rebecca ME, van den Berg, Esther, van der Flier, Wiesje M, Venketasubramanian, Narayanaswamy, Vernooij, Meike W, Wolters, Frank J, Xin, Xu, Biesbroek, J Matthijs, and Kuijf, Hugo J

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Dementia, Brain Disorders, Networking and Information Technology R&D (NITRD), Clinical Research, Aging, Neurosciences, Neurodegenerative, Acquired Cognitive Impairment, Cerebrovascular, Alzheimer's Disease Related Dementias (ADRD), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Machine Learning and Artificial Intelligence, Vascular Cognitive Impairment/Dementia, Neurological, Humans, White Matter, Brain, Magnetic Resonance Imaging, Neuroimaging, Cognitive Dysfunction, Multicenter Studies as Topic, White matter hyperintensities, Brain MRI, Distribution frequencies, Lesion location, Alzheimer's Disease Neuroimaging Initiative, Biological psychology, Clinical and health psychology
Abstract

IntroductionThe spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns.MethodsIndividual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented.ResultsWMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected.DiscussionAggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.

Published
2023

8. Investigating the clinico-anatomical dissociation in the behavioral variant of Alzheimer disease

Author

Singleton, Ellen H, Pijnenburg, Yolande AL, Sudre, Carole H, Groot, Colin, Kochova, Elena, Barkhof, Frederik, La Joie, Renaud, Rosen, Howard J, Seeley, William W, Miller, Bruce, Cardoso, M Jorge, Papma, Janne, Scheltens, Philip, Rabinovici, Gil D, and Ossenkoppele, Rik

Subjects
Biomedical and Clinical Sciences, Health Sciences, Brain Disorders, Aging, Biomedical Imaging, Neurodegenerative, Basic Behavioral and Social Science, Acquired Cognitive Impairment, Dementia, Behavioral and Social Science, Neurosciences, Clinical Research, Alzheimer's Disease, Alzheimer's Disease Related Dementias (ADRD), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 2.1 Biological and endogenous factors, Neurological, Alzheimer Disease, Frontotemporal Dementia, Gray Matter, Humans, Magnetic Resonance Imaging, Retrospective Studies, Alzheimer&#8217, s disease, Behavior, Frontotemporal dementia, MRI, PET, Alzheimer’s disease, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundWe previously found temporoparietal-predominant atrophy patterns in the behavioral variant of Alzheimer's disease (bvAD), with relative sparing of frontal regions. Here, we aimed to understand the clinico-anatomical dissociation in bvAD based on alternative neuroimaging markers.MethodsWe retrospectively included 150 participants, including 29 bvAD, 28 "typical" amnestic-predominant AD (tAD), 28 behavioral variant of frontotemporal dementia (bvFTD), and 65 cognitively normal participants. Patients with bvAD were compared with other diagnostic groups on glucose metabolism and metabolic connectivity measured by [18F]FDG-PET, and on subcortical gray matter and white matter hyperintensity (WMH) volumes measured by MRI. A receiver-operating-characteristic-analysis was performed to determine the neuroimaging measures with highest diagnostic accuracy.ResultsbvAD and tAD showed predominant temporoparietal hypometabolism compared to controls, and did not differ in direct contrasts. However, overlaying statistical maps from contrasts between patients and controls revealed broader frontoinsular hypometabolism in bvAD than tAD, partially overlapping with bvFTD. bvAD showed greater anterior default mode network (DMN) involvement than tAD, mimicking bvFTD, and reduced connectivity of the posterior cingulate cortex with prefrontal regions. Analyses of WMH and subcortical volume showed closer resemblance of bvAD to tAD than to bvFTD, and larger amygdalar volumes in bvAD than tAD respectively. The top-3 discriminators for bvAD vs. bvFTD were FDG posterior-DMN-ratios (bvADbvFTD, area under the curve [AUC] range 0.85-0.91, all p tAD), MRI anterior-DMN-ratios (bvADConclusionsSubtle frontoinsular hypometabolism and anterior DMN involvement may underlie the prominent behavioral phenotype in bvAD.

Published
2020

9. Clinical value of cerebrospinal fluid neurofilament light chain in semantic dementia.

Author

Meeter, Lieke HH, Steketee, Rebecca ME, Salkovic, Dina, Vos, Maartje E, Grossman, Murray, McMillan, Corey T, Irwin, David J, Boxer, Adam L, Rojas, Julio C, Olney, Nicholas T, Karydas, Anna, Miller, Bruce L, Pijnenburg, Yolande AL, Barkhof, Frederik, Sánchez-Valle, Raquel, Lladó, Albert, Borrego-Ecija, Sergi, Diehl-Schmid, Janine, Grimmer, Timo, Goldhardt, Oliver, Santillo, Alexander F, Hansson, Oskar, Vestberg, Susanne, Borroni, Barbara, Padovani, Alessandro, Galimberti, Daniela, Scarpini, Elio, Rohrer, Jonathan D, Woollacott, Ione OC, Synofzik, Matthis, Wilke, Carlo, de Mendonca, Alexandre, Vandenberghe, Rik, Benussi, Luisa, Ghidoni, Roberta, Binetti, Giuliano, Niessen, Wiro J, Papma, Janne M, Seelaar, Harro, Jiskoot, Lize C, de Jong, Frank Jan, Donker Kaat, Laura, Del Campo, Marta, Teunissen, Charlotte E, Bron, Esther E, Van den Berg, Esther, and Van Swieten, John C

Subjects
Humans, Neurofilament Proteins, Magnetic Resonance Imaging, Proportional Hazards Models, Case-Control Studies, Retrospective Studies, Cross-Sectional Studies, Neuropsychological Tests, Aged, Middle Aged, Female, Male, Frontotemporal Dementia, Neuroimaging, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

BackgroundSemantic dementia (SD) is a neurodegenerative disorder characterised by progressive language problems falling within the clinicopathological spectrum of frontotemporal lobar degeneration (FTLD). The development of disease-modifying agents may be facilitated by the relative clinical and pathological homogeneity of SD, but we need robust monitoring biomarkers to measure their efficacy. In different FTLD subtypes, neurofilament light chain (NfL) is a promising marker, therefore we investigated the utility of cerebrospinal fluid (CSF) NfL in SD.MethodsThis large retrospective multicentre study compared cross-sectional CSF NfL levels of 162 patients with SD with 65 controls. CSF NfL levels of patients were correlated with clinical parameters (including survival), neuropsychological test scores and regional grey matter atrophy (including longitudinal data in a subset).ResultsCSF NfL levels were significantly higher in patients with SD (median: 2326 pg/mL, IQR: 1628-3593) than in controls (577 (446-766), p

Published
2019

11. Early neurotransmitters changes in prodromal frontotemporal dementia

Author

Premi, Enrico, Pengo, Marta, Mattioli, Irene, Cantoni, Valentina, Dukart, Juergen, Gasparotti, Roberto, Buratti, Emanuele, Padovani, Alessandro, Bocchetta, Martina, Todd, Emily G., Bouzigues, Arabella, Cash, David M., Convery, Rhian S., Russell, Lucy L., Thomas, David L., van Swieten, John C., Jiskoot, Lize C., Seelaar, Harro, Galimberti, Daniela, Sanchez-Valle, Raquel, Laforce, Robert, Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B., Tsvetanov, Kamen A., Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, de Mendonça, Alexandre, Santana, Isabel, Butler, Chris R., Ducharme, Simon, Gerhard, Alexander, Danek, Adrian, Levin, Johannes, Otto, Markus, Sorbi, Sandro, Le Ber, Isabelle, Pasquier, Florence, Rohrer, Jonathan D., Borroni, Barbara, Foster, Phoebe, Tiraboschi, Pietro, Esteve, Aitana Sogorb, Heller, Carolin, Greaves, Caroline V., Zetterberg, Henrik, Swift, Imogen J., Samra, Kiran, Shafei, Rachelle, Timberlake, Carolyn, Cope, Thomas, Rittman, Timothy, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Borracci, Vittoria, Rossi, Giacomina, Giaccone, Giorgio, Di Fede, Giuseppe, Caroppo, Paola, 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, Nacmias, Benedetta, 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, do Couto, Frederico Simões, 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, Saracino, Dario, 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, Repositório da Universidade de Lisboa, Bruffaerts, Rose, Genetic Frontotemporal dementia Initiative (GENFI), Neurology, Verdelho, Ana, Maruta, Carolina, Ferreira, Catarina B, Miltenberger, Gabriel, do Couto, Frederico Simões, 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, Poesen, Koen, Rosa-Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Saracino, Dario, 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, Esteve, Aitana Sogorb, Heller, Carolin, Greaves, Caroline V, Zetterberg, Henrik, Swift, Imogen J, Samra, Kiran, Shafei, Rachelle, Timberlake, Carolyn, Cope, Thomas, Rittman, Timothy, 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, Nacmias, Benedetta, 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, and Borrego-Ecija, Sergi

Subjects
Serotonin, Positron emission tomography, Frontotemporal dementia, Frontotemporal lobar degeneration, Genes, Magnetic resonance imaging, Mutation, Neurotransmitters, C9orf72 Protein, Dopamine, Medizin, tau Proteins, diagnostic imaging [Frontotemporal Dementia], Acetylcholine, genetics [tau Proteins], methods [Magnetic Resonance Imaging], Pick Disease of the Brain, Neurology, ddc:570, Humans, Human medicine, genetics [Frontotemporal Dementia], genetics [C9orf72 Protein]
Abstract

Crown Copyright © 2023 Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., Background: Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches. Methods: In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission. We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD. Results: In prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p < 0.05, Family Wise Error corrected). In symptomatic FTD, a widespread involvement of dopamine, serotonin, glutamate and acetylcholine pathways across all genetic subtypes was found. Social cognition scores, loss of empathy and poor response to emotional cues were found to correlate with the strength of GMV colocalization of dopamine and serotonin pathways (all p < 0.01). Conclusions: This study, indirectly assessing neurotransmitter deficits in monogenic FTD, provides novel insight into disease mechanisms and might suggest potential therapeutic targets to counteract disease-related symptoms., This work is supported by JPND grant “GENFI-prox” (2019–02248), the Centre d'Investigation Clinique (ICM, France) and the Centre pour l'Acquisition et le Traitement des Images platform (CATI, France), the UK Medical Research Council, the Italian Ministry of Health (CoEN015 and Ricerca Corrente), and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant, and the Italian Ministry of Health (GR-2018-12365105). This work was also supported by the MRC UK GENFI grant (MR/M023664/1), the Alzheimer's Society grant (AS-PG-16-007), and the Bluefield Project. This work was funded 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).

Published
2023
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12. Language impairment in the genetic forms of behavioural variant frontotemporal dementia

Author

Samra, Kiran, MacDougall, Amy M., Bouzigues, Arabella, Bocchetta, Martina, Cash, David M., Greaves, Caroline V., Convery, Rhian S., van Swieten, John C., Seelaar, Harro, Jiskoot, Lize, Moreno, Fermin, Gabilondo, Alazne, Gorostidi, Ana, Villanua, Jorge, Cañada, Marta, Tainta, Mikel, Zulaica, Miren, Barandiaran, Myriam, Alves, Patricia, Bender, Benjamin, Wilke, Carlo, Sanchez-Valle, Raquel, Graf, Lisa, Vogels, Annick, Vandenbulcke, Mathieu, Van Damme, Philip, Bruffaerts, Rose, Poesen, Koen, Rosa-Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Laforce, Robert, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Saracino, Dario, Colliot, Olivier, Sayah, Sabrina, Prix, Catharina, Wlasich, Elisabeth, Wagemann, Olivia, Loosli, Sandra, Graff, Caroline, Schönecker, Sonja, Hoegen, Tobias, Lombardi, Jolina, Anderl-Straub, Sarah, Rollin, Adeline, Kuchcinski, Gregory, Bertoux, Maxime, Lebouvier, Thibaud, Deramecourt, Vincent, Santiago, Beatriz, Masellis, Mario, Duro, Diana, Leitão, Maria João, Almeida, Maria Rosario, Tábuas-Pereira, Miguel, Afonso, Sónia, Tartaglia, Maria Carmela, Rowe, James B., Borroni, Barbara, Finger, Elizabeth, Synofzik, Matthis, Galimberti, Daniela, Vandenberghe, Rik, De Mendonça, Alexandre, Butler, Christopher R., Gerhard, Alexander, Ducharme, Simon, Le Ber, Isabelle, Tiraboschi, Pietro, Santana, Isabel, Pasquier, Florence, Levin, Johannes, Otto, Markus, Sorbi, Sandro, Rohrer, Jonathan D., Russell, Lucy L., Nelson, Annabel, Thomas, David L., Todd, Emily, Benotmane, Hanya, Nicholas, Jennifer, Shafei, Rachelle, 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, 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, Nacmias, Benedetta, 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-Miltenyi, Gabriel, Simões Do Couto, Frederico, Neurology, Amsterdam Neuroscience - Neurodegeneration, Repositório da Universidade de Lisboa, Genetic FTD Initiative (GENFI), Erasmus MC other, Radiology & Nuclear Medicine, Clinical Genetics, Samra, Kiran [0000-0002-3105-7099], Apollo - University of Cambridge Repository, do Couto, Frederico Simões, 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, Saracino, Dario, 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, Nelson, Annabel, Thomas, David L, Todd, Emily, Benotmane, Hanya, Nicholas, Jennifer, Shafei, Rachelle, 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, Nacmias, Benedetta, 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, and Miltenberger, Gabriel

Subjects
Progranulin, Medizin, genetics [Mutation], tau Proteins, diagnostic imaging [Frontotemporal Dementia], frontotemporal dementia, Settore BIO/13 - Biologia Applicata, C9orf72, progranulin, Genetics, Humans, genetics, Language Development Disorders, ddc:610, tau, genetics [Frontotemporal Dementia], genetics [C9orf72 Protein], Frontotemporal dementia, Language, Tau, language, C9orf72 Protein, Magnetic Resonance Imaging, genetics [tau Proteins], Neurology, FOS: Biological sciences, Frontotemporal Dementia, Mutation, Human medicine, Neurology (clinical), Atrophy
Abstract

Funder: CIBERNED, Funder: Lemaire Family Foundation, Funder: Swedish Frontotemporal Dementia Initiative Schorling Foundation, Funder: Swedish Alzheimer Foundation, Funder: Karolinska Institutet; doi: http://dx.doi.org/10.13039/501100004047, Funder: Weston Brain Institute; doi: http://dx.doi.org/10.13039/100012479, Funder: Miriam Marks Brain Research UK, BACKGROUND: Behavioural variant fronto-temporal dementia (bvFTD) is characterised by a progressive change in personality in association with atrophy of the frontal and temporal lobes. Whilst language impairment has been described in people with bvFTD, little is currently known about the extent or type of linguistic difficulties that occur, particularly in the genetic forms. METHODS: Participants with genetic bvFTD along with healthy controls were recruited from the international multicentre Genetic FTD Initiative (GENFI). Linguistic symptoms were assessed using items from the Progressive Aphasia Severity Scale (PASS). Additionally, participants undertook the Boston Naming Test (BNT), modified Camel and Cactus Test (mCCT) and a category fluency test. Participants underwent a 3T volumetric T1-weighted MRI, with language network regional brain volumes measured and compared between the genetic groups and controls. RESULTS: 76% of the genetic bvFTD cohort had impairment in at least one language symptom: 83% C9orf72, 80% MAPT and 56% GRN mutation carriers. All three genetic groups had significantly impaired functional communication, decreased fluency, and impaired sentence comprehension. C9orf72 mutation carriers also had significantly impaired articulation and word retrieval as well as dysgraphia whilst the MAPT mutation group also had impaired word retrieval and single word comprehension. All three groups had difficulties with naming, semantic knowledge and verbal fluency. Atrophy in key left perisylvian language regions differed between the groups, with generalised involvement in the C9orf72 group and more focal temporal and insula involvement in the other groups. Correlates of language symptoms and test scores also differed between the groups. CONCLUSIONS: Language deficits exist in a substantial proportion of people with familial bvFTD across all three genetic groups. Significant atrophy is seen in the dominant perisylvian language areas and correlates with language impairments within each of the genetic groups. Improved understanding of the language phenotype in the main genetic bvFTD subtypes will be helpful in future studies, particularly in clinical trials where accurate stratification and monitoring of disease progression is required.

Published
2023
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13. 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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14. 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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15. Data‐driven staging of genetic frontotemporal dementia using multi‐modal <scp>MRI</scp>

Author

McCarthy, Jillian, Borroni, Barbara, Tartaglia, Maria Carmela, Neason, Mollie, Nicholas, Jennifer, Öijerstedt, Linn, Olives, Jaume, Ourselin, Sebastien, Padovani, Alessandro, Panman, Jessica, Papma, Janne, Peakman, Georgia, Piaceri, Irene, Finger, Elizabeth, Pievani, Michela, Pijnenburg, Yolande, Polito, Cristina, Premi, Enrico, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rittman, Tim, Rogaeva, Ekaterina, Vandenberghe, Rik, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Scarpini, Elio, Schönecker, Sonja, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Tábuas-Pereira, Miguel, de Mendonça, Alexandre, Tainta, Mikel, Taipa, Ricardo, Tang-Wai, David, Thomas, David L, Thompson, Paul, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Todd, Emily, Vandamme, Philip, Tagliavini, Fabrizio, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Woollacott, Ione, Wlasich, Elisabeth, Zetterberg, Henrik, Zulaica, Miren, Santana, Isabel, Butler, Chris, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Sanchez-Valle, Raquel, Otto, Markus, Frisoni, Giovanni B, Ghidoni, Roberta, Sorbi, Sandro, Jiskoot, Lize C, Seelaar, Harro, van Swieten, John C, Rohrer, Jonathan D, Iturria-Medina, Yasser, Ducharme, Simon, Moreno, Fermin, Initiative, GENetic Frontotemporal Dementia, Afonso, Sónia, Almeida, Maria Rosario, Anderl-Straub, Sarah, Andersson, Christin, Antonell, Anna, Archetti, Silvana, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Laforce, Robert, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Alberto, Benussi, Luisa, Bessi, Valentina, Binetti, Giuliano, Black, Sandra, Bocchetta, Martina, Borrego-Ecija, Sergi, Graff, Caroline, Bras, Jose, Bruffaerts, Rose, Cañada, Marta, Cantoni, Valentina, Caroppo, Paola, Cash, David, Castelo-Branco, Miguel, Convery, Rhian, Cope, Thomas, Cosseddu, Maura, Synofzik, Matthis, de Arriba, María, Di Fede, Giuseppe, Díaz, Zigor, Díez, Alina, Duro, Diana, Fenoglio, Chiara, Ferrari, Camilla, Ferreira, Carlos, Ferreira, Catarina B, Flanagan, Toby, Galimberti, Daniela, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gabilondo, Alazne, Gasparotti, Roberto, Gauthier, Serge, Gazzina, Stefano, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Rowe, James B, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Karnath, Hans Otto, Keren, Ron, Langheinrich, Tobias, Leitão, Maria João, Lladó, Albert, Masellis, Mario, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Moore, Katrina M, Nacmias, Benedetta, Repositório da Universidade de Lisboa, Neurology, Amsterdam Neuroscience - Neurodegeneration, McCarthy, Jillian [0000-0002-9285-0023], Borroni, Barbara [0000-0001-9340-9814], Apollo - University of Cambridge Repository, GENetic Frontotemporal Dementia Initiative (GENFI), Clinical Genetics, and Clinical Psychology

Subjects
disease progression, frontotemporal dementia, magnetic resonance imaging, unsupervised machine learning, BIOMARKER, Heterozygote, Medizin, Neuroimaging, diagnostic imaging [Frontotemporal Dementia], Magnetic resonance imaging, SDG 3 - Good Health and Well-being, HARMONIZATION, Settore BIO/13 - Biologia Applicata, NEUROFILAMENT LIGHT-CHAIN, BEHAVIORAL VARIANT, CRITERIA, Humans, Radiology, Nuclear Medicine and imaging, ddc:610, Cross-Sectional Studies, Language, Magnetic Resonance Imaging, Frontotemporal Dementia, genetics [Frontotemporal Dementia], Unsupervised machine learning, Disease progression, Science & Technology, Radiological and Ultrasound Technology, Radiology, Nuclear Medicine & Medical Imaging, Neurosciences, DEGENERATION, DIFFUSION, psychology [Frontotemporal Dementia], Neurology, GRAY-MATTER ATROPHY, Neurosciences & Neurology, Neurology (clinical), Anatomy, Life Sciences & Biomedicine, GENFI, CLINICAL-TRIALS, Frontotemporal dementia
Abstract

Funder: Fondation Brain Canada; Id: http://dx.doi.org/10.13039/100009408, Funder: Fonds de Recherche du Québec ‐ Santé; Id: http://dx.doi.org/10.13039/501100000156, Funder: Health Canada; Id: http://dx.doi.org/10.13039/501100000008, Funder: Brain Canada Foundation; Id: http://dx.doi.org/10.13039/100009408, Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high-dimensional large-scale population datasets to obtain individual scores of disease stage. We used cross-sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting-state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI-obtained disease scores to the estimated years to onset (age-mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre-dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data-driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics.

Published
2022
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16. Network structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia

Author

Shafiei, Golia, Bazinet, Vincent, Dadar, Mahsa, Manera, Ana L., Collins, D. Louis, Dagher, Alain, Borroni, Barbara, Sanchez-Valle, Raquel, Moreno, Fermin, Laforce, Robert, Graff, Caroline, Synofzik, Matthis, Galimberti, Daniela, Rowe, James B., Masellis, Mario, Tartaglia, Maria Carmela, Finger, Elizabeth, Vandenberghe, Rik, de Mendonça, Alexandre, Tagliavini, Fabrizio, Santana, Isabel, Butler, Chris, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Sorbi, Sandro, Jiskoot, Lize C., Seelaar, Harro, van Swieten, John C., Rohrer, Jonathan D., Misic, Bratislav, Ducharme, Simon, 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, 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, van Der Ende, Emma, Poos, Jackie, Papma, Janne M., Giannini, Lucia, van Minkelen, Rick, Pijnenburg, Yolande, Nacmias, Benedetta, 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, Rosa-Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Saracino, Dario, 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, Fede, Giuseppe Di, do Couto, Frederico Simões, Shafiei, Golia [0000-0002-2036-5571], Dadar, Mahsa [0000-0003-4008-2672], Collins, D Louis [0000-0002-8432-7021], Dagher, Alain [0000-0002-0945-5779], Sanchez-Valle, Raquel [0000-0001-7750-896X], Graff, Caroline [0000-0002-9949-2951], Synofzik, Matthis [0000-0002-2280-7273], Masellis, Mario [0000-0002-6244-2096], Jiskoot, Lize C [0000-0002-8120-7366], Seelaar, Harro [0000-0003-1989-7527], Misic, Bratislav [0000-0003-0307-2862], Ducharme, Simon [0000-0002-7309-1113], and Apollo - University of Cambridge Repository

Subjects
Aging, connectome, disease epicentre, frontotemporal dementia, gene expression, network spreading, GENetic Frontotemporal dementia Initiative, Medizin, Neurodegenerative, Neuropsychological Tests, Alzheimer's Disease, diagnostic imaging [Frontotemporal Dementia], Medical and Health Sciences, Pick Disease of the Brain, Settore BIO/13 - Biologia Applicata, pathology [Brain], Frontotemporal Lobar Degeneration Neuroimaging Initiative, Acquired Cognitive Impairment, Connectome, 2.1 Biological and endogenous factors, Humans, ddc:610, Aetiology, genetics [Frontotemporal Dementia], pathology [Atrophy], Neurology & Neurosurgery, Psychology and Cognitive Sciences, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain, Magnetic Resonance Imaging, Brain Disorders, Frontotemporal Dementia (FTD), pathology [Pick Disease of the Brain], Neurological, pathology [Frontotemporal Dementia], Dementia, Neurology (clinical), Atrophy, Transcriptome
Abstract

Copyright © The Author(s) 2022. Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioural variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). First, we identified distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbours, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicentre of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and antero-medial temporal areas. We found that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability, providing an explanation as to how heterogenous pathological entities can lead to the same clinical syndrome. Canada First Research Excellence Fund, awarded to McGill University for the Healthy Brains for Healthy Lives initiative. B.M. acknowledges support from the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant RGPIN #017-04265) and from the Canada Research Chairs Program. S.D. receives salary support from the Fonds de Recherche du Québec—Santé (FRQS). G.S. acknowledges support from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Fonds de recherche du Québec—Nature et Technologies (FRQNT). V.B. acknowledges support from the Fonds de recherche du Québec—Nature et Technologies (FRQNT). FTLDNI data collection and sharing was funded by the Frontotemporal Lobar Degeneration Neuroimaging Initiative (National Institutes of Health Grant R01 AG032306) and 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.

Published
2022
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17. Structural brain splitting is a hallmark of Granulin-related frontotemporal dementia

Author

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

Subjects
Aging, Progranulin, genetics [Granulins], Medizin, Granulin, Pick Disease of the Brain, pathology [Brain], Humans, ddc:610, diagnostic imaging [Brain], genetics [Frontotemporal Dementia], Granulins, pathology [Atrophy], General Neuroscience, Brain, Frontotemporal dementia, Graph theory, Mutation, Structural MRI, Magnetic Resonance Imaging, pathology [Pick Disease of the Brain], pathology [Frontotemporal Dementia], Neurology (clinical), Geriatrics and Gerontology, Atrophy, Developmental Biology
Abstract

© 2022 Elsevier Inc. All rights reserved., Frontotemporal dementia associated with granulin (GRN) mutations presents asymmetric brain atrophy. We applied a Minimum Spanning Tree plus an Efficiency Cost Optimization approach to cortical thickness data in order to test whether graph theory measures could identify global or local impairment of connectivity in the presymptomatic phase of pathology, where other techniques failed in demonstrating changes. We included 52 symptomatic GRN mutation carriers (SC), 161 presymptomatic GRN mutation carriers (PSC) and 341 non-carriers relatives from the Genetic Frontotemporal dementia research Initiative cohort. Group differences of global, nodal and edge connectivity in (Minimum Spanning Tree plus an Efficiency Cost Optimization) graph were tested via Structural Equation Models. Global graph perturbation was selectively impaired in SC compared to non-carriers, with no changes in PSC. At the local level, only SC exhibited perturbation of frontotemporal nodes, but edge connectivity revealed a characteristic pattern of interhemispheric disconnection, involving homologous parietal regions, in PSC. Our results suggest that GRN-related frontotemporal dementia resembles a disconnection syndrome, with interhemispheric disconnection between parietal regions in presymptomatic phases that progresses to frontotemporal areas as symptoms emerge.

Published
2022
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18. Comparing two artificial intelligence software packages for normative brain volumetry in memory clinic imaging

Author

Vernooij, Meike W., Zaki, Lara A.M., Smits, Marion, Tolman, Christine, Papma, Janne M., Visser, Jacob J., Steketee, Rebecca M.E., Radiology & Nuclear Medicine, Epidemiology, and Neurology

Subjects
Alzheimer Disease, Artificial Intelligence, Brain, Humans, Radiology, Nuclear Medicine and imaging, Neurology (clinical), Cardiology and Cardiovascular Medicine, Magnetic Resonance Imaging, Software, Retrospective Studies
Abstract

Purpose To compare two artificial intelligence software packages performing normative brain volumetry and explore whether they could differently impact dementia diagnostics in a clinical context. Methods Sixty patients (20 Alzheimer’s disease, 20 frontotemporal dementia, 20 mild cognitive impairment) and 20 controls were included retrospectively. One MRI per subject was processed by software packages from two proprietary manufacturers, producing two quantitative reports per subject. Two neuroradiologists assigned forced-choice diagnoses using only the normative volumetry data in these reports. They classified the volumetric profile as “normal,” or “abnormal”, and if “abnormal,” they specified the most likely dementia subtype. Differences between the packages’ clinical impact were assessed by comparing (1) agreement between diagnoses based on software output; (2) diagnostic accuracy, sensitivity, and specificity; and (3) diagnostic confidence. Quantitative outputs were also compared to provide context to any diagnostic differences. Results Diagnostic agreement between packages was moderate, for distinguishing normal and abnormal volumetry (K = .41–.43) and for specific diagnoses (K = .36–.38). However, each package yielded high inter-observer agreement when distinguishing normal and abnormal profiles (K = .73–.82). Accuracy, sensitivity, and specificity were not different between packages. Diagnostic confidence was different between packages for one rater. Whole brain intracranial volume output differed between software packages (10.73%, p rs = .12–.80). Conclusion Different artificial intelligence software packages for quantitative normative assessment of brain MRI can produce distinct effects at the level of clinical interpretation. Clinics should not assume that different packages are interchangeable, thus recommending internal evaluation of packages before adoption.

Published
2021

19. Faster Cortical Thinning and Surface Area Loss in Presymptomatic and Symptomatic C9orf72 Repeat Expansion Adult Carriers

Author

Le Blanc, Gabriella, Jetté Pomerleau, Vincent, Graff, Caroline, Rittman, Tim, Rogaeva, Ekaterina, Rosa‐Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Scarpini, Elio, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Masellis, Mario, Tábuas‐Pereira, Miguel, Tainta, Mikel, Tang‐Wai, David, Thomas, David L, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Vandamme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Tartaglia, Maria C., Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Zetterberg, Henrik, Zulaica, Miren, Rowe, James B., Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, Mendonça, Alexandre, Santana, Isabel, Butler, Chris, McCarthy, Jillian, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Frisoni, Giovanni, Sorbi, Sandro, Rohrer, Jonathan D., Ducharme, Simon, Almeida, Maria Rosario, Anderl‐Straub, Sarah, Borroni, Barbara, Andersson, Christin, Antonell, Anna, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Luisa, Binetti, Giuliano, Swieten, John, Black, Sandra, Bocchetta, Martina, Borrego, Sergi, Bras, Jose, Bruffaerts, Rose, Caroppo, Paola, Cash, David, Castelo‐Branco, Miguel, Convery, Rhian, Cope, Thomas, Galimberti, Daniela, Arriba, María, Di Fede, Giuseppe, Díaz, Zigor, Dick, Katrina M, Duro, Diana, Fenoglio, Chiara, Ferreira, Carlos, Ferreira, Catarina B., Flanagan, Toby, Fox, Nick, Sanchez‐Valle, Raquel, Freedman, Morris, Fumagalli, Giorgio, Gabilondo, Alazne, Gauthier, Serge, Ghidoni, Roberta, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, LaForce, Robert, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Jiskoot, Lize, Karnath, Hans‐Otto, Keren, Ron, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Moreno, Fermin, Maruta, Carolina, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, Minkelen, Rick, Mitchell, Sara, Nacmias, Benedetta, Neason, Mollie, Nicholas, Jennifer, Öijerstedt, Linn, Synofzik, Matthis, Olives, Jaume, Panman, Jessica, Papma, Janne, Patzig, Maximilian, Pievani, Michela, Pijnenburg, Yolande, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Neurology, Ducharme, Simon [0000-0002-7309-1113], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Adult, Male, medicine.medical_specialty, Adolescent, diagnostic imaging [Frontotemporal Dementia], 03 medical and health sciences, Young Adult, 0302 clinical medicine, Atrophy, C9orf72, Internal medicine, diagnostic imaging [Cerebral Cortex], medicine, Humans, ddc:610, Young adult, genetics [C9orf72 Protein], genetics [Frontotemporal Dementia], Aged, Aged, 80 and over, Cerebral Cortex, DNA Repeat Expansion, medicine.diagnostic_test, C9orf72 Protein, business.industry, Magnetic resonance imaging, diagnostic imaging [Atrophy], Middle Aged, medicine.disease, Magnetic Resonance Imaging, 030104 developmental biology, medicine.anatomical_structure, Neurology, Cerebral cortex, Frontotemporal Dementia, Cardiology, Female, Neurology (clinical), Trinucleotide repeat expansion, business, Asymptomatic carrier, 030217 neurology & neurosurgery, Frontotemporal dementia, genetics [Atrophy]
Abstract

Objective C9orf72 expansion is the most common genetic cause of frontotemporal dementia (FTD). We examined aging trajectories of cortical thickness (CTh) and surface area in C9orf72 expansion adult carriers compared to healthy controls to characterize preclinical cerebral changes leading to symptoms. Methods Data were obtained from the Genetic Frontotemporal Dementia Initiative. T1-weighted magnetic resonance imaging scans were processed with CIVET 2.1 to extract vertex-wide CTh and cortical surface area (CSA). Symptomatic and presymptomatic subjects were compared to age-matched controls using mixed-effects models, controlling for demographic variables. Aging trajectories were compared between carriers and noncarriers by testing the "age by genetic status" interaction. False discovery rate corrections were applied to all vertex-wide analyses. Results The sample included 640 scans from 386 subjects, including 54 symptomatic C9orf72 carriers (72.2% behavioral variant FTD), 83 asymptomatic carriers, and 249 controls (age range = 18-86 years). Symptomatic carriers showed fairly symmetric reduction in CTh/CSA in most of the frontal lobes, in addition to large temporoparietal areas. Presymptomatic subjects had reduced CTh/CSA in more restricted areas of the medial frontoparietal lobes, in addition to scattered lateral frontal, parietal, and temporal areas. These differences were explained by faster cortical thinning linearly throughout adulthood in a similar anatomical distribution, with differences emerging in the early 30s. CSA reduction was also faster in mutation carriers predominantly in the ventrofrontal regions. Interpretation C9orf72 mutation carriers have faster cortical thinning and surface loss throughout adulthood in regions that show atrophy in symptomatic subjects. This suggests that the pathogenic effects of the mutation lead to structural cerebral changes decades prior to symptoms. ANN NEUROL 2020 ANN NEUROL 2020;88:113-122.

Published
2020
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20. The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint

Author

Premi, Enrico, Calhoun, Vince D, Galimberti, Daniela, Panman, Jessica, Papma, Janne, Patzig, Maximilian, Pievani, Michela, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rittman, Tim, Rogaeva, Ekaterina, Sanchez-Valle, Raquel, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Scarpini, Elio, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Tábuas-Pereira, Miguel, Tainta, Mikel, Laforce, Robert, Tang-Wai, David, Thomas, David L, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Vandamme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Moreno, Fermin, Warren, Jason, Wilke, Carlo, Zetterberg, Henrik, Zulaica, Miren, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James, Vandenberghe, Rik, Diano, Matteo, Finger, Elizabeth, Tagliavini, Fabrizio, de Mendonça, Alexandre, Santana, Isabel, Butler, Chris, Ducharme, Simon, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Gazzina, Stefano, Frisoni, Giovanni, Cappa, Stefano, Sorbi, Sandro, Padovani, Alessandro, Rohrer, Jonathan D, Borroni, Barbara, Genetic FTD Initiative, GENFI, Almeida, Maria Rosario, Anderl-Straub, Sarah, Andersson, Christin, Cosseddu, Maura, Antonell, Anna, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Luisa, Binetti, Giuliano, Black, Sandra, Alberici, Antonella, Bocchetta, Martina, Borrego-Ecija, Sergi, Bras, Jose, Bruffaerts, Rose, Caroppo, Paola, Cash, David, Castelo-Branco, Miguel, Convery, Rhian, Cope, Thomas, de Arriba, María, Archetti, Silvana, Di Fede, Giuseppe, Díaz, Zigor, Dick, Katrina M, Duro, Diana, Fenoglio, Chiara, Ferreira, Carlos, Ferreira, Catarina B, Flanagan, Toby, Fox, Nick, Freedman, Morris, Paternicò, Donata, Fumagalli, Giorgio, Gabilondo, Alazne, Gauthier, Serge, Ghidoni, Roberta, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Gasparotti, Roberto, Indakoetxea, Begoña, Jelic, Vesna, Jiskoot, Lize, Karnath, Hans-Otto, Keren, Ron, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, van Swieten, John, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Nacmias, Benedetta, Neason, Mollie, Nicholas, Jennifer, Öijerstedt, Linn, Olives, Jaume, Rowe, James [0000-0001-7216-8679], Apollo - University of Cambridge Repository, Neurology, National Institutes of Health (US), National Science Foundation (US), Wellcome Trust, and Repositório da Universidade de Lisboa

Subjects
Male, Time Factors, MOTION, Gene mutation, physiopathology [Frontotemporal Dementia], methods [Connectome], 0302 clinical medicine, C9orf72, physiopathology [Nerve Net], BEHAVIORAL VARIANT, Medicine, genetics [Frontotemporal Dementia], 11 Medical and Health Sciences, dult Connectome/*methods Female Frontotemporal Dementia/diagnostic imaging/genetics/*physiopathology Heterozygote Humans Magnetic Resonance Imaging Male Middle Aged Nerve Net/diagnostic imaging/*physiopathology *Prodromal Symptoms Time Factors C9orf72 Chronnectome Dynamic brain functional connectivity Frontotemporal dementia Granulin Microtuble associate protein tau Mutation resting-state fMRI, medicine.diagnostic_test, Radiology, Nuclear Medicine & Medical Imaging, 05 social sciences, Genetic FTD Initiative, GENFI, Middle Aged, Magnetic Resonance Imaging, Demência Frontotemporal, 17 Psychology and Cognitive Sciences, DYNAMIC FUNCTIONAL CONNECTIVITY, Chronnectome, Dynamic brain functional connectivity, Frontotemporal dementia, Granulin, Microtuble associate protein tau, Mutation, resting-state fMRI, Adult, Connectome, Female, Frontotemporal Dementia, Heterozygote, Humans, Nerve Net, Prodromal Symptoms, Neurology, SENSITIVITY, Life Sciences & Biomedicine, Cognitive Neuroscience, Neuroimaging, FREQUENCY, diagnostic imaging [Frontotemporal Dementia], Article, 050105 experimental psychology, 03 medical and health sciences, mental disorders, 0501 psychology and cognitive sciences, LOBAR DEGENERATION, ddc:610, Dynamic functional connectivity, RESTING-STATE NETWORKS, Neurology & Neurosurgery, Science & Technology, Resting state fMRI, SUBJECT, diagnostic imaging [Nerve Net], business.industry, Neurosciences, medicine.disease, FMRI DATA, PATTERNS, Neurosciences & Neurology, business, Functional magnetic resonance imaging, Neuroscience, 030217 neurology & neurosurgery
Abstract

© 2019 Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/), Frontotemporal Dementia (FTD) is preceded by a long period of subtle brain changes, occurring in the absence of overt cognitive symptoms, that need to be still fully characterized. Dynamic network analysis based on resting-state magnetic resonance imaging (rs-fMRI) is a potentially powerful tool for the study of preclinical FTD. In the present study, we employed a "chronnectome" approach (recurring, time-varying patterns of connectivity) to evaluate measures of dynamic connectivity in 472 at-risk FTD subjects from the Genetic Frontotemporal dementia research Initiative (GENFI) cohort. We considered 249 subjects with FTD-related pathogenetic mutations and 223 mutation non-carriers (HC). Dynamic connectivity was evaluated using independent component analysis and sliding-time window correlation to rs-fMRI data, and meta-state measures of global brain flexibility were extracted. Results show that presymptomatic FTD exhibits diminished dynamic fluidity, visiting less meta-states, shifting less often across them, and travelling through a narrowed meta-state distance, as compared to HC. Dynamic connectivity changes characterize preclinical FTD, arguing for the desynchronization of the inner fluctuations of the brain. These changes antedate clinical symptoms, and might represent an early signature of FTD to be used as a biomarker in clinical trials., This work was supported in part by grants from the NIH (R01REB020407, P20GM103472), NSF grant 1539067 and the Well- come Trust grant (JBR 103838).

Published
2019
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21. The Revised Self-Monitoring Scale detects early impairment of social cognition in genetic frontotemporal dementia within the GENFI cohort

Author

Franklin, Hannah D, Russell, Lucy L, Jiskoot, Lize, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Moore, Katrina, Nacmias, Benedetta, Nelson, Annabel, Öijerstedt, Linn, Olives, Jaume, Ourselin, Sebastien, Moreno, Fermin, Padovani, Alessandro, Panman, Jessica, Papma, Janne M, Pijnenburg, Yolande, Polito, Cristina, Premi, Enrico, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Sanchez-Valle, Raquel, Rinaldi, Daisy, Rittman, Tim, Rogaeva, Ekaterina, Rollin, Adeline, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Saracino, Dario, Sayah, Sabrina, Borroni, Barbara, Scarpini, Elio, Schönecker, Sonja, Seelaar, Harro, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Swift, Imogen, Tábuas-Pereira, Miguel, Tainta, Mikel, Taipa, Ricardo, Laforce, Robert, Tang-Wai, David, Thomas, David L, Thompson, Paul, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Todd, Emily, Van Damme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Masellis, Mario, Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Woollacott, Ione, Wlasich, Elisabeth, Zetterberg, Henrik, Zulaica, Miren, Tartaglia, Maria Carmela, Graff, Caroline, Galimberti, Daniela, Rowe, James B, Peakman, Georgia, Finger, Elizabeth, Synofzik, Matthis, Vandenberghe, Rik, de Mendonça, Alexandre, Tagliavini, Fabrizio, Santana, Isabel, Ducharme, Simon, Butler, Chris, Gerhard, Alex, Levin, Johannes, Greaves, Caroline V, Danek, Adrian, Otto, Markus, Sorbi, Sandro, Le Ber, Isabelle, Pasquier, Florence, Rohrer, Jonathan D, Genetic FTD Initiative, GENFI, Afonso, Sónia, Almeida, Maria Rosario, Anderl-Straub, Sarah, Bocchetta, Martina, Andersson, Christin, Antonell, Anna, Archetti, Silvana, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Alberto, Nicholas, Jennifer, Bertoux, Maxime, Bertrand, Anne, Bessi, Valentina, Black, Sandra, Borrego-Ecija, Sergi, Bras, Jose, Brice, Alexis, Bruffaerts, Rose, Camuzat, Agnès, Cañada, Marta, Poos, Jackie, Cantoni, Valentina, Caroppo, Paola, Castelo-Branco, Miguel, Colliot, Olivier, Cope, Thomas, Deramecourt, Vincent, de Arriba, María, Di Fede, Giuseppe, Díez, Alina, Duro, Diana, Convery, Rhian S, Fenoglio, Chiara, Ferrari, Camilla, Ferreira, Catarina B, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Funkiewiez, Aurélie, Gabilondo, Alazne, Gasparotti, Roberto, Gauthier, Serge, Cash, David M, Gazzina, Stefano, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Karnath, Hans Otto, van Swieten, John, Keren, Ron, Kuchcinski, Gregory, Langheinrich, Tobias, Lebouvier, Thibaud, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, Mead, Simon, Rohrer, Jonathan D. [0000-0002-6155-8417], Apollo - University of Cambridge Repository, Bocchetta, Martina [0000-0003-1814-5024], Rowe, James B [0000-0001-7216-8679], Rohrer, Jonathan D [0000-0002-6155-8417], Neurology, Clinical Psychology, Clinical Genetics, and Repositório da Universidade de Lisboa

Subjects
Social Cognition, Neurology, Medizin, RSMS, PROGRESSION, Audiology, genetics [Progranulins], 0302 clinical medicine, Progranulins, Familial, C9orf72, MAPT, Medicine, CDR® plus NACC FTLD, VBM, genetics [Frontotemporal Dementia], 11 Medical and Health Sciences, Socioemotional selectivity theory, 05 social sciences, Prodromal Stage, Genetic FTD Initiative, GENFI, Frontotemporal dementia, GRN, C9orf72 Protein, Humans, Magnetic Resonance Imaging, Mutation, tau Proteins, Frontotemporal Dementia, ORBITOFRONTAL CORTEX, Life Sciences & Biomedicine, RC321-571, medicine.medical_specialty, Cognitive Neuroscience, Clinical Neurology, Neurosciences. Biological psychiatry. Neuropsychiatry, genetics [Mutation], diagnostic imaging [Frontotemporal Dementia], 050105 experimental psychology, Temporal lobe, 03 medical and health sciences, mental disorders, 0501 psychology and cognitive sciences, ddc:610, RC346-429, genetics [C9orf72 Protein], Science & Technology, CDR (R) plus NACC FTLD, business.industry, Research, Neurosciences, medicine.disease, DYSFUNCTION, genetics [tau Proteins], Orbitofrontal cortex, Neurology. Diseases of the nervous system, Neurosciences & Neurology, Neurology (clinical), business, Insula, 030217 neurology & neurosurgery
Abstract

© The Author(s). 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data., Background: Although social cognitive dysfunction is a major feature of frontotemporal dementia (FTD), it has been poorly studied in familial forms. A key goal of studies is to detect early cognitive impairment using validated measures in large patient cohorts. Methods: We used the Revised Self-Monitoring Scale (RSMS) as a measure of socioemotional sensitivity in 730 participants from the genetic FTD initiative (GENFI) observational study: 269 mutation-negative healthy controls, 193 C9orf72 expansion carriers, 193 GRN mutation carriers and 75 MAPT mutation carriers. All participants underwent the standardised GENFI clinical assessment including the 'CDR® plus NACC FTLD' scale and RSMS. The RSMS total score and its two subscores, socioemotional expressiveness (EX score) and modification of self-presentation (SP score) were measured. Volumetric T1-weighted magnetic resonance imaging was available from 377 mutation carriers for voxel-based morphometry (VBM) analysis. Results: The RSMS was decreased in symptomatic mutation carriers in all genetic groups but at a prodromal stage only in the C9orf72 (for the total score and both subscores) and GRN (for the modification of self-presentation subscore) groups. RSMS score correlated with disease severity in all groups. The VBM analysis implicated an overlapping network of regions including the orbitofrontal cortex, insula, temporal pole, medial temporal lobe and striatum. Conclusions: The RSMS indexes socioemotional impairment at an early stage of genetic FTD and may be a suitable outcome measure in forthcoming trials., The Dementia Research Centre is supported by Alzheimer’s Research UK, Brain Research Trust and The Wolfson Foundation. This work was supported by the NIHR Queen Square Dementia Biomedical Research Unit, the NIHR UCL/H Biomedical Research Centre and the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility as well as an Alzheimer’s Society grant [AS-PG-16-007]. This work was also supported by the MRC UK GENFI grant [MR/M023664/1], the Italian Ministry of Health (CoEN015 and Ricerca Corrente) and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant, The Bluefield Project and the JPND GENFI-PROX grant [2019-02248]. JDR is supported by an MRC Clinician Scientist Fellowship [MR/M008525/1] and has received funding from the NIHR Rare Disease Translational Research Collaboration [BRC149/NS/MH], the Bluefield Project and the Association for Frontotemporal Degeneration. MB is supported by a Fellowship award from the Alzheimer’s Society, UK [AS-JF-19a-004-517]. JBR is supported by the Wellcome Trust [103838], the Medical Research Council and NIHR Cambridge Biomedical Research Centre. This work was also funded 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]. Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases - Project ID No 739510.

Published
2021
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22. Differential early subcortical involvement in genetic FTD within the GENFI cohort

Author

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

Subjects
Pathology, SEGMENTATION, Medizin, Hippocampus, Presymptomatic stage, genetics [Progranulins], Progranulins, 0302 clinical medicine, Limbic system, Basal ganglia, BRAIN ATROPHY, skin and connective tissue diseases, genetics [Frontotemporal Dementia], 05 social sciences, Subiculum, Regular Article, DEGENERATION, Magnetic Resonance Imaging, 3. Good health, Brain volumetry, medicine.anatomical_structure, Neurology, Frontotemporal Dementia, MRI imaging, Life Sciences & Biomedicine, Frontotemporal dementia, medicine.medical_specialty, Cognitive Neuroscience, Computer applications to medicine. Medical informatics, Thalamus, R858-859.7, Prodromal Symptoms, Neuroimaging, tau Proteins, genetics [Mutation], Grey matter, Biology, diagnostic imaging [Frontotemporal Dementia], Genetic frontotemporal dementia, 050105 experimental psychology, Temporal lobe, 03 medical and health sciences, mental disorders, medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, ddc:610, PROGRANULIN, RC346-429, genetics [C9orf72 Protein], Science & Technology, C9orf72 Protein, PATHWAYS, FRONTOTEMPORAL DEMENTIA, C9ORF72 MUTATION, medicine.disease, Atrophy, Mutation, PATHOLOGY, genetics [tau Proteins], nervous system, Neurosciences & Neurology, sense organs, Neurology. Diseases of the nervous system, Neurology (clinical), TAU, NEUROPATHOLOGY, 030217 neurology & neurosurgery
Abstract

© 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), Background: Studies have previously shown evidence for presymptomatic cortical atrophy in genetic FTD. Whilst initial investigations have also identified early deep grey matter volume loss, little is known about the extent of subcortical involvement, particularly within subregions, and how this differs between genetic groups. Methods: 480 mutation carriers from the Genetic FTD Initiative (GENFI) were included (198 GRN, 202 C9orf72, 80 MAPT), together with 298 non-carrier cognitively normal controls. Cortical and subcortical volumes of interest were generated using automated parcellation methods on volumetric 3 T T1-weighted MRI scans. Mutation carriers were divided into three disease stages based on their global CDR® plus NACC FTLD score: asymptomatic (0), possibly or mildly symptomatic (0.5) and fully symptomatic (1 or more). Results: In all three groups, subcortical involvement was seen at the CDR 0.5 stage prior to phenoconversion, whereas in the C9orf72 and MAPT mutation carriers there was also involvement at the CDR 0 stage. In the C9orf72 expansion carriers the earliest volume changes were in thalamic subnuclei (particularly pulvinar and lateral geniculate, 9-10%) cerebellum (lobules VIIa-Crus II and VIIIb, 2-3%), hippocampus (particularly presubiculum and CA1, 2-3%), amygdala (all subregions, 2-6%) and hypothalamus (superior tuberal region, 1%). In MAPT mutation carriers changes were seen at CDR 0 in the hippocampus (subiculum, presubiculum and tail, 3-4%) and amygdala (accessory basal and superficial nuclei, 2-4%). GRN mutation carriers showed subcortical differences at CDR 0.5 in the presubiculum of the hippocampus (8%). Conclusions: C9orf72 expansion carriers show the earliest and most widespread changes including the thalamus, basal ganglia and medial temporal lobe. By investigating individual subregions, changes can also be seen at CDR 0 in MAPT mutation carriers within the limbic system. Our results suggest that subcortical brain volumes may be used as markers of neurodegeneration even prior to the onset of prodromal symptoms., This work was also supported by the MRC UK GENFI grant (MR/M023664/1), the Italian Ministry of Health (CoEN015 and Ricerca Corrente), the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant, the Alzheimer's Society grant (AS-PG-16-007), the Bluefield Project and the JPND GENFI-PROX grant (2019-02248). MB is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517). MB’s work was also supported 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. MB acknowledges the support of NVIDIA Corporation with the donation of the Titan V GPU used for part of the analyses in this research. JDR is an MRC Clinician Scientist (MR/M008525/1) and has received funding from the NIHR Rare Diseases Translational Research Collaboration (BRC149/NS/MH), the Bluefield Project and the Association for Frontotemporal Degeneration. JEI is supported by the European Research Council (Starting Grant 677697, project BUNGEE-TOOLS), Alzheimer’s Research UK (ARUK-IRG2019A003) and NIH 1RF1MH123195-01. JBR is funded by the Wellcome Trust (103838) and the National Institute for Health Research Cambridge Biomedical Research Centre. This work was funded 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). Several authors of this publication (JCvS, MS, RSV, AD, MO, JDR) are members of the European Reference Network for Rare Neurological Diseases (ERN-RND) - Project ID No 739510.

Published
2021
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23. Characterizing the Clinical Features and Atrophy Patterns of MAPT-Related Frontotemporal Dementia With Disease Progression Modeling

Author

Young, Alexandra L, Bocchetta, Martina, Seelaar, Harro, Bruffaerts, Rose, Van Damme, Philip, Vandenbulcke, Mathieu, Ferreira, Catarina B, Miltenberger, Gabriel, Maruta, Carolina, Verdelho, Ana, Afonso, Sónia, Taipa, Ricardo, Caroppo, Paola, Moreno, Fermin, Di Fede, Giuseppe, Giaccone, Giorgio, Prioni, Sara, Redaelli, Veronica, Rossi, Giacomina, Tiraboschi, Pietro, Duro, Diana, Almeida, Maria Rosario, Branco, Miguel Castelo, Leitão, Maria João, Sanchez-Valle, Raquel, Pereira, Miguel Tábuas, Santiago, Beatriz, Gauthier, Serge, Neto, Pedro Rosa, Veldsman, Michele, Thompson, Paul, Prix, Catharina, Hoegen, Tobias, Mag Rer Nat, Elisabeth Wlasich, Loosli, Sandra, Borroni, Barbara, Schönecker, Sonja, Dr Hum Bio, Elisa Semler, Psych, Dipl, Anderl-Straub, Sarah, Nacmias, Benedetta, Ferrari, Camilla, Polito, Cristina, Lombardi, Gemma, Bessi, Valentina, Laforce, Robert, Masellis, Mario, Tartaglia, Maria Carmela, Graff, Caroline, Galimberti, Daniela, Rowe, James B, Russell, Lucy L, Finger, Elizabeth, Synofzik, Matthis, Vandenberghe, Rik, de Mendonça, Alexandre, Tagliavini, Fabrizio, Santana, Isabel, Ducharme, Simon, Butler, Chris, Gerhard, Alex, Levin, Johannes, Convery, Rhian S, Danek, Adrian, Otto, Markus, Sorbi, Sandro, Williams, Steven C R, Alexander, Daniel C, Rohrer, Jonathan D, Initiative, Genetic FTD, Rossor, Martin N, Fox, Nick C, Warren, Jason D, Peakman, Georgia, Woollacott, Ione, Shafei, Rachelle, Heller, Carolin, Swift, Imogen J, Moore, Katrina, Guerreiro, Rita, Bras, Jose, Thomas, David L, Nicholas, Jennifer, Mead, Simon, Todd, Emily, Meeter, Lieke, Panman, Jessica, Papma, Janne M, Poos, Jackie, van Minkelen, Rick, Pijnenburg, Yolande, Barandiaran, Myriam, Indakoetxea, Begoña, Gabilondo, Alazne, Tainta, Mikel, Cash, David M, de Arriba, María, Gorostidi, Ana, Zulaica, Miren, Villanua, Jorge, Díaz, Zigor, Borrego-Ecija, Sergi, Olives, Jaume, Lladó, Albert, Balasa, Mircea, Antonell, Anna, Greaves, Caroline V, Bargalló, Nuria, Premi, Enrico, Cosseddu, Maura, Gazzina, Stefano, Padovani, Alessandro, Gasparotti, Roberto, Archetti, Silvana, Black, Sandra, Mitchell, Sara, Rogaeva, Ekaterina, van Swieten, John, Freedman, Morris, Keren, Ron, Tang-Wai, David, Öijerstedt, Linn, Andersson, Christin, Jelic, Vesna, Thonberg, Hakan, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Jiskoot, Lize, Fumagalli, Giorgio, Cope, Thomas, Timberlake, Carolyn, Rittman, Timothy, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Wilke, Carlo, Karnath, Hans Otto, Bender, Benjamin, Young, Alexandra L [0000-0002-7772-781X], Todd, Emily [0000-0003-1551-5691], Cash, David M [0000-0001-7833-616X], Seelaar, Harro [0000-0003-1989-7527], 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], Williams, Steven CR [0000-0003-4299-1941], Apollo - University of Cambridge Repository, Genetic FTD Initiative (GENFI), Repositório da Universidade de Lisboa, and Neurology

Subjects
Male, Medizin, Hippocampus, volumetric MRI, frontotemporal dementia, Machine Learning, 0302 clinical medicine, pathology [Brain], 030212 general & internal medicine, genetics [Frontotemporal Dementia], Temporal cortex, pathology [Atrophy], Brain, Middle Aged, Magnetic Resonance Imaging, neuropsychological assessment, medicine.anatomical_structure, Frontotemporal Dementia, Disease Progression, CHAMELEON, Female, methods [Neuroimaging], Life Sciences & Biomedicine, Research Article, Frontotemporal dementia, genetics [Atrophy], Adult, Ventromedial prefrontal cortex, Clinical Neurology, Neuroimaging, MAPT protein, human, tau Proteins, methods [Image Interpretation, Computer-Assisted], Biology, Temporal lobe, 03 medical and health sciences, Atrophy, Image Interpretation, Computer-Assisted, Aged, Humans, Mutation, medicine, ddc:610, Science & Technology, MUTATIONS, medicine.disease, genetics [tau Proteins], association studies in genetics, pathology [Frontotemporal Dementia], Neurology (clinical), Neurosciences & Neurology, Neuroscience, Insula, 030217 neurology & neurosurgery, Executive dysfunction
Abstract

Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited., Background and objective: Mutations in the MAPT gene cause frontotemporal dementia (FTD). Most previous studies investigating the neuroanatomical signature of MAPT mutations have grouped all different mutations together and shown an association with focal atrophy of the temporal lobe. However, the variability in atrophy patterns between each particular MAPT mutation is less well characterised. We aimed to investigate whether there were distinct groups of MAPT mutation carriers based on their neuroanatomical signature. Methods: We applied Subtype and Stage Inference (SuStaIn), an unsupervised machine learning technique that identifies groups of individuals with distinct progression patterns, to characterise patterns of regional atrophy in MAPT-associated FTD within the Genetic FTD Initiative (GENFI) cohort study. Results: 82 MAPT mutation carriers were analysed, the majority of whom had P301L, IVS10+16 or R406W mutations, along with 48 healthy non-carriers. SuStaIn identified two groups of MAPT mutation carriers with distinct atrophy patterns: a 'temporal' subtype in which atrophy was most prominent in the hippocampus, amygdala, temporal cortex and insula, and a 'frontotemporal' subtype in which atrophy was more localised to the lateral temporal lobe and anterior insula, as well as the orbitofrontal and ventromedial prefrontal cortex and anterior cingulate. There was a one-to-one mapping between IVS10+16 and R406W mutations and the temporal subtype, and a near one-to-one mapping between P301L mutations and the frontotemporal subtype. There were differences in clinical symptoms and neuropsychological test scores between subtypes: the temporal subtype was associated with amnestic symptoms, whereas the frontotemporal subtype was associated with executive dysfunction. Discussion: Our results demonstrate that different MAPT mutations give rise to distinct atrophy patterns and clinical phenotype, providing insights into the underlying disease biology, and potential utility for patient stratification in therapeutic trials., The Dementia Research Centre is supported by Alzheimer's Research UK, Brain Research Trust, and The Wolfson Foundation. This work was supported by the NIHR Queen Square Dementia Biomedical Research Unit, the NIHR UCL/H Biomedical Research Centre and the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility, NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and Kings College London, as well as an Alzheimer's Society grant (AS-PG-16-007). This work was also supported by the MRC UK GENFI grant (MR/M023664/1), the Italian Ministry of Health (CoEN015 and Ricerca Corrente), and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant and The Bluefield Project, and the JPND GENFI-PROX grant (2019-02248). This work was funded 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). Nonfinancial support was also provided through the European Reference Network for Rare Neurologic Diseases (ERN-RND), 1 of 24 ERNs funded by the European Commission (ERNRND: 3HP 767231).

Published
2021
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24. Functional network resilience to pathology in presymptomatic genetic frontotemporal dementia

Author

Rittman, Timothy, Borchert, Robin, Frisoni, Giovanni B, Rosser, Martin, Santiago, Beatriz, Scarpini, Elio, Schönecker, Sonja, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Tábuas-Pereira, Miguel, Tainta, Mikel, Taipa, Ricardo, Laforce, Robert, Tang-Wai, David, Thomas, David L, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Vandamme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Finger, Elizabeth, Warren, Jason, Wilke, Carlo, Woollacott, Ione, Wlasich, Elisabeth, Zetterberg, Henrik, Zulaica, Miren, Mendonça, Alexandre, Sorbi, Sandro, Rohrer, Jonathan D, Rowe, James B, Initiative, Genetic Frontotemporal Dementia, Afonso, Sónia, Almeida, Maria Rosario, Jones, Simon, Anderl-Straub, Sarah, Andersson, Christin, Antonell, Anna, Archetti, Silvana, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, van Swieten, John, Benussi, Luisa, Bessi, Valentina, Binetti, Giuliano, Black, Sandra, Bocchetta, Martina, Borrego-Ecija, Sergi, Bras, Jose, Bruffaerts, Rose, Caroppo, Paola, Cash, David, Borroni, Barbara, Castelo-Branco, Miguel, Convery, Rhian, Cope, Thomas, Cosseddu, Maura, de Arriba, María, Di Fede, Giuseppe, Díaz, Zigor, Dick, Katrina M, Duro, Diana, Fenoglio, Chiara, Galimberti, Daniela, Ferrari, Camilla, Ferreira, Catarina B, Flanagana, Toby, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gabilondo, Alazne, Gasparotti, Roberto, Gauthier, Serge, Gazzina, Stefano, Masellis, Mario, Ghidoni, Roberta, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Jiskoot, Lize, Tartaglia, Maria Carmela, Karnath, Hans-Otto, Keren, Ron, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, Graff, Caroline, van Minkelen, Rick, Mitchell, Sara, Nacmias, Benedetta, Neason, Mollie, Nicholas, Jennifer, Öijerstedt, Linn, Olives, Jaume, Padovani, Alessandro, Panman, Jessica, Papma, Janne, Tagliavini, Fabrizio, Pievani, Michela, Pijnenburg, Yolande, Premi, Enrico, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rogaeva, Ekaterina, Rosa-Neto, Pedro, Rossi, Giacomina, Rittman, Timothy [0000-0003-1063-6937], Jones, Simon [0000-0001-9695-0702], Rowe, James [0000-0001-7216-8679], Apollo - University of Cambridge Repository, and Repositório da Universidade de Lisboa

Subjects
Adult, Male, Heterozygote, Tau Proteins/genetics, pathology [Nerve Net], C9orf72 Protein/genetics, MAPT protein, human, Neuroimaging, tau Proteins, Brain/diagnostic imaging/pathology/physiopathology, physiopathology [Brain], Article, ddc:616.89, Frontotemporal Dementia/genetics/pathology/psychology, Cognition, pathology [Brain], physiopathology [Nerve Net], Genetics, Humans, ddc:610, diagnostic imaging [Brain], genetics [C9orf72 Protein], genetics [Frontotemporal Dementia], Aged, Connectivity, C9orf72 Protein, diagnostic imaging [Nerve Net], Brain, Organ Size, Middle Aged, Magnetic Resonance Imaging, psychology [Frontotemporal Dementia], Frontotemporal dementia, Functional imaging, genetics [tau Proteins], FOS: Biological sciences, Frontotemporal Dementia, pathology [Frontotemporal Dementia], Female, C9orf72 protein, human, Atrophy, Nerve Net, Nerve Net/diagnostic imaging/pathology/physiopathology
Abstract

© 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), The presymptomatic phase of neurodegenerative diseases are characterized by structural brain changes without significant clinical features. We set out to investigate the contribution of functional network resilience to preserved cognition in presymptomatic genetic frontotemporal dementia. We studied 172 people from families carrying genetic abnormalities in C9orf72, MAPT, or PGRN. Networks were extracted from functional MRI data and assessed using graph theoretical analysis. We found that despite loss of both brain volume and functional connections, there is maintenance of an efficient topological organization of the brain's functional network in the years leading up to the estimated age of frontotemporal dementia symptom onset. After this point, functional network efficiency declines markedly. Reduction in connectedness was most marked in highly connected hub regions. Measures of topological efficiency of the brain's functional network and organization predicted cognitive dysfunction in domains related to symptomatic frontotemporal dementia and connectivity correlated with brain volume loss in frontotemporal dementia. We propose that maintaining the efficient organization of the brain's functional network supports cognitive health even as atrophy and connectivity decline presymptomatically., This work was funded by the UK Medical Research Council, the Italian Ministry of Health, and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant [grant number CoEN015]. JBR was supported by the Wellcome Trust [grant number 103838]. JBR, RB, TR, and SJ were supported by the NIHR Cambridge Biomedical Research Centre and Medical Research Council [grant number G1100464]. The Dementia Research Centre at UCL is supported by Alzheimer's Research UK, Brain Research Trust, and The Wolfson Foundation, NIHR Queen Square Dementia Biomedical Research Unit, NIHR UCL/H Biomedical Research Centre and Dementia Platforms UK. JDR is supported by an MRC Clinician Scientist Fellowship [grant number MR/M008525/1] and has received funding from the NIHR Rare Disease Translational Research Collaboration [grant number BRC149/NS/MH]. MM is supported by the Canadian Institutes of Health Research, Department of Medicine at Sunnybrook Health Sciences Centre and the University of Toronto, and the Sunnybrook Research Institute. RL is supported by Réseau de médecine génétique appliquée, Fonds de recherche du Québec—Santé [grant number FRQS]. FT is supported by the Italian Ministry of Health. DG is supported by the Fondazione Monzino and Italian Ministry of Health, Ricerca Corrente. SS is supported by Cassa di Risparmio di Firenze [grant number CRF 2013/0199] and the Ministry of Health [grant number RF-2010-2319722]. JvS is supported by The Netherlands Organisation for Health Research and Development Memorable grant [grant number 733050103] and Netherlands Alzheimer Foundation Memorable grant [grant number 733050103].

Published
2019
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25. Multiparametric computer-aided differential diagnosis of Alzheimer's disease and frontotemporal dementia using structural and advanced MRI.

Author

Bron, Esther, Smits, Marion, Papma, Janne, Steketee, Rebecca, Meijboom, Rozanna, Groot, Marius, Swieten, John, Niessen, Wiro, Klein, Stefan, Bron, Esther E, Papma, Janne M, Steketee, Rebecca M E, de Groot, Marius, van Swieten, John C, and Niessen, Wiro J

Subjects
DIFFUSION tensor imaging, SPIN labels, ALZHEIMER'S disease, DIAGNOSIS of dementia, FRONTOTEMPORAL dementia, MAGNETIC resonance imaging, BRAIN, DIFFERENTIAL diagnosis, FREE radicals, RETROSPECTIVE studies, RECEIVER operating characteristic curves, EARLY diagnosis, COMPUTER-aided diagnosis
Abstract

Objectives: To investigate the added diagnostic value of arterial spin labelling (ASL) and diffusion tensor imaging (DTI) to structural MRI for computer-aided classification of Alzheimer's disease (AD), frontotemporal dementia (FTD), and controls.Methods: This retrospective study used MRI data from 24 early-onset AD and 33 early-onset FTD patients and 34 controls (CN). Classification was based on voxel-wise feature maps derived from structural MRI, ASL, and DTI. Support vector machines (SVMs) were trained to classify AD versus CN (AD-CN), FTD-CN, AD-FTD, and AD-FTD-CN (multi-class). Classification performance was assessed by the area under the receiver-operating-characteristic curve (AUC) and accuracy. Using SVM significance maps, we analysed contributions of brain regions.Results: Combining ASL and DTI with structural MRI resulted in higher classification performance for differential diagnosis of AD and FTD (AUC = 84%; p = 0.05) than using structural MRI by itself (AUC = 72%). The performance of ASL and DTI themselves did not improve over structural MRI. The classifications were driven by different brain regions for ASL and DTI than for structural MRI, suggesting complementary information.Conclusions: ASL and DTI are promising additions to structural MRI for classification of early-onset AD, early-onset FTD, and controls, and may improve the computer-aided differential diagnosis on a single-subject level.Key Points: • Multiparametric MRI is promising for computer-aided diagnosis of early-onset AD and FTD. • Diagnosis is driven by different brain regions when using different MRI methods. • Combining structural MRI, ASL, and DTI may improve differential diagnosis of dementia. [ABSTRACT FROM AUTHOR]

Published
2017
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26. Cerebral small vessel disease affects white matter microstructure in mild cognitive impairment

Author

Papma, Janne M., de Groot, Marius, de Koning, Inge, Mattace‐Raso, Francesco U., van der Lugt, Aad, Vernooij, Meike W., Niessen, Wiro J., van Swieten, John C., Koudstaal, Peter J., Prins, Niels D., and Smits, Marion

Subjects
Male, Brain, Organ Size, Neuropsychological Tests, behavioral disciplines and activities, Magnetic Resonance Imaging, Nerve Fibers, Myelinated, White Matter, Cohort Studies, Diffusion Tensor Imaging, Cerebral Small Vessel Diseases, mental disorders, Image Processing, Computer-Assisted, Humans, Regression Analysis, Cognitive Dysfunction, Female, human activities, Research Articles, Aged
Abstract

Microstructural white matter deterioration is a frequent finding in mild cognitive impairment (MCI), potentially underlying default mode network (DMN) dysfunctioning. Thus far, microstructural damage in MCI has been attributed to Alzheimer's disease pathophysiology. A cerebrovascular role, in particular the role of cerebral small vessel disease (CSVD), received less interest. Here, we used diffusion tensor imaging (DTI) to examine the role of CSVD in microstructural deterioration within the normal appearing white matter (NAWM) in MCI. MCI patients were subdivided into those with (n = 20) and without (n = 31) macrostructural CSVD evidence on MRI. Using TBSS we performed microstructural integrity comparisons within the whole brain NAWM. Secondly, we segmented white matter tracts interconnecting DMN brain regions by means of automated tractography segmentation. We used NAWM DTI measures from these tracts as dependent variables in a stepwise‐linear regression analysis, with structural and demographical predictors. Our results indicated microstructural deterioration within the anterior corpus callosum, internal and external capsule and periventricular white matter in MCI patients with CSVD, while in MCI patients without CSVD, deterioration was restricted to the right perforant path, a tract along the hippocampus. Within the full cohort of MCI patients, microstructure within the NAWM of the DMN fiber tracts was affected by the presence of CSVD. Within the cingulum along the hippocampal cortex we found a relationship between microstructural integrity and ipsilateral hippocampal volume and the extent of white matter hyperintensity. In conclusion, we found evidence of CSVD‐related microstructural damage in fiber tracts subserving the DMN in MCI. Hum Brain Mapp 35:2836–2851, 2014. © 2013 Wiley Periodicals, Inc.

Published
2013

27. Association of Cerebrospinal Fluid (CSF) Insulin with Cognitive Performance and CSF Biomarkers of Alzheimer's Disease.

Author

Geijselaers, Stefan L. C., Aalten, Pauline, Ramakers, Inez H. G. B., De Deyn, Peter Paul, Heijboer, Annemieke C., Koek, Huiberdina L., OldeRikkert, Marcel G. M., Papma, Janne M., Reesink, Fransje E., Smits, Lieke L., Stehouwer, Coen D. A., Teunissen, Charlotte E., Verhey, Frans R. J., van der Flier, Wiesje M., Biessels, Geert Jan, and Parelsnoer Institute Neurodegenerative Diseases study group

Subjects
CEREBROSPINAL fluid, ALZHEIMER'S disease, MAGNETIC resonance imaging, MILD cognitive impairment, DEMENTIA, COGNITION disorders diagnosis, BRAIN metabolism, APOLIPOPROTEINS, BRAIN, CELLULAR signal transduction, COGNITION disorders, INSULIN, NEUROPSYCHOLOGICAL tests, NERVE tissue proteins, PEPTIDES, PSYCHOLOGICAL tests, DISEASE complications
Abstract

Background: Abnormal insulin signaling in the brain has been linked to Alzheimer's disease (AD).Objective: To evaluate whether cerebrospinal fluid (CSF) insulin levels are associated with cognitive performance and CSF amyloid-β and Tau. Additionally, we explore whether any such association differs by sex or APOE ɛ4 genotype.Methods: From 258 individuals participating in the Parelsnoer Institute Neurodegenerative Diseases, a nationwide multicenter memory clinic population, we selected 138 individuals (mean age 66±9 years, 65.2% male) diagnosed with subjective cognitive impairment (n = 45), amnestic mild cognitive impairment (n = 44), or AD (n = 49), who completed a neuropsychological assessment, including tests of global cognition and memory performance, and who underwent lumbar puncture. We measured CSF levels of insulin, amyloid-β1-42, total (t-)Tau, and phosphorylated (p-)Tau.Results: CSF insulin levels did not differ between the diagnostic groups (p = 0.136). Across the whole study population, CSF insulin was unrelated to cognitive performance and CSF biomarkers of AD, after adjustment for age, sex, body mass index, diabetes status, and clinic site (all p≥0.131). Importantly, however, we observed effect modification by sex and APOE ɛ4 genotype. Specifically, among women, higher insulin levels in the CSF were associated with worse global cognition (standardized regression coefficient -0.483; p = 0.008) and higher p-Tau levels (0.353; p = 0.040). Among non-carriers of the APOE ɛ4 allele, higher CSF insulin was associated with higher t-Tau (0.287; p = 0.008) and p-Tau (0.246; p = 0.029).Conclusion: Our findings provide further evidence for a relationship between brain insulin signaling and AD pathology. It also highlights the need to consider sex and APOE ɛ4 genotype when assessing the role of insulin. [ABSTRACT FROM AUTHOR]

Published
2018
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28. Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia

Author

Bussy, A., Levy, J., Best, T., Patel, R., Cupo, L., Van Langenhove, T., Nielsen, J., Pijnenburg, Y., Waldö, M., Remes, A., Schroeter, M., Santana, I., Pasquier, F., Otto, M., Danek, A., Levin, J., Le Ber, I., Vandenberghe, R., Synofzik, M., Moreno, F., de Mendonça, A., Sanchez‐Valle, R., Laforce, R., Langheinrich, T., Gerhard, A., Graff, C., Butler, C., Sorbi, S., Jiskoot, L., Seelaar, H., van Swieten, J., Finger, E., Tartaglia, M., Masellis, M., Tiraboschi, P., Galimberti, D., Borroni, B., Rowe, J., Bocchetta, M., Rohrer, J., Devenyi, G., Chakravarty, M., Ducharme, S., Esteve, A., Nelson, A., Bouzigues, A., Heller, C., Greaves, C., Cash, D., Thomas, D., Todd, E., Benotmane, H., Zetterberg, H., Swift, I., Nicholas, J., Samra, K., Russell, L., Shafei, R., Convery, R., Timberlake, C., Cope, T., Rittman, T., Benussi, A., Premi, E., Gasparotti, R., Archetti, S., Gazzina, S., Cantoni, V., Arighi, A., Fenoglio, C., Scarpini, E., Fumagalli, G., Borracci, V., Rossi, G., Giaccone, G., Di Fede, G., Caroppo, P., Prioni, S., Redaelli, V., Tang‐Wai, D., Rogaeva, E., Castelo‐Branco, M., Freedman, M., Keren, R., Black, S., Mitchell, S., Shoesmith, C., Bartha, R., Rademakers, R., Poos, J., Papma, J., Giannini, L., van Minkelen, R., Nacmias, B., Ferrari, C., Polito, C., Lombardi, G., Bessi, V., Veldsman, M., Andersson, C., Thonberg, H., Öijerstedt, L., Jelic, V., Thompson, P., Lladó, A., Antonell, A., Olives, J., Balasa, M., Bargalló, N., Borrego‐Ecija, S., Verdelho, A., Maruta, C., Ferreira, C., Miltenberger, G., do Couto, F., Gabilondo, A., Gorostidi, A., Villanua, J., Cañada, M., Tainta, M., Zulaica, M., Barandiaran, M., Alves, P., Bender, B., Wilke, C., Graf, L., Vogels, A., Vandenbulcke, M., Van Damme, P., Bruffaerts, R., Poesen, K., Rosa‐Neto, P., Gauthier, S., Camuzat, A., Brice, A., Bertrand, A., Funkiewiez, A., Rinaldi, D., Saracino, D., Colliot, O., Sayah, S., Prix, C., Wlasich, E., Wagemann, O., Loosli, S., Schönecker, S., Hoegen, T., Lombardi, J., Anderl‐Straub, S., Rollin, A., Kuchcinski, G., Bertoux, M., Lebouvier, T., Deramecourt, V., Santiago, B., Duro, D., Leitão, M., Almeida, M., Tábuas‐Pereira, M., Afonso, S., Engel, A., Polyakova, M., Erasmus MC other, Neurology, Radiology & Nuclear Medicine, Clinical Genetics, GENetic Frontotemporal dementia Initiative (GENFI), 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, do Couto, Frederico Simões, 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, Saracino, Dario, 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, Nacmias, Benedetta, Ferrari, Camilla, Polito, Cristina, Bussy, Aurélie [0000-0001-6695-9941], Nielsen, Jørgen E [0000-0003-0453-5582], Borroni, Barbara [0000-0001-9340-9814], Bocchetta, Martina [0000-0003-1814-5024], Devenyi, Gabriel A [0000-0002-7766-1187], Apollo - University of Cambridge Repository, and Amsterdam Neuroscience - Neurodegeneration

Subjects
C9orf72 Protein, Radiological and Ultrasound Technology, Medizin, frontotemporal dementia, Neurology, Frontotemporal Dementia, Cerebellum, Humans, magnetic resonance imaging, genetics, neuropsychiatry, Radiology, Nuclear Medicine and imaging, Human medicine, ddc:610, Neurology (clinical), Atrophy, Anatomy, genetics [Frontotemporal Dementia], genetics [C9orf72 Protein]
Abstract

Funder: Alzheimer Society of Canada; Id: http://dx.doi.org/10.13039/501100000143, Funder: Weston Brain Institute; Id: http://dx.doi.org/10.13039/100012479, Funder: Fonds de Recherche du Québec ‐ Santé, Funder: Canadian Institutes of Health Research; Id: http://dx.doi.org/10.13039/501100000024, Funder: NIHR Rare Diseases Translational Research Collaboration, Funder: Deutsche Forschungsgemeinschaft; Id: http://dx.doi.org/10.13039/501100001659, Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers.

Published
2023
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29. Gray and white matter changes in presymptomatic genetic frontotemporal dementia: a longitudinal MRI study.

Author

Panman, Jessica L., Jiskoot, Lize C., Bouts, Mark J.R.J., Meeter, Lieke H.H., van der Ende, Emma L., Poos, Jackie M., Feis, Rogier A., Kievit, Anneke J.A., van Minkelen, Rick, Dopper, Elise G.P., Rombouts, Serge A.R.B., van Swieten, John C., and Papma, Janne M.

Subjects
*FRONTOTEMPORAL dementia, *MAGNETIC resonance imaging, *TEMPORAL lobe, *VOXEL-based morphometry, *LONGITUDINAL method
Abstract

Abstract In genetic frontotemporal dementia, cross-sectional studies have identified profiles of presymptomatic neuroanatomical loss for C9orf72 repeat expansion, MAPT , and GRN mutations. In this study, we characterize longitudinal gray matter (GM) and white matter (WM) brain changes in presymptomatic frontotemporal dementia. We included healthy carriers of C9orf72 repeat expansion (n = 12), MAPT (n = 15), GRN (n = 33) mutations, and related noncarriers (n = 53), that underwent magnetic resonance imaging at baseline and 2-year follow-up. We analyzed cross-sectional baseline, follow-up, and longitudinal GM and WM changes using voxel-based morphometry and cortical thickness analysis in SPM and tract-based spatial statistics in FSL. Compared with noncarriers, C9orf72 repeat expansion carriers showed lower GM volume in the cerebellum and insula, and WM differences in the anterior thalamic radiation, at baseline and follow-up. MAPT mutation carriers showed emerging GM temporal lobe changes and longitudinal WM degeneration of the uncinate fasciculus. GRN mutation carriers did not show presymptomatic neurodegeneration. This study shows distinct presymptomatic cross-sectional and longitudinal patterns of GM and WM changes across C9orf72 repeat expansion, MAPT, and GRN mutation carriers compared with noncarriers. Highlights • Presymptomatic brain changes differ across FTD mutations compared to non-carriers. • In presymptomatic C9orf72 carriers, cross-sectional brain change is stable over time. • In presymptomatic MAPT carriers, longitudinal changes occur in the temporal lobes. • GRN carriers show no cross-sectional or longitudinal gray or white matter changes. [ABSTRACT FROM AUTHOR]

Published
2019
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