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1. 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

2. 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, Dementia, Vascular Cognitive Impairment/Dementia, Biomedical Imaging, Aging, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Behavioral and Social Science, Alzheimer's Disease, Neurodegenerative, Cerebrovascular, Alzheimer's Disease Related Dementias (ADRD), Clinical Research, Brain Disorders, Neurosciences, 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

3. 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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4. Machine Learning Methods Applied to Cortico-Cortical Evoked Potentials Aid in Localizing Seizure Onset Zones

Author

Malone, Ian G., Smith, Kaleb E., Urdaneta, Morgan E., Davis, Tyler S., Anderson, Daria Nesterovich, Phillip, Brian J., Rolston, John D., and Butson, Christopher R.

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing, Quantitative Biology - Neurons and Cognition
Abstract

Epilepsy affects millions of people, reducing quality of life and increasing risk of premature death. One-third of epilepsy cases are drug-resistant and require surgery for treatment, which necessitates localizing the seizure onset zone (SOZ) in the brain. Attempts have been made to use cortico-cortical evoked potentials (CCEPs) to improve SOZ localization but none have been successful enough for clinical adoption. Here, we compare the performance of ten machine learning classifiers in localizing SOZ from CCEP data. This preliminary study validates a novel application of machine learning, and the results establish our approach as a promising line of research that warrants further investigation. This work also serves to facilitate discussion and collaboration with fellow machine learning and/or epilepsy researchers., Comment: Extended Abstract presented at Machine Learning for Health (ML4H) symposium 2022, November 28th, 2022, New Orleans, United States & Virtual, http://www.ml4h.cc, 6 pages

Published
2022

6. 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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7. 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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8. 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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12. 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., and Senjem, Matthew L.

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. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Rates of cortical thinning in Alzheimer’s disease signature regions associate with vascular burden but not with β-amyloid status in cognitively normal adults at age 70.

Author

Keuss, Sarah E., Coath, William, Cash, David M., Barnes, Josephine, Nicholas, Jennifer M., Lane, Christopher A., Parker, Thomas D., Keshavan, Ashvini, Buchanan, Sarah M., Wagen, Aaron Z., Storey, Mathew, Harris, Matthew, Lu, Kirsty, James, Sarah-Naomi, Street, Rebecca, Malone, Ian B., Sudre, Carole H., Thomas, David L., Dickson, John C., and Barkhof, Frederik

Subjects
CEREBRAL amyloid angiopathy, CEREBRAL small vessel diseases, ALZHEIMER'S disease, SCHOLARSHIPS, RESEARCH institutes, POSITRON emission tomography
Published
2024
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14. Dissociable effects of APOE ε4 and β-amyloid pathology on visual working memory

Author

Lu, Kirsty, Nicholas, Jennifer M., Pertzov, Yoni, Grogan, John, Husain, Masud, Pavisic, Ivanna M., James, Sarah-Naomi, Parker, Thomas D., Lane, Christopher A., Keshavan, Ashvini, Keuss, Sarah E., Buchanan, Sarah M., Murray-Smith, Heidi, Cash, David M., Malone, Ian B., Sudre, Carole H., Coath, William, Wong, Andrew, Henley, Susie M. D., Fox, Nick C., Richards, Marcus, Schott, Jonathan M., and Crutch, Sebastian J.

Published
2021
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15. Presymptomatic atrophy in autosomal dominant Alzheimer's disease: A serial magnetic resonance imaging study

Author

Kinnunen, Kirsi M, Cash, David M, Poole, Teresa, Frost, Chris, Benzinger, Tammie LS, Ahsan, R Laila, Leung, Kelvin K, Cardoso, M Jorge, Modat, Marc, Malone, Ian B, Morris, John C, Bateman, Randall J, Marcus, Daniel S, Goate, Alison, Salloway, Stephen P, Correia, Stephen, Sperling, Reisa A, Chhatwal, Jasmeer P, Mayeux, Richard P, Brickman, Adam M, Martins, Ralph N, Farlow, Martin R, Ghetti, Bernardino, Saykin, Andrew J, Jack, Clifford R, Schofield, Peter R, McDade, Eric, Weiner, Michael W, Ringman, John M, Thompson, Paul M, Masters, Colin L, Rowe, Christopher C, Rossor, Martin N, Ourselin, Sebastien, Fox, Nick C, and Network, Dominantly Inherited Alzheimer

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Clinical Research, Acquired Cognitive Impairment, Alzheimer's Disease, Bioengineering, Biomedical Imaging, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Neurodegenerative, Brain Disorders, Neurological, Adult, Alzheimer Disease, Apolipoproteins E, Atrophy, Brain, Female, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Psychiatric Status Rating Scales, Statistics, Nonparametric, Time Factors, Longitudinal, Alzheimer's disease, Autosomal dominant, Neuroimaging, MRI, Boundary Shift Integral, Nonlinear modeling, Change-point, Dominantly Inherited Alzheimer Network, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionIdentifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials.MethodsSerial T1-weighted magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed-effects models estimated the change-points when atrophy rates deviate from normal and the rates of change before and after this point.ResultsAtrophy increased after the change-point, which occurred 1-1.5 years (assuming a single step change in atrophy rate) or 3-8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change-point.DiscussionAtrophy rates are pathologically increased up to seven years before "expected onset". During this period, atrophy rates may be useful for inclusion and tracking of disease progression.

Published
2018

17. Safety and efficacy of losartan for the reduction of brain atrophy in clinically diagnosed Alzheimer's disease (the RADAR trial): a double-blind, randomised, placebo-controlled, phase 2 trial

Author

Harkness, Kirsty, Kuruvilla, Tarun, McShane, Rupert, Connelly, Peter, Duncan, Gordon, Calvert, Lucy, Lawrie, Alasdair, Sheridan, Matthew, Jackson, Eric, Udeze, Bernard, Pearson, Stephen, Langheinrich, Tobias, Wagle, Suvarna, Butchart, Joseph, Macharouthu, Ajay, Donaldson, Andrew, Neil, Wendy, Pattan, Vivek, Findlay, David, Thomas, Alan, Barber, Robert, Byrne, Andrew, Dalvi, Madhusudan, Negi, Rashi, McGuinness, Bernadette, Kehoe, Patrick Gavin, Turner, Nicholas, Howden, Beth, Jarutyte, Lina, Clegg, Shona Louise, Malone, Ian Brian, Barnes, Josephine, Nielsen, Casper, Sudre, Carole Hélène, Wilson, Aileen, Thai, Ngoc Jade, Blair, Peter Sinclair, Coulthard, Elizabeth, Lane, Janet Athene, Passmore, Peter, Taylor, Jodi, Mutsaerts, Henk-Jan, Thomas, David Lee, Fox, Nick Charles, Wilkinson, Ian, and Ben-Shlomo, Yoav

Published
2021
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19. Exposure to area disadvantage across the life course and its influence on cognition and neurodegenerative pathology in later life.

Author

Cartlidge, Molly R E, primary, Liu, Yiwen, additional, Bakolis, Ioannis, additional, Nicholas, Jennifer M, additional, Keuss, Sarah E, additional, Coath, William, additional, Cash, David M, additional, Malone, Ian B, additional, Sudre, Carole H, additional, Schott, Jonathan M, additional, and Richards, Marcus, additional

Published
2023
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21. Associations between accelerated long‐term forgetting of Complex Figure Drawing, cerebral amyloid deposition, brain atrophy and serum neurofilament light in 73‐year‐olds

Author

Lu, Kirsty, primary, Keshavan, Ashvini, additional, Baker, John, additional, Nicholas, Jennifer M, additional, Street, Rebecca E, additional, Keuss, Sarah E, additional, Coath, William, additional, James, Sarah‐Naomi, additional, Weston, Philip SJ, additional, Murray‐Smith, Heidi, additional, Cash, David M, additional, Malone, Ian B, additional, Wong, Andrew, additional, Fox, Nick C, additional, Richards, Marcus, additional, Crutch, Sebastian J, additional, and Schott, Jonathan M, additional

Published
2023
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23. Investigating associations of age at natural menopause with neuroimaging indicators of brain health in later‐life, using a British population‐based birth cohort

Author

Needham, Louisa P, primary, Nicholas, Jennifer M, additional, Barnes, Jo, additional, Sudre, Carole H, additional, Cash, David M, additional, Coath, William, additional, Malone, Ian B, additional, Lu, Kirsty, additional, Schott, Jonathan M, additional, Richards, Marcus, additional, and James, Sarah‐Naomi, additional

Published
2023
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24. MK‐6240 tau‐PET in an Aβ‐enriched sample from the 1946 British birth cohort

Author

Coath, William, primary, Markiewicz, Pawel J, additional, Modat, Marc, additional, Scott, Catherine J, additional, Malone, Ian B, additional, Arstad, Erik, additional, Awais, Ramla, additional, Sander, Kerstin, additional, Weston, Philip SJ, additional, Thomas, David L, additional, Dickson, John, additional, Schöll, Michael, additional, Ourselin, Sebastien, additional, Richards, Marcus, additional, Fox, Nick C, additional, Cash, David M, additional, and Schott, Jonathan M, additional

Published
2023
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25. The association between microstructural MRI biomarkers and sequential amyloid and tau‐related cortical changes in asymptomatic elderly individuals

Author

Weston, Philip SJ, primary, Coath, William, additional, Brown, Thomas M., additional, Scott, Catherine J, additional, Malone, Ian B, additional, Arstad, Erik, additional, Awais, Ramla, additional, Sander, Kerstin, additional, Thomas, David L, additional, Dickson, John, additional, Schöll, Michael, additional, Richards, Marcus, additional, Fox, Nick C, additional, Zhang, Hui, additional, Cash, David M, additional, and Schott, Jonathan M, additional

Published
2023
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26. Participating in leisure time physical activity across adulthood and later‐life brain health: 30 years follow‐up in 1946 British Birth Cohort

Author

James, Sarah‐Naomi, primary, Nicholas, Jennifer M, additional, Chiou, Yu‐Jie, additional, Parker, Thomas D, additional, Lu, Kirsty, additional, Murray‐Smith, Heidi, additional, Cash, David M, additional, Malone, Ian B, additional, Sudre, Carole H, additional, Keshavan, Ashvini, additional, Coath, William, additional, Flores‐Guerrero, Jose L, additional, Orini, Michele, additional, Almeida‐Meza, Pamela, additional, Fox, Nick C, additional, Richards, Marcus, additional, and Schott, Jonathan M, additional

Published
2023
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27. White matter hyperintensity volume changes are associated with progressive hippocampal atrophy in Insight 46: the neuroscience sub‐study of the MRC National Survey of Health and Development, the British 1946 birth cohort

Author

Brown, Thomas M., primary, Sudre, Carole H, additional, Keuss, Sarah E, additional, Coath, William, additional, Prosser, Lloyd, additional, Nicholas, Jennifer M, additional, Malone, Ian B, additional, James, Sarah‐Naomi, additional, Murray‐Smith, Heidi, additional, Cash, David M, additional, Richards, Marcus, additional, Barnes, Jo, additional, and Schott, Jonathan M, additional

Published
2023
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28. An ultra‐fast MRI protocol in dementia enabled by Wave‐CAIPI

Author

Grilo, Miguel A Rosa, primary, Chughtai, Haroon R, additional, Thomas, David L, additional, Cash, David M, additional, Beament, Millie, additional, Coath, William, additional, Prosser, Lloyd, additional, Malone, Ian B, additional, Lim, Emma, additional, Jäger, H Rolf, additional, Alexander, Daniel C, additional, Fox, Nick C, additional, Mummery, Catherine J, additional, Parker, Geoff JM, additional, and Barkhof, Frederik, additional

Published
2023
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30. Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Author

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

Published
2023
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31. Olfactory testing does not predict β-amyloid, MRI measures of neurodegeneration or vascular pathology in the British 1946 birth cohort

Author

Buchanan, Sarah M., Parker, Thomas D., Lane, Christopher A., Keshavan, Ashvini, Keuss, Sarah E., Lu, Kirsty, James, Sarah-Naomi, Murray-Smith, Heidi, Wong, Andrew, Nicholas, Jennifer, Cash, David M., Malone, Ian B., Coath, William, Thomas, David L., Sudre, Carole, Fox, Nick C., Richards, Marcus, and Schott, Jonathan M.

Published
2020
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32. Investigating the relationship between BMI across adulthood and late life brain pathologies

Author

Lane, Christopher A., Barnes, Josephine, Nicholas, Jennifer M., Baker, John W., Sudre, Carole H., Cash, David M., Parker, Thomas D., Malone, Ian B., Lu, Kirsty, James, Sarah-Naomi, Keshavan, Ashvini, Buchanan, Sarah, Keuss, Sarah, Murray-Smith, Heidi, Wong, Andrew, Gordon, Elizabeth, Coath, William, Modat, Marc, Thomas, David, Hardy, Rebecca, Richards, Marcus, Fox, Nick C., and Schott, Jonathan M.

Published
2021
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33. Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2

Author

Jack, Clifford R, Barnes, Josephine, Bernstein, Matt A, Borowski, Bret J, Brewer, James, Clegg, Shona, Dale, Anders M, Carmichael, Owen, Ching, Christopher, DeCarli, Charles, Desikan, Rahul S, Fennema‐Notestine, Christine, Fjell, Anders M, Fletcher, Evan, Fox, Nick C, Gunter, Jeff, Gutman, Boris A, Holland, Dominic, Hua, Xue, Insel, Philip, Kantarci, Kejal, Killiany, Ron J, Krueger, Gunnar, Leung, Kelvin K, Mackin, Scott, Maillard, Pauline, Malone, Ian B, Mattsson, Niklas, McEvoy, Linda, Modat, Marc, Mueller, Susanne, Nosheny, Rachel, Ourselin, Sebastien, Schuff, Norbert, Senjem, Matthew L, Simonson, Alix, Thompson, Paul M, Rettmann, Dan, Vemuri, Prashanthi, Walhovd, Kristine, Zhao, Yansong, Zuk, Samantha, and Weiner, Michael

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Aging, Clinical Research, Acquired Cognitive Impairment, Neurosciences, Alzheimer's Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Biomedical Imaging, Clinical Trials and Supportive Activities, Dementia, Neurodegenerative, Neurological, Alzheimer Disease, Biomarkers, Brain, Cognition Disorders, History, 20th Century, History, 21st Century, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Positron-Emission Tomography, Spin Labels, Alzheimer's disease, Alzheimer's Disease Neuroimaging Initiative, ADNI, Diffusion, MRI, Neuroimaging, Perfusion, Resting functional MRI, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionAlzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders.MethodsWe review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3.ResultsContributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials.DiscussionOver the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future.

Published
2015

34. Effects of changing from non-accelerated to accelerated MRI for follow-up in brain atrophy measurement

Author

Leung, Kelvin K, Malone, Ian M, Ourselin, Sebastien, Gunter, Jeffrey L, Bernstein, Matt A, Thompson, Paul M, Jack, Clifford R, Weiner, Michael W, Fox, Nick C, and Initiative, for the Alzheimer's Disease Neuroimaging

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Bioengineering, Biomedical Imaging, Neurosciences, Alzheimer Disease, Atrophy, Brain, Cognitive Dysfunction, Follow-Up Studies, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Neurodegenerative Diseases, Reproducibility of Results, Boundary shift integral, Accelerated acquisition, Non-accelerated acquisition, Brain atrophy, Alzheimer's disease, Alzheimer's Disease Neuroimaging Initiative, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

Stable MR acquisition is essential for reliable measurement of brain atrophy in longitudinal studies. One attractive recent advance in MRI is to speed up acquisition using parallel imaging (e.g. reducing volumetric T1-weighted acquisition scan times from around 9 to 5 min). In some studies, a decision to change to an accelerated acquisition may have been deliberately taken, while in others repeat scans may occasionally be accidentally acquired with an accelerated acquisition. In ADNI, non-accelerated and accelerated scans were acquired in the same scanning session on each individual. We investigated the impact on brain atrophy as measured by k-means normalized boundary shift integral (KN-BSI) and deformation-based morphometry when changing from non-accelerated to accelerated MRI acquisitions over a 12-month interval using scans of 422 subjects from ADNI. KN-BSIs were calculated using both a non-accelerated baseline scan and non-accelerated 12-month scans (i.e. consistent acquisition), and a non-accelerated baseline scan and an accelerated 12-month scan (i.e. changed acquisition). Fluid-based non-rigid registration was also performed on those scans to estimate the brain atrophy rate. We found that the effect on KN-BSI and fluid-based non-rigid registration depended on the scanner manufacturer. For KN-BSI, in Philips and Siemens scanners, the change had very little impact on the measured atrophy rate (increase of 0.051% in Philips and -0.035% in Siemens from consistent acquisition to changed acquisition), whereas, in GE, the change caused a mean reduction of 0.65% in the brain atrophy rate. This is likely due to the difference in tissue contrast between gray matter and cerebrospinal fluid in the non-accelerated and accelerated scans in GE, which uses IR-FSPGR instead of MP-RAGE. For fluid-based non-rigid registration, the change caused a mean increase of 0.29% in the brain atrophy rate in the changed acquisition compared with consistent acquisition in Philips, whereas in GE and Siemens, the change had less impact on the mean atrophy rate (increase of 0.18% in GE and 0.049% in Siemens). Moving from non-accelerated baseline scans to accelerated scans for follow-up may have surprisingly little effect on computed atrophy rates depending on the exact sequence details and the scanner manufacturer; even accidentally inconsistent scans of this nature may still be useful.

Published
2015

35. Associations between blood pressure across adulthood and late-life brain structure and pathology in the neuroscience substudy of the 1946 British birth cohort (Insight 46): an epidemiological study

Author

Lane, Christopher A, Barnes, Josephine, Nicholas, Jennifer M, Sudre, Carole H, Cash, David M, Parker, Thomas D, Malone, Ian B, Lu, Kirsty, James, Sarah-Naomi, Keshavan, Ashvini, Murray-Smith, Heidi, Wong, Andrew, Buchanan, Sarah M, Keuss, Sarah E, Gordon, Elizabeth, Coath, William, Barnes, Anna, Dickson, John, Modat, Marc, Thomas, David, Crutch, Sebastian J, Hardy, Rebecca, Richards, Marcus, Fox, Nick C, and Schott, Jonathan M

Published
2019
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38. DTI changes of thalamic subregions in genetic frontotemporal dementia: findings from the GENFI cohort.

Author

Soskic, Sonja, Tregidgo, Henry F. J., Todd, Emily G., Bouzigues, Arabella, Cash, David M, Russell, Lucy L., Thomas, David L, Malone, Ian B, van Swieten, John C., Jiskoot, Lize C., Seelaar, Harro, Borroni, Barbara, Galimberti, Daniela, Sanchez‐Valle, Raquel, Laforce, Robert, Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, and Tartaglia, Carmela

Abstract

Background: Atrophy of thalamic subregions has been observed across the spectrum of frontotemporal dementia (FTD). To gain better insight into underlying tissue changes, we investigated how thalamic subregional fractional anisotropy (FA) and mean diffusivity (MD) derived from diffusion tensor imaging (DTI) are altered in genetic FTD. Method: We used our newly developed thalamus segmentation tool, which jointly combines structural and diffusion input MRI data, to segment thalami and extract thalamic subregional FA and MD values for 163 genetic mutation carriers and 126 non‐carriers with suitable 3T MRI data from the GENetic FTD Initiative (GENFI). Mutation carriers were divided according to their genetic diagnosis and CDR®+NACC FTLD global scores into presymptomatic/prodromal (≤0.5: 41 C9orf72, 59 GRN, 34 MAPT) and symptomatic (≥1: 8 C9orf72, 11 GRN, 10 MAPT) groups. Mean FA and MD values for thalamic subregions were obtained using diffusion tensors interpolated in the log domain and weighted by segmentation posterior probabilities. Thalamic subregional FA and MD values for presymptomatic and symptomatic mutation carriers within each genetic group were compared with non‐carriers using analysis of covariance with bootstrapping, where age, scanner type, and sex were covariates. We corrected for multiple comparisons and calculated percentage changes in adjusted FA and MD mean values for mutation carriers relative to non‐carriers. Result: The only significant change at the presymptomatic stage was found for C9orf72 expansion carriers, who showed FA reduction in the intralaminar subregion (5%) (Figure 1, Table 1). In symptomatic C9orf72 expansion carriers, FA was reduced in the laterodorsal (21%), lateral posterior (13%), anteroventral (13%) and intralaminar (11%) subregions. Symptomatic MAPT mutation carriers also showed FA reduction in the laterodorsal (15%) and anteroventral (11%) subregions. No significant FA reductions were found for GRN mutation carriers and no significant MD changes were observed for any group after correction for multiple comparisons. Conclusion: We detected FA reductions of thalamic subregions only for C9orf72 expansion carriers at the presymptomatic stage, and for C9orf72 and MAPT mutation carriers at the symptomatic stage. Combined with the lack of robust MD changes, our findings may warrant further assessment of thalamic microstructure with more advanced diffusion models. [ABSTRACT FROM AUTHOR]

Published
2023
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39. Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort

Author

Bocchetta, Martina, Todd, Emily G, Bouzigues, Arabella, Cash, David M, Nicholas, Jennifer M, Convery, Rhian S, Russell, Lucy L, Thomas, David L, Malone, Ian B, Iglesias, Juan Eugenio, Van Swieten, John C, Jiskoot, Lize C, Seelaar, Harro, Borroni, Barbara, Galimberti, Daniela, Sanchez-Valle, Raquel, Laforce, Robert, Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B, Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, De Mendonca, Alexandre, Santana, Isabel, Butler, Chris R, Ducharme, Simon, Gerhard, Alexander, Danek, Adrian, Levin, Johannes, Otto, Markus, Sorbi, Sandro, Le Ber, Isabelle, Pasquier, Florence, Rohrer, Jonathan D, Esteve, Aitana Sogorb, Nelson, Annabel, Heller, Carolin, Greaves, Caroline V, Benotmane, Hanya, Zetterberg, Henrik, Swift, Imogen J, Samra, Kiran, Shafei, Rachelle, Timberlake, Carolyn, Cope, Thomas, Rittman, Timothy, Benussi, Alberto, Premi, Enrico, Gasparotti, Roberto, Archetti, Silvana, Gazzina, Stefano, Cantoni, Valentina, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Borracci, Vittoria, Rossi, Giacomina, Giaccone, Giorgio, Di Fede, Giuseppe, Caroppo, Paola, Tiraboschi, Pietro, Prioni, Sara, Redaelli, Veronica, Tang-Wai, David, Rogaeva, Ekaterina, Castelo-Branco, Miguel, Freedman, Morris, Keren, Ron, Black, Sandra, Mitchell, Sara, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Poos, Jackie, Papma, Janne M, Giannini, Lucia, van Minkelen, Rick, Pijnenburg, Yolande, Nacmias, Benedetta, Ferrari, Camilla, Polito, Cristina, Lombardi, Gemma, Bessi, Valentina, Veldsman, Michele, Andersson, Christin, Thonberg, Hakan, Öijerstedt, Linn, Jelic, Vesna, Thompson, Paul, Langheinrich, Tobias, Lladó, Albert, Antonell, Anna, Olives, Jaume, Balasa, Mircea, Bargalló, Nuria, Borrego-Ecija, Sergi, Verdelho, Ana, Maruta, Carolina, Ferreira, Catarina B, Miltenberger, Gabriel, Simões do Couto, Frederico, Gabilondo, Alazne, Gorostidi, Ana, Villanua, Jorge, Cañada, Marta, Tainta, Mikel, Zulaica, Miren, Barandiaran, Myriam, Alves, Patricia, Bender, Benjamin, Wilke, Carlo, Graf, Lisa, Vogels, Annick, Vandenbulcke, Mathieu, Van Damme, Philip, Bruffaerts, Rose, Poesen, Koen, Rosa-Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Saracino, Dario, Colliot, Olivier, Sayah, Sabrina, Prix, Catharina, Wlasich, Elisabeth, Wagemann, Olivia, Loosli, Sandra, Schönecker, Sonja, Hoegen, Tobias, Lombardi, Jolina, Anderl-Straub, Sarah, Rollin, Adeline, Kuchcinski, Gregory, Bertoux, Maxime, Lebouvier, Thibaud, Deramecourt, Vincent, Santiago, Beatriz, Duro, Diana, Leitão, Maria João, Almeida, Maria Rosario, Tábuas-Pereira, Miguel, Afonso, Sónia, Bocchetta, Martina [0000-0003-1814-5024], Todd, Emily G [0000-0003-1551-5691], Cash, David M [0000-0001-7833-616X], Malone, Ian B [0000-0001-7512-7856], Jiskoot, Lize C [0000-0002-1120-1858], Seelaar, Harro [0000-0003-1989-7527], Borroni, Barbara [0000-0001-9340-9814], Sanchez-Valle, Raquel [0000-0001-7750-896X], Synofzik, Matthis [0000-0002-2280-7273], Graff, Caroline [0000-0002-9949-2951], Vandenberghe, Rik [0000-0001-6237-2502], Ducharme, Simon [0000-0002-7309-1113], Gerhard, Alexander [0000-0002-8071-6062], Danek, Adrian [0000-0001-8857-5383], Pasquier, Florence [0000-0001-9880-9788], Apollo - University of Cambridge Repository, Genetic Frontotemporal dementia Initiative (GENFI), Neurology, Bargalló, Nuria, Borrego-Ecija, Sergi, Verdelho, Ana, Maruta, Carolina, Ferreira, Catarina B, Miltenberger, Gabriel, Simões do Couto, Frederico, Gabilondo, Alazne, Gorostidi, Ana, Villanua, Jorge, Cañada, Marta, Tainta, Mikel, Zulaica, Miren, Barandiaran, Myriam, Alves, Patricia, Bender, Benjamin, Wilke, Carlo, Graf, Lisa, Vogels, Annick, Vandenbulcke, Mathieu, Van Damme, Philip, Bruffaerts, Rose, Poesen, Koen, Rosa-Neto, Pedro, Gauthier, Serge, Camuzat, Agnès, Brice, Alexis, Bertrand, Anne, Funkiewiez, Aurélie, Rinaldi, Daisy, Saracino, Dario, Colliot, Olivier, Sayah, Sabrina, Prix, Catharina, Wlasich, Elisabeth, Wagemann, Olivia, Loosli, Sandra, Schönecker, Sonja, Hoegen, Tobias, Lombardi, Jolina, Anderl-Straub, Sarah, Rollin, Adeline, Kuchcinski, Gregory, Bertoux, Maxime, Lebouvier, Thibaud, Deramecourt, Vincent, Santiago, Beatriz, Duro, Diana, Leitão, Maria João, Almeida, Maria Rosario, Tábuas-Pereira, Miguel, Afonso, Sónia, Esteve, Aitana Sogorb, Nelson, Annabel, Heller, Carolin, Greaves, Caroline V, Benotmane, Hanya, Zetterberg, Henrik, Swift, Imogen J, Samra, Kiran, Shafei, Rachelle, Timberlake, Carolyn, Cope, Thomas, Rittman, Timothy, Benussi, Alberto, Premi, Enrico, Gasparotti, Roberto, Archetti, Silvana, Gazzina, Stefano, Cantoni, Valentina, Arighi, Andrea, Fenoglio, Chiara, Scarpini, Elio, Fumagalli, Giorgio, Borracci, Vittoria, Rossi, Giacomina, Giaccone, Giorgio, Di Fede, Giuseppe, Caroppo, Paola, Tiraboschi, Pietro, Prioni, Sara, Redaelli, Veronica, Tang-Wai, David, Rogaeva, Ekaterina, Castelo-Branco, Miguel, Freedman, Morris, Keren, Ron, Black, Sandra, Mitchell, Sara, Shoesmith, Christen, Bartha, Robart, Rademakers, Rosa, Poos, Jackie, Papma, Janne M, Giannini, Lucia, van Minkelen, Rick, Pijnenburg, Yolande, Nacmias, Benedetta, Ferrari, Camilla, Polito, Cristina, Lombardi, Gemma, Bessi, Valentina, Veldsman, Michele, Andersson, Christin, Thonberg, Hakan, Öijerstedt, Linn, Jelic, Vesna, Thompson, Paul, Langheinrich, Tobias, Lladó, Albert, Antonell, Anna, Olives, Jaume, and Balasa, Mircea

Subjects
Cellular and Molecular Neuroscience, Psychiatry and Mental health, Neurology, SDG 3 - Good Health and Well-being, brain volumetry, diffusion imaging, genetic frontotemporal dementia, MRI imaging, Medizin, presymptomatic stage, ddc:610, Biological Psychiatry
Abstract

Funder: Deutsche Forschungsgemeinschaft, Funder: Dementia Research Institute, Funder: Leonard Wolfson Experimental Neurology Centre, Funder: Canadian Institutes of Health Research, Funder: Medical Research Council, Funder: Miriam Marks Brain Research UK Senior Fellowship, Funder: Wolfson Foundation, Funder: Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie, Funder: NVIDIA, Funder: Alzheimer's Research UK, Funder: Alzheimer's Society and Alzheimer's Research, Funder: Brain Research UK, Funder: University College London, Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative. Three hundred eighty-seven mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR®+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). The w-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as 'normal' or 'abnormal' based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the 'normal' and 'abnormal' groups within each genetic subtype, as measured by the CDR®+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score. Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR®+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 points in the GRN group as well as a statistically significant increase in the revised Cambridge Behavioural Inventory of up to 11 points in MAPT, 10 points in GRN, and 8 points in C9orf72 mutation carriers. Baseline regional brain abnormalities on MRI in presymptomatic mutation carriers are associated with different profiles of clinical progression over time. These results may be helpful to inform stratification of participants in future trials.

Published
2023

40. Cognition at age 70: Life course predictors and associations with brain pathologies

Author

Lu, Kirsty, Nicholas, Jennifer M., Collins, Jessica D., James, Sarah-Naomi, Parker, Thomas D., Lane, Christopher A., Keshavan, Ashvini, Keuss, Sarah E., Buchanan, Sarah M., Murray-Smith, Heidi, Cash, David M., Sudre, Carole H., Malone, Ian B., Coath, William, Wong, Andrew, Henley, Susie M.D., Crutch, Sebastian J., Fox, Nick C., Richards, Marcus, and Schott, Jonathan M.

Published
2019
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43. Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia:Findings from the GENetic Frontotemporal dementia Initiative cohort

Author

Bocchetta, Martina, Todd, Emily G., Bouzigues, Arabella, Cash, David M., Nicholas, Jennifer M., Convery, Rhian S., Russell, Lucy L., Thomas, David L., Malone, Ian B., Iglesias, Juan Eugenio, Van Swieten, John C., Jiskoot, Lize C., Seelaar, Harro, Borroni, Barbara, Galimberti, Daniela, Sanchez-Valle, Raquel, Laforce, Robert, Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B., Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, De Mendonca, Alexandre, Santana, Isabel, Butler, Chris R., Ducharme, Simon, Gerhard, Alexander, Danek, Adrian, Levin, Johannes, Otto, Markus, Sorbi, Sandro, Le Ber, Isabelle, Pasquier, Florence, Rohrer, Jonathan D., Bocchetta, Martina, Todd, Emily G., Bouzigues, Arabella, Cash, David M., Nicholas, Jennifer M., Convery, Rhian S., Russell, Lucy L., Thomas, David L., Malone, Ian B., Iglesias, Juan Eugenio, Van Swieten, John C., Jiskoot, Lize C., Seelaar, Harro, Borroni, Barbara, Galimberti, Daniela, Sanchez-Valle, Raquel, Laforce, Robert, Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B., Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, De Mendonca, Alexandre, Santana, Isabel, Butler, Chris R., Ducharme, Simon, Gerhard, Alexander, Danek, Adrian, Levin, Johannes, Otto, Markus, Sorbi, Sandro, Le Ber, Isabelle, Pasquier, Florence, and Rohrer, Jonathan D.

Abstract

Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative. Three hundred eighty-seven mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR®+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). The w-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as 'normal' or 'abnormal' based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the 'normal' and 'abnormal' groups within each genetic subtype, as measured by the CDR®+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score. Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR®+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 poi

Published
2023

44. Predicting Cognitive Decline in Older Adults Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration

Author

Neurologen, Brain, Circulatory Health, Prosser, Lloyd, MacDougall, Amy, Sudre, Carole H., Manning, Emily N., Malone, Ian B., Walsh, Phoebe, Goodkin, Olivia, Pemberton, Hugh, Barkhof, Frederik, Biessels, Geert Jan, Cash, David M., Barnes, Josephine, Neurologen, Brain, Circulatory Health, Prosser, Lloyd, MacDougall, Amy, Sudre, Carole H., Manning, Emily N., Malone, Ian B., Walsh, Phoebe, Goodkin, Olivia, Pemberton, Hugh, Barkhof, Frederik, Biessels, Geert Jan, Cash, David M., and Barnes, Josephine

Published
2023

45. Operationalizing the centiloid scale for [18 F]florbetapir PET studies on PET/MRI

Author

Coath, William, Modat, Marc, Cardoso, M. Jorge, Markiewicz, Pawel, Lane, Christopher, Parker, Thomas, Keshavan, Ashvini, Buchanan, Sarah, Keuss, Sarah, Harris, Matthew, Burgos, Ninon, Dickson, John, Barnes, Anna, Thomas, David, Beasley, Daniel, Malone, Ian, Wong, Andrew, Erlandsson, Kjell, Thomas, Benjamin, Schöll, Michael, Ourselin, Sebastien, Richards, Marcus, Fox, Nick, Schott, Jonathan, Cash, David, UCL Institute of Neurology, Queen Square [London], King‘s College London, University College of London [London] (UCL), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and University College London Hospitals (UCLH)

Subjects
[INFO.INFO-IM]Computer Science [cs]/Medical Imaging
Abstract

International audience; INTRODUCTIONThe Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid transformation with data from Insight 46 acquired with PET/magnetic resonanceimaging (MRI).METHODSWe transformed standardized uptake value ratios (SUVRs) from 432 florbetapir PET/MRI scans processed using whole cerebellum (WC) and white matter (WM) references, with and without partial volume correction. Gaussian-mixture-modelling–derived cutpoints for Aβ PET positivity were converted.RESULTSThe Centiloid cutpoint was 14.2 for WC SUVRs. The relationship between WM and WC uptake differed between the calibration and testing datasets, producing implausibly low WM-based Centiloids. Linear adjustment produced a WM-based cutpoint of 18.1.DISCUSSIONTransformation of PET/MRI florbetapir data to Centiloids is valid. However, further understanding of the effects of acquisition or biological factors on the transformation using a WM reference is needed.HIGHLIGHTS Centiloid conversion of amyloid beta positron emission tomography (PET) data aims to standardize results. Centiloid values can be influenced by differences in acquisition. We converted florbetapir PET/magnetic resonance imaging data from a large birth cohort. Whole cerebellum referenced values could be reliably transformed to Centiloids. White matter referenced values may be less generalizable between datasets.

Published
2023

46. Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds.

Author

James, Sarah-Naomi, Manning, Emily N., Storey, Mathew, Nicholas, Jennifer M., Coath, William, Keuss, Sarah E., Cash, David M., Lane, Christopher A., Parker, Thomas, Keshavan, Ashvini, Buchanan, Sarah M., Wagen, Aaron, Harris, Mathew, Malone, Ian, Lu, Kirsty, Needham, Louisa P., Street, Rebecca, Thomas, David, Dickson, John, and Murray-Smith, Heidi

Published
2023
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47. Rates of cortical thinning in Alzheimer’s disease signature regions: pathological influences and cognitive consequences in members of the 1946 British birth cohort

Author

Keuss, Sarah E, primary, Cash, David M, additional, Nicholas, Jennifer M, additional, Parker, Thomas D, additional, Lane, Christopher A, additional, Keshavan, Ashvini, additional, Buchanan, Sarah M, additional, Wagen, Aaron Z, additional, Storey, Mathew, additional, Harris, Matthew J, additional, Lu, Kirsty, additional, James, Sarah‐Naomi, additional, Street, Rebecca E, additional, Barnes, Jo, additional, Malone, Ian B, additional, Sudre, Carole H, additional, Thomas, David L, additional, Dickson, John, additional, Murray‐Smith, Heidi, additional, Freiberger, Tamar, additional, Wong, Andrew, additional, Crutch, Sebastian J, additional, Richards, Marcus, additional, Fox, Nick C, additional, Schott, Jonathan M, additional, and Coath, William, additional

Published
2022
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48. Additional file 7 of 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

Abstract

Additional file 7: Supplementary file 7: Supplementary Notes. Supplementary Notes (metabolomics acquisition, metabolomic and genomic quality control, polygenic risk scores, software and packages used, additional analyses, participant characteristics split by amyloid status).

Published
2023
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49. Additional file 6 of 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

Abstract

Additional file 6: Supplementary file 6: Figure 1. A. Plot showing the Zsummary preservation statistics for each module against the module size. Thresholds for moderate and strong evidence of module preservation are indicated. B. Plot showing the median rank for module preservation. Modules are ranked from most preserved (lowest number) to least preserved (highest number).

Published
2023
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