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1. The Active Brains Digital Intervention to Reduce Cognitive Decline in Older Adults: Protocol for a Feasibility Randomized Controlled Trial

Author: Smith, Kirsten Ailsa, Bradbury, Katherine, Essery, Rosie, Pollet, Sebastien, Mowbray, Fiona, Slodkowska-Barabasz, Joanna, Denison-Day, James, Hayter, Victoria, Kelly, Jo, Somerville, Jane, Zhang, Jin, Grey, Elisabeth, Western, Max, Ferrey, Anne E, Krusche, Adele, Stuart, Beth, Mutrie, Nanette, Robinson, Sian, Yao, Guiqing Lily, Griffiths, Gareth, Robinson, Louise, Rossor, Martin, Gallacher, John, Griffin, Simon, Kendrick, Tony, Rathod, Shanaya, Gudgin, Bernard, Phillips, Rosemary, Stokes, Tom, Niven, John, Little, Paul, and Yardley, Lucy
Subjects: Medicine, Computer applications to medicine. Medical informatics, R858-859.7
Abstract: BackgroundIncreasing physical activity, improving diet, and performing brain training exercises are associated with reduced cognitive decline in older adults. ObjectiveIn this paper, we describe a feasibility trial of the Active Brains intervention, a web-based digital intervention developed to support older adults to make these 3 healthy behavior changes associated with improved cognitive health. The Active Brains trial is a randomized feasibility trial that will test how accessible, acceptable, and feasible the Active Brains intervention is and the effectiveness of the study procedures that we intend to use in the larger, main trial. MethodsIn the randomized controlled trial (RCT), we use a parallel design. We will be conducting the intervention with 2 populations recruited through GP practices (family practices) in England from 2018 to 2019: older adults with signs of cognitive decline and older adults without any cognitive decline. Trial participants were randomly allocated to 1 of 3 study groups: usual care, the Active Brains intervention, or the Active Brains website plus brief support from a trained coach (over the phone or by email). The main outcomes are performance on cognitive tasks, quality of life (using EuroQol-5D 5 level), Instrumental Activities of Daily Living, and diagnoses of dementia. Secondary outcomes (including depression, enablement, and health care costs) and process measures (including qualitative interviews with participants and supporters) will also be collected. The trial has been approved by the National Health Service Research Ethics Committee (reference 17/SC/0463). ResultsResults will be published in peer-reviewed journals, presented at conferences, and shared at public engagement events. Data collection was completed in May 2020, and the results will be reported in 2021. ConclusionsThe findings of this study will help us to identify and make important changes to the website, the support received, or the study procedures before we progress to our main randomized phase III trial. Trial RegistrationInternational Standard Randomized Controlled Trial Number 23758980; http://www.isrctn.com/ISRCTN23758980 International Registered Report Identifier (IRRID)DERR1-10.2196/18929
Published: 2020
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2. GeoSPM: Geostatistical parametric mapping for medicine

Author: Engleitner, Holger, Jha, Ashwani, Pinilla, Marta Suarez, Nelson, Amy, Herron, Daniel, Rees, Geraint, Friston, Karl, Rossor, Martin, and Nachev, Parashkev
Subjects: Statistics - Methodology
Abstract: The characteristics and determinants of health and disease are often organised in space, reflecting our spatially extended nature. Understanding the influence of such factors requires models capable of capturing spatial relations. Though a mature discipline, spatial analysis is comparatively rare in medicine, arguably a consequence of the complexity of the domain and the inclemency of the data regimes that govern it. Drawing on statistical parametric mapping, a framework for topological inference well-established in the realm of neuroimaging, we propose and validate a novel approach to the spatial analysis of diverse clinical data - GeoSPM - based on differential geometry and random field theory. We evaluate GeoSPM across an extensive array of synthetic simulations encompassing diverse spatial relationships, sampling, and corruption by noise, and demonstrate its application on large-scale data from UK Biobank. GeoSPM is transparently interpretable, can be implemented with ease by non-specialists, enables flexible modelling of complex spatial relations, exhibits robustness to noise and under-sampling, offers well-founded criteria of statistical significance, and is through computational efficiency readily scalable to large datasets. We provide a complete, open-source software implementation of GeoSPM, and suggest that its adoption could catalyse the wider use of spatial analysis across the many aspects of medicine that urgently demand it., Comment: 29 pages, 22 figures
Published: 2022

3. The link between cognitive health and neighbourhood: perceptions of the public, and of policy-makers, about problems and solutions

Author: Stevens, Madeleine, Matosevic, Tihana, Suarez-Pinilla, Marta, Pais, Sarah, Rossor, Martin, and Knapp, Martin
Published: 2023
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4. Dementia

Author: Rossor, Martin, primary
Published: 2023
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5. Prioritization of Drug Targets for Neurodegenerative Diseases by Integrating Genetic and Proteomic Data From Brain and Blood

Author: Ferrari, Raffaele, Hernandez, Dena G., Nalls, Michael A., Rohrer, Jonathan D., Ramasamy, Adaikalavan, Kwok, John B.J., Dobson-Stone, Carol, Brooks, William S., Schofield, Peter R., Halliday, Glenda M., Hodges, John R., Piguet, Olivier, Bartley, Lauren, Thompson, Elizabeth, Haan, Eric, Hernández, Isabel, Ruiz, Agustín, Boada, Mercè, Borroni, Barbara, Padovani, Alessandro, Cruchaga, Carlos, Cairns, Nigel J., Benussi, Luisa, Binetti, Giuliano, Ghidoni, Roberta, Forloni, Gianluigi, Galimberti, Daniela, Fenoglio, Chiara, Serpente, Maria, Scarpini, Elio, Clarimón, Jordi, Lleó, Alberto, Blesa, Rafael, Waldö, Maria Landqvist, Nilsson, Karin, Nilsson, Christer, Mackenzie, Ian R.A., Hsiung, Ging-Yuek R., Mann, David M.A., Grafman, Jordan, Morris, Christopher M., Attems, Johannes, Griffiths, Timothy D., McKeith, Ian G., Thomas, Alan J., Pietrini, P., Huey, Edward D., Wassermann, Eric M., Baborie, Atik, Jaros, Evelyn, Tierney, Michael C., Pastor, Pau, Razquin, Cristina, Ortega-Cubero, Sara, Alonso, Elena, Perneczky, Robert, Diehl-Schmid, Janine, Alexopoulos, Panagiotis, Kurz, Alexander, Rainero, Innocenzo, Rubino, Elisa, Pinessi, Lorenzo, Rogaeva, Ekaterina, St. George-Hyslop, Peter, Rossi, Giacomina, Tagliavini, Fabrizio, Giaccone, Giorgio, Rowe, James B., Schlachetzki, Johannes C.M., Uphill, James, Collinge, John, Mead, Simon, Danek, Adrian, Van Deerlin, Vivianna M., Grossman, Murray, Trojanowski, John Q., van der Zee, Julie, Deschamps, William, Van Langenhove, Tim, Cruts, Marc, Van Broeckhoven, Christine, Cappa, Stefano F., Le Ber, Isabelle, Hannequin, Didier, Golfier, Véronique, Vercelletto, Martine, Brice, Alexis, Nacmias, Benedetta, Sorbi, Sandro, Bagnoli, Silvia, Piaceri, Irene, Nielsen, Jørgen E., Hjermind, Lena E., Riemenschneider, Matthias, Mayhaus, Manuel, Ibach, Bernd, Gasparoni, Gilles, Pichler, Sabrina, Gu, Wei, Rossor, Martin N., Fox, Nick C., Warren, Jason D., Spillantini, Maria Grazia, Morris, Huw R., Rizzu, Patrizia, Heutink, Peter, Snowden, Julie S., Rollinson, Sara, Richardson, Anna, Gerhard, Alexander, Bruni, Amalia C., Maletta, Raffaele, Frangipane, Francesca, Cupidi, Chiara, Bernardi, Livia, Anfossi, Maria, Gallo, Maura, Conidi, Maria Elena, Smirne, Nicoletta, Rademakers, Rosa, Baker, Matt, Dickson, Dennis W., Graff-Radford, Neill R., Petersen, Ronald C., Knopman, David, Josephs, Keith A., Boeve, Bradley F., Parisi, Joseph E., Seeley, William W., Miller, Bruce L., Karydas, Anna M., Rosen, Howard, van Swieten, John C., Dopper, Elise G.P., Seelaar, Harro, Pijnenburg, Yolande A.L., Scheltens, Philip, Logroscino, Giancarlo, Capozzo, Rosa, Novelli, Valeria, Puca, Annibale A., Franceschi, Massimo, Postiglione, Alfredo, Milan, Graziella, Sorrentino, Paolo, Kristiansen, Mark, Chiang, Huei-Hsin, Graff, Caroline, Pasquier, Florence, Rollin, Adeline, Deramecourt, Vincent, Lebert, Florence, Kapogiannis, Dimitrios, Ferrucci, Luigi, Pickering-Brown, Stuart, Singleton, Andrew B., Hardy, John, Momeni, Parastoo, Ge, Yi-Jun, Ou, Ya-Nan, Deng, Yue-Ting, Wu, Bang-Sheng, Yang, Liu, Zhang, Ya-Ru, Chen, Shi-Dong, Huang, Yu-Yuan, Dong, Qiang, Tan, Lan, and Yu, Jin-Tai
Published: 2023
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6. A national initiative in data science for health: an evaluation of the UK Farr Institute

Author: Hemingway, H, Lyons, R, Li, Q, Buchan, I, Ainsworth, J, Pell, J, Morris, A, Barnes, Michael R, Bedford, Helen, Bennie, Marion, Blandford, Ann, Briggs, Andy, Brocklehurst, Peter, Brophy, Sinead, Brown, Gavin, Burton, Paul, Butler, Christopher, Capewell, Simon, Carpenter, James, Carroll, John, Cassell, Jackie A, Castillo, Fortunato, Catchpole, Mike, Caulfield, Mark, Colhoun, Helen, Coveney, Peter, Cunningham-Burley, Sarah, Custovic, Adnan, Deanfield, John, Denaxas, Spiros, Dennis, Michael, Dezateux, Carol, Dibben, Chris, Diggle, Peter, Dixon, Will, Dunn, Graham, Emam, Khaled El, Fone, David, Ford, David, Ford, Ian, Frank, John, Freemantle, Nick, Gabbe, Belinda, Gallacher, John, Gibson, Martin, Gilbert, Ruth, Gissler, Mika, Goble, Carol, Goldberg, Andy, Gravenor, Mike, Gunnell, David, Hannaford, Phil, Hayward, Andrew, Hickman, Matthew, Hingorani, Aroon, Holm, Soren, Holman, Cashel, John, Gareth, John, Ann, Jones, Kerina, Kalra, Dipak, Laurie, Graeme, Lewis, Shon, Lloyd, Keith, Lowe, Sarah, McCowan, Colin, Macleod, John, Martin, Richard M, Moore, Anthony, Moore, Laurence, Nazareth, Irwin, Nenadic, Goran, Paranjothy, Shantini, Parmar, Max, Pebody, Richard, Petersen, Steffen, Petersen, Irene, Pillay, Deenan, Preen, David, Pickett, Kate, Pritchard-Jones, Kathy, Przulj, Natasa, Renehan, Andrew, Roberts, Stephen, Robson, John, Rodgers, Sarah, Rossor, Martin, Russell, Ian, Shawe-Taylor, John, Sheikh, Aziz, Siebert, Stefan, Snooks, Helen, Sperrin, Matthew, Stephenson, Judith, Sullivan, Frank, Taylor, Chris, Taylor, Paul, Timmis, Adam, and Ward, Hester JT
Subjects: Information and Computing Sciences, Library and Information Studies, Health Sciences, Generic health relevance, Health sciences, Human society, Information and computing sciences
Abstract: ObjectiveTo evaluate the extent to which the inter-institutional, inter-disciplinary mobilisation of data and skills in the Farr Institute contributed to establishing the emerging field of data science for health in the UK.Design and outcome measuresWe evaluated evidence of six domains characterising a new field of science:defining central scientific challenges,demonstrating how the central challenges might be solved,creating novel interactions among groups of scientists,training new types of experts,re-organising universities,demonstrating impacts in society.We carried out citation, network and time trend analyses of publications, and a narrative review of infrastructure, methods and tools.SettingFour UK centres in London, North England, Scotland and Wales (23 university partners), 2013-2018.Results1. The Farr Institute helped define a central scientific challenge publishing a research corpus, demonstrating insights from electronic health record (EHR) and administrative data at each stage of the translational cycle in 593 papers with at least one Farr Institute author affiliation on PubMed. 2. The Farr Institute offered some demonstrations of how these scientific challenges might be solved: it established the first four ISO27001 certified trusted research environments in the UK, and approved more than 1000 research users, published on 102 unique EHR and administrative data sources, although there was no clear evidence of an increase in novel, sustained record linkages. The Farr Institute established open platforms for the EHR phenotyping algorithms and validations (>70 diseases, CALIBER). Sample sizes showed some evidence of increase but remained less than 10% of the UK population in primary care-hospital care linked studies. 3.The Farr Institute created novel interactions among researchers: the co-author publication network expanded from 944 unique co-authors (based on 67 publications in the first 30 months) to 3839 unique co-authors (545 papers in the final 30 months). 4. Training expanded substantially with 3 new masters courses, training >400 people at masters, short-course and leadership level and 48 PhD students. 5. Universities reorganised with 4/5 Centres established 27 new faculty (tenured) positions, 3 new university institutes. 6. Emerging evidence of impacts included: > 3200 citations for the 10 most cited papers and Farr research informed eight practice-changing clinical guidelines and policies relevant to the health of millions of UK citizens.ConclusionThe Farr Institute played a major role in establishing and growing the field of data science for health in the UK, with some initial evidence of benefits for health and healthcare. The Farr Institute has now expanded into Health Data Research (HDR) UK but key challenges remain including, how to network such activities internationally.
Published: 2020

7. Age at symptom onset and death and disease duration in genetic frontotemporal dementia: an international retrospective cohort study.

Author: Moore, Katrina M, Nicholas, Jennifer, Grossman, Murray, McMillan, Corey T, Irwin, David J, Massimo, Lauren, Van Deerlin, Vivianna M, Warren, Jason D, Fox, Nick C, Rossor, Martin N, Mead, Simon, Bocchetta, Martina, Boeve, Bradley F, Knopman, David S, Graff-Radford, Neill R, Forsberg, Leah K, Rademakers, Rosa, Wszolek, Zbigniew K, van Swieten, John C, Jiskoot, Lize C, Meeter, Lieke H, Dopper, Elise Gp, Papma, Janne M, Snowden, Julie S, Saxon, Jennifer, Jones, Matthew, Pickering-Brown, Stuart, Le Ber, Isabelle, Camuzat, Agnès, Brice, Alexis, Caroppo, Paola, Ghidoni, Roberta, Pievani, Michela, Benussi, Luisa, Binetti, Giuliano, Dickerson, Bradford C, Lucente, Diane, Krivensky, Samantha, Graff, Caroline, Öijerstedt, Linn, Fallström, Marie, Thonberg, Håkan, Ghoshal, Nupur, Morris, John C, Borroni, Barbara, Benussi, Alberto, Padovani, Alessandro, Galimberti, Daniela, Scarpini, Elio, Fumagalli, Giorgio G, Mackenzie, Ian R, Hsiung, Ging-Yuek R, Sengdy, Pheth, Boxer, Adam L, Rosen, Howie, Taylor, Joanne B, Synofzik, Matthis, Wilke, Carlo, Sulzer, Patricia, Hodges, John R, Halliday, Glenda, Kwok, John, Sanchez-Valle, Raquel, Lladó, Albert, Borrego-Ecija, Sergi, Santana, Isabel, Almeida, Maria Rosário, Tábuas-Pereira, Miguel, Moreno, Fermin, Barandiaran, Myriam, Indakoetxea, Begoña, Levin, Johannes, Danek, Adrian, Rowe, James B, Cope, Thomas E, Otto, Markus, Anderl-Straub, Sarah, de Mendonça, Alexandre, Maruta, Carolina, Masellis, Mario, Black, Sandra E, Couratier, Philippe, Lautrette, Geraldine, Huey, Edward D, Sorbi, Sandro, Nacmias, Benedetta, Laforce, Robert, Tremblay, Marie-Pier L, Vandenberghe, Rik, Damme, Philip Van, Rogalski, Emily J, Weintraub, Sandra, Gerhard, Alexander, Onyike, Chiadi U, Ducharme, Simon, Papageorgiou, Sokratis G, Ng, Adeline Su Lyn, Brodtmann, Amy, Finger, Elizabeth, and Guerreiro, Rita
Subjects: FTD Prevention Initiative, Humans, Disease Progression, tau Proteins, Retrospective Studies, Cohort Studies, Family, Age of Onset, Phenotype, Mutation, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Frontotemporal Dementia, C9orf72 Protein, Progranulins, Clinical Research, Rare Diseases, Dementia, Aging, Brain Disorders, Genetic Testing, Neurodegenerative, Neurosciences, Alzheimer's Disease Related Dementias (ADRD), Prevention, Genetics, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 2.1 Biological and endogenous factors, Neurological, Neurology & Neurosurgery, Clinical Sciences
Abstract: BackgroundFrontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72.MethodsIn this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried.FindingsData were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49·5 years (SD 10·0; onset) and 58·5 years (11·3; death) in the MAPT group, 58·2 years (9·8; onset) and 65·3 years (10·9; death) in the C9orf72 group, and 61·3 years (8·8; onset) and 68·8 years (9·7; death) in the GRN group. Mean disease duration was 6·4 years (SD 4·9) in the C9orf72 group, 7·1 years (3·9) in the GRN group, and 9·3 years (6·4) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0·45 between individual and parental age at onset, r=0·63 between individual and mean family age at onset, r=0·58 between individual and parental age at death, and r=0·69 between individual and mean family age at death) than in either the C9orf72 group (r=0·32 individual and parental age at onset, r=0·36 individual and mean family age at onset, r=0·38 individual and parental age at death, and r=0·40 individual and mean family age at death) or the GRN group (r=0·22 individual and parental age at onset, r=0·18 individual and mean family age at onset, r=0·22 individual and parental age at death, and r=0·32 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35-62, for age at onset; 61%, 47-73, for age at death), and even more by family membership (66%, 56-75, for age at onset; 74%, 65-82, for age at death). In the GRN group, only 2% (0-10) of the variability of age at onset and 9% (3-21) of that of age of death was explained by the specific mutation, whereas 14% (9-22) of the variability of age at onset and 20% (12-30) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11-26) of the variability of age at onset and 19% (12-29) of that of age at death.InterpretationOur study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates.FundingUK Medical Research Council, National Institute for Health Research, and Alzheimer's Society.
Published: 2020

8. Longitudinal neuroanatomical and cognitive progression of posterior cortical atrophy.

Author: Firth, Nicholas C, Primativo, Silvia, Marinescu, Razvan-Valentin, Shakespeare, Timothy J, Suarez-Gonzalez, Aida, Lehmann, Manja, Carton, Amelia, Ocal, Dilek, Pavisic, Ivanna, Paterson, Ross W, Slattery, Catherine F, Foulkes, Alexander JM, Ridha, Basil H, Gil-Néciga, Eulogio, Oxtoby, Neil P, Young, Alexandra L, Modat, Marc, Cardoso, M Jorge, Ourselin, Sebastien, Ryan, Natalie S, Miller, Bruce L, Rabinovici, Gil D, Warrington, Elizabeth K, Rossor, Martin N, Fox, Nick C, Warren, Jason D, Alexander, Daniel C, Schott, Jonathan M, Yong, Keir XX, and Crutch, Sebastian J
Subjects: Cerebral Cortex, Humans, Alzheimer Disease, Disease Progression, Magnetic Resonance Imaging, Case-Control Studies, Longitudinal Studies, Neuropsychological Tests, Models, Neurological, Middle Aged, Female, Male, Cognitive Dysfunction, Alzheimer’s disease, brain atrophy, dementia, memory, structural MRI, Alzheimer's disease, Models, Neurological, Neurology & Neurosurgery, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract: Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer's disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer's disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer's disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer's disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer's disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer's disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer's disease showed early hippocampal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion. Cognitive models showed tests sensitive to visuospatial dysfunction declined earlier in posterior cortical atrophy than typical Alzheimer's disease whilst tests sensitive to working memory impairment declined earlier in typical Alzheimer's disease than posterior cortical atrophy. These findings indicate that posterior cortical atrophy and typical Alzheimer's disease have distinct sites of onset and different profiles of spatial and temporal progression. The ordering of disease events both motivates investigation of biological factors underpinning phenotypic heterogeneity, and informs the selection of measures for clinical trials in posterior cortical atrophy.
Published: 2019

9. Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer’s disease

Author: Preische, Oliver, Schultz, Stephanie A, Apel, Anja, Kuhle, Jens, Kaeser, Stephan A, Barro, Christian, Gräber, Susanne, Kuder-Buletta, Elke, LaFougere, Christian, Laske, Christoph, Vöglein, Jonathan, Levin, Johannes, Masters, Colin L, Martins, Ralph, Schofield, Peter R, Rossor, Martin N, Graff-Radford, Neill R, Salloway, Stephen, Ghetti, Bernardino, Ringman, John M, Noble, James M, Chhatwal, Jasmeer, Goate, Alison M, Benzinger, Tammie LS, Morris, John C, Bateman, Randall J, Wang, Guoqiao, Fagan, Anne M, McDade, Eric M, Gordon, Brian A, and Jucker, Mathias
Subjects: Dementia, Alzheimer's Disease, Aging, Acquired Cognitive Impairment, Neurosciences, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Clinical Research, Detection, screening and diagnosis, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Aetiology, Neurological, Good Health and Well Being, Alzheimer Disease, Disease Progression, Humans, Mutation, Nerve Degeneration, Neurofilament Proteins, Dominantly Inherited Alzheimer Network, Medical and Health Sciences, Immunology
Abstract: Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker.
Published: 2019

10. CSF progranulin increases in the course of Alzheimer's disease and is associated with sTREM2, neurodegeneration and cognitive decline

Author: Suárez‐Calvet, Marc, Capell, Anja, Caballero, Miguel Ángel Araque, Morenas‐Rodríguez, Estrella, Fellerer, Katrin, Franzmeier, Nicolai, Kleinberger, Gernot, Eren, Erden, Deming, Yuetiva, Piccio, Laura, Karch, Celeste M, Cruchaga, Carlos, Paumier, Katrina, Bateman, Randall J, Fagan, Anne M, Morris, John C, Levin, Johannes, Danek, Adrian, Jucker, Mathias, Masters, Colin L, Rossor, Martin N, Ringman, John M, Shaw, Leslie M, Trojanowski, John Q, Weiner, Michael, Ewers, Michael, Haass, Christian, Network, the Dominantly Inherited Alzheimer, and Initiative, the Alzheimer's Disease Neuroimaging
Subjects: Biochemistry and Cell Biology, Biological Sciences, Genetics, Neurodegenerative, Aging, Brain Disorders, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Clinical Research, Alzheimer's Disease, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Alzheimer Disease, Cognitive Dysfunction, Cross-Sectional Studies, Female, Humans, Male, Membrane Glycoproteins, Microglia, Middle Aged, Progranulins, Receptors, Immunologic, Dominantly Inherited Alzheimer Network, Alzheimer's Disease Neuroimaging Initiative, Alzheimer's disease, TREM2, biomarker, microglia, progranulin, Medical and Health Sciences, Biochemistry and cell biology
Abstract: Progranulin (PGRN) is predominantly expressed by microglia in the brain, and genetic and experimental evidence suggests a critical role in Alzheimer's disease (AD). We asked whether PGRN expression is changed in a disease severity-specific manner in AD We measured PGRN in cerebrospinal fluid (CSF) in two of the best-characterized AD patient cohorts, namely the Dominant Inherited Alzheimer's Disease Network (DIAN) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). In carriers of AD causing dominant mutations, cross-sectionally assessed CSF PGRN increased over the course of the disease and significantly differed from non-carriers 10 years before the expected symptom onset. In late-onset AD, higher CSF PGRN was associated with more advanced disease stages and cognitive impairment. Higher CSF PGRN was associated with higher CSF soluble TREM2 (triggering receptor expressed on myeloid cells 2) only when there was underlying pathology, but not in controls. In conclusion, we demonstrate that, although CSF PGRN is not a diagnostic biomarker for AD, it may together with sTREM2 reflect microglial activation during the disease.
Published: 2018

11. Structural brain splitting is a hallmark of Granulin-related frontotemporal dementia

Author: Afonso, Sónia, Almeida, Maria Rosario, Andersson, Christin, Antonell, Anna, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Bertoux, Maxime, Bertrand, Anne, Bessi, Valentina, Black, Sandra, Borrego-Ecija, Sergi, Bouzigues, Arabella, Bras, Jose, Brice, Alexis, Bruffaerts, Rose, Camuzat, Agnès, Cañada, Marta, Cantoni, Valentina, Caroppo, Paola, Castelo-Branco, Miguel, Colliot, Olivier, Cope, Thomas, Deramecourt, Vincent, Fede, Giuseppe Di, Díez, Alina, Duro, Diana, Fenoglio, Chiara, Ferrari, Camilla, Ferreira, Catarina B., Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Funkiewiez, Aurélie, Gabilondo, Alazne, Gauthier, Serge, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Karnath, Hans-Otto, Keren, Ron, Kuchcinski, Gregory, Langheinrich, Tobias, Lebouvier, Thibaud, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Lombardi, Jolina, Loosli, Sandra, Maruta, Carolina, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Moore, Katrina, Nacmias, Benedetta, Nelson, Annabel, Nicholas, Jennifer, Öijerstedt, Linn, Olives, Jaume, Ourselin, Sebastien, Panman, Jessica, Papma, Janne M., Pijnenburg, Yolande, Polito, Cristina, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rinaldi, Daisy, Rittman, Tim, Rogaeva, Ekaterina, Rollin, Adeline, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Saracino, Dario, Sayah, Sabrina, Scarpini, Elio, Schönecker, Sonja, Shafei, Rachelle, Shoesmith, Christen, Swift, Imogen, Tábuas-Pereira, Miguel, Tainta, Mikel, Taipa, Ricardo, Tang-Wai, David, Thomas, David L, Thompson, Paul, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Van Damme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Woollacott, Ione, Wlasich, Elisabeth, Zetterberg, Henrik, Zulaica, Miren, Gazzina, Stefano, Grassi, Mario, Premi, Enrico, Alberici, Antonella, Benussi, Alberto, Archetti, Silvana, Gasparotti, Roberto, Bocchetta, Martina, Cash, David M., Todd, Emily G., Peakman, Georgia, Convery, Rhian S., van Swieten, John C., Jiskoot, Lize C., Seelaar, Harro, Sanchez-Valle, Raquel, Moreno, Fermin, Laforce, Robert, Jr, Graff, Caroline, Synofzik, Matthis, Galimberti, Daniela, Rowe, James B., Masellis, Mario, Tartaglia, Maria Carmela, Finger, Elizabeth, Vandenberghe, Rik, de Mendonça, Alexandre, Tagliavini, Fabrizio, Butler, Chris R., Santana, Isabel, Gerhard, Alexander, Ber, Isabelle Le, Pasquier, Florence, Ducharme, Simon, Levin, Johannes, Danek, Adrian, Sorbi, Sandro, Otto, Markus, Rohrer, Jonathan D., and Borroni, Barbara
Published: 2022
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12. Examining empathy deficits across familial forms of frontotemporal dementia within the GENFI cohort

Author: Afonso, Sónia, Almeida, Maria Rosario, Anderl-Straub, Sarah, Andersson, Christin, Antonell, Anna, Archetti, Silvana, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Alberto, Bertoux, Maxime, Bertrand, Anne, Bessi, Valentina, Black, Sandra, Borrego-Ecija, Sergi, Bras, Jose, Brice, Alexis, Bruffaerts, Rose, Camuzat, Agnès, Cañada, Marta, Cantoni, Valentina, Caroppo, Paola, Cash, David, Castelo-Branco, Miguel, Colliot, Olivier, Cope, Thomas, Deramecourt, Vincent, de Arriba, María, Di Fede, Giuseppe, Díez, Alina, Duro, Diana, Fenoglio, Chiara, Ferrari, Camilla, Ferreira, Catarina B., Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Funkiewiez, Aurélie, Gabilondo, Alazne, Gasparotti, Roberto, Gauthier, Serge, Gazzina, Stefano, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Karnath, Hans-Otto, Keren, Ron, Kuchcinski, Gregory, Langheinrich, Tobias, Lebouvier, Thibaud, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Moore, Katrina, Nacmias, Benedetta, Nelson, Annabel, Öijerstedt, Linn, Olives, Jaume, Ourselin, Sebastien, Padovani, Alessandro, Panman, Jessica, Papma, Janne M., Pijnenburg, Yolande, Polito, Cristina, Premi, Enrico, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rinaldi, Daisy, Rittman, Tim, Rogaeva, Ekaterina, Rollin, Adeline, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Saracino, Dario, Sayah, Sabrina, Scarpini, Elio, Schönecker, Sonja, Seelaar, Harro, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Swift, Imogen, Tábuas-Pereira, Miguel, Tainta, Mikel, Taipa, Ricardo, Tang-Wai, David, Thomas, David L., Thompson, Paul, Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Todd, Emily, Van Damme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Woollacott, Ione, Wlasich, Elisabeth, Zetterberg, Henrik, Zulaica, Miren, Foster, Phoebe H., Russell, Lucy L., Peakman, Georgia, Convery, Rhian S., Bouzigues, Arabella, Greaves, Caroline V., Bocchetta, Martina, Cash, David M., van Swieten, John C., Jiskoot, Lize C., Moreno, Fermin, Sanchez-Valle, Raquel, Laforce, Robert, Graff, Caroline, Masellis, Mario, Tartaglia, Carmela, Rowe, James B., Borroni, Barbara, Finger, Elizabeth, Synofzik, Matthis, Galimberti, Daniela, Vandenberghe, Rik, de Mendonça, Alexandre, Butler, Chris R., Gerhard, Alex, Ducharme, Simon, Le Ber, Isabelle, Tagliavini, Fabrizio, Santana, Isabel, Pasquier, Florence, Levin, Johannes, Danek, Adrian, Otto, Markus, Sorbi, Sandro, and Rohrer, Jonathan D.
Published: 2022
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13. Different Perspectives on Dementia

Author: Assche, Lies Van, primary, Rossor, Martin, additional, Lyketsos, Constantine, additional, Keady, John, additional, and Vandenbulcke, Mathieu, additional
Published: 2022
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14. Inspired by chance : valuing patients’ informal contributions to research

Author: Crutch, Sebastian, Herron, Daniel, Pickett, James, Rosser, Simon, and Rossor, Martin
Published: 2020

15. White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease

Author: Caballero, Miguel Ángel Araque, Suárez-Calvet, Marc, Duering, Marco, Franzmeier, Nicolai, Benzinger, Tammie, Fagan, Anne M, Bateman, Randall J, Jack, Clifford R, Levin, Johannes, Dichgans, Martin, Jucker, Mathias, Karch, Celeste, Masters, Colin L, Morris, John C, Weiner, Michael, Rossor, Martin, Fox, Nick C, Lee, Jae-Hong, Salloway, Stephen, Danek, Adrian, Goate, Alison, Yakushev, Igor, Hassenstab, Jason, Schofield, Peter R, Haass, Christian, and Ewers, Michael
Subjects: Health Services and Systems, Health Sciences, Neurosciences, Dementia, Biomedical Imaging, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Brain Disorders, Alzheimer's Disease, Neurodegenerative, Aging, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Alzheimer Disease, Brain, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, White Matter, Alzheimer's disease, autosomal dominant, white matter, diffusion tensor imaging, TREM2, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences, Psychology
Abstract: White matter alterations are present in the majority of patients with Alzheimer's disease type dementia. However, the spatiotemporal pattern of white matter changes preceding dementia symptoms in Alzheimer's disease remains unclear, largely due to the inherent diagnostic uncertainty in the preclinical phase and increased risk of confounding age-related vascular disease and stroke in late-onset Alzheimer's disease. In early-onset autosomal-dominantly inherited Alzheimer's disease, participants are destined to develop dementia, which provides the opportunity to assess brain changes years before the onset of symptoms, and in the absence of ageing-related vascular disease. Here, we assessed mean diffusivity alterations in the white matter in 64 mutation carriers compared to 45 non-carrier family non-carriers. Using tract-based spatial statistics, we mapped the interaction of mutation status by estimated years from symptom onset on mean diffusivity. For major atlas-derived fibre tracts, we determined the earliest time point at which abnormal mean diffusivity changes in the mutation carriers were detectable. Lastly, we assessed the association between mean diffusivity and cerebrospinal fluid biomarkers of amyloid, tau, phosphorylated-tau, and soluble TREM2, i.e. a marker of microglia activity. Results showed a significant interaction of mutations status by estimated years from symptom onset, i.e. a stronger increase of mean diffusivity, within the posterior parietal and medial frontal white matter in mutation carriers compared with non-carriers. The earliest increase of mean diffusivity was observed in the forceps major, forceps minor and long projecting fibres-many connecting default mode network regions-between 5 to 10 years before estimated symptom onset. Higher mean diffusivity in fibre tracts was associated with lower grey matter volume in the tracts' projection zones. Global mean diffusivity was correlated with lower cerebrospinal fluid levels of amyloid-β1-42 but higher levels of tau, phosphorylated-tau and soluble TREM2. Together, these results suggest that regionally selective white matter degeneration occurs years before the estimated symptom onset. Such white matter alterations are associated with primary Alzheimer's disease pathology and microglia activity in the brain.
Published: 2018

16. Downregulation of exosomal miR-204-5p and miR-632 as a biomarker for FTD: a GENFI study

Author: Schneider, Raphael, McKeever, Paul, Kim, TaeHyung, Graff, Caroline, van Swieten, John Cornelis, Karydas, Anna, Boxer, Adam, Rosen, Howie, Miller, Bruce L, Laforce, Robert, Galimberti, Daniela, Masellis, Mario, Borroni, Barbara, Zhang, Zhaolei, Zinman, Lorne, Rohrer, Jonathan Daniel, Tartaglia, Maria Carmela, Robertson, Janice, Andersson, Christin, Archetti, Silvana, Arighi, Andrea, Benussi, Luisa, Binetti, Giuliano, Black, Sandra, Bocchetta, Martina, Cash, David, Cosseddu, Maura, Dick, Katrina, Fallström, Marie, Ferreira, Carlos, Fenoglio, Chiara, Fox, Nick, Freedman, Morris, Frisoni, Giovanni, Fumagalli, Giorgio, Gazzina, Stefano, Ghidoni, Roberta, Grisoli, Marina, Jelic, Vesna, Jiskoot, Lize, Keren, Ron, Lombardi, Gemma, Maruta, Carolina, Meeter, Lieke, van Minkelen, Mendonça A Rick, Nacmias, Benedetta, Öijerstedt, Linn, Ourselin, Sebastien, Padovani, Alessandro, Panman, Jessica, Pievani, Michela, Polito, Cristina, Premi, Enrico, Prioni, Sara, Rademakers, Rosa, Redaelli, Veronica, Rogaeva, Ekaterina, Rossi, Giacomina, Rossor, Martin, Row, James, Scarpini, Elio, Tagliavini, Fabrizio, Sorbi, Sandro, Tang-Wai, David, Thomas, David, Thonberg, Hakan, Tiraboschi, Pietro, Verdelho, Ana, and Warren, Jason
Subjects: Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Genetics, Neurodegenerative, Alzheimer's Disease, Biotechnology, Prevention, Rare Diseases, Aging, Brain Disorders, Acquired Cognitive Impairment, Alzheimer's Disease Related Dementias (ADRD), 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Neurological, Biomarkers, Down-Regulation, Exosomes, Female, Frontotemporal Dementia, Humans, Male, MicroRNAs, tau Proteins, Genetic FTD Initiative, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract: ObjectiveTo determine whether exosomal microRNAs (miRNAs) in cerebrospinal fluid (CSF) of patients with frontotemporal dementia (FTD) can serve as diagnostic biomarkers, we assessed miRNA expression in the Genetic Frontotemporal Dementia Initiative (GENFI) cohort and in sporadic FTD.MethodsGENFI participants were either carriers of a pathogenic mutation in progranulin, chromosome 9 open reading frame 72 or microtubule-associated protein tau or were at risk of carrying a mutation because a first-degree relative was a known symptomatic mutation carrier. Exosomes were isolated from CSF of 23 presymptomatic and 15 symptomatic mutation carriers and 11 healthy non-mutation carriers. Expression of 752 miRNAs was measured using quantitative PCR (qPCR) arrays and validated by qPCR using individual primers. MiRNAs found differentially expressed in symptomatic compared with presymptomatic mutation carriers were further evaluated in a cohort of 17 patients with sporadic FTD, 13 patients with sporadic Alzheimer's disease (AD) and 10 healthy controls (HCs) of similar age.ResultsIn the GENFI cohort, miR-204-5p and miR-632 were significantly decreased in symptomatic compared with presymptomatic mutation carriers. Decrease of miR-204-5p and miR-632 revealed receiver operator characteristics with an area of 0.89 (90% CI 0.79 to 0.98) and 0.81 (90% CI 0.68 to 0.93), respectively, and when combined an area of 0.93 (90% CI 0.87 to 0.99). In sporadic FTD, only miR-632 was significantly decreased compared with AD and HCs. Decrease of miR-632 revealed an area of 0.90 (90% CI 0.81 to 0.98).ConclusionsExosomal miR-204-5p and miR-632 have potential as diagnostic biomarkers for genetic FTD and miR-632 also for sporadic FTD.
Published: 2018

17. Analysis of shared heritability in common disorders of the brain

Author: Consortium, The Brainstorm, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Schott, Jonathan M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, and Cuenca-Leon, Ester
Subjects: Biological Sciences, Genetics, Biological Psychology, Health Sciences, Psychology, Brain Disorders, Human Genome, Clinical Research, Neurosciences, Mental Illness, Mental Health, 2.1 Biological and endogenous factors, Neurological, Mental health, Brain Diseases, Genetic Variation, Genome-Wide Association Study, Humans, Mental Disorders, Phenotype, Quantitative Trait, Heritable, Risk Factors, Brainstorm Consortium, General Science & Technology
Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
Published: 2018

18. Analysis of shared heritability in common disorders of the brain.

Author: Brainstorm Consortium, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, Cuenca-Leon, Ester, and Furlotte, Nicholas
Subjects: Brainstorm Consortium, Humans, Brain Diseases, Risk Factors, Mental Disorders, Quantitative Trait, Heritable, Phenotype, Genetic Variation, Genome-Wide Association Study, Clinical Research, Neurosciences, Rare Diseases, Human Genome, Brain Disorders, Genetics, Mental Health, 2.1 Biological and endogenous factors, Mental health, Neurological, General Science & Technology
Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
Published: 2018

19. Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer’s disease

Author: Franzmeier, Nicolai, Düzel, Emrah, Jessen, Frank, Buerger, Katharina, Levin, Johannes, Duering, Marco, Dichgans, Martin, Haass, Christian, Suárez-Calvet, Marc, Fagan, Anne M, Paumier, Katrina, Benzinger, Tammie, Masters, Colin L, Morris, John C, Perneczky, Robert, Janowitz, Daniel, Catak, Cihan, Wolfsgruber, Steffen, Wagner, Michael, Teipel, Stefan, Kilimann, Ingo, Ramirez, Alfredo, Rossor, Martin, Jucker, Mathias, Chhatwal, Jasmeer, Spottke, Annika, Boecker, Henning, Brosseron, Frederic, Falkai, Peter, Fliessbach, Klaus, Heneka, Michael T, Laske, Christoph, Nestor, Peter, Peters, Oliver, Fuentes, Manuel, Menne, Felix, Priller, Josef, Spruth, Eike J, Franke, Christiana, Schneider, Anja, Kofler, Barbara, Westerteicher, Christine, Speck, Oliver, Wiltfang, Jens, Bartels, Claudia, Caballero, Miguel Ángel Araque, Metzger, Coraline, Bittner, Daniel, Weiner, Michael, Lee, Jae-Hong, Salloway, Stephen, Danek, Adrian, Goate, Alison, Schofield, Peter R, Bateman, Randall J, and Ewers, Michael
Subjects: Clinical Trials and Supportive Activities, Brain Disorders, Aging, Basic Behavioral and Social Science, Dementia, Neurosciences, Behavioral and Social Science, Acquired Cognitive Impairment, Clinical Research, Alzheimer's Disease, Neurodegenerative, Biomedical Imaging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Alzheimer Disease, Amyloid beta-Protein Precursor, Brain Mapping, Cognitive Dysfunction, Female, Frontal Lobe, Functional Laterality, Humans, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Male, Middle Aged, Mutation, Nerve Net, Presenilin-1, Presenilin-2, Alzheimer's disease, cognitive reserve, resting state connectivity, memory, dementia biomarkers, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract: Patients with Alzheimer's disease vary in their ability to sustain cognitive abilities in the presence of brain pathology. A major open question is which brain mechanisms may support higher reserve capacity, i.e. relatively high cognitive performance at a given level of Alzheimer's pathology. Higher functional MRI-assessed functional connectivity of a hub in the left frontal cortex is a core candidate brain mechanism underlying reserve as it is associated with education (i.e. a protective factor often associated with higher reserve) and attenuated cognitive impairment in prodromal Alzheimer's disease. However, no study has yet assessed whether such hub connectivity of the left frontal cortex supports reserve throughout the evolution of pathological brain changes in Alzheimer's disease, including the presymptomatic stage when cognitive decline is subtle. To address this research gap, we obtained cross-sectional resting state functional MRI in 74 participants with autosomal dominant Alzheimer's disease, 55 controls from the Dominantly Inherited Alzheimer's Network and 75 amyloid-positive elderly participants, as well as 41 amyloid-negative cognitively normal elderly subjects from the German Center of Neurodegenerative Diseases multicentre study on biomarkers in sporadic Alzheimer's disease. For each participant, global left frontal cortex connectivity was computed as the average resting state functional connectivity between the left frontal cortex (seed) and each voxel in the grey matter. As a marker of disease stage, we applied estimated years from symptom onset in autosomal dominantly inherited Alzheimer's disease and cerebrospinal fluid tau levels in sporadic Alzheimer's disease cases. In both autosomal dominant and sporadic Alzheimer's disease patients, higher levels of left frontal cortex connectivity were correlated with greater education. For autosomal dominant Alzheimer's disease, a significant left frontal cortex connectivity × estimated years of onset interaction was found, indicating slower decline of memory and global cognition at higher levels of connectivity. Similarly, in sporadic amyloid-positive elderly subjects, the effect of tau on cognition was attenuated at higher levels of left frontal cortex connectivity. Polynomial regression analysis showed that the trajectory of cognitive decline was shifted towards a later stage of Alzheimer's disease in patients with higher levels of left frontal cortex connectivity. Together, our findings suggest that higher resilience against the development of cognitive impairment throughout the early stages of Alzheimer's disease is at least partially attributable to higher left frontal cortex-hub connectivity.
Published: 2018

20. Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study

Author: Gordon, Brian A, Blazey, Tyler M, Su, Yi, Hari-Raj, Amrita, Dincer, Aylin, Flores, Shaney, Christensen, Jon, McDade, Eric, Wang, Guoqiao, Xiong, Chengjie, Cairns, Nigel J, Hassenstab, Jason, Marcus, Daniel S, Fagan, Anne M, Jack, Clifford R, Hornbeck, Russ C, Paumier, Katrina L, Ances, Beau M, Berman, Sarah B, Brickman, Adam M, Cash, David M, Chhatwal, Jasmeer P, Correia, Stephen, Förster, Stefan, Fox, Nick C, Graff-Radford, Neill R, la Fougère, Christian, Levin, Johannes, Masters, Colin L, Rossor, Martin N, Salloway, Stephen, Saykin, Andrew J, Schofield, Peter R, Thompson, Paul M, Weiner, Michael M, Holtzman, David M, Raichle, Marcus E, Morris, John C, Bateman, Randall J, and Benzinger, Tammie LS
Subjects: Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurosciences, Acquired Cognitive Impairment, Neurodegenerative, Clinical Research, Dementia, Alzheimer's Disease, Brain Disorders, Biomedical Imaging, Aging, Rare Diseases, Aetiology, Detection, screening and diagnosis, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Neurological, Adult, Alzheimer Disease, Amyloid beta-Protein Precursor, Aniline Compounds, Brain, Brain Mapping, Family Health, Female, Fluorodeoxyglucose F18, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Positron-Emission Tomography, Presenilin-1, Presenilin-2, Statistics, Nonparametric, Thiazoles, Clinical Sciences, Neurology & Neurosurgery
Abstract: BackgroundModels of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal.MethodsBetween Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11C-Pittsburgh Compound B (11C-PiB) PET, 18F-Fluorodeoxyglucose (18F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at ClinicalTrials.gov (number NCT00869817) FINDINGS: 11C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the brain, with the precuneus being the first cortical region for each method to show divergence between groups (22·2 years before expected onset for Aβ accumulation, 18·8 years before expected onset for hypometabolism, and 13·0 years before expected onset for cortical thinning).InterpretationMutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning compared with non-carriers which preceded the expected onset of dementia. Accrual of these pathologies varied throughout the brain, suggesting differential regional and temporal vulnerabilities to Aβ, metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting as well as designing and evaluating clinical trials.FundingUS National Institutes of Health, the German Center for Neurodegenerative Diseases, and the Medical Research Council Dementias Platform UK.
Published: 2018

21. Presymptomatic atrophy in autosomal dominant Alzheimer's disease: A serial magnetic resonance imaging study

Author: Kinnunen, Kirsi M, Cash, David M, Poole, Teresa, Frost, Chris, Benzinger, Tammie LS, Ahsan, R Laila, Leung, Kelvin K, Cardoso, M Jorge, Modat, Marc, Malone, Ian B, Morris, John C, Bateman, Randall J, Marcus, Daniel S, Goate, Alison, Salloway, Stephen P, Correia, Stephen, Sperling, Reisa A, Chhatwal, Jasmeer P, Mayeux, Richard P, Brickman, Adam M, Martins, Ralph N, Farlow, Martin R, Ghetti, Bernardino, Saykin, Andrew J, Jack, Clifford R, Schofield, Peter R, McDade, Eric, Weiner, Michael W, Ringman, John M, Thompson, Paul M, Masters, Colin L, Rowe, Christopher C, Rossor, Martin N, Ourselin, Sebastien, Fox, Nick C, and Network, Dominantly Inherited Alzheimer
Subjects: Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Clinical Research, Acquired Cognitive Impairment, Alzheimer's Disease, Bioengineering, Biomedical Imaging, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Neurodegenerative, Brain Disorders, Neurological, Adult, Alzheimer Disease, Apolipoproteins E, Atrophy, Brain, Female, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Psychiatric Status Rating Scales, Statistics, Nonparametric, Time Factors, Longitudinal, Alzheimer's disease, Autosomal dominant, Neuroimaging, MRI, Boundary Shift Integral, Nonlinear modeling, Change-point, Dominantly Inherited Alzheimer Network, Geriatrics, Clinical sciences, Biological psychology
Abstract: IntroductionIdentifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials.MethodsSerial T1-weighted magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed-effects models estimated the change-points when atrophy rates deviate from normal and the rates of change before and after this point.ResultsAtrophy increased after the change-point, which occurred 1-1.5 years (assuming a single step change in atrophy rate) or 3-8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change-point.DiscussionAtrophy rates are pathologically increased up to seven years before "expected onset". During this period, atrophy rates may be useful for inclusion and tracking of disease progression.
Published: 2018

22. Habitual exercise levels are associated with cerebral amyloid load in presymptomatic autosomal dominant Alzheimer's disease

Author: Brown, Belinda M, Sohrabi, Hamid R, Taddei, Kevin, Gardener, Samantha L, Rainey‐Smith, Stephanie R, Peiffer, Jeremiah J, Xiong, Chengjie, Fagan, Anne M, Benzinger, Tammie, Buckles, Virginia, Erickson, Kirk I, Clarnette, Roger, Shah, Tejal, Masters, Colin L, Weiner, Michael, Cairns, Nigel, Rossor, Martin, Graff‐Radford, Neill R, Salloway, Stephen, Vöglein, Jonathan, Laske, Christoph, Noble, James, Schofield, Peter R, Bateman, Randall J, Morris, John C, and Martins, Ralph N
Subjects: Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Alzheimer's Disease, Brain Disorders, Acquired Cognitive Impairment, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Aging, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Alzheimer Disease, Amyloid, Amyloid beta-Peptides, Amyloid beta-Protein Precursor, Aniline Compounds, Apolipoproteins E, Brain, Cohort Studies, Cross-Sectional Studies, Exercise, Female, Genotype, Humans, Linear Models, Magnetic Resonance Imaging, Male, Middle Aged, Mutation, Peptide Fragments, Positron-Emission Tomography, Presenilin-1, Presenilin-2, Surveys and Questionnaires, Thiazoles, tau Proteins, Physical activity, Amyloid beta, Genetics, Tau, Alzheimer's disease, Dominantly Inherited Alzheimer Network, Amyloid β, Geriatrics, Clinical sciences, Biological psychology
Abstract: IntroductionThe objective of this study was to evaluate the relationship between self-reported exercise levels and Alzheimer's disease (AD) biomarkers, in a cohort of autosomal dominant AD mutation carriers.MethodsIn 139 presymptomatic mutation carriers from the Dominantly Inherited Alzheimer Network, the relationship between self-reported exercise levels and brain amyloid load, cerebrospinal fluid (CSF) Aβ42, and CSF tau levels was evaluated using linear regression.ResultsNo differences in brain amyloid load, CSF Aβ42, or CSF tau were observed between low and high exercise groups. Nevertheless, when examining only those already accumulating AD pathology (i.e., amyloid positive), low exercisers had higher mean levels of brain amyloid than high exercisers. Furthermore, the interaction between exercise and estimated years from expected symptom onset was a significant predictor of brain amyloid levels.DiscussionOur findings indicate a relationship exists between self-reported exercise levels and brain amyloid in autosomal dominant AD mutation carriers.
Published: 2017

23. Cognitive Impairment and Dementia

Author: Warren, Jason, primary, Collinge, John, additional, Fox, Nick, additional, Mead, Simon, additional, Mummery, Catherine, additional, Rohrer, Jonathan, additional, Rossor, Martin, additional, Schott, Jonathan, additional, and Weil, Rimona, additional
Published: 2024
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24. The Dementias Platform UK (DPUK) Data Portal

Author: Bauermeister, Sarah, Orton, Christopher, Thompson, Simon, Barker, Roger A., Bauermeister, Joshua R., Ben-Shlomo, Yoav, Brayne, Carol, Burn, David, Campbell, Archie, Calvin, Catherine, Chandran, Siddharthan, Chaturvedi, Nishi, Chêne, Geneviève, Chessell, Iain P., Corbett, Anne, Davis, Daniel H. J., Denis, Mike, Dufouil, Carole, Elliott, Paul, Fox, Nick, Hill, Derek, Hofer, Scott M., Hu, Michele T., Jindra, Christoph, Kee, Frank, Kim, Chi-Hun, Kim, Changsoo, Kivimaki, Mika, Koychev, Ivan, Lawson, Rachael A., Linden, Gerry J., Lyons, Ronan A., Mackay, Clare, Matthews, Paul M., McGuiness, Bernadette, Middleton, Lefkos, Moody, Catherine, Moore, Katrina, Na, Duk L., O’Brien, John T., Ourselin, Sebastien, Paranjothy, Shantini, Park, Ki-Soo, Porteous, David J., Richards, Marcus, Ritchie, Craig W., Rohrer, Jonathan D., Rossor, Martin N., Rowe, James B., Scahill, Rachael, Schnier, Christian, Schott, Jonathan M., Seo, Sang W., South, Matthew, Steptoe, Matthew, Tabrizi, Sarah J., Tales, Andrea, Tillin, Therese, Timpson, Nicholas J., Toga, Arthur W., Visser, Pieter-Jelle, Wade-Martins, Richard, Wilkinson, Tim, Williams, Julie, Wong, Andrew, and Gallacher, John E. J.
Published: 2020

25. Plasma phospho-tau181 in presymptomatic and symptomatic familial Alzheimer’s disease: a longitudinal cohort study

Author: O’Connor, Antoinette, Karikari, Thomas K., Poole, Teresa, Ashton, Nicholas J., Lantero Rodriguez, Juan, Khatun, Ayesha, Swift, Imogen, Heslegrave, Amanda J., Abel, Emily, Chung, Elisha, Weston, Philip S. J., Pavisic, Ivanna M., Ryan, Natalie S., Barker, Suzie, Rossor, Martin N., Polke, James M., Frost, Chris, Mead, Simon, Blennow, Kaj, Zetterberg, Henrik, and Fox, Nick C.
Published: 2021
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26. Consensus classification of posterior cortical atrophy

Author: Crutch, Sebastian J, Schott, Jonathan M, Rabinovici, Gil D, Murray, Melissa, Snowden, Julie S, van der Flier, Wiesje M, Dickerson, Bradford C, Vandenberghe, Rik, Ahmed, Samrah, Bak, Thomas H, Boeve, Bradley F, Butler, Christopher, Cappa, Stefano F, Ceccaldi, Mathieu, de Souza, Leonardo Cruz, Dubois, Bruno, Felician, Olivier, Galasko, Douglas, Graff‐Radford, Jonathan, Graff‐Radford, Neill R, Hof, Patrick R, Krolak‐Salmon, Pierre, Lehmann, Manja, Magnin, Eloi, Mendez, Mario F, Nestor, Peter J, Onyike, Chiadi U, Pelak, Victoria S, Pijnenburg, Yolande, Primativo, Silvia, Rossor, Martin N, Ryan, Natalie S, Scheltens, Philip, Shakespeare, Timothy J, González, Aida Suárez, Tang‐Wai, David F, Yong, Keir XX, Carrillo, Maria, Fox, Nick C, and Area, Alzheimer's Association ISTAART Atypical Alzheimer's Disease and Associated Syndromes Professional Interest
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Aging, Rare Diseases, Neurosciences, Neurodegenerative, Neurological, Brain, Brain Diseases, Humans, Posterior cortical atrophy, Alzheimer's disease, Clinico-radiological syndrome, Pathophysiology, Biomarker, Alzheimer's Association ISTAART Atypical Alzheimer's Disease and Associated Syndromes Professional Interest Area, Geriatrics, Clinical sciences, Biological psychology
Abstract: IntroductionA classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings.MethodsConsensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA.ResultsA three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum.DiscussionThere was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work.
Published: 2017

27. Patterns of gray matter atrophy in genetic frontotemporal dementia: results from the GENFI study

Author: Andersson, Christin, Archetti, Silvana, Arighi, Andrea, Benussi, Luisa, Black, Sandra, Cosseddu, Maura, Fallström, Marie, Ferreira, Carlos, Fenoglio, Chiara, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gazzina, Stefano, Ghidoni, Roberta, Grisoli, Marina, Jelic, Vesna, Jiskoot, Lize, Keren, Ron, Lombardi, Gemma, Maruta, Carolina, Mead, Simon, Meeter, Lieke, van Minkelen, Rick, Nacmias, Benedetta, Öijerstedt, Linn, Padovani, Alessandro, Panman, Jessica, Pievani, Michela, Polito, Cristina, Premi, Enrico, Prioni, Sara, Rademakers, Rosa, Redaelli, Veronica, Rogaeva, Ekaterina, Rossi, Giacomina, Rossor, Martin, Scarpini, Elio, Tang-Wai, David, Tartaglia, Carmela, Thonberg, Hakan, Tiraboschi, Pietro, Verdelho, Ana, Warren, Jason, Cash, David M., Bocchetta, Martina, Thomas, David L., Dick, Katrina M., van Swieten, John C., Borroni, Barbara, Galimberti, Daniela, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B., Graff, Caroline, Tagliavini, Fabrizio, Frisoni, Giovanni B., Laforce, Robert, Jr., Finger, Elizabeth, de Mendonça, Alexandre, Sorbi, Sandro, Rossor, Martin N., Ourselin, Sebastien, and Rohrer, Jonathan D.
Published: 2018
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28. Social cognition impairment in genetic frontotemporal dementia within the GENFI cohort

Author: Rossor, Martin N., Fox, Nick C., Woollacott, Ione O.C., Shafei, Rachelle, Heller, Carolin, Guerreiro, Rita, Bras, Jose, Thomas, David L., Mead, Simon, Meeter, Lieke, Panman, Jessica, Papma, Janne, Poos, Jackie, van Minkelen, Rick, Pijnenburg, Yolanda, Barandiaran, Myriam, Indakoetxea, Begoña, Gabilondo, Alazne, Tainta, Mikel, de Arriba, Maria, Gorostidi, Ana, Zulaica, Miren, Villanua, Jorge, Diaz, Zigor, Borrego-Ecija, Sergi, Olives, Jaume, Lladó, Albert, Balasa, Mircea, Antonell, Anna, Bargallo, Nuria, Premi, Enrico, Cosseddu MPsych, Maura, Gazzina, Stefano, Padovani, Alessandro, Gasparotti, Roberto, Archetti, Silvana, Black, Sandra, Mitchell, Sara, Rogaeva, Ekaterina, Freedman, Morris, Keren, Ron, Tang-Wai, Daid, Öijerstedt, Linn, Andersson, Christin, Jelic, Vesna, Thonberg, Hakan, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Cope, Thomas, Timberlake, Carolyn, Rittman, Timothy, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Wilke, Carlo, Karnarth, Hans-Otto, Bender, Benjamin, Bruffaerts, Rose, Vandamme, Philip, Vandenbulcke, Mathieu, Ferreira, Catarina B., Miltenberger, Gabriel, Maruta MPsych, Carolina, Verdelho, Ana, Afonso, Sónia, Taipa, Ricardo, Caroppo, Paola, Di Fede, Giuseppe, Giaccone, Giorgio, Muscio, Cristina, Prioni, Sara, Redaelli, Veronica, Rossi, Giacomina, Tiraboschi, Pietro, Duro NPsych, Diana, Almeida, Maria R., Castelo-Branco, Miguel, Leitão, Maria J., Tabuas-Pereira, Miguel, Santiago, Beatriz, Gauthier, Serge, Rosa-Neto, Pedro, Veldsman, Michele, Thompson, Paul, Langheinrich, Tobias, Prix, Catharina, Hoegen, Tobias, Wlasich, Elisabeth, Loosli, Sandra, Schonecker, Sonja, Semler, Elisa, Anderl-Straub, Sarah, Russell, Lucy L., Greaves, Caroline V., Bocchetta, Martina, Nicholas, Jennifer, Convery, Rhian S., Moore, Katrina, Cash, David M., van Swieten, John, Jiskoot, Lize, Moreno, Fermin, Sanchez-Valle, Raquel, Borroni, Barbara, Laforce, Robert, Jr., Masellis, Mario, Tartaglia, Maria Carmela, Graff, Caroline, Rotondo, Emanuela, Galimberti, Daniela, Rowe, James B., Finger, Elizabeth, Synofzik, Matthis, Vandenberghe, Rik, de Mendonça, Alexandre, Tagliavini, Fabrizio, Santana, Isabel, Ducharme, Simon, Butler, Chris, Gerhard, Alex, Levin, Johannes, Danek, Adrian, Otto, Markus, Warren, Jason D., and Rohrer, Jonathan D.
Published: 2020
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29. The BDNFVal66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer’s disease

Author: Franzmeier, Nicolai, Ren, Jinyi, Damm, Alexander, Monté-Rubio, Gemma, Boada, Mercè, Ruiz, Agustín, Ramirez, Alfredo, Jessen, Frank, Düzel, Emrah, Rodríguez Gómez, Octavio, Benzinger, Tammie, Goate, Alison, Karch, Celeste M., Fagan, Anne M., McDade, Eric, Buerger, Katharina, Levin, Johannes, Duering, Marco, Dichgans, Martin, Suárez-Calvet, Marc, Haass, Christian, Gordon, Brian A., Lim, Yen Ying, Masters, Colin L., Janowitz, Daniel, Catak, Cihan, Wolfsgruber, Steffen, Wagner, Michael, Milz, Esther, Moreno-Grau, Sonia, Teipel, Stefan, Grothe, Michel J, Kilimann, Ingo, Rossor, Martin, Fox, Nick, Laske, Christoph, Chhatwal, Jasmeer, Falkai, Peter, Perneczky, Robert, Lee, Jae-Hong, Spottke, Annika, Boecker, Henning, Brosseron, Frederic, Fliessbach, Klaus, Heneka, Michael T., Nestor, Peter, Peters, Oliver, Fuentes, Manuel, Menne, Felix, Priller, Josef, Spruth, Eike J., Franke, Christiana, Schneider, Anja, Westerteicher, Christine, Speck, Oliver, Wiltfang, Jens, Bartels, Claudia, Araque Caballero, Miguel Ángel, Metzger, Coraline, Bittner, Daniel, Salloway, Stephen, Danek, Adrian, Hassenstab, Jason, Yakushev, Igor, Schofield, Peter R., Morris, John C., Bateman, Randall J., and Ewers, Michael
Published: 2021
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30. Binary reversals: a diagnostic sign in primary progressive aphasia.

Author: Mulroy, Eoin, Core, Lucy B., Chokesuwattanaskul, Anthipa, Johnson, Jeremy C. S., Fletcher, Phillip D., Marshall, Charles R., Volkmer, Anna, Rohrer, Jonathan D., Hardy, Chris J. D., Rossor, Martin N., and Warren, Jason D.
Subjects: SPEECH apraxia, APHASIA, ALZHEIMER'S disease
Published: 2024
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31. Age at symptom onset and death and disease duration in genetic frontotemporal dementia: an international retrospective cohort study

Author: Heller, Carolin, Convery, Rhian S, Woollacott, Ione OC, Shafei, Rachelle M, Graff-Radford, Jonathan, Jones, David T, Dheel, Christina M, Savica, Rodolfo, Lapid, Maria I, Baker, Matt, Fields, Julie A, Gavrilova, Ralitza, Domoto-Reilly, Kimiko, Poos, Jackie M, Van der Ende, Emma L, Panman, Jessica L, Donker Kaat, Laura, Seelaar, Harro, Richardson, Anna, Frisoni, Giovanni, Mega, Anna, Fostinelli, Silvia, Chiang, Huei-Hsin, Alberici, Antonella, Arighi, Andrea, Fenoglio, Chiara, Heuer, Hilary, Miller, Bruce, Karydas, Anna, Fong, Jamie, João Leitão, Maria, Santiago, Beatriz, Duro, Diana, Ferreira, Carlos, Gabilondo, Alazne, De Arriba, Maria, Tainta, Mikel, Zulaica, Miren, Ferreira, Catarina, Semler, Elisa, Ludolph, Albert, Landwehrmeyer, Bernhard, Volk, Alexander E, Miltenberger, Gabriel, Verdelho, Ana, Afonso, Sónia, Tartaglia, Maria Carmela, Freedman, Morris, Rogaeva, Ekaterina, Ferrari, Camilla, Piaceri, Irene, Bessi, Valentina, Lombardi, Gemma, St-Onge, Frédéric, Doré, Marie-Claire, Bruffaerts, Rose, Vandenbulcke, Mathieu, Van den Stock, Jan, Mesulam, M Marsel, Bigio, Eileen, Koros, Christos, Papatriantafyllou, John, Kroupis, Christos, Stefanis, Leonidas, Shoesmith, Christien, Robertson, Erik, Coppola, Giovanni, Da Silva Ramos, Eliana Marisa, Geschwind, Daniel, Moore, Katrina M, Nicholas, Jennifer, Grossman, Murray, McMillan, Corey T, Irwin, David J, Massimo, Lauren, Van Deerlin, Vivianna M, Warren, Jason D, Fox, Nick C, Rossor, Martin N, Mead, Simon, Bocchetta, Martina, Boeve, Bradley F, Knopman, David S, Graff-Radford, Neill R, Forsberg, Leah K, Rademakers, Rosa, Wszolek, Zbigniew K, van Swieten, John C, Jiskoot, Lize C, Meeter, Lieke H, Dopper, Elise GP, Papma, Janne M, Snowden, Julie S, Saxon, Jennifer, Jones, Matthew, Pickering-Brown, Stuart, Le Ber, Isabelle, Camuzat, Agnès, Brice, Alexis, Caroppo, Paola, Ghidoni, Roberta, Pievani, Michela, Benussi, Luisa, Binetti, Giuliano, Dickerson, Bradford C, Lucente, Diane, Krivensky, Samantha, Graff, Caroline, Öijerstedt, Linn, Fallström, Marie, Thonberg, Håkan, Ghoshal, Nupur, Morris, John C, Borroni, Barbara, Benussi, Alberto, Padovani, Alessandro, Galimberti, Daniela, Scarpini, Elio, Fumagalli, Giorgio G, Mackenzie, Ian R, Hsiung, Ging-Yuek R, Sengdy, Pheth, Boxer, Adam L, Rosen, Howie, Taylor, Joanne B, Synofzik, Matthis, Wilke, Carlo, Sulzer, Patricia, Hodges, John R, Halliday, Glenda, Kwok, John, Sanchez-Valle, Raquel, Lladó, Albert, Borrego-Ecija, Sergi, Santana, Isabel, Almeida, Maria Rosário, Tábuas-Pereira, Miguel, Moreno, Fermin, Barandiaran, Myriam, Indakoetxea, Begoña, Levin, Johannes, Danek, Adrian, Rowe, James B, Cope, Thomas E, Otto, Markus, Anderl-Straub, Sarah, de Mendonça, Alexandre, Maruta, Carolina, Masellis, Mario, Black, Sandra E, Couratier, Philippe, Lautrette, Geraldine, Huey, Edward D, Sorbi, Sandro, Nacmias, Benedetta, Laforce, Robert, Jr, Tremblay, Marie-Pier L, Vandenberghe, Rik, Damme, Philip Van, Rogalski, Emily J, Weintraub, Sandra, Gerhard, Alexander, Onyike, Chiadi U, Ducharme, Simon, Papageorgiou, Sokratis G, Ng, Adeline Su Lyn, Brodtmann, Amy, Finger, Elizabeth, Guerreiro, Rita, Bras, Jose, and Rohrer, Jonathan D
Published: 2020
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32. Epidemiology and subtypes of dementia

Author: Penn, Dexter, primary and Rossor, Martin, additional
Published: 2021
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33. Binary reversals: a diagnostic sign in primary progressive aphasia

Author: Mulroy, Eoin, primary, Core, Lucy B, additional, Chokesuwattanaskul, Anthipa, additional, Johnson, Jeremy CS, additional, Fletcher, Phillip D, additional, Marshall, Charles R, additional, Volkmer, Anna, additional, Rohrer, Jonathan D, additional, Hardy, Chris JD, additional, Rossor, Martin N, additional, and Warren, Jason D, additional
Published: 2023
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34. Serum neurofilament light chain in genetic frontotemporal dementia: a longitudinal, multicentre cohort study

Author: Rossor, Martin N., Warren, Jason D., Fox, Nick C., Woollacott, Ione O.C., Shafei, Rachelle, Greaves, Caroline, Guerreiro, Rita, Bras, Jose, Thomas, David L., Nicholas, Jennifer, Mead, Simon, van Minkelen, Rick, Barandiaran, Myriam, Indakoetxea, Begoña, Gabilondo, Alazne, Tainta, Mikel, de Arriba, Maria, Gorostidi, Ana, Zulaica, Miren, Villanua, Jorge, Diaz, Zigor, Borrego-Ecija, Sergi, Olives, Jaume, Lladó, Albert, Balasa, Mircea, Antonell, Anna, Bargallo, Nuria, Premi, Enrico, Cosseddu, Maura, Gazzina, Stefano, Padovani, Alessandro, Gasparotti, Roberto, Archetti, Silvana, Black, Sandra, Mitchell, Sara, Rogaeva, Ekaterina, Freedman, Morris, Keren, Ron, Tang-Wai, David, Öijerstedt, Linn, Andersson, Christin, Jelic, Vesna, Thonberg, Hakan, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Cope, Thomas, Timberlake, Carolyn, Rittman, Timothy, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Wilke, Carlo, Karnath, Hans-Otto, Bender, Benjamin, Bruffaerts, Rose, Vandamme, Philip, Vandenbulcke, Mathieu, Ferreira, Catarina B., Miltenberger, Gabriel, Maruta, Carolina, Verdelho, Ana, Afonso, Sónia, Taipa, Ricardo, Caroppo, Paola, Di Fede, Giuseppe, Giaccone, Giorgio, Prioni, Sara, Redaelli, Veronica, Rossi, Giacomina, Tiraboschi, Pietro, Duro, Diana, Rosario Almeida, Maria, Castelo-Branco, Miguel, João Leitão, Maria, Tabuas-Pereira, Miguel, Santiago, Beatriz, Gauthier, Serge, Schonecker, Sonja, Semler, Elisa, Anderl-Straub, Sarah, Benussi, Luisa, Binetti, Giuliano, Ghidoni, Roberta, Pievani, Michela, Lombardi, Gemma, Nacmias, Benedetta, Ferrari, Camilla, Bessi, Valentina, van der Ende, Emma L, Meeter, Lieke H, Poos, Jackie M, Panman, Jessica L, Jiskoot, Lize C, Dopper, Elise G P, Papma, Janne M, de Jong, Frank Jan, Verberk, Inge M W, Teunissen, Charlotte, Rizopoulos, Dimitris, Heller, Carolin, Convery, Rhian S, Moore, Katrina M, Bocchetta, Martina, Neason, Mollie, Cash, David M, Borroni, Barbara, Galimberti, Daniela, Sanchez-Valle, Raquel, Laforce, Robert, Jr, Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Carmela Tartaglia, Maria, Rowe, James B, Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, de Mendonça, Alexandre, Santana, Isabel, Butler, Chris, Ducharme, Simon, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Frisoni, Giovanni B, Cappa, Stefano, Pijnenburg, Yolande A L, Rohrer, Jonathan D, and van Swieten, John C
Published: 2019
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35. Seizures as an early symptom of autosomal dominant Alzheimer's disease

Author: Vöglein, Jonathan, Noachtar, Soheyl, McDade, Eric, Quaid, Kimberly A., Salloway, Stephen, Ghetti, Bernardino, Noble, James, Berman, Sarah, Chhatwal, Jasmeer, Mori, Hiroshi, Fox, Nick, Allegri, Ricardo, Masters, Colin L., Buckles, Virginia, Ringman, John M., Rossor, Martin, Schofield, Peter R., Sperling, Reisa, Jucker, Mathias, Laske, Christoph, Paumier, Katrina, Morris, John C., Bateman, Randall J., Levin, Johannes, and Danek, Adrian
Published: 2019
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36. The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint

Author: Almeida, Maria Rosario, Anderl-Straub, Sarah, Andersson, Christin, Antonell, Anna, Arighi, Andrea, Balasa, Mircea, Barandiaran, Myriam, Bargalló, Nuria, Bartha, Robart, Bender, Benjamin, Benussi, Luisa, Binetti, Giuliano, Black, Sandra, Bocchetta, Martina, Borrego-Ecija, Sergi, Bras, Jose, Bruffaerts, Rose, Caroppo, Paola, Cash, David, Castelo-Branco, Miguel, Convery, Rhian, Cope, Thomas, de Arriba, María, Di Fede, Giuseppe, Díaz, Zigor, Dick, Katrina M., Duro, Diana, Fenoglio, Chiara, Ferreira, Carlos, Ferreira, Catarina B., Flanagan, Toby, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gabilondo, Alazne, Gauthier, Serge, Ghidoni, Roberta, Giaccone, Giorgio, Gorostidi, Ana, Greaves, Caroline, Guerreiro, Rita, Heller, Carolin, Hoegen, Tobias, Indakoetxea, Begoña, Jelic, Vesna, Jiskoot, Lize, Karnath, Hans-Otto, Keren, Ron, Leitão, Maria João, Lladó, Albert, Lombardi, Gemma, Loosli, Sandra, Maruta, Carolina, Mead, Simon, Meeter, Lieke, Miltenberger, Gabriel, van Minkelen, Rick, Mitchell, Sara, Nacmias, Benedetta, Neason, Mollie, Nicholas, Jennifer, Öijerstedt, Linn, Olives, Jaume, Panman, Jessica, Papma, Janne, Patzig, Maximilian, Pievani, Michela, Prioni, Sara, Prix, Catharina, Rademakers, Rosa, Redaelli, Veronica, Rittman, Tim, Rogaeva, Ekaterina, Rosa-Neto, Pedro, Rossi, Giacomina, Rossor, Martin, Santiago, Beatriz, Scarpini, Elio, Semler, Elisa, Shafei, Rachelle, Shoesmith, Christen, Tábuas-Pereira, Miguel, Tainta, Mikel, Tang-Wai, David, Thomas, David L., Thonberg, Hakan, Timberlake, Carolyn, Tiraboschi, Pietro, Vandamme, Philip, Vandenbulcke, Mathieu, Veldsman, Michele, Verdelho, Ana, Villanua, Jorge, Warren, Jason, Wilke, Carlo, Zetterberg, Henrik, Zulaica, Miren, Premi, Enrico, Calhoun, Vince D., Diano, Matteo, Gazzina, Stefano, Cosseddu, Maura, Alberici, Antonella, Archetti, Silvana, Paternicò, Donata, Gasparotti, Roberto, van Swieten, John, Galimberti, Daniela, Sanchez-Valle, Raquel, Laforce, Robert, Jr., Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James, Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, de Mendonça, Alexandre, Santana, Isabel, Butler, Chris, Ducharme, Simon, Gerhard, Alex, Danek, Adrian, Levin, Johannes, Otto, Markus, Frisoni, Giovanni, Cappa, Stefano, Sorbi, Sandro, Padovani, Alessandro, Rohrer, Jonathan D., and Borroni, Barbara
Published: 2019
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37. Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort

Author: Andersson, Christin, Archetti, Silvana, Arighi, Andrea, Benussi, Luisa, Black, Sandra, Cosseddu, Maura, Fallstrm, Marie, Ferreira, Carlos, Fenoglio, Chiara, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gazzina, Stefano, Ghidoni, Roberta, Grisoli, Marina, Jelic, Vesna, Jiskoot, Lize, Keren, Ron, Lombardi, Gemma, Maruta, Carolina, Meeter, Lieke, van Minkelen, Rick, Nacmias, Benedetta, ijerstedt, Linn, Padovani, Alessandro, Panman, Jessica, Pievani, Michela, Polito, Cristina, Premi, Enrico, Prioni, Sara, Rademakers, Rosa, Redaelli, Veronica, Rogaeva, Ekaterina, Rossi, Giacomina, Rossor, Martin, Scarpini, Elio, Tang-Wai, David, Tartaglia, Carmela, Thonberg, Hakan, Tiraboschi, Pietro, Verdelho, Ana, Warren, Jason, Cury, Claire, Durrleman, Stanley, Cash, David M., Lorenzi, Marco, Nicholas, Jennifer M., Bocchetta, Martina, van Swieten, John C., Borroni, Barbara, Galimberti, Daniela, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B., Graff, Caroline, Tagliavini, Fabrizio, Frisoni, Giovanni B., Laforce, Robert, Jr., Finger, Elizabeth, de Mendonça, Alexandre, Sorbi, Sandro, Ourselin, Sebastien, Rohrer, Jonathan D., and Modat, Marc
Published: 2019
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38. Functional Connectivity in Autosomal Dominant and Late-Onset Alzheimer Disease

Author: Thomas, Jewell B, Brier, Matthew R, Bateman, Randall J, Snyder, Abraham Z, Benzinger, Tammie L, Xiong, Chengjie, Raichle, Marcus, Holtzman, David M, Sperling, Reisa A, Mayeux, Richard, Ghetti, Bernardino, Ringman, John M, Salloway, Stephen, McDade, Eric, Rossor, Martin N, Ourselin, Sebastien, Schofield, Peter R, Masters, Colin L, Martins, Ralph N, Weiner, Michael W, Thompson, Paul M, Fox, Nick C, Koeppe, Robert A, Jack, Clifford R, Mathis, Chester A, Oliver, Angela, Blazey, Tyler M, Moulder, Krista, Buckles, Virginia, Hornbeck, Russ, Chhatwal, Jasmeer, Schultz, Aaron P, Goate, Alison M, Fagan, Anne M, Cairns, Nigel J, Marcus, Daniel S, Morris, John C, and Ances, Beau M
Subjects: Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Acquired Cognitive Impairment, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Aging, Alzheimer's Disease, Clinical Research, Dementia, Neurological, Adult, Age of Onset, Aged, Aged, 80 and over, Alzheimer Disease, Cohort Studies, Connectome, Cross-Sectional Studies, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Severity of Illness Index
Abstract: ImportanceAutosomal dominant Alzheimer disease (ADAD) is caused by rare genetic mutations in 3 specific genes in contrast to late-onset Alzheimer disease (LOAD), which has a more polygenetic risk profile.ObjectiveTo assess the similarities and differences in functional connectivity changes owing to ADAD and LOAD.Design, setting, and participantsWe analyzed functional connectivity in multiple brain resting state networks (RSNs) in a cross-sectional cohort of participants with ADAD (n = 79) and LOAD (n = 444), using resting-state functional connectivity magnetic resonance imaging at multiple international academic sites.Main outcomes and measuresFor both types of AD, we quantified and compared functional connectivity changes in RSNs as a function of dementia severity measured by the Clinical Dementia Rating Scale. In ADAD, we qualitatively investigated functional connectivity changes with respect to estimated years from onset of symptoms within 5 RSNs.ResultsA decrease in functional connectivity with increasing Clinical Dementia Rating scores were similar for both LOAD and ADAD in multiple RSNs. Ordinal logistic regression models constructed in one type of Alzheimer disease accurately predicted clinical dementia rating scores in the other, further demonstrating the similarity of functional connectivity loss in each disease type. Among participants with ADAD, functional connectivity in multiple RSNs appeared qualitatively lower in asymptomatic mutation carriers near their anticipated age of symptom onset compared with asymptomatic mutation noncarriers.Conclusions and relevanceResting-state functional connectivity magnetic resonance imaging changes with progressing AD severity are similar between ADAD and LOAD. Resting-state functional connectivity magnetic resonance imaging may be a useful end point for LOAD and ADAD therapy trials. Moreover, the disease process of ADAD may be an effective model for the LOAD disease process.
Published: 2014

39. Frontotemporal dementia and its subtypes: a genome-wide association study

Author: Ferrari, Raffaele, Hernandez, Dena G, Nalls, Michael A, Rohrer, Jonathan D, Ramasamy, Adaikalavan, Kwok, John BJ, Dobson-Stone, Carol, Brooks, William S, Schofield, Peter R, Halliday, Glenda M, Hodges, John R, Piguet, Olivier, Bartley, Lauren, Thompson, Elizabeth, Haan, Eric, Hernández, Isabel, Ruiz, Agustín, Boada, Mercè, Borroni, Barbara, Padovani, Alessandro, Cruchaga, Carlos, Cairns, Nigel J, Benussi, Luisa, Binetti, Giuliano, Ghidoni, Roberta, Forloni, Gianluigi, Galimberti, Daniela, Fenoglio, Chiara, Serpente, Maria, Scarpini, Elio, Clarimón, Jordi, Lleó, Alberto, Blesa, Rafael, Waldö, Maria Landqvist, Nilsson, Karin, Nilsson, Christer, Mackenzie, Ian RA, Hsiung, Ging-Yuek R, Mann, David MA, Grafman, Jordan, Morris, Christopher M, Attems, Johannes, Griffiths, Timothy D, McKeith, Ian G, Thomas, Alan J, Pietrini, P, Huey, Edward D, Wassermann, Eric M, Baborie, Atik, Jaros, Evelyn, Tierney, Michael C, Pastor, Pau, Razquin, Cristina, Ortega-Cubero, Sara, Alonso, Elena, Perneczky, Robert, Diehl-Schmid, Janine, Alexopoulos, Panagiotis, Kurz, Alexander, Rainero, Innocenzo, Rubino, Elisa, Pinessi, Lorenzo, Rogaeva, Ekaterina, St George-Hyslop, Peter, Rossi, Giacomina, Tagliavini, Fabrizio, Giaccone, Giorgio, Rowe, James B, Schlachetzki, Johannes CM, Uphill, James, Collinge, John, Mead, Simon, Danek, Adrian, Van Deerlin, Vivianna M, Grossman, Murray, Trojanowski, John Q, van der Zee, Julie, Deschamps, William, Van Langenhove, Tim, Cruts, Marc, Van Broeckhoven, Christine, Cappa, Stefano F, Le Ber, Isabelle, Hannequin, Didier, Golfier, Véronique, Vercelletto, Martine, Brice, Alexis, Nacmias, Benedetta, Sorbi, Sandro, Bagnoli, Silvia, Piaceri, Irene, Nielsen, Jørgen E, Hjermind, Lena E, Riemenschneider, Matthias, Mayhaus, Manuel, Ibach, Bernd, Gasparoni, Gilles, Pichler, Sabrina, Gu, Wei, and Rossor, Martin N
Subjects: Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Brain Disorders, Alzheimer's Disease Related Dementias (ADRD), Genetics, Neurodegenerative, Dementia, Acquired Cognitive Impairment, Frontotemporal Dementia (FTD), Aging, Human Genome, Clinical Research, Rare Diseases, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Aged, Aged, 80 and over, Female, Frontotemporal Dementia, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Neurology & Neurosurgery, Clinical sciences
Abstract: BackgroundFrontotemporal dementia (FTD) is a complex disorder characterised by a broad range of clinical manifestations, differential pathological signatures, and genetic variability. Mutations in three genes-MAPT, GRN, and C9orf72--have been associated with FTD. We sought to identify novel genetic risk loci associated with the disorder.MethodsWe did a two-stage genome-wide association study on clinical FTD, analysing samples from 3526 patients with FTD and 9402 healthy controls. To reduce genetic heterogeneity, all participants were of European ancestry. In the discovery phase (samples from 2154 patients with FTD and 4308 controls), we did separate association analyses for each FTD subtype (behavioural variant FTD, semantic dementia, progressive non-fluent aphasia, and FTD overlapping with motor neuron disease [FTD-MND]), followed by a meta-analysis of the entire dataset. We carried forward replication of the novel suggestive loci in an independent sample series (samples from 1372 patients and 5094 controls) and then did joint phase and brain expression and methylation quantitative trait loci analyses for the associated (p
Published: 2014

40. Relationship between physical activity, cognition, and Alzheimer pathology in autosomal dominant Alzheimer's disease

Author: Müller, Stephan, Preische, Oliver, Sohrabi, Hamid R., Gräber, Susanne, Jucker, Mathias, Ringman, John M., Martins, Ralph N., McDade, Eric, Schofield, Peter R., Ghetti, Bernardino, Rossor, Martin, Fox, Nick N., Graff-Radford, Neill R., Levin, Johannes, Danek, Adrian, Vöglein, Jonathan, Salloway, Stephen, Xiong, Chengjie, Benzinger, Tammie, Buckles, Virginia, Masters, Colin L., Sperling, Reisa, Bateman, Randall J., Morris, John C., and Laske, Christoph
Published: 2018
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41. TMEM106B is a genetic modifier of frontotemporal lobar degeneration with C9orf72 hexanucleotide repeat expansions.

Author: Gallagher, Michael D, Suh, Eunran, Grossman, Murray, Elman, Lauren, McCluskey, Leo, Van Swieten, John C, Al-Sarraj, Safa, Neumann, Manuela, Gelpi, Ellen, Ghetti, Bernardino, Rohrer, Jonathan D, Halliday, Glenda, Van Broeckhoven, Christine, Seilhean, Danielle, Shaw, Pamela J, Frosch, Matthew P, Alafuzoff, Irina, Antonell, Anna, Bogdanovic, Nenad, Brooks, William, Cairns, Nigel J, Cooper-Knock, Johnathan, Cotman, Carl, Cras, Patrick, Cruts, Marc, De Deyn, Peter P, DeCarli, Charles, Dobson-Stone, Carol, Engelborghs, Sebastiaan, Fox, Nick, Galasko, Douglas, Gearing, Marla, Gijselinck, Ilse, Grafman, Jordan, Hartikainen, Päivi, Hatanpaa, Kimmo J, Highley, J Robin, Hodges, John, Hulette, Christine, Ince, Paul G, Jin, Lee-Way, Kirby, Janine, Kofler, Julia, Kril, Jillian, Kwok, John BJ, Levey, Allan, Lieberman, Andrew, Llado, Albert, Martin, Jean-Jacques, Masliah, Eliezer, McDermott, Christopher J, McKee, Ann, McLean, Catriona, Mead, Simon, Miller, Carol A, Miller, Josh, Munoz, David G, Murrell, Jill, Paulson, Henry, Piguet, Olivier, Rossor, Martin, Sanchez-Valle, Raquel, Sano, Mary, Schneider, Julie, Silbert, Lisa C, Spina, Salvatore, van der Zee, Julie, Van Langenhove, Tim, Warren, Jason, Wharton, Stephen B, White, Charles L, Woltjer, Randall L, Trojanowski, John Q, Lee, Virginia MY, Van Deerlin, Vivianna, and Chen-Plotkin, Alice S
Subjects: Humans, Amyotrophic Lateral Sclerosis, Genetic Predisposition to Disease, Intercellular Signaling Peptides and Proteins, Proteins, Membrane Proteins, Nerve Tissue Proteins, Cohort Studies, Age Factors, Age of Onset, DNA Repeat Expansion, Genotype, Heterozygote, Polymorphism, Single Nucleotide, Alleles, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Frontotemporal Lobar Degeneration, C9orf72 Protein, Progranulins, Rare Diseases, Aging, Neurosciences, Alzheimer's Disease Related Dementias (ADRD), Brain Disorders, Neurodegenerative, Prevention, Genetics, Dementia, Frontotemporal Dementia (FTD), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Aetiology, 2.1 Biological and endogenous factors, Neurological, TMEM106B, C9orf72, Frontotemporal dementia, Frontotemporal lobar degeneration, Amyotrophic lateral sclerosis, Genetic modifier, Clinical Sciences, Neurology & Neurosurgery
Abstract: Hexanucleotide repeat expansions in chromosome 9 open reading frame 72 (C9orf72) have recently been linked to frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis, and may be the most common genetic cause of both neurodegenerative diseases. Genetic variants at TMEM106B influence risk for the most common neuropathological subtype of FTLD, characterized by inclusions of TAR DNA-binding protein of 43 kDa (FTLD-TDP). Previous reports have shown that TMEM106B is a genetic modifier of FTLD-TDP caused by progranulin (GRN) mutations, with the major (risk) allele of rs1990622 associating with earlier age at onset of disease. Here, we report that rs1990622 genotype affects age at death in a single-site discovery cohort of FTLD patients with C9orf72 expansions (n = 14), with the major allele correlated with later age at death (p = 0.024). We replicate this modifier effect in a 30-site international neuropathological cohort of FTLD-TDP patients with C9orf72 expansions (n = 75), again finding that the major allele associates with later age at death (p = 0.016), as well as later age at onset (p = 0.019). In contrast, TMEM106B genotype does not affect age at onset or death in 241 FTLD-TDP cases negative for GRN mutations or C9orf72 expansions. Thus, TMEM106B is a genetic modifier of FTLD with C9orf72 expansions. Intriguingly, the genotype that confers increased risk for developing FTLD-TDP (major, or T, allele of rs1990622) is associated with later age at onset and death in C9orf72 expansion carriers, providing an example of sign epistasis in human neurodegenerative disease.
Published: 2014

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

Author: Young, Alexandra L., Bocchetta, Martina, Russell, Lucy L., Convery, Rhian S., Peakman, Georgia, Todd, Emily, Cash, David M., Greaves, Caroline V., van Swieten, John, Jiskoot, Lize, Seelaar, Harro, Moreno, Fermin, Sanchez-Valle, Raquel, Borroni, Barbara, Laforce, Robert, Jr, Masellis, Mario, Tartaglia, Maria Carmela, Graff, Caroline, Galimberti, Daniela, Rowe, James B., Finger, Elizabeth, Synofzik, Matthis, Vandenberghe, Rik, de Mendonça, Alexandre, Tagliavini, Fabrizio, Santana, Isabel, Ducharme, Simon, Butler, Chris, Gerhard, Alex, Levin, Johannes, Danek, Adrian, Otto, Markus, Sorbi, Sandro, Williams, Steven C.R., Alexander, Daniel C., Rohrer, Jonathan D., Rossor, Martin N., Fox, Nick C., Warren, Jason D., Woollacott, Ione, Shafei, Rachelle, Heller, Carolin, Swift, Imogen J, Moore, Katrina, Guerreiro, Rita, Bras, Jose, Thomas, David L., Nicholas, Jennifer, Mead, Simon, Meeter, Lieke, Panman, Jessica, Papma, Janne M., Poos, Jackie, van Minkelen, Rick, Pijnenburg, Yolande, Barandiaran, Myriam, Indakoetxea, Begoña, Gabilondo, Alazne, Tainta, Mikel, de Arriba, María, Gorostidi, Ana, Zulaica, Miren, Villanua, Jorge, Díaz, Zigor, Borrego-Ecija, Sergi, Olives, Jaume, Lladó, Albert, Balasa, Mircea, Antonell, Anna, Bargalló, Nuria, Premi, Enrico, Cosseddu, Maura, Gazzina, Stefano, Padovani, Alessandro, Gasparotti, Roberto, Archetti, Silvana, Black, Sandra, Mitchell, Sara, Rogaeva, Ekaterina, Freedman, Morris, Keren, Ron, Tang-Wai, David, Öijerstedt, Linn, Andersson, Christin, Jelic, Vesna, Thonberg, Hakan, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Cope, Thomas, Timberlake, Carolyn, Rittman, Timothy, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Wilke, Carlo, Karnath, Hans Otto, Bender, Benjamin, Bruffaerts, Rose, Van Damme, Philip, Vandenbulcke, Mathieu, Ferreira, Catarina B., Miltenberger, Gabriel, Maruta, Carolina, Verdelho, Ana, Afonso, Sónia, Taipa, Ricardo, Caroppo, Paola, Di Fede, Giuseppe, Giaccone, Giorgio, Prioni, Sara, Redaelli, Veronica, Rossi, Giacomina, Tiraboschi, Pietro, Duro, Diana, Almeida, Maria Rosario, Branco, Miguel Castelo, Leitão, Maria João, 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, Schönecker, Sonja, Dr.hum.bio, Elisa Semler, Psych, Dipl., Anderl-Straub, Sarah, Psych, Dipl., Nacmias, Benedetta, Ferrari, Camilla, Polito, Cristina, Lombardi, Gemma, and Bessi, Valentina
Published: 2021
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43. Genetic evidence for serum amyloid P component as a drug target for treatment of neurodegenerative disorders

Author: Schmidt, Amand Floriaan, primary, Finan, Chris, additional, Chopade, Sandesh, additional, Ellmerich, Stephan, additional, Rossor, Martin, additional, Hingorani, Aroon Dinesh, additional, and Pepys, Mark, additional
Published: 2023
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44. Regional variability of imaging biomarkers in autosomal dominant Alzheimer’s disease

Author: Benzinger, Tammie LS, Blazey, Tyler, Jack, Clifford R, Koeppe, Robert A, Su, Yi, Xiong, Chengjie, Raichle, Marcus E, Snyder, Abraham Z, Ances, Beau M, Bateman, Randall J, Cairns, Nigel J, Fagan, Anne M, Goate, Alison, Marcus, Daniel S, Aisen, Paul S, Christensen, Jon J, Ercole, Lindsay, Hornbeck, Russ C, Farrar, Angela M, Aldea, Patricia, Jasielec, Mateusz S, Owen, Christopher J, Xie, Xianyun, Mayeux, Richard, Brickman, Adam, McDade, Eric, Klunk, William, Mathis, Chester A, Ringman, John, Thompson, Paul M, Ghetti, Bernardino, Saykin, Andrew J, Sperling, Reisa A, Johnson, Keith A, Salloway, Stephen, Correia, Stephen, Schofield, Peter R, Masters, Colin L, Rowe, Christopher, Villemagne, Victor L, Martins, Ralph, Ourselin, Sebastien, Rossor, Martin N, Fox, Nick C, Cash, David M, Weiner, Michael W, Holtzman, David M, Buckles, Virginia D, Moulder, Krista, and Morris, John C
Subjects: Clinical Research, Dementia, Alzheimer's Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Neurodegenerative, Biomedical Imaging, Neurosciences, Acquired Cognitive Impairment, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Age of Onset, Alzheimer Disease, Aniline Compounds, Biomarkers, Brain, Carbon Radioisotopes, Cohort Studies, Female, Fluorodeoxyglucose F18, Genes, Dominant, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Models, Biological, Positron-Emission Tomography, Regression Analysis, Thiazoles, Time Factors, neuroimaging, aging, dementia, neurodegeneration, DIAN
Abstract: Major imaging biomarkers of Alzheimer's disease include amyloid deposition [imaged with [(11)C]Pittsburgh compound B (PiB) PET], altered glucose metabolism (imaged with [(18)F]fluro-deoxyglucose PET), and structural atrophy (imaged by MRI). Recently we published the initial subset of imaging findings for specific regions in a cohort of individuals with autosomal dominant Alzheimer's disease. We now extend this work to include a larger cohort, whole-brain analyses integrating all three imaging modalities, and longitudinal data to examine regional differences in imaging biomarker dynamics. The anatomical distribution of imaging biomarkers is described in relation to estimated years from symptom onset. Autosomal dominant Alzheimer's disease mutation carrier individuals have elevated PiB levels in nearly every cortical region 15 y before the estimated age of onset. Reduced cortical glucose metabolism and cortical thinning in the medial and lateral parietal lobe appeared 10 and 5 y, respectively, before estimated age of onset. Importantly, however, a divergent pattern was observed subcortically. All subcortical gray-matter regions exhibited elevated PiB uptake, but despite this, only the hippocampus showed reduced glucose metabolism. Similarly, atrophy was not observed in the caudate and pallidum despite marked amyloid accumulation. Finally, before hypometabolism, a hypermetabolic phase was identified for some cortical regions, including the precuneus and posterior cingulate. Additional analyses of individuals in which longitudinal data were available suggested that an accelerated appearance of volumetric declines approximately coincides with the onset of the symptomatic phase of the disease.
Published: 2013

45. Consent recommendations for research and international data sharing involving persons with dementia

Author: Thorogood, Adrian, Mäki-Petäjä-Leinonen, Anna, Brodaty, Henry, Dalpé, Gratien, Gastmans, Chris, Gauthier, Serge, Gove, Dianne, Harding, Rosie, Knoppers, Bartha Maria, Rossor, Martin, and Bobrow, Martin
Published: 2018
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46. Accelerated long-term forgetting in presymptomatic autosomal dominant Alzheimer's disease: a cross-sectional study

Author: Weston, Philip S J, Nicholas, Jennifer M, Henley, Susie M D, Liang, Yuying, Macpherson, Kirsty, Donnachie, Elizabeth, Schott, Jonathan M, Rossor, Martin N, Crutch, Sebastian J, Butler, Christopher R, Zeman, Adam Z, and Fox, Nick C
Published: 2018
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47. Developing an international network for Alzheimer’s research: the Dominantly Inherited Alzheimer Network

Author: Morris, John C, Aisen, Paul S, Bateman, Randall J, Benzinger, Tammie LS, Cairns, Nigel J, Fagan, Anne M, Ghetti, Bernardino, Goate, Alison M, Holtzman, David M, Klunk, William E, McDade, Eric, Marcus, Daniel S, Martins, Ralph N, Masters, Colin L, Mayeux, Richard, Oliver, Angela, Quaid, Kimberly, Ringman, John M, Rossor, Martin N, Salloway, Stephen, Schofield, Peter R, Selsor, Natalie J, Sperling, Reisa A, Weiner, Michael W, Xiong, Chengjie, Moulder, Krista L, and Buckles, Virginia D
Subjects: Health Services and Systems, Health Sciences, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease, Dementia, Acquired Cognitive Impairment, Neurosciences, Genetics, Aging, Brain Disorders, Prevention, Clinical Research, Neurological
Abstract: The Dominantly Inherited Alzheimer Network (DIAN) is a collaborative effort of international Alzheimer disease (AD) centers that are conducting a multifaceted prospective biomarker study in individuals at-risk for autosomal dominant AD (ADAD). DIAN collects comprehensive information and tissue in accordance with standard protocols from asymptomatic and symptomatic ADAD mutation carriers and their non-carrier family members to determine the pathochronology of clinical, cognitive, neuroimaging, and fluid biomarkers of AD. This article describes the structure, implementation, and underlying principles of DIAN, as well as the demographic features of the initial DIAN cohort.
Published: 2012

48. Creation of an open-access, mutation-defined fibroblast resource for neurological disease research.

Author: Wray, Selina, Self, Matthew, NINDS Parkinson's Disease iPSC Consortium, NINDS Huntington's Disease iPSC Consortium, NINDS ALS iPSC Consortium, Lewis, Patrick A, Taanman, Jan-Willem, Ryan, Natalie S, Mahoney, Colin J, Liang, Yuying, Devine, Michael J, Sheerin, Una-Marie, Houlden, Henry, Morris, Huw R, Healy, Daniel, Marti-Masso, Jose-Felix, Preza, Elisavet, Barker, Suzanne, Sutherland, Margaret, Corriveau, Roderick A, D'Andrea, Michael, Schapira, Anthony HV, Uitti, Ryan J, Guttman, Mark, Opala, Grzegorz, Jasinska-Myga, Barbara, Puschmann, Andreas, Nilsson, Christer, Espay, Alberto J, Slawek, Jaroslaw, Gutmann, Ludwig, Boeve, Bradley F, Boylan, Kevin, Stoessl, A Jon, Ross, Owen A, Maragakis, Nicholas J, Van Gerpen, Jay, Gerstenhaber, Melissa, Gwinn, Katrina, Dawson, Ted M, Isacson, Ole, Marder, Karen S, Clark, Lorraine N, Przedborski, Serge E, Finkbeiner, Steven, Rothstein, Jeffrey D, Wszolek, Zbigniew K, Rossor, Martin N, and Hardy, John
Subjects: NINDS Parkinson's Disease iPSC Consortium, NINDS Huntington's Disease iPSC Consortium, NINDS ALS iPSC Consortium, Cell Line, Fibroblasts, Humans, Nervous System Diseases, Biopsy, Immunohistochemistry, Cell Differentiation, Cell Proliferation, Mutation, Models, Genetic, Access to Information, Databases, Factual, Tissue Banks, Induced Pluripotent Stem Cells, Stem Cell Research - Induced Pluripotent Stem Cell - Human, Stem Cell Research - Induced Pluripotent Stem Cell, Genetics, Stem Cell Research, Neurosciences, Brain Disorders, Aetiology, 2.6 Resources and infrastructure (aetiology), 2.1 Biological and endogenous factors, Generic health relevance, Neurological, General Science & Technology
Abstract: Our understanding of the molecular mechanisms of many neurological disorders has been greatly enhanced by the discovery of mutations in genes linked to familial forms of these diseases. These have facilitated the generation of cell and animal models that can be used to understand the underlying molecular pathology. Recently, there has been a surge of interest in the use of patient-derived cells, due to the development of induced pluripotent stem cells and their subsequent differentiation into neurons and glia. Access to patient cell lines carrying the relevant mutations is a limiting factor for many centres wishing to pursue this research. We have therefore generated an open-access collection of fibroblast lines from patients carrying mutations linked to neurological disease. These cell lines have been deposited in the National Institute for Neurological Disorders and Stroke (NINDS) Repository at the Coriell Institute for Medical Research and can be requested by any research group for use in in vitro disease modelling. There are currently 71 mutation-defined cell lines available for request from a wide range of neurological disorders and this collection will be continually expanded. This represents a significant resource that will advance the use of patient cells as disease models by the scientific community.
Published: 2012

49. Toward common mechanisms for risk factors in Alzheimer's syndrome

Author: Medina, Miguel, Khachaturian, Zaven S., Rossor, Martin, Avila, Jesús, and Cedazo-Minguez, Angel
Published: 2017
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50. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease.

Author: McKhann, Guy M, Knopman, David S, Chertkow, Howard, Hyman, Bradley T, Jack, Clifford R, Kawas, Claudia H, Klunk, William E, Koroshetz, Walter J, Manly, Jennifer J, Mayeux, Richard, Mohs, Richard C, Morris, John C, Rossor, Martin N, Scheltens, Philip, Carrillo, Maria C, Thies, Bill, Weintraub, Sandra, and Phelps, Creighton H
Subjects: Humans, Alzheimer Disease, Disease Progression, Diagnosis, Differential, Diagnostic Imaging, Societies, Medical, United States, Practice Guidelines as Topic, National Institute on Aging (U.S.), Biomarkers, Alzheimer's disease, Dementia, Diagnosis, Magnetic resonance brain imaging, Positron emission tomography, Cerebrospinal fluid, Differential, Societies, Medical, National Institute on Aging, Geriatrics, Neurosciences, Clinical Sciences
Abstract: The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of revising the 1984 criteria for Alzheimer's disease (AD) dementia. The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available. We present criteria for all-cause dementia and for AD dementia. We retained the general framework of probable AD dementia from the 1984 criteria. On the basis of the past 27 years of experience, we made several changes in the clinical criteria for the diagnosis. We also retained the term possible AD dementia, but redefined it in a manner more focused than before. Biomarker evidence was also integrated into the diagnostic formulations for probable and possible AD dementia for use in research settings. The core clinical criteria for AD dementia will continue to be the cornerstone of the diagnosis in clinical practice, but biomarker evidence is expected to enhance the pathophysiological specificity of the diagnosis of AD dementia. Much work lies ahead for validating the biomarker diagnosis of AD dementia.
Published: 2011

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