Search

Your search keyword '"Bateman, Randall J"' showing total 1,553 results
Start Over Author "Bateman, Randall J"
1,553 results on '"Bateman, Randall J"'

1. Highly accurate blood test for Alzheimer’s disease is similar or superior to clinical cerebrospinal fluid tests

Author

Barthélemy, Nicolas R, Salvadó, Gemma, Schindler, Suzanne E, He, Yingxin, Janelidze, Shorena, Collij, Lyduine E, Saef, Benjamin, Henson, Rachel L, Chen, Charles D, Gordon, Brian A, Li, Yan, La Joie, Renaud, Benzinger, Tammie LS, Morris, John C, Mattsson-Carlgren, Niklas, Palmqvist, Sebastian, Ossenkoppele, Rik, Rabinovici, Gil D, Stomrud, Erik, Bateman, Randall J, and Hansson, Oskar

Subjects
Biomedical and Clinical Sciences, Health Sciences, Neurodegenerative, Dementia, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Biomedical Imaging, Aging, Neurosciences, Brain Disorders, Alzheimer's Disease, 4.2 Evaluation of markers and technologies, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Neurological, Humans, Alzheimer Disease, tau Proteins, Biomarkers, Amyloid beta-Peptides, Cognitive Dysfunction, Hematologic Tests, Positron-Emission Tomography, Medical and Health Sciences, Immunology, Biomedical and clinical sciences, Health sciences
Abstract

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Published
2024

2. Plasma extracellular vesicle tau and TDP-43 as diagnostic biomarkers in FTD and ALS

Author

Chatterjee, Madhurima, Özdemir, Selcuk, Fritz, Christian, Möbius, Wiebke, Kleineidam, Luca, Mandelkow, Eckhard, Biernat, Jacek, Doğdu, Cem, Peters, Oliver, Cosma, Nicoleta Carmen, Wang, Xiao, Schneider, Luisa-Sophia, Priller, Josef, Spruth, Eike, Kühn, Andrea A., Krause, Patricia, Klockgether, Thomas, Vogt, Ina R., Kimmich, Okka, Spottke, Annika, Hoffmann, Daniel C., Fliessbach, Klaus, Miklitz, Carolin, McCormick, Cornelia, Weydt, Patrick, Falkenburger, Björn, Brandt, Moritz, Guenther, René, Dinter, Elisabeth, Wiltfang, Jens, Hansen, Niels, Bähr, Mathias, Zerr, Inga, Flöel, Agnes, Nestor, Peter J., Düzel, Emrah, Glanz, Wenzel, Incesoy, Enise, Bürger, Katharina, Janowitz, Daniel, Perneczky, Robert, Rauchmann, Boris S., Hopfner, Franziska, Wagemann, Olivia, Levin, Johannes, Teipel, Stefan, Kilimann, Ingo, Goerss, Doreen, Prudlo, Johannes, Gasser, Thomas, Brockmann, Kathrin, Mengel, David, Zimmermann, Milan, Synofzik, Matthis, Wilke, Carlo, Selma-González, Judit, Turon-Sans, Janina, Santos-Santos, Miguel Angel, Alcolea, Daniel, Rubio-Guerra, Sara, Fortea, Juan, Carbayo, Álvaro, Lleó, Alberto, Rojas-García, Ricardo, Illán-Gala, Ignacio, Wagner, Michael, Frommann, Ingo, Roeske, Sandra, Bertram, Lucas, Heneka, Michael T., Brosseron, Frederic, Ramirez, Alfredo, Schmid, Matthias, Beschorner, Rudi, Halle, Annett, Herms, Jochen, Neumann, Manuela, Barthélemy, Nicolas R., Bateman, Randall J., Rizzu, Patrizia, Heutink, Peter, Dols-Icardo, Oriol, Höglinger, Günter, Hermann, Andreas, and Schneider, Anja

Published
2024
Full Text
View/download PDF

3. Disease staging of Alzheimer’s disease using a CSF-based biomarker model

Author

Salvadó, Gemma, Horie, Kanta, Barthélemy, Nicolas R., Vogel, Jacob W., Pichet Binette, Alexa, Chen, Charles D., Aschenbrenner, Andrew J., Gordon, Brian A., Benzinger, Tammie L. S., Holtzman, David M., Morris, John C., Palmqvist, Sebastian, Stomrud, Erik, Janelidze, Shorena, Ossenkoppele, Rik, Schindler, Suzanne E., Bateman, Randall J., and Hansson, Oskar

Published
2024
Full Text
View/download PDF

4. Biomarker-based staging of Alzheimer disease: rationale and clinical applications

Author

Therriault, Joseph, Schindler, Suzanne E., Salvadó, Gemma, Pascoal, Tharick A., Benedet, Andréa Lessa, Ashton, Nicholas J., Karikari, Thomas K., Apostolova, Liana, Murray, Melissa E., Verberk, Inge, Vogel, Jacob W., La Joie, Renaud, Gauthier, Serge, Teunissen, Charlotte, Rabinovici, Gil D., Zetterberg, Henrik, Bateman, Randall J., Scheltens, Philip, Blennow, Kaj, Sperling, Reisa, Hansson, Oskar, Jack, Jr, Clifford R., and Rosa-Neto, Pedro

Published
2024
Full Text
View/download PDF

5. Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center

Author

Fernandez, Maria Victoria, Liu, Menghan, Beric, Aleksandra, Johnson, Matt, Cetin, Arda, Patel, Maulik, Budde, John, Kohlfeld, Pat, Bergmann, Kristy, Lowery, Joseph, Flynn, Allison, Brock, William, Sanchez Montejo, Brenda, Gentsch, Jen, Sykora, Nicholas, Norton, Joanne, Gentsch, Jen, Valdez, Olga, Gorijala, Priyanka, Sanford, Jessie, Sun, Yichen, Wang, Ciyang, Western, Dan, Timsina, Jigyasha, Mangetti Goncalves, Tassia, Do, Anh N., Sung, Yun Ju, Zhao, Guoyan, Morris, John C., Moulder, Krista, Holtzman, David M., Bateman, Randall J., Karch, Celeste, Hassenstab, Jason, Xiong, Chengjie, Schindler, Suzanne E., Balls-Berry, Joyce (Joy), Benzinger, Tammie L. S., Perrin, Richard J., Denny, Andrea, Snider, B. Joy, Stark, Susan L., Ibanez, Laura, and Cruchaga, Carlos

Published
2024
Full Text
View/download PDF

6. Baseline levels and longitudinal changes in plasma Aβ42/40 among Black and white individuals

Author

Xiong, Chengjie, Luo, Jingqin, Wolk, David A., Shaw, Leslie M., Roberson, Erik D., Murchison, Charles F., Henson, Rachel L., Benzinger, Tammie L. S., Bui, Quoc, Agboola, Folasade, Grant, Elizabeth, Gremminger, Emily N., Moulder, Krista L., Geldmacher, David S., Clay, Olivio J., Babulal, Ganesh, Cruchaga, Carlos, Holtzman, David M., Bateman, Randall J., Morris, John C., and Schindler, Suzanne E.

Published
2024
Full Text
View/download PDF

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

Author

Boerwinkle, Anna H, Gordon, Brian A, Wisch, Julie, Flores, Shaney, Henson, Rachel L, Butt, Omar H, McKay, Nicole, Chen, Charles D, Benzinger, Tammie LS, 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, Ances, Beau M, Syndrome, Alzheimer's Biomarker Consortium-Down, 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, McHale, Sharon J Krinsky-, 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, Network, Dominantly Inherited Alzheimer, 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, and DeLaCruz, Chrismary

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Biomedical Imaging, Aging, Alzheimer's Disease, Clinical Research, Neurodegenerative, Brain Disorders, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Intellectual and Developmental Disabilities (IDD), Genetics, Acquired Cognitive Impairment, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Aged, Humans, Middle Aged, Alzheimer Disease, Amyloid beta-Peptides, Apolipoproteins E, Biomarkers, Cross-Sectional Studies, Down Syndrome, Positron-Emission Tomography, Cerebral Cortex, Alzheimer's Biomarker Consortium-Down Syndrome, Dominantly Inherited Alzheimer Network, Neurology & Neurosurgery, Clinical sciences
Abstract

BackgroundImportant insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people.MethodsIn this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid β42 (Aβ42) to Aβ40 (Aβ42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aβ42/40 was evaluated.Findings192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aβ42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p

Published
2023

8. CSF tau microtubule-binding region identifies pathological changes in primary tauopathies

Author

Horie, Kanta, Barthélemy, Nicolas R, Spina, Salvatore, VandeVrede, Lawren, He, Yingxin, Paterson, Ross W, Wright, Brenton A, Day, Gregory S, Davis, Albert A, Karch, Celeste M, Seeley, William W, Perrin, Richard J, Koppisetti, Rama K, Shaikh, Faris, Lago, Argentina Lario, Heuer, Hilary W, Ghoshal, Nupur, Gabelle, Audrey, Miller, Bruce L, Boxer, Adam L, Bateman, Randall J, and Sato, Chihiro

Subjects
Biomedical and Clinical Sciences, Health Sciences, Dementia, Clinical Research, Alzheimer's Disease Related Dementias (ADRD), Pick's Disease, Alzheimer's Disease, Neurodegenerative, Aging, Clinical Trials and Supportive Activities, Brain Disorders, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Rare Diseases, Frontotemporal Dementia (FTD), Neurosciences, Neurological, Humans, Tauopathies, tau Proteins, Alzheimer Disease, Frontotemporal Lobar Degeneration, Frontotemporal Dementia, Biomarkers, Microtubules, Medical and Health Sciences, Immunology, Biomedical and clinical sciences, Health sciences
Abstract

Despite recent advances in fluid biomarker research in Alzheimer's disease (AD), there are no fluid biomarkers or imaging tracers with utility for diagnosis and/or theragnosis available for other tauopathies. Using immunoprecipitation and mass spectrometry, we show that 4 repeat (4R) isoform-specific tau species from microtubule-binding region (MTBR-tau275 and MTBR-tau282) increase in the brains of corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), frontotemporal lobar degeneration (FTLD)-MAPT and AD but decrease inversely in the cerebrospinal fluid (CSF) of CBD, FTLD-MAPT and AD compared to control and other FTLD-tau (for example, Pick's disease). CSF MTBR-tau measures are reproducible in repeated lumbar punctures and can be used to distinguish CBD from control (receiver operating characteristic area under the curve (AUC) = 0.889) and other FTLD-tau, such as PSP (AUC = 0.886). CSF MTBR-tau275 and MTBR-tau282 may represent the first affirmative biomarkers to aid in the diagnosis of primary tauopathies and facilitate clinical trial designs.

Published
2022

9. 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

10. 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
Full Text
View/download PDF

12. Cerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer’s disease

Author

Johnson, Erik C. B., Bian, Shijia, Haque, Rafi U., Carter, E. Kathleen, Watson, Caroline M., Gordon, Brian A., Ping, Lingyan, Duong, Duc M., Epstein, Michael P., McDade, Eric, Barthélemy, Nicolas R., Karch, Celeste M., Xiong, Chengjie, Cruchaga, Carlos, Perrin, Richard J., Wingo, Aliza P., Wingo, Thomas S., Chhatwal, Jasmeer P., Day, Gregory S., Noble, James M., Berman, Sarah B., Martins, Ralph, Graff-Radford, Neill R., Schofield, Peter R., Ikeuchi, Takeshi, Mori, Hiroshi, Levin, Johannes, Farlow, Martin, Lah, James J., Haass, Christian, Jucker, Mathias, Morris, John C., Benzinger, Tammie L. S., Roberts, Blaine R., Bateman, Randall J., Fagan, Anne M., Seyfried, Nicholas T., and Levey, Allan I.

Published
2023
Full Text
View/download PDF

13. CSF MTBR-tau243 is a specific biomarker of tau tangle pathology in Alzheimer’s disease

Author

Horie, Kanta, Salvadó, Gemma, Barthélemy, Nicolas R., Janelidze, Shorena, Li, Yan, He, Yingxin, Saef, Benjamin, Chen, Charles D., Jiang, Hong, Strandberg, Olof, Pichet Binette, Alexa, Palmqvist, Sebastian, Sato, Chihiro, Sachdev, Pallavi, Koyama, Akihiko, Gordon, Brian A., Benzinger, Tammie L. S., Holtzman, David M., Morris, John C., Mattsson-Carlgren, Niklas, Stomrud, Erik, Ossenkoppele, Rik, Schindler, Suzanne E., Hansson, Oskar, and Bateman, Randall J.

Published
2023
Full Text
View/download PDF

14. 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
Full Text
View/download PDF

15. Longitudinal head-to-head comparison of 11C-PiB and 18F-florbetapir PET in a Phase 2/3 clinical trial of anti-amyloid-β monoclonal antibodies in dominantly inherited Alzheimer’s disease

Author

Chen, Charles D., McCullough, Austin, Gordon, Brian, Joseph-Mathurin, Nelly, Flores, Shaney, McKay, Nicole S., Hobbs, Diana A., Hornbeck, Russ, Fagan, Anne M., Cruchaga, Carlos, Goate, Alison M., Perrin, Richard J., Wang, Guoqiao, Li, Yan, Shi, Xinyu, Xiong, Chengjie, Pontecorvo, Michael J., Klein, Gregory, Su, Yi, Klunk, William E., Jack, Clifford, Koeppe, Robert, Snider, B. Joy, Berman, Sarah B., Roberson, Erik D., Brosch, Jared, Surti, Ghulam, Jiménez-Velázquez, Ivonne Z., Galasko, Douglas, Honig, Lawrence S., Brooks, William S., Clarnette, Roger, Wallon, David, Dubois, Bruno, Pariente, Jérémie, Pasquier, Florence, Sanchez-Valle, Raquel, Shcherbinin, Sergey, Higgins, Ixavier, Tunali, Ilke, Masters, Colin L., van Dyck, Christopher H., Masellis, Mario, Hsiung, Robin, Gauthier, Serge, Salloway, Steve, Clifford, David B., Mills, Susan, Supnet-Bell, Charlene, McDade, Eric, Bateman, Randall J., and Benzinger, Tammie L. S.

Published
2023
Full Text
View/download PDF

16. 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
Full Text
View/download PDF

17. 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
Full Text
View/download PDF

18. Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease

Author

Millar, Peter R, Gordon, Brian A, Wisch, Julie K, Schultz, Stephanie A, Benzinger, Tammie LS, Cruchaga, Carlos, Hassenstab, Jason J, Ibanez, Laura, Karch, Celeste, Llibre-Guerra, Jorge J, Morris, John C, Perrin, Richard J, Supnet-Bell, Charlene, Xiong, Chengjie, Allegri, Ricardo F, Berman, Sarah B, Chhatwal, Jasmeer P, Chrem Mendez, Patricio A, Day, Gregory S, Hofmann, Anna, Ikeuchi, Takeshi, Jucker, Mathias, Lee, Jae-Hong, Levin, Johannes, Lopera, Francisco, Niimi, Yoshiki, Sánchez-González, Victor J, Schofield, Peter R, Sosa-Ortiz, Ana Luisa, Vöglein, Jonathan, Bateman, Randall J, Ances, Beau M, and McDade, Eric M

Published
2023
Full Text
View/download PDF

20. Single-nucleus RNA-sequencing of autosomal dominant Alzheimer disease and risk variant carriers

Author

Brase, Logan, You, Shih-Feng, D’Oliveira Albanus, Ricardo, Del-Aguila, Jorge L., Dai, Yaoyi, Novotny, Brenna C., Soriano-Tarraga, Carolina, Dykstra, Taitea, Fernandez, Maria Victoria, Budde, John P., Bergmann, Kristy, Morris, John C., Bateman, Randall J., Perrin, Richard J., McDade, Eric, Xiong, Chengjie, Goate, Alison M., Farlow, Martin, Sutherland, Greg T., Kipnis, Jonathan, Karch, Celeste M., Benitez, Bruno A., and Harari, Oscar

Published
2023
Full Text
View/download PDF

21. Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease

Author

Ali, Muhammad, Archer, Derek B., Gorijala, Priyanka, Western, Daniel, Timsina, Jigyasha, Fernández, Maria V., Wang, Ting-Chen, Satizabal, Claudia L., Yang, Qiong, Beiser, Alexa S., Wang, Ruiqi, Chen, Gengsheng, Gordon, Brian, Benzinger, Tammie L. S., Xiong, Chengjie, Morris, John C., Bateman, Randall J., Karch, Celeste M., McDade, Eric, Goate, Alison, Seshadri, Sudha, Mayeux, Richard P., Sperling, Reisa A., Buckley, Rachel F., Johnson, Keith A., Won, Hong-Hee, Jung, Sang-Hyuk, Kim, Hang-Rai, Seo, Sang Won, Kim, Hee Jin, Mormino, Elizabeth, Laws, Simon M., Fan, Kang-Hsien, Kamboh, M. Ilyas, Vemuri, Prashanthi, Ramanan, Vijay K., Yang, Hyun-Sik, Wenzel, Allen, Rajula, Hema Sekhar Reddy, Mishra, Aniket, Dufouil, Carole, Debette, Stephanie, Lopez, Oscar L., DeKosky, Steven T., Tao, Feifei, Nagle, Michael W., Hohman, Timothy J., Sung, Yun Ju, Dumitrescu, Logan, and Cruchaga, Carlos

Published
2023
Full Text
View/download PDF

22. Validation of Plasma Amyloid-β 42/40 for Detecting Alzheimer Disease Amyloid Plaques

Author

Li, Yan, Schindler, Suzanne E, Bollinger, James G, Ovod, Vitaliy, Mawuenyega, Kwasi G, Weiner, Michael W, Shaw, Leslie M, Masters, Colin L, Fowler, Christopher J, Trojanowski, John Q, Korecka, Magdalena, Martins, Ralph N, Janelidze, Shorena, Hansson, Oskar, and Bateman, Randall J

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Clinical Research, Alzheimer's Disease, Brain Disorders, Acquired Cognitive Impairment, Dementia, Aging, Neurological, Good Health and Well Being, Alzheimer Disease, Amyloid beta-Peptides, Biomarkers, Humans, Peptide Fragments, Plaque, Amyloid, Positron-Emission Tomography, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

Background and objectivesTo determine the diagnostic accuracy of a plasma Aβ42/Aβ40 assay in classifying amyloid PET status across global research studies using samples collected by multiple centers that utilize different blood collection and processing protocols.MethodsPlasma samples (n = 465) were obtained from 3 large Alzheimer disease (AD) research cohorts in the United States (n = 182), Australia (n = 183), and Sweden (n = 100). Plasma Aβ42/Aβ40 was measured by a high precision immunoprecipitation mass spectrometry (IPMS) assay and compared to the reference standards of amyloid PET and CSF Aβ42/Aβ40.ResultsIn the combined cohort of 465 participants, plasma Aβ42/Aβ40 had good concordance with amyloid PET status (receiver operating characteristic area under the curve [AUC] 0.84, 95% confidence interval [CI] 0.80-0.87); concordance improved with the inclusion of APOE ε4 carrier status (AUC 0.88, 95% CI 0.85-0.91). The AUC of plasma Aβ42/Aβ40 with CSF amyloid status was 0.85 (95% CI 0.78-0.91) and improved to 0.93 (95% CI 0.89-0.97) with APOE ε4 status. These findings were consistent across the 3 cohorts, despite differences in protocols. The assay performed similarly in both cognitively unimpaired and impaired individuals.DiscussionPlasma Aβ42/Aβ40 is a robust measure for detecting amyloid plaques and can be utilized to aid in the diagnosis of AD, identify those at risk for future dementia due to AD, and improve the diversity of populations enrolled in AD research and clinical trials.Classification of evidenceThis study provides Class II evidence that plasma Aβ42/Aβ40, as measured by a high precision IPMS assay, accurately diagnoses brain amyloidosis in both cognitively unimpaired and impaired research participants.

Published
2022

23. Does Data-Independent Acquisition Data Contain Hidden Gems? A Case Study Related to Alzheimer’s Disease

Author

Hubbard, Evan E, Heil, Lilian R, Merrihew, Gennifer E, Chhatwal, Jasmeer P, Farlow, Martin R, McLean, Catriona A, Ghetti, Bernardino, Newell, Kathy L, Frosch, Matthew P, Bateman, Randall J, Larson, Eric B, Keene, C Dirk, Perrin, Richard J, Montine, Thomas J, MacCoss, Michael J, and Julian, Ryan R

Subjects
Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease, Brain Disorders, Acquired Cognitive Impairment, Aging, Neurodegenerative, Neurosciences, Neurological, Alzheimer Disease, Amyloid beta-Peptides, Autophagy, Brain, Humans, Proteomics, tau Proteins, proteomics, age-related neurodegenerative disease, proteostasis, lysosome, aspartic acid, amyloid, neurofibrillary tangle, amyloid-beta, post-translational modification, hippocampus, Chemical Sciences, Biological Sciences, Biochemistry & Molecular Biology
Abstract

One of the potential benefits of using data-independent acquisition (DIA) proteomics protocols is that information not originally targeted by the study may be present and discovered by subsequent analysis. Herein, we reanalyzed DIA data originally recorded for global proteomic analysis to look for isomerized peptides, which occur as a result of spontaneous chemical modifications to long-lived proteins. Examination of a large set of human brain samples revealed a striking relationship between Alzheimer's disease (AD) status and isomerization of aspartic acid in a peptide from tau. Relative to controls, a surprising increase in isomer abundance was found in both autosomal dominant and sporadic AD samples. To explore potential mechanisms that might account for these observations, quantitative analysis of proteins related to isomerization repair and autophagy was performed. Differences consistent with reduced autophagic flux in AD-related samples relative to controls were found for numerous proteins, including most notably p62, a recognized indicator of autophagic inhibition. These results suggest, but do not conclusively demonstrate, that lower autophagic flux may be strongly associated with loss of function in AD brains. This study illustrates that DIA data may contain unforeseen results of interest and may be particularly useful for pilot studies investigating new research directions. In this case, a promising target for future investigations into the therapy and prevention of AD has been identified.

Published
2022

24. CSF tau phosphorylation occupancies at T217 and T205 represent improved biomarkers of amyloid and tau pathology in Alzheimer’s disease

Author

Barthélemy, Nicolas R., Saef, Benjamin, Li, Yan, Gordon, Brian A., He, Yingxin, Horie, Kanta, Stomrud, Erik, Salvadó, Gemma, Janelidze, Shorena, Sato, Chihiro, Ovod, Vitaliy, Henson, Rachel L., Fagan, Anne M., Benzinger, Tammie L. S., Xiong, Chengjie, Morris, John C., Hansson, Oskar, Bateman, Randall J., and Schindler, Suzanne E.

Published
2023
Full Text
View/download PDF

25. Accelerated functional brain aging in pre-clinical familial Alzheimer’s disease

Author

Gonneaud, Julie, Baria, Alex T, Pichet Binette, Alexa, Gordon, Brian A, Chhatwal, Jasmeer P, Cruchaga, Carlos, Jucker, Mathias, Levin, Johannes, Salloway, Stephen, Farlow, Martin, Gauthier, Serge, Benzinger, Tammie LS, Morris, John C, Bateman, Randall J, Breitner, John CS, Poirier, Judes, Vachon-Presseau, Etienne, and Villeneuve, Sylvia

Subjects
Biological Psychology, Psychology, Clinical Research, Neurodegenerative, Aging, Brain Disorders, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Alzheimer's Disease, Dementia, Neurological, Adult, Aged, Aged, 80 and over, Alzheimer Disease, Amyloid beta-Peptides, Brain, Brain Mapping, Cognitive Dysfunction, Female, Genetic Predisposition to Disease, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Mutation, Positron-Emission Tomography, Young Adult, Alzheimer’s Disease Neuroimaging Initiative, Dominantly Inherited Alzheimer Network (DIAN) Study Group, Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer’s Disease (PREVENT-AD) Research Group
Abstract

Resting state functional connectivity (rs-fMRI) is impaired early in persons who subsequently develop Alzheimer's disease (AD) dementia. This impairment may be leveraged to aid investigation of the pre-clinical phase of AD. We developed a model that predicts brain age from resting state (rs)-fMRI data, and assessed whether genetic determinants of AD, as well as beta-amyloid (Aβ) pathology, can accelerate brain aging. Using data from 1340 cognitively unimpaired participants between 18-94 years of age from multiple sites, we showed that topological properties of graphs constructed from rs-fMRI can predict chronological age across the lifespan. Application of our predictive model to the context of pre-clinical AD revealed that the pre-symptomatic phase of autosomal dominant AD includes acceleration of functional brain aging. This association was stronger in individuals having significant Aβ pathology.

Published
2021

27. Detection of β-amyloid positivity in Alzheimer’s Disease Neuroimaging Initiative participants with demographics, cognition, MRI and plasma biomarkers

Author

Tosun, Duygu, Veitch, Dallas, Aisen, Paul, Jack, Clifford R, Jagust, William J, Petersen, Ronald C, Saykin, Andrew J, Bollinger, James, Ovod, Vitaliy, Mawuenyega, Kwasi G, Bateman, Randall J, Shaw, Leslie M, Trojanowski, John Q, Blennow, Kaj, Zetterberg, Henrik, and Weiner, Michael W

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Neurodegenerative, Clinical Research, Brain Disorders, Dementia, Biomedical Imaging, Acquired Cognitive Impairment, Alzheimer's Disease, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Neurological, Alzheimer's, beta-amyloid, MRI, PET, plasma, Alzheimer’s, β-amyloid, Clinical sciences, Biological psychology
Abstract

In vivo gold standard for the ante-mortem assessment of brain β-amyloid pathology is currently β-amyloid positron emission tomography or cerebrospinal fluid measures of β-amyloid42 or the β-amyloid42/β-amyloid40 ratio. The widespread acceptance of a biomarker classification scheme for the Alzheimer's disease continuum has ignited interest in more affordable and accessible approaches to detect Alzheimer's disease β-amyloid pathology, a process that often slows down the recruitment into, and adds to the cost of, clinical trials. Recently, there has been considerable excitement concerning the value of blood biomarkers. Leveraging multidisciplinary data from cognitively unimpaired participants and participants with mild cognitive impairment recruited by the multisite biomarker study of Alzheimer's Disease Neuroimaging Initiative, here we assessed to what extent plasma β-amyloid42/β-amyloid40, neurofilament light and phosphorylated-tau at threonine-181 biomarkers detect the presence of β-amyloid pathology, and to what extent the addition of clinical information such as demographic data, APOE genotype, cognitive assessments and MRI can assist plasma biomarkers in detecting β-amyloid-positivity. Our results confirm plasma β-amyloid42/β-amyloid40 as a robust biomarker of brain β-amyloid-positivity (area under curve, 0.80-0.87). Plasma phosphorylated-tau at threonine-181 detected β-amyloid-positivity only in the cognitively impaired with a moderate area under curve of 0.67, whereas plasma neurofilament light did not detect β-amyloid-positivity in either group of participants. Clinical information as well as MRI-score independently detected positron emission tomography β-amyloid-positivity in both cognitively unimpaired and impaired (area under curve, 0.69-0.81). Clinical information, particularly APOE ε4 status, enhanced the performance of plasma biomarkers in the detection of positron emission tomography β-amyloid-positivity by 0.06-0.14 units of area under curve for cognitively unimpaired, and by 0.21-0.25 units for cognitively impaired; and further enhancement of these models with an MRI-score of β-amyloid-positivity yielded an additional improvement of 0.04-0.11 units of area under curve for cognitively unimpaired and 0.05-0.09 units for cognitively impaired. Taken together, these multi-disciplinary results suggest that when combined with clinical information, plasma phosphorylated-tau at threonine-181 and neurofilament light biomarkers, and an MRI-score could effectively identify β-amyloid+ cognitively unimpaired and impaired (area under curve, 0.80-0.90). Yet, when the MRI-score is considered in combination with clinical information, plasma phosphorylated-tau at threonine-181 and plasma neurofilament light have minimal added value for detecting β-amyloid-positivity. Our systematic comparison of β-amyloid-positivity detection models identified effective combinations of demographics, APOE, global cognition, MRI and plasma biomarkers. Promising minimally invasive and low-cost predictors such as plasma biomarkers of β-amyloid42/β-amyloid40 may be improved by age and APOE genotype.

Published
2021

28. Item response theory analysis of the Clinical Dementia Rating.

Author

Li, Yan, Xiong, Chengjie, Aschenbrenner, Andrew J, Chang, Chih-Hung, Weiner, Michael W, Nosheny, Rachel L, Mungas, Dan, Bateman, Randall J, Hassenstab, Jason, Moulder, Krista L, and Morris, John C

Subjects
Humans, Alzheimer Disease, Psychiatric Status Rating Scales, Algorithms, Aged, Female, Male, Cognitive Dysfunction, Mental Status and Dementia Tests, Alzheimer's disease, Clinical Dementia Rating, bi-factor model, cognitive assessment, dementia severity, item response theory, Alzheimer's Disease, Brain Disorders, Neurosciences, Dementia, Acquired Cognitive Impairment, Neurodegenerative, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurological, Alzheimer&apos, s disease, bi&#8208, factor model, Clinical Sciences, Geriatrics
Abstract

IntroductionThe Clinical Dementia Rating (CDR) is widely used in Alzheimer's disease research studies and has well established reliability and validity. To facilitate the development of an online, electronic CDR (eCDR) for more efficient clinical applications, this study aims to produce a shortened version of the CDR, and to develop the statistical model for automatic scoring.MethodsItem response theory (IRT) was used for item evaluation and model development. An automatic scoring algorithm was validated using existing CDR global and domain box scores as the reference standard.ResultsMost CDR items discriminate well at mild and very mild levels of cognitive impairment. The bi-factor IRT model fits best and the shortened CDR still demonstrates very high classification accuracy (81%∼92%).DiscussionThe shortened version of the CDR and the automatic scoring algorithm has established a good foundation for developing an eCDR and will ultimately improve the efficiency of cognitive assessment.

Published
2021

30. Differential roles of Aβ42/40, p-tau231 and p-tau217 for Alzheimer’s trial selection and disease monitoring

Author

Ashton, Nicholas J., Janelidze, Shorena, Mattsson-Carlgren, Niklas, Binette, Alexa Pichet, Strandberg, Olof, Brum, Wagner S., Karikari, Thomas K., González-Ortiz, Fernándo, Di Molfetta, Guglielmo, Meda, Francisco J., Jonaitis, Erin M., Koscik, Rebecca Langhough, Cody, Karly, Betthauser, Tobey J., Li, Yan, Vanmechelen, Eugeen, Palmqvist, Sebastian, Stomrud, Erik, Bateman, Randall J., Zetterberg, Henrik, Johnson, Sterling C., Blennow, Kaj, and Hansson, Oskar

Published
2022
Full Text
View/download PDF

32. 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

33. Comparison of Pittsburgh compound B and florbetapir in cross‐sectional and longitudinal studies

Author

Su, Yi, Flores, Shaney, Wang, Guoqiao, Hornbeck, Russ C, Speidel, Benjamin, Joseph‐Mathurin, Nelly, Vlassenko, Andrei G, Gordon, Brian A, Koeppe, Robert A, Klunk, William E, Jack, Clifford R, Farlow, Martin R, Salloway, Stephen, Snider, Barbara J, Berman, Sarah B, Roberson, Erik D, Brosch, Jared, Jimenez‐Velazques, Ivonne, Dyck, Christopher H, Galasko, Douglas, Yuan, Shauna H, Jayadev, Suman, Honig, Lawrence S, Gauthier, Serge, Hsiung, Ging‐Yuek R, Masellis, Mario, Brooks, William S, Fulham, Michael, Clarnette, Roger, Masters, Colin L, Wallon, David, Hannequin, Didier, Dubois, Bruno, Pariente, Jeremie, Sanchez‐Valle, Raquel, Mummery, Catherine, Ringman, John M, Bottlaender, Michel, Klein, Gregory, Milosavljevic‐Ristic, Smiljana, McDade, Eric, Xiong, Chengjie, Morris, John C, Bateman, Randall J, and Benzinger, Tammie LS

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Bioengineering, Aging, Alzheimer's Disease, Clinical Research, Brain Disorders, Neurodegenerative, Dementia, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Biomedical Imaging, Neurosciences, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, PiB, Florbetapir, Amyloid imaging, Centiloid, Positron emission tomography, Genetics, Biological psychology
Abstract

IntroductionQuantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design.MethodsPittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally.ResultsGlobal amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers.DiscussionAlthough the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.

Published
2019

34. An atlas of cortical circular RNA expression in Alzheimer disease brains demonstrates clinical and pathological associations

Author

Dube, Umber, Del-Aguila, Jorge L, Li, Zeran, Budde, John P, Jiang, Shan, Hsu, Simon, Ibanez, Laura, Fernandez, Maria Victoria, Farias, Fabiana, Norton, Joanne, Gentsch, Jen, Wang, Fengxian, Salloway, Stephen, Masters, Colin L, Lee, Jae-Hong, Graff-Radford, Neill R, Chhatwal, Jasmeer P, Bateman, Randall J, Morris, John C, Karch, Celeste M, Harari, Oscar, and Cruchaga, Carlos

Subjects
Brain Disorders, Neurodegenerative, Aging, Dementia, Acquired Cognitive Impairment, Genetics, Alzheimer's Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Neurological, Alzheimer Disease, Atlases as Topic, Case-Control Studies, Gene Expression Profiling, Humans, MicroRNAs, Parietal Lobe, RNA, Circular, RNA, Messenger, Sequence Analysis, RNA, Severity of Illness Index, Dominantly Inherited Alzheimer Network, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Parietal cortex RNA-sequencing (RNA-seq) data were generated from individuals with and without Alzheimer disease (AD; ncontrol = 13; nAD = 83) from the Knight Alzheimer Disease Research Center (Knight ADRC). Using this and an independent (Mount Sinai Brain Bank (MSBB)) AD RNA-seq dataset, cortical circular RNA (circRNA) expression was quantified in the context of AD. Significant associations were identified between circRNA expression and AD diagnosis, clinical dementia severity and neuropathological severity. It was demonstrated that most circRNA-AD associations are independent of changes in cognate linear messenger RNA expression or estimated brain cell-type proportions. Evidence was provided for circRNA expression changes occurring early in presymptomatic AD and in autosomal dominant AD. It was also observed that AD-associated circRNAs co-expressed with known AD genes. Finally, potential microRNA-binding sites were identified in AD-associated circRNAs for miRNAs predicted to target AD genes. Together, these results highlight the importance of analyzing non-linear RNAs and support future studies exploring the potential roles of circRNAs in AD pathogenesis.

Published
2019

35. 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
Full Text
View/download PDF

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

Author

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

Published
2024
Full Text
View/download PDF

37. Cerebrospinal fluid neurofilament light chain profiling and quantitation in neurological diseases

Author

Leckey, Claire A, primary, Coulton, John B, additional, Giovannucci, Tatiana A, additional, He, Yingxin, additional, Aslanyan, Aram, additional, Laban, Rhiannon, additional, Heslegrave, Amanda, additional, Doykov, Ivan, additional, Ammoscato, Francesca, additional, Chataway, Jeremy, additional, De Angelis, Floriana, additional, Gnanapavan, Sharmilee, additional, Byrne, Lauren M, additional, Schott, Jonathan M, additional, Wild, Edward J, additional, Barthelémy, Nicolas R, additional, Zetterberg, Henrik, additional, Wray, Selina, additional, Bateman, Randall J, additional, Mills, Kevin, additional, and Paterson, Ross W, additional

Published
2024
Full Text
View/download PDF

39. Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease

Author

Strain, Jeremy F., Brier, Matthew R., Tanenbaum, Aaron, Gordon, Brian A., McCarthy, John E., Dincer, Aylin, Marcus, Daniel S., Chhatwal, Jasmeer P., Graff-Radford, Neill R., Day, Gregory S., la Fougère, Christian, Perrin, Richard J., Salloway, Stephen, Schofield, Peter R., Yakushev, Igor, Ikeuchi, Takeshi, Vöglein, Jonathan, Morris, John C., Benzinger, Tammie L.S., Bateman, Randall J., Ances, Beau M., and Snyder, Abraham Z.

Published
2022
Full Text
View/download PDF

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

Author

Preische, Oliver, Schultz, Stephanie A, Apel, Anja, Kuhle, Jens, Kaeser, Stephan A, Barro, Christian, Gräber, Susanne, Kuder-Buletta, Elke, LaFougere, Christian, Laske, Christoph, Vöglein, Jonathan, Levin, Johannes, Masters, Colin L, Martins, Ralph, Schofield, Peter R, Rossor, Martin N, Graff-Radford, Neill R, Salloway, Stephen, Ghetti, Bernardino, Ringman, John M, Noble, James M, Chhatwal, Jasmeer, Goate, Alison M, Benzinger, Tammie LS, Morris, John C, Bateman, Randall J, Wang, Guoqiao, Fagan, Anne M, McDade, Eric M, Gordon, Brian A, and Jucker, Mathias

Subjects
Dementia, Alzheimer's Disease, Aging, Acquired Cognitive Impairment, Neurosciences, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Clinical Research, Detection, screening and diagnosis, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Aetiology, Neurological, Good Health and Well Being, Alzheimer Disease, Disease Progression, Humans, Mutation, Nerve Degeneration, Neurofilament Proteins, Dominantly Inherited Alzheimer Network, Medical and Health Sciences, Immunology
Abstract

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker.

Published
2019

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

Author

Suárez‐Calvet, Marc, Capell, Anja, Caballero, Miguel Ángel Araque, Morenas‐Rodríguez, Estrella, Fellerer, Katrin, Franzmeier, Nicolai, Kleinberger, Gernot, Eren, Erden, Deming, Yuetiva, Piccio, Laura, Karch, Celeste M, Cruchaga, Carlos, Paumier, Katrina, Bateman, Randall J, Fagan, Anne M, Morris, John C, Levin, Johannes, Danek, Adrian, Jucker, Mathias, Masters, Colin L, Rossor, Martin N, Ringman, John M, Shaw, Leslie M, Trojanowski, John Q, Weiner, Michael, Ewers, Michael, Haass, Christian, Network, the Dominantly Inherited Alzheimer, and Initiative, the Alzheimer's Disease Neuroimaging

Subjects
Biochemistry and Cell Biology, Biological Sciences, Genetics, Neurodegenerative, Aging, Brain Disorders, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Clinical Research, Alzheimer's Disease, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Alzheimer Disease, Cognitive Dysfunction, Cross-Sectional Studies, Female, Humans, Male, Membrane Glycoproteins, Microglia, Middle Aged, Progranulins, Receptors, Immunologic, Dominantly Inherited Alzheimer Network, Alzheimer's Disease Neuroimaging Initiative, Alzheimer's disease, TREM2, biomarker, microglia, progranulin, Medical and Health Sciences, Biochemistry and cell biology
Abstract

Progranulin (PGRN) is predominantly expressed by microglia in the brain, and genetic and experimental evidence suggests a critical role in Alzheimer's disease (AD). We asked whether PGRN expression is changed in a disease severity-specific manner in AD We measured PGRN in cerebrospinal fluid (CSF) in two of the best-characterized AD patient cohorts, namely the Dominant Inherited Alzheimer's Disease Network (DIAN) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). In carriers of AD causing dominant mutations, cross-sectionally assessed CSF PGRN increased over the course of the disease and significantly differed from non-carriers 10 years before the expected symptom onset. In late-onset AD, higher CSF PGRN was associated with more advanced disease stages and cognitive impairment. Higher CSF PGRN was associated with higher CSF soluble TREM2 (triggering receptor expressed on myeloid cells 2) only when there was underlying pathology, but not in controls. In conclusion, we demonstrate that, although CSF PGRN is not a diagnostic biomarker for AD, it may together with sTREM2 reflect microglial activation during the disease.

Published
2018

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

Author

Caballero, Miguel Ángel Araque, Suárez-Calvet, Marc, Duering, Marco, Franzmeier, Nicolai, Benzinger, Tammie, Fagan, Anne M, Bateman, Randall J, Jack, Clifford R, Levin, Johannes, Dichgans, Martin, Jucker, Mathias, Karch, Celeste, Masters, Colin L, Morris, John C, Weiner, Michael, Rossor, Martin, Fox, Nick C, Lee, Jae-Hong, Salloway, Stephen, Danek, Adrian, Goate, Alison, Yakushev, Igor, Hassenstab, Jason, Schofield, Peter R, Haass, Christian, and Ewers, Michael

Subjects
Health Services and Systems, Health Sciences, Neurosciences, Dementia, Biomedical Imaging, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Brain Disorders, Alzheimer's Disease, Neurodegenerative, Aging, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Alzheimer Disease, Brain, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, White Matter, Alzheimer's disease, autosomal dominant, white matter, diffusion tensor imaging, TREM2, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

White matter alterations are present in the majority of patients with Alzheimer's disease type dementia. However, the spatiotemporal pattern of white matter changes preceding dementia symptoms in Alzheimer's disease remains unclear, largely due to the inherent diagnostic uncertainty in the preclinical phase and increased risk of confounding age-related vascular disease and stroke in late-onset Alzheimer's disease. In early-onset autosomal-dominantly inherited Alzheimer's disease, participants are destined to develop dementia, which provides the opportunity to assess brain changes years before the onset of symptoms, and in the absence of ageing-related vascular disease. Here, we assessed mean diffusivity alterations in the white matter in 64 mutation carriers compared to 45 non-carrier family non-carriers. Using tract-based spatial statistics, we mapped the interaction of mutation status by estimated years from symptom onset on mean diffusivity. For major atlas-derived fibre tracts, we determined the earliest time point at which abnormal mean diffusivity changes in the mutation carriers were detectable. Lastly, we assessed the association between mean diffusivity and cerebrospinal fluid biomarkers of amyloid, tau, phosphorylated-tau, and soluble TREM2, i.e. a marker of microglia activity. Results showed a significant interaction of mutations status by estimated years from symptom onset, i.e. a stronger increase of mean diffusivity, within the posterior parietal and medial frontal white matter in mutation carriers compared with non-carriers. The earliest increase of mean diffusivity was observed in the forceps major, forceps minor and long projecting fibres-many connecting default mode network regions-between 5 to 10 years before estimated symptom onset. Higher mean diffusivity in fibre tracts was associated with lower grey matter volume in the tracts' projection zones. Global mean diffusivity was correlated with lower cerebrospinal fluid levels of amyloid-β1-42 but higher levels of tau, phosphorylated-tau and soluble TREM2. Together, these results suggest that regionally selective white matter degeneration occurs years before the estimated symptom onset. Such white matter alterations are associated with primary Alzheimer's disease pathology and microglia activity in the brain.

Published
2018

43. 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
Full Text
View/download PDF

44. Soluble TREM2 in CSF and its association with other biomarkers and cognition in autosomal-dominant Alzheimer's disease: a longitudinal observational study

Author

Adams, Sarah, Allegri, Ricardo, Araki, Aki, Barthelemy, Nicolas, Bechara, Jacob, Berman, Sarah, Bodge, Courtney, Brandon, Susan, Brooks, William (Bill), Brosch, Jared, Buck, Jill, Buckles, Virginia, Carter, Kathleen, Cash, Lisa, Chen, Charlie, Chhatwal, Jasmeer, Chrem, Patricio, Chua, Jasmin, Chui, Helena, Cruchaga, Carlos, Day, Gregory S, De La Cruz, Chrismary, Denner, Darcy, Diffenbacher, Anna, Dincer, Aylin, Donahue, Tamara, Douglas, Jane, Duong, Duc, Egido, Noelia, Esposito, Bianca, Farlow, Marty, Feldman, Becca, Fitzpatrick, Colleen, Flores, Shaney, Fox, Nick, Franklin, Erin, Friedrichsen, 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, Häsler, 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, Käser, Stephan, Kasuga, Kensaku, Keefe, Sarah, Klunk, William (Bill), Koeppe, Robert, Koudelis, Deb, Kuder-Buletta, Elke, Laske, Christoph, Levey, Allan, Lopez, Oscar, Marsh, Jacob, Martinez, Rita, Martins, Ralph, Mason, Neal Scott, Masters, Colin, Mawuenyega, Kwasi, McCullough, Austin, Mejia, Arlene, MountzMD, James, Mummery, Cath, Nadkarni, Neelesh, Nagamatsu, Akemi, Neimeyer, Katie, Niimi, Yoshiki, Noble, James, Norton, Joanne, Nuscher, Brigitte, O'Connor, Antoinette, Obermüller, Ulricke, Patira, Riddhi, Perrin, Richard, Ping, Lingyan, Preische, Oliver, Renton, Alan, Ringman, John, Salloway, Stephen, Schofield, Peter, Senda, Michio, Seyfried, Nick, Shady, Kristine, Shimada, Hiroyuki, Sigurdson, Wendy, Smith, Jennifer, Smith, Lori, Snitz, Beth, Sohrabi, Hamid, Stephens, Sochenda, Taddei, Kevin, Thompson, Sarah, Wang, Peter, Wang, Qing, Weamer, Elise, Xu, Jinbin, Xu, Xiong, Morenas-Rodríguez, Estrella, Li, Yan, Franzmeier, Nicolai, Xiong, Chengjie, Suárez-Calvet, Marc, Fagan, Anne M, Schultz, Stephanie, Gordon, Brian A, Benzinger, Tammie L S, Hassenstab, Jason, McDade, Eric, Feederle, Regina, Karch, Celeste M, Schlepckow, Kai, Morris, John C, Kleinberger, Gernot, Nellgard, Bengt, Vöglein, Jonathan, Blennow, Kaj, Zetterberg, Henrik, Ewers, Michael, Jucker, Mathias, Levin, Johannes, Bateman, Randall J, and Haass, Christian

Published
2022
Full Text
View/download PDF

45. Circular RNA detection identifies circPSEN1 alterations in brain specific to autosomal dominant Alzheimer's disease

Author

Chen, Hsiang-Han, Eteleeb, Abdallah, Wang, Ciyang, Fernandez, Maria Victoria, Budde, John P., Bergmann, Kristy, Norton, Joanne, Wang, Fengxian, Ebl, Curtis, Morris, John C., Perrin, Richard J., Bateman, Randall J., McDade, Eric, Xiong, Chengjie, Goate, Alison, Farlow, Martin, Chhatwal, Jasmeer, Schofield, Peter R., Chui, Helena, Harari, Oscar, Cruchaga, Carlos, and Ibanez, Laura

Published
2022
Full Text
View/download PDF

46. Discovery and validation of dominantly inherited Alzheimer’s disease mutations in populations from Latin America

Author

Takada, Leonel Tadao, Aláez-Verson, Carmen, Burgute, Bhagyashri D., Nitrini, Ricardo, Sosa, Ana Luisa, Castilhos, Raphael Machado, Chaves, Marcia Fagundes, Longoria, Erika-Mariana, Carrillo-Sánchez, Karol, Brucki, Sonia Maria Dozzi, Flores-Lagunes, Luis Leonardo, Molina, Carolina, Olivares, Marcos Jimenez, Ziegemeier, Ellen, Petranek, Jennifer, Goate, Alison M., Cruchaga, Carlos, Renton, Alan E., Fernández, Maria Victoria, Day, Gregory S., McDade, Eric, Bateman, Randall J., Karch, Celeste M., and Llibre-Guerra, Jorge J.

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results