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1. Developing a Framework for Safe AI Model Development on Sensitive Healthcare Data

Author: Lewis Hotchkiss, Emma Squires, Timothy Rittman, John Gallacher, and Simon Thompson
Subjects: Demography. Population. Vital events, HB848-3697
Abstract: The Dementias Platform UK (DPUK) Data Portal holds over 60 cohort datasets from over 3 million participants with a range of multi-modal data including neuroimaging and genomics. This has meant we have seen an increasing interest in the development of AI models with the potential for clinical implementation. However, this presents a unique challenge to disclosure control when it comes to assessing these AI models for release due to the risk of attacks such as membership inference, model inversion or even just vulnerabilities in the models like overfitting. This is why we hosted a series of workshops bringing together members of the public, expert researchers, and data owners across the UK to build a framework for allowing the safe development and release of AI models trained on sensitive healthcare data. From this, we have put together recommendations and guidelines for the use of privacy-preserving techniques in AI models to protect patient privacy, and to allow the safe deployment of these models outside of trusted research environments. We also identified the unique challenges to privacy and implementation of privacy-preserving techniques in AI models regarding the use of complex data such as neuroimaging and genomics. This framework has created a path forward for supporting safe AI model development which takes into consideration rapidly evolving ethical, legal and privacy considerations.
Published: 2024
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2. Synaptic density affects clinical severity via network dysfunction in syndromes associated with frontotemporal lobar degeneration

Author: David J. Whiteside, Negin Holland, Kamen A. Tsvetanov, Elijah Mak, Maura Malpetti, George Savulich, P. Simon Jones, Michelle Naessens, Matthew A. Rouse, Tim D. Fryer, Young T. Hong, Franklin I. Aigbirhio, Eoin Mulroy, Kailash P. Bhatia, Timothy Rittman, John T. O’Brien, and James B. Rowe
Subjects: Science
Abstract: Abstract There is extensive synaptic loss from frontotemporal lobar degeneration, in preclinical models and human in vivo and post mortem studies. Understanding the consequences of synaptic loss for network function is important to support translational models and guide future therapeutic strategies. To examine this relationship, we recruited 55 participants with syndromes associated with frontotemporal lobar degeneration and 24 healthy controls. We measured synaptic density with positron emission tomography using the radioligand [11C]UCB-J, which binds to the presynaptic vesicle glycoprotein SV2A, neurite dispersion with diffusion magnetic resonance imaging, and network function with task-free magnetic resonance imaging functional connectivity. Synaptic density and neurite dispersion in patients was associated with reduced connectivity beyond atrophy. Functional connectivity moderated the relationship between synaptic density and clinical severity. Our findings confirm the importance of synaptic loss in frontotemporal lobar degeneration syndromes, and the resulting effect on behaviour as a function of abnormal connectivity.
Published: 2023
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3. Accurate digital quantification of tau pathology in progressive supranuclear palsy

Author: Tanrada Pansuwan, Annelies Quaegebeur, Sanne S. Kaalund, Eric Hidari, Mayen Briggs, James B. Rowe, and Timothy Rittman
Subjects: Digital pathology, Random forest, Neurodegenerative diseases, Machine learning, PSP, Neurology. Diseases of the nervous system, RC346-429
Abstract: Abstract The development of novel treatments for Progressive Supranuclear Palsy (PSP) is hindered by a knowledge gap of the impact of neurodegenerative neuropathology on brain structure and function. The current standard practice for measuring postmortem tau histology is semi-quantitative assessment, which is prone to inter-rater variability, time-consuming and difficult to scale. We developed and optimized a tau aggregate type-specific quantification pipeline for cortical and subcortical regions, in human brain donors with PSP. We quantified 4 tau objects (‘neurofibrillary tangles’, ‘coiled bodies’, ‘tufted astrocytes’, and ‘tau fragments’) using a probabilistic random forest machine learning classifier. The tau pipeline achieved high classification performance (F1-score > 0.90), comparable to neuropathologist inter-rater reliability in the held-out test set. Using 240 AT8 slides from 32 postmortem brains, the tau burden was correlated against the PSP pathology staging scheme using Spearman’s rank correlation. We assessed whether clinical severity (PSP rating scale, PSPRS) score reflects neuropathological severity inferred from PSP stage and tau burden using Bayesian linear mixed regression. Tufted astrocyte density in cortical regions and coiled body density in subcortical regions showed the highest correlation to PSP stage (r = 0.62 and r = 0.38, respectively). Using traditional manual staging, only PSP patients in stage 6, not earlier stages, had significantly higher clinical severity than stage 2. Cortical tau density and neurofibrillary tangle density in subcortical regions correlated with clinical severity. Overall, our data indicate the potential for highly accurate digital tau aggregate type-specific quantification for neurodegenerative tauopathies; and the importance of studying tau aggregate type-specific burden in different brain regions as opposed to overall tau, to gain insights into the pathogenesis and progression of tauopathies.
Published: 2023
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4. Bridging modifiable risk factors and cognitive decline: the mediating role of brain age

Author: Marcella Montagnese and Timothy Rittman
Subjects: Geriatrics, RC952-954.6, Medicine
Published: 2024
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5. Identifying healthy individuals with Alzheimer’s disease neuroimaging phenotypes in the UK Biobank

Author: Tiago Azevedo, Richard A. I. Bethlehem, David J. Whiteside, Nol Swaddiwudhipong, James B. Rowe, Pietro Lió, Timothy Rittman, and the Alzheimer’s Disease Neuroimaging Initiative
Subjects: Medicine
Abstract: Abstract Background Identifying prediagnostic neurodegenerative disease is a critical issue in neurodegenerative disease research, and Alzheimer’s disease (AD) in particular, to identify populations suitable for preventive and early disease-modifying trials. Evidence from genetic and other studies suggests the neurodegeneration of Alzheimer’s disease measured by brain atrophy starts many years before diagnosis, but it is unclear whether these changes can be used to reliably detect prediagnostic sporadic disease. Methods We trained a Bayesian machine learning neural network model to generate a neuroimaging phenotype and AD score representing the probability of AD using structural MRI data in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Cohort (cut-off 0.5, AUC 0.92, PPV 0.90, NPV 0.93). We go on to validate the model in an independent real-world dataset of the National Alzheimer’s Coordinating Centre (AUC 0.74, PPV 0.65, NPV 0.80) and demonstrate the correlation of the AD-score with cognitive scores in those with an AD-score above 0.5. We then apply the model to a healthy population in the UK Biobank study to identify a cohort at risk for Alzheimer’s disease. Results We show that the cohort with a neuroimaging Alzheimer’s phenotype has a cognitive profile in keeping with Alzheimer’s disease, with strong evidence for poorer fluid intelligence, and some evidence of poorer numeric memory, reaction time, working memory, and prospective memory. We found some evidence in the AD-score positive cohort for modifiable risk factors of hypertension and smoking. Conclusions This approach demonstrates the feasibility of using AI methods to identify a potentially prediagnostic population at high risk for developing sporadic Alzheimer’s disease.
Published: 2023
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6. Harnessing the potential of machine learning and artificial intelligence for dementia research

Author: Janice M. Ranson, Magda Bucholc, Donald Lyall, Danielle Newby, Laura Winchester, Neil P. Oxtoby, Michele Veldsman, Timothy Rittman, Sarah Marzi, Nathan Skene, Ahmad Al Khleifat, Isabelle F. Foote, Vasiliki Orgeta, Andrey Kormilitzin, Ilianna Lourida, and David J. Llewellyn
Subjects: Dementia, Artificial intelligence, Machine learning, Genetics, Drug discovery, Neuroimaging, Computer applications to medicine. Medical informatics, R858-859.7, Computer software, QA76.75-76.765
Abstract: Abstract Progress in dementia research has been limited, with substantial gaps in our knowledge of targets for prevention, mechanisms for disease progression, and disease-modifying treatments. The growing availability of multimodal data sets opens possibilities for the application of machine learning and artificial intelligence (AI) to help answer key questions in the field. We provide an overview of the state of the science, highlighting current challenges and opportunities for utilisation of AI approaches to move the field forward in the areas of genetics, experimental medicine, drug discovery and trials optimisation, imaging, and prevention. Machine learning methods can enhance results of genetic studies, help determine biological effects and facilitate the identification of drug targets based on genetic and transcriptomic information. The use of unsupervised learning for understanding disease mechanisms for drug discovery is promising, while analysis of multimodal data sets to characterise and quantify disease severity and subtype are also beginning to contribute to optimisation of clinical trial recruitment. Data-driven experimental medicine is needed to analyse data across modalities and develop novel algorithms to translate insights from animal models to human disease biology. AI methods in neuroimaging outperform traditional approaches for diagnostic classification, and although challenges around validation and translation remain, there is optimism for their meaningful integration to clinical practice in the near future. AI-based models can also clarify our understanding of the causality and commonality of dementia risk factors, informing and improving risk prediction models along with the development of preventative interventions. The complexity and heterogeneity of dementia requires an alternative approach beyond traditional design and analytical approaches. Although not yet widely used in dementia research, machine learning and AI have the potential to unlock current challenges and advance precision dementia medicine.
Published: 2023
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7. Early neurotransmitters changes in prodromal frontotemporal dementia: A GENFI study

Author: Enrico Premi, Marta Pengo, Irene Mattioli, Valentina Cantoni, Juergen Dukart, Roberto Gasparotti, Emanuele Buratti, Alessandro Padovani, Martina Bocchetta, Emily G. Todd, Arabella Bouzigues, David M. Cash, Rhian S. Convery, Lucy L. Russell, Phoebe Foster, David L. Thomas, John C. van Swieten, Lize C. Jiskoot, Harro Seelaar, Daniela Galimberti, Raquel Sanchez-Valle, Robert Laforce, Jr, Fermin Moreno, Matthis Synofzik, Caroline Graff, Mario Masellis, Maria Carmela Tartaglia, James B. Rowe, Kamen A. Tsvetanov, Rik Vandenberghe, Elizabeth Finger, Pietro Tiraboschi, Alexandre de Mendonça, Isabel Santana, Chris R. Butler, Simon Ducharme, Alexander Gerhard, Johannes Levin, Markus Otto, Sandro Sorbi, Isabelle Le Ber, Florence Pasquier, Jonathan D. Rohrer, Barbara Borroni, Aitana Sogorb Esteve, Carolin Heller, Caroline V. Greaves, Henrik Zetterberg, Imogen J. Swift, Kiran Samra, Rachelle Shafei, Carolyn Timberlake, Thomas Cope, Timothy Rittman, Andrea Arighi, Chiara Fenoglio, Elio Scarpini, Giorgio Fumagalli, Vittoria Borracci, Giacomina Rossi, Giorgio Giaccone, Giuseppe Di Fede, Paola Caroppo, Sara Prioni, Veronica Redaelli, David Tang-Wai, Ekaterina Rogaeva, Miguel Castelo-Branco, Morris Freedman, Ron Keren, Sandra Black, Sara Mitchell, Christen Shoesmith, Robart Bartha, Rosa Rademakers, Jackie Poos, Janne M. Papma, Lucia Giannini, Rick van Minkelen, Yolande Pijnenburg, Benedetta Nacmias, Camilla Ferrari, Cristina Polito, Gemma Lombardi, Valentina Bessi, Michele Veldsman, Christin Andersson, Hakan Thonberg, Linn Öijerstedt, Vesna Jelic, Paul Thompson, Tobias Langheinrich, Albert Lladó, Anna Antonell, Jaume Olives, Mircea Balasa, Nuria Bargalló, Sergi Borrego-Ecija, Ana Verdelho, Carolina Maruta, Catarina B. Ferreira, Gabriel Miltenberger, Frederico Simões do Couto, Alazne Gabilondo, Ana Gorostidi, Jorge Villanua, Marta Cañada, Mikel Tainta, Miren Zulaica, Myriam Barandiaran, Patricia Alves, Benjamin Bender, Carlo Wilke, Lisa Graf, Annick Vogels, Mathieu Vandenbulcke, Philip Van Damme, Rose Bruffaerts, Koen Poesen, Pedro Rosa-Neto, Serge Gauthier, Agnès Camuzat, Alexis Brice, Anne Bertrand, Aurélie Funkiewiez, Daisy Rinaldi, Dario Saracino, Olivier Colliot, Sabrina Sayah, Catharina Prix, Elisabeth Wlasich, Olivia Wagemann, Sandra Loosli, Sonja Schönecker, Tobias Hoegen, Jolina Lombardi, Sarah Anderl-Straub, Adeline Rollin, Gregory Kuchcinski, Maxime Bertoux, Thibaud Lebouvier, Vincent Deramecourt, Beatriz Santiago, Diana Duro, Maria João Leitão, Maria Rosario Almeida, Miguel Tábuas-Pereira, and Sónia Afonso
Subjects: Frontotemporal dementia, Frontotemporal lobar degeneration, Genes, Magnetic resonance imaging, Positron emission tomography, Neurotransmitters, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Background: Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches. Methods: In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission.We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD. Results: In prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p
Published: 2023
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8. Modifiable risk factors for dementia and dementia risk profiling. A user manual for Brain Health Services—part 2 of 6

Author: Janice M. Ranson, Timothy Rittman, Shabina Hayat, Carol Brayne, Frank Jessen, Kaj Blennow, Cornelia van Duijn, Frederik Barkhof, Eugene Tang, Catherine J. Mummery, Blossom C. M. Stephan, Daniele Altomare, Giovanni B. Frisoni, Federica Ribaldi, José Luis Molinuevo, Philip Scheltens, David J. Llewellyn, and on behalf of the European Task Force for Brain Health Services
Subjects: Alzheimer’s disease, Dementia, Aging, Brain health services, Risk factors, Risk profiling, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract: Abstract We envisage the development of new Brain Health Services to achieve primary and secondary dementia prevention. These services will complement existing memory clinics by targeting cognitively unimpaired individuals, where the focus is on risk profiling and personalized risk reduction interventions rather than diagnosing and treating late-stage disease. In this article, we review key potentially modifiable risk factors and genetic risk factors and discuss assessment of risk factors as well as additional fluid and imaging biomarkers that may enhance risk profiling. We then outline multidomain measures and risk profiling and provide practical guidelines for Brain Health Services, with consideration of outstanding uncertainties and challenges. Users of Brain Health Services should undergo risk profiling tailored to their age, level of risk, and availability of local resources. Initial risk assessment should incorporate a multidomain risk profiling measure. For users aged 39–64, we recommend the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) Dementia Risk Score, whereas for users aged 65 and older, we recommend the Brief Dementia Screening Indicator (BDSI) and the Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI). The initial assessment should also include potentially modifiable risk factors including sociodemographic, lifestyle, and health factors. If resources allow, apolipoprotein E ɛ4 status testing and structural magnetic resonance imaging should be conducted. If this initial assessment indicates a low dementia risk, then low intensity interventions can be implemented. If the user has a high dementia risk, additional investigations should be considered if local resources allow. Common variant polygenic risk of late-onset AD can be tested in middle-aged or older adults. Rare variants should only be investigated in users with a family history of early-onset dementia in a first degree relative. Advanced imaging with 18-fluorodeoxyglucose positron emission tomography (FDG-PET) or amyloid PET may be informative in high risk users to clarify the nature and burden of their underlying pathologies. Cerebrospinal fluid biomarkers are not recommended for this setting, and blood-based biomarkers need further validation before clinical use. As new technologies become available, advances in artificial intelligence are likely to improve our ability to combine diverse data to further enhance risk profiling. Ultimately, Brain Health Services have the potential to reduce the future burden of dementia through risk profiling, risk communication, personalized risk reduction, and cognitive enhancement interventions.
Published: 2021
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9. Synaptic density in carriers of C9orf72 mutations: a [11C]UCB‐J PET study

Author: Maura Malpetti, Negin Holland, P. Simon Jones, Rong Ye, Thomas E. Cope, Tim D. Fryer, Young T. Hong, George Savulich, Timothy Rittman, Luca Passamonti, Elijah Mak, Franklin I. Aigbirhio, John T. O’Brien, and James B. Rowe
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract: Abstract Synaptic loss is an early and clinically relevant feature of many neurodegenerative diseases. Here we assess three adults at risk of frontotemporal dementia from C9orf72 mutation, using [11C]UCB‐J PET to quantify synaptic density in comparison with 19 healthy controls and one symptomatic patient with behavioural variant frontotemporal dementia. The three pre‐symptomatic C9orf72 carriers showed reduced synaptic density in the thalamus compared to controls, and there was an additional extensive synaptic loss in frontotemporal regions of the symptomatic patient. [11C]UCB‐J PET may facilitate early, pre‐symptomatic assessment, monitoring of disease progression and evaluation of new preventive treatment strategies for frontotemporal dementia.
Published: 2021
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10. Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment

Author: Kun Zhao, Qiang Zheng, Martin Dyrba, Timothy Rittman, Ang Li, Tongtong Che, Pindong Chen, Yuqing Sun, Xiaopeng Kang, Qiongling Li, Bing Liu, Yong Liu, Shuyu Li, and for the Alzheimer's Disease Neuroimaging Initiative
Subjects: mild cognitive impairment, progression, regional radiomics similarity network, subtypes, Science
Abstract: Abstract Individuals with mild cognitive impairment (MCI) of different subtypes show distinct alterations in network patterns. The first aim of this study is to identify the subtypes of MCI by employing a regional radiomics similarity network (R2SN). The second aim is to characterize the abnormality patterns associated with the clinical manifestations of each subtype. An individual‐level R2SN is constructed for N = 605 normal controls (NCs), N = 766 MCI patients, and N = 283 Alzheimer's disease (AD) patients. MCI patients’ R2SN profiles are clustered into two subtypes using nonnegative matrix factorization. The patterns of brain alterations, gene expression, and the risk of cognitive decline in each subtype are evaluated. MCI patients are clustered into “similar to the pattern of NCs” (N‐CI, N = 252) and “similar to the pattern of AD” (A‐CI, N = 514) subgroups. Significant differences are observed between the subtypes with respect to the following: 1) clinical measures; 2) multimodal neuroimaging; 3) the proportion of progression to dementia (61.54% for A‐CI and 21.77% for N‐CI) within three years; 4) enriched genes for potassium‐ion transport and synaptic transmission. Stratification into the two subtypes provides new insight for risk assessment and precise early intervention for MCI patients.
Published: 2022
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11. Asymmetrical atrophy of thalamic subnuclei in Alzheimer's disease and amyloid‐positive mild cognitive impairment is associated with key clinical features

Author: Audrey Low, Elijah Mak, Maura Malpetti, Leonidas Chouliaras, Nicolas Nicastro, Li Su, Negin Holland, Timothy Rittman, Patricia Vázquez Rodríguez, Luca Passamonti, W Richard Bevan‐Jones, PP Simon Jones, James B. Rowe, and John T. O'Brien
Subjects: Alzheimer's disease, Mild cognitive impairment, Cognitive aging, Thalamus, Magnetic resonance imaging, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract: Abstract Introduction Although widespread cortical asymmetries have been identified in Alzheimer's disease (AD), thalamic asymmetries and their relevance to clinical severity in AD remain unclear. Methods Lateralization indices were computed for individual thalamic subnuclei of 65 participants (33 healthy controls, 14 amyloid‐positive patients with mild cognitive impairment, and 18 patients with AD dementia). We compared lateralization indices across diagnostic groups and correlated them with clinical measures. Results Although overall asymmetry of the thalamus did not differ between groups, greater leftward lateralization of atrophy in the ventral nuclei was demonstrated in AD, compared with controls and amyloid‐positive mild cognitive impairment. Increased posterior ventrolateral and ventromedial nuclei asymmetry were associated with worse cognitive dysfunction, informant‐reported neuropsychiatric symptoms, and functional ability. Discussion Leftward ventral thalamic atrophy was associated with disease severity in AD. Our findings suggest the clinically relevant involvement of thalamic nuclei in the pathophysiology of AD.
Published: 2019
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12. Disease-related cortical thinning in presymptomatic granulin mutation carriers

Author: Sergi Borrego-Écija, Roser Sala-Llonch, John van Swieten, Barbara Borroni, Fermín Moreno, Mario Masellis, Carmela Tartaglia, Caroline Graff, Daniela Galimberti, Robert Laforce, Jr, James B Rowe, Elizabeth Finger, Rik Vandenberghe, Fabrizio Tagliavini, Alexandre de Mendonça, Isabel Santana, Matthis Synofzik, Simon Ducharme, Johannes Levin, Adrian Danek, Alex Gerhard, Markus Otto, Chris Butler, Giovanni Frisoni, Sandro Sorbi, Carolin Heller, Martina Bocchetta, David M Cash, Rhian S Convery, Katrina M Moore, Jonathan D Rohrer, Raquel Sanchez-Valle, Martin N. Rossor, Nick C. Fox, Ione O.C. Woollacott, Rachelle Shafei, Caroline Greaves, Mollie Neason, Rita Guerreiro, Jose Bras, David L. Thomas, Jennifer Nicholas, Simon Mead, Lieke Meeter, Jessica Panman, Janne Papma, Rick van Minkelen, Yolande Pijnenburg, Begoña Indakoetxea, Alazne Gabilondo, Mikel TaintaMD, Maria de Arriba, Ana Gorostidi, Miren Zulaica, Jorge Villanua, Zigor Diaz, Jaume Olives, Albert Lladó, Mircea Balasa, Anna Antonell, Nuria Bargallo, Enrico Premi, Maura Cosseddu, Stefano Gazzina, Alessandro Padovani, Roberto Gasparotti, Silvana Archetti, Sandra Black, Sara Mitchell, Ekaterina Rogaeva, Morris Freedman, Ron Keren, David Tang-Wai, Linn Öijerstedt, Christin Andersson, Vesna Jelic, Hakan Thonberg, Andrea Arighi, Chiara Fenoglio, Elio Scarpini MD, Giorgio Fumagalli, Thomas Cope, Carolyn Timberlake, Timothy Rittman, Christen Shoesmith, Robart Bartha, Rosa Rademakers, Carlo Wilke, Benjamin Bender, Rose Bruffaerts, Philip Vandamme, Mathieu Vandenbulcke, Carolina Maruta, Catarina B. Ferreira, Gabriel Miltenberger, Ana Verdelho, Sónia Afonso, Ricardo Taipa, Paola Caroppo, Giuseppe Di Fede, Giorgio Giaccone, Sara Prioni, Veronica Redaelli, Giacomina Rossi, Pietro Tiraboschi, Diana Duro, Maria Rosario Almeida, Miguel Castelo-Branco, Maria João Leitão, Miguel Tabuas-Pereira, Beatriz Santiago, Serge Gauthier, Pedro Rosa-Neto, Michele Veldsman, Toby Flanagan, Catharina Prix, Tobias Hoegen, Elisabeth Wlasich, Sandra Loosli, Sonja Schonecker, Elisa Semler, and Sarah Anderl-Straub
Subjects: Frontotemporal dementia, Cortical thickness, GRN, Presymptomatic, Genetic mutations, Computer applications to medicine. Medical informatics, R858-859.7, Neurology. Diseases of the nervous system, RC346-429
Abstract: Mutations in the granulin gene (GRN) cause familial frontotemporal dementia. Understanding the structural brain changes in presymptomatic GRN carriers would enforce the use of neuroimaging biomarkers for early diagnosis and monitoring. We studied 100 presymptomatic GRN mutation carriers and 94 noncarriers from the Genetic Frontotemporal dementia initiative (GENFI), with MRI structural images. We analyzed 3T MRI structural images using the FreeSurfer pipeline to calculate the whole brain cortical thickness (CTh) for each subject. We also perform a vertex-wise general linear model to assess differences between groups in the relationship between CTh and diverse covariables as gender, age, the estimated years to onset and education. We also explored differences according to TMEM106B genotype, a possible disease modifier. Whole brain CTh did not differ between carriers and noncarriers. Both groups showed age-related cortical thinning. The group-by-age interaction analysis showed that this age-related cortical thinning was significantly greater in GRN carriers in the left superior frontal cortex. TMEM106B did not significantly influence the age-related cortical thinning. Our results validate and expand previous findings suggesting an increased CTh loss associated with age and estimated proximity to symptoms onset in GRN carriers, even before the disease onset.
Published: 2021
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13. In vivo coupling of tau pathology and cortical thinning in Alzheimer's disease

Author: Elijah Mak, Richard A.I. Bethlehem, Rafael Romero‐Garcia, Simon Cervenka, Timothy Rittman, Silvy Gabel, Ajenthan Surendranathan, Richard W. Bevan‐Jones, Luca Passamonti, Patricia Vázquez Rodríguez, Li Su, Robert Arnold, Guy B. Williams, Young T. Hong, Tim D. Fryer, Franklin I. Aigbirhio, James B. Rowe, and John T. O'Brien
Subjects: Alzheimer's disease, Tau, Amyloid, Positron emission tomography, Atrophy, Cortical thickness, Neurology. Diseases of the nervous system, RC346-429, Geriatrics, RC952-954.6
Abstract: Abstract Introduction The deposition of neurofibrillary tangles in neurodegenerative disorders is associated with neuronal loss on autopsy; however, their in vivo associations with atrophy across the continuum of Alzheimer's disease (AD) remain unclear. Methods We estimated cortical thickness, tau ([18F]‐AV‐1451), and amyloid β (Aβ) status ([11C]‐PiB) in 47 subjects who were stratified into Aβ− (14 healthy controls and six mild cognitive impairment–Aβ−) and Aβ+ (14 mild cognitive impairment–Aβ+ and 13 AD) groups. Results Compared with the Aβ− group, tau was increased in widespread regions whereas cortical thinning was restricted to the temporal cortices. Increased tau binding was associated with cortical thinning in each Aβ group. Locally, regional tau was associated with temporoparietal atrophy. Discussion These findings position tau as a promising therapeutic target. Further studies are needed to elucidate the casual relationships between tau pathology and trajectories of atrophy in AD.
Published: 2018
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14. Test Your Memory (TYM) and Test Your Memory for Mild Cognitive Impairment (TYM-MCI): A Review and Update Including Results of Using the TYM Test in a General Neurology Clinic and Using a Telephone Version of the TYM Test

Author: Jeremy M. Brown, Julie Wiggins, Kate Dawson, Timothy Rittman, and James B. Rowe
Subjects: dementia, TYM, TYM-MCI, Alzheimer’s, Medicine (General), R5-920
Abstract: This paper summarises the current status of two novel short cognitive tests (SCT), known as Test Your Memory (TYM) and Test Your Memory for Mild Cognitive Impairment (TYM-MCI). The history of and recent research on the TYM and TYM-MCI are summarised in applications for Alzheimer’s and non-Alzheimer’s dementia and mild cognitive impairment. The TYM test can be used in a general neurology clinic and can help distinguish patients with Alzheimer’s disease (AD) from those with no neurological cause for their memory complaints. An adapted tele-TYM test administered by telephone to patients produces scores which correlate strongly with the clinic-administered Addenbrookes Cognitive Examination revised (ACE-R) test and can identify patients with dementia. Patients with AD decline on the TYM test at a rate of 3.6–4.1 points/year.
Published: 2019
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15. Multiple modes of impulsivity in Parkinson's disease.

Author: Cristina Nombela, Timothy Rittman, Trevor W Robbins, and James B Rowe
Subjects: Medicine, Science
Abstract: Cognitive problems are a major factor determining quality of life of patients with Parkinson's disease. These include deficits in inhibitory control, ranging from subclinical alterations in decision-making to severe impulse control disorders. Based on preclinical studies, we proposed that Parkinson's disease does not cause a unified disorder of inhibitory control, but rather a set of impulsivity factors with distinct psychological profiles, anatomy and pharmacology. We assessed a broad set of measures of the cognitive, behavioural and temperamental/trait aspects of impulsivity. Sixty adults, including 30 idiopathic Parkinson's disease patients (Hoehn and Yahr stage I-III) and 30 healthy controls, completed a neuropsychological battery, objective behavioural measures and self-report questionnaires. Univariate analyses of variance confirmed group differences in nine out of eleven metrics. We then used factor analysis (principal components method) to identify the structure of impulsivity in Parkinson's disease. Four principal factors were identified, consistent with four different mechanisms of impulsivity, explaining 60% of variance. The factors were related to (1) tests of response conflict, interference and self assessment of impulsive behaviours on the Barrett Impulsivity Scale, (2) tests of motor inhibitory control, and the self-report behavioural approach system, (3) time estimation and delay aversion, and (4) reflection in hypothetical scenarios including temporal discounting. The different test profiles of these four factors were consistent with human and comparative studies of the pharmacology and functional anatomy of impulsivity. Relationships between each factor and clinical and demographic features were examined by regression against factor loadings. Levodopa dose equivalent was associated only with factors (2) and (3). The results confirm that impulsivity is common in Parkinson's disease, even in the absence of impulse control disorders, and that it is not a unitary phenomenon. A better understanding of the structure of impulsivity in Parkinson's disease will support more evidence-based and effective strategies to treat impulsivity.
Published: 2014
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16. Synaptic Loss in Frontotemporal Dementia Revealed by [ <scp> 11 C </scp> ] <scp>UCB‐J Positron Emission Tomography</scp>

Author: Maura Malpetti, P. Simon Jones, Thomas E. Cope, Negin Holland, Michelle Naessens, Matthew A. Rouse, Timothy Rittman, George Savulich, David J. Whiteside, Duncan Street, Tim D. Fryer, Young T. Hong, Selena Milicevic Sephton, Franklin I. Aigbirhio, John T. O′Brien, and James B. Rowe
Subjects: Neurology, Neurology (clinical)
Published: 2022
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17. Pre‐diagnostic cognitive and functional impairment in multiple sporadic neurodegenerative diseases

Author: Nol, Swaddiwudhipong, David J, Whiteside, Frank H, Hezemans, Duncan, Street, James B, Rowe, and Timothy, Rittman
Subjects: Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Abstract: The pathophysiological processes of neurodegenerative diseases begin years before diagnosis. However, pre-diagnostic changes in cognition and physical function are poorly understood, especially in sporadic neurodegenerative disease.UK Biobank data were extracted. Cognitive and functional measures in individuals who subsequently developed Alzheimer's disease (AD), Parkinson disease, frontotemporal dementia, progressive supranuclear palsy, dementia with Lewy bodies, or multiple system atrophy were compared against individuals without neurodegenerative diagnoses. The same measures were regressed against time to diagnosis, after adjusting for the effects of age.There was evidence for pre-diagnostic cognitive impairment and decline with time, particularly in AD. Pre-diagnostic functional impairment and decline were observed in multiple diseases.The scale and longitudinal follow-up of UK Biobank participants provides evidence for cognitive and functional decline years before symptoms become obvious in multiple neurodegenerative diseases. Identifying pre-diagnostic functional and cognitive changes could improve selection for preventive and early disease-modifying treatment trials.
Published: 2022
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18. Longitudinal Synaptic Loss in Primary Tauopathies: An In Vivo [ <scp> 11 C </scp> ] <scp>UCB‐J</scp> Positron Emission Tomography Study

Author: Negin Holland, P. Simon Jones, George Savulich, Michelle Naessens, Maura Malpetti, David J. Whiteside, Duncan Street, Peter Swann, Young T. Hong, Tim D. Fryer, Timothy Rittman, Eoin Mulroy, Franklin I. Aigbirhio, Kailash P. Bhatia, John T. O'Brien, and James B. Rowe
Subjects: Neurology, Neurology (clinical)
Published: 2023
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19. Pre-diagnostic cognitive and functional impairment in multiple sporadic neurodegenerative diseases

Author: Nol Swaddiwudhipong, David J. Whiteside, Frank H. Hezemans, Duncan Street, James B. Rowe, Timothy Rittman, and Apollo - University of Cambridge Repository
Subjects: cognition, UK Biobank, pre-diagnostic, multiple system atrophy, Neurodegenerative Diseases, Parkinson Disease, progressive supranuclear palsy, Alzheimer's disease, frontotemporal dementia, neurodegenerative disease, physical function, Alzheimer Disease, sporadic, Humans, Cognitive Dysfunction, Supranuclear Palsy, Progressive, dementia with Lewy bodies, dementia
Abstract: Funder: Cambridge Centre for Parkinson‐plus, INTRODUCTION: The pathophysiological processes of neurodegenerative diseases begin years before diagnosis. However, pre-diagnostic changes in cognition and physical function are poorly understood, especially in sporadic neurodegenerative disease. METHODS: UK Biobank data were extracted. Cognitive and functional measures in individuals who subsequently developed Alzheimer's disease (AD), Parkinson disease, frontotemporal dementia, progressive supranuclear palsy, dementia with Lewy bodies, or multiple system atrophy were compared against individuals without neurodegenerative diagnoses. The same measures were regressed against time to diagnosis, after adjusting for the effects of age. RESULTS: There was evidence for pre-diagnostic cognitive impairment and decline with time, particularly in AD. Pre-diagnostic functional impairment and decline were observed in multiple diseases. DISCUSSION: The scale and longitudinal follow-up of UK Biobank participants provides evidence for cognitive and functional decline years before symptoms become obvious in multiple neurodegenerative diseases. Identifying pre-diagnostic functional and cognitive changes could improve selection for preventive and early disease-modifying treatment trials.
Published: 2023

20. Understanding ethnic diversity in open dementia neuroimaging datasets

Author: Nicholas Heng and Timothy Rittman
Abstract: IntroductionEthnic differences in dementia are increasingly recognised in epidemiological measures and diagnostic biomarkers. Nonetheless, ethnic diversity remains limited in many study populations Here we provide insights into ethnic diversity in open access neuroimaging dementia datasets.MethodsDatasets comprising dementia populations who underwent neuroimaging assessment with available data on ethnicity were included. Statistical analyses of sample and effect sizes were based on the Cochrane Handbook.Results14 databases were included, with 12 studies of healthy and MCI groups, and 11 of dementia groups. Combining all studies, the largest ethnic group was Caucasian (21,512 participants) with the next most common being Afro-Caribbean (1,960), followed by Asian (780). The smallest effect size detectable within the Caucasian group was 0.03, compared to Afro-Caribbean (0.1) and Asian (0.16).DiscussionOur findings quantify the lack of ethnic diversity in openly available neuroimaging dementia datasets. More representative data would facilitate the development and validation of neuroimaging biomarkers relevant across ethnicities.
Published: 2023
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21. A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

Author: Ione O.C. Woollacott, Cristina Polito, Philip Van Damme, Mathieu Vandenbulcke, Rose Bruffaerts, Diana Duro, Chiara Fenoglio, David M. Cash, Maria Rosário Almeida, Sonja Schönecker, C. Ferreira, Sónia Afonso, Matthis Synofzik, Sara Prioni, Marta Cañada, Mikel Tainta, Miguel Tábuas-Pereira, Christin Andersson, Caroline Graff, Miguel Castelo-Branco, Enrico Premi, Håkan Thonberg, Fabrizio Tagliavini, Rachelle Shafei, Benjamin Bender, Ana Gorostidi, Maria João Leitão, Jennifer M. Nicholas, Elise G.P. Dopper, Silvana Archetti, Esther E. Bron, Ana Verdelho, Ron Keren, Isabel Santana, Christen Shoesmith, Pietro Tiraboschi, Sergi Borrego-Écija, Michela Pievani, Sandro Sorbi, Rick van Minkelen, Hans-Otto Karnath, Albert Lladó, Caroline V. Greaves, Jaume Olives, Alessandro Padovani, Miren Zulaica, Giuliano Binetti, Martin Rosser, Pedro Rosa-Neto, Vesna Jelic, Alexander Gerhard, Rosa Rademakers, Sandra E. Black, Wiro J. Niessen, Tobias Hoegen, Rhian S Convery, Janne M. Papma, Maria Carmela Tartaglia, Emily Todd, Adrian Danek, Rita Guerreiro, Robart Bartha, Linn Öijerstedt, Giuseppe Di Fede, Sebastien Ourselin, Núria Bargalló, James B. Rowe, Christopher C Butler, Giorgio G. Fumagalli, Valentina Bessi, Alberto Benussi, Nick C. Fox, Beatriz Santiago, Ekaterina Rogaeva, Alazne Gabilondo, Giacomina Rossi, Mircea Balasa, David L. Thomas, Benedetta Nacmias, Veronica Redaelli, Anna Antonell, Vikram Venkatraghavan, Jonathan D. Rohrer, Jackie M. Poos, Yolande A.L. Pijnenburg, Lieke H.H. Meeter, Carlo Wilke, Sandra V. Loosli, Elio Scarpini, Tobias Langheinrich, Alina Díez, Elisa Semler, Elizabeth Finger, Begoña Indakoetxea, Jessica L. Panman, Carolyn Timberlake, Gemma Lombardi, Luisa Benussi, Morris Freedman, Barbara Borroni, Ricardo Taipa, Johannes Levin, Thomas E. Cope, Paul M. Thompson, Giorgio Giaccone, Valentina Cantoni, Arabella Bouzigues, Jose Bras, Serge Gauthier, Andrea Arighi, Stefan Klein, Fermin Moreno, Markus Otto, Georgia Peakman, Emma L. van der Ende, David F. Tang-Wai, Sarah Anderl-Straub, Jason D. Warren, Alexandre de Mendonça, Camilla Ferrari, Elisabeth Wlasich, Catharina Prix, Michele Veldsman, Raquel Sánchez-Valle, Sara Mitchell, Carolina Maruta, Robert Laforce, Paola Caroppo, Jorge Villanua, Imogen J Swift, Harro Seelaar, Henrik Zetterberg, Simon Mead, Simon Ducharme, Myriam Barandiaran, Katrina M. Moore, John C. van Swieten, Gabriel Miltenberger, Mario Masellis, Timothy Rittman, Lize C. Jiskoot, Daniela Galimberti, Rik Vandenberghe, Carolin Heller, Stefano Gazzina, Aitana Sogorb-Esteve, Roberto Gasparotti, Martina Bocchetta, Neurology, Amsterdam Neuroscience - Neurodegeneration, Repositório da Universidade de Lisboa, Radiology & Nuclear Medicine, and Neurosurgery
Subjects: Oncology, medicine.medical_specialty, Medizin, tau Proteins, Disease, medicine.disease_cause, frontotemporal dementia, biomarker, disease progression model, event-based modelling, neurofilament light chain, Biomarkers, C9orf72 Protein, Complement C1q, Cross-Sectional Studies, Disease Progression, Glial Fibrillary Acidic Protein, Humans, Longitudinal Studies, Mutation, Frontotemporal Dementia, diagnosis [Frontotemporal Dementia], Settore BIO/13 - Biologia Applicata, C9orf72, Internal medicine, Medicine, ddc:610, genetics [C9orf72 Protein], genetics [Frontotemporal Dementia], business.industry, medicine.disease, Astrogliosis, genetics [tau Proteins], Cohort, Biomarker (medicine), Neurology (clinical), Sample collection, business, Frontotemporal dementia
Abstract: © The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/ by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com, Several CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions., This study was supported in the Netherlands by two Memorabel grants from Deltaplan Dementie (The Netherlands Organisation for Health Research and Development and Alzheimer Nederland; grant numbers 733050813,733050103 and 733050513), the Bluefield Project to Cure Frontotemporal Dementia, the Dioraphte foundation (grant number 1402 1300), the European Joint Programme—Neurodegenerative Disease Research and the Netherlands Organisation for Health Research and Development (PreFrontALS: 733051042, RiMod-FTD: 733051024); V.V. and S.K. have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 666992 (EuroPOND). E.B. was supported by the Hartstichting (PPP Allowance, 2018B011); in Belgium by the Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie; in the UK by the MRC UK GENFI grant (MR/M023664/1); J.D.R. is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH); I.J.S. is supported by the Alzheimer’s Association; J.B.R. is supported by the Wellcome Trust (103838); in Spain by the Fundació Marató de TV3 (20143810 to R.S.V.); in Germany by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198) and by grant 779357 ‘Solve-RD’ from the Horizon 2020 Research and Innovation Programme (to MS); in Sweden by grants from the Swedish FTD Initiative funded by the Schörling Foundation, grants from JPND PreFrontALS Swedish Research Council (VR) 529–2014-7504, Swedish Research Council (VR) 2015–02926, Swedish Research Council (VR) 2018–02754, Swedish Brain Foundation, Swedish Alzheimer Foundation, Stockholm County Council ALF, Swedish Demensfonden, Stohnes foundation, Gamla Tjänarinnor, Karolinska Institutet Doctoral Funding and StratNeuro. H.Z. is a Wallenberg Scholar.
Published: 2022
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22. Incidence of syndromes associated with Frontotemporal Lobar Degeneration (S19.004)

Author: Giancarlo Logroscino, Marco Piccininni, Caroline Graff, Orla Hardiman, Albert Ludolph, Fermin Moreno, Markus Otto, Anne Remes, James Rowe, Harro Seelaar, Eino Solje, Elka Stefanova, Latchezar Traykov, Vesna Jelic, Melissa Thaeri Rydell, Niall Pender, Sarah Anderl-Straub, Myriam Barandiaran, Alazne Gabilondo, Johanna Kruger, Alexander Murley, Timothy Rittman, Emma L. van der Ende, John Van Swieten, Paivi Hartikainen, Gorana Mandic Stojmenovic, Shima Meherabian, Luisa Benussi, Antonella Alberici, Maria Teresa Dell’Abate, Chiara Zecca, and Barbara Borroni
Published: 2023
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23. Functional Networks: A New Window Into Alzheimer’s Disease Subtypes

Author: Timothy Rittman
Subjects: Biological Psychiatry
Published: 2023
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24. Automated brain image analysis in dementia using artificial intelligence: a roadmap for the development of clinical tools

Author: Ashwin V Venkataraman, Charles Marshall, and Timothy Rittman
Abstract: Artificial intelligence (AI) and machine learning (ML) developments applied to neuroimaging in dementia are rapidly advancing. This paper provides a roadmap for clinically meaningful translation of this to healthcare systems. Firstly we discuss the current state of neuroimaging in dementia. Secondly we discuss the potential benefits of AI/ML applied to neuroimaging. Thirdly we discuss the pressing need to translate these advances in a clinically meaningful way for improved diagnosis, prognosis and stratification. Fourthly we discuss the translational barriers, regulatory requirements, and finally the potential solutions and roadmap for the development of clinical tools using AI/ML technologies in brain imaging to memory clinics.
Published: 2023
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25. The Deep Dementia Phenotyping (DEMON) Network: A global platform for innovation using data science and artificial intelligence

Author: Janice M Ranson, Ahmad Al Khleifat, Donald M Lyall, Danielle Newby, Laura M Winchester, Petroula Proitsi, Michele Veldsman, Timothy Rittman, Sarah Marzi, Zhi Yao, Nathan Skene, Conceição Bettencourt, Andrey Kormilitzin, Isabelle F Foote, Cecilia Golborne, Ilianna Lourida, Magda Bucholc, Eugene Tang, Neil P Oxtoby, Peter Bagshaw, Zuzana Walker, Richard Everson, Clive G Ballard, Cornelia M van Duijn, Kenneth M Langa, Malcolm MacLeod, Kenneth Rockwood, and David J Llewellyn
Subjects: Psychiatry and Mental health, Cellular and Molecular Neuroscience, Biomedical Research, Developmental Neuroscience, Alzheimer Disease, Artificial Intelligence, Epidemiology, Health Policy, Data Science, Humans, Neurology (clinical), Geriatrics and Gerontology
Abstract: The increasing availability of large high-dimensional data from experimental medicine, population-based and clinical cohorts, clinical trials, and electronic health records has the potential to transform dementia research. Our ability to make best use of this rich data will depend on utilisation of advanced machine learning and artificial intelligence (AI) techniques and collaboration across disciplinary and geographic boundaries.The Deep Dementia Phenotyping (DEMON) Network launched in 2019Membership on 4th February 2022 comprised 1,321 individuals from 61 countries across 6 continents (see Figure). Areas of expertise include dementia research (904; 68%), data science (692; 52%), clinical practice (244; 18%), industry (162; 12%), and regulation (26; 2%). Individual membership is free, and regular knowledge transfer events are provided including a monthly seminar series, talks and workshops, training, networking, and early career development. Each Working Group meets monthly, with multiple grants, reviews, and original research articles in progress. Eight state of the science position papers are in preparation, resulting from a Symposium held in April 2021. In January 2022, 110 early career researchers participated in the Network's flagship event 'NEUROHACK', a 4-day competitive global hackathon, with pilot grants awarded to those generating the most innovative solutions.The DEMON Network is a rapidly growing global platform for innovation that is supporting the global dementia research community to collaborate. Find out more at demondementia.com.
Published: 2022
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26. Ocular Biomarkers for Alzheimer Disease Dementia: An Umbrella Review of Systematic Reviews and Meta-analyses

Author: Eliana Costanzo, Imre Lengyel, Mariacristina Parravano, Ilaria Biagini, Michele Veldsman, AmanPreet Badhwar, Matthew Betts, Antonio Cherubini, David J. Llewellyn, Ilianna Lourida, Tom MacGillivray, Timothy Rittman, Stefano Tamburin, Xin You Tai, and Gianni Virgili
Subjects: Ophthalmology, Cross-Sectional Studies, diagnosis [Cognitive Dysfunction], accuracy, diagnosis [Alzheimer Disease], Humans, ddc:610, ocular biomarkers, Alzheimer disease, complications [Cognitive Dysfunction], Retina, Biomarkers, early diagnosis
Abstract: ImportanceSeveral ocular biomarkers have been proposed for the early detection of Alzheimer disease (AD) and mild cognitive impairment (MCI), particularly fundus photography, optical coherence tomography (OCT), and OCT angiography (OCTA).ObjectiveTo perform an umbrella review of systematic reviews to assess the diagnostic accuracy of ocular biomarkers for early diagnosis of Alzheimer disease.Data SourcesMEDLINE, Embase, and PsycINFO were searched from January 2000 to November 2021. The references of included reviews were also searched.Study SelectionSystematic reviews investigating the diagnostic accuracy of ocular biomarkers to detect AD and MCI, in secondary care or memory clinics, against established clinical criteria or clinical judgment.Data Extraction and SynthesisThe Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline checklist was followed and the Risk Of Bias in Systematic reviews tool was used to assess review quality.Main Outcomes and MeasuresThe prespecified outcome was the accuracy of ocular biomarkers for diagnosing AD and MCI. The area under the curve (AUC) was derived from standardized mean difference.ResultsFrom the 591 titles, 14 systematic reviews were included (median [range] number of studies in each review, 14 [5-126]). Only 4 reviews were at low risk of bias on all Risk of Bias in Systematic Reviews domains. The imaging-derived parameters with the most evidence for detecting AD compared with healthy controls were OCT peripapillary retinal nerve fiber layer thickness (38 studies including 1883 patients with AD and 2510 controls; AUC = 0.70; 95% CI, 0.53-0.79); OCTA foveal avascular zone (5 studies including 177 patients with AD and 371 controls; AUC = 0.73; 95% CI, 0.50-0.89); and saccadic eye movements prosaccade latency (30 studies including 651 patients with AD/MCI and 771 controls; AUC = 0.64; 95% CI, 0.58-0.69). Antisaccade error was investigated in fewer studies (12 studies including 424 patients with AD/MCI and 382 controls) and yielded the best accuracy (AUC = 0.79; 95% CI, 0.70-0.88).Conclusions and RelevanceThis umbrella review has highlighted limitations in design and reporting of the existing research on ocular biomarkers for diagnosing AD. Parameters with the best evidence showed poor to moderate diagnostic accuracy in cross-sectional studies. Future longitudinal studies should investigate whether changes in OCT and OCTA measurements over time can yield accurate predictions of AD onset.
Published: 2022
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27. Apathy in presymptomatic genetic frontotemporal dementia predicts cognitive decline and is driven by structural brain changes

Author: Matthis Synofzik, Alexandre de Mendonça, Giovanni B. Frisoni, Maura Malpetti, Fermin Moreno, Christopher C Butler, Roberta Ghidoni, Daniela Galimberti, Rik Vandenberghe, Elizabeth Finger, Isabel Santana, Alexander Gerhard, Georgia Peakman, Emily Todd, Carolin Heller, Jonathan D. Rohrer, Katrina M. Moore, Kamen A. Tsvetanov, Rhian S Convery, P. Simon Jones, Johannes Levin, James B. Rowe, Caroline Graff, Markus Otto, Barbara Borroni, Raquel Sánchez-Valle, Sandro Sorbi, Fabrizio Tagliavini, John C. van Swieten, Maria Carmela Tartaglia, Rogier A. Kievit, Simon Ducharme, Robert Laforce, Mario Masellis, Timothy Rittman, Adrian Danek, David M. Cash, Martina Bocchetta, Apollo - University of Cambridge Repository, Repositório da Universidade de Lisboa, Neurology, Malpetti, Maura [0000-0001-8923-9656], Jones, Simon [0000-0001-9695-0702], Tsvetanov, Kamen A. [0000-0002-3178-6363], Rittman, Timothy [0000-0003-1063-6937], and Rowe, James [0000-0001-7216-8679]
Subjects: Male, longitudinal design, SYMPTOMS, pathology [Cognitive Dysfunction], Epidemiology, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], Medizin, apathy, DISEASE, 0302 clinical medicine, pathology [Brain], pathology [Gray Matter], C9orf72, presymptomatic carriers, cognitive decline, genetic frontotemporal dementia, MRI, Apathy, Gray Matter, Cognitive decline, genetics [Frontotemporal Dementia], pathology [Atrophy], 0303 health sciences, Health Policy, Brain, Cognition, IMPAIRMENT, Middle Aged, DEPRESSION, Magnetic Resonance Imaging, Psychiatry and Mental health, Frontotemporal Dementia, Female, IMPULSIVITY, medicine.symptom, Life Sciences & Biomedicine, Clinical psychology, Frontotemporal dementia, Clinical Neurology, FEATURED ARTICLE, Prodromal Symptoms, PHENOTYPES, genetics [Mutation], Impulsivity, 03 medical and health sciences, Cellular and Molecular Neuroscience, All institutes and research themes of the Radboud University Medical Center, Atrophy, SDG 3 - Good Health and Well-being, Developmental Neuroscience, mental disorders, medicine, Humans, Dementia, Cognitive Dysfunction, ddc:610, BEHAVIORAL-VARIANT, 030304 developmental biology, Science & Technology, EXECUTIVE FUNCTION, business.industry, DIGIT SYMBOL, 1103 Clinical Sciences, medicine.disease, DYSFUNCTION, Geriatrics, Mutation, FEATURED ARTICLES, Neurosciences & Neurology, Neurology (clinical), Geriatrics and Gerontology, 1109 Neurosciences, business, 030217 neurology & neurosurgery
Abstract: © 2020 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited., Introduction: Apathy adversely affects prognosis and survival of patients with frontotemporal dementia (FTD). We test whether apathy develops in presymptomatic genetic FTD, and is associated with cognitive decline and brain atrophy. Methods: Presymptomatic carriers of MAPT, GRN or C9orf72 mutations (N = 304), and relatives without mutations (N = 296) underwent clinical assessments and MRI at baseline, and annually for 2 years. Longitudinal changes in apathy, cognition, gray matter volumes, and their relationships were analyzed with latent growth curve modeling. Results: Apathy severity increased over time in presymptomatic carriers, but not in non-carriers. In presymptomatic carriers, baseline apathy predicted cognitive decline over two years, but not vice versa. Apathy progression was associated with baseline low gray matter volume in frontal and cingulate regions. Discussion: Apathy is an early marker of FTD-related changes and predicts a subsequent subclinical deterioration of cognition before dementia onset. Apathy may be a modifiable factor in those at risk of FTD., This work is co‐funded by the UK Medical Research Council (MR/M023664/1), the Italian Ministry of Health and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant and the Bluefield Project, as well as a JPND grant “GENFI‐prox” (by DLR/BMBF to MS, joined with JDR, JvS, MO, BB and CG). MM is supported by the Cambridge Trust & Sidney Sussex College Scholarship. PSJ is supported by the Cambridge Centre for Parkinson Plus. KAT is supported by the British Academy Postdoctoral Fellowship (KAT: PF160048) and Guarantors of Brain (KAT: 101149). TR is supported by the Cambridge Centre for Parkinson Plus and Cambridge Biomedical Resource Centre. RAK is supported by Medical Research Council (RAK: SUAG/047/G101400). JBR reports grants from the NIHR Cambridge Biomedical research centre, Wellcome Trust (103838), and Medical Research Council (SUAG051/G101400; MR/T033371/1); personal fees from Asceneuron, WAVE, Astex, and Biogen; and grants from Janssen, AZ Medimmune, and Eli Lilly, outside the submitted work. JDR is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). MB is supported by a Fellowship award from the Alzheimer's Society, UK (AS‐JF‐19a‐004‐517), and by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society, and Alzheimer's Research UK.
Published: 2020
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28. Brain charts for the human lifespan

Author: Armin Raznahan, Eric Courchesne, Andrea Parolin Jackowski, Kamen A. Tsvetanov, Cameron T. Ellis, R.C. Gur, Bin Bae J, Park Mtm, Pedro A. Valdes-Sosa, Simon N. Vandekar, Jacob W. Vogel, Juan Zhou, Machteld Marcelis, Kiho Im, Patricia Ellen Grant, Minhui Ouyang, Blesa Cabez M, Michael V. Lombardo, Sarah E. Morgan, James P. Boardman, Adamson C, Calhoun Vd, Delarue M, James H. Cole, Pichet Binette A, Roberto Toro, David H. Rowitch, Nynke A. Groenewold, Kevin M. Anderson, David T.W. Jones, Michael Schöll, Wang Ys, Aiden Corvin, R.E. Gur, Damien A. Fair, Gareth Ball, Herma Lina Schaare, Andrew Zalesky, Evdokia Anagnostou, Michael J. Meaney, Taki Y, Gareth J. Sullivan, Warrier, Petra E. Vértes, Chixiang Chen, Lisa T. Eyler, Wei Liao, Tomáš Paus, Jeremy A. Elman, Phillip McGuire, Hisham Ziauddeen, William S. Kremen, Etienne Vachon-Presseau, E.T. Bullmore, Christophe Tzourio, White, Hammill Cf, Mothersill D, Richard N. Henson, Jiang Qiu, Duncan E. Astle, Fabrice Crivello, Paul C. Fletcher, Chertavian C, Kim K, Jennifer Crosbie, Russell Schachar, Gabriel A. Devenyi, Manfred G. Kitzbichler, Tianye Jia, Trey Hedden, Sang Jae Lee, Ross D. Markello, Silke Kern, Ian M. Goodyer, Keith A. Johnson, Frauke Beyer, Bernard Mazoyer, A. Heinz, Sylvane Desrivières, Rosenberg, Gary Donohoe, Ong Mq, Alexander D. Edwards, Dan J. Stein, Nenad Medic, Zuo Xn, Travis T. Mallard, Peter Fonagy, Lindsay W. Victoria, Ingmar Skoog, Avram J. Holmes, Jason P. Lerch, Jed T. Elison, Jianfu Li, John H. Gilmore, Rosemary Holt, Caitlin K. Rollins, Carol E. Franz, Pedro Mario Pan, Saashi A Bedford, Yang N, Jonathan C Ipser, Richard A. I. Bethlehem, Tuulari Jj, Stolicyn A, Hua Huang, Bratislav Misic, Conor Liston, Ayub M, Lisa Ronan, Yeo Bt, Sophie Adler, Charles J. Lynch, Faith M. Gunning, Konrad Wagstyl, M. Mallar Chakravarty, John Suckling, Theodore D. Satterthwaite, Bharath Holla, Yap Seng Chong, Jinglei Lv, Jakob Seidlitz, Niall J Bourke, Xinlei Qian, Simon Baron-Cohen, Cynthia M. Ortinau, Deirel Paz Linares, Thyreau B, René S. Kahn, Aaron P. Schultz, Vanessa Cropley, Eric Westman, Mitchell Valdés-Sosa, Rik Ossenkoppele, André Zugman, Hasse Karlsson, Sylvia Villeneuve, Katja Heuer, Di Biase Ma, Margaret L. Westwater, Sofie L. Valk, David J. Sharp, Brigitte Landeau, Matthew Borzage, Kirsten A. Donald, Timothy Rittman, Richard Beare, Giovanni Abrahão Salum, Gunter Schumann, Ryuta Kawashima, Romero-Garcia R, John Blangero, Yun Hj, Russel T. Shinohara, Nicolas Crossley, Simon K. Warfield, Karen Pierce, George S. Alexopoulos, Katharine Dunlop, David C. Glahn, Francois Lalonde, Anqi Qiu, Lana Vasung, Gaël Chételat, Lídice Galán-García, Clifford R. Jack, Reisa A. Sperling, Anna Zettergren, Elizabeth Kelley, Arno Villringer, Andrea Mechelli, Benegal, Aaron Alexander-Bloch, Nicholas B. Turk-Browne, van Amelsvoort T, John D. Lewis, Heather C. Whalley, A. V. Witte, Zdenka Pausova, Joel T. Nigg, Heather J. Zar, Raymond J. Dolan, Christopher D. Smyser, Jay N. Giedd, Lena Palaniyappan, Ali Gholipour, Areces-Gonzalez A, Peter B. Jones, Jacqueline Hoare, Oskar Hansson, Linnea Karlsson, C Pantelis, Paly L, Bonnie Auyeung, Jorge Bosch-Bayard, Bethlehem, Richard [0000-0002-0714-0685], White, Simon [0000-0001-8642-7037], Astle, Duncan [0000-0002-7042-5392], Baron-Cohen, Simon [0000-0001-9217-2544], Henson, Rik [0000-0002-0712-2639], Jones, Peter [0000-0002-0387-880X], Kitzbichler, Manfred [0000-0002-4494-0753], Rittman, Timothy [0000-0003-1063-6937], Rowitch, David [0000-0002-0079-0060], Tsvetanov, Kamen A. [0000-0002-3178-6363], Westwater-Wozniak, Margaret [0000-0002-2918-0979], Ziauddeen, Hisham [0000-0003-4044-1719], Apollo - University of Cambridge Repository, British Academy, Autism Research Trust, National Institute of Mental Health (US), UK Research and Innovation, Medical Research Council (UK), National Institute for Health and Care Research (US), Wellcome Trust, University of Cambridge, Cambridge Biomedical Research Centre, University of Cambridge [UK] (CAM), University of Pennsylvania, Yale University [New Haven], Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie et imagerie des troubles neurologiques (PhIND), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Child and Adolescent Psychiatry Department [AP- HP Hôpital Robert Debré], AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Département de Neuroscience - Department of Neuroscience, Centre de Recherche Interdisciplinaire / Center for Research and Interdisciplinarity [Paris, France] (CRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Med Staf Spec Psychiatrie (9), Neurology, Amsterdam Neuroscience - Neurodegeneration, 3R-BRAIN, AIBL, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Repository Without Borders Investigators, CALM Team, Cam-CAN, CCNP, COBRE, cVEDA, ENIGMA Developmental Brain Age Working Group, Developing Human Connectome Project, FinnBrain, Harvard Aging Brain Study, IMAGEN, KNE96, The Mayo Clinic Study of Aging, NSPN, POND, The PREVENT-AD Research Group, VETSA, [Bethlehem, R. A. I.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Auyeung, B.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Baron-Cohen, S.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Bedford, S. A.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Holt, R.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Lombardo, M. V.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Bethlehem, R. A. I.] Univ Cambridge, Dept Psychiat, Brain Mapping Unit, Cambridge, England, [Kitzbichler, M. G.] Univ Cambridge, Dept Psychiat, Brain Mapping Unit, Cambridge, England, [Seidlitz, J.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Vogel, J. W.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Gur, R. E.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Gur, R. C.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Jackowski, A. P.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Satterthwaite, T. D.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Alexander-Bloch, A. F.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Seidlitz, J.] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA, [Alexander-Bloch, A. F.] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA, [Seidlitz, J.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Chertavian, C.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Gur, R. E.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Gur, R. C.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Alexander-Bloch, A. F.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [White, S. R.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Goodyer, I. M.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Henson, R. N.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Jones, P. B.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Kitzbichler, M. G.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Medic, N.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Morgan, S. E.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Romero-Garcia, R.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Ronan, L.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Suckling, J.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Vertes, P. E.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Warrier, V.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Westwater, M. L.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Ziauddeen, H.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Bullmore, E. T.] Univ Cambridge, Dept Psychiat, Cambridge, England, [White, S. R.] Univ Cambridge, MRC Biostat Unit, Cambridge, England, [Vogel, J. W.] Univ Penn, Lifespan Informat & Neuroimaging Ctr, Philadelphia, PA 19104 USA, [Satterthwaite, T. D.] Univ Penn, Lifespan Informat & Neuroimaging Ctr, Philadelphia, PA 19104 USA, [Anderson, K. M.] Yale Univ, Dept Psychol, New Haven, CT USA, [Ellis, C. T.] Yale Univ, Dept Psychol, New Haven, CT USA, [Turk-Browne, N. B.] Yale Univ, Dept Psychol, New Haven, CT USA, [Adamson, C.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Ball, G.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Beare, R.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Jackowski, A. P.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Adamson, C.] Monash Univ, Dept Med, Melbourne, Vic, Australia, [Beare, R.] Monash Univ, Dept Med, Melbourne, Vic, Australia, [Adler, S.] UCL Great Ormond St Inst Child Hlth, London, England, [Alexopoulos, G. S.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Anagnostou, E.] Univ Toronto, Dept Pediat, Toronto, ON, Canada, [Anagnostou, E.] Holland Bloorview Kids Rehabil Hosp, Toronto, ON, Canada, [Pierce, K.] Holland Bloorview Kids Rehabil Hosp, Toronto, ON, Canada, [Areces-Gonzalez, A.] Univ Elect Sci & Technol China, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Paz-Linares, D.] Univ Elect Sci & Technol China, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Areces-Gonzalez, A.] Univ Pinar del Rio Hermanos Saiz Montes de Oca, Pinar Del Rio, Cuba, [Astle, D. E.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Henson, R. N.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Whalley, H. C.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Auyeung, B.] Univ Edinburgh, Sch Philosophy Psychol & Language Sci, Dept Psychol, Edinburgh, Midlothian, Scotland, [Pausova, Z.] Univ Edinburgh, Sch Philosophy Psychol & Language Sci, Dept Psychol, Edinburgh, Midlothian, Scotland, [Ayub, M.] Queens Univ, Dept Psychiat, Ctr Neurosci Studies, Kingston, ON, Canada, [Ayub, M.] UCL, Mental Hlth Neurosci Res Dept, Div Psychiat, London, England, [Bae, J.] Seoul Natl Univ, Bundang Hosp, Dept Neuropsychiat, Seongnam, South Korea, [Ball, G.] Univ Melbourne, Dept Paediat, Melbourne, Vic, Australia, [Baron-Cohen, S.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge Lifetime Asperger Syndrome Serv CLASS, Cambridge, England, [Benegal, V.] Natl Inst Mental Hlth & Neurosci NIMHANS, Ctr Addict Med, Bengaluru, India, [Beyer, F.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Villringer, A.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Witte, A. V.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Blangero, J.] Univ Texas Rio Grande Valley, South Texas Diabet & Obes Inst, Dept Human Genet, Edinburg, TX USA, [Blesa Cabez, M.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Boardman, J. P.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Sullivan, G.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Borzage, M.] Univ Southern Calif, Childrens Hosp Los Angeles, Keck Sch Med, Fetal & Neonatal Inst,Div Neonatol,Dept Pediat, Los Angeles, CA 90007 USA, [Bosch-Bayard, J. F.] Montreal Neurol Inst, Ludmer Ctr Neuroinformat & Mental Hlth, McGill Ctr Integrat Neurosci, Montreal, PQ, Canada, [Bosch-Bayard, J. F.] McGill Univ, Montreal, PQ, Canada, [Chakravarty, M. M.] McGill Univ, Montreal, PQ, Canada, [Bourke, N.] Imperial Coll London, Dept Brain Sci, London, England, [Sharp, D.] Imperial Coll London, Dept Brain Sci, London, England, [Alexander-Bloch, A. F.] Imperial Coll London, Dept Brain Sci, London, England, [Bourke, N.] Dementia Res Inst, Care Res & Technol Ctr, London, England, [Calhoun, V. D.] Georgia State Univ, Triinst Ctr Translat Res Neuroimaging & Data Sci, Georgia Inst Technol, Atlanta, GA 30303 USA, [Calhoun, V. D.] Emory Univ, Atlanta, GA 30322 USA, [Chakravarty, M. M.] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Comp Brain Anat CoBrA Lab, Montreal, PQ, Canada, [Chen, C.] Univ Penn, Penn Stat Imaging & Visualizat Ctr, Dept Biostat Epidemiol & Informat, Perelman Sch Med, Philadelphia, PA 19104 USA, [Shinohara, R. T.] Univ Penn, Penn Stat Imaging & Visualizat Ctr, Dept Biostat Epidemiol & Informat, Perelman Sch Med, Philadelphia, PA 19104 USA, [Chetelat, G.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Delarue, M.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Landeau, B.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Paly, L.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Chong, Y. S.] Agcy Sci Technol & Res, Singapore Inst Clin Sci, Singapore, Singapore, [Chong, Y. S.] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Obstet & Gynaecol, Singapore, Singapore, [Cole, J. H.] UCL, Ctr Med Image Comp CMIC, London, England, [Cole, J. H.] UCL, Dementia Res Ctr DRC, London, England, [Corvin, A.] Trinity Coll Dublin, Dept Psychiat, Dublin, Ireland, [Costantino, M.] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Verdun, PQ, Canada, [Costantino, M.] McGill Univ, Undergrad Program Neurosci, Montreal, PQ, Canada, [Courchesne, E.] Univ Calif San Diego, Dept Neurosci, San Diego, CA 92103 USA, [Courchesne, E.] Univ Calif San Diego, Autism Ctr Excellence, San Diego, CA 92103 USA, [Crivello, F.] Univ Bordeaux, Inst Neurodegenerat Disorders, CNRS UMR5293, CEA, Bordeaux, France, [Mazoyer, B.] Univ Bordeaux, Inst Neurodegenerat Disorders, CNRS UMR5293, CEA, Bordeaux, France, [Cropley, V. L.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Di Biase, M. A.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Lv, J.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Zalesky, A.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Hammill, C. F.] Hosp Sick Children, Toronto, ON, Canada, [Schachar, R. J.] Hosp Sick Children, Toronto, ON, Canada, [Crossley, N.] Pontificia Univ Catolica Chile, Sch Med, Dept Psychiat, Santiago, Chile, [Crossley, N.] Kings Coll London, Dept Psychosis Studies, Inst Psychiat Psychol & Neurosci, London, England, [McGuire, P.] Kings Coll London, Dept Psychosis Studies, Inst Psychiat Psychol & Neurosci, London, England, [Crossley, N.] Inst Milenio Intelligent Healthcare Engn, Santiago, Chile, [Delorme, R.] Robert Debre Univ Hosp, AP HP, Child & Adolescent Psychiat Dept, Paris, France, [Delorme, R.] Inst Pasteur, Human Genet & Cognit Funct, Paris, France, [Desrivieres, S.] Kings Coll London, Inst Psychiat Psychol & Neurosci, Social Genet & Dev Psychiat Ctr, London, England, [Devenyi, G. A.] Douglas Mental Hlth Univ Inst, McGill Dept Psychiat, Cerebral Imaging Ctr, Montreal, PQ, Canada, [Devenyi, G. A.] McGill Univ, Dept Psychiat, Montreal, PQ, Canada, [Di Biase, M. A.] Harvard Med Sch, Brigham & Womens Hosp, Dept Psychiat, Boston, MA 02115 USA, [Dolan, R.] UCL, Max Planck UCL Ctr Computat Psychiat & Ageing Res, London, England, [Dolan, R.] Wellcome Ctr Human Neuroimaging, London, England, [Wagstyl, K.] Wellcome Ctr Human Neuroimaging, London, England, [Donald, K. A.] Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Div Dev Paediat, Cape Town, South Africa, [Donald, K. A.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Groenewold, N. A.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Donohoe, G.] Natl Univ Ireland Galway, Sch Psychol, Ctr Neuroimaging Cognit & Genom NICOG, Galway, Ireland, [Dunlop, K.] Weill Cornell Med, Dept Psychiat, Weil Family Brain & Mind Res Inst, New York, NY USA, [Lynch, C.] Weill Cornell Med, Dept Psychiat, Weil Family Brain & Mind Res Inst, New York, NY USA, [Edwards, A. D.] Kings Coll London, Ctr Dev Brain, London, England, [Edwards, A. D.] Evelina London Childrens Hosp, London, England, [Edwards, A. D.] MRC Ctr Neurodev Disorders, London, England, [Elison, J. T.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Fair, D. A.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Feczko, E.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Ellis, C. T.] Haskins Labs Inc, New Haven, CT USA, [Elman, J. A.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Franz, C. E.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Kremen, W. S.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Eyler, L.] VA San Diego Healthcare, Desert Pacific Mental Illness Res Educ & Clin Ctr, San Diego, CA USA, [Eyler, L.] Univ Calif San Diego, Dept Psychiat, Los Angeles, CA USA, [Fletcher, P. C.] Univ Cambridge, Dept Psychiat, Cambridge Biomed Campus, Cambridge, England, [Fletcher, P. C.] Wellcome Trust MRC Inst Metab Sci, Cambridge Biomed Campus, Cambridge, England, [Fletcher, P. C.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Jones, P. B.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Suckling, J.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Ziauddeen, H.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Fonagy, P.] UCL, Dept Clin Educ & Hlth Psychol, London, England, [Fonagy, P.] Anna Freud Natl Ctr Children & Families, London, England, [Galan-Garcia, L.] Cuban Ctr Neurosci, Havana, Cuba, [Valdes-Sosa, M. J.] Cuban Ctr Neurosci, Havana, Cuba, [Gholipour, A.] Boston Childrens Hosp, Computat Radiol Lab, Boston, MA USA, [Warfield, S. K.] Boston Childrens Hosp, Computat Radiol Lab, Boston, MA USA, [Giedd, J.] Univ Calif San Diego, Dept Child & Adolescent Psychiat, San Diego, CA 92103 USA, [Giedd, J.] Univ Calif San Diego, Dept Psychiat, San Diego, CA 92103 USA, [Gilmore, J. H.] Univ N Carolina, Dept Psychiat, Chapel Hill, NC 27515 USA, [Glahn, D. C.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Im, K.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Mathias, S. R.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Rodrigue, A.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Glahn, D. C.] Harvard Med Sch, Boston, MA 02115 USA, [Im, K.] Harvard Med Sch, Boston, MA 02115 USA, [Johnson, K. A.] Harvard Med Sch, Boston, MA 02115 USA, [Mathias, S. R.] Harvard Med Sch, Boston, MA 02115 USA, [Rodrigue, A.] Harvard Med Sch, Boston, MA 02115 USA, [Schultz, A. P.] Harvard Med Sch, Boston, MA 02115 USA, [Sperling, R. A.] Harvard Med Sch, Boston, MA 02115 USA, [Grant, P. E.] Harvard Med Sch, Fetal Neonatal Neuroimaging & Dev Sci Ctr, Boston Childrens Hosp, Div Newborn Med & Neuroradiol, Boston, MA 02115 USA, [Groenewold, N. A.] Univ Cape Town, SA MRC Unit Child & Adolescent Hlth, Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Cape Town, South Africa, [Zar, H. J.] Univ Cape Town, SA MRC Unit Child & Adolescent Hlth, Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Cape Town, South Africa, [Gunning, F. M.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Victoria, L. W.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Hammill, C. F.] Mouse Imaging Ctr, Toronto, ON, Canada, [Hansson, O.] Lund Univ, Dept Clin Sci Malmo, Clin Memory Res Unit, Malmo, Sweden, [Hansson, O.] Skane Univ Hosp, Memory Clin, Malmo, Sweden, [Hedden, T.] Icahn Sch Med Mt Sinai, Dept Neurol, New York, NY 10029 USA, [Hedden, T.] Harvard Med Sch, Massachusetts Gen Hosp, Dept Radiol, Athinoula Martinos Ctr Biomed Imaging, Boston, MA 02115 USA, [Heinz, A.] Charite Univ Med Berlin, Charite Campus Mitte, Berlin, Germany, [Heinz, A.] Free Univ Berlin, Charite Campus Mitte, Berlin, Germany, [Heinz, A.] Humboldt Univ, Dept Psychiat & Psychotherapy, Charite Campus Mitte, Berlin, Germany, [Heuer, K.] Max Planck Inst Human Cognit & Brain Sci, Dept Neuropsychol, Leipzig, Germany, [Heuer, K.] Univ Paris, Paris, France, [Toro, R.] Univ Paris, Paris, France, [Hoare, J.] Univ Cape Town, Dept Psychiat, Cape Town, South Africa, [Holla, B.] NIMHANS, Dept Integrat Med, Bengaluru, India, [Holla, B.] NIMHANS, Dept Psychiat, Accelerator Program Discovery Brain Disorders Usi, Bengaluru, India, [Holmes, A. J.] Yale Univ, Dept Psychol, New Haven, CT USA, [Villeneuve, S.] Yale Univ, Dept Psychol, New Haven, CT USA, [Holmes, A. J.] Yale Univ, Dept Psychiat, New Haven, CT 06520 USA, [Villeneuve, S.] Yale Univ, Dept Psychiat, New Haven, CT 06520 USA, [Huang, H.] Childrens Hosp Philadelphia, Radiol Res, Philadelphia, PA 19104 USA, [Ouyang, M.] Childrens Hosp Philadelphia, Radiol Res, Philadelphia, PA 19104 USA, [Huang, H.] Univ Penn, Dept Radiol, Perelman Sch Med, Philadelphia, PA 19104 USA, [Ipser, J.] Univ Cape Town, Dept Psychiat & Mental Hlth, Clin Neurosci Inst, Cape Town, South Africa, [Jack, C. R., Jr.] Mayo Clin, Dept Radiol, Rochester, MN USA, [Jones, D. T.] Mayo Clin, Dept Radiol, Rochester, MN USA, Univ Fed Sao Paulo, Dept Psychiat, Sao Paulo, Brazil, [Jackowski, A. P.] Natl Inst Dev Psychiat, Beijing, Peoples R China, [Jia, T.] Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Shanghai, Peoples R China, [Jia, T.] Fudan Univ, Minist Educ, Key Lab Computat Neurosci & Brain Inspired Intell, Shanghai, Peoples R China, [Jia, T.] Kings Coll London, Inst Psychiat Psychol & Neurosci, Ctr Populat Neurosci & Precis Med PONS, SGDP Ctr, London, England, [Johnson, K. A.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Schultz, A. P.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Sperling, R. A.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Johnson, K. A.] Brigham & Womens Hosp, Dept Neurol, Ctr Alzheimer Res & Treatment, 75 Francis St, Boston, MA 02115 USA, [Sperling, R. A.] Brigham & Womens Hosp, Dept Neurol, Ctr Alzheimer Res & Treatment, 75 Francis St, Boston, MA 02115 USA, [Johnson, K. A.] Massachusetts Gen Hosp, Dept Radiol, Boston, MA USA, [Jones, D. T.] Mayo Clin, Dept Neurol, Rochester, MN USA, [3R-BRAIN] Mayo Clin, Dept Neurol, Rochester, MN USA, [Kahn, R. S.] Icahn Sch Med Mt Sinai, Dept Psychiat, New York, NY 10029 USA, [Karlsson, H.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Karlsson, L.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Tuulari, J. J.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Karlsson, H.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Karlsson, L.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Tuulari, J. J.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Karlsson, H.] Turku Univ Hosp, Turku, Finland, [Karlsson, L.] Turku Univ Hosp, Turku, Finland, [Tuulari, J. J.] Turku Univ Hosp, Turku, Finland, [Karlsson, H.] Turku Univ Hosp, Ctr Populat Hlth Res, Turku, Finland, [Karlsson, L.] Turku Univ Hosp, Ctr Populat Hlth Res, Turku, Finland, [Karlsson, H.] Univ Turku, Turku, Finland, [Karlsson, L.] Univ Turku, Turku, Finland, [Kawashima, R.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Taki, Y.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Thyreau, B.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Kelley, E. A.] Queens Univ, Ctr Neurosci Studies, Dept Psychol, Kingston, ON, Canada, [Kelley, E. A.] Queens Univ, Ctr Neurosci Studies, Dept Psychiat, Kingston, ON, Canada, [Kern, S.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Skoog, I.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Zettergren, A.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Kern, S.] Sahlgrens Univ Hosp, Psychiat Cognit & Old Age Psychiat Clin, Reg Vastra Gotaland, Gothenburg, Sweden, [Skoog, I.] Sahlgrens Univ Hosp, Psychiat Cognit & Old Age Psychiat Clin, Reg Vastra Gotaland, Gothenburg, Sweden, [Kim, K. W.] Seoul Natl Univ, Dept Brain & Cognit Sci, Coll Nat Sci, Seoul, South Korea, [Kim, K. W.] Seoul Natl Univ, Bundang Hosp, Dept Neuropsychiat, Seongnam, South Korea, [Kim, K. W.] Seoul Natl Univ, Dept Psychiat, Coll Med, Seoul, South Korea, [Kim, K. W.] SNU MRC, Inst Human Behav Med, Seoul, South Korea, [Lalonde, F.] NIMH, Sect Dev Neurogenom, Human Genet Branch, Bethesda, MD 20892 USA, [Raznahan, A.] NIMH, Sect Dev Neurogenom, Human Genet Branch, Bethesda, MD 20892 USA, [Lee, S.] Seoul Natl Univ, Coll Nat Sci, Dept Brain & Cognit Sci, Seoul, South Korea, [Lerch, J.] Univ Toronto, Dept Med Biophys, Toronto, ON, Canada, [Lerch, J.] Univ Oxford, Nuffield Dept Clin Neurosci, FMRIB, Wellcome Ctr Integrat Neuroimaging, Oxford, England, [Lewis, J. D.] McGill Univ, Montreal Neurol Inst, Montreal, PQ, Canada, [Li, J.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Liao, W.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Valdes-Sosa, P. A.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Liston, C.] Weill Cornell Med, Dept Psychiat, New York, NY USA, [Liston, C.] Weill Cornell Med, Brain & Mind Res Inst, New York, NY USA, [Lombardo, M. V.] Ist Italiano Tecnol, Ctr Neurosci & Cognit Syst UniTn, Lab Autism & Neurodev Disorders, Rovereto, Italy, [Lv, J.] Univ Sydney, Sch Biomed Engn, Sydney, NSW, Australia, [Lv, J.] Univ Sydney, Brain & Mind Ctr, Sydney, NSW, Australia, [Mallard, T. T.] Univ Texas Austin, Dept Psychol, Austin, TX 78712 USA, [Marcelis, M.] Maastricht Univ, Sch Mental Hlth & Neurosci, Dept Psychiat & Neuropsychol, EURON,Med Ctr, Maastricht, Netherlands, [Marcelis, M.] Inst Mental Hlth Care Eindhoven GGzE, Eindhoven, Netherlands, [Markello, R. D.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Misic, B.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Vasung, L.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Mazoyer, B.] Douglas Mental Hlth Univ Inst, Ludmer Ctr Neuroinformat & Mental Hlth, Montreal, PQ, Canada, [Meaney, M. J.] Douglas Mental Hlth Univ Inst, Ludmer Ctr Neuroinformat & Mental Hlth, Montreal, PQ, Canada, [Meaney, M. J.] Singapore Inst Clin Sci, Singapore, Singapore, [Mechelli, A.] Bordeaux Univ Hosp, Bordeaux, France, [Morgan, S. E.] Univ Cambridge, Dept Comp Sci & Technol, Cambridge, England, [Morgan, S. E.] Alan Turing Inst, London, England, [Vertes, P. E.] Alan Turing Inst, London, England, [Mothersill, D.] Natl Coll Ireland, Sch Business, Dept Psychol, Dublin, Ireland, [Mothersill, D.] Natl Univ Ireland Galway, Sch Psychol, Galway, Ireland, [Mothersill, D.] Natl Univ Ireland Galway, Ctr Neuroimaging & Cognit Genom, Galway, Ireland, [Mothersill, D.] Trinity Coll Dublin, Dept Psychiat, Dublin, Ireland, [Nigg, J.] Oregon Hlth & Sci Univ, Dept Psychiat, Sch Med, Portland, OR 97201 USA, [Ong, M. Q. W.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Qian, X.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Zhou, J. H.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Ortinau, C.] Washington Univ, Dept Pediat, St Louis, MO 63130 USA, [Ossenkoppele, R.] Vrije Univ Amsterdam, Alzheimer Ctr Amsterdam, Amsterdam UMC, Dept Neurol,Amsterdam Neurosci, Amsterdam, Netherlands, [Ossenkoppele, R.] Lund Univ, Clin Memory Res Unit, Lund, Sweden, [Palaniyappan, L.] Univ Western Ontario, Robarts Res Inst, London, ON, Canada, [Palaniyappan, L.] Univ Western Ontario, Brain & Mind Inst, London, ON, Canada, [Pan, P. M.] Fed Univ Sao Poalo UNIFESP, Dept Psychiat, Sao Poalo, Brazil, [Pan, P. M.] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Poalo, Brazil, [Zugman, A.] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Poalo, Brazil, [Pantelis, C.] Univ Melbourne, Dept Psychiat, Melbourne Neuropsychiat Ctr, Carlton, Vic, Australia, [Pantelis, C.] Melbourne Hlth, Carlton, Vic, Australia, [Pantelis, C.] Univ Melbourne, Melbourne Sch Engn, Parkville, Vic, Australia, [Pantelis, C.] Florey Inst Neurosci & Mental Hlth, Parkville, Vic, Australia, [Park, M. M.] Western Univ, Schulich Sch Med & Dent, Dept Psychiat, London, ON, Canada, [Rollins, C. K.] Univ Montreal, Dept Psychiat, Fac Med, Montreal, PQ, Canada, [Rollins, C. K.] Univ Montreal, CHU St Justine, Montreal, PQ, Canada, [Romero-Garcia, R.] Univ Toronto, Dept Psychiat, Toronto, ON, Canada, [Romero-Garcia, R.] Univ Toronto, Dept Psychol, Toronto, ON, Canada, [Rosenberg, M. D.] Univ Toronto, Dept Physiol, Toronto, ON, Canada, [Rosenberg, M. D.] Univ Toronto, Dept Nutr Sci, Toronto, ON, Canada, [Paz-Linares, D.] Cuban Neurosci Ctr, Havana, Cuba, [Pichet Binette, A.] McGill Univ, Fac Med, Dept Psychiat, Montreal, PQ, Canada, [Villeneuve, S.] McGill Univ, Fac Med, Dept Psychiat, Montreal, PQ, Canada, [Pichet Binette, A.] Douglas Mental Hlth Univ Inst, Montreal, PQ, Canada, [Villeneuve, S.] Douglas Mental Hlth Univ Inst, Montreal, PQ, Canada, [Qiu, J.] Southwest Univ, Sch Psychol, Chongqing, Peoples R China, [Qiu, A.] Natl Univ Singapore, N1 Inst Hlth, Dept Biomed Engn, Singapore, Singapore, [Rittman, T.] Univ Cambridge, Dept Clin Neurosci, Cambridge, England, [Tsvetanov, K. A.] Univ Cambridge, Dept Clin Neurosci, Cambridge, England, [Rollins, C. K.] Harvard Med Sch, Dept Neurol, Boston, MA 02115 USA, [Rollins, C. K.] Boston Childrens Hosp, Dept Neurol, Boston, MA USA, [Romero-Garcia, R.] Univ Seville, Dpto Fisiol Med & Biofis, Inst Biomed Sevilla IBiS HUVR CSIC, Seville, Spain, [Rosenberg, M. D.] Univ Chicago, Dept Psychol, 5848 S Univ Ave, Chicago, IL 60637 USA, [Rosenberg, M. D.] Univ Chicago, Inst Neurosci, Chicago, IL USA, [Rowitch, D. H.] Univ Cambridge, Dept Paediat, Cambridge, England, [Rowitch, D. H.] Univ Cambridge, Wellcome MRC Cambridge Stem Cell Inst, Cambridge, England, [Salum, G. A.] Univ Fed Rio Grande Sul UFRGS, Hosp Clin Porto Alegre, Dept Psychiat, Porto Alegre, RS, Brazil, [Salum, G. A.] Natl Inst Dev Psychiat INPD, Sao Paulo, Brazil, [Schaare, H. L.] Max Planck Inst Human Cognit & Brain Sci, Otto Hahn Grp Cognit Neurogenet, Leipzig, Germany, [Schaare, H. L.] Res Ctr Juelich, Inst Neurosci & Med INM 7 Brain & Behav, Julich, Germany, [Schultz, A. P.] Massachusetts Gen Hosp, Dept Radiol, Athinoula Martinos Ctr Biomed Imaging, Charlestown, MA USA, [Schumann, G.] Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Ctr Populat Neurosci & Stratified Med PONS, Shanghai, Peoples R China, [Schumann, G.] Charite Campus Mitte, Dept Psychiat & Psychotherapy, Charite Mental Hlth, PONS Ctr, Berlin, Germany, [Scholl, M.] Univ Gothenburg, Wallenberg Ctr Mol & Translat Med, Gothenburg, Sweden, [Scholl, M.] Univ Gothenburg, Dept Psychiat & Neurochem, Gothenburg, Sweden, [Scholl, M.] UCL, Queens Sq Inst Neurol, Dementia Res Ctr, London, England, [Sharp, D.] UK Dementia Res Inst, Care Res & Technol Ctr, London, England, [Shinohara, R. T.] Univ Penn, Perelman Sch Med, Dept Radiol, Ctr Biomed Image Comp & Analyt, Philadelphia, PA 19104 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Neurol, St Louis, MO 63110 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Pediat, St Louis, MO 63110 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Radiol, St Louis, MO 63110 USA, [Stein, D. J.] Univ Cape Town, Dept Psychiat, SA MRC Unit Risk & Resilience Mental Disorders, Cape Town, South Africa, [Stein, D. J.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Stolicyn, A.] Univ Edinburgh, Ctr Clin Brain Sci, Div Psychiat, Edinburgh, Midlothian, Scotland, [Whalley, H. C.] Univ Edinburgh, Ctr Clin Brain Sci, Div Psychiat, Edinburgh, Midlothian, Scotland, [Toro, R.] Inst Pasteur, Dept Neurosci, Paris, France, [Traut, N.] Inst Pasteur, Dept Neurosci, Paris, France, [Traut, N.] Univ Paris 05, Ctr Res & Interdisciplinar CRI, Paris, France, [Tsvetanov, K. A.] Univ Cambridge, Dept Psychol, Cambridge, England, [Turk-Browne, N. B.] Yale Univ, Wu Tsai Inst, New Haven, CT USA, [Tuulari, J. J.] Univ Turku, Dept Clin Med, Turku, Finland, [Tuulari, J. J.] Univ Turku, Turku Coll Sci Med & Technol, Turku, Finland, [Tzourio, C.] Univ Bordeaux, Bordeaux Populat Hlth Res Ctr, CHU Bordeaux, U1219,INSERM, Bordeaux, France, [Vachon-Presseau, E.] McGill Univ, Fac Dent Med & Oral Hlth Sci, Montreal, PQ, Canada, [Valdes-Sosa, P. A.] McGill Univ, Alan Edwards Ctr Res Pain AECRP, Montreal, PQ, Canada, [Valk, S. L.] Forschungszentrum Julich, Inst Neurosci & Med 7, Julich, Germany, [Valk, S. L.] Max Planck Inst Human Cognit & Brain Sci, Leipzig, Germany, [van Amelsvoort, T.] Maastricht Univ, Dept Psychiat & Neurosychol, Maastricht, Netherlands, [Vandekar, S. N.] Vanderbilt Univ, Dept Biostat, 221 Kirkland Hall, Nashville, TN 37235 USA, [Villeneuve, S.] Vanderbilt Univ, Med Ctr, Dept Biostat, Nashville, TN USA, [Villringer, A.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Witte, A. V.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Zuo, X. N.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Wang, Y. S.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Yang, N.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Yeo, B.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Zuo, X. N.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Wang, Y. S.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Yang, N.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Zuo, X. N.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Wang, Y. S.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Yang, N.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Zuo, X. N.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Wang, Y. S.] Chinese Acad Sci, Res Ctr Lifespan Dev Brain & Mind, Inst Psychol, Beijing, Peoples R China, [Yang, N.] Chinese Acad Sci, Res Ctr Lifespan Dev Brain & Mind, Inst Psychol, Beijing, Peoples R China, [Westman, E.] Karolinska Inst, Ctr Alzheimer Res, Dept Neurobiol Care Sci & Soc, Div Clin Geriatr, Stockholm, Sweden, [Witte, A. V.] Univ Leipzig, CRC 1052 Obes Mech, Fac Med, Leipzig, Germany, [Zhou, J. H.] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Translat MR Res, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, N1 Inst Hlth, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Inst Digital Med, Singapore, Singapore, [Yun, H.] Natl Univ Singapore, Integrat Sci & Engn Programme ISEP, Singapore, Singapore, [Zar, H. J.] Univ Melbourne, Dept Biomed Engn, Melbourne, Vic, Australia, [Zhou, J. H.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Translat Magnet Resonance Res, Singapore, Singapore, [Ziauddeen, H.] Univ Cambridge, Wellcome Trust MRC Inst Metab Sci, Cambridge, England, [Zugman, A.] NIMH, NIH, Bethesda, MD 20892 USA, [Zugman, A.] Escola Paulista Med, Dept Psychiat, Sao Paulo, Brazil, [Zuo, X. N.] Nanning Normal Univ, Sch Educ Sci, Key Lab Brain & Educ, Nanning, Peoples R China, British Academy Postdoctoral fellowship, NIMH, UKRI Medical Research Council, NIHR Cambridge Biomedical Research Centre, NIHR Senior Investigator award, MRC research infrastructure award, Commonwealth Scientific and Industrial Research Organisation (CSIRO), and Ontario Brain Institute
Subjects: 631/378/2649, OpenPain Project, KNE96, Growth, Psychiatric-disorders, DISEASE, 3R-BRAIN, Brain charts, MRI Brain, OASIS-3, Disease, CCNP, 631/378/2571, UMN BCP, Multidisciplinary, medicine.diagnostic_test, PSYCHIATRIC-DISORDERS, article, Brain, Human brain, ASSOCIATION, Magnetic Resonance Imaging, Harvard Aging Brain Study, The Mayo Clinic Study of Aging, NSPN, medicine.anatomical_structure, GROWTH, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], ddc:500, BURDEN, WHITE-MATTER, FinnBrain, Harvard Aging Brain Study, Organization, Mri, MRI, medicine.medical_specialty, Concurrent validity, MODELS, Cam-CAN, Longevity, CALM Team, POND, Neuroimaging, Burden, ORGANIZATION, AIBL, The PREVENT-AD Research Group, VETSA, Cortical thickness, Association, Physical medicine and rehabilitation, FinnBrain, IMAGEN, KNE96, White-matter, medicine, Humans, ASRB, 631/378/1689, COBRE, business.industry, 631/378/2611, Brain morphometry, Neurosciences, Alzheimer’s Disease Repository Without Borders Investigators, Magnetic resonance imaging, Alzheimer’s Disease Neuroimaging Initiative, Anthropometry, Body Height, Brain growth, Birth, 59/57, Normative, IMAGEN, ENIGMA Developmental Brain Age working group, NSPN, business, CCNP, 3R-BRAIN, CORTICAL THICKNESS, Developing Human Connectome Project, ENIGMA Developmental Brain Age working group, The PREVENT-AD Research Group, VETSA, Bullmore, E.T
Abstract: Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes., R.A.I.B. was supported by a British Academy Postdoctoral fellowship and by the Autism Research Trust. J. Seidlitz was supported by NIMH T32MH019112-29 and K08MH120564. S.R.W. was funded by UKRI Medical Research Council MC_UU_00002/2 and was supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). E.T.B. was supported by an NIHR Senior Investigator award and the Wellcome Trust collaborative award for the Neuroscience in Psychiatry Network. A.F.A.-B. was supported by NIMH K08MH120564. Data were curated and analysed using a computational facility funded by an MRC research infrastructure award (MR/M009041/1) to the School of Clinical Medicine, University of Cambridge and supported by the mental health theme of the NIHR Cambridge Biomedical Research Centre.
Published: 2022
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29. Prediagnostic Progressive Supranuclear Palsy - Insights from the UK Biobank

Author: Duncan Street, David Whiteside, Timothy Rittman, James B. Rowe, Street, Duncan [0000-0003-2168-2242], Rittman, Timothy [0000-0003-1063-6937], Rowe, James [0000-0001-7216-8679], and Apollo - University of Cambridge Repository
Subjects: Parkinson's Disease, Hand Strength, Progressive supranuclear palsy, Prodromal markers, Parkinson Disease, eye diseases, United Kingdom, Prospective, Neurology, Humans, Neurology (clinical), Supranuclear Palsy, Progressive, Geriatrics and Gerontology, Biological Specimen Banks
Abstract: INTRODUCTION: Prediagnostic features of Parkinson's Disease are well described but prediagnostic Progressive Supranuclear Palsy (PSP) is less understood. The diagnosis of PSP is delayed by an average of three years after symptom onset. Understanding the changes that occur in the prediagnostic period will aid earlier diagnosis, clarify the natural history, and may aid the design of early disease-modifying therapy trials. We set out to identify motor and cognitive markers of prediagnostic PSP, with Parkinson's disease as a comparator condition, in a large prospective cohort. METHODS: Baseline UK Biobank data from 502,504 individuals were collected between 2006 and 2010. Subsequent PSP and Parkinson's disease cases were identified from primary and secondary care electronic health records' diagnostic coding data and death registry, with 5404 matched controls. RESULTS: 176 PSP cases (time to diagnosis 7.8 ± 2.8 years) and 2526 Parkinson's disease cases (time to diagnosis 7.8 ± 2.9 years) were identified. At baseline, those later diagnosed with PSP had slower reaction times, weaker hand grip, lower fluid intelligence, prospective memory, self-rated health scores and digit recall than controls. Reaction times were correlated with time to diagnosis. The PSP group had higher mortality than both Parkinson's disease and control groups. CONCLUSIONS: Motor slowing, cognitive dysfunction, and postural instability are clinical diagnostic features of PSP that are typically symptomatic three years before diagnosis. Objective markers of these features were evident on average 7.8 years before diagnosis. Our findings suggest the existence of a long prediagnostic phase in PSP, with subtle changes in motor and cognitive function.
Published: 2022

30. Identifying healthy individuals with Alzheimer neuroimaging phenotypes in the UK Biobank

Author: Tiago Azevedo, Richard A.I. Bethlehem, David J. Whiteside, Nol Swaddiwudhipong, James B. Rowe, Pietro Lió, and Timothy Rittman
Abstract: Identifying prediagnostic neurodegenerative disease is a critical issue in neurodegenerative disease research, and Alzheimer’s disease (AD) in particular, to identify populations suitable for preventive and early disease modifying trials. Evidence from genetic studies suggest the neurodegeneration of Alzheimer’s disease measured by brain atrophy starts many years before diagnosis, but it is unclear whether these changes can be detected in sporadic disease. To address this challenge we train a Bayesian machine learning neural network model to generate a neuroimaging phenotype and AD-score representing the probability of AD using structural MRI data in the Alzheimer’s Disease Neuroimaging Cohort (cut-off 0.5, AUC 0.92, PPV 0.90, NPV 0.93). We go on to validate the model in an independent real world dataset of the National Alzheimer’s Coordinating Centre (AUC 0.74, PPV 0.65, NPV 0.80), and demonstrate correlation of the AD-score with cognitive scores in those with an AD-score above 0.5. We then apply the model to a healthy population in the UK Biobank study to identify a cohort at risk for Alzheimer’s disease. This cohort have a cognitive profile in keeping with Alzheimer’s disease, with strong evidence for poorer fluid intelligence, and with some evidence of poorer performance on tests of numeric memory, reaction time, working memory and prospective memory. We found some evidence in the AD-score positive cohort for modifiable risk factors of hypertension and smoking. This approach demonstrates the feasibility of using AI methods to identify a potentially prediagnostic population at high risk for developing sporadic Alzheimer’s disease.
Published: 2022
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31. The Emerging Role of AI in Dementia Research and Healthcare

Author: Janice M. Ranson, Magda Bucholc, Donald Lyall, Danielle Newby, Laura Winchester, Neil Oxtoby, Michele Veldsman, Timothy Rittman, Sarah Marzi, Nathan Skene, Ahmad Al Khleifat, Isabelle Foote, Vasiliki Orgeta, Andrey Kormilitzin, and David J. Llewellyn
Published: 2022
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32. European Incidence of Syndromes Associated with Frontotemporal Lobar Degeneration

Author: Giancarlo Logroscino, Marco Piccininni, Caroline Graff, Orla Hardiman, Albert C. Ludolph, Fermin Moreno, Markus Otto, Anne M. Remes, James Rowe, Harro Seelaar, Eino Solje, Elka Stefanova, Latchezar Traykov, Vesna Jelic, Melissa Taheri, Neil Pinder, Sarah Anderl-Straub, Myriam Barandiaran, Alazne Gabilondo, Johanna Krüger, Alexander Murley, Timothy Rittman, Emma L. van der Ende, John van Swieten, Päivi Hartikainen, Gorana Mandić Stojmenović, Shima Mehrabian, Luisa Benussi, Antonella Alberici, Maria Teresa Dell’Abate, Chiara Zecca, Barbara Borroni, and FRONTIERS Group
Published: 2022
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33. In vivo 18 F-flortaucipir PET does not accurately support the staging of progressive supranuclear palsy

Author: Franklin I. Aigbirhio, Richard W. Bevan-Jones, Elijah Mak, Mayen Briggs, Kieren Allinson, Timothy Rittman, John T. O'Brien, Kamen A. Tsvetanov, Negin Holland, Antonina Kouli, James B. Rowe, George Savulich, Maura Malpetti, P. Simon Jones, Sanne S Kaalund, Luca Passamonti, Tim D. Fryer, Caroline H. Williams-Gray, Young T. Hong, and Maria Grazia Spillantini
Subjects: Oncology, medicine.medical_specialty, Tau pathology, Neurology, business.industry, Pathological staging, Neuropathology, medicine.disease, Progressive supranuclear palsy, In vivo, Internal medicine, medicine, Radiology, Nuclear Medicine and imaging, Clinical severity, 18F-flortaucipir, PET, PET-to-autopsy, Progressive Supranuclear Palsy, Statistical Analysis, staging, tau pathology, Stage (cooking), business
Abstract: Progressive Supranuclear Palsy (PSP) is a neurodegenerative disorder characterised by neuro-glial tau pathology. A new staging system for PSP pathology at post-mortem has been described and validated. We used a data-driven approach to test whether post-mortem pathological staging in PSP can be reproduced in vivo with 18F-flortaucipir PET. Methods:N = 42 patients with probable PSP and N = 39 controls underwent 18F-flortaucipir PET. Conditional inference tree analyses on regional binding potential values identified absent/present pathology thresholds to define in vivo staging. Following the staging system for PSP pathology, the combination of absent/present values across all regions was evaluated to assign each participant to in vivo stages. Analysis of variance was applied to analyse differences among means of disease severity between stages. In vivo staging was compared with post-mortem staging in N = 9 patients who also had post-mortem confirmation of the diagnosis and stage. Results: Stage assignment was estimable in 41 patients: N = 10 patients were classified in stage I/II, N = 26 in stage III/IV, N = 5 in stage V/VI, while N = 1 was not classifiable. An explorative sub-staging identified N = 2 patients in stage I, N = 8 in stage II, N = 9 in stage III, N = 17 in stage IV and N = 5 in stage V. However, the nominal 18F-flortaucipir derived stage was not associated with clinical severity and was not indicative of pathology staging at post-mortem. Conclusion:18F-flortaucipir PET in vivo does not correspond to neuropathological staging in PSP. This analytic approach, seeking to mirror in vivo the neuropathology staging with PET-to-autopsy correlational analyses might enable in vivo staging with next-generation PET tracers for tau, but further evidence and comparison with post-mortem data are needed.
Published: 2022
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34. Rate‐limiting processes of tau aggregate accumulation in Alzheimer's disease

Author: Georg Meisl, Yukun Zuo, Kieren Allinson, Timothy Rittman, Sarah L. DeVos, Justin S Sanchez, Catherine K. Xu, Karen E. Duff, Keith A. Johnson, James B. Rowe, Bradley T. Hyman, Tuomas Knowles, and David Klenerman
Subjects: Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Published: 2021
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35. A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers

Author: Yolande A.L. Pijnenburg, Alessandro Padovani, Lieke H.H. Meeter, Rita Guerreiro, Mathieu Vandenbulcke, Rose Bruffaerts, Sonja Schönecker, Sofia Bergström, Florence Pasquier, Mikel Tainta, Beatriz Santiago, Roberto Gasparotti, Maria Rosário Almeida, Núria Bargalló, Abbe Ullgren, Martina Bocchetta, James B. Rowe, Pietro Tiraboschi, Robart Bartha, Rachelle Shafei, Benjamin Bender, Anna Månberg, Enrico Premi, Sergi Borrego-Écija, Sandro Sorbi, Christopher C Butler, Rick van Minkelen, Alberto Benussi, Marta Cañada, Carlo Wilke, Christin Andersson, Caroline Graff, Isabel Santana, Elisa Semler, Valentina Bessi, Miren Zulaica, Benedetta Nacmias, Tobias Langheinrich, Christen Shoesmith, Philip Van Damme, Camilla Ferrari, Martin Rosser, Pedro Rosa-Neto, Alexandre de Mendonça, Jennifer M. Nicholas, Catharina Prix, Sebastien Ourselin, Michele Veldsman, Jessica L. Panman, Håkan Thonberg, Jennie Olofsson, Paul M. Thompson, Ana Gorostidi, Andrea Arighi, Raquel Sánchez-Valle, Anna Antonell, Vesna Jelic, Ana Verdelho, Sara Mitchell, Janne M. Papma, Alina Díez, Giuliano Binetti, Rhian S Convery, Silvana Archetti, Ekaterina Rogaeva, Michela Pievani, C. Ferreira, Hans-Otto Karnath, Veronica Redaelli, Giuseppe Di Fede, Giovanni B. Frisoni, Carolina Maruta, Giacomina Rossi, Jaume Olives, Simon Ducharme, Roberta Ghidoni, Alexander Gerhard, Ron Keren, Johannes Levin, Sandra V. Loosli, Jose Bras, Isabelle Le Ber, Emily Todd, Robert Laforce, Sónia Afonso, Matthis Synofzik, Alazne Gabilondo, Elizabeth Finger, Thomas E. Cope, Paola Caroppo, Jorge Villanua, Diana Duro, Georgia Peakman, Giorgio G. Fumagalli, Serge Gauthier, Mario Masellis, Markus Otto, Caroline V. Greaves, Carolyn Timberlake, Harro Seelaar, Ione O.C. Woollacott, Sara Prioni, Jason D. Warren, Cristina Polito, Miguel Tábuas-Pereira, David F. Tang-Wai, Carmela Tartaglia, Linn Öijerstedt, Luisa Benussi, Barbara Borroni, Ricardo Taipa, Albert Lladó, Mircea Balasa, Rosa Rademakers, Lize C. Jiskoot, Miguel Castelo-Branco, Julia Remnestål, Fabrizio Tagliavini, Giorgio Giaccone, Maria João Leitão, Henrik Zetterberg, Valentina Cantoni, Daniela Galimberti, Sarah Anderl-Straub, Simon Mead, Myriam Barandiaran, Adrian Danek, Timothy Rittman, Chiara Fenoglio, Katrina M. Moore, David M. Cash, Rik Vandenberghe, Peter Nilsson, Elisabeth Wlasich, John C. van Swieten, Morris Freedman, Sandra E. Black, Carolin Heller, Stefano Gazzina, Gabriel Miltenberger, Fermin Moreno, Nick C. Fox, David L. Thomas, Jonathan D. Rohrer, Begoña Indakoetxea, Tobias Hoegen, Gemma Lombardi, Elio Scarpini, Bergström, Sofia [0000-0003-2910-4754], Apollo - University of Cambridge Repository, Neurology, Amsterdam Neuroscience - Neurodegeneration, Genetic Frontotemporal Dementia Initiative (GENFI), Jiskoot, Lize (Beitragende*r), Rowe, James B. (Beitragende*r), de Mendonça, Alexandre (Beitragende*r), Tagliavini, Fabrizio (Beitragende*r), Santana, Isabel (Beitragende*r), Le Ber, Isabelle (Beitragende*r), Levin, Johannes (Beitragende*r), Danek, Adrian (Beitragende*r), Otto, Markus (Beitragende*r), Frisoni, Giovanni (Beitragende*r), Ghidoni, Roberta (Beitragende*r), Sorbi, Sandro (Beitragende*r), Pasquier, Florence (Beitragende*r), Jelic, Vesna (Beitragende*r), Andersson, Christin (Beitragende*r), Afonso, Sónia (Beitragende*r), Almeida, Maria Rosario (Beitragende*r), Anderl-Straub, Sarah (Beitragende*r), Antonell, Anna (Beitragende*r), Archetti, Silvana (Beitragende*r), Arighi, Andrea (Beitragende*r), Balasa, Mircea (Beitragende*r), Barandiaran, Myriam (Beitragende*r), Bargalló, Nuria (Beitragende*r), Bartha, Robart (Beitragende*r), Bender, Benjamin (Beitragende*r), Benussi, Alberto (Beitragende*r), Benussi, Luisa (Beitragende*r), Bessi, Valentina (Beitragende*r), Binetti, Giuliano (Beitragende*r), Black, Sandra (Beitragende*r), Bocchetta, Martina (Beitragende*r), Borrego-Ecija, Sergi (Beitragende*r), Bras, Jose (Beitragende*r), Bruffaerts, Rose (Beitragende*r), Cañada, Marta (Beitragende*r), Cantoni, Valentina (Beitragende*r), Caroppo, Paola (Beitragende*r), Cash, David (Beitragende*r), Castelo-Branco, Miguel (Beitragende*r), Convery, Rhian (Beitragende*r), Cope, Thomas (Beitragende*r), Di Fede, Giuseppe (Beitragende*r), Díez, Alina (Beitragende*r), Duro, Diana (Beitragende*r), Fenoglio, Chiara (Beitragende*r), Ferrari, Camilla (Beitragende*r), Ferreira, Catarina B. (Beitragende*r), Fox, Nick (Beitragende*r), Freedman, Morris (Beitragende*r), Fumagalli, Giorgio (Beitragende*r), Gabilondo, Alazne (Beitragende*r), Gasparotti, Roberto (Beitragende*r), Gauthier, Serge (Beitragende*r), Gazzina, Stefano (Beitragende*r), Giaccone, Giorgio (Beitragende*r), Gorostidi, Ana (Beitragende*r), Greaves, Caroline (Beitragende*r), Guerreiro, Rita (Beitragende*r), Heller, Carolin (Beitragende*r), Hoegen, Tobias (Beitragende*r), Indakoetxea, Begoña (Beitragende*r), Karnath, Hans-Otto (Beitragende*r), Keren, Ron (Beitragende*r), Langheinrich, Tobias (Beitragende*r), Leitão, Maria João (Beitragende*r), Lladó, Albert (Beitragende*r), Lombardi, Gemma (Beitragende*r), Loosli, Sandra (Beitragende*r), Maruta, Carolina (Beitragende*r), Mead, Simon (Beitragende*r), Meeter, Lieke (Beitragende*r), Miltenberger, Gabriel (Beitragende*r), van Minkelen, Rick (Beitragende*r), Mitchell, Sara (Beitragende*r), Moore, Katrina (Beitragende*r), Nacmias, Benedetta (Beitragende*r), Nicholas, Jennifer (Beitragende*r), Olives, Jaume (Beitragende*r), Ourselin, Sebastien (Beitragende*r), Padovani, Alessandro (Beitragende*r), Panman, Jessica (Beitragende*r), Papma, Janne M. (Beitragende*r), Peakman, Georgia (Beitragende*r), Pievani, Michela (Beitragende*r), Pijnenburg, Yolande (Beitragende*r), Polito, Cristina (Beitragende*r), Premi, Enrico (Beitragende*r), Prioni, Sara (Beitragende*r), Prix, Catharina (Beitragende*r), Rademakers, Rosa (Beitragende*r), Redaelli, Veronica (Beitragende*r), Rittman, Tim (Beitragende*r), Rogaeva, Ekaterina (Beitragende*r), Rosa-Neto, Pedro (Beitragende*r), Rossi, Giacomina (Beitragende*r), Rosser, Martin (Beitragende*r), Santiago, Beatriz (Beitragende*r), Scarpini, Elio (Beitragende*r), Schönecker, Sonja (Beitragende*r), Semler, Elisa (Beitragende*r), Shafei, Rachelle (Beitragende*r), Shoesmith, Christen (Beitragende*r), Tábuas-Pereira, Miguel (Beitragende*r), Tainta, Mikel (Beitragende*r), Taipa, Ricardo (Beitragende*r), Tang-Wai, David (Beitragende*r), Thomas, David L. (Beitragende*r), Thompson, Paul (Beitragende*r), Thonberg, Håkan (Beitragende*r), Timberlake, Carolyn (Beitragende*r), Tiraboschi, Pietro (Beitragende*r), Todd, Emily (Beitragende*r), Van Damme, Philip (Beitragende*r), Vandenbulcke, Mathieu (Beitragende*r), Veldsman, Michele (Beitragende*r), Verdelho, Ana (Beitragende*r), Villanua, Jorge (Beitragende*r), Warren, Jason (Beitragende*r), Wilke, Carlo (Beitragende*r), Woollacott, Ione (Beitragende*r), Wlasich, Elisabeth (Beitragende*r), Zetterberg, Henrik (Beitragende*r), and Zulaica, Miren (Beitragende*r)
Subjects: medicine.medical_specialty, Neurology, NEFM, Medizin, genetics [Mutation], LASSO, Biology, Aquaporin 4 (AQP4), Neurosecretory protein VGF (VGF), DISEASE, genetics [Progranulins], Cellular and Molecular Neuroscience, Progranulins, CEREBROSPINAL-FLUID, C9orf72, ddc:570, medicine, CRITERIA, Humans, Neuronal pentraxin 2 (NPTX2), RC346-429, genetics [Frontotemporal Dementia], Molecular Biology, Pathological, Genetics, Science & Technology, Neurosciences, RC952-954.6, Brain, Neurofilament medium polypeptide (NEFM), medicine.disease, Molecular medicine, Cerebrospinal fluid, Aquaporin 4, Geriatrics, Suspension bead array, Frontotemporal Dementia, Mutation, Mutation (genetic algorithm), Neurosciences & Neurology, Neurology. Diseases of the nervous system, Neurology (clinical), Life Sciences & Biomedicine, Random forest, Biomarkers, Research Article, Frontotemporal dementia
Abstract: Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Supplementary Information: Additional file 1 of A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study; Additional file 2 of A panel of CSF proteins separates genetic frontotemporal dementia from presymptomatic mutation carriers: a GENFI study; both files are available online at https://doi.org/10.1186/s13024-021-00499-4 Copyright © The Author(s) 2021. Background: A detailed understanding of the pathological processes involved in genetic frontotemporal dementia is critical in order to provide the patients with an optimal future treatment. Protein levels in CSF have the potential to reflect different pathophysiological processes in the brain. We aimed to identify and evaluate panels of CSF proteins with potential to separate symptomatic individuals from individuals without clinical symptoms (unaffected), as well as presymptomatic individuals from mutation non-carriers. Methods: A multiplexed antibody-based suspension bead array was used to analyse levels of 111 proteins in CSF samples from 221 individuals from families with genetic frontotemporal dementia. The data was explored using LASSO and Random forest. Results: When comparing affected individuals with unaffected individuals, 14 proteins were identified as potentially important for the separation. Among these, four were identified as most important, namely neurofilament medium polypeptide (NEFM), neuronal pentraxin 2 (NPTX2), neurosecretory protein VGF (VGF) and aquaporin 4 (AQP4). The combined profile of these four proteins successfully separated the two groups, with higher levels of NEFM and AQP4 and lower levels of NPTX2 in affected compared to unaffected individuals. VGF contributed to the models, but the levels were not significantly lower in affected individuals. Next, when comparing presymptomatic GRN and C9orf72 mutation carriers in proximity to symptom onset with mutation non-carriers, six proteins were identified with a potential to contribute to a separation, including progranulin (GRN). Conclusion: In conclusion, we have identified several proteins with the combined potential to separate affected individuals from unaffected individuals, as well as proteins with potential to contribute to the separation between presymptomatic individuals and mutation non-carriers. Further studies are needed to continue the investigation of these proteins and their potential association to the pathophysiological mechanisms in genetic FTD. This study has received support from the Swedish FTD initiative funded by the Schörling Family Foundation. This work was also funded by KTH Center for Applied Precision Medicine (KCAP) funded by the Erling-Persson Family Foundation, grants from Vetenskapsrådet Dnr 529-2014-7504, VR 2015-02926 and 2018-02754, Swedish Alzheimer Foundation, Swedish Brain Foundation, Åhlén foundation, Demensfonden, Stohnes foundation, Gamla Tjänarinnor and Stockholm County Council ALF. Furthermore, support was received by the MRC UK GENFI grant (MR/M023664/1), the Bluefield Project, the JPND GENFI-PROX grant (2019-02248), the Dioraphte Foundation [grant numbers 09-02-00]; the Association for Frontotemporal Dementias Research Grant 2009; The Netherlands Organization for Scientific Research (NWO) (grant HCMI 056-13-018); ZonMw Memorabel (Deltaplan Dementie), (project numbers 733 050 103 and 733 050 813); JPND PreFrontAls consortium (project number 733051042). JDR is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases - Project ID No 739510. M.S. was supported by the JPND grant “GENFI-prox” (by DLR/BMBF to M. S, joint with JDR., J.vS., M.O., B.B. and C.G.). Open Access funding provided by Royal Institute of Technology.
Published: 2021
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36. Microglial activation and atrophy in frontal cortex predict executive dysfunction in frontotemporal dementia

Author: Maura Malpetti, P. Simon Jones, Frank H. Hezemans, Elijah Mak, Duncan Street, Luca Passamonti, Timothy Rittman, Thomas E. Cope, W. Richard Bevan‐Jones, Karalyn Patterson, Tim D. Fryer, Young T. Hong, Franklin I. Aigbirho, John T. O'Brien, and James B. Rowe
Subjects: Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Published: 2021
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37. Decision letter: Impact of long- and short-range fibre depletion on the cognitive deficits of fronto-temporal dementia

Author: Timothy Rittman
Published: 2021
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38. Altered network stability in progressive supranuclear palsy

Author: Michele T.M. Hu, James B. Rowe, P. Nigel Leigh, Johannes C. Klein, P. Simon Jones, Alistair Church, Timothy Rittman, David J. Burn, Boyd C.P. Ghosh, Huw R. Morris, Alexander Gerhard, Ian Ts Coyle-Gilchrist, David J Whiteside, Whiteside, David [0000-0002-5890-9220], Jones, Simon [0000-0001-9695-0702], Rowe, James [0000-0001-7216-8679], Rittman, Timothy [0000-0003-1063-6937], and Apollo - University of Cambridge Repository
Subjects: Male, Aging, Network dynamics, Neuropsychological Tests, CCPP, Cambridge Centre for Parkinson-plus, Article, Progressive supranuclear palsy, Multiscale entropy, Synapse, Cognition, Atrophy, ICA, Independent component analysis, PSPRS, Progressive supranuclear palsy-rating-scale, PROSPECT-MR, Progressive Supranuclear Palsy-Corticobasal Syndrome-Multiple System Atrophy-UK study, medicine, Humans, Hidden Markov models, Aged, PCA, Principal component analysis, Neurotransmitter Agents, Artificial neural network, business.industry, General Neuroscience, ACE, Addenbrooke's Cognitive Examination, Brain, Complexity, Middle Aged, medicine.disease, Magnetic Resonance Imaging, PSP, Progressive supranuclear palsy, Markov Chains, eye diseases, Synapses, MSE, Multi-scale entropy, Female, Supranuclear Palsy, Progressive, Neurology (clinical), Neuropsychological testing, Nerve Net, Geriatrics and Gerontology, business, Neuroscience, HMM, Hidden Markov models, Developmental Biology
Abstract: Highlights • We investigated network dynamics in the tauopathy progressive supranuclear palsy • Abnormal temporal properties of large-scale networks are related to phenotype • Progressive supranuclear palsy paradoxically increases frontoparietal state time • Reductions in neural signal complexity relate to altered network dynamics • Dynamic network and topological changes occur distally to primary sites of atrophy, The clinical syndromes of Progressive Supranuclear Palsy (PSP) may be mediated by abnormal temporal dynamics of brain networks, due to the impact of atrophy, synapse loss and neurotransmitter deficits. We tested the hypothesis that alterations in signal complexity in neural networks influence short-latency state transitions. Ninety-four participants with PSP and 64 healthy controls were recruited from two independent cohorts. All participants underwent clinical and neuropsychological testing and resting-state functional MRI. Network dynamics were assessed using hidden Markov models and neural signal complexity measured in terms of multiscale entropy. In both cohorts, PSP increased the proportion of time in networks associated with higher cognitive functions. This effect correlated with clinical severity as measured by the PSP-rating-scale, and with reduced neural signal complexity. Regional atrophy influenced abnormal brain-state occupancy, but abnormal network topology and dynamics were not restricted to areas of atrophy. Our findings show that the pathology of PSP causes clinically relevant changes in neural temporal dynamics, leading to a greater proportion of time in inefficient brain-states.
Published: 2021

39. Social cognition impairment in genetic frontotemporal dementia within the GENFI cohort

Author: Rachelle Shafei, Benjamin Bender, Jackie M. Poos, Maria Carmela Tartaglia, Janne M. Papma, Lieke H.H. Meeter, Isabel Santana, Christen Shoesmith, Mikel Tainta, Simon Mead, Albert Lladó, Alazne Gabilondo, Emanuela Rotondo, Alexander Gerhard, Simon Ducharme, Myriam Barandiaran, Mario Masellis, Caroline V. Greaves, Jaume Olives, Rita Guerreiro, Andrea Arighi, Diana Duro NPsych, Sara Mitchell, Roberto Gasparotti, Mathieu Vandenbulcke, Tobias Langheinrich, Thomas E. Cope, Martina Bocchetta, Robart Bartha, Daid Tang-Wai, Jessica L. Panman, Maria Rosário Almeida, Christopher C Butler, Rose Bruffaerts, Núria Bargalló, Pietro Tiraboschi, Beatriz Santiago, Elisabeth Wlasich, Philip Vandamme, Giorgio Giaccone, Sergi Borrego-Écija, Sonja Schönecker, Robert Laforce, Paola Caroppo, Katrina M. Moore, Ione O.C. Woollacott, Maria de Arriba, Veronica Redaelli, Rick van Minkelen, Jorge Villanua, Sónia Afonso, Matthis Synofzik, Nick C. Fox, Jennifer M. Nicholas, David L. Thomas, James B. Rowe, Carlo Wilke, Miren Zulaica, Pedro Rosa-Neto, Jonathan D. Rohrer, Elizabeth Finger, Carolyn Timberlake, C. Ferreira, David M. Cash, Timothy Rittman, Alessandro Padovani, Barbara Borroni, Ricardo Taipa, John C. van Swieten, Sandra V. Loosli, Begoña Indakoetxea, Daniela Galimberti, Sandra E. Black, Ana Gorostidi, Vesna Jelic, Catharina Prix, Ron Keren, Y.A.L. Pijnenburg, Michele Veldsman, Rosa Rademakers, Adrian Danek, Zigor Diaz, Miguel Tábuas-Pereira, Johannes Levin, Raquel Sánchez-Valle, Jose Bras, Rhian S Convery, Silvana Archetti, Markus Otto, Miguel Castelo-Branco, Rik Vandenberghe, Anna Antonell, Fabrizio Tagliavini, Sarah Anderl-Straub, Giuseppe Di Fede, Martin N. Rossor, Carolina Maruta MPsych, Enrico Premi, Giorgio G. Fumagalli, Sara Prioni, Cristina Muscio, Maria João Leitão, Lucy L. Russell, Håkan Thonberg, Ana Verdelho, Gabriel Miltenberger, Ekaterina Rogaeva, Giacomina Rossi, Linn Öijerstedt, Christin Andersson, Caroline Graff, Serge Gauthier, Maura Cosseddu MPsych, Carolin Heller, Stefano Gazzina, Jason D. Warren, Chiara Fenoglio, Tobias Hoegen, Elio Scarpini, Morris Freedman, Fermin Moreno, Mircea Balasa, Lize C. Jiskoot, Alexandre de Mendonça, Paul Thompson, Elisa Semler, Hans-Otto Karnarth, Amsterdam Neuroscience - Neurodegeneration, Neurology, Clinical Genetics, and Repositório da Universidade de Lisboa
Subjects: Social Cognition, C9orf72, Emotion processing, Facial emotion recognition, Faux pas, Frontotemporal dementia, MAPT, Progranulin, Theory of mind, 1702 Cognitive Sciences, Medizin, Social Sciences, Audiology, DISEASE, Behavioural Neurology, genetics [Progranulins], 0302 clinical medicine, Progranulins, Psychology, genetics [Frontotemporal Dementia], Faux pa, Psychology, Experimental, NEUROANATOMY, 05 social sciences, Genetic FTD Initiative, GENFI, Experimental Psychology, MIND, Magnetic Resonance Imaging, ORBITOFRONTAL CORTEX, Neuropsychology and Physiological Psychology, Frontal lobe, Frontotemporal Dementia, Life Sciences & Biomedicine, Behavioral Sciences, medicine.medical_specialty, Cognitive Neuroscience, FRONTAL VARIANT, Experimental and Cognitive Psychology, 050105 experimental psychology, Lateralization of brain function, Temporal lobe, 03 medical and health sciences, AGE, Social cognition, mental disorders, medicine, Humans, 0501 psychology and cognitive sciences, ddc:610, genetics [C9orf72 Protein], DECLINE, Science & Technology, EMOTION RECOGNITION, C9orf72 Protein, Neurosciences, PERFORMANCE, medicine.disease, Facial emotion recognitions, 1701 Psychology, Mutation, Orbitofrontal cortex, Neurosciences & Neurology, GENDER, 1109 Neurosciences, Insula, 030217 neurology & neurosurgery
Abstract: © 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., A key symptom of frontotemporal dementia (FTD) is difficulty interacting socially with others. Social cognition problems in FTD include impaired emotion processing and theory of mind difficulties, and whilst these have been studied extensively in sporadic FTD, few studies have investigated them in familial FTD. Facial Emotion Recognition (FER) and Faux Pas (FP) recognition tests were used to study social cognition within the Genetic Frontotemporal Dementia Initiative (GENFI), a large familial FTD cohort of C9orf72, GRN, and MAPT mutation carriers. 627 participants undertook at least one of the tasks, and were separated into mutation-negative healthy controls, presymptomatic mutation carriers (split into early and late groups) and symptomatic mutation carriers. Groups were compared using a linear regression model with bootstrapping, adjusting for age, sex, education, and for the FP recognition test, language. Neural correlates of social cognition deficits were explored using a voxel-based morphometry (VBM) study. All three of the symptomatic genetic groups were impaired on both tasks with no significant difference between them. However, prior to onset, only the late presymptomatic C9orf72 mutation carriers on the FER test were impaired compared to the control group, with a subanalysis showing differences particularly in fear and sadness. The VBM analysis revealed that impaired social cognition was mainly associated with a left hemisphere predominant network of regions involving particularly the striatum, orbitofrontal cortex and insula, and to a lesser extent the inferomedial temporal lobe and other areas of the frontal lobe. In conclusion, theory of mind and emotion processing abilities are impaired in familial FTD, with early changes occurring prior to symptom onset in C9orf72 presymptomatic mutation carriers. Future work should investigate how performance changes over time, in order to gain a clearer insight into social cognitive impairment over the course of the disease.
Published: 2020
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40. 038 Cerebellar cognitive affective syndrome in ataxia-telangiectasia patients

Author: May Yung Tiet, Timothy Rittman, Rita Horvath, and Anke Hensiek
Subjects: Psychiatry and Mental health, Surgery, Neurology (clinical)
Abstract: BackgroundCognitive function in Ataxia telangiectasia (AT) has been reported in few studies. The cer- ebellum is increasingly recognised as a pivotal structure in cognition and Cerebellar Cognitive Affective Syndrome (CCAS) has been observed in AT. Here, we report on cognitive studies in adult AT patients.MethodsWe performed cognitive assessments on an adult AT cohort and healthy volunteers. We assessed patients using the CCAS Scale, Mini Linguistic State Examination (MLSE) and the Test Your Memory (TYM) assessment. A nominated carer completed the Cambridge Behavioural Inventory Revised (CBI-R). AT patients were also assessed for severity of neurological symptoms using Scale for Assessment and Rating of Ataxia (SARA) and Inventory of Non-Ataxia Signs (INAS).ResultsOur interim analysis confirms Cerebellar Cognitive Affective Syndrome in the adult AT cohort. AT patients showed deficits primarily in tasks relying on executive function: semantic and phonemic fluency, category switching, digit span and affect. There were language deficits in motor speech and phonologi- cal errors greater than syntax or semantic errors.ConclusionsOur large-scale cross-sectional study demonstrates the presence of cognitive dysfunction in AT affecting executive function, motor language function, and affect. We advocate routine cognitive assessment in AT patients as part of their clinical care.
Published: 2022
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41. In Vivo

Author: Maura, Malpetti, Sanne S, Kaalund, Kamen A, Tsvetanov, Timothy, Rittman, Mayen, Briggs, Kieren S J, Allinson, Luca, Passamonti, Negin, Holland, P Simon, Jones, Tim D, Fryer, Young T, Hong, Antonina, Kouli, W Richard, Bevan-Jones, Elijah, Mak, George, Savulich, Maria Grazia, Spillantini, Franklin I, Aigbirhio, Caroline H, Williams-Gray, John T, O'Brien, and James B, Rowe
Subjects: Positron-Emission Tomography, Humans, tau Proteins, Supranuclear Palsy, Progressive, Carbolines
Abstract: Progressive supranuclear palsy (PSP) is a neurodegenerative disorder characterized by neuroglial tau pathology. A new staging system for PSP pathology postmortem has been described and validated. We used a data-driven approach to test whether postmortem pathologic staging in PSP can be reproduced in vivo with
Published: 2021

42. Progressive supranuclear palsy: diagnosis and management

Author: Negin Holland, James B. Rowe, Timothy Rittman, Rowe, James [0000-0001-7216-8679], Rittman, Timothy [0000-0003-1063-6937], and Apollo - University of Cambridge Repository
Subjects: cognition, medicine.medical_specialty, Movement disorders, Context (language use), Review, Multidisciplinary team, Progressive supranuclear palsy, Diagnosis, Differential, 03 medical and health sciences, 0302 clinical medicine, medicine, Dementia, supranuclear palsy, Humans, Psychiatry, business.industry, Cognition, General Medicine, medicine.disease, eye diseases, Harm, movement disorders, Neurology (clinical), Supranuclear Palsy, Progressive, medicine.symptom, business, 030217 neurology & neurosurgery, Patient centred, dementia
Abstract: Treating patients with progressive supranuclear palsy (PSP) is both effective and rewarding. This review aims to share our experience in the proactive management of PSP, considering the patient, the family and the medical context in which the illness unfolds. There are many opportunities to assist your patients, ameliorate their symptoms, reduce their risks and harm, and guide them through the complex medical, social and legal minefield that characterises life with chronic neurological illness. We summarise the challenges of early diagnosis, consider PSP mimics and the role of investigations in excluding these, and discuss the available pharmacological and non-pharmacological treatment strategies to tackle the common and challenging symptoms of PSP. The best treatment will be patient centred and as part of a multidisciplinary team.
Published: 2021
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43. Neuroinflammation predicts disease progression in progressive supranuclear palsy

Author: P.S. Jones, Maura Malpetti, Timothy Rittman, Luca Passamonti, Young T. Hong, Tim D. Fryer, James B. Rowe, William Richard Bevan-Jones, Franklin I. Aigbirhio, P. Vasquez-Rodriguez, John T. O'Brien, Duncan Street, Malpetti, Maura [0000-0001-8923-9656], Rittman, Timothy [0000-0003-1063-6937], O'Brien, John Tiernan [0000-0002-0837-5080], Rowe, James Benedict [0000-0001-7216-8679], and Apollo - University of Cambridge Repository
Subjects: Oncology, Male, medicine.medical_specialty, Linear mixed effect model, Cerebellum, tau Proteins, Severity of Illness Index, Progressive supranuclear palsy, Atrophy, Internal medicine, medicine, Humans, Neuroinflammation, Aged, business.industry, Disease progression, Brain, Middle Aged, medicine.disease, Prognosis, Magnetic Resonance Imaging, eye diseases, Clinical trial, medicine.anatomical_structure, Neuro-inflammation, Positron-Emission Tomography, Disease Progression, Encephalitis, Female, Brainstem, Supranuclear Palsy, Progressive, business
Abstract: Introduction: In addition to tau pathology and neuronal loss, neuroinflammation occurs in progressive supranuclear palsy (PSP). However, the prognostic value of the in vivo imaging markers for these processes in PSP remains unclear. We test the primary hypothesis that baseline in vivo imaging assessment of neuroinflammation in subcortical regions predicts clinical progression in patients with PSP. Methods: Seventeen patients with PSP–Richardson’s syndrome underwent a baseline multimodal imaging assessment, including [11C]PK11195 positron emission tomography (PET) to index microglial activation, [18F]AV-1451 PET for tau pathology and structural MRI. Disease severity was measured at baseline and serially up to 4 years with the Progressive Supranuclear Palsy Rating Scale (PSPRS) (average interval of 5 months). Regional grey-matter volumes and PET ligand binding potentials were summarised by three principal component analyses (PCAs). A linear mixed-effects model was applied to the longitudinal PSPRS scores. Single-modality imaging predictors were regressed against the individuals’ estimated rate of progression to identify the prognostic value of baseline imaging markers. Results: PCA components reflecting neuroinflammation and tau burden in the brainstem and cerebellum correlated with the subsequent annual rate of change in the PSPRS. PCA-derived PET markers of neuroinflammation and tau pathology correlated with regional brain volume in the same regions. However, MRI volumes alone did not predict the rate of clinical progression. Conclusions: Molecular imaging with PET for microglial activation and tau pathology can predict clinical progression in PSP. These data encourage the evaluation of immunomodulatory approaches to disease-modifying therapies in PSP and the potential for PET to stratify patients in early phase clinical trials.
Published: 2021

44. Prodromal Progressive Supranuclear Palsy: insights from the UK Biobank

Author: Duncan Street, James B. Rowe, Timothy Rittman, and Whiteside D
Subjects: Pediatrics, medicine.medical_specialty, Recall, business.industry, Cognition, Disease, medicine.disease, eye diseases, Progressive supranuclear palsy, Natural history, Prospective memory, medicine, business, Prospective cohort study, Self-rated health
Abstract: Background: Prodromal Parkinsons Disease is well described but prodromal Progressive Supranuclear Palsy (PSP) is much less understood. The diagnosis of PSP is typically delayed by an average of three years after symptom onset. Understanding the changes that occur in the prodromal and prediagnostic period will aid earlier diagnosis, clarify the natural history, and aid the design of early disease modifying therapy trials. Objectives: To determine motor and cognitive markers of prodromal PSP, with Parkinsons disease as a comparator condition, in a large prospective cohort. Methods: Baseline UK Biobank data from 502,504 individuals were collected between 2006 and 2010. Subsequent PSP and Parkinsons disease cases were identified from primary and secondary care electronic health records diagnostic coding data and death registry, with 5,404 matched controls. Results: 176 PSP cases (mean [SD] time to diagnosis 7.8 [2.8] years) and 2,526 Parkinsons disease cases (time to diagnosis 7.8 [2.9] years) were identified. At baseline, those later diagnosed with PSP had slower reaction times, weaker hand grip, lower fluid intelligence, poorer prospective memory, worse self rated health score and lower digit recall than controls. They had higher mortality than both Parkinsons disease and control groups. Conclusions: Motor slowing, cognitive dysfunction, and postural instability are clinical diagnostic features of PSP and are typically symptomatic three years before diagnosis. However, objective markers of these features are evident over seven years before diagnosis. This suggests a long prodromal course in PSP with subtle changes in motor and cognitive function.
Published: 2021
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45. In vivo coupling of dendritic complexity with presynaptic density in primary tauopathies

Author: Luca Passamonti, James B. Rowe, George Savulich, John O'Brien, Young T. Hong, Maura Malpetti, P. Simon Jones, Rafael Romero-Garcia, Audrey Low, Roido Manavaki, Sanne S Kaalund, Tim D. Fryer, Guy B. Williams, Franklin I. Aigbirhio, Negin Holland, Timothy Rittman, Elijah Mak, Mak, Elijah [0000-0002-6437-8024], Holland, Negin [0000-0003-3813-0882], Jones, Simon [0000-0001-9695-0702], Low, Audrey [0000-0002-2520-454X], Malpetti, Maura [0000-0001-8923-9656], Kaalund, Sanne [0000-0002-8975-1825], Passamonti, Luca [0000-0002-7937-0615], Rittman, Timothy [0000-0003-1063-6937], Manavaki, Roido [0000-0002-4384-6626], Williams, Guy [0000-0001-5223-6654], Aigbirhio, Franklin [0000-0001-9453-5257], O'Brien, John [0000-0002-0837-5080], Rowe, James [0000-0001-7216-8679], and Apollo - University of Cambridge Repository
Subjects: 0301 basic medicine, Male, Aging, PSP-RS, Progressive Supranuclear Palsy – Richardson's Syndrome, PET, Positron Emission Tomography, Synapse, 0302 clinical medicine, Presynaptic density, Aged, 80 and over, NODDI, Neuronal Plasticity, General Neuroscience, Neurodegeneration, Neurodegenerative Diseases, Middle Aged, musculoskeletal system, Magnetic Resonance Imaging, humanities, [11C]UCB-J, Tauopathy, surgical procedures, operative, Tauopathies, embryonic structures, CBD, Corticobasal degeneration, Female, musculoskeletal diseases, Article, Progressive supranuclear palsy, 03 medical and health sciences, Atrophy, In vivo, medicine, NODDI, Neurite Orientation and Dispersion Imaging, Humans, Aged, business.industry, Binding potential, [(11)C]UCB-J, Dendrites, medicine.disease, eye diseases, 030104 developmental biology, PET, Positron-Emission Tomography, Synapses, Neurology (clinical), Geriatrics and Gerontology, business, Neuroscience, 030217 neurology & neurosurgery, Developmental Biology
Abstract: Highlights • Dendritic complexity and presynaptic density are reduced in the 4R-tauopathies of PSP and CBD. • The reduction in ODI and UCB-J binding is coupled across the cortical mantle as well as subcortically. • The relationship between ODI and UCB-J binding is not attributed to atrophy. • ODI may be a useful biomarker of synaptic pathology in neurodegenerative diseases., Understanding the cellular underpinnings of neurodegeneration remains a challenge; loss of synapses and dendritic arborization are characteristic and can be quantified in vivo, with [11C]UCB-J PET and MRI-based Orientation Dispersion Imaging (ODI), respectively. We aimed to assess how both measures are correlated, in 4R-tauopathies of progressive supranuclear palsy – Richardson's Syndrome (PSP-RS; n = 22) and amyloid-negative (determined by [11C]PiB PET) Corticobasal Syndrome (Cortiobasal degeneration, CBD; n =14), as neurodegenerative disease models, in this proof-of-concept study. Compared to controls (n = 27), PSP-RS and CBD patients had widespread reductions in cortical ODI, and [11C]UCB-J non-displaceable binding potential (BPND) in excess of atrophy. In PSP-RS and CBD separately, regional cortical ODI was significantly associated with [11C]UCB-J BPND in disease-associated regions (p < 0.05, FDR corrected). Our findings indicate that reductions in synaptic density and dendritic complexity in PSP-RS and CBD are more severe and extensive than atrophy. Furthermore, both measures are tightly coupled in vivo, furthering our understanding of the pathophysiology of neurodegeneration, and applicable to studies of early neurodegeneration with a safe and widely available MRI platform.
Published: 2021

46. Molecular pathology and synaptic loss in primary tauopathies: [18F]AV-1451 and [11C]UCB-J PET study

Author: P.S. Jones, Maura Malpetti, Luca Passamonti, Elijah Mak, Sanne S Kaalund, John T. O'Brien, Franklin I. Aigbirhio, James B. Rowe, George Savulich, Young T. Hong, Negin Holland, Timothy Rittman, T Fryer, and Frank H. Hezemans
Subjects: Molecular pathology, business.industry, Putamen, medicine, Caudate nucleus, Corticobasal degeneration, Substantia nigra, Tauopathy, Alzheimer's disease, medicine.disease, business, Neuroscience, Progressive supranuclear palsy
Abstract: The relationship betweenin vivosynaptic density and tau burden in primary tauopathies is key to understanding the impact of tauopathy on functional decline and in informing new early therapeutic strategies. In this cross-sectional observational study, we determine thein vivorelationship between synaptic density and molecular pathology, in the primary tauopathies of Progressive Supranuclear Palsy (PSP) and Corticobasal Degeneration (CBD), as a function of disease severity.Twenty three patients with PSP, and twelve patients with Corticobasal Syndrome (CBS) were recruited from a tertiary referral centre. Nineteen education, sex and gender-matched control participants were recruited from the National Institute for Health Research ‘Join Dementia Research’ platform. Cerebral synaptic density and molecular pathology, in all participants, were estimated using PET imaging with the radioligands [11C]UCB-J and [18F]AV-1451, respectively. Patients with CBS also underwent amyloid PET imaging with [11C]PiB to exclude those with likely Alzheimer’s pathology – we refer to the amyloid negative cohort as having CBD although acknowledge other pathologies exist. Disease severity was assessed with the PSP rating scale; regional non-displaceable binding potentials (BPND) of [11C]UCB-J and [18F]AV-1451 were estimated in regions of interest from the Hammersmith Atlas, excluding those with known off-target binding for [18F]AV-1451. As an exploratory analysis, we also investigated the relationship between molecular pathology in cortical brain regions, and synaptic density in connected subcortical areas.Across brain regions, there was apositivecorrelation between [11C]UCB-J and [18F]AV-1451 BPND(β=0.4, t=4.7, p<0.0001). However, the direction of this correlation became less positive as a function of disease severity in patients(β = -0.03, T = -4.0, p = 0.002). Between brain regions, cortical [18F]AV-1451 binding wasnegativelycorrelated with synaptic density in subcortical areas (caudate nucleus, putamen, and substantia nigra).Brain regions with higher synaptic density are associated with a higher [18F]AV-1451 binding in PSP/CBD, but this association diminishes with disease severity. Moreover, higher cortical [18F]AV-1451 binding correlates with lower subcortical synaptic density. Longitudinal imaging is required to confirm the mediation of synaptic loss by molecular pathology. However, the effect of disease severity suggests a biphasic relationship between synaptic density and tauopathy, with synapse rich regions vulnerable to accrual of pathology, followed by a loss of synapses in response to pathology. Given the importance of synaptic function for cognition, our study elucidates the pathophysiology of primary tauopathies and may inform the design of future clinical trials.
Published: 2021
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47. Co-occurrence of apathy and impulsivity in progressive supranuclear palsy

Author: Timothy Rittman, Luca Passamonti, Alexander G Murley, James B. Rowe, and Zi Qi Kok
Subjects: Emotional lability, Clinical cohort, business.industry, Medical record, Cognition, Retrospective cohort study, Impulsivity, medicine.disease, eye diseases, Progressive supranuclear palsy, medicine, Apathy, medicine.symptom, business, Clinical psychology
Abstract: BackgroundApathy and impulsivity are common problems in progressive supranuclear palsy (PSP) and can worsen its prognosis. They can co-exist in the same patients although their concomitant prevalence remains unclear. Their relationship to emotional lability is also unknown.ObjectivesTo estimate the co-occurrence of apathy and impulsivity and their relationship to emotional lability in PSP. To characterize the demographic, clinical, and cognitive features of PSP patients with apathy and impulsivity.MethodsIn a retrospective study of a long-term clinical cohort, we assessed the prevalence of apathy, impulsivity, and emotional lability from clinical interviews, medical records, and contemporary carer questionnaires. N=154 patients with a diagnosis of probable or possible PSP (according to the 2017 Movement Disorder Society criteria) were identified. N=64 of these patients had neuropathological confirmation of PSP. PSP patients with both apathy and impulsivity were compared in terms of demographic, clinical, and cognitive characteristics to PSP patients with either one or neither of these neuropsychiatric features.ResultsApathy and impulsivity co-existed in two-thirds of people with PSP. A fifth displayed emotional lability in addition to apathy and impulsivity. Apathy and impulsivity were more commonly co-expressed than by chance. There was no single demographic, clinical or cognitive feature that distinguished between PSP patients with versus patients without apathy and impulsivity.ConclusionsThe co-existence of apathy and impulsivity in PSP suggests that these neuropsychiatric features may share similar risk factors and etio-pathogenetic mechanisms. Apathy and impulsivity should be jointly assessed when planning symptomatic treatments for behavioural problems in PSP.
Published: 2021
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48. Structural and Functional Thalamic Changes in Progressive Supranuclear Palsy

Author: Sean YW Tan, P Simon Jones, David J Whiteside, James Rowe, and Timothy Rittman
Subjects: Psychiatry and Mental health
Abstract: AimsStudies of thalamic structure and function in Progressive Supranuclear Palsy (PSP) suggest it may play a role in key aspects of the clinical syndrome. This study examined thalamic changes across PSP phenotypes investigating (i) thalamic atrophy (ii) thalamic functional connectivity and (iii) the relationship between thalamic structural and functional connectivity changes with clinical severity.MethodsParticipants92 participants with PSP [63 PSP-Richardson's Syndrome (RS), 24 PSP-cortical, 5 PSP-subcortical] and 104 age-matched controls were recruited from the Cambridge Centre for Parkinson's Plus Disorders cohort. Clinical assessments and imaging were conducted within 1 year of diagnosis.Structural AnalysisThalamic volumes (TVs) were obtained using FreeSurfer. Bayesian multiple regression (brms, R) was used to model (i) mean TVs (ii) group differences in mean TVs (iii) relationships between Z-standardised clinical scores and TVs with age, gender, and total grey matter as covariates.Functional AnalysisVoxel-wise seed-based functional connectivity of the thalamus used the Functional Magnetic Resonance Imaging Expert Analysis Tool (FEAT) in FMRIB's Software Library (FSL). Inter-group differences and relationships between clinical scores and functional connectivity for each group were assessed using a general linear model with age and gender as covariates.ResultsStructural AnalysisTVs for all PSP subgroups were smaller than controls. No differences between PSP subgroups were detected. There was evidence for a relationship between TVs for the entire PSP group and Revised Addenbrooke's Cognitive Examination (ACER) scores [ß = 0.28, 95% credible interval (CI) = 0.04–0.53]. Subgroup analysis showed evidence for a relationship between ACER scores and TVs in PSP-RS [ß = 0.33, 95% CI = 0.09–0.57] and PSP-cortical [ß = 0.46, 95% CI = 0.12–0.83] phenotypes. A negative influence of TVs on total PSP rating scale scores was found for the PSP cohort a whole [ß = −0.51, 95% CI = −1.00 – −0.02].Functional AnalysisPSP patients as a group showed decreased thalamic functional connectivity in higher cortical regions. Subgroup analysis revealed decreased connectivity in those areas compared to controls but in distinct distributions and magnitude. Increased thalamic connectivity with the middle temporal gyrus correlated with ACER scores for PSP patients as a group and in the PSP-cortical subtype.ConclusionThalamic volume loss is a prominent aspect of PSP and is associated with a wide network of changes in functional connectivity that may be distinct between PSP subtypes. Changes in thalamic structure and function predict clinical severity, particularly in PSP-RS and PSP-cortical subtypes.
Published: 2022
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49. Co-Occurrence of Apathy and Impulsivity in Progressive Supranuclear Palsy

Author: Alexander G Murley, James B. Rowe, Luca Passamonti, Timothy Rittman, and Zi Qi Kok
Subjects: apathy, impulsivity, progressive supranuclear palsy, Emotional lability, Clinical cohort, business.industry, Medical record, Retrospective cohort study, Cognition, Impulsivity, medicine.disease, eye diseases, Progressive supranuclear palsy, Neurology, medicine, Apathy, Neurology (clinical), medicine.symptom, business, Research Articles, Clinical psychology, Research Article
Abstract: Background Apathy and impulsivity are common consequences of progressive supranuclear palsy (PSP) and can worsen its prognosis. They can co-exist in the same patients although their concomitant prevalence remains unclear. Their relationship to emotional lability is unknown. Objectives To estimate the co-occurrence of apathy and impulsivity and their relationship to emotional lability in PSP. To characterize the demographic, clinical, and cognitive features of PSP patients with apathy and impulsivity. Methods In a retrospective study of a long-term clinical cohort, we assessed the prevalence of apathy, impulsivity, and emotional lability from clinical interviews, medical records, and contemporary carer questionnaires. One hundred fifty-four patients with a diagnosis of probable or possible PSP (according to the 2017 Movement Disorder Society criteria) were identified. Sixty-four of these patients had neuropathological confirmation of PSP. PSP patients with both apathy and impulsivity were compared in terms of demographic, clinical, and cognitive characteristics to PSP patients with either one or neither of these neuropsychiatric features. Results Apathy and impulsivity co-existed in two-thirds of people with PSP. A fifth displayed emotional lability in addition to apathy and impulsivity. Apathy and impulsivity were more commonly co-expressed than by chance. There was no single demographic, clinical or cognitive feature that distinguished between PSP patients with versus patients without apathy and impulsivity. Conclusions The co-existence of apathy and impulsivity in PSP suggests that these neuropsychiatric features may share similar risk factors and etio-pathogenetic mechanisms. Apathy and impulsivity should be jointly assessed when planning symptomatic treatments for detrimental behavioral problems caused by PSP.
Published: 2021
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50. Clinical progression of progressive supranuclear palsy: impact of trials bias and phenotype variants

Author: Duncan Street, Timothy Rittman, Maura Malpetti, Luca Passamonti, Boyd C.P. Ghosh, Alexander G Murley, Ian Coyle-Gilchrist, James B. Rowe, Street, Duncan [0000-0003-2168-2242], Malpetti, Maura [0000-0001-8923-9656], Rittman, Timothy [0000-0003-1063-6937], Murley, Alexander G [0000-0003-0813-0670], Passamonti, Luca [0000-0002-7937-0615], Apollo - University of Cambridge Repository, and Rowe, James B [0000-0001-7216-8679]
Subjects: Pediatrics, medicine.medical_specialty, MathematicsofComputing_GENERAL, Progressive supranuclear palsy, Rating scale, Medicine, selection bias, ComputingMilieux_MISCELLANEOUS, Hardware_MEMORYSTRUCTURES, Mini–Mental State Examination, medicine.diagnostic_test, business.industry, AcademicSubjects/SCI01870, Parkinsonism, Richardson's syndrome, heterogeneity, prognosis, progressive supranuclear palsy, General Engineering, Richardson’s syndrome, medicine.disease, Gait, ComputingMilieux_GENERAL, Clinical trial, Cohort, Original Article, AcademicSubjects/MED00310, business, Clinical progression
Abstract: Progressive supranuclear palsy causes diverse clinical presentations, including classical Richardson’s syndrome and several variant phenotypes. Clinical trials of disease-modifying therapies have recently been completed, with more planned for the next 2 years. However, many people with progressive supranuclear palsy do not meet eligibility criteria for these clinical trials. Understanding clinical progression with different phenotypes would improve trial design and enhance the accuracy of risk–benefit and cost–benefit assessments of new treatments for progressive supranuclear palsy. We set out to determine rates of motor and cognitive progression of possible, probable and definite progressive supranuclear palsy, with different phenotypes, from a representative cohort in a regional UK healthcare service. Longitudinal clinical data from people with Richardson’s syndrome and variant phenotypes were analysed using linear mixed-modelling, using both the full and modified versions of the Progressive Supranuclear Palsy Rating Scale, Mini-Mental State Examination and the revised Addenbrooke’s Cognitive Examination. Subgroup analyses considered patients meeting recent Phase II trial entry criteria and patients with neuropathological confirmation. Two hundred and twenty-seven patients [male = 59%, mean age (±standard deviation), 71.8 (±7.0) years] were followed for a mean 21.6 (±15.6) months. One hundred and seventy-four (77%) had Richardson’s syndrome at the outset, 25 had cortical variant presentations (13%, frontal, corticobasal, speech and language variants) and 28 had subcortical variant presentations (14%, parkinsonism, postural instability and gait freezing variants). Across all participants, annual progression in Richardson’s syndrome was faster than variant phenotypes on the Mini-Mental State Examination (−1.8 versus −0.9/year, P = 0.005) and revised Addenbrooke’s Cognitive Examination (−5.3 versus −3.0/year, P = 0.01) but not the Progressive Supranuclear Palsy Rating Scale (9.0 versus 7.1/year, P = 0.2) nor the modified Progressive Supranuclear Palsy Rating Scale (2.7 versus 2.3/year, P = 0.4). However, for those with more than 1 years’ follow-up, a significant difference was observed between Richardson’s syndrome and variant phenotypes in Progressive Supranuclear Palsy Rating Scale (8.7 versus 6.3/year, P = 0.04). Survival was longer in variant phenotypes than Richardson’s syndrome [7.3 (±3.9) versus 5.6 (±2.0) years, P = 0.02]. Pathologically confirmed cases (n = 49) supported these findings. Patients meeting basic trial-eligibility criteria (n = 129) progressed faster on the Progressive Supranuclear Palsy Rating Scale than trial-not-eligible patients (10.1 versus 6.1/year, P = 0.001). In conclusion, phenotypes other than Richardson’s syndrome show slower progression and longer survival. Trial criteria do not select representative progressive supranuclear palsy cases. This has implications for trial design, and application of trial results to clinically more diverse patient populations., Street et al. show that progression and survival with progressive supranuclear palsy vary according to people’s symptoms and clinical trial eligibility. Common clinical trial criteria exclude many patients. Their exclusion may limit the relevance of clinical trials and affect the relative risks and benefits of future treatments for many people., Graphical Abstract Graphical Abstract
Published: 2021
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