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

Author

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

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Dementia, Alzheimer's Disease, Biomedical Imaging, Brain Disorders, Clinical Research, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Neurodegenerative, 2.1 Biological and endogenous factors, 4.2 Evaluation of markers and technologies, Neurological, Good Health and Well Being, Alzheimer's disease, amyloid-PET, brain glucose metabolism, FDG-PET, Alzheimer’s disease, Clinical sciences, Biological psychology
Abstract

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

Published
2024

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

Author

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

Published
2024
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3. Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration

Author

Boyle, Rory, Townsend, Diana L., Klinger, Hannah M., Scanlon, Catherine E., Yuan, Ziwen, Coughlan, Gillian T., Seto, Mabel, Shirzadi, Zahra, Yau, Wai-Ying Wendy, Jutten, Roos J., Schneider, Christoph, Farrell, Michelle E., Hanseeuw, Bernard J., Mormino, Elizabeth C., Yang, Hyun-Sik, Papp, Kathryn V., Amariglio, Rebecca E., Jacobs, Heidi I. L., Price, Julie C., Chhatwal, Jasmeer P., Schultz, Aaron P., Properzi, Michael J., Rentz, Dorene M., Johnson, Keith A., Sperling, Reisa A., Hohman, Timothy J., Donohue, Michael C., and Buckley, Rachel F.

Published
2024
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4. Longitudinal clinical, cognitive and biomarker profiles in dominantly inherited versus sporadic early-onset Alzheimer’s disease

Author

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

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

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

Published
2023

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

Author

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

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

Author

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

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

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

Published
2023

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. 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

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

Author

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

Published
2024
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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
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11. 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
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12. Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

Author

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

Published
2023
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13. Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging

Author

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

Published
2024
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14. 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

15. The Advisory Group on Risk Evidence Education for Dementia: Multidisciplinary and Open to All.

Author

Rosen, Allyson C, Arias, Jalayne J, Ashford, J Wesson, Blacker, Deborah, Chhatwal, Jasmeer P, Chin, Nathan A, Clark, Lindsay, Denny, Sharon S, Goldman, Jill S, Gleason, Carey E, Grill, Joshua D, Heidebrink, Judith L, Henderson, Victor W, Lavacot, James A, Lingler, Jennifer H, Menon, Malavika, Nosheny, Rachel L, Oliveira, Fabricio F, Parker, Monica W, Rahman-Filipiak, Annalise, Revoori, Anwita, Rumbaugh, Malia C, Sanchez, Danurys L, Schindler, Suzanne E, Schwarz, Christopher G, Toy, Leslie, Tyrone, Jamie, Walter, Sarah, Wang, Li-San, Wijsman, Ellen M, Zallen, Doris T, and Aggarwal, Neelum T

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Brain Disorders, Clinical Research, Dementia, Alzheimer's Disease, Prevention, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Acquired Cognitive Impairment, Neurodegenerative, Behavioral and Social Science, Neurological, Humans, Alzheimer Disease, Cognitive Dysfunction, Amyloid, Biomarkers, Alzheimer's disease, amyloid, biomarkers, dementia, genetics, members of AGREEDementia, Alzheimer’s disease, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences, Biological psychology
Abstract

The brain changes of Alzheimer's disease and other degenerative dementias begin long before cognitive dysfunction develops, and in people with subtle cognitive complaints, clinicians often struggle to predict who will develop dementia. The public increasingly sees benefits to accessing dementia risk evidence (DRE) such as biomarkers, predictive algorithms, and genetic information, particularly as this information moves from research to demonstrated usefulness in guiding diagnosis and clinical management. For example, the knowledge that one has high levels of amyloid in the brain may lead one to seek amyloid reducing medications, plan for disability, or engage in health promoting behaviors to fight cognitive decline. Researchers often hesitate to share DRE data, either because they are insufficiently validated or reliable for use in individuals, or there are concerns about assuring responsible use and ensuring adequate understanding of potential problems when one's biomarker status is known. Concerns include warning people receiving DRE about situations in which they might be compelled to disclose their risk status potentially leading to discrimination or stigma. The Advisory Group on Risk Evidence Education for Dementia (AGREEDementia) welcomes all concerned with how best to share and use DRE. Supporting understanding in clinicians, stakeholders, and people with or at risk for dementia and clearly delineating risks, benefits, and gaps in knowledge is vital. This brief overview describes elements that made this group effective as a model for other health conditions where there is interest in unfettered collaboration to discuss diagnostic uncertainty and the appropriate use and communication of health-related risk information.

Published
2022

16. 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
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18. 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

19. Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease

Author

Keret, Ophir, Staffaroni, Adam M, Ringman, John M, Cobigo, Yann, Goh, Sheng‐Yang M, Wolf, Amy, Allen, Isabel Elaine, Salloway, Stephen, Chhatwal, Jasmeer, Brickman, Adam M, Reyes‐Dumeyer, Dolly, Bateman, Randal J, Benzinger, Tammie LS, Morris, John C, Ances, Beau M, Joseph‐Mathurin, Nelly, Perrin, Richard J, Gordon, Brian A, Levin, Johannes, Vöglein, Jonathan, Jucker, Mathias, la Fougère, Christian, Martins, Ralph N, Sohrabi, Hamid R, Taddei, Kevin, Villemagne, Victor L, Schofield, Peter R, Brooks, William S, Fulham, Michael, Masters, Colin L, Ghetti, Bernardino, Saykin, Andrew J, Jack, Clifford R, Graff‐Radford, Neill R, Weiner, Michael, Cash, David M, Allegri, Ricardo F, Chrem, Patricio, Yi, Su, Miller, Bruce L, Rabinovici, Gil D, Rosen, Howard J, and Network, Dominantly Inherited Alzheimer

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Neurosciences, Psychology, Aging, Prevention, Neurodegenerative, Alzheimer's Disease, Dementia, Brain Disorders, Acquired Cognitive Impairment, Genetics, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Patient Safety, Neurological, Good Health and Well Being, autosomal dominant Alzheimer's disease, brain atrophy, Dominantly Inherited Alzheimer Network, preclinical Alzheimer's disease, Biological psychology
Abstract

IntroductionAsymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment.MethodsWe created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally.ResultsOur risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset.DiscussionIndividualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.

Published
2021

21. 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

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

Author

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

Published
2023
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24. 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

25. 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

26. 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
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27. CSF Tau phosphorylation at Thr205 is associated with loss of white matter integrity in autosomal dominant Alzheimer disease

Author

Strain, Jeremy F., Barthelemy, Nicolas, Horie, Kanta, Gordon, Brian A., Kilgore, Collin, Aschenbrenner, Andrew, Cruchaga, Carlos, Xiong, Chengjie, Joseph-Mathurin, Nelly, Hassenstab, Jason, Fagan, Anne M., Li, Yan, Karch, Celeste M., Perrin, Richard J., Berman, Sarah B., Chhatwal, Jasmeer P., Graff-Radford, Neill R., Mori, Hiroshi, Levin, Johannes, Noble, James M., Allegri, Ricardo, Schofield, Peter R., Marcus, Daniel S., Holtzman, David M., Morris, John C., Benzinger, Tammie L.S., McDade, Eric M., Bateman, Randall J., and Ances, Beau M.

Published
2022
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28. Identification of fibrinogen as a plasma protein binding partner for lecanemab biosimilar IgG.

Author

Bellier, Jean‐Pierre, Román Viera, Andrea M., Christiano, Caitlyn, Anzai, Juliana A. U., Moreno, Stephanie, Campbell, Emily C., Godwin, Lucas, Li, Amy, Chen, Alan Y., Alam, Sarah M., Saba, Adriana, Yoo, Han Bin, Yang, Hyun‐Sik, Chhatwal, Jasmeer P., Selkoe, Dennis J., and Liu, Lei

Abstract

Objective: Recombinant monoclonal therapeutic antibodies like lecanemab, which target amyloid beta in Alzheimer's disease, offer a promising approach for modifying the disease progression. Due to its relatively short half‐life, lecanemab administered as a bi‐monthly infusion (typically 10 mg/kg) has a relatively brief half‐life. Interaction with abundant plasma proteins binder in the bloodstream can affect pharmacokinetics of drugs, including their half‐life. In this study, we investigated potential plasma protein binding (PPB) interaction to lecanemab using lecanemab biosimilar. Methods: Lecanemab biosimilar used in this study was based on publicly available sequences. ELISA and western blotting were used to assess lecanemab biosimilar immunoreactivity in the fractions of human plasma obtained through size exclusion chromatography. The binding of lecanemab biosimilar to candidate plasma binders was confirmed by western blotting, ELISA, and surface plasmon resonance analysis. Results: Using a combination of equilibrium dialysis, ELISA, and western blotting in human plasma, we first describe the presence of likely PPB partners to lecanemab biosimilar and then identify fibrinogen as one of them. Utilizing surface plasmon resonance, we confirmed that lecanemab biosimilar does bind to fibrinogen, although with lower affinity than to monomeric amyloid beta. Interpretation: In the context of lecanemab therapy, these results imply that fibrinogen levels could impact the levels of free antibodies in the bloodstream and that fibrinogen might serve as a reservoir for lecanemab. More broadly, these results indicate that PPB may be an important consideration when clinically utilizing therapeutic antibodies in neurodegenerative disease. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Longitudinal associations between exercise and biomarkers in autosomal dominant Alzheimer's disease.

Author

Sewell, Kelsey R., Doecke, James D., Xiong, Chengjie, Benzinger, Tammie, Masters, Colin L., Laske, Christoph, Jucker, Mathias, Lopera, Francisco, Gordon, Brian A., Llibre‐Guerra, Jorge, Levin, Johannes, Huey, Edward D., Hassenstab, Jason, Schofield, Peter R., Day, Gregory S., Fox, Nick C., Chhatwal, Jasmeer, Ibanez, Laura, Roh, Jee Hoon, and Perrin, Richard

Abstract

INTRODUCTION: We investigated longitudinal associations between self‐reported exercise and Alzheimer's disease (AD)‐related biomarkers in individuals with autosomal dominant AD (ADAD) mutations. METHODS: Participants were 308 ADAD mutation carriers aged 39.7 ± 10.8 years from the Dominantly Inherited Alzheimer's Network. Weekly exercise volume was measured via questionnaire and associations with brain volume (magnetic resonance imaging), cerebrospinal fluid biomarkers, and brain amyloid beta (Aβ) measured by positron emission tomography were investigated. RESULTS: Greater volume of weekly exercise at baseline was associated with slower accumulation of brain Aβ at preclinical disease stages β = –0.16 [–0.23 to –0.08], and a slower decline in multiple brain regions including hippocampal volume β = 0.06 [0.03 to 0.08]. DISCUSSION: Exercise is associated with more favorable profiles of AD‐related biomarkers in individuals with ADAD mutations. Exercise may have therapeutic potential for delaying the onset of AD; however, randomized controlled trials are vital to determine a causal relationship before a clinical recommendation of exercise is implemented. Highlights: Greater self‐reported weekly exercise predicts slower declines in brain volume in autosomal dominant Alzheimer's disease (ADAD).Greater self‐reported weekly exercise predicts slower accumulation of brain amyloid beta in ADAD.Associations varied depending on closeness to estimated symptom onset. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Variant-dependent heterogeneity in amyloid β burden in autosomal dominant Alzheimer's disease: cross-sectional and longitudinal analyses of an observational study

Author

Chhatwal, Jasmeer P, Schultz, Stephanie A, McDade, Eric, Schultz, Aaron P, Liu, Lei, Hanseeuw, Bernard J, Joseph-Mathurin, Nelly, Feldman, Rebecca, Fitzpatrick, Colleen D, Sparks, Kathryn P, Levin, Johannes, Berman, Sarah B, Renton, Alan E, Esposito, Bianca T, Fernandez, Maria Vitoria, Sung, Yun Ju, Lee, Jae Hong, Klunk, William E, Hofmann, Anna, Noble, James M, Graff-Radford, Neill, Mori, Hiroshi, Salloway, Steven M, Masters, Colin L, Martins, Ralph, Karch, Celeste M, Xiong, Chengjie, Cruchaga, Carlos, Perrin, Richard J, Gordon, Brian A, Benzinger, Tammie L S, Fox, Nick C, Schofield, Peter R, Fagan, Anne M, Goate, Alison M, Morris, John C, Bateman, Randall J, Johnson, Keith A, and Sperling, Reisa A

Published
2022
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32. Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer’s disease

Author

Franzmeier, Nicolai, Düzel, Emrah, Jessen, Frank, Buerger, Katharina, Levin, Johannes, Duering, Marco, Dichgans, Martin, Haass, Christian, Suárez-Calvet, Marc, Fagan, Anne M, Paumier, Katrina, Benzinger, Tammie, Masters, Colin L, Morris, John C, Perneczky, Robert, Janowitz, Daniel, Catak, Cihan, Wolfsgruber, Steffen, Wagner, Michael, Teipel, Stefan, Kilimann, Ingo, Ramirez, Alfredo, Rossor, Martin, Jucker, Mathias, Chhatwal, Jasmeer, Spottke, Annika, Boecker, Henning, Brosseron, Frederic, Falkai, Peter, Fliessbach, Klaus, Heneka, Michael T, Laske, Christoph, Nestor, Peter, Peters, Oliver, Fuentes, Manuel, Menne, Felix, Priller, Josef, Spruth, Eike J, Franke, Christiana, Schneider, Anja, Kofler, Barbara, Westerteicher, Christine, Speck, Oliver, Wiltfang, Jens, Bartels, Claudia, Caballero, Miguel Ángel Araque, Metzger, Coraline, Bittner, Daniel, Weiner, Michael, Lee, Jae-Hong, Salloway, Stephen, Danek, Adrian, Goate, Alison, Schofield, Peter R, Bateman, Randall J, and Ewers, Michael

Subjects
Clinical Trials and Supportive Activities, Brain Disorders, Aging, Basic Behavioral and Social Science, Dementia, Neurosciences, Behavioral and Social Science, Acquired Cognitive Impairment, Clinical Research, Alzheimer's Disease, Neurodegenerative, Biomedical Imaging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Alzheimer Disease, Amyloid beta-Protein Precursor, Brain Mapping, Cognitive Dysfunction, Female, Frontal Lobe, Functional Laterality, Humans, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Male, Middle Aged, Mutation, Nerve Net, Presenilin-1, Presenilin-2, Alzheimer's disease, cognitive reserve, resting state connectivity, memory, dementia biomarkers, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Patients with Alzheimer's disease vary in their ability to sustain cognitive abilities in the presence of brain pathology. A major open question is which brain mechanisms may support higher reserve capacity, i.e. relatively high cognitive performance at a given level of Alzheimer's pathology. Higher functional MRI-assessed functional connectivity of a hub in the left frontal cortex is a core candidate brain mechanism underlying reserve as it is associated with education (i.e. a protective factor often associated with higher reserve) and attenuated cognitive impairment in prodromal Alzheimer's disease. However, no study has yet assessed whether such hub connectivity of the left frontal cortex supports reserve throughout the evolution of pathological brain changes in Alzheimer's disease, including the presymptomatic stage when cognitive decline is subtle. To address this research gap, we obtained cross-sectional resting state functional MRI in 74 participants with autosomal dominant Alzheimer's disease, 55 controls from the Dominantly Inherited Alzheimer's Network and 75 amyloid-positive elderly participants, as well as 41 amyloid-negative cognitively normal elderly subjects from the German Center of Neurodegenerative Diseases multicentre study on biomarkers in sporadic Alzheimer's disease. For each participant, global left frontal cortex connectivity was computed as the average resting state functional connectivity between the left frontal cortex (seed) and each voxel in the grey matter. As a marker of disease stage, we applied estimated years from symptom onset in autosomal dominantly inherited Alzheimer's disease and cerebrospinal fluid tau levels in sporadic Alzheimer's disease cases. In both autosomal dominant and sporadic Alzheimer's disease patients, higher levels of left frontal cortex connectivity were correlated with greater education. For autosomal dominant Alzheimer's disease, a significant left frontal cortex connectivity × estimated years of onset interaction was found, indicating slower decline of memory and global cognition at higher levels of connectivity. Similarly, in sporadic amyloid-positive elderly subjects, the effect of tau on cognition was attenuated at higher levels of left frontal cortex connectivity. Polynomial regression analysis showed that the trajectory of cognitive decline was shifted towards a later stage of Alzheimer's disease in patients with higher levels of left frontal cortex connectivity. Together, our findings suggest that higher resilience against the development of cognitive impairment throughout the early stages of Alzheimer's disease is at least partially attributable to higher left frontal cortex-hub connectivity.

Published
2018

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

Author

Gordon, Brian A, Blazey, Tyler M, Su, Yi, Hari-Raj, Amrita, Dincer, Aylin, Flores, Shaney, Christensen, Jon, McDade, Eric, Wang, Guoqiao, Xiong, Chengjie, Cairns, Nigel J, Hassenstab, Jason, Marcus, Daniel S, Fagan, Anne M, Jack, Clifford R, Hornbeck, Russ C, Paumier, Katrina L, Ances, Beau M, Berman, Sarah B, Brickman, Adam M, Cash, David M, Chhatwal, Jasmeer P, Correia, Stephen, Förster, Stefan, Fox, Nick C, Graff-Radford, Neill R, la Fougère, Christian, Levin, Johannes, Masters, Colin L, Rossor, Martin N, Salloway, Stephen, Saykin, Andrew J, Schofield, Peter R, Thompson, Paul M, Weiner, Michael M, Holtzman, David M, Raichle, Marcus E, Morris, John C, Bateman, Randall J, and Benzinger, Tammie LS

Subjects
Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurosciences, Acquired Cognitive Impairment, Neurodegenerative, Clinical Research, Dementia, Alzheimer's Disease, Brain Disorders, Biomedical Imaging, Aging, Rare Diseases, Aetiology, Detection, screening and diagnosis, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Neurological, Adult, Alzheimer Disease, Amyloid beta-Protein Precursor, Aniline Compounds, Brain, Brain Mapping, Family Health, Female, Fluorodeoxyglucose F18, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Positron-Emission Tomography, Presenilin-1, Presenilin-2, Statistics, Nonparametric, Thiazoles, Clinical Sciences, Neurology & Neurosurgery
Abstract

BackgroundModels of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal.MethodsBetween Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11C-Pittsburgh Compound B (11C-PiB) PET, 18F-Fluorodeoxyglucose (18F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at ClinicalTrials.gov (number NCT00869817) FINDINGS: 11C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the brain, with the precuneus being the first cortical region for each method to show divergence between groups (22·2 years before expected onset for Aβ accumulation, 18·8 years before expected onset for hypometabolism, and 13·0 years before expected onset for cortical thinning).InterpretationMutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning compared with non-carriers which preceded the expected onset of dementia. Accrual of these pathologies varied throughout the brain, suggesting differential regional and temporal vulnerabilities to Aβ, metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting as well as designing and evaluating clinical trials.FundingUS National Institutes of Health, the German Center for Neurodegenerative Diseases, and the Medical Research Council Dementias Platform UK.

Published
2018

34. 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

35. White matter hyperintensities and the mediating role of cerebral amyloid angiopathy in dominantly-inherited Alzheimer’s disease

Author

Lee, Seonjoo, Zimmerman, Molly E, Narkhede, Atul, Nasrabady, Sara E, Tosto, Giuseppe, Meier, Irene B, Benzinger, Tammie LS, Marcus, Daniel S, Fagan, Anne M, Fox, Nick C, Cairns, Nigel J, Holtzman, David M, Buckles, Virginia, Ghetti, Bernardino, McDade, Eric, Martins, Ralph N, Saykin, Andrew J, Masters, Colin L, Ringman, John M, Fӧrster, Stefan, Schofield, Peter R, Sperling, Reisa A, Johnson, Keith A, Chhatwal, Jasmeer P, Salloway, Stephen, Correia, Stephen, Jack, Clifford R, Weiner, Michael, Bateman, Randall J, Morris, John C, Mayeux, Richard, and Brickman, Adam M

Subjects
Health Services and Systems, Health Sciences, Genetics, Biological Sciences, Neurodegenerative, Vascular Cognitive Impairment/Dementia, Aging, Alzheimer's Disease, Dementia, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Neurosciences, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Alzheimer Disease, Cerebral Amyloid Angiopathy, Female, Hemorrhage, Humans, Magnetic Resonance Imaging, Male, Mutation, Organ Size, White Matter, Dominantly Inherited Alzheimer Network, General Science & Technology
Abstract

IntroductionWhite matter hyperintensity (WMH) volume on MRI is increased among presymptomatic individuals with autosomal dominant mutations for Alzheimer's disease (AD). One potential explanation is that WMH, conventionally considered a marker of cerebrovascular disease, are a reflection of cerebral amyloid angiopathy (CAA) and that increased WMH in this population is a manifestation of this vascular form of primary AD pathology. We examined whether the presence of cerebral microbleeds, a marker of CAA, mediates the relationship between WMH and estimated symptom onset in individuals with and without autosomal dominant mutations for AD.Participants and methodsParticipants (n = 175, mean age = 41.1 years) included 112 with an AD mutation and 63 first-degree non-carrier controls. We calculated the estimated years from expected symptom onset (EYO) and analyzed baseline MRI data for WMH volume and presence of cerebral microbleeds. Mixed effects regression and tests of mediation were used to examine microbleed and WMH differences between carriers and non-carriers and to test the whether the association between WMH and mutation status is dependent on the presence of microbleeds.ResultsMutation carriers were more likely to have microbleeds than non-carriers (p

Published
2018

36. 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
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37. Experimental evidence for temporal uncoupling of brain Aβ deposition and neurodegenerative sequelae

Author

Rother, Christine, Uhlmann, Ruth E., Müller, Stephan A., Schelle, Juliane, Skodras, Angelos, Obermüller, Ulrike, Häsler, Lisa M., Lambert, Marius, Baumann, Frank, Xu, Ying, Bergmann, Carina, Salvadori, Giulia, Loos, Maarten, Brzak, Irena, Shimshek, Derya, Neumann, Ulf, Walker, Lary C., Schultz, Stephanie A., Chhatwal, Jasmeer P., Kaeser, Stephan A., Lichtenthaler, Stefan F., Staufenbiel, Matthias, and Jucker, Mathias

Published
2022
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38. Amyloid and tau burden relate to longitudinal changes in the performance of complex everyday activities among cognitively unimpaired older adults: results from the performance-based Harvard Automated Phone Task

Author

Dubbelman, Mark A., primary, Diez, Ibai, additional, Gonzalez, Christopher, additional, Amariglio, Rebecca E., additional, Becker, J. Alex, additional, Chhatwal, Jasmeer P., additional, Gatchel, Jennifer R., additional, Johnson, Keith A., additional, Locascio, Joseph J., additional, Udeogu, Onyinye J., additional, Wang, Sharon, additional, Papp, Kathryn V., additional, Properzi, Michael J., additional, Rentz, Dorene M., additional, Schultz, Aaron P., additional, Sperling, Reisa A., additional, Vannini, Patrizia, additional, and Marshall, Gad A., additional

Published
2024
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39. 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
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40. Comparing amyloid-β plaque burden with antemortem PiB PET in autosomal dominant and late-onset Alzheimer disease

Author

Chen, Charles D., Joseph-Mathurin, Nelly, Sinha, Namita, Zhou, Aihong, Li, Yan, Friedrichsen, Karl, McCullough, Austin, Franklin, Erin E., Hornbeck, Russ, Gordon, Brian, Sharma, Vijay, Cruchaga, Carlos, Goate, Alison, Karch, Celeste, McDade, Eric, Xiong, Chengjie, Bateman, Randall J., Ghetti, Bernardino, Ringman, John M., Chhatwal, Jasmeer, Masters, Colin L., McLean, Catriona, Lashley, Tammaryn, Su, Yi, Koeppe, Robert, Jack, Clifford, Klunk, William E., Morris, John C., Perrin, Richard J., Cairns, Nigel J., and Benzinger, Tammie L. S.

Published
2021
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41. Comparison of CSF biomarkers in Down syndrome and autosomal dominant Alzheimer's disease: a cross-sectional study

Author

Fagan, Anne M, Henson, Rachel L, Li, Yan, Boerwinkle, Anna H, Xiong, Chengjie, Bateman, Randall J, Goate, Alison, Ances, Beau M, Doran, Eric, Christian, Bradley T, Lai, Florence, Rosas, H Diana, Schupf, Nicole, Krinsky-McHale, Sharon, Silverman, Wayne, Lee, Joseph H, Klunk, William E, Handen, Benjamin L, Allegri, Ricardo F, Chhatwal, Jasmeer P, Day, Gregory S, Graff-Radford, Neill R, Jucker, Mathias, Levin, Johannes, Martins, Ralph N, Masters, Colin L, Mori, Hiroshi, Mummery, Catherine J, Niimi, Yoshiki, Ringman, John M, Salloway, Stephen, Schofield, Peter R, Shoji, Mikio, and Lott, Ira T

Published
2021
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43. Meningeal lymphatics affect microglia responses and anti-Aβ immunotherapy

Author

Da Mesquita, Sandro, Papadopoulos, Zachary, Dykstra, Taitea, Brase, Logan, Farias, Fabiana Geraldo, Wall, Morgan, Jiang, Hong, Kodira, Chinnappa Dilip, de Lima, Kalil Alves, Herz, Jasmin, Louveau, Antoine, Goldman, Dylan H., Salvador, Andrea Francesca, Onengut-Gumuscu, Suna, Farber, Emily, Dabhi, Nisha, Kennedy, Tatiana, Milam, Mary Grace, Baker, Wendy, Smirnov, Igor, Rich, Stephen S., Benitez, Bruno A., Karch, Celeste M., Perrin, Richard J., Farlow, Martin, Chhatwal, Jasmeer P., Holtzman, David M., Cruchaga, Carlos, Harari, Oscar, and Kipnis, Jonathan

Published
2021
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44. Axonal damage and inflammation response are biological correlates of decline in small-world values: a cohort study in autosomal dominant Alzheimer's disease.

Author

Vermunt, Lisa, Sutphen, Courtney L, Dicks, Ellen, Leeuw, Diederick M de, Allegri, Ricardo F, Berman, Sarah B, Cash, David M, Chhatwal, Jasmeer P, Cruchaga, Carlos, Day, Gregory S, Ewers, Michael, Farlow, Martin R, Fox, Nick C, Ghetti, Bernardino, Graff-Radford, Neill R, Hassenstab, Jason, Jucker, Mathias, Karch, Celeste M, Kuhle, Jens, and Laske, Christoph

Published
2024
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45. Vascular contributions to cognitive decline: Beyond amyloid and tau in the Harvard Aging Brain Study.

Author

Shirzadi, Zahra, Boyle, Rory, Yau, Wai-Ying W, Coughlan, Gillian, Fu, Jessie Fanglu, Properzi, Michael J, Buckley, Rachel F, Yang, Hyun-Sik, Scanlon, Catherine E, Hsieh, Stephanie, Amariglio, Rebecca E, Papp, Kathryn, Rentz, Dorene, Price, Julie C, Johnson, Keith A, Sperling, Reisa A, Chhatwal, Jasmeer P, and Schultz, Aaron P

Abstract

In addition to amyloid and tau pathology, elevated systemic vascular risk, white matter injury, and reduced cerebral blood flow contribute to late-life cognitive decline. Given the strong collinearity among these parameters, we proposed a framework to extract the independent latent features underlying cognitive decline using the Harvard Aging Brain Study (N = 166 cognitively unimpaired older adults at baseline). We used the following measures from the baseline visit: cortical amyloid, inferior temporal cortex tau, relative cerebral blood flow, white matter hyperintensities, peak width of skeletonized mean diffusivity, and Framingham Heart Study cardiovascular disease risk. We used exploratory factor analysis to extract orthogonal factors from these variables and their interactions. These factors were used in a regression model to explain longitudinal Preclinical Alzheimer Cognitive Composite-5 (PACC) decline (follow-up = 8.5 ±2.7 years). We next examined whether gray matter volume atrophy acts as a mediator of factors and PACC decline. Latent factors of systemic vascular risk, white matter injury, and relative cerebral blood flow independently explain cognitive decline beyond amyloid and tau. Gray matter volume atrophy mediates these associations with the strongest effect on white matter injury. These results suggest that systemic vascular risk contributes to cognitive decline beyond current markers of cerebrovascular injury, amyloid, and tau. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Amyloid beta–independent sleep markers associated with early regional tau burden and cortical thinning.

Author

Stankeviciute, Laura, Chhatwal, Jasmeer P., Levin, Raina, Pinilla, Valentina, Schultz, Aaron P., Redline, Susan, Johnson, Keith A., Sperling, Reisa A., Kozhemiako, Nataliia, Purcell, Shaun, and Djonlagic, Ina

Subjects
POSITRON emission tomography, ALZHEIMER'S disease, CEREBRAL cortical thinning, OLDER people, TAU proteins
Abstract

INTRODUCTION: Sleep is crucial for memory consolidation and the clearance of toxic proteins associated with Alzheimer's disease (AD). We examined the association between sleep characteristics and imaging biomarkers of early amyloid beta (Aβ) and tau pathology as well as neurodegeneration in brain regions known to be affected in the incipient stages of AD. METHODS: Thirty‐nine cognitively unimpaired (CU) participants of the Harvard Aging Brain Study underwent at‐home polysomnography as well as tau positron emission tomography (flortaucipir‐PET), amyloid PET (Pittsburgh compound B [PiB]‐PET), and magnetic resonance imaging–derived assessment of cortical thickness (CT). RESULTS: Increased N1 sleep was associated with a higher tau PET signal (β = 0.009, p = 0.001) and lower CT in the temporal composite region of interest (β = –0.017, p = 0.007). Decreased slow‐wave sleep (SWS) was associated with higher tau burden in the temporal composite (β = –0.008, p = 0.005) and lower CT (β = 0.008, p = 0.002), even after controlling for global PiB‐PET. DISCUSSION: In CU older adults, lower SWS and higher N1 sleep were associated with higher tau burden and lower CT in brain regions associated with early tau deposition and vulnerable to AD‐related neurodegeneration through mechanisms dissociable from amyloid deposition. Highlights: We report the results of an observational study, which leveraged ‐a well‐characterized cohort of healthy aging (Harvard Aging Brain Study) by adding in‐home full polysomnograms.By adding at‐home polysomnograms to this unique and deeply phenotyped cohort, we examined variations in sleep architecture that are associated with Alzheimer's disease (AD) pathologic changes.Our results confirmed the association of sleep changes with early tau and cortical neurodegenerative changes that were independent of amyloid.The results will be of importance in monitoring sleep‐related variations in relation to the natural history of AD pathology and in designing sleep‐focused clinical trials. [ABSTRACT FROM AUTHOR]

Published
2024
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