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1. Overview of ADNI MRI

Author

Jack, Clifford R, Arani, Arvin, Borowski, Bret J, Cash, Dave M, Crawford, Karen, Das, Sandhitsu R, DeCarli, Charles, Fletcher, Evan, Fox, Nick C, Gunter, Jeffrey L, Ittyerah, Ranjit, Harvey, Danielle J, Jahanshad, Neda, Maillard, Pauline, Malone, Ian B, Nir, Talia M, Reid, Robert I, Reyes, Denise A, Schwarz, Christopher G, Senjem, Matthew L, Thomas, David L, Thompson, Paul M, Tosun, Duygu, Yushkevich, Paul A, Ward, Chadwick P, Weiner, Michael W, and Initiative, Alzheimer's Disease Neuroimaging

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease, Acquired Cognitive Impairment, Brain Disorders, Neurodegenerative, Biomedical Imaging, Clinical Research, Dementia, Bioengineering, Humans, Alzheimer Disease, Magnetic Resonance Imaging, Neuroimaging, Brain, ADNI, Alzheimer's disease imaging, Alzheimer's disease MRI, magnetic resonance imaging, Alzheimer's Disease Neuroimaging Initiative, Geriatrics, Clinical sciences, Biological psychology
Abstract

The magnetic resonance imaging (MRI) Core has been operating since Alzheimer's Disease Neuroimaging Initiative's (ADNI) inception, providing 20 years of data including reliable, multi-platform standardized protocols, carefully curated image data, and quantitative measures provided by expert investigators. The overarching purposes of the MRI Core include: (1) optimizing and standardizing MRI acquisition methods, which have been adopted by many multicenter studies and trials worldwide and (2) providing curated images and numeric summary values from relevant MRI sequences/contrasts to the scientific community. Over time, ADNI MRI has become increasingly complex. To remain technically current, the ADNI MRI protocol has changed substantially over the past two decades. The ADNI 4 protocol contains nine different imaging types (e.g., three dimensional [3D] T1-weighted and fluid-attenuated inversion recovery [FLAIR]). Our view is that the ADNI MRI data are a greatly underutilized resource. The purpose of this paper is to educate the scientific community on ADNI MRI methods and content to promote greater awareness, accessibility, and use. HIGHLIGHTS: The MRI Core provides multi-platform standardized protocols, carefully curated image data, and quantitative analysis by expert groups. The ADNI MRI protocol has undergone major changes over the past two decades to remain technically current. As of April 25, 2024, the following numbers of image series are available: 17,141 3D T1w; 6877 FLAIR; 3140 T2/PD; 6623 GRE; 3237 dMRI; 2846 ASL; 2968 TF-fMRI; and 2861 HighResHippo (see Table 1 for abbreviations). As of April 25, 2024, the following numbers of quantitative analyses are available: FreeSurfer 10,997; BSI 6120; tensor based morphometry (TBM) and TBM-SYN 12,019; WMH 9944; dMRI 1913; ASL 925; TF-fMRI NFQ 2992; and medial temporal subregion volumes 2726 (see Table 4 for abbreviations). ADNI MRI is an underutilized resource that could be more useful to the research community.

Published
2024

2. Clinical recognition of frontotemporal dementia with right anterior temporal predominance: A multicenter retrospective cohort study

Author

Ulugut, Hulya, Bertoux, Maxime, Younes, Kyan, Montembeault, Maxime, Fumagalli, Giorgio G, Samanci, Bedia, Illán‐Gala, Ignacio, Kuchcinski, Gregory, Leroy, Melanie, Thompson, Jennifer C, Kobylecki, Christopher, Santillo, Alexander F, Englund, Elisabet, Waldö, Maria Landqvist, Riedl, Lina, Van den Stock, Jan, Vandenbulcke, Mathieu, Vandenberghe, Rik, Laforce, Robert, Ducharme, Simon, Pressman, Peter S, Caramelli, Paulo, de Souza, Leonardo Cruz, Takada, Leonel T, Gurvit, Hakan, Hansson, Oskar, Diehl‐Schmid, Janine, Galimberti, Daniela, Pasquier, Florence, Miller, Bruce L, Scheltens, Philip, Ossenkoppele, Rik, van der Flier, Wiesje M, Barkhof, Frederik, Fox, Nick C, Sturm, Virginia E, Miyagawa, Toji, Whitwell, Jennifer L, Boeve, Bradley, Rohrer, Jonathan D, Gorno‐Tempini, Maria Luisa, Josephs, Keith A, Snowden, Julie, Warren, Jason D, Rankin, Katherine P, Pijnenburg, Yolande AL, and Group, International rtvFTD Working

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Acquired Cognitive Impairment, Dementia, Neurosciences, Alzheimer's Disease Related Dementias (ADRD), Aging, Neurodegenerative, Clinical Research, Mental Health, Basic Behavioral and Social Science, Frontotemporal Dementia (FTD), Rare Diseases, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Behavioral and Social Science, Mental health, Neurological, Good Health and Well Being, Humans, Male, Frontotemporal Dementia, Retrospective Studies, Female, Temporal Lobe, Aged, Middle Aged, Neuropsychological Tests, Atrophy, emotion recognition, frontotemporal dementia, frontotemporal lobar degeneration, right anterior temporal lobe, semantic dementia, social cognition, International rtvFTD Working Group, Clinical Sciences, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionAlthough frontotemporal dementia (FTD) with right anterior temporal lobe (RATL) predominance has been recognized, a uniform description of the syndrome is still missing. This multicenter study aims to establish a cohesive clinical phenotype.MethodsRetrospective clinical data from 18 centers across 12 countries yielded 360 FTD patients with predominant RATL atrophy through initial neuroimaging assessments.ResultsCommon symptoms included mental rigidity/preoccupations (78%), disinhibition/socially inappropriate behavior (74%), naming/word-finding difficulties (70%), memory deficits (67%), apathy (65%), loss of empathy (65%), and face-recognition deficits (60%). Real-life examples unveiled impairments regarding landmarks, smells, sounds, tastes, and bodily sensations (74%). Cognitive test scores indicated deficits in emotion, people, social interactions, and visual semantics however, lacked objective assessments for mental rigidity and preoccupations.DiscussionThis study cumulates the largest RATL cohort unveiling unique RATL symptoms subdued in prior diagnostic guidelines. Our novel approach, combining real-life examples with cognitive tests, offers clinicians a comprehensive toolkit for managing these patients.HighlightsThis project is the first international collaboration and largest reported cohort. Further efforts are warranted for precise nomenclature reflecting neural mechanisms. Our results will serve as a clinical guideline for early and accurate diagnoses.

Published
2024

3. Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer’s disease

Author

Iaccarino, Leonardo, Llibre-Guerra, Jorge J, McDade, Eric, Edwards, Lauren, Gordon, Brian, Benzinger, Tammie, Hassenstab, Jason, Kramer, Joel H, Li, Yan, Miller, Bruce L, Miller, Zachary, Morris, John C, Mundada, Nidhi, Perrin, Richard J, Rosen, Howard J, Soleimani-Meigooni, David, Strom, Amelia, Tsoy, Elena, Wang, Guoqiao, Xiong, Chengjie, Allegri, Ricardo, Chrem, Patricio, Vazquez, Silvia, Berman, Sarah B, Chhatwal, Jasmeer, Masters, Colin L, Farlow, Martin R, Jucker, Mathias, Levin, Johannes, Salloway, Stephen, Fox, Nick C, Day, Gregory S, Gorno-Tempini, Maria Luisa, Boxer, Adam L, La Joie, Renaud, Bateman, Randall, and Rabinovici, Gil D

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Acquired Cognitive Impairment, Brain Disorders, Dementia, Biomedical Imaging, Clinical Research, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Alzheimer's Disease, 2.1 Biological and endogenous factors, Aetiology, Neurological, Good Health and Well Being, Alzheimer's disease, amyloid-PET, brain glucose metabolism, FDG-PET, Alzheimer’s disease, Clinical sciences, Biological psychology
Abstract

Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.

Published
2024

4. Genetic associations with dementia‐related proteinopathy: Application of item response theory

Author

Katsumata, Yuriko, Fardo, David W, Shade, Lincoln MP, Wu, Xian, Karanth, Shama D, Hohman, Timothy J, Schneider, Julie A, Bennett, David A, Farfel, Jose M, Gauthreaux, Kathryn, Mock, Charles, Kukull, Walter A, Abner, Erin L, Nelson, Peter T, Carrillo, Maria, Reiman, Eric M, Chen, Kewei, Masterman, Donna, Green, Robert C, Ho, Carole, Fleisher, Adam, Saykin, Andrew J, Nho, Kwangsik, Apostolova, Liana G, Risacher, Shannon L, Jackson, Jonathan, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Schwarz, Christopher, Jack, Clifford R, Jones, David, Gunter, Jeff, Kantarci, Kejal, Senjem, Matthew, Vemuri, Prashanthi, Reid, Robert, Petersen, Ronald, Hsiao, John K, Potter, William, Masliah, Eliezer, Ryan, Laurie, Bernard, Marie, Silverberg, Nina, Kormos, Adrienne, Conti, Cat, Veitch, Dallas, Flenniken, Derek, Sacrey, Diana Truran, Choe, Mark, Ashford, Miriam, Chen, Stephanie Rossi, Faber, Kelley, Nudelman, Kelly, Wilme, Kristi, Foroud, Tatiana M, Trojanowki, John Q, Shaw, Leslie M, Korecka, Magdalena, Figurski, Michal, Khachaturian, Zaven, Barnes, Lisa, Malone, Ian, Fox, Nick C, Beckett, Laurel, Weiner, Michael W, Jagust, William, Landau, Susan, Knaack, Alexander, DeCarli, Charles, Harvey, Danielle, Fletcher, Evan, González, Hector, Jin, Chengshi, Tosun‐Turgut, Duygu, Neuhaus, John, Fockler, Juliet, Nosheny, Rachel, Koeppe, Robert A, Yushkevich, Paul A, Das, Sandhitsu, Mathis, Chet, Toga, Arthur W, Zimmerman, Caileigh, Gessert, Devon, Shcrer, Elizabeth, Miller, Garrett, Coker, Godfrey, Jimenez, Gustavo, Salazar, Jennifer, Pizzola, Jeremy, Crawford, Karen, Hergesheimer, Lindsey, Donohue, Michael, and Rafii, Michael

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Acquired Cognitive Impairment, Neurodegenerative, Brain Disorders, Dementia, Genetics, Prevention, Aging, 2.1 Biological and endogenous factors, Aetiology, Neurological, Humans, alpha-Synuclein, TDP-43 Proteinopathies, Proteostasis Deficiencies, DNA-Binding Proteins, Biological Products, Alzheimer Disease, Membrane Proteins, Nerve Tissue Proteins, Alzheimer's Disease Neuroimaging Initiative, National Alzheimer's Coordinating Center, ARHGEF28, Alzheimer's Coordinating Center, Alzheimer's Disease Sequencing Project, Alzheimer's disease neuropathologic changes, Item response theory, Lewy, RGNEF, Religious Orders Study, Rush Memory and Aging Project, SDHAF1, TMEM68, neuropathology, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionAlthough dementia-related proteinopathy has a strong negative impact on public health, and is highly heritable, understanding of the related genetic architecture is incomplete.MethodsWe applied multidimensional generalized partial credit modeling (GPCM) to test genetic associations with dementia-related proteinopathies. Data were analyzed to identify candidate single nucleotide variants for the following proteinopathies: Aβ, tau, α-synuclein, and TDP-43.ResultsFinal included data comprised 966 participants with neuropathologic and WGS data. Three continuous latent outcomes were constructed, corresponding to TDP-43-, Aβ/Tau-, and α-synuclein-related neuropathology endophenotype scores. This approach helped validate known genotype/phenotype associations: for example, TMEM106B and GRN were risk alleles for TDP-43 pathology; and GBA for α-synuclein/Lewy bodies. Novel suggestive proteinopathy-linked alleles were also discovered, including several (SDHAF1, TMEM68, and ARHGEF28) with colocalization analyses and/or high degrees of biologic credibility.DiscussionA novel methodology using GPCM enabled insights into gene candidates for driving misfolded proteinopathies.HighlightsLatent factor scores for proteinopathies were estimated using a generalized partial credit model. The three latent continuous scores corresponded well with proteinopathy severity. Novel genes associated with proteinopathies were identified. Several genes had high degrees of biologic credibility for dementia risk factors.

Published
2024

5. Longitudinal clinical, cognitive and biomarker profiles in dominantly inherited versus sporadic early-onset Alzheimer’s disease

Author

Llibre-Guerra, Jorge J, Iaccarino, Leonardo, Coble, Dean, Edwards, Lauren, Li, Yan, McDade, Eric, Strom, Amelia, Gordon, Brian, Mundada, Nidhi, Schindler, Suzanne E, Tsoy, Elena, Ma, Yinjiao, Lu, Ruijin, Fagan, Anne M, Benzinger, Tammie LS, Soleimani-Meigooni, David, Aschenbrenner, Andrew J, Miller, Zachary, Wang, Guoqiao, Kramer, Joel H, Hassenstab, Jason, Rosen, Howard J, Morris, John C, Miller, Bruce L, Xiong, Chengjie, Perrin, Richard J, Allegri, Ricardo, Chrem, Patricio, Surace, Ezequiel, Berman, Sarah B, Chhatwal, Jasmeer, Masters, Colin L, Farlow, Martin R, Jucker, Mathias, Levin, Johannes, Fox, Nick C, Day, Gregory, Gorno-Tempini, Maria Luisa, Boxer, Adam L, La Joie, Renaud, Rabinovici, Gil D, and Bateman, Randall

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Neurodegenerative, Acquired Cognitive Impairment, Genetics, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Clinical Research, Alzheimer's Disease, Aging, Dementia, 2.1 Biological and endogenous factors, Neurological, early-onset Alzheimer's disease, sporadic, dominantly inherited, early-onset Alzheimer’s disease, Clinical sciences, Biological psychology
Abstract

Approximately 5% of Alzheimer's disease cases have an early age at onset (

Published
2023

6. Determinants of cognitive and brain resilience to tau pathology: a longitudinal analysis

Author

Bocancea, Diana I, Svenningsson, Anna L, van Loenhoud, Anna C, Groot, Colin, Barkhof, Frederik, Strandberg, Olof, Smith, Ruben, Weiner, Michael W, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Jagust, William, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Saykin, Andrew J, Morris, John C, Perrin, Richard J, Shaw, Leslie M, Khachaturian, Zaven, Carrillo, Maria, Potter, William, Barnes, Lisa, Bernard, Marie, González, Hector, Ho, Carole, Hsiao, John K, Jackson, Jonathan, Masliah, Eliezer, Masterman, Donna, Okonkwo, Ozioma, Ryan, Laurie, Silverberg, Nina, Fleisher, Adam, Sacrey, Diana Truran, Fockler, Juliet, Conti, Cat, Veitch, Dallas, Neuhaus, John, Jin, Chengshi, Nosheny, Rachel, Ashford, Miriam, Flenniken, Derek, Kormo, Adrienne, Montine, Tom, Conti, Cat B, Rafii, Michael, Raman, Rema, Jimenez, Gustavo, Donohue, Michael, Gessert, Devon, Salazar, Jennifer, Zimmerman, Caileigh, Cabrera, Yuliana, Walter, Sarah, Miller, Garrett, Coker, Godfrey, Clanton, Taylor, Hergesheimer, Lindsey, Smith, Stephanie, Adegoke, Olusegun, Mahboubi, Payam, Moore, Shelley, Pizzola, Jeremy, Shaffer, Elizabeth, Harvey, Danielle, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Schwarz, Christopher, Jones, David, Gunter, Jeff, Kantarci, Kejal, Senjem, Matthew, Vemuri, Prashanthi, Reid, Robert, Fox, Nick C, Malone, Ian, Thompson, Paul, Thomopoulos, Sophia I, Nir, Talia M, Jahanshad, Neda, DeCarli, Charles, Knaack, Alexander, Fletcher, Evan, Tosun-Turgut, Duygu, Chen, Stephanie Rossi, Choe, Mark, and Crawfor, Karen

Subjects
Health Sciences, Neurosciences, Alzheimer's Disease Related Dementias (ADRD), Clinical Research, Acquired Cognitive Impairment, Vascular Cognitive Impairment/Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Biomedical Imaging, Behavioral and Social Science, Alzheimer's Disease, Aging, Neurodegenerative, Brain Disorders, Cerebrovascular, Dementia, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Neurological, Mental health, Humans, Alzheimer Disease, Longitudinal Studies, tau Proteins, Cross-Sectional Studies, Cerebral Cortical Thinning, Positron-Emission Tomography, Brain, Cognition, Apolipoproteins E, Alzheimer's disease, tau, resilience, cognition, PET, MRI, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s disease, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.

Published
2023

7. Comparative neurofilament light chain trajectories in CSF and plasma in autosomal dominant Alzheimer’s disease

Author

Hofmann, Anna, Häsler, Lisa M., Lambert, Marius, Kaeser, Stephan A., Gräber-Sultan, Susanne, Obermüller, Ulrike, Kuder-Buletta, Elke, la Fougere, Christian, Laske, Christoph, Vöglein, Jonathan, Levin, Johannes, Fox, Nick C., Ryan, Natalie S., Zetterberg, Henrik, Llibre-Guerra, Jorge J., Perrin, Richard J., Ibanez, Laura, Schofield, Peter R., Brooks, William S., Day, Gregory S., Farlow, Martin R., Allegri, Ricardo F., Chrem Mendez, Patricio, Ikeuchi, Takeshi, Kasuga, Kensaku, Lee, Jae-Hong, Roh, Jee Hoon, Mori, Hiroshi, Lopera, Francisco, Bateman, Randall J., McDade, Eric, Gordon, Brian A., Chhatwal, Jasmeer P., Jucker, Mathias, and Schultz, Stephanie A.

Published
2024
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8. Updating the study protocol: Insight 46 – a longitudinal neuroscience sub-study of the MRC National Survey of Health and Development – phases 2 and 3

Author

Murray-Smith, Heidi, Barker, Suzie, Barkhof, Frederik, Barnes, Josephine, Brown, Thomas M., Captur, Gabriella, R.E.Cartlidge, Molly, Cash, David M., Coath, William, Davis, Daniel, Dickson, John C., Groves, James, Hughes, Alun D., James, Sarah-Naomi, Keshavan, Ashvini, Keuss, Sarah E., King-Robson, Josh, Lu, Kirsty, Malone, Ian B., Nicholas, Jennifer M., Rapala, Alicja, Scott, Catherine J., Street, Rebecca, Sudre, Carole H., Thomas, David L., Wong, Andrew, Wray, Selina, Zetterberg, Henrik, Chaturvedi, Nishi, Fox, Nick C., Crutch, Sebastian J., Richards, Marcus, and Schott, Jonathan M.

Published
2024
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10. Biomarker clustering in autosomal dominant Alzheimers disease.

Author

Luckett, Patrick, Chen, Charlie, Gordon, Brian, Wisch, Julie, Berman, Sarah, Chhatwal, Jasmeer, Cruchaga, Carlos, Fagan, Anne, Farlow, Martin, Fox, Nick, Jucker, Mathias, Levin, Johannes, Masters, Colin, Mori, Hiroshi, Noble, James, Salloway, Stephen, Schofield, Peter, Brickman, Adam, Brooks, William, Cash, David, Fulham, Michael, Ghetti, Bernardino, Jack, Clifford, Vöglein, Jonathan, Klunk, William, Koeppe, Robert, Su, Yi, Weiner, Michael, Wang, Qing, Marcus, Daniel, Koudelis, Deborah, Joseph-Mathurin, Nelly, Cash, Lisa, Hornbeck, Russ, Xiong, Chengjie, Perrin, Richard, Karch, Celeste, Hassenstab, Jason, McDade, Eric, Morris, John, Benzinger, Tammie, Bateman, Randall, and Ances, Beau

Subjects
Autosomal dominant Alzheimers disease, biomarkers, machine learning, Humans, Alzheimer Disease, Amyloid beta-Peptides, Amyloidogenic Proteins, Biomarkers, Cross-Sectional Studies, Inflammation, tau Proteins
Abstract

INTRODUCTION: As the number of biomarkers used to study Alzheimers disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others. METHODS: We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation. RESULTS: Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors. DISCUSSION: These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.

Published
2023

11. A data‐driven examination of apathy and depressive symptoms in dementia with independent replication

Author

Da Silva, Miguel Vasconcelos, Melendez‐Torres, Gerardo Javier, Ismail, Zahinoor, Testad, Ingelin, Ballard, Clive, Creese, Byron, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Jagust, William, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Saykin, Andrew J, Morris, John, Shaw, Leslie M, Liu, Enchi, Montine, Tom, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Jiminez, Gus, Harvey, Danielle, Bernstein, Matthew, Fox, Nick, Thompson, Paul, Schuff, Norbert, DeCArli, Charles, Borowski, Bret, Gunter, Jeff, Senjem, Matt, Vemuri, Prashanthi, Jones, David, Kantarci, Kejal, Ward, Chad, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Landau, Susan, Cairns, Nigel J, Householder, Erin, Reinwald, Lisa Taylor, Lee, Virginia, Korecka, Magdalena, Figurski, Michal, Crawford, Karen, Neu, Scott, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kelley, Faber, Kim, Sungeun, Nho, Kwangsik, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lind, Betty, Carter, Raina, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Beccera, Mauricio, Teodoro, Liberty, Spann, Bryan M, Brewer, James, Van der Swag, Helen, Fleisher, Adam, Heidebrink, Judith L, Lord, Joanne L, Mason, Sara S, Albers, Colleen S, Knopman, David, Johnson, Kris, Doody, Rachelle S, Meyer, Javier Villanueva, Chowdhury, Munir, Rountree, Susan, Dang, Mimi, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Ances, Beau, Morris, John C, Carroll, Maria, Leon, Sue, Mintun, Mark A, Schneider, Stacy, and Oliver, Angela

Subjects
Clinical and Health Psychology, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Mental Health, Depression, Mental Illness, Mental health, Alzheimer's Disease Neuroimaging Initiative, apathy, dementia, depression, latent class analysis, Genetics, Neurosciences, Biological psychology
Abstract

Apathy is one of the most common neuropsychiatric symptoms (NPS) and is associated with poor clinical outcomes. Research that helps define the apathy phenotype is urgently needed, particularly for clinical and biomarker studies. We used latent class analysis (LCA) with two independent cohorts to understand how apathy and depression symptoms co-occur statistically. We further explored the relationship between latent class membership, demographics, and the presence of other NPS. The LCA identified a four-class solution (no symptoms, apathy, depression, and combined apathy/depression), reproducible over both cohorts, providing robust support for an apathy syndrome distinct from depression and confirming that an apathy/depression syndrome exists, supported by the model fit test with the four-class solution scores evidencing better fitting (Bayesian information criterion adjusted and entropy R 2). Using a data-driven method, we show distinct and statistically meaningful co-occurrence of apathy and depressive symptoms. There was evidence that these classes have different clinical associations, which may help inform diagnostic categories for research studies and clinical practice.HighlightsWe found four classes: no symptoms, apathy, depression and apathy/depression.Apathy conferred a higher probability for agitation.Apathy diagnostic criteria should include accompanying neuropsychiatric symptoms.

Published
2023

12. Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as risk factors for Alzheimer’s disease

Author

Holstege, Henne, Hulsman, Marc, Charbonnier, Camille, Grenier-Boley, Benjamin, Quenez, Olivier, Grozeva, Detelina, van Rooij, Jeroen GJ, Sims, Rebecca, Ahmad, Shahzad, Amin, Najaf, Norsworthy, Penny J, Dols-Icardo, Oriol, Hummerich, Holger, Kawalia, Amit, Amouyel, Philippe, Beecham, Gary W, Berr, Claudine, Bis, Joshua C, Boland, Anne, Bossù, Paola, Bouwman, Femke, Bras, Jose, Campion, Dominique, Cochran, J Nicholas, Daniele, Antonio, Dartigues, Jean-François, Debette, Stéphanie, Deleuze, Jean-François, Denning, Nicola, DeStefano, Anita L, Farrer, Lindsay A, Fernández, Maria Victoria, Fox, Nick C, Galimberti, Daniela, Genin, Emmanuelle, Gille, Johan JP, Le Guen, Yann, Guerreiro, Rita, Haines, Jonathan L, Holmes, Clive, Ikram, M Arfan, Ikram, M Kamran, Jansen, Iris E, Kraaij, Robert, Lathrop, Marc, Lemstra, Afina W, Lleó, Alberto, Luckcuck, Lauren, Mannens, Marcel MAM, Marshall, Rachel, Martin, Eden R, Masullo, Carlo, Mayeux, Richard, Mecocci, Patrizia, Meggy, Alun, Mol, Merel O, Morgan, Kevin, Myers, Richard M, Nacmias, Benedetta, Naj, Adam C, Napolioni, Valerio, Pasquier, Florence, Pastor, Pau, Pericak-Vance, Margaret A, Raybould, Rachel, Redon, Richard, Reinders, Marcel JT, Richard, Anne-Claire, Riedel-Heller, Steffi G, Rivadeneira, Fernando, Rousseau, Stéphane, Ryan, Natalie S, Saad, Salha, Sanchez-Juan, Pascual, Schellenberg, Gerard D, Scheltens, Philip, Schott, Jonathan M, Seripa, Davide, Seshadri, Sudha, Sie, Daoud, Sistermans, Erik A, Sorbi, Sandro, van Spaendonk, Resie, Spalletta, Gianfranco, Tesi, Niccolo’, Tijms, Betty, Uitterlinden, André G, van der Lee, Sven J, Visser, Pieter Jelle, Wagner, Michael, Wallon, David, Wang, Li-San, Zarea, Aline, Clarimon, Jordi, van Swieten, John C, Greicius, Michael D, Yokoyama, Jennifer S, Cruchaga, Carlos, Hardy, John, and Ramirez, Alfredo

Subjects
Biological Sciences, Genetics, Dementia, Alzheimer's Disease, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Prevention, Acquired Cognitive Impairment, Neurodegenerative, Aging, Clinical Research, Biotechnology, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Humans, Adenosine Triphosphatases, Alzheimer Disease, ATP Binding Cassette Transporter 1, Genome-Wide Association Study, Risk Factors, Exosomes, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Alzheimer's disease (AD), the leading cause of dementia, has an estimated heritability of approximately 70%1. The genetic component of AD has been mainly assessed using genome-wide association studies, which do not capture the risk contributed by rare variants2. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals-16,036 AD cases and 16,522 controls. Next to variants in TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Additionally, the rare-variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential drivers of respective AD-genome-wide association study loci. Variants associated with the strongest effect on AD risk, in particular loss-of-function variants, are enriched in early-onset AD cases. Our results provide additional evidence for a major role for amyloid-β precursor protein processing, amyloid-β aggregation, lipid metabolism and microglial function in AD.

Published
2022

14. Autosomal dominant and sporadic late onset Alzheimer's disease share a common in vivo pathophysiology

Author

Morris, John C, Weiner, Michael, Xiong, Chengjie, Beckett, Laurel, Coble, Dean, Saito, Naomi, Aisen, Paul S, Allegri, Ricardo, Benzinger, Tammie LS, Berman, Sarah B, Cairns, Nigel J, Carrillo, Maria C, Chui, Helena C, Chhatwal, Jasmeer P, Cruchaga, Carlos, Fagan, Anne M, Farlow, Martin, Fox, Nick C, Ghetti, Bernardino, Goate, Alison M, Gordon, Brian A, Graff-Radford, Neill, Day, Gregory S, Hassenstab, Jason, Ikeuchi, Takeshi, Jack, Clifford R, Jagust, William J, Jucker, Mathias, Levin, Johannes, Massoumzadeh, Parinaz, Masters, Colin L, Martins, Ralph, McDade, Eric, Mori, Hiroshi, Noble, James M, Petersen, Ronald C, Ringman, John M, Salloway, Stephen, Saykin, Andrew J, Schofield, Peter R, Shaw, Leslie M, Toga, Arthur W, Trojanowski, John Q, Vöglein, Jonathan, Weninger, Stacie, Bateman, Randall J, and Buckles, Virginia D

Subjects
Biomedical and Clinical Sciences, Health Sciences, Psychology, Brain Disorders, Clinical Trials and Supportive Activities, Alzheimer's Disease, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Biomedical Imaging, Genetics, Aging, Acquired Cognitive Impairment, Neurosciences, Neurodegenerative, Dementia, 2.1 Biological and endogenous factors, Aetiology, Neurological, Humans, Alzheimer Disease, Amyloid beta-Peptides, Magnetic Resonance Imaging, Amyloidosis, Biomarkers, Alzheimer pathophysiology, biomarkers, rates of change, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

The extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of 'sporadic' late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease. We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer's Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset. Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants. These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.

Published
2022

15. CSF proteomics identifies early changes in autosomal dominant Alzheimer’s disease

Author

Noble, James M., Day, Gregory S., Graff-Radford, Neill R., Voglein, Jonathan, Allegri, Ricardo, Mendez, Patricio Chrem, Surace, Ezequiel, Berman, Sarah B., Ikonomovic, Snezana, Nadkarni, Neelesh, Lopera, Francisco, Ramirez, Laura, Aguillon, David, Leon, Yudy, Ramos, Claudia, Alzate, Diana, Baena, Ana, Londono, Natalia, Mathias Jucker, Sonia Moreno, Laske, Christoph, Kuder-Buletta, Elke, Graber-Sultan, Susanne, Preische, Oliver, Hofmann, Anna, Ikeuchi, Takeshi, Kasuga, Kensaku, Niimi, Yoshiki, Ishii, Kenji, Senda, Michio, Sanchez-Valle, Raquel, Rosa-Neto, Pedro, Fox, Nick, Cash, Dave, Lee, Jae-Hong, Roh, Jee Hoon, Riddle, Meghan, Menard, William, Bodge, Courtney, Surti, Mustafa, Takada, Leonel Tadao, Farlow, Martin, Chhatwal, Jasmeer P., Sanchez-Gonzalez, V.J., Orozco-Barajas, Maribel, Goate, Alison, Renton, Alan, Esposito, Bianca, Karch, Celeste M., Marsh, Jacob, Cruchaga, Carlos, Fernandez, Victoria, Gordon, Brian A., Fagan, Anne M., Jerome, Gina, Herries, Elizabeth, Llibre-Guerra, Jorge, Levey, Allan I., Johnson, Erik C.B., Seyfried, Nicholas T., Schofield, Peter R., Brooks, William, Bechara, Jacob, Bateman, Randall J., McDade, Eric, Hassenstab, Jason, Perrin, Richard J., Franklin, Erin, Benzinger, Tammie L.S., Chen, Allison, Chen, Charles, Flores, Shaney, Friedrichsen, Nelly, Hantler, Nancy, Hornbeck, Russ, Jarman, Steve, Keefe, Sarah, Koudelis, Deborah, Massoumzadeh, Parinaz, McCullough, Austin, McKay, Nicole, Nicklaus, Joyce, Pulizos, Christine, Wang, Qing, Mishall, Sheetal, Sabaredzovic, Edita, Deng, Emily, Candela, Madison, Smith, Hunter, Hobbs, Diana, Scott, Jalen, Levin, Johannes, Xiong, Chengjie, Wang, Peter, Xu, Xiong, Li, Yan, Gremminger, Emily, Ma, Yinjiao, Bui, Ryan, Lu, Ruijin, Martins, Ralph, Sosa Ortiz, Ana Luisa, Daniels, Alisha, Courtney, Laura, Mori, Hiroshi, Supnet-Bell, Charlene, Xu, Jinbin, Ringman, John, Shen, Yuanyuan, Timsina, Jigyasha, Heo, Gyujin, Beric, Aleksandra, Ali, Muhammad, Wang, Ciyang, Yang, Chengran, Wang, Yueyao, Western, Daniel, Liu, Menghan, Gorijala, Priyanka, Budde, John, Do, Anh, Liu, Haiyan, Gordon, Brian, Llibre-Guerra, Jorge J., Joseph-Mathurin, Nelly, Maschi, Dario, Wyss-Coray, Tony, Pastor, Pau, Renton, Alan E., Surace, Ezequiel I., Alvarez, Ignacio, Ringman, John M., Allegri, Ricardo Francisco, Seyfried, Nicholas, Day, Gregg S., Wu, Qisi, Fernández, M. Victoria, Tarawneh, Rawan, Morris, John C., Ibanez, Laura, and Sung, Yun Ju

Published
2024
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16. γ-Secretase activity, clinical features, and biomarkers of autosomal dominant Alzheimer's disease: cross-sectional and longitudinal analysis of the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS)

Author

Aguillon, David, Allegri, Ricardo F., Aschenbrenner, Andrew J., Baker, Bryce, Barthelemy, Nicolas, Bechara, Jacob A., Berman, Sarah B., Brooks, William S., Cash, David M., Chen, Allison, Chrem Mendez, Patricio, Courtney, Laura, Cruchaga, Carlos, Daniels, Alisha J., Fagan, Anne M., Flores, Shaney, Fox, Nick C., Franklin, Erin, Goate, Alison M., Graber-Sultan, Susanne, Graff-Radford, Neill R., Gremminger, Emily, Herries, Elizabeth, Hofmann, Anna, Holtzman, David M., Hornbeck, Russ, Huey, Edward D., Ibanez, Laura, Ikeuchi, Takeshi, Ikonomovic, Snezana, Jackson, Kelley, Jarman, Steve, Jerome, Gina, Johnson, Erik C.B, Kasuga, Kensaku, Keefe, Sarah, Koudelis, Deborah, Kuder-Buletta, Elke, Laske, Christoph, Leon, Yudy Milena, Levey, Allan I., Li, Yan, Llibre-Guerra, Jorge J., Lopera, Francisco, Lu, Ruijin, Marsh, Jacob, Martins, Ralph, Massoumzadeh, Parinaz, Masters, Colin, McCullough, Austin, McKay, Nicole, Minton, Matthew, Mori, Hiroshi, Morris, John C., Nadkarni, Neelesh K., Nicklaus, Joyce, Niimi, Yoshiki, Noble, James M., Obermueller, Ulrike, Picarello, Danielle M., Pulizos, Christine, Ramirez, Laura, Renton, Alan E., Ringman, John, Rizzo, Jacqueline, Roedenbeck, Yvonne, Roh, Jee Hoon, Rosa-Neto, Pedro, Ryan, Natalie S., Sabaredzovic, Edita, Salloway, Stephen, Sanchez-Valle, Raquel, Scott, Jalen, Seyfried, Nicholas T., Simmons, Ashlee, Smith, Jennifer, Smith, Hunter, Stauber, Jennifer, Stout, Sarah, Supnet-Bell, Charlene, Surace, Ezequiel, Vazquez, Silvia, Vöglein, Jonathan, Wang, Guoqiao, Wang, Qing, Xu, Xiong, Xu, Jinbin, Schultz, Stephanie A, Liu, Lei, Schultz, Aaron P, Fitzpatrick, Colleen D, Levin, Raina, Bellier, Jean-Pierre, Shirzadi, Zahra, Joseph-Mathurin, Nelly, Chen, Charles D, Benzinger, Tammie L S, Day, Gregory S, Farlow, Martin R, Gordon, Brian A, Hassenstab, Jason J, Jack, Clifford R, Jr, Jucker, Mathias, Karch, Celeste M, Lee, Jae-Hong, Levin, Johannes, Perrin, Richard J, Schofield, Peter R, Xiong, Chengjie, Johnson, Keith A, McDade, Eric, Bateman, Randall J, Sperling, Reisa A, Selkoe, Dennis J, and Chhatwal, Jasmeer P

Published
2024
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17. Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission

Author

Livingston, Gill, Huntley, Jonathan, Liu, Kathy Y, Costafreda, Sergi G, Selbæk, Geir, Alladi, Suvarna, Ames, David, Banerjee, Sube, Burns, Alistair, Brayne, Carol, Fox, Nick C, Ferri, Cleusa P, Gitlin, Laura N, Howard, Robert, Kales, Helen C, Kivimäki, Mika, Larson, Eric B, Nakasujja, Noeline, Rockwood, Kenneth, Samus, Quincy, Shirai, Kokoro, Singh-Manoux, Archana, Schneider, Lon S, Walsh, Sebastian, Yao, Yao, Sommerlad, Andrew, and Mukadam, Naaheed

Published
2024
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20. Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer’s disease

Author

Green, Rebecca E., Lord, Jodie, Scelsi, Marzia A., Xu, Jin, Wong, Andrew, Naomi-James, Sarah, Handy, Alex, Gilchrist, Lachlan, Williams, Dylan M., Parker, Thomas D., Lane, Christopher A., Malone, Ian B., Cash, David M., Sudre, Carole H., Coath, William, Thomas, David L., Keuss, Sarah, Dobson, Richard, Legido-Quigley, Cristina, Fox, Nick C., Schott, Jonathan M., Richards, Marcus, and Proitsi, Petroula

Published
2023
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22. Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

Author

McKay, Nicole S., Gordon, Brian A., Hornbeck, Russ C., Dincer, Aylin, Flores, Shaney, Keefe, Sarah J., Joseph-Mathurin, Nelly, Jack, Clifford R., Koeppe, Robert, Millar, Peter R., Ances, Beau M., Chen, Charles D., Daniels, Alisha, Hobbs, Diana A., Jackson, Kelley, Koudelis, Deborah, Massoumzadeh, Parinaz, McCullough, Austin, Nickels, Michael L., Rahmani, Farzaneh, Swisher, Laura, Wang, Qing, Allegri, Ricardo F., Berman, Sarah B., Brickman, Adam M., Brooks, William S., Cash, David M., Chhatwal, Jasmeer P., Day, Gregory S., Farlow, Martin R., la Fougère, Christian, Fox, Nick C., Fulham, Michael, Ghetti, Bernardino, Graff-Radford, Neill, Ikeuchi, Takeshi, Klunk, William, Lee, Jae-Hong, Levin, Johannes, Martins, Ralph, Masters, Colin L., McConathy, Jonathan, Mori, Hiroshi, Noble, James M., Reischl, Gerald, Rowe, Christopher, Salloway, Stephen, Sanchez-Valle, Raquel, Schofield, Peter R., Shimada, Hiroyuki, Shoji, Mikio, Su, Yi, Suzuki, Kazushi, Vöglein, Jonathan, Yakushev, Igor, Cruchaga, Carlos, Hassenstab, Jason, Karch, Celeste, McDade, Eric, Perrin, Richard J., Xiong, Chengjie, Morris, John C., Bateman, Randall J., and Benzinger, Tammie L. S.

Published
2023
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23. Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study

Author

Aizenstein, Howard J., Andrews, Howard F., Bell, Karen, Birn, Rasmus M., Bulova, Peter, Cheema, Amrita, Chen, Kewei, Clare, Isabel, Clark, Lorraine, Cohen, Ann D., Constantino, John N., Doran, Eric W., Feingold, Eleanor, Foroud, Tatiana M., Hartley, Sigan L., Hom, Christy, Honig, Lawrence, Ikonomovic, Milos D., Johnson, Sterling C., Jordan, Courtney, Kamboh, M. Ilyas, Keator, David, Klunk, William E., Kofler, Julia K., Kreisl, William C., Krinsky-McHale, Sharon J., Lao, Patrick, Laymon, Charles, Lott, Ira T., Lupson, Victoria, Mathis, Chester A., Minhas, Davneet S., Nadkarni, Neelesh, Pang, Deborah, Petersen, Melissa, Price, Julie C., Pulsifer, Margaret, Reiman, Eric, Rizvi, Batool, Sabbagh, Marwan N., Schupf, Nicole, Tudorascu, Dana L., Tumuluru, Rameshwari, Tycko, Benjamin, Varadarajan, Badri, White, Desiree A., Yassa, Michael A., Zaman, Shahid, Zhang, Fan, Bateman, Randall, Daniels, Alisha J., Courtney, Laura, McDade, Eric, Llibre-Guerra, Jorge J., Supnet-Bell, Charlene, Xiong, Chengie, Xu, Xiong, Lu, Ruijin, Wang, Guoqiao, Li, Yan, Gremminger, Emily, Perrin, Richard J., Franklin, Erin, Ibanez, Laura, Jerome, Gina, Herries, Elizabeth, Stauber, Jennifer, Baker, Bryce, Minton, Matthew, Cruchaga, Carlos, Goate, Alison M., Renton, Alan E., Picarello, Danielle M., Benzinger, Tammie, Gordon, Brian A., Hornbeck, Russall, Hassenstab, Jason, Smith, Jennifer, Stout, Sarah, Aschenbrenner, Andrew J., Karch, Celeste M., Marsh, Jacob, Morris, John C., Holtzman, David M., Barthelemy, Nicolas, Xu, Jinbin, Noble, James M., Berman, Sarah B., Ikonomovic, Snezana, Nadkarni, Neelesh K., Day, Gregory, Graff-Radford, Neill R., Farlow, Martin, Chhatwal, Jasmeer P., Ikeuchi, Takeshi, Kasuga, Kensaku, Niimi, Yoshiki, Huey, Edward D., Salloway, Stephen, Schofield, Peter R., Brooks, William S., Bechara, Jacob A., Martins, Ralph, Fox, Nick C., Cash, David M., Ryan, Natalie S., Jucker, Mathias, Laske, Christoph, Hofmann, Anna, Kuder-Buletta, Elke, Graber-Sultan, Susanne, Obermueller, Ulrike, Levin, Johannes, Roedenbeck, Yvonne, Vöglein, Jonathan, Lee, Jae-Hong, Roh, Jee Hoon, Sanchez-Valle, Raquel, Rosa-Neto, Pedro, Allegri, Ricardo F., Chrem Mendez, Patricio, Surace, Ezequiel, Vazquez, Silvia, Lopera, Francisco, Leon, Yudy Milena, Ramirez, Laura, Aguillon, David, Levey, Allan I., Johnson, Erik C.B, Seyfried, Nicholas T., Ringman, John, Mori, Hiroshi, Wisch, Julie K, McKay, Nicole S, Boerwinkle, Anna H, Kennedy, James, Flores, Shaney, Handen, Benjamin L, Christian, Bradley T, Head, Elizabeth, Mapstone, Mark, Rafii, Michael S, O’Bryant, Sid E, Price, Julie C, Laymon, Charles M, Krinsky-McHale, Sharon J, Lai, Florence, Rosas, H Diana, Hartley, Sigan L, Lott, Ira T, Tudorascu, Dana, Zammit, Matthew, Brickman, Adam M, Lee, Joseph H, Bird, Thomas D, Cohen, Annie, Chrem, Patricio, Daniels, Alisha, Chhatwal, Jasmeer P, Karch, Celeste M, Day, Gregory S, Llibre-Guerra, Jorge, Ringman, John M, van Dyck, Christopher H, Xiong, Chengjie, Morris, John C, Bateman, Randall J, Benzinger, Tammie L S, Gordon, Brian A, and Ances, Beau M

Published
2024
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24. Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging

Author

Noble, James M., Day, Gregory S., Graff-Radford, Neill R., Voglein, Jonathan, Levin, Johannes, Allegri, Ricardo F., Mendez, Patricio Chrem, Surace, Ezequiel, Berman, Sarah B., Ikonomovic, Snezana, Nadkarni, Neelesh K., Lopera, Francisco, Ramirez, Laura, Aguillon, David, Leon, Yudy, Ramos, Claudia, Alzate, Diana, Baena, Ana, Londono, Natalia, Moreno, Sonia, Jucker, Mathias, Laske, Christoph, Kuder-Buletta, Elke, Graber-Sultan, Susanne, Preische, Oliver, Hofmann, Anna, Ikeuchi, Takeshi, Kasuga, Kensaku, Niimi, Yoshiki, Ishii, Kenji, Senda, Michio, Sanchez-Valle, Raquel, Rosa-Neto, Pedro, Fox, Nick C., Cash, Dave, Lee, Jae-Hong, Roh, Jee Hoon, Salloway, Stephen, Riddle, Meghan C., Menard, William, Bodge, Courtney, Surti, Mustafa, Takada, Leonel Tadao, Farlow, Martin, Chhatwal, Jasmeer P., Sanchez-Gonzalez, V.J., Orozco-Barajas, Maribel, Goate, Alison M., Renton, Alan E., Esposito, Bianca T., Karch, Celeste M., Marsh, Jacob, Cruchaga, Carlos, Fernanadez, Victoria, Gordon, Brian A., Fagan, Anne M., Jerome, Gina, Herries, Elizabeth, Llibre-Guerra, Jorge, Levey, Allan I., Johnson, Erik C.B., Seyfried, Nicholas T., Schofield, Peter R., Brooks, William S., Bechara, Jacob A., Bateman, Randall, McDade, Eric, Hassenstab, Jason, Perrin, Richard J., Franklin, Erin E., Benzinger, Tammie, Chen, Allison, Chen, Charles, Flores, Shaney, Friedrichsen, Nelly, Gordon, Brian, Hantler, Nancy, Hornbeck, Russ, Jarman, Steve, Keefe, Sarah, Koudelis, Deborah, Massoumzadeh, Parinaz, McCullough, Austin, McKay, Nicole, Nicklaus, Joyce, Pulizos, Christine, Wang, Qing, Mishall, Sheetal, Sabaredzovic, Edita, Deng, Emily, Candela, Madison, Smith, Hunter, Hobbs, Diana, Scott, Jalen, Xiong, Chengjie, Wang, Peter, Xu, Xiong, Li, Yan, Gremminger, Emily, Ma, Yinjiao, Bui, Ryan, Lu, Ruijin, Martins, Ralph, Sosa Ortiz, Ana Luisa, Daniels, Alisha, Courtney, Laura, Mori, Hiroshi, Supnet-Bell, Charlene, Xu, Jinbin, Ringman, John, Barthelemy, Nicolas, Morris, John, Smith, Jennifer, Doering, Stephanie, Chen, Charles D., Jarman, Stephen, Jackson, Kelley, Hornbeck, Russ C., Ances, Beau M., Aschenbrenner, Andrew J., Bateman, Randall J., Morris, John C., and Benzinger, Tammie L.S.

Published
2024
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26. Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis

Author

Abdi, Zeinab, Agosta, Federica, Ahmed, Samrah, Alcolea, Daniel, Allen, Isabel Elaine, Allinson, Kieren S.J., Apostolova, Liana G., Arighi, Andrea, Balasa, Mircea, Barkhof, Frederik, Best, John, Boon, Baayla D., Brandt, Katherine D., Brosch, Jared, Burrell, James, Butler, Christopher R., Calandri, Ismael, Caminiti, Silvia Paola, Canu, Elisa, Carrillo, Maria C., Caso, Francesca, Chapleau, Marianne, Chrem Mendez, Patricio, Chu, Min, Crutch, Sebastian, Cordato, Nicholas, Costa, Ana Sofia, Cui, Yue, Dickerson, Bradford, Dickson, Dennis W., Duara, Ranjan, Dubois, Bruno, Eldaief, Mark, Farlow, Martin, Fenoglio, Chiara, Filippi, Massimo, Fliessbach, Klaus, Formaglio, Maïté, Fortea, Juan, Fox, Nick, Foxe, David, Tilikete, Caroline Froment, Frosch, Matthew P., Fumagalli, Giorgio Giulio, Galasko, Douglas, Galimberti, Daniela, Garat, Oscar, Giardinieri, Giulia, Graff-Radford, Jonathan, Graff-Radford, Neill R., Grinberg, Lea, Groot, Colin, Hake, Ann Marie, Hansson, Oskar, Headley, Alison, Hernandez, Micaela, Hochberg, Daisy, Hodges, John R., Hof, Patrick R., Holton, Janice, Hromas, Gabrielle, Gala, Ignacio Illán, Irwin, David J., Jaunmuktane, Zane, Jing, Donglai, Josephs, Keith, Kagerer, Sonja M., Kasuga, Kensaku, Kong, Yu, Kövari, Enikö, Lacombe-Thibault, Mégane, Lleó, Alberto, Laforce, Robert, La Joie, Renaud, Lashley, Tammaryn, Leger, Gabriel, Levin, Netta, Levy, Richard, Liu, Yang, Liu, Li, Lladó Plarrumaní, Albert, Lucente, Diane E., Machulda, Mary M., Magnani, Giuseppe, Magnin, Eloi, Malpetti, Maura, Matthews, Brandy, McGinnis, Scott, Mendez, Mario F., Mesulam, Marsel, Migliaccio, Raffaella, Miklitz, Carolin, Miller, Zachary A., Montembeault, Maxime, Murray, Melissa E., Mundada, Nidhi, Nemes, Sara, Nestor, Peter J., Ocal, Dilek, Ossenkoppele, Rik, Paterson, Ross, Pelak, Victoria, Perani, Daniela, Phillips, Jeffrey, Piguet, Olivier, Pijnenburg, Yolande, Putcha, Deepti, Quimby, Megan, Rabinovici, Gil D., Reetz, Kathrin, Rein, Netaniel, Revesz, Tamas, Rezaii, Neguine, Rodriguez-Porcel, Federico, Rogalski, Emily, Rowe, James B., Ryan, Natalie, Sanchez-Valle, Raquel, Sacchi, Luca, Santos-Santos, Miguel Ángel, Schott, Jonathan M., Seeley, William, Sherman, Janet, Spina, Salvatore, Stomrud, Erik, Sullivan, A. Campbell, Tanner, Jeremy, Tideman, Pontus, Tokutake, Takayoshi, Tondo, Giacomo, Touroutoglou, Alexandra, Tousi, Babak, Vandenberghe, Rik, van der Flier, Wiesje, Walker, Jamie M., Weintraub, Sandra, Whitwell, Jennifer L., Wolk, David A., Wong, Bonnie, Wu, Liyong, Xie, Kexin, Yong, Keir, Apostolova, Liana, Boon, Baayla D C, Grinberg, Lea T, Irwin, David J, Josephs, Keith A, Mendez, Mario F, Mendez, Patricio Chrem, Miller, Zachary A, Murray, Melissa E, Nemes, Sára, Schott, Jonathan M, Sullivan, A Campbell, Walker, Jamie, Whitwell, Jennifer L, Wolk, David A, and Rabinovici, Gil D

Published
2024
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27. The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

Author

Marinescu, Razvan V., Oxtoby, Neil P., Young, Alexandra L., Bron, Esther E., Toga, Arthur W., Weiner, Michael W., Barkhof, Frederik, Fox, Nick C., Eshaghi, Arman, Toni, Tina, Salaterski, Marcin, Lunina, Veronika, Ansart, Manon, Durrleman, Stanley, Lu, Pascal, Iddi, Samuel, Li, Dan, Thompson, Wesley K., Donohue, Michael C., Nahon, Aviv, Levy, Yarden, Halbersberg, Dan, Cohen, Mariya, Liao, Huiling, Li, Tengfei, Yu, Kaixian, Zhu, Hongtu, Tamez-Pena, Jose G., Ismail, Aya, Wood, Timothy, Bravo, Hector Corrada, Nguyen, Minh, Sun, Nanbo, Feng, Jiashi, Yeo, B. T. Thomas, Chen, Gang, Qi, Ke, Chen, Shiyang, Qiu, Deqiang, Buciuman, Ionut, Kelner, Alex, Pop, Raluca, Rimocea, Denisa, Ghazi, Mostafa M., Nielsen, Mads, Ourselin, Sebastien, Sorensen, Lauge, Venkatraghavan, Vikram, Liu, Keli, Rabe, Christina, Manser, Paul, Hill, Steven M., Howlett, James, Huang, Zhiyue, Kiddle, Steven, Mukherjee, Sach, Rouanet, Anais, Taschler, Bernd, Tom, Brian D. M., White, Simon R., Faux, Noel, Sedai, Suman, Oriol, Javier de Velasco, Clemente, Edgar E. V., Estrada, Karol, Aksman, Leon, Altmann, Andre, Stonnington, Cynthia M., Wang, Yalin, Wu, Jianfeng, Devadas, Vivek, Fourrier, Clementine, Raket, Lars Lau, Sotiras, Aristeidis, Erus, Guray, Doshi, Jimit, Davatzikos, Christos, Vogel, Jacob, Doyle, Andrew, Tam, Angela, Diaz-Papkovich, Alex, Jammeh, Emmanuel, Koval, Igor, Moore, Paul, Lyons, Terry J., Gallacher, John, Tohka, Jussi, Ciszek, Robert, Jedynak, Bruno, Pandya, Kruti, Bilgel, Murat, Engels, William, Cole, Joseph, Golland, Polina, Klein, Stefan, and Alexander, Daniel C.

Subjects
Quantitative Biology - Populations and Evolution, Statistics - Applications
Abstract

We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of biomarkers. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials., Comment: Presents final results of the TADPOLE competition. 60 pages, 7 tables, 14 figures

Published
2020

28. TADPOLE Challenge: Accurate Alzheimer's disease prediction through crowdsourced forecasting of future data

Author

Marinescu, Razvan V., Oxtoby, Neil P., Young, Alexandra L., Bron, Esther E., Toga, Arthur W., Weiner, Michael W., Barkhof, Frederik, Fox, Nick C., Golland, Polina, Klein, Stefan, and Alexander, Daniel C.

Subjects
Quantitative Biology - Populations and Evolution, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Applications
Abstract

The TADPOLE Challenge compares the performance of algorithms at predicting the future evolution of individuals at risk of Alzheimer's disease. TADPOLE Challenge participants train their models and algorithms on historical data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Participants are then required to make forecasts of three key outcomes for ADNI-3 rollover participants: clinical diagnosis, ADAS-Cog 13, and total volume of the ventricles -- which are then compared with future measurements. Strong points of the challenge are that the test data did not exist at the time of forecasting (it was acquired afterwards), and that it focuses on the challenging problem of cohort selection for clinical trials by identifying fast progressors. The submission phase of TADPOLE was open until 15 November 2017; since then data has been acquired until April 2019 from 219 subjects with 223 clinical visits and 150 Magnetic Resonance Imaging (MRI) scans, which was used for the evaluation of the participants' predictions. Thirty-three teams participated with a total of 92 submissions. No single submission was best at predicting all three outcomes. For diagnosis prediction, the best forecast (team Frog), which was based on gradient boosting, obtained a multiclass area under the receiver-operating curve (MAUC) of 0.931, while for ventricle prediction the best forecast (team EMC1), which was based on disease progression modelling and spline regression, obtained mean absolute error of 0.41% of total intracranial volume (ICV). For ADAS-Cog 13, no forecast was considerably better than the benchmark mixed effects model (BenchmarkME), provided to participants before the submission deadline. Further analysis can help understand which input features and algorithms are most suitable for Alzheimer's disease prediction and for aiding patient stratification in clinical trials., Comment: 10 pages, 1 figure, 4 tables. arXiv admin note: substantial text overlap with arXiv:1805.03909

Published
2020
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29. Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Author

Kaddurah-Daouk, Rima, Kueider-Paisley, Alexandra, Doraiswamy, P. Murali, Blach, Colette, Moseley, Arthur, Thompson, Will, St John-Williams, Lisa, Mahmoudiandehkhordi, Siamak, Tenenbaum, Jessica, Welsh-Balmer, Kathleen, Plassman, Brenda, Saykin, Andrew J., Nho, Kwangsik, Risacher, Shannon L., Kastenmüller, Gabi, Arnold, Matthias, Han, Xianlin, Baillie, Rebecca, Knight, Rob, Dorrestein, Pieter, Brewer, James, Mayer, Emeran, Labus, Jennifer, Baldi, Pierre, Gupta, Arpana, Fiehn, Oliver, Barupal, Dinesh, Meikle, Peter, Mazmanian, Sarkis, Rader, Dan, Kling, Mitchel, Shaw, Leslie, Trojanowski, John, van Duijin, Cornelia, Nevado-Holgado, Alejo, Bennett, David, Krishnan, Ranga, Keshavarzian, Ali, Vogt, Robin, Ikram, Arfan, Hankemeier, Thomas, Thiele, Ines, Price, Nathan, Funk, Cory, Baloni, Priyanka, Jia, Wei, Wishart, David, Brinton, Roberta, Chang, Rui, Farrer, Lindsay, Au, Rhoda, Qiu, Wendy, Würtz, Peter, Koal, Therese, Mangravite, Lara, Krumsiek, Jan, Suhre, Karsten, Newman, John, Moreno, Herman, Foroud, Tatania, Sacks, Frank, Jansson, Janet, Weiner, Michael W., Aisen, Paul, Petersen, Ronald, Jack, Clifford R., Jr., Jagust, William, Trojanowki, John Q., Toga, Arthur W., Beckett, Laurel, Green, Robert C., Morris, John C., Perrin, Richard J., Shaw, Leslie M., Khachaturian, Zaven, Carrillo, Maria, Potter, William, Barnes, Lisa, Bernard, Marie, Gonzalez, Hector, Ho, Carole, Hsiao, John K., Jackson, Jonathan, Masliah, Eliezer, Masterman, Donna, Okonkwo, Ozioma, Perrin, Richard, Ryan, Laurie, Silverberg, Nina, Fleisher, Adam, Sacrey, Diana Truran, Fockler, Juliet, Conti, Cat, Veitch, Dallas, Neuhaus, John, Jin, Chengshi, Nosheny, Rachel, Ashford, Miriam, Flenniken, Derek, Kormos, Adrienne, Montine, Tom, Rafii, Michael, Raman, Rema, Jimenez, Gustavo, Donohue, Michael, Gessert, Devon, Salazar, Jennifer, Zimmerman, Caileigh, Cabrera, Yuliana, Walter, Sarah, Miller, Garrett, Coker, Godfrey, Clanton, Taylor, Hergesheimer, Lindsey, Smith, Stephanie, Adegoke, Olusegun, Mahboubi, Payam, Moore, Shelley, Pizzola, Jeremy, Shaffer, Elizabeth, Sloan, Brittany, Harvey, Danielle, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Schwarz, Christopher, Jones, David, Gunter, Jeff, Kantarci, Kejal, Senjem, Matthew, Vemuri, Prashanthi, Reid, Robert, Fox, Nick C., Malone, Ian, Thompson, Paul, Thomopoulos, Sophia I., Nir, Talia M., Jahanshad, Neda, DeCarli, Charles, Knaack, Alexander, Fletcher, Evan, Tosun-Turgut, Duygu, Chen, Stephanie Rossi, Choe, Mark, Crawford, Karen, Yushkevich, Paul A., Das, Sandhitsu, Koeppe, Robert A., Reiman, Eric M., Chen, Kewei, Mathis, Chet, Landau, Susan, Cairns, Nigel J., Householder, Erin, Franklin, Erin, Bernhardt, Haley, Taylor-Reinwald, Lisa, Korecka, Magdalena, Figurski, Michal, Neu, Scott, Apostolova, Liana G., Shen, Li, Foroud, Tatiana M., Nudelman, Kelly, Faber, Kelley, Wilmes, Kristi, Thal, Leon, Silbert, Lisa C., Lind, Betty, Crissey, Rachel, Kaye, Jeffrey A., Carter, Raina, Dolen, Sara, Quinn, Joseph, Schneider, Lon S., Pawluczyk, Sonia, Becerra, Mauricio, Teodoro, Liberty, Dagerman, Karen, Spann, Bryan M., Vanderswag, Helen, Ziolkowski, Jaimie, Heidebrink, Judith L., Zbizek-Nulph, Lisa, Lord, Joanne L., Mason, Sara S., Albers, Colleen S., Knopman, David, Johnson, Kris, Villanueva-Meyer, Javier, Pavlik, Valory, Pacini, Nathaniel, Lamb, Ashley, Kass, Joseph S., Doody, Rachelle S., Shibley, Victoria, Chowdhury, Munir, Rountree, Susan, Dang, Mimi, Stern, Yaakov, Honig, Lawrence S., Mintz, Akiva, Ances, Beau, Winkfield, David, Carroll, Maria, Stobbs-Cucchi, Georgia, Oliver, Angela, Creech, Mary L., Mintun, Mark A., Schneider, Stacy, Geldmacher, David, Love, Marissa Natelson, Griffith, Randall, Clark, David, Brockington, John, Marson, Daniel, Grossman, Hillel, Goldstein, Martin A., Greenberg, Jonathan, Mitsis, Effie, Shah, Raj C., Lamar, Melissa, Samuels, Patricia, Duara, Ranjan, Greig-Custo, Maria T., Rodriguez, Rosemarie, Albert, Marilyn, Onyike, Chiadi, Farrington, Leonie, Rudow, Scott, Brichko, Rottislav, Kielb, Stephanie, Smith, Amanda, Raj, Balebail Ashok, Fargher, Kristin, Sadowski, Martin, Wisniewski, Thomas, Shulman, Melanie, Faustin, Arline, Rao, Julia, Castro, Karen M., Ulysse, Anaztasia, Chen, Shannon, Sheikh, Mohammed O., Singleton-Garvin, Jamika, Petrella, JeffreyR., James, Olga, Wong, Terence Z., Borges-Neto, Salvador, Karlawish, Jason H., Wolk, David A., Vaishnavi, Sanjeev, Clark, Christopher M., Arnold, Steven E., Smith, Charles D., Jicha, Gregory A., Raslau, Flavius D., Lopez, Oscar L., Oakley, MaryAnn, Simpson, Donna M., Porsteinsson, Anton P., Martin, Kim, Kowalski, Nancy, Keltz, Melanie, Goldstein, Bonnie S., Makino, Kelly M., Ismail, M. Saleem, Brand, Connie, Thai, Gaby, Pierce, Aimee, Yanez, Beatriz, Sosa, Elizabeth, Witbracht, Megan, Kelley, Brendan, Nguyen, Trung, Womack, Kyle, Mathews, Dana, Quiceno, Mary, Levey, Allan I., Lah, James J., Hajjar, Ihab, Cellar, Janet S., Burns, Jeffrey M., Swerdlow, Russell H., Brooks, William M., Silverman, Daniel H.S., Kremen, Sarah, Apostolova, Liana, Tingus, Kathleen, Lu, Po H., Bartzokis, George, Woo, Ellen, Teng, Edmond, Graff-Radford, Neill R., Parfitt, Francine, Poki-Walker, Kim, Farlow, Martin R., Hake, Ann Marie, Matthews, Brandy R., Brosch, Jared R., Herring, Scott, van, Christopher H., Mecca, Adam P., Good, Susan P., MacAvoy, Martha G., Carson, Richard E., Varma, Pradeep, Chertkow, Howard, Vaitekunis, Susan, Hosein, Chris, Black, Sandra, Stefanovic, Bojana, Heyn, Chris (Chinthaka), Robin Hsiung, Ging-Yuek, Kim, Ellen, Mudge, Benita, Sossi, Vesna, Feldman, Howard, Assaly, Michele, Finger, Elizabeth, Pasternak, Stephen, Rachinsky, Irina, Kertesz, Andrew, Drost, Dick, Rogers, John, Grant, Ian, Muse, Brittanie, Rogalski, Emily, Robson, Jordan, Mesulam, M.-Marsel, Kerwin, Diana, Wu, Chuang-Kuo, Johnson, Nancy, Lipowski, Kristine, Weintraub, Sandra, Bonakdarpour, Borna, Pomara, Nunzio, Hernando, Raymundo, Sarrael, Antero, Rosen, Howard J., Miller, Bruce L., Perry, David, Turner, Raymond Scott, Johnson, Kathleen, Reynolds, Brigid, MCCann, Kelly, Poe, Jessica, Sperling, Reisa A., Johnson, Keith A., Marshall, Gad A., Yesavage, Jerome, Taylor, Joy L., Chao, Steven, Coleman, Jaila, White, Jessica D., Lane, Barton, Rosen, Allyson, Tinklenberg, Jared, Belden, Christine M., Atri, Alireza, Clark, Kelly A., Zamrini, Edward, Sabbagh, Marwan, Killiany, Ronald, Stern, Robert, Mez, Jesse, Kowall, Neil, Budson, Andrew E., Obisesan, Thomas O., Ntekim, Oyonumo E., Wolday, Saba, Khan, Javed I., Nwulia, Evaristus, Nadarajah, Sheeba, Lerner, Alan, Ogrocki, Paula, Tatsuoka, Curtis, Fatica, Parianne, Maillard, Pauline, Olichney, John, Carmichael, Owen, Bates, Vernice, Capote, Horacio, Rainka, Michelle, Borrie, Michael, Lee, T.-Y., Bartha, Dr Rob, Johnson, Sterling, Asthana, Sanjay, Carlsson, Cynthia M., Perrin, Allison, Burke, Anna, Scharre, Douglas W., Kataki, Maria, Tarawneh, Rawan, Hart, David, Zimmerman, Earl A., Celmins, Dzintra, Miller, Delwyn D., BolesPonto, Laura L., Smith, Karen Ekstam, Koleva, Hristina, Shim, Hyungsub, Nam, Ki Won, Schultz, Susan K., Williamson, Jeff D., Craft, Suzanne, Cleveland, Jo, Yang, Mia, Sink, Kaycee M., Ott, Brian R., Drake, Jonathan, Tremont, Geoffrey, Daiello, Lori A., Drake, Jonathan D., Ritter, Aaron, Bernick, Charles, Munic, Donna, O'Connelll, Abigail, Mintzer, Jacobo, Wiliams, Arthur, Masdeu, Joseph, Shi, Jiong, Garcia, Angelica, Newhouse, Paul, Potkin, Steven, Salloway, Stephen, Malloy, Paul, Correia, Stephen, Kittur, Smita, Pearlson, Godfrey D., Blank, Karen, Anderson, Karen, Flashman, Laura A., Seltzer, Marc, Hynes, Mary L., Santulli, Robert B., Relkin, Norman, Chiang, Gloria, Lee, Athena, Lin, Michael, Ravdin, Lisa, Petersen, Ron, Neylan, Thomas, Grafman, Jordan, Danowski, Sarah, Nguyen-Barrera, Catherine, Hayes, Jacqueline, Finley, Shannon, Bernstein, Matthew, Senjem, Matt, Foster, Norm, Kim, Sungeun, Sood, Ajay, Blanchard, Kimberly S., Fleischman, Debra, Arfanakis, Konstantinos, Varon, Daniel, Greig, Maria T., Petrella, Jeffrey R., Goldstein, Bonnie, Martin, Kimberly S., Reist, Christopher, Sadowsky, Carl, Martinez, Walter, Villena, Teresa, Rosen, Howard, Marshall, Gad, Peskind, Elaine R., Petrie, Eric C., Li, Gail, Mackin, Scott, Jimenez-Maggiora, Gustavo, Drake, Erin, Donohue, Mike, Nelson, Craig, Bickford, David, Butters, Meryl, Zmuda, Michelle, Reyes, Denise, Faber, Kelley M., Nudelman, Kelly N., Au, Yiu Ho, Scherer, Kelly, Catalinotto, Daniel, Stark, Samuel, Ong, Elise, Fernandez, Dariella, Jo, Taeho, Kim, Junpyo, Bice, Paula, Huynh, Kevin, Wang, Tingting, Meikle, Peter J., and Giles, Corey

Published
2023
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30. In vivo Analysis of Normal Optic Nerve in an Elderly Population Using Diffusion Magnetic Resonance Imaging Tractography

Author

Moon, Yeji, Yang, Jin-Ju, Lee, Won June, Lee, Ji Young, Kim, Yu Jeong, Lim, Han Woong, Initiative, The Alzheimer's Disease Neuroimaging, Weiner, Michael W, Aisen, Paul, Petersen, Ronald, Jack, Clifford, Bernstein, Matthew, Fox, Nick, Thompson, Paul, Schuff, Norbert, DeCArli, Charles, Borowski, Bret, Gunter, Jeff, Senjem, Matt, Vemuri, Prashanthi, Jones, David, Kantarci, Kejal, Ward, Chad, and Beckett, Laurel

Subjects
Biomedical and Clinical Sciences, Ophthalmology and Optometry, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Biomedical Imaging, Brain Disorders, Acquired Cognitive Impairment, Neurosciences, Neurological, Alzheimer's Disease Neuroimaging Initiative, diffusion magnetic resonance imaging, fractional anisotropy, mean diffusivity, optic nerve, tractography, Clinical Sciences, Psychology, Clinical sciences, Biological psychology
Abstract

Purpose: To quantitatively investigate the microstructural properties of the optic nerve (ON) in vivo using diffusion magnetic resonance imaging (dMRI) tractography in an elderly population and to determine the differences between the ON diffusion properties stratified by basic demographics. Methods: We measured fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) of the intraorbital ON in cognitively normal controls selected from the Alzheimer's Disease Neuroimaging Initiative 3 database (n =104; mean age = 73. 8 ± 8.1 years) using dMRI probabilistic tractography and evaluated the correlation between diffusion parameters and demographic factors. Diffusion parameters were measured in 20 equidistant nodes along the tract, and the data from proximal 70% (14 nodes) of the intraorbital ON were averaged. Results: The mean FA of the intraorbital ON was 0.392 ± 0.063, and the mean MD was 1.163 ± 0.165 μm2/s. The mean RD was 0.882 ± 0.152 μm2/s, and the mean AD was 1.693 ± 0.183 μm2/s. The multiple linear regression model showed a negative correlation between FA and age. FA in females was significantly higher than males, whereas RD in female was significantly lower. Conclusions: We measured the diffusion properties of the intraorbital ON using dMRI tractography in an elderly cognitively normal population. The diffusion properties detected by dMRI tractography may substantially reflect the microstructure of the ON.

Published
2021

31. Doing New Materialist Data Analysis: A Spinozo-Deleuzian Ethological Toolkit

Author

Fox, Nick J. and Alldred, Pam

Abstract

With growing social science interest in new materialist and posthuman ontologies, it is timely to explore how these may translate practically into social research methodologies. This task is complicated by differing interpretations of how new materialist precepts should shape research. This paper aims to fill a gap in the literature by setting out a methodology using one specific thread within the new materialisms: Deleuzian 'ethology'. Inspired by Spinoza's "Ethics," Deleuze established a conceptual toolkit for ethological inquiry, comprising 'relation', 'assemblage', 'affect' and 'capacity'. We show how this toolkit translates into a design for analysing empirical data. Effective data analysis also depends on the adequacy and appropriateness of earlier stages in the research process. We therefore also consider an ethological approach to setting a research question, choosing data collection methods and presenting study findings. We conclude with some reflections on the challenges of translating philosophical theory into social science methodology.

Published
2022
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33. The Secret Service Is Becoming a Symbol of Incompetence

Author

Fox, Nick

Subjects
United States. Secret Service, Ex-presidents, News, opinion and commentary
Abstract

After Kimberly Cheatle’s insultingly evasive congressional testimony on Monday — though even she acknowledged the colossal failure of the agency she leads, the United States Secret Service, to deter the [...]

Published
2024

34. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission

Author

Livingston, Gill, Huntley, Jonathan, Sommerlad, Andrew, Ames, David, Ballard, Clive, Banerjee, Sube, Brayne, Carol, Burns, Alistair, Cohen-Mansfield, Jiska, Cooper, Claudia, Costafreda, Sergi G, Dias, Amit, Fox, Nick, Gitlin, Laura N, Howard, Robert, Kales, Helen C, Kivimäki, Mika, Larson, Eric B, Ogunniyi, Adesola, Orgeta, Vasiliki, Ritchie, Karen, Rockwood, Kenneth, Sampson, Elizabeth L, Samus, Quincy, Schneider, Lon S, Selbæk, Geir, Teri, Linda, and Mukadam, Naaheed

Subjects
Air Pollution, Alcoholism, Craniocerebral Trauma, Dementia, Health Policy, Healthcare Disparities, Healthy Lifestyle, Humans, Risk Factors, Medical and Health Sciences, General & Internal Medicine
Published
2020

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

Author

Moore, Katrina M, Nicholas, Jennifer, Grossman, Murray, McMillan, Corey T, Irwin, David J, Massimo, Lauren, Van Deerlin, Vivianna M, Warren, Jason D, Fox, Nick C, Rossor, Martin N, Mead, Simon, Bocchetta, Martina, Boeve, Bradley F, Knopman, David S, Graff-Radford, Neill R, Forsberg, Leah K, Rademakers, Rosa, Wszolek, Zbigniew K, van Swieten, John C, Jiskoot, Lize C, Meeter, Lieke H, Dopper, Elise Gp, Papma, Janne M, Snowden, Julie S, Saxon, Jennifer, Jones, Matthew, Pickering-Brown, Stuart, Le Ber, Isabelle, Camuzat, Agnès, Brice, Alexis, Caroppo, Paola, Ghidoni, Roberta, Pievani, Michela, Benussi, Luisa, Binetti, Giuliano, Dickerson, Bradford C, Lucente, Diane, Krivensky, Samantha, Graff, Caroline, Öijerstedt, Linn, Fallström, Marie, Thonberg, Håkan, Ghoshal, Nupur, Morris, John C, Borroni, Barbara, Benussi, Alberto, Padovani, Alessandro, Galimberti, Daniela, Scarpini, Elio, Fumagalli, Giorgio G, Mackenzie, Ian R, Hsiung, Ging-Yuek R, Sengdy, Pheth, Boxer, Adam L, Rosen, Howie, Taylor, Joanne B, Synofzik, Matthis, Wilke, Carlo, Sulzer, Patricia, Hodges, John R, Halliday, Glenda, Kwok, John, Sanchez-Valle, Raquel, Lladó, Albert, Borrego-Ecija, Sergi, Santana, Isabel, Almeida, Maria Rosário, Tábuas-Pereira, Miguel, Moreno, Fermin, Barandiaran, Myriam, Indakoetxea, Begoña, Levin, Johannes, Danek, Adrian, Rowe, James B, Cope, Thomas E, Otto, Markus, Anderl-Straub, Sarah, de Mendonça, Alexandre, Maruta, Carolina, Masellis, Mario, Black, Sandra E, Couratier, Philippe, Lautrette, Geraldine, Huey, Edward D, Sorbi, Sandro, Nacmias, Benedetta, Laforce, Robert, Tremblay, Marie-Pier L, Vandenberghe, Rik, Damme, Philip Van, Rogalski, Emily J, Weintraub, Sandra, Gerhard, Alexander, Onyike, Chiadi U, Ducharme, Simon, Papageorgiou, Sokratis G, Ng, Adeline Su Lyn, Brodtmann, Amy, Finger, Elizabeth, and Guerreiro, Rita

Subjects
FTD Prevention Initiative, Humans, Disease Progression, tau Proteins, Retrospective Studies, Cohort Studies, Family, Age of Onset, Phenotype, Mutation, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Frontotemporal Dementia, C9orf72 Protein, Progranulins, Clinical Research, Rare Diseases, Dementia, Aging, Brain Disorders, Genetic Testing, Neurodegenerative, Neurosciences, Alzheimer's Disease Related Dementias (ADRD), Prevention, Genetics, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 2.1 Biological and endogenous factors, Neurological, Neurology & Neurosurgery, Clinical Sciences
Abstract

BackgroundFrontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72.MethodsIn this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried.FindingsData were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49·5 years (SD 10·0; onset) and 58·5 years (11·3; death) in the MAPT group, 58·2 years (9·8; onset) and 65·3 years (10·9; death) in the C9orf72 group, and 61·3 years (8·8; onset) and 68·8 years (9·7; death) in the GRN group. Mean disease duration was 6·4 years (SD 4·9) in the C9orf72 group, 7·1 years (3·9) in the GRN group, and 9·3 years (6·4) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0·45 between individual and parental age at onset, r=0·63 between individual and mean family age at onset, r=0·58 between individual and parental age at death, and r=0·69 between individual and mean family age at death) than in either the C9orf72 group (r=0·32 individual and parental age at onset, r=0·36 individual and mean family age at onset, r=0·38 individual and parental age at death, and r=0·40 individual and mean family age at death) or the GRN group (r=0·22 individual and parental age at onset, r=0·18 individual and mean family age at onset, r=0·22 individual and parental age at death, and r=0·32 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35-62, for age at onset; 61%, 47-73, for age at death), and even more by family membership (66%, 56-75, for age at onset; 74%, 65-82, for age at death). In the GRN group, only 2% (0-10) of the variability of age at onset and 9% (3-21) of that of age of death was explained by the specific mutation, whereas 14% (9-22) of the variability of age at onset and 20% (12-30) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11-26) of the variability of age at onset and 19% (12-29) of that of age at death.InterpretationOur study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates.FundingUK Medical Research Council, National Institute for Health Research, and Alzheimer's Society.

Published
2020

36. Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Author

Dincer, Aylin, Gordon, Brian A, Hari-Raj, Amrita, Keefe, Sarah J, Flores, Shaney, McKay, Nicole S, Paulick, Angela M, Lewis, Kristine E Shady, Feldman, Rebecca L, Hornbeck, Russ C, Allegri, Ricardo, Ances, Beau M, Berman, Sarah B, Brickman, Adam M, Brooks, William S, Cash, David M, Chhatwal, Jasmeer P, Farlow, Martin R, la Fougère, Christian, Fox, Nick C, Fulham, Michael J, Jack, Clifford R, Joseph-Mathurin, Nelly, Karch, Celeste M, Lee, Athene, Levin, Johannes, Masters, Colin L, McDade, Eric M, Oh, Hwamee, Perrin, Richard J, Raji, Cyrus, Salloway, Stephen P, Schofield, Peter R, Su, Yi, Villemagne, Victor L, Wang, Qing, Weiner, Michael W, Xiong, Chengjie, Yakushev, Igor, Morris, John C, Bateman, Randall J, Benzinger, Tammie LS, and DIAN, for the Dominantly Inherited Alzheimer Network

Subjects
Neurodegenerative, Dementia, Clinical Research, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurosciences, Aging, Acquired Cognitive Impairment, Alzheimer's Disease, 2.1 Biological and endogenous factors, Aetiology, Neurological, Alzheimer Disease, Amyloid beta-Peptides, Atrophy, Hippocampus, Humans, Magnetic Resonance Imaging, Positron-Emission Tomography, Alzheimer disease, Autosomal dominant Alzheimer disease, Preclinical, Cortical signature, Amyloid, Cortical thickness, Dominantly Inherited Alzheimer Network DIAN
Abstract

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.

Published
2020

37. Women can bear a bigger burden: ante- and post-mortem evidence for reserve in the face of tau

Author

Digma, Leonardino A, Madsen, John R, Rissman, Robert A, Jacobs, Diane M, Brewer, James B, Banks, Sarah J, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Jagust, William, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Saykin, Andrew J, Morris, John, Shaw, Leslie M, Liu, Enchi, Montine, Tom, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Jiminez, Gus, Harvey, Danielle, Bernstein, Matthew, Fox, Nick, Thompson, Paul, Schuff, Norbert, DeCArli, Charles, Borowski, Bret, Gunter, Jeff, Senjem, Matt, Vemuri, Prashanthi, Jones, David, Kantarci, Kejal, Ward, Chad, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Landau, Susan, Cairns, Nigel J, Householder, Erin, Reinwald, Lisa Taylor, Lee, Virginia, Korecka, Magdalena, Figurski, Michal, Crawford, Karen, Neu, Scott, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kelley, Faber, Kim, Sungeun, Nho, Kwangsik, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lind, Betty, Carter, Raina, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Beccera, Mauricio, Teodoro, Liberty, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Fleisher, Adam, Heidebrink, Judith L, Lord, Joanne L, Mason, Sara S, Albers, Colleen S, Knopman, David, Johnson, Kris, Doody, Rachelle S, Meyer, Javier Villanueva, Chowdhury, Munir, Rountree, Susan, Dang, Mimi, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Ances, Beau, Morris, John C, Carroll, Maria, Leon, Sue, Mintun, Mark A, Schneider, Stacy, and Oliver, Angela

Subjects
Biological Psychology, Psychology, Brain Disorders, Neurodegenerative, Alzheimer's Disease, Neurosciences, Acquired Cognitive Impairment, Women's Health, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Clinical Research, tau, verbal memory, sex differences, Alzheimer's disease, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s disease, Clinical sciences, Biological psychology
Abstract

In this study, we aimed to assess whether women are able to withstand more tau before exhibiting verbal memory impairment. Using data from 121 amyloid-β-positive Alzheimer's Disease Neuroimaging Initiative participants, we fit a linear model with Rey Auditory Verbal Learning Test score as the response variable and tau-PET standard uptake value ratio as the predictor and took the residuals as an estimate of verbal memory reserve for each subject. Women demonstrated higher reserve (i.e. residuals), whether the Learning (t = 2.78, P = 0.006) or Delay (t = 2.14, P = 0.03) score from the Rey Auditory Verbal Learning Test was used as a measure of verbal memory ability. To validate these findings, we examined 662 National Alzheimer's Coordinating Center participants with a C2/C3 score (Consortium to Establish a Registry for Alzheimer's Disease) at autopsy. We stratified our National Alzheimer's Coordinating Center sample into Braak 1/2, Braak 3/4 and Braak 5/6 subgroups. Within each subgroup, we compared Logical Memory scores between men and women. Men had worse verbal memory scores within the Braak 1/2 (Logical Memory Immediate: β = -5.960 ± 1.517, P

Published
2020

38. Prioritization of Drug Targets for Neurodegenerative Diseases by Integrating Genetic and Proteomic Data From Brain and Blood

Author

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

Published
2023
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39. Adulthood cognitive trajectories over 26 years and brain health at 70 years of age: findings from the 1946 British Birth Cohort

Author

James, Sarah-Naomi, Nicholas, Jennifer M., Lu, Kirsty, Keshavan, Ashvini, Lane, Christopher A., Parker, Thomas, Buchanan, Sarah M., Keuss, Sarah E., Murray-Smith, Heidi, Wong, Andrew, Cash, David M., Malone, Ian B., Barnes, Josephine, Sudre, Carole H., Coath, William, Modat, Marc, Ourselin, Sebastien, Crutch, Sebastian J., Kuh, Diana, Fox, Nick C., Schott, Jonathan M., and Richards, Marcus

Published
2023
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40. Comparison of amyloid burden in individuals with Down syndrome versus autosomal dominant Alzheimer's disease: a cross-sectional study

Author

Aizenstein, Howard J, Andrews, Howard F, Bell, Karen, Birn, Rasmus M, Bulova, Peter, Cheema, Amrita, Chen, Kewei, Clare, Isabel, Clark, Lorraine, Cohen, Ann D, Constantino, John N, Doran, Eric W, Feingold, Eleanor, Foroud, Tatiana M, Hartley, Sigan L, Hom, Christy, Honig, Lawrence, Ikonomovic, Milos D, Johnson, Sterling C, Jordan, Courtney, Kamboh, M Ilyas, Keator, David, Klunk MD, William E, Kofler, Julia K, Kreisl, William C, Krinsky- McHale, Sharon J, Lao, Patrick, Laymon, Charles, Lott, Ira T, Lupson, Victoria, Mathis, Chester A, Minhas, Davneet S, Nadkarni, Neelesh, Pang, Deborah, Petersen, Melissa, Price, Julie C, Pulsifer, Margaret, Reiman, Eric, Rizvi, Batool, Sabbagh, Marwan N, Schupf, Nicole, Tudorascu, Dana L, Tumuluru, Rameshwari, Tycko, Benjamin, Varadarajan, Badri, White, Desiree A, Yassa, Michael A, Zaman, Shahid, Zhang, Fan, Adams, Sarah, Allegri, Ricardo, Araki, Aki, Barthelemy, Nicolas, Bechara, Jacob, Berman, Sarah, Bodge, Courtney, Brandon, Susan, Brooks, William, Brosch, Jared, Buck, Jill, Buckles, Virginia, Carter, Kathleen, Cash, Lisa, Mendez, Patricio C, Chua, Jasmin, Chui, Helena, Courtney, Laura, Day, Gregory, DeLaCruz, Chrismary, Denner, Darcy, Diffenbacher, Anna, Dincer, Aylin, Donahue, Tamara, Douglas, Jane, Duong, Duc, Egido, Noelia, Esposito, Bianca, Farlow, Marty, Feldman, Becca, Fitzpatrick, Colleen, Fox, Nick, Franklin, Erin, Joseph-Mathurin, Nelly, Fujii, Hisako, Gardener, Samantha, Ghetti, Bernardino, Goate, Alison, Goldberg, Sarah, Goldman, Jill, Gonzalez, Alyssa, Gräber-Sultan, Susanne, Graff-Radford, Neill, Graham, Morgan, Gray, Julia, Gremminger, Emily, Grilo, Miguel, Groves, Alex, Haass, Christian, Häslerc, Lisa, Hellm, Cortaiga, Herries, Elizabeth, Hoechst-Swisher, Laura, Hofmann, Anna, Holtzman, David, Hornbeck, Russ, Igor, Yakushev, Ihara, Ryoko, Ikeuchi, Takeshi, Ikonomovic, Snezana, Ishii, Kenji, Jack, Clifford, Jerome, Gina, Johnson, Erik, Jucker, Mathias, Karch, Celeste, Käser, Stephan, Kasuga, Kensaku, Keefe, Sarah, Klunk, William, Koeppe, Robert, Koudelis, Deb, Kuder-Buletta, Elke, Laske, Christoph, Levey, Allan, Levin, Johannes, Li, Yan, Lopez, Oscar, Marsh, Jacob, Martins, Ralph, Mason, Neal S, Masters, Colin, Mawuenyega, Kwasi, McCullough, Austin, Mejia, Arlene, Morenas-Rodriguez, Estrella, Morris, John C, Mountz, James, Mummery, Catherine, Nagamatsu, Akemi, Neimeyer, Katie, Niimi, Yoshiki, Noble, James, Norton, Joanne, Nuscher, Brigitte, Obermüller, Ulricke, O'Connor, Antoinette, Patira, Riddhi, Ping, Lingyan, Preische, Oliver, Renton, Alan, Ringman, John, Salloway, Stephen, Schofield, Peter, Senda, Michio, Seyfried, Nicholas T, Shady, Kristine, Shimada, Hiroyuki, Sigurdson, Wendy, Smith, Jennifer, Smith, Lori, Snitz, Beth, Sohrabi, Hamid, Stephens, Sochenda, Taddei, Kevin, Thompson, Sarah, Vöglein, Jonathan, Wang, Peter, Wang, Qing, Weamer, Elise, Xu, Jinbin, Xu, Xiong, Boerwinkle, Anna H, Gordon, Brian A, Wisch, Julie, Flores, Shaney, Henson, Rachel L, Butt, Omar H, McKay, Nicole, Chen, Charles D, Benzinger, Tammie L S, Fagan, Anne M, Handen, Benjamin L, Christian, Bradley T, Head, Elizabeth, Mapstone, Mark, Rafii, Michael S, O'Bryant, Sid, Lai, Florence, Rosas, H Diana, Lee, Joseph H, Silverman, Wayne, Brickman, Adam M, Chhatwal, Jasmeer P, Cruchaga, Carlos, Perrin, Richard J, Xiong, Chengjie, Hassenstab, Jason, McDade, Eric, Bateman, Randall J, and Ances, Beau M

Published
2023
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41. Climate change and disorders of the nervous system

Author

Sisodiya, Sanjay M, primary, Gulcebi, Medine I, additional, Fortunato, Francesco, additional, Mills, James D, additional, Haynes, Ethan, additional, Bramon, Elvira, additional, Chadwick, Paul, additional, Ciccarelli, Olga, additional, David, Anthony S, additional, De Meyer, Kris, additional, Fox, Nick C, additional, Davan Wetton, Joanna, additional, Koltzenburg, Martin, additional, Kullmann, Dimitri M, additional, Kurian, Manju A, additional, Manji, Hadi, additional, Maslin, Mark A, additional, Matharu, Manjit, additional, Montgomery, Hugh, additional, Romanello, Marina, additional, Werring, David J, additional, Zhang, Lisa, additional, Friston, Karl J, additional, and Hanna, Michael G, additional

Published
2024
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44. TADPOLE Challenge: Prediction of Longitudinal Evolution in Alzheimer's Disease

Author

Marinescu, Razvan V., Oxtoby, Neil P., Young, Alexandra L., Bron, Esther E., Toga, Arthur W., Weiner, Michael W., Barkhof, Frederik, Fox, Nick C., Klein, Stefan, Alexander, Daniel C., and Consortium, the EuroPOND

Subjects
Quantitative Biology - Populations and Evolution, Statistics - Applications
Abstract

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge compares the performance of algorithms at predicting future evolution of individuals at risk of Alzheimer's disease. TADPOLE Challenge participants train their models and algorithms on historical data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study or any other datasets to which they have access. Participants are then required to make monthly forecasts over a period of 5 years from January 2018, of three key outcomes for ADNI-3 rollover participants: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. These individual forecasts are later compared with the corresponding future measurements in ADNI-3 (obtained after the TADPOLE submission deadline). The first submission phase of TADPOLE was open for prize-eligible submissions between 15 June and 15 November 2017. The submission system remains open via the website: https://tadpole.grand-challenge.org, although since 15 November 2017 submissions are not eligible for the first round of prizes. This paper describes the design of the TADPOLE Challenge., Comment: For more details on TADPOLE Challenge, see https://tadpole.grand-challenge.org/ This paper outlines the design of the TADPOLE Challenge. Paper contains 8 pages, 2 figures, 5 tables

Published
2018

45. Author Correction: Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Author

Kunkle, Brian W, Grenier-Boley, Benjamin, Sims, Rebecca, Bis, Joshua C, Damotte, Vincent, Naj, Adam C, Boland, Anne, Vronskaya, Maria, van der Lee, Sven J, Amlie-Wolf, Alexandre, Bellenguez, Céline, Frizatti, Aura, Chouraki, Vincent, Martin, Eden R, Sleegers, Kristel, Badarinarayan, Nandini, Jakobsdottir, Johanna, Hamilton-Nelson, Kara L, Moreno-Grau, Sonia, Olaso, Robert, Raybould, Rachel, Chen, Yuning, Kuzma, Amanda B, Hiltunen, Mikko, Morgan, Taniesha, Ahmad, Shahzad, Vardarajan, Badri N, Epelbaum, Jacques, Hoffmann, Per, Boada, Merce, Beecham, Gary W, Garnier, Jean-Guillaume, Harold, Denise, Fitzpatrick, Annette L, Valladares, Otto, Moutet, Marie-Laure, Gerrish, Amy, Smith, Albert V, Qu, Liming, Bacq, Delphine, Denning, Nicola, Jian, Xueqiu, Zhao, Yi, Del Zompo, Maria, Fox, Nick C, Choi, Seung-Hoan, Mateo, Ignacio, Hughes, Joseph T, Adams, Hieab H, Malamon, John, Sanchez-Garcia, Florentino, Patel, Yogen, Brody, Jennifer A, Dombroski, Beth A, Naranjo, Maria Candida Deniz, Daniilidou, Makrina, Eiriksdottir, Gudny, Mukherjee, Shubhabrata, Wallon, David, Uphill, James, Aspelund, Thor, Cantwell, Laura B, Garzia, Fabienne, Galimberti, Daniela, Hofer, Edith, Butkiewicz, Mariusz, Fin, Bertrand, Scarpini, Elio, Sarnowski, Chloe, Bush, Will S, Meslage, Stéphane, Kornhuber, Johannes, White, Charles C, Song, Yuenjoo, Barber, Robert C, Engelborghs, Sebastiaan, Sordon, Sabrina, Voijnovic, Dina, Adams, Perrie M, Vandenberghe, Rik, Mayhaus, Manuel, Cupples, L Adrienne, Albert, Marilyn S, De Deyn, Peter P, Gu, Wei, Himali, Jayanadra J, Beekly, Duane, Squassina, Alessio, Hartmann, Annette M, Orellana, Adelina, Blacker, Deborah, Rodriguez-Rodriguez, Eloy, Lovestone, Simon, Garcia, Melissa E, Doody, Rachelle S, Munoz-Fernadez, Carmen, Sussams, Rebecca, Lin, Honghuang, Fairchild, Thomas J, and Benito, Yolanda A

Subjects
Biochemistry and Cell Biology, Biological Sciences, Alzheimer Disease Genetics Consortium, European Alzheimer’s Disease Initiative, Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium, Genetic and Environmental Risk in AD/Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology, Genetics
Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019

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

Author

Firth, Nicholas C, Primativo, Silvia, Marinescu, Razvan-Valentin, Shakespeare, Timothy J, Suarez-Gonzalez, Aida, Lehmann, Manja, Carton, Amelia, Ocal, Dilek, Pavisic, Ivanna, Paterson, Ross W, Slattery, Catherine F, Foulkes, Alexander JM, Ridha, Basil H, Gil-Néciga, Eulogio, Oxtoby, Neil P, Young, Alexandra L, Modat, Marc, Cardoso, M Jorge, Ourselin, Sebastien, Ryan, Natalie S, Miller, Bruce L, Rabinovici, Gil D, Warrington, Elizabeth K, Rossor, Martin N, Fox, Nick C, Warren, Jason D, Alexander, Daniel C, Schott, Jonathan M, Yong, Keir XX, and Crutch, Sebastian J

Subjects
Cerebral Cortex, Humans, Alzheimer Disease, Disease Progression, Magnetic Resonance Imaging, Case-Control Studies, Longitudinal Studies, Neuropsychological Tests, Models, Neurological, Middle Aged, Female, Male, Cognitive Dysfunction, Alzheimer’s disease, brain atrophy, dementia, memory, structural MRI, Alzheimer's disease, Models, Neurological, Neurology & Neurosurgery, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract

Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer's disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer's disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer's disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer's disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer's disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer's disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer's disease showed early hippocampal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion. Cognitive models showed tests sensitive to visuospatial dysfunction declined earlier in posterior cortical atrophy than typical Alzheimer's disease whilst tests sensitive to working memory impairment declined earlier in typical Alzheimer's disease than posterior cortical atrophy. These findings indicate that posterior cortical atrophy and typical Alzheimer's disease have distinct sites of onset and different profiles of spatial and temporal progression. The ordering of disease events both motivates investigation of biological factors underpinning phenotypic heterogeneity, and informs the selection of measures for clinical trials in posterior cortical atrophy.

Published
2019

47. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Author

Kunkle, Brian W, Grenier-Boley, Benjamin, Sims, Rebecca, Bis, Joshua C, Damotte, Vincent, Naj, Adam C, Boland, Anne, Vronskaya, Maria, van der Lee, Sven J, Amlie-Wolf, Alexandre, Bellenguez, Céline, Frizatti, Aura, Chouraki, Vincent, Martin, Eden R, Sleegers, Kristel, Badarinarayan, Nandini, Jakobsdottir, Johanna, Hamilton-Nelson, Kara L, Moreno-Grau, Sonia, Olaso, Robert, Raybould, Rachel, Chen, Yuning, Kuzma, Amanda B, Hiltunen, Mikko, Morgan, Taniesha, Ahmad, Shahzad, Vardarajan, Badri N, Epelbaum, Jacques, Hoffmann, Per, Boada, Merce, Beecham, Gary W, Garnier, Jean-Guillaume, Harold, Denise, Fitzpatrick, Annette L, Valladares, Otto, Moutet, Marie-Laure, Gerrish, Amy, Smith, Albert V, Qu, Liming, Bacq, Delphine, Denning, Nicola, Jian, Xueqiu, Zhao, Yi, Del Zompo, Maria, Fox, Nick C, Choi, Seung-Hoan, Mateo, Ignacio, Hughes, Joseph T, Adams, Hieab H, Malamon, John, Sanchez-Garcia, Florentino, Patel, Yogen, Brody, Jennifer A, Dombroski, Beth A, Naranjo, Maria Candida Deniz, Daniilidou, Makrina, Eiriksdottir, Gudny, Mukherjee, Shubhabrata, Wallon, David, Uphill, James, Aspelund, Thor, Cantwell, Laura B, Garzia, Fabienne, Galimberti, Daniela, Hofer, Edith, Butkiewicz, Mariusz, Fin, Bertrand, Scarpini, Elio, Sarnowski, Chloe, Bush, Will S, Meslage, Stéphane, Kornhuber, Johannes, White, Charles C, Song, Yuenjoo, Barber, Robert C, Engelborghs, Sebastiaan, Sordon, Sabrina, Voijnovic, Dina, Adams, Perrie M, Vandenberghe, Rik, Mayhaus, Manuel, Cupples, L Adrienne, Albert, Marilyn S, De Deyn, Peter P, Gu, Wei, Himali, Jayanadra J, Beekly, Duane, Squassina, Alessio, Hartmann, Annette M, Orellana, Adelina, Blacker, Deborah, Rodriguez-Rodriguez, Eloy, Lovestone, Simon, Garcia, Melissa E, Doody, Rachelle S, Munoz-Fernadez, Carmen, Sussams, Rebecca, Lin, Honghuang, Fairchild, Thomas J, and Benito, Yolanda A

Subjects
Biochemistry and Cell Biology, Genetics, Biological Sciences, Neurodegenerative, Dementia, Alzheimer's Disease, Aging, Prevention, Brain Disorders, Neurosciences, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Acquired Cognitive Impairment, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Neurological, Aged, Alzheimer Disease, Amyloid beta-Peptides, Case-Control Studies, Female, Genetic Loci, Genetic Predisposition to Disease, Genetic Testing, Genome-Wide Association Study, Haplotypes, Humans, Immunity, Lipid Metabolism, Lipids, Male, tau Proteins, Alzheimer Disease Genetics Consortium (ADGC), European Alzheimer’s Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease Consortium (GERAD/PERADES), Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

Published
2019

49. Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease

Author

Adams, Sarah, Allegri, Ricardo, Araki, Aki, Barthelemy, Nicolas, Bateman, Randall, Bechara, Jacob, Benzinger, Tammie, Berman, Sarah, Bodge, Courtney, Brandon, Susan, Brooks, William (Bill), Brosch, Jared, Buck, Jill, Buckles, Virginia, Carter, Kathleen, Cash, Lisa, Chen, Charlie, Chhatwal, Jasmeer, Mendez, Patricio Chrem, Chua, Jasmin, Chui, Helena, Courtney, Laura, Cruchaga, Carlos, Day, Gregory S, DeLaCruz, Chrismary, Denner, Darcy, Diffenbacher, Anna, Dincer, Aylin, Donahue, Tamara, Douglas, Jane, Duong, Duc, Egido, Noelia, Esposito, Bianca, Fagan, Anne, Farlow, Marty, Feldman, Becca, Fitzpatrick, Colleen, Flores, Shaney, Fox, Nick, Franklin, Erin, Joseph-Mathurin, Nelly, Fujii, Hisako, Gardener, Samantha, Ghetti, Bernardino, Goate, Alison, Goldberg, Sarah, Goldman, Jill, Gonzalez, Alyssa, Gordon, Brian, Gräber-Sultan, Susanne, Graff-Radford, Neill, Graham, Morgan, Gray, Julia, Gremminger, Emily, Grilo, Miguel, Groves, Alex, Haass, Christian, Häsler, Lisa, Hassenstab, Jason, Hellm, Cortaiga, Herries, Elizabeth, Hoechst-Swisher, Laura, Hofmann, Anna, Holtzman, David, Hornbeck, Russ, Igor, Yakushev, Ihara, Ryoko, Ikeuchi, Takeshi, Ikonomovic, Snezana, Ishii, Kenji, Jack, Clifford, Jerome, Gina, Johnson, Erik, Jucker, Mathias, Karch, Celeste, Käser, Stephan, Kasuga, Kensaku, Keefe, Sarah, Klunk, William, Koeppe, Robert, Koudelis, Deb, Kuder-Buletta, Elke, Laske, Christoph, Levey, Allan, Levin, Johannes, Li, Yan, Lopez, Oscar, Marsh, Jacob, Martins, Ralph, Mason, Neal Scott, Masters, Colin, Mawuenyega, Kwasi, McCullough, Austin, McDade, Eric, Mejia, Arlene, Morenas-Rodriguez, Estrella, Morris, John, Mountz, James, Mummery, Cath, Nadkarni, N eelesh, Nagamatsu, Akemi, Neimeyer, Katie, Niimi, Yoshiki, Noble, James, Norton, Joanne, Nuscher, Brigitte, Obermüller, Ulricke, O'Connor, Antoinette, Patira, Riddhi, Perrin, Richard, Ping, Lingyan, Preische, Oliver, Renton, Alan, Ringman, John, Salloway, Stephen, Schofield, Peter, Senda, Michio, Seyfried, Nicholas T, Shady, Kristine, Shimada, Hiroyuki, Sigurdson, Wendy, Smith, Jennifer, Smith, Lori, Snitz, Beth, Sohrabi, Hamid, Stephens, Sochenda, Taddei, Kevin, Thompson, Sarah, Vöglein, Jonathan, Wang, Peter, Wang, Qing, Weamer, Elise, Xiong, Chengjie, Xu, Jinbin, Xu, Xiong, Millar, Peter R., Luckett, Patrick H., Gordon, Brian A., Benzinger, Tammie L.S., Schindler, Suzanne E., Fagan, Anne M., Bateman, Randall J., Lee, Jae-Hong, Mori, Hiroshi, Salloway, Stephen P, Yakushev, Igor, Morris, John C., and Ances, Beau M.

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

Author

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

Published
2022
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