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1. Robust, fully-automated assessment of cerebral perivascular spaces and white matter lesions: a multicentre MRI longitudinal study of their evolution and association with risk of dementia and accelerated brain atrophy

Author

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

Subjects
Health Services and Systems, Health Sciences, Aging, Clinical Trials and Supportive Activities, Clinical Research, Bioengineering, Acquired Cognitive Impairment, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Alzheimer's Disease Related Dementias (ADRD), Cerebrovascular, Vascular Cognitive Impairment/Dementia, Alzheimer's Disease, Biomedical Imaging, Brain Disorders, Prevention, Neurosciences, 4.1 Discovery and preclinical testing of markers and technologies, 4.2 Evaluation of markers and technologies, Neurological, Alzheimer’s Disease Neuroimaging Initiative, Brain, Humans, Atrophy, Magnetic Resonance Imaging, Longitudinal Studies, Reproducibility of Results, Algorithms, Aged, Aged, 80 and over, Middle Aged, Female, Male, White Matter, Glymphatic System, Alzheimer’s disease, Glymphatic system, Perivascular spaces, Small vessel disease, White matter lesions, Clinical Sciences, Public Health and Health Services, Clinical sciences, Epidemiology
Abstract

BackgroundPerivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. However, it is unknown whether PVS can predict dementia risk and brain atrophy trajectories in participants without dementia, as longitudinal studies on PVS are scarce and current methods for PVS assessment lack robustness and inter-scanner reproducibility.MethodsWe developed a robust algorithm to automatically assess PVS count and size on clinical MRI, and investigated 1) their relationship with dementia risk and brain atrophy in participants without dementia, 2) their longitudinal evolution, and 3) their potential use as a screening tool in simulated clinical trials. We analysed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1 ± 9.7 years-old, 56.6% women) from three publicly available observational studies on ageing and dementia (the Alzheimer's Disease Neuroimaging Initiative, the National Alzheimer's Coordinating Centre database, and the Open Access Series of Imaging Studies). Clinical and MRI data collected between 2004 and 2022 were analysed with consistent methods, controlling for confounding factors, and combined using mixed-effects models.FindingsOur fully-automated method for PVS assessment showed excellent inter-scanner reproducibility (intraclass correlation coefficients >0.8). Fewer PVS and larger PVS diameter at baseline predicted higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers differed significantly in participants without dementia who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants at low risk of dementia based on our PVS markers enhanced the power of the trial independently of Alzheimer's disease biomarkers.InterpretationThese robust cerebrovascular markers predict dementia risk and brain atrophy and may improve risk-stratification of patients, potentially reducing cost and increasing throughput of clinical trials to combat dementia.FundingUS National Institutes of Health.

Published
2025

3. Feasibility of Remote Unsupervised Cognitive Screening With SATURN in Older Adults.

Author

Tagliabue, Chiara, Kaye, Jeffrey, Mazza, Veronica, Assecondi, Sara, and Bissig, David

Subjects
Cognitive screening, computer-based test, e-health, self-administered cognitive test, telecare, Humans, Aged, Feasibility Studies, Saturn, Extraterrestrial Environment, Cognition
Abstract

Widespread cognitive test screening as part of tele-public health initiatives necessitates a test that is self-administered online and automatically scored, with no clinician effort. The feasibility of unsupervised cognitive screening is unclear. We adapted the Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN) to make it suitable for self-administration and automatic scoring. A sample of 364 healthy older adults completed SATURN via a web browser, in a fully independent manner. SATURNs overall score was not modulated by gender, education, reading speed, the time of day at which the test was taken, or an individuals familiarity with technology. SATURN proved extremely portable across operating systems. Importantly, comments from participants reported satisfaction with the experience and the clarity of the instructions. SATURN represents a fast and easy screening tool that can be used for a first assessment, during a routine test or clinical evaluation, or during periodic health monitoring, in person or remotely.

Published
2023

4. LATE-NC risk alleles (in TMEM106B, GRN, and ABCC9 genes) among persons with African ancestry.

Author

Katsumata, Yuriko, Fardo, David W, Shade, Lincoln MP, Bowen, James D, Crane, Paul K, Jarvik, Gail P, Keene, C Dirk, Larson, Eric B, McCormick, Wayne C, McCurry, Susan M, Mukherjee, Shubhabrata, Kowall, Neil W, McKee, Ann C, Honig, Robert A, Lawrence, S, Vonsattel, Jean Paul, Williamson, Jennifer, Small, Scott, Burke, James R, Hulette, Christine M, Welsh-Bohmer, Kathleen A, Gearing, Marla, Lah, James J, Levey, Allan I, Wingo, Thomas S, Apostolova, Liana G, Farlow, Martin R, Ghetti, Bernardino, Saykin, Andrew J, Spina, Salvatore, Albert, Marilyn S, Lyketsos, Constantine G, Troncoso, Juan C, Frosch, Matthew P, Green, Robert C, Growdon, John H, Hyman, Bradley T, Tanzi, Rudolph E, Potter, Huntington, Dickson, Dennis W, Ertekin-Taner, Nilufer, Graff-Radford, Neill R, Parisi, Joseph E, Petersen, Ronald C, Duara, Ranjan, Buxbaum, Joseph D, Goate, Alison M, Sano, Mary, Masurkar, Arjun V, Wisniewski, Thomas, Bigio, Eileen H, Mesulam, Marsel, Weintraub, Sandra, Vassar, Robert, Kaye, Jeffrey A, Quinn, Joseph F, Woltjer, Randall L, Barnes, Lisa L, Bennett, David A, Schneider, Julie A, Yu, Lei, Henderson, Victor, Fallon, Kenneth B, Harrell, Lindy E, Marson, Daniel C, Roberson, Erik D, DeCarli, Charles, Jin, Lee-Way, Olichney, John M, Kim, Ronald, LaFerla, Frank M, Monuki, Edwin, Head, Elizabeth, Sultzer, David, Geschwind, Daniel H, Vinters, Harry V, Chesselet, Marie-Francoise, Galasko, Douglas R, Brewer, James B, Boxer, Adam, Karydas, Anna, Kramer, Joel H, Miller, Bruce L, Rosen, Howard J, Seeley, William W, Burns, Jeffrey M, Swerdlow, Russell H, Abner, Erin, Van Eldik, Linda J, Albin, Roger L, Lieberman, Andrew P, Paulson, Henry L, Arnold, Steven E, Trojanowski, John Q, Van Deerlin, Vivianna M, Hamilton, Ronald L, Kamboh, M Ilyas, Lopez, Oscar L, and Becker, James T

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Aging, Prevention, Neurodegenerative, Acquired Cognitive Impairment, Alzheimer's Disease, Dementia, Minority Health, Health Disparities, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Genetics, 2.1 Biological and endogenous factors, Humans, Alleles, Polymorphism, Single Nucleotide, Alzheimer Disease, TDP-43 Proteinopathies, Progranulins, Membrane Proteins, Nerve Tissue Proteins, Sulfonylurea Receptors, Alzheimer’s Disease Genetics Consortium, KCNMB2, Diversity, Epidemiology, FTLD, Genome-Wide Association Studies, KATP, Neurology & Neurosurgery, Clinical sciences
Abstract

Limbic-predominant age-related TDP-43 encephalopathy (LATE) affects approximately one-third of older individuals and is associated with cognitive impairment. However, there is a highly incomplete understanding of the genetic determinants of LATE neuropathologic changes (LATE-NC) in diverse populations. The defining neuropathologic feature of LATE-NC is TDP-43 proteinopathy, often with comorbid hippocampal sclerosis (HS). In terms of genetic risk factors, LATE-NC and/or HS are associated with single nucleotide variants (SNVs) in 3 genes-TMEM106B (rs1990622), GRN (rs5848), and ABCC9 (rs1914361 and rs701478). We evaluated these 3 genes in convenience samples of individuals of African ancestry. The allele frequencies of the LATE-associated alleles were significantly different between persons of primarily African (versus European) ancestry: In persons of African ancestry, the risk-associated alleles for TMEM106B and ABCC9 were less frequent, whereas the risk allele in GRN was more frequent. We performed an exploratory analysis of data from African-American subjects processed by the Alzheimer's Disease Genomics Consortium, with a subset of African-American participants (n = 166) having corroborating neuropathologic data through the National Alzheimer's Coordinating Center (NACC). In this limited-size sample, the ABCC9/rs1914361 SNV was associated with HS pathology. More work is required concerning the genetic factors influencing non-Alzheimer disease pathology such as LATE-NC in diverse cohorts.

Published
2023

5. Robust, fully-automated assessment of cerebral perivascular spaces and white matter lesions: a multicentre MRI longitudinal study of their evolution and association with risk of dementia and accelerated brain atrophy

Author

Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R., Jagust, William, Trojanowki, John Q., Toga, Arthur W., Beckett, Laurel, Green, Robert C., Saykin, Andrew J., Morris, John, Shaw, Leslie M., Liu, Enchi, Montine, Tom, Thomas, Ronald G., Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Jiminez, Gus, Harvey, Danielle, Bernstein, Matthew, Fox, Nick, Thompson, Paul, Schuff, Norbert, DeCarli, Charles, Borowski, Bret, Gunter, Jeff, Senjem, Matt, Vemuri, Prashanthi, Jones, David, Kantarci, Kejal, Ward, Chad, Koeppe, Robert A., Foster, Norm, Reiman, Eric M., Chen, Kewei, Mathis, Chet, Landau, Susan, Cairns, Nigel J., Householder, Erin, Reinwald, Lisa Taylor, Lee, Virginia, Korecka, Magdalena, Figurski, Michal, Crawford, Karen, Neu, Scott, Foroud, Tatiana M., Potkin, Steven, Shen, Li, Kelley, Faber, Kim, Sungeun, Nho, Kwangsik, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J., Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lind, Betty, Carter, Raina, Dolen, Sara, Schneider, Lon S., Pawluczyk, Sonia, Beccera, Mauricio, Teodoro, Liberty, Spann, Bryan M., Brewer, James, Vanderswag, Helen, Fleisher, Adam, Heidebrink, Judith L., Lord, Joanne L., Mason, Sara S., Albers, Colleen S., Knopman, David, Johnson, Kris, Doody, Rachelle S., Meyer, Javier Villanueva, Chowdhury, Munir, Rountree, Susan, Dang, Mimi, Stern, Yaakov, Honig, Lawrence S., Bell, Karen L., Ances, Beau, Morris, John C., Carroll, Maria, Leon, Sue, Mintun, Mark A., Schneider, Stacy, Oliver, Angela, Marson, Daniel, Griffith, Randall, Clark, David, Geld-macher, David, Brockington, John, Roberson, Erik, Grossman, Hillel, Mitsis, Effie, Leyla deToledo-Morrell, Shah, Raj C., Duara, Ranjan, Varon, Daniel, Greig, Maria T., Roberts, Peggy, Albert, Marilyn, Onyike, Chiadi, D’Agostino, Daniel, Kielb, Stephanie, Galvin, James E., Pogorelec, Dana M., Cerbone, Brittany, Michel, Christina A., Rusinek, Henry, de Leon, Mony J., Glodzik, Lidia, De Santi, Susan, Doraiswamy, P. Murali, Petrella, Jeffrey R., Wong, Terence Z., Arnold, Steven E., Karlawish, Jason H., Wolk, David, Smith, Charles D., Jicha, Greg, Hardy, Peter, Sinha, Partha, Oates, Elizabeth, Conrad, Gary, Lopez, Oscar L., Oakley, MaryAnn, Simpson, Donna M., Porsteinsson, Anton P., Goldstein, Bonnie S., Martin, Kim, Makino, Kelly M., Ismail, M. Saleem, Brand, Connie, Mulnard, Ruth A., Thai, Gaby, Adams Ortiz, Catherine Mc, Womack, Kyle, Mathews, Dana, Quiceno, Mary, Arrastia, Ramon Diaz, King, Richard, Weiner, Myron, Cook, Kristen Martin, DeVous, Michael, Levey, Allan I., Lah, James J., Cellar, Janet S., Burns, Jeffrey M., Anderson, Heather S., Swerdlow, Russell H., Apostolova, Liana, Tingus, Kathleen, Woo, Ellen, Silverman, Daniel H.S., Lu, Po H., Bartzokis, George, Graff Radford, Neill R., Parfitt, Francine, Kendall, Tracy, Johnson, Heather, Farlow, Martin R., Hake, AnnMarie, Matthews, Brandy R., Herring, Scott, Hunt, Cynthia, van Dyck, Christopher H., Carson, Richard E., MacAvoy, Martha G., Chertkow, Howard, Bergman, Howard, Hosein, Chris, Black, Sandra, Stefanovic, Bojana, Caldwell, Curtis, Robin Hsiung, Ging-Yuek, Feldman, Howard, Mudge, Benita, Assaly, Michele, Kertesz, Andrew, Rogers, John, Trost, Dick, Bernick, Charles, Munic, Donna, Kerwin, Diana, Mesulam, Marek Marsel, Lipowski, Kristine, Wu, Chuang Kuo, Johnson, Nancy, Sadowsky, Carl, Martinez, Walter, Villena, Teresa, Turner, Raymond Scott, Johnson, Kathleen, Reynolds, Brigid, Sperling, Reisa A., Johnson, Keith A., Marshall, Gad, Frey, Meghan, Yesavage, Jerome, Taylor, Joy L., Lane, Barton, Rosen, Allyson, Tinklenberg, Jared, Sabbagh, Marwan N., Belden, Christine M., Jacobson, Sandra A., Sirrel, Sherye A., Kowall, Neil, Killiany, Ronald, Budson, Andrew E., Norbash, Alexander, Johnson, Patricia Lynn, Obisesan, Thomas O., Wolday, Saba, Allard, Joanne, Lerner, Alan, Ogrocki, Paula, Hudson, Leon, Fletcher, Evan, Carmichael, Owen, Olichney, John, Kittur, Smita, Borrie, Michael, Lee, T.Y., Bartha, Rob, Johnson, Sterling, Asthana, Sanjay, Carlsson, Cynthia M., Potkin, Steven G., Preda, Adrian, Nguyen, Dana, Tariot, Pierre, Reeder, Stephanie, Bates, Vernice, Capote, Horacio, Rainka, Michelle, Scharre, Douglas W., Kataki, Maria, Adeli, Anahita, Zimmerman, Earl A., Celmins, Dzintra, Brown, Alice D., Pearlson, Godfrey D., Blank, Karen, Anderson, Karen, Santulli, Robert B., Kitzmiller, Tamar J., Schwartz, Eben S., Sink, Kaycee M., Williamson, Jeff D., Garg, Pradeep, Watkins, Franklin, Ott, Brian R., Querfurth, Henry, Tremont, Geoffrey, Salloway, Stephen, Malloy, Paul, Correia, Stephen, Rosen, Howard J., Miller, Bruce L., Mintzer, Jacobo, Spicer, Kenneth, Bachman, David, Finger, Elizabeth, Pasternak, Stephen, Rachinsky, Irina, Drost, Dick, Pomara, Nunzio, Hernando, Raymundo, Sarrael, Antero, Schultz, Susan K., Boles Ponto, Laura L., Shim, Hyungsub, Smith, Karen Elizabeth, Relkin, Norman, Chaing, Gloria, Raudin, Lisa, Smith, Amanda, Fargher, Kristin, Raj, Balebail Ashok, Barisano, Giuseppe, Iv, Michael, Choupan, Jeiran, and Hayden-Gephart, Melanie

Published
2025
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6. A data‐driven examination of apathy and depressive symptoms in dementia with independent replication

Author

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

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

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

Published
2023

7. α-Synuclein Seed Amplification in CSF and Brain from Patients with Different Brain Distributions of Pathological α-Synuclein in the Context of Co-Pathology and Non-LBD Diagnoses.

Author

Arnold, Moriah, Brumbach, Barbara, Smirnov, Denis, Concha-Marambio, Luis, Farris, Carly, Ma, Yihua, Kim, Yongya, Wilson, Edward, Kaye, Jeffrey, Hiniker, Annie, Woltjer, Randy, Galasko, Doug, Quinn, Joseph, and Coughlin, David

Subjects
Brain, Humans, Sensitivity and Specificity, alpha-Synuclein
Abstract

OBJECTIVE: The purpose of this study was to determine the sensitivity and specificity of α-synuclein seed amplification assay (αSyn-SAA) in antemortem and postmortem cerebrospinal fluid (CSF) of autopsy-confirmed patients with different distributions of pathological αSyn, co-pathologies, and clinical diagnoses. METHODS: The αSyn-SAA was used to test antemortem CSF samples from 119 subjects with a variety of clinical syndromes and standardized neuropathological examinations from Oregon Health and Science University (OHSU) and University of California San Diego (UCSD; 56 additional postmortem CSF samples available). The αSyn-SAA was also applied to frontal cortex and amygdala homogenates. Sensitivity and specificity were compared across distributions of αSyn pathology. Clinical data and co-pathologies were compared across αSyn-SAA positive and negative groups. RESULTS: Fifty-three individuals without and 66 with αSyn-pathology (neocortical [n = 38], limbic [n = 7], and amygdala-predominant [n = 21]) were included. There was a sensitivity of 97.8% and specificity of 98.1% of the αSyn-SAA to identify patients with limbic/neocortical pathology from antemortem CSF. Sensitivity to detect amygdala-predominant pathology was only 14.3%. Postmortem CSF and brain tissue αSyn-SAA analyses also showed higher assay positivity in samples from limbic/neocortical cases. INTERPRETATION: CSF αSyn-SAA reliably identifies αSyn seeds in patients with diffuse αSyn pathology in the context of co-pathology and non-Lewy body disease (LBD) diagnoses. The analysis of brain homogenates suggests that pathological αSyn in the amygdala might differ from pathological αSyn in the frontal cortex. The αSyn-SAA might facilitate the differential diagnosis of dementias with mixed pathologies. ANN NEUROL 2022;92:650-662.

Published
2022

8. Impact of potential modifications to Alzheimer’s disease clinical trials in response to disruption by COVID-19: a simulation study

Author

Schneider, Lon S, Qiu, Yuqi, Thomas, Ronald G, Evans, Carol, Jacobs, Diane M, Jin, Shelia, Kaye, Jeffrey A, LaCroix, Andrea Z, Messer, Karen, Salmon, David P, Sano, Mary, Schafer, Kimberly, and Feldman, Howard H

Subjects
Biomedical and Clinical Sciences, Health Sciences, Brain Disorders, Acquired Cognitive Impairment, Clinical Trials and Supportive Activities, Alzheimer's Disease, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Dementia, Aging, Alzheimer Disease, COVID-19, Computer Simulation, Humans, Pandemics, SARS-CoV-2, Alzheimer, Clinical trials, Simulations, Mild cognitive impairment, Disease modification, Symptomatic treatment, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundThe COVID-19 pandemic disrupted Alzheimer disease randomized clinical trials (RCTs), forcing investigators to make changes in the conduct of such trials while endeavoring to maintain their validity. Changing ongoing RCTs carries risks for biases and threats to validity. To understand the impact of exigent modifications due to COVID-19, we examined several scenarios in symptomatic and disease modification trials that could be made.MethodsWe identified both symptomatic and disease modification Alzheimer disease RCTs as exemplars of those that would be affected by the pandemic and considered the types of changes that sponsors could make to each. We modeled three scenarios for each of the types of trials using existing datasets, adjusting enrollment, follow-ups, and dropouts to examine the potential effects COVID-19-related changes. Simulations were performed that accounted for completion and dropout patterns using linear mixed effects models, modeling time as continuous and categorical. The statistical power of the scenarios was determined.ResultsTruncating both symptomatic and disease modification trials led to underpowered trials. By contrast, adapting the trials by extending the treatment period, temporarily stopping treatment, delaying outcomes assessments, and performing remote assessment allowed for increased statistical power nearly to the level originally planned.DiscussionThese analyses support the idea that disrupted trials under common scenarios are better continued and extended even in the face of dropouts, treatment disruptions, missing outcomes, and other exigencies and that adaptations can be made that maintain the trials' validity. We suggest some adaptive methods to do this noting that some changes become under-powered to detect the original effect sizes and expected outcomes. These analyses provide insight to better plan trials that are resilient to unexpected changes to the medical, social, and political milieu.

Published
2021

9. Unstructured Primary Outcome in Randomized Controlled Trials

Author

Taylor-Rodriguez, Daniel, Lovitz, David, Mattek, Nora, Wu, Chao-Yi, Dodge, Hiroko, Kaye, Jeffrey, and Jedynak, Bruno M.

Subjects
Statistics - Methodology
Abstract

The primary outcome of Randomized clinical Trials (RCTs) are typically dichotomous, continuous, multivariate continuous, or time-to-event. However, what if this outcome is unstructured, e.g., a list of variables of mixed types, longitudinal sequences, images, audio recordings, etc. When the outcome is unstructured it is unclear how to assess RCT success and how to compute sample size. We show that kernel methods offer natural extensions to traditional biostatistics methods. We demonstrate our approach with the measurements of computer usage in a cohort of aging participants, some of which will become cognitively impaired. Simulations as well as a real data experiment show the superiority of the proposed approach compared to the standard in this situation: generalized mixed effect models.

Published
2020

10. Brain Health Living Labs

Author

Richardson, Shannon, Sinha, Anika, Vahia, Ipsit, Dawson, Walter, Kaye, Jeffrey, Reynolds, Charles F, Smith, Erin, Cummings, Jeffrey, Berk, Michael, Lavretsky, Helen, and Eyre, Harris A

Subjects
Health Services and Systems, Health Sciences, Neurological, Generic health relevance, Good Health and Well Being, Aged, Brain, Ecosystem, Health Personnel, Humans, Innovation, technology, entrepreneur, brain health, late-life, mental health, living lab, psychiatry, Clinical Sciences, Public Health and Health Services, Cognitive Sciences, Geriatrics, Clinical sciences, Health services and systems, Clinical and health psychology
Abstract

We call on geriatric brain health care providers, executives and entrepreneurs to embrace our Brain Health Living Lab model-a user-centered, iterative ecosystem, integrating concurrent clinical care, research and innovation processes.

Published
2021

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

Author

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

Published
2023
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12. Using Digital Tools to Advance Alzheimer’s Drug Trials During a Pandemic: The EU/US CTAD Task Force

Author

Kaye, Jeffrey, Aisen, P, Amariglio, R, Au, R, Ballard, C, Carrillo, M, Fillit, H, Iwatsubo, T, Jimenez-Maggiora, G, Lovestone, S, Natanegara, F, Papp, K, Soto, ME, Weiner, M, and Vellas, B

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Brain Disorders, Clinical Research, Neurosciences, Aging, Neurodegenerative, Clinical Trials and Supportive Activities, Alzheimer's Disease, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Neurological, Good Health and Well Being, Advisory Committees, Alzheimer Disease, Biomedical Research, COVID-19, Clinical Trials as Topic, Digital Technology, European Union, Humans, United States, Alzheimer’s disease, clinical outcomes, digital tools, remote assessments, Biological psychology, Cognitive and computational psychology
Abstract

The 2020 COVID-19 pandemic has disrupted Alzheimer's disease (AD) clinical studies worldwide. Digital technologies may help minimize disruptions by enabling remote assessment of subtle cognitive and functional changes over the course of the disease. The EU/US Clinical Trials in Alzheimer's Disease (CTAD) Task Force met virtually in November 2020 to explore the opportunities and challenges associated with the use of digital technologies in AD clinical research. While recognizing the potential of digital tools to accelerate clinical trials, improve the engagement of diverse populations, capture clinically meaningful data, and lower costs, questions remain regarding the stability, validity, generalizability, and reproducibility of digital data. Substantial concerns also exist regarding regulatory acceptance and privacy. Nonetheless, the Task Force supported further exploration of digital technologies through collaboration and data sharing, noting the need for standardization of digital readouts. They also concluded that while it may be premature to employ remote assessments for trials of novel experimental medications, remote studies of non-invasive, multi-domain approaches may be feasible at this time.

Published
2021

14. Brain health INnovation Diplomacy: a model binding diverse disciplines to manage the promise and perils of technological innovation

Author

Ternes, Kylie, Iyengar, Vijeth, Lavretsky, Helen, Dawson, Walter D, Booi, Laura, Ibanez, Agustin, Vahia, Ipsit, Reynolds, Charles, DeKosky, Steven, Cummings, Jeffrey, Miller, Bruce, Perissinotto, Carla, Kaye, Jeffrey, and Eyre, Harris A

Subjects
Psychology, Applied and Developmental Psychology, Brain Disorders, Behavioral and Social Science, Neurosciences, Prevention, Neurological, Good Health and Well Being, Alzheimer Disease, Dementia, Global Health, Humans, Inventions, Technology, Brain health, dementia, Alzheimer's, technology, depression, innovation, diplomacy, entrepreneurship, Alzheimer’s, Medical and Health Sciences, Psychology and Cognitive Sciences, Geriatrics, Applied and developmental psychology
Abstract

BackgroundBrain health diplomacy aims to influence the global policy environment for brain health (i.e. dementia, depression, and other mind/brain disorders) and bridges the disciplines of global brain health, international affairs, management, law, and economics. Determinants of brain health include educational attainment, diet, access to health care, physical activity, social support, and environmental exposures, as well as chronic brain disorders and treatment. Global challenges associated with these determinants include large-scale conflicts and consequent mass migration, chemical contaminants, air quality, socioeconomic status, climate change, and global population aging. Given the rapidly advancing technological innovations impacting brain health, it is paramount to optimize the benefits and mitigate the drawbacks of such technologies.ObjectiveWe propose a working model of Brain health INnovation Diplomacy (BIND).MethodsWe prepared a selective review using literature searches of studies pertaining to brain health technological innovation and diplomacy.ResultsBIND aims to improve global brain health outcomes by leveraging technological innovation, entrepreneurship, and innovation diplomacy. It acknowledges the key role that technology, entrepreneurship, and digitization play and will increasingly play in the future of brain health for individuals and societies alike. It strengthens the positive role of novel solutions, recognizes and works to manage both real and potential risks of digital platforms. It is recognition of the political, ethical, cultural, and economic influences that brain health technological innovation and entrepreneurship can have.ConclusionsBy creating a framework for BIND, we can use this to ensure a systematic model for the use of technology to optimize brain health.

Published
2020

15. Validation of SATURN, a free, electronic, self‐administered cognitive screening test

Author

Bissig, David, Kaye, Jeffrey, and Erten‐Lyons, Deniz

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Brain Disorders, Clinical Research, Behavioral and Social Science, Dementia, Prevention, Acquired Cognitive Impairment, Aging, Neurological, Alzheimer's disease, cognitive screening, computer-based test, dementia screening, psychomet-rics, self-administered cognitive test, computer‐based test, psychometrics, self‐administered cognitive test, Clinical sciences, Biological psychology
Abstract

BackgroundCognitive screening is limited by clinician time and variability in administration and scoring. We therefore developed Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN), a free, public-domain, self-administered, and automatically scored cognitive screening test, and validated it on inexpensive (

Published
2020

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

Author

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

Subjects
Biological Psychology, Psychology, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Alzheimer's Disease, Dementia, Women's Health, Brain Disorders, Clinical Research, Neurosciences, Acquired Cognitive Impairment, 2.1 Biological and endogenous factors, tau, verbal memory, sex differences, Alzheimer's disease, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s disease, Clinical sciences, Biological psychology
Abstract

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

Published
2020

17. Categorizing Sleep in Older Adults with Wireless Activity Monitors Using LSTM Neural Networks

Author

Yildiz, Selda, Opel, Ryan A, Elliott, Jonathan E, Kaye, Jeffrey, Cao, Hung, and Lim, Miranda M

Subjects
Information and Computing Sciences, Biomedical and Clinical Sciences, Clinical Sciences, Basic Behavioral and Social Science, Sleep Research, Clinical Research, Neurosciences, Lung, Behavioral and Social Science, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Good Health and Well Being, Adult, Aged, Female, Humans, Machine Learning, Male, Middle Aged, Neural Networks, Computer, Polysomnography, Sleep, Wakefulness, Wearable Electronic Devices, Wireless Technology, Wearable device, actigraphy, sleep monitoring, long-short-term memory, neural network
Abstract

Novel approaches are needed to accurately classify and monitor sleep patterns in older adults, particularly those with cognitive impairment and non-normative sleep. Traditional methods ignore underlying sleep architecture in these patient populations, and other modern approaches tend to focus on healthy, normative patient populations. In this paper, we developed a model using a long-short-term memory neural network (LSTM) and trained it on a sample of older, non-normative patients. The 22 nights of data collected were trained on gold-standard polysomnography (PSG) as ground truth and were compared against the clinical standard threshold-based method for sleep detection. The LSTM more than doubled the traditional method's ability to detect clinically-relevant wakefulness during sleep (37.7% vs. 15%) without significantly sacrificing accuracy (67.7% vs. 75%) or precision (90.7% vs. 94%) of sleep classification.

Published
2019

18. A randomized clinical trial to evaluate home‐based assessment of people over 75 years old

Author

Sano, Mary, Zhu, Carolyn W, Kaye, Jeffrey, Mundt, James C, Hayes, Tamara L, Ferris, Steven, Thomas, Ronald G, Sun, Chung‐Kai, Jiang, Yanxin, Donohue, Michael C, Schneider, Lon S, Egelko, Susan, Aisen, Paul S, Feldman, Howard H, and Investigators, for the Alzheimer Disease Cooperative Study

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Clinical Research, Behavioral and Social Science, Clinical Trials and Supportive Activities, Prevention, Aged, Aged, 80 and over, Dementia, Feasibility Studies, Female, Geriatric Assessment, Healthy Volunteers, Home Care Services, Humans, Male, Neuropsychological Tests, Surveys and Questionnaires, Telephone, Dementia prevention, Home-based assessment, Alzheimer's disease, Randomized clinical trial, Alzheimer Disease Cooperative Study Investigators, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionThere is an unmet need for effective methods for conducting dementia prevention trials.MethodsHome-based assessment study compared feasibility and efficiency, ability to capture change over time using in-home instruments, and ability to predict cognitive conversion using predefined triggers in a randomized clinical trial in (1) mail-in questionnaire/live telephone interviews, (2) automated telephone/interactive voice recognition, and (3) internet-based computer Kiosk technologies. Primary endpoint was defined as cognitive conversion.ResultsAnalysis followed a modified intent-to-treat principle. Dropout rates were low and similar across technologies but participants in Kiosk were more likely to dropout earlier. Staff resources needed were higher in Kiosk. In-home instruments distinguished conversion and stable groups. Cognitively stable group showed improvement in cognitive measures. Triggering was associated with higher likelihood of conversion but statistically significant only in mail-in questionnaire/live telephone interviews.DiscussionRelatively low efficiency of internet-based assessment compared with testing by live-assessors has implications for internet-based recruitment and assessment efforts currently proposed for diverse populations.

Published
2019

23. Advancing Research on Care Needs and Supportive Approaches for Persons With Dementia: Recommendations and Rationale

Author

Kolanowski, Ann, Fortinsky, Richard H, Calkins, Margaret, Devanand, Davangere P, Gould, Elizabeth, Heller, Tamar, Hodgson, Nancy A, Kales, Helen C, Kaye, Jeffrey, Lyketsos, Constantine, Resnick, Barbara, Schicker, Melanie, and Zimmerman, Sheryl

Subjects
Health Services and Systems, Nursing, Health Sciences, Dementia, Behavioral and Social Science, Rehabilitation, Prevention, Clinical Research, Acquired Cognitive Impairment, Aging, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease, Mental Health, Neurodegenerative, Health and social care services research, 8.1 Organisation and delivery of services, Neurological, Good Health and Well Being, Aged, Biomedical Research, Congresses as Topic, Health Services Needs and Demand, Homes for the Aged, Humans, Long-Term Care, Nursing Homes, Psychosocial Support Systems, United States, National Dementia Care Summit, research recommendations, dementia, Clinical Sciences, Public Health and Health Services, Geriatrics, Health services and systems, Public health
Abstract

The first National Research Summit on Care, Services, and Supports for Persons with Dementia and Their Caregivers was held on October 16-17, 2017, at the National Institutes of Health. In this paper, participants from the Summit Session on Research on Care Needs and Supportive Approaches for Persons with Dementia summarize the state of the science, identify gaps in knowledge, and offer recommendations to improve science and practice in long-term care. Recommendations cover 4 areas focused on persons living with dementia: (1) symptoms (behavioral and psychological symptoms of dementia, function, cognition, and sleep); (2) dementia care settings (physical and social environments, home, and residential care); (3) living with dementia (living well with dementia, living alone with dementia, and living with dementia and intellectual and developmental disabilities); and (4) technology as a cross-cutting theme. The participants identify 10 of the most pressing research issues based on the findings from their collective papers. Final Summit recommendations included those presented by session participants and will be used to advise federal agencies and other organizations that fund research.

Published
2018

24. Participant satisfaction with dementia prevention research: Results from Home‐Based Assessment trial

Author

Sano, Mary, Egelko, Susan, Zhu, Carolyn W, Li, Clara, Donohue, Michael C, Ferris, Steven, Kaye, Jeffrey, Mundt, James C, Sun, Chung‐Kai, Aisen, Paul S, and Feldman, Howard H

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Neurodegenerative, Clinical Research, Acquired Cognitive Impairment, Behavioral and Social Science, Dementia, Clinical Trials and Supportive Activities, Prevention, Brain Disorders, Aging, 3.1 Primary prevention interventions to modify behaviours or promote wellbeing, Good Health and Well Being, Aged, 80 and over, Altruism, Biomedical Research, Cohort Studies, Community Participation, Female, Humans, Male, Motivation, Neuropsychological Tests, Dementia prevention, Research satisfaction, Home-based assessment, Clinical Trial, Technology, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionLittle is known about factors affecting motivation and satisfaction of participants in dementia prevention trials.MethodsA Research Satisfaction Survey was administered to 422 nondemented older adults who participated in the Home-Based Assessment trial.ResultsOverall satisfaction was high, with means of all individual items near to above a value of 3 on a scale from 1 (worst) to 4 (best). Greater satisfaction was associated with staff-administered interviews versus automated technologies. The most liked aspects of research participation were volunteerism, opportunity to challenge and improve mental function, and positive interactions with staff. The least liked aspect was repetitiveness of the assessments. Participants requested more contact with staff and other older adults and more feedback on performance.DiscussionOlder adults' participation in research was primarily motivated by altruism. Methodologies that facilitate human contact, encourage feedback and novelty of tasks should be incorporated into future trial design.

Published
2018

25. Analysis of shared heritability in common disorders of the brain

Author

Consortium, The Brainstorm, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Schott, Jonathan M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, and Cuenca-Leon, Ester

Subjects
Biological Sciences, Genetics, Biological Psychology, Health Sciences, Psychology, Neurosciences, Clinical Research, Mental Health, Human Genome, Brain Disorders, Mental Illness, 2.1 Biological and endogenous factors, Neurological, Mental health, Brain Diseases, Genetic Variation, Genome-Wide Association Study, Humans, Mental Disorders, Phenotype, Quantitative Trait, Heritable, Risk Factors, Brainstorm Consortium, General Science & Technology
Abstract

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Published
2018

26. Analysis of shared heritability in common disorders of the brain.

Author

Brainstorm Consortium, Anttila, Verneri, Bulik-Sullivan, Brendan, Finucane, Hilary K, Walters, Raymond K, Bras, Jose, Duncan, Laramie, Escott-Price, Valentina, Falcone, Guido J, Gormley, Padhraig, Malik, Rainer, Patsopoulos, Nikolaos A, Ripke, Stephan, Wei, Zhi, Yu, Dongmei, Lee, Phil H, Turley, Patrick, Grenier-Boley, Benjamin, Chouraki, Vincent, Kamatani, Yoichiro, Berr, Claudine, Letenneur, Luc, Hannequin, Didier, Amouyel, Philippe, Boland, Anne, Deleuze, Jean-François, Duron, Emmanuelle, Vardarajan, Badri N, Reitz, Christiane, Goate, Alison M, Huentelman, Matthew J, Kamboh, M Ilyas, Larson, Eric B, Rogaeva, Ekaterina, St George-Hyslop, Peter, Hakonarson, Hakon, Kukull, Walter A, Farrer, Lindsay A, Barnes, Lisa L, Beach, Thomas G, Demirci, F Yesim, Head, Elizabeth, Hulette, Christine M, Jicha, Gregory A, Kauwe, John SK, Kaye, Jeffrey A, Leverenz, James B, Levey, Allan I, Lieberman, Andrew P, Pankratz, Vernon S, Poon, Wayne W, Quinn, Joseph F, Saykin, Andrew J, Schneider, Lon S, Smith, Amanda G, Sonnen, Joshua A, Stern, Robert A, Van Deerlin, Vivianna M, Van Eldik, Linda J, Harold, Denise, Russo, Giancarlo, Rubinsztein, David C, Bayer, Anthony, Tsolaki, Magda, Proitsi, Petra, Fox, Nick C, Hampel, Harald, Owen, Michael J, Mead, Simon, Passmore, Peter, Morgan, Kevin, Nöthen, Markus M, Rossor, Martin, Lupton, Michelle K, Hoffmann, Per, Kornhuber, Johannes, Lawlor, Brian, McQuillin, Andrew, Al-Chalabi, Ammar, Bis, Joshua C, Ruiz, Agustin, Boada, Mercè, Seshadri, Sudha, Beiser, Alexa, Rice, Kenneth, van der Lee, Sven J, De Jager, Philip L, Geschwind, Daniel H, Riemenschneider, Matthias, Riedel-Heller, Steffi, Rotter, Jerome I, Ransmayr, Gerhard, Hyman, Bradley T, Cruchaga, Carlos, Alegret, Montserrat, Winsvold, Bendik, Palta, Priit, Farh, Kai-How, Cuenca-Leon, Ester, and Furlotte, Nicholas

Subjects
Brainstorm Consortium, Humans, Brain Diseases, Risk Factors, Mental Disorders, Quantitative Trait, Heritable, Phenotype, Genetic Variation, Genome-Wide Association Study, Clinical Research, Neurosciences, Rare Diseases, Human Genome, Brain Disorders, Genetics, Mental Health, 2.1 Biological and endogenous factors, Mental health, Neurological, General Science & Technology
Abstract

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Published
2018

29. Detecting cognitive changes in preclinical Alzheimer's disease: A review of its feasibility

Author

Mortamais, Marion, Ash, Jessica A, Harrison, John, Kaye, Jeffrey, Kramer, Joel, Randolph, Christopher, Pose, Carine, Albala, Bruce, Ropacki, Michael, Ritchie, Craig W, and Ritchie, Karen

Subjects
Biological Psychology, Cognitive and Computational Psychology, Psychology, Neurosciences, Dementia, Aging, Neurodegenerative, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease, Acquired Cognitive Impairment, Basic Behavioral and Social Science, Behavioral and Social Science, Clinical Research, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, Alzheimer Disease, Cognition, Humans, Neuropsychological Tests, Prodromal Symptoms, Neuropsychology, Alzheimer's disease, Diagnosis, Preclinical markers, Clinical Sciences, Geriatrics, Clinical sciences, Biological psychology
Abstract

Significant progress has been made in characterizing the biological changes occurring in preclinical Alzheimer's disease (AD). Cognitive dysfunction has been viewed, however, as a late-stage phenomenon, despite increasing evidence that changes may be detected in the decades preceding dementia. In the absence of comprehensive evidence-based guidelines for preclinical cognitive assessment, longitudinal cohort and neuroimaging studies have been reviewed to determine the temporal order and brain biomarker correlates of specific cognitive functions. Episodic memory decline was observed to be the most salient cognitive function, correlating with high levels of amyloid deposition and hypoconnectivity across large-scale brain networks. Prospective studies point to early decline in both episodic and semantic memory processing as well as executive functions in the predementia period. The cognitive tests have, however, been principally those used to diagnose dementia. New procedures are required which target more finely the medial temporal lobe subregions first affected by clinically silent AD pathology.

Published
2017

30. Walking and Social Reminiscence in Gentrifying Neighborhoods: Feasibility and Impact on Cognitive, Physical, and Mental Health Among Older Black Adults in the SHARP Study.

Author

Croff, Raina, Aron, Sophia, Wachana, Anne, Fuller, Patrice, Mattek, Nora, Towns, Juell, and Kaye, Jeffrey

Subjects
RESIDENTIAL segregation, SELF-evaluation, WEIGHT loss, EXERCISE, COGNITION in old age, MENTAL health, HEALTH status indicators, MILD cognitive impairment, AFRICAN Americans, HEALTH impact assessment, RESEARCH funding, FOCUS groups, T-test (Statistics), PILOT projects, QUESTIONNAIRES, EVALUATION of human services programs, RESPONSIBILITY, REMINISCENCE, HUMAN research subjects, CLINICAL trials, DESCRIPTIVE statistics, WALKING, PRE-tests & post-tests, THEMATIC analysis, DIASTOLIC blood pressure, CONCEPTUAL structures, RESEARCH, REMINISCENCE therapy, SYSTOLIC blood pressure, COMPARATIVE studies, PSYCHOLOGICAL tests, AFFECT (Psychology), SOCIALIZATION, BLOOD pressure measurement, PHYSICAL activity, SOCIAL participation, PATIENT participation
Abstract

Background and Objectives Two exploratory 6-month pilots of triadic walking with culturally celebratory social reminiscence in gentrifying neighborhoods tested feasibility and health impact among normal and mildly cognitively impaired (MCI) older Black adults. Research Design and Methods Fourteen triads walked 1-mile 3×/week, using a navigational application with image-based reminiscence prompts. Focus groups evaluated perceived health impact and experience. Primary outcome measures were program evaluations (feasibility), pre–post self-report health, Montreal Cognitive Assessment, blood pressure, and weight. Analysis used mean rank scores for program evaluations, pre–post paired t -tests for health outcomes, and thematic coding for 30 focus groups. Results Feasibility: Retention was 74% and 86% for pilots, and 100% and 92%, respectively, were "extremely likely" to recommend to friends/family. Mean rank scores indicated appropriate pace and dose, effective conversational prompts, and program readiness with minor changes. Health impact: Self-rated health, mood, activity levels, and energy improved, days feeling downhearted decreased, and days feeling calm/peaceful were maintained or improved. Among Cohort 2, cognitive assessment scores were maintained or improved for 67%; for MCI, 76% had mean improvement of 2.4 (p  = .045). Blood pressure and weight decreased for 78% and 44%, respectively. Focus groups: Perceived impact of triadic walking included increased physical and social activity outside the program, increased awareness of cognitive decline risk and personal agency, and deep-seated sense of community connection. Discussion and Implications Triadic walking provides structure, accountability, connection, and purpose, motivating sustained engagement. Walking programs that center socialization, particularly within culturally meaningful contexts, may be more effective among older Black adults. Clinical Trial Registration Number NCT05906654 ; NCT05906667 [ABSTRACT FROM AUTHOR]

Published
2024
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31. Recommended cognitive outcomes in preclinical Alzheimer's disease: Consensus statement from the European Prevention of Alzheimer's Dementia project

Author

Ritchie, Karen, Ropacki, Michael, Albala, Bruce, Harrison, John, Kaye, Jeffrey, Kramer, Joel, Randolph, Christopher, and Ritchie, Craig W

Subjects
Biological Psychology, Psychology, Clinical Research, Alzheimer's Disease, Aging, Brain Disorders, Dementia, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Prevention, Neurodegenerative, Neurological, Alzheimer Disease, Clinical Trials as Topic, Cognition, Humans, Neuropsychological Tests, Prodromal Symptoms, Alzheimer's disease, Preclinical, Neuropsychology, Clinical Sciences, Geriatrics, Clinical sciences, Biological psychology
Abstract

The Horizon 2020/IMI European Prevention of Alzheimer's Dementia (EPAD) project will undertake large-scale proof-of-concept trials in predementia Alzheimer's disease (AD). Within EPAD, the monitoring of cognitive trajectories in the preclinical period will constitute a central outcome measure; however, there are currently no clear guidelines as to how this should be achieved as most measures have been developed for the period around dementia diagnosis. The EPAD Scientific Advisory Group for Clinical and Cognitive Outcomes identified appropriate cognitive measures based on a literature search covering both cognitive correlates of preclinical brain changes from imaging studies and cognitive changes observed over time in nondementia population cohorts developing incident dementia. These measures were evaluated according to the following criteria: validity, coherence with biomarker changes, psychometric properties, cross-cultural suitability, availability of alternative forms, and normative data limited practice effects. The resulting consensus statement provides recommendations for both future drug trials and research into preclinical Alzheimer's disease.

Published
2017

34. ICC-dementia (International Centenarian Consortium - dementia): an international consortium to determine the prevalence and incidence of dementia in centenarians across diverse ethnoracial and sociocultural groups

Author

Brodaty, Henry, Woolf, Claudia, Andersen, Stacy, Barzilai, Nir, Brayne, Carol, Cheung, Karen Siu-Lan, Corrada, Maria M, Crawford, John D, Daly, Catriona, Gondo, Yasuyuki, Hagberg, Bo, Hirose, Nobuyoshi, Holstege, Henne, Kawas, Claudia, Kaye, Jeffrey, Kochan, Nicole A, Lau, Bobo Hi-Po, Lucca, Ugo, Marcon, Gabriella, Martin, Peter, Poon, Leonard W, Richmond, Robyn, Robine, Jean-Marie, Skoog, Ingmar, Slavin, Melissa J, Szewieczek, Jan, Tettamanti, Mauro, Viña, José, Perls, Thomas, and Sachdev, Perminder S

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Neurodegenerative, Dementia, Acquired Cognitive Impairment, Clinical Research, Aging, Brain Disorders, 2.4 Surveillance and distribution, Neurological, Aged, 80 and over, Brain, Cognition, Cognitive Dysfunction, Female, Humans, Incidence, Male, Prevalence, Risk, Centenarians, International, Risk factors, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

BackgroundConsiderable variability exists in international prevalence and incidence estimates of dementia. The accuracy of estimates of dementia in the oldest-old and the controversial question of whether dementia incidence and prevalence decline at very old age will be crucial for better understanding the dynamics between survival to extreme old age and the occurrence and risk for various types of dementia and comorbidities. International Centenarian Consortium - Dementia (ICC-Dementia) seeks to harmonise centenarian and near-centenarian studies internationally to describe the cognitive and functional profiles of exceptionally old individuals, and ascertain the trajectories of decline and thereby the age-standardised prevalence and incidence of dementia in this population. The primary goal of the ICC-Dementia is to establish a large and thorough heterogeneous sample that has the power to answer epidemiological questions that small, separate studies cannot. A secondary aim is to examine cohort-specific effects and differential survivorship into very old age. We hope to lay the foundation for further investigation into risk and protective factors for dementia and healthy exceptional brain ageing in centenarians across diverse ethnoracial and sociocultural groups.MethodsStudies focusing on individuals aged ≥95 years (approximately the oldest 1 percentile for men, oldest 5th percentile for women), with a minimum sample of 80 individuals, including assessment of cognition and functional status, are invited to participate. There are currently seventeen member or potential member studies from Asia, Europe, the Americas, and Oceania. Initial attempts at harmonising key variables are in progress.DiscussionGeneral challenges facing large, international consortia like ICC-Dementia include timely and effective communication among member studies, ethical and practical issues relating to human subject studies and data sharing, and the challenges related to data harmonisation. A specific challenge for ICC-Dementia relates to the concept and definition of'abnormal' in this exceptional group of individuals who are rarely free of physical, sensory and/or cognitive impairments.

Published
2016

35. Accelerating rates of cognitive decline and imaging markers associated with &bgr;-amyloid pathology

Author

Insel, Philip S, Mattsson, Niklas, Mackin, R Scott, Schöll, Michael, Nosheny, Rachel L, Tosun, Duygu, Donohue, Michael C, Aisen, Paul S, Jagust, William J, Weiner, Michael W, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Jagust, William, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Saykin, Andrew J, Morris, John, Liu, Enchi, Montine, Tom, Gamst, Anthony, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Harvey, Danielle, Kornak, John, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Thompson, Paul, Schuff, Norbert, Alexander, Gene, DeCarli, Charles, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Cairns, Nigel J, Taylor-Reinwald, Lisa, Trojanowki, JQ, Shaw, Les, Lee, Virginia MY, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lind, Betty, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Morris, John C, Ances, Beau, Carroll, Maria, Leon, Sue, Mintun, Mark A, Schneider, Stacy, Marson, Daniel, and Griffith, Randall

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Acquired Cognitive Impairment, Alzheimer's Disease, Brain Disorders, Neurodegenerative, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Biomedical Imaging, Neurosciences, Aging, Neurological, Aged, Amyloid beta-Peptides, Aniline Compounds, Atrophy, Biomarkers, Brain, Cognition, Cognitive Dysfunction, Disease Progression, Ethylene Glycols, Female, Fluorodeoxyglucose F18, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Mental Status Schedule, Neuropsychological Tests, Peptide Fragments, Positron-Emission Tomography, Radiopharmaceuticals, Regression Analysis, Alzheimer's Disease Neuroimaging Initiative, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveTo estimate points along the spectrum of β-amyloid pathology at which rates of change of several measures of neuronal injury and cognitive decline begin to accelerate.MethodsIn 460 patients with mild cognitive impairment (MCI), we estimated the points at which rates of florbetapir PET, fluorodeoxyglucose (FDG) PET, MRI, and cognitive and functional decline begin to accelerate with respect to baseline CSF Aβ42. Points of initial acceleration in rates of decline were estimated using mixed-effects regression.ResultsRates of neuronal injury and cognitive and even functional decline accelerate substantially before the conventional threshold for amyloid positivity, with rates of florbetapir PET and FDG PET accelerating early. Temporal lobe atrophy rates also accelerate prior to the threshold, but not before the acceleration of cognitive and functional decline.ConclusionsA considerable proportion of patients with MCI would not meet inclusion criteria for a trial using the current threshold for amyloid positivity, even though on average, they are experiencing cognitive/functional decline associated with prethreshold levels of CSF Aβ42. Future trials in early Alzheimer disease might consider revising the criteria regarding β-amyloid thresholds to include the range of amyloid associated with the first signs of accelerating rates of decline.

Published
2016

36. Assessment of the genetic variance of late-onset Alzheimer's disease

Author

Ridge, Perry G, Hoyt, Kaitlyn B, Boehme, Kevin, Mukherjee, Shubhabrata, Crane, Paul K, Haines, Jonathan L, Mayeux, Richard, Farrer, Lindsay A, Pericak-Vance, Margaret A, Schellenberg, Gerard D, Kauwe, John SK, Consortium, Alzheimer's Disease Genetics, Adams, Perrie M, Albert, Marilyn S, Albin, Roger L, Apostolova, Liana G, Arnold, Steven E, Asthana, Sanjay, Atwood, Craig S, Baldwin, Clinton T, Barber, Robert C, Barmada, Michael M, Barnes, Lisa L, Barral, Sandra, Beach, Thomas G, Becker, James T, Beecham, Gary W, Beekly, Duane, Bennett, David A, Bigio, Eileen H, Bird, Thomas D, Blacker, Deborah, Boeve, Bradley F, Bowen, James D, Boxer, Adam, Burke, James R, Burns, Jeffrey M, Buxbaum, Joseph D, Cairns, Nigel J, Cantwell, Laura B, Cao, Chuanhai, Carlson, Chris S, Carlsson, Cynthia M, Carney, Regina M, Carrasquillo, Minerva M, Carroll, Steven L, Chui, Helena C, Clark, David G, Corneveaux, Jason, Cribbs, David H, Crocco, Elizabeth A, Cruchaga, Carlos, De Jager, Philip L, DeCarli, Charles, Demirci, F Yesim, Dick, Malcolm, Dickson, Dennis W, Doody, Rachelle S, Duara, Ranjan, Ertekin-Taner, Nilufer, Evans, Denis A, Faber, Kelley M, Fairchild, Thomas J, Fallon, Kenneth B, Fardo, David W, Farlow, Martin R, Ferris, Steven, Foroud, Tatiana M, Frosch, Matthew P, Galasko, Douglas R, Gearing, Marla, Geschwind, Daniel H, Ghetti, Bernardino, Gilbert, John R, Goate, Alison M, Graff-Radford, Neill R, Green, Robert C, Growdon, John H, Hakonarson, Hakon, Hamilton, Ronald L, Hamilton-Nelson, Kara L, Hardy, John, Harrell, Lindy E, Honig, Lawrence S, Huebinger, Ryan M, Huentelman, Matthew J, Hulette, Christine M, Hyman, Bradley T, Jarvik, Gail P, Jicha, Gregory A, Jin, Lee-Way, Jun, Gyungah, Kamboh, M Ilyas, Karydas, Anna, Katz, Mindy J, Kaye, Jeffrey A, Kim, Ronald, and Kowall, Neil W

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Neurosciences, Psychology, Aging, Human Genome, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Brain Disorders, Acquired Cognitive Impairment, Alzheimer's Disease, Genetics, Neurodegenerative, 2.1 Biological and endogenous factors, Neurological, Aged, Aged, 80 and over, Alzheimer Disease, Amyloid beta-Protein Precursor, Datasets as Topic, Female, Genetic Variation, Genome-Wide Association Study, Humans, Male, Membrane Glycoproteins, Netrin Receptors, Polymorphism, Single Nucleotide, Receptors, Cell Surface, Receptors, Immunologic, Risk, Alzheimer's Disease Genetics Consortium, Alzheimer's disease, Genetic variance, Clinical Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

Alzheimer's disease (AD) is a complex genetic disorder with no effective treatments. More than 20 common markers have been identified, which are associated with AD. Recently, several rare variants have been identified in Amyloid Precursor Protein (APP), Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) and Unc-5 Netrin Receptor C (UNC5C) that affect risk for AD. Despite the many successes, the genetic architecture of AD remains unsolved. We used Genome-wide Complex Trait Analysis to (1) estimate phenotypic variance explained by genetics; (2) calculate genetic variance explained by known AD single nucleotide polymorphisms (SNPs); and (3) identify the genomic locations of variation that explain the remaining unexplained genetic variance. In total, 53.24% of phenotypic variance is explained by genetics, but known AD SNPs only explain 30.62% of the genetic variance. Of the unexplained genetic variance, approximately 41% is explained by unknown SNPs in regions adjacent to known AD SNPs, and the remaining unexplained genetic variance outside these regions.

Published
2016

37. Better verbal memory in women than men in MCI despite similar levels of hippocampal atrophy

Author

Sundermann, Erin E, Biegon, Anat, Rubin, Leah H, Lipton, Richard B, Mowrey, Wenzhu, Landau, Susan, Maki, Pauline M, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Jagust, William, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Saykin, Andrew J, Morris, John, Liu, Enchi, Montine, Tom, Gamst, Anthony, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Harvey, Danielle, Kornak, John, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Thompson, Paul, Schuff, Norbert, Alexander, Gene, DeCarli, Charles, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Cairns, Nigel J, Taylor-Reinwald, Lisa, Trojanowki, JQ, Shaw, Les, Lee, Virginia MY, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lind, Betty, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Morris, John C, Ances, Beau, Carroll, Maria, Leon, Sue, Mintun, Mark A, Schneider, Stacy, Marson, Daniel, Griffith, Randall, Clark, David, Grossman, Hillel, and Mitsis, Effie

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Dementia, Basic Behavioral and Social Science, Mental Health, Acquired Cognitive Impairment, Neurodegenerative, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Behavioral and Social Science, Alzheimer's Disease, Clinical Research, 2.1 Biological and endogenous factors, Neurological, Mental health, Aged, Aged, 80 and over, Atrophy, Cognitive Dysfunction, Cross-Sectional Studies, Female, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Memory, Middle Aged, Sex Characteristics, Verbal Learning, Alzheimer's Disease Neuroimaging Initiative, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveTo examine sex differences in the relationship between clinical symptoms related to Alzheimer disease (AD) (verbal memory deficits) and neurodegeneration (hippocampal volume/intracranial volume ratio [HpVR]) across AD stages.MethodsThe sample included 379 healthy participants, 694 participants with amnestic mild cognitive impairment (aMCI), and 235 participants with AD and dementia from the Alzheimer's Disease Neuroimaging Initiative who completed the Rey Auditory Verbal Learning Test (RAVLT). Cross-sectional analyses were conducted using linear regression to examine the interaction between sex and HpVR on RAVLT across and within diagnostic groups adjusting for age, education, and APOE ε4 status.ResultsAcross groups, there were significant sex × HpVR interactions for immediate and delayed recall (p < 0.01). Women outperformed men among individuals with moderate to larger HpVR, but not among individuals with smaller HpVR. In diagnosis-stratified analyses, the HpVR × sex interaction was significant in the aMCI group, but not in the control or AD dementia groups, for immediate and delayed recall (p < 0.01). Among controls, women outperformed men on both outcomes irrespective of HpVR (p < 0.001). In AD dementia, better RAVLT performance was independently associated with female sex (immediate, p = 0.04) and larger HpVR (delayed, p = 0.001).ConclusionWomen showed an advantage in verbal memory despite evidence of moderate hippocampal atrophy. This advantage may represent a sex-specific form of cognitive reserve delaying verbal memory decline until more advanced disease stages.

Published
2016

38. Continuous Gait Velocity Estimation using Houseohld Motion Detectors

Author

Rana, Rajib, Austin, Daniel, Jacob, Peter G., Karunanithi, Mohanraj, and Kaye, Jeffrey

Subjects
Computer Science - Systems and Control
Abstract

Gait velocity has been consistently shown to be an important indicator and predictor of health status, especially in older adults. Gait velocity is often assessed clinically, but the assessments occur infrequently and thus do not allow optimal detection of key health changes when they occur. In this paper, we show the time it takes a person to move between rooms in their home denoted 'transition times' can predict gait velocity when estimated from passive infrared motion detectors installed in a patient's own home. Using a support vector regression approach to model the relationship between transition times and gait velocities, we show that velocity can be predicted with an average error less than 2.5 cm/sec. This is demonstrated with data collected over a 5 year period from 74 older adults monitored in their own homes. This method is simple and cost effective, and has advantages over competing approaches such as: obtaining 20 to100x more gait velocity measurements per day, and offering the fusion of location specific information with time stamped gait estimates. These advantages allow stable estimates of gait parameters (maximum or average speed, variability) at shorter time scales than current approaches. This also provides a pervasive in home method for context aware gait velocity sensing that allows for monitoring of gait trajectories in space and time., Comment: arXiv admin note: substantial text overlap with arXiv:1310.4880

Published
2014

39. Periventricular hyperintensities are associated with elevated cerebral amyloid

Author

Marnane, Michael, Al-Jawadi, Osama O, Mortazavi, Shervin, Pogorzelec, Kathleen J, Wang, Bing Wei, Feldman, Howard H, Hsiung, Ging-Yuek R, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Jagust, William, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Saykin, Andrew J, Morris, John, Liu, Enchi, Montine, Tom, Gamst, Anthony, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Harvey, Danielle, Kornak, John, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Thompson, Paul, Schuff, Norbert, Alexander, Gene, DeCarli, Charles, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Cairns, Nigel J, Taylor-Reinwald, Lisa, Trojanowki, JQ, Shaw, Les, Lee, Virginia MY, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lind, Betty, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Morris, John C, Ances, Beau, Carroll, Maria, Leon, Sue, Mintun, Mark A, Schneider, Stacy, Marson, Daniel, Griffith, Randall, Clark, David, Grossman, Hillel, and Mitsis, Effie

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Neurosciences, Biomedical Imaging, Brain Disorders, Prevention, Acquired Cognitive Impairment, Cerebrovascular, Alzheimer's Disease, Dementia, Vascular Cognitive Impairment/Dementia, Aging, Alzheimer's Disease Related Dementias (ADRD), Clinical Research, 2.1 Biological and endogenous factors, Neurological, Adult, Aged, Aged, 80 and over, Amyloid beta-Peptides, Biomarkers, Cerebral Ventricles, Cognitive Dysfunction, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Positron-Emission Tomography, Prospective Studies, Alzheimer's Disease Neuroimaging Initiative, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveTo investigate the association between periventricular white mater hyperintensities (PVWMH) and biomarkers of elevated cerebral β-amyloid (Aβ) in the Alzheimer's Disease Neuroimaging Initiative, a large prospective multicenter observational study.MethodsThe burden of frontal, parietal, and occipital PVWMH on 3T fluid-attenuated inversion recovery MRI was evaluated in 698 cognitively normal participants and participants with mild cognitive impairment (MCI) using a novel semiquantitative visual rating scale. Results were correlated with CSF-Aβ, florbetapir-PET, and fluorodeoxyglucose (FDG)-PET.ResultsIncreased burden of parietal, occipital, and frontal PVWMH was associated with elevated cerebral amyloid evidenced by high florbetapir-PET signal (p < 0.01) and low CSF-Aβ (p < 0.01). In logistic regression models, including PVWMH, age, sex, APOE status, vascular risk factors, pulse pressure, vascular secondary prevention medications, education, ethnicity, and race, parietal, occipital, and frontal PVWMH burden was independently associated with high florbetapir-PET uptake (p < 0.05). In a similar logistic regression model, parietal and occipital (p < 0.05) but not frontal (p = 0.05) PVWMH were independently associated with CSF-Aβ. Weaker associations were found between parieto-occipital PVWMH and elevated CSF-tau (p < 0.05) and occipital PVWMH and elevated CSF-phospho-tau (p < 0.05). PVWMH were associated with cerebral hypometabolism on FDG-PET independent of CSF-Aβ levels (p < 0.05). Absolute and consistency of agreement intraclass correlation coefficients were, respectively, 0.83 and 0.83 for frontal, 0.78 and 0.8 for parietal, and 0.45 and 0.75 for occipital PVWMH measurements.ConclusionsIncreased PVWMH were associated with elevated cerebral amyloid independent of potential confounders such as age, APOE genotype, and vascular risk factors. The mechanisms underlying the association between PVWMH and cerebral amyloid remain to be clarified.

Published
2016

40. Memory, executive, and multidomain subtle cognitive impairment

Author

Toledo, Jon B, Bjerke, Maria, Chen, Kewei, Rozycki, Martin, Jack, Clifford R, Weiner, Michael W, Arnold, Steven E, Reiman, Eric M, Davatzikos, Christos, Shaw, Leslie M, Trojanowski, John Q, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jagust, William, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Saykin, Andrew J, Morris, John, Liu, Enchi, Montine, Tom, Gamst, Anthony, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Harvey, Danielle, Kornak, John, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Thompson, Paul, Schuff, Norbert, Alexander, Gene, DeCarli, Charles, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Mathis, Chet, Cairns, Nigel J, Taylor-Reinwald, Lisa, Trojanowki, JQ, Shaw, Les, Lee, Virginia MY, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lind, Betty, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Morris, John C, Ances, Beau, Leon, Sue, Schneider, Stacy, Marson, Daniel, Griffith, Randall, and Clark, David

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Biomedical Imaging, Brain Disorders, Prevention, Acquired Cognitive Impairment, Alzheimer's Disease, Dementia, Aging, Behavioral and Social Science, Clinical Research, 4.1 Discovery and preclinical testing of markers and technologies, 2.1 Biological and endogenous factors, 4.2 Evaluation of markers and technologies, Mental health, Neurological, Aged, Aged, 80 and over, Alzheimer Disease, Biomarkers, Brain, Cognition Disorders, Cognitive Dysfunction, Disease Progression, Executive Function, Female, Humans, Magnetic Resonance Imaging, Male, Memory Disorders, Multimodal Imaging, Positron-Emission Tomography, Alzheimer's Disease Neuroimaging Initiative, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveWe studied the biomarker signatures and prognoses of 3 different subtle cognitive impairment (SCI) groups (executive, memory, and multidomain) as well as the subjective memory complaints (SMC) group.MethodsWe studied 522 healthy controls in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cutoffs for executive, memory, and multidomain SCI were defined using participants who remained cognitively normal (CN) for 7 years. CSF Alzheimer disease (AD) biomarkers, composite and region-of-interest (ROI) MRI, and fluorodeoxyglucose-PET measures were compared in these participants.ResultsUsing a stringent cutoff (fifth percentile), 27.6% of the ADNI participants were classified as SCI. Most single ROI or global-based measures were not sensitive to detect differences between groups. Only MRI-SPARE-AD (Spatial Pattern of Abnormalities for Recognition of Early AD), a quantitative MRI pattern-based global index, showed differences between all groups, excluding the executive SCI group. Atrophy patterns differed in memory SCI and SMC. The CN and the SMC groups presented a similar distribution of preclinical dementia stages. Fifty percent of the participants with executive, memory, and multidomain SCI progressed to mild cognitive impairment or dementia at 7, 5, and 2 years, respectively.ConclusionsOur results indicate that (1) the different SCI categories have different clinical prognoses and biomarker signatures, (2) longitudinally followed CN subjects are needed to establish clinical cutoffs, (3) subjects with SMC show a frontal pattern of brain atrophy, and (4) pattern-based analyses outperform commonly used single ROI-based neuroimaging biomarkers and are needed to detect initial stages of cognitive impairment.

Published
2015

41. Brain structure and function as mediators of the effects of amyloid on memory

Author

Mattsson, Niklas, Insel, Philip S, Aisen, Paul S, Jagust, William, Mackin, Scott, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Saykin, Andrew J, Morris, John, Liu, Enchi, Montine, Tom, Gamst, Anthony, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Gessert, Devon, Sather, Tamie, Harvey, Danielle, Kornak, John, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Thompson, Paul, Schuff, Norbert, Alexander, Gene, DeCarli, Charles, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Cairns, Nigel J, Taylor-Reinwald, Lisa, Trojanowki, JQ, Shaw, Les, Lee, Virginia MY, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Quinn, Joseph, Lind, Betty, Dolen, Sara, Schneider, Lon S, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Morris, John C, Ances, Beau, Carroll, Maria, Leon, Sue, Mintun, Mark A, Schneider, Stacy, Marson, Daniel, Griffith, Randall, Clark, David, Grossman, Hillel, Mitsis, Effie, and Romirowsky, Aliza

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Dementia, Acquired Cognitive Impairment, Neurodegenerative, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Alzheimer's Disease, Biomedical Imaging, 2.1 Biological and endogenous factors, Neurological, Mental health, Aged, Aged, 80 and over, Amyloid beta-Peptides, Brain, Cohort Studies, Female, Follow-Up Studies, Humans, Male, Memory, Episodic, Middle Aged, Prospective Studies, Radionuclide Imaging, Alzheimer's Disease Neuroimaging Initiative, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveThe objective of this study was to test whether effects of β-amyloid (Aβ) pathology on episodic memory were mediated by metabolism and gray matter volume in the early stages of Alzheimer disease.MethodsThis was a prospective cohort study. We measured baseline Aβ (using florbetapir-PET), brain function (using fluorodeoxyglucose-PET), and brain structure (using MRI). A mediation analysis was performed to test whether statistical effects of Aβ positivity on cross-sectional and longitudinal episodic memory were mediated by hypometabolism or regional gray matter volume in cognitively healthy controls (CN, n = 280) and mild cognitive impairment (MCI, n = 463).ResultsLower memory scores were associated with Aβ positivity (CN, mildly; MCI, strongly), smaller gray matter volumes (CN, few regions, including hippocampus; MCI, widespread), and hypometabolism. Smaller volumes and hypometabolism mediated effects of Aβ in MCI but not in CN. The strongest individual regions mediated up to approximately 25%. A combination of brain structure and function mediated up to approximately 40%. In several regions, gray matter atrophy and hypometabolism predicted episodic memory without being associated (at p < 0.05) with Aβ positivity.ConclusionsChanges in brain structure and function appear to be, in part, downstream events from Aβ pathology, ultimately resulting in episodic memory deficits. However, Aβ pathology is also strongly related to memory deficits through mechanisms that are not quantified by these imaging measurements, and episodic memory decline is partly caused by Alzheimer disease-like brain changes independently of Aβ pathology.

Published
2015

42. Gait Velocity Estimation using time interleaved between Consecutive Passive IR Sensor Activations

Author

Rana, Rajib, Austin, Daniel, Jacobs, Peter G., Karunanithi, Mohanraj, and Kaye, Jeffrey

Subjects
Computer Science - Other Computer Science
Abstract

Gait velocity has been consistently shown to be an important indicator and predictor of health status, especially in older adults. It is often assessed clinically, but the assessments occur infrequently and do not allow optimal detection of key health changes when they occur. In this paper, we show that the time gap between activations of a pair of Passive Infrared (PIR) motion sensors installed in the consecutively visited room pair carry rich latent information about a person's gait velocity. We name this time gap transition time and show that despite a six second refractory period of the PIR sensors, transition time can be used to obtain an accurate representation of gait velocity. Using a Support Vector Regression (SVR) approach to model the relationship between transition time and gait velocity, we show that gait velocity can be estimated with an average error less than 2.5 cm/sec. This is demonstrated with data collected over a 5 year period from 74 older adults monitored in their own homes. This method is simple and cost effective and has advantages over competing approaches such as: obtaining 20 to 100x more gait velocity measurements per day and offering the fusion of location-specific information with time stamped gait estimates. These advantages allow stable estimates of gait parameters (maximum or average speed, variability) at shorter time scales than current approaches. This also provides a pervasive in-home method for context-aware gait velocity sensing that allows for monitoring of gait trajectories in space and time.

Published
2013

43. Predictors of cognitive impairment in primary age-related tauopathy: an autopsy study

Author

Iida, Megan A., Farrell, Kurt, Walker, Jamie M., Richardson, Timothy E., Marx, Gabriel A., Bryce, Clare H., Purohit, Dushyant, Ayalon, Gai, Beach, Thomas G., Bigio, Eileen H., Cortes, Etty P., Gearing, Marla, Haroutunian, Vahram, McMillan, Corey T., Lee, Edward B., Dickson, Dennis W., McKee, Ann C., Stein, Thor D., Trojanowski, John Q., Woltjer, Randall L., Kovacs, Gabor G., Kofler, Julia K., Kaye, Jeffrey, White, III, Charles L., and Crary, John F.

Published
2021
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45. Brain amyloidosis ascertainment from cognitive, imaging, and peripheral blood protein measures

Author

Apostolova, Liana G, Hwang, Kristy S, Avila, David, Elashoff, David, Kohannim, Omid, Teng, Edmond, Sokolow, Sophie, Jack, Clifford R, Jagust, William J, Shaw, Leslie, Trojanowski, John Q, Weiner, Michael W, Thompson, Paul M, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jagust, Wiliam, Trojanowki, JQ, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Gamst, Anthony, Sakin, Andrew J, Morris, John, Potter, William Z, Montine, Tom, Donohue, Michael, Walter, Sarah, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Thompson, Paul, Schuff, Norbert, Alexander, Gene, DeCarli, Charles, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Cairns, Nigel J, Taylor-Reinwald, Lisa, Shaw, Lee, Lee, Virginia M-Y, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Harvey, Danielle, Kornak, John, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Dolen, Sara, Quinn, Joseph, Schneider, Lon, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Mintun, Mark A, Schneider, Stacy, Marson, Daniel, Griffith, Randall, Clark, David, Grossman, Hillel, Tang, Cheuk, Marzloff, George, deToledo-Morrell, Leyla, Shah, Raj C, Duara, Ranjan, Varon, Daniel, Robers, Peggy, Albert, Marilyn S, Kozauer, Nicholas, Zerrate, Maria, Rusinek, Henry, de Leon, Mony J, De Santi, Susan M, Doraiswamy, P Murali, Petrella, Jeffrey R, Aiello, Marilyn, Arnold, Steve, and Karlawish, Jason H

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Dementia, Acquired Cognitive Impairment, Neurodegenerative, Behavioral and Social Science, Clinical Research, Brain Disorders, Aging, Biomedical Imaging, Clinical Trials and Supportive Activities, Alzheimer's Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 4.1 Discovery and preclinical testing of markers and technologies, 4.2 Evaluation of markers and technologies, Neurological, Aged, Algorithms, Alzheimer Disease, Amyloid beta-Peptides, Amyloidosis, Aniline Compounds, Biomarkers, Brain, Cognition, Cognitive Dysfunction, Cohort Studies, Databases, Factual, Disease Progression, Female, Humans, Male, Neuropsychological Tests, Pattern Recognition, Automated, Peptide Fragments, Positron-Emission Tomography, Sensitivity and Specificity, Thiazoles, Alzheimer's Disease Neuroimaging Initiative, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

BackgroundThe goal of this study was to identify a clinical biomarker signature of brain amyloidosis in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) mild cognitive impairment (MCI) cohort.MethodsWe developed a multimodal biomarker classifier for predicting brain amyloidosis using cognitive, imaging, and peripheral blood protein ADNI1 MCI data. We used CSF β-amyloid 1-42 (Aβ42) ≤ 192 pg/mL as proxy measure for Pittsburgh compound B (PiB)-PET standard uptake value ratio ≥ 1.5. We trained our classifier in the subcohort with CSF Aβ42 but no PiB-PET data and tested its performance in the subcohort with PiB-PET but no CSF Aβ42 data. We also examined the utility of our biomarker signature for predicting disease progression from MCI to Alzheimer dementia.ResultsThe CSF training classifier selected Mini-Mental State Examination, Trails B, Auditory Verbal Learning Test delayed recall, education, APOE genotype, interleukin 6 receptor, clusterin, and ApoE protein, and achieved leave-one-out accuracy of 85% (area under the curve [AUC] = 0.8). The PiB testing classifier achieved an AUC of 0.72, and when classifier self-tuning was allowed, AUC = 0.74. The 36-month disease-progression classifier achieved AUC = 0.75 and accuracy = 71%.ConclusionsAutomated classifiers based on cognitive and peripheral blood protein variables can identify the presence of brain amyloidosis with a modest level of accuracy. Such methods could have implications for clinical trial design and enrollment in the near future.Classification of evidenceThis study provides Class II evidence that a classification algorithm based on cognitive, imaging, and peripheral blood protein measures identifies patients with brain amyloid on PiB-PET with moderate accuracy (sensitivity 68%, specificity 78%).

Published
2015

46. Mild cognitive impairment with suspected nonamyloid pathology (SNAP)

Author

Caroli, Anna, Prestia, Annapaola, Galluzzi, Samantha, Ferrari, Clarissa, van der Flier, Wiesje M, Ossenkoppele, Rik, Van Berckel, Bart, Barkhof, Frederik, Teunissen, Charlotte, Wall, Anders E, Carter, Stephen F, Schöll, Michael, Choo, Il Han, Grimmer, Timo, Redolfi, Alberto, Nordberg, Agneta, Scheltens, Philip, Drzezga, Alexander, Frisoni, Giovanni B, Weiner, Michael, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Jagust, William, Trojanowki, JQ, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Gamst, Anthony, Saykin, Andrew J, Morris, John, Potter, William Z, Montine, Tom, Thomas, Ronald G, Donohue, Michael, Walter, Sarah, Dale, Anders, Bernstein, Matthew, Felmlee, Joel, Fox, Nick, Thompson, Paul, Schuff, Norbert, Alexander, Gene, DeCarli, Charles, Bandy, Dan, Koeppe, Robert A, Foster, Norm, Reiman, Eric M, Chen, Kewei, Mathis, Chet, Cairns, Nigel J, Taylor-Reinwald, Lisa, Shaw, Les, Lee, Virginia M-Y, Korecka, Magdalena, Crawford, Karen, Neu, Scott, Harvey, Danielle, Kornak, John, Foroud, Tatiana M, Potkin, Steven, Shen, Li, Kachaturian, Zaven, Frank, Richard, Snyder, Peter J, Molchan, Susan, Kaye, Jeffrey, Dolen, Sara, Quinn, Joseph, Schneider, Lon, Pawluczyk, Sonia, Spann, Bryan M, Brewer, James, Vanderswag, Helen, Heidebrink, Judith L, Lord, Joanne L, Johnson, Kris, Doody, Rachelle S, Villanueva-Meyer, Javier, Chowdhury, Munir, Stern, Yaakov, Honig, Lawrence S, Bell, Karen L, Morris, John C, and Mintun, Mark A

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Neurodegenerative, Brain Disorders, Alzheimer's Disease, Vascular Cognitive Impairment/Dementia, Acquired Cognitive Impairment, Neurosciences, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Cerebrovascular, Alzheimer's Disease Related Dementias (ADRD), Dementia, Clinical Research, 2.1 Biological and endogenous factors, 4.2 Evaluation of markers and technologies, 4.1 Discovery and preclinical testing of markers and technologies, Neurological, Aged, Aged, 80 and over, Cognitive Dysfunction, Databases, Factual, Disease Progression, Female, Follow-Up Studies, Humans, Male, Middle Aged, Neurodegenerative Diseases, Plaque, Amyloid, Predictive Value of Tests, Alzheimer's Disease Neuroimaging Initiative, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectivesThe aim of this study was to investigate predictors of progressive cognitive deterioration in patients with suspected non-Alzheimer disease pathology (SNAP) and mild cognitive impairment (MCI).MethodsWe measured markers of amyloid pathology (CSF β-amyloid 42) and neurodegeneration (hippocampal volume on MRI and cortical metabolism on [(18)F]-fluorodeoxyglucose-PET) in 201 patients with MCI clinically followed for up to 6 years to detect progressive cognitive deterioration. We categorized patients with MCI as A+/A- and N+/N- based on presence/absence of amyloid pathology and neurodegeneration. SNAPs were A-N+ cases.ResultsThe proportion of progressors was 11% (8/41), 34% (14/41), 56% (19/34), and 71% (60/85) in A-N-, A+N-, SNAP, and A+N+, respectively; the proportion of APOE ε4 carriers was 29%, 70%, 31%, and 71%, respectively, with the SNAP group featuring a significantly different proportion than both A+N- and A+N+ groups (p ≤ 0.005). Hypometabolism in SNAP patients was comparable to A+N+ patients (p = 0.154), while hippocampal atrophy was more severe in SNAP patients (p = 0.002). Compared with A-N-, SNAP and A+N+ patients had significant risk of progressive cognitive deterioration (hazard ratio = 2.7 and 3.8, p = 0.016 and p < 0.001), while A+N- patients did not (hazard ratio = 1.13, p = 0.771). In A+N- and A+N+ groups, none of the biomarkers predicted time to progression. In the SNAP group, lower time to progression was correlated with greater hypometabolism (r = 0.42, p = 0.073).ConclusionsOur findings support the notion that patients with SNAP MCI feature a specific risk progression profile.

Published
2015

47. The EADC‐ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: Evidence of validity

Author

Frisoni, Giovanni B, Jack, Clifford R, Bocchetta, Martina, Bauer, Corinna, Frederiksen, Kristian S, Liu, Yawu, Preboske, Gregory, Swihart, Tim, Blair, Melanie, Cavedo, Enrica, Grothe, Michel J, Lanfredi, Mariangela, Martinez, Oliver, Nishikawa, Masami, Portegies, Marileen, Stoub, Travis, Ward, Chadwich, Apostolova, Liana G, Ganzola, Rossana, Wolf, Dominik, Barkhof, Frederik, Bartzokis, George, DeCarli, Charles, Csernansky, John G, deToledo‐Morrell, Leyla, Geerlings, Mirjam I, Kaye, Jeffrey, Killiany, Ronald J, Lehéricy, Stephane, Matsuda, Hiroshi, O'Brien, John, Silbert, Lisa C, Scheltens, Philip, Soininen, Hilkka, Teipel, Stefan, Waldemar, Gunhild, Fellgiebel, Andreas, Barnes, Josephine, Firbank, Michael, Gerritsen, Lotte, Henneman, Wouter, Malykhin, Nikolai, Pruessner, Jens C, Wang, Lei, Watson, Craig, Wolf, Henrike, deLeon, Mony, Pantel, Johannes, Ferrari, Clarissa, Bosco, Paolo, Pasqualetti, Patrizio, Duchesne, Simon, Duvernoy, Henri, Boccardi, Marina, Initiative, EADC‐ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Volumetry and for the Alzheimer's Disease Neuroimaging, Albert, Marilyn S, Bennet, David, Camicioli, Richard, Collins, D Louis, Dubois, Bruno, Hampel, Harald, denHeijer, Tom, Hock, Christofer, Jagust, William, Launer, Leonore, Maller, Jerome J, Mueller, Susan, Sachdev, Perminder, Simmons, Andy, Thompson, Paul M, Visser, Peter‐Jelle, Wahlund, Lars‐Olof, Weiner, Michael W, and Winblad, Bengt

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Biomedical Imaging, Neurodegenerative, Clinical Research, Brain Disorders, Acquired Cognitive Impairment, Bioengineering, Aged, Alzheimer Disease, Atrophy, Female, Functional Laterality, Hippocampus, Humans, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Internet, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Organ Size, Reproducibility of Results, Hippocampal volumetry, Magnetic resonance, Alzheimer's disease, Biomarkers, Diagnostic criteria, Enrichment, Clinical trials, Validation, Harmonized protocol, Standard operating procedures, Manual segmentation, EADC-ADNI Working Group on The Harmonized Protocol for Manual Hippocampal Volumetry and for the Alzheimer's Disease Neuroimaging Initiative, Geriatrics, Clinical sciences, Biological psychology
Abstract

BackgroundAn international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance.MethodsFourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T.ResultsThe agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001).ConclusionsThe HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.

Published
2015

48. Rarity of the Alzheimer Disease-Protective APP A673T Variant in the United States

Author

Wang, Li-San, Naj, Adam C, Graham, Robert R, Crane, Paul K, Kunkle, Brian W, Cruchaga, Carlos, Murcia, Josue D. Gonzalez, Cannon-Albright, Lisa, Baldwin, Clinton T, Zetterberg, Henrik, Blennow, Kaj, Kukull, Walter A, Faber, Kelley M, Schupf, Nicole, Norton, Maria C, Tschanz, JoAnn T, Munger, Ronald G, Corcoran, Christopher D, Rogaeva, Ekaterina, Lin, Chiao-Feng, Dombroski, Beth A, Cantwell, Laura B, Partch, Amanda, Valladares, Otto, Hakonarson, Hakon, St George-Hyslop, Peter, Green, Robert C, Goate, Alison M, Foroud, Tatiana M, Carney, Regina M, Larson, Eric B, Behrens, Timothy W, Kauwe, John S. K, Haines, Jonathan L, Farrer, Lindsay A, Pericak-Vance, Margaret A, Mayeux, Richard, Schellenberg, Gerard D, Albert, Marilyn S, Albin, Roger L, Apostolova, Liana G, Arnold, Steven E, Barber, Robert, Barmada, M. Michael, Barnes, Lisa L, Beach, Thomas G, Becker, James T, Beecham, Gary W, Beekly, Duane, Bennett, David A, Bigio, Eileen H, Bird, Thomas D, Blacker, Deborah, Boeve, Bradley F, Bowen, James D, Boxer, Adam, Burke, James R, Buxbaum, Joseph D, Cairns, Nigel J, Cao, Chuanhai, Carlson, Chris S, Carroll, Steven L, Chui, Helena C, Clark, David G, Cribbs, David H, Crocco, Elizabeth A, DeCarli, Charles, DeKosky, Steven T, Demirci, F. Yesim, Dick, Malcolm, Dickson, Dennis W, Duara, Ranjan, Ertekin-Taner, Nilufer, Fallon, Kenneth B, Farlow, Martin R, Ferris, Steven, Frosch, Matthew P, Galasko, Douglas R, Ganguli, Mary, Gearing, Marla, Geschwind, Daniel H, Ghetti, Bernardino, Gilbert, John R, Glass, Jonathan D, Graff-Radford, Neill R, Growdon, John H, Hamilton, Ronald L, Hamilton-Nelson, Kara L, Harrell, Lindy E, Head, Elizabeth, Honig, Lawrence S, Hulette, Christine M, Hyman, Bradley T, Jarvik, Gail P, Jicha, Gregory A, Jin, Lee-Way, Jun, Gyungah, Kamboh, M. Ilyas, Karydas, Anna, and Kaye, Jeffrey A

Published
2015

49. At the interface of sensory and motor dysfunctions and Alzheimer's disease

Author

Albers, Mark W, Gilmore, Grover C, Kaye, Jeffrey, Murphy, Claire, Wingfield, Arthur, Bennett, David A, Boxer, Adam L, Buchman, Aron S, Cruickshanks, Karen J, Devanand, Davangere P, Duffy, Charles J, Gall, Christine M, Gates, George A, Granholm, Ann‐Charlotte, Hensch, Takao, Holtzer, Roee, Hyman, Bradley T, Lin, Frank R, McKee, Ann C, Morris, John C, Petersen, Ronald C, Silbert, Lisa C, Struble, Robert G, Trojanowski, John Q, Verghese, Joe, Wilson, Donald A, Xu, Shunbin, and Zhang, Li I

Subjects
Biological Psychology, Psychology, Acquired Cognitive Impairment, Alzheimer's Disease, Neurosciences, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Neurodegenerative, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Alzheimer Disease, Disease Progression, Early Diagnosis, Humans, Movement Disorders, National Institute on Aging (U.S.), Sensation Disorders, United States, Sensory, Motor, Olfaction, Vision, Auditory function, Alzheimer's disease, Clinical Sciences, Geriatrics, Clinical sciences, Biological psychology
Abstract

Recent evidence indicates that sensory and motor changes may precede the cognitive symptoms of Alzheimer's disease (AD) by several years and may signify increased risk of developing AD. Traditionally, sensory and motor dysfunctions in aging and AD have been studied separately. To ascertain the evidence supporting the relationship between age-related changes in sensory and motor systems and the development of AD and to facilitate communication between several disciplines, the National Institute on Aging held an exploratory workshop titled "Sensory and Motor Dysfunctions in Aging and AD." The scientific sessions of the workshop focused on age-related and neuropathologic changes in the olfactory, visual, auditory, and motor systems, followed by extensive discussion and hypothesis generation related to the possible links among sensory, cognitive, and motor domains in aging and AD. Based on the data presented and discussed at this workshop, it is clear that sensory and motor regions of the central nervous system are affected by AD pathology and that interventions targeting amelioration of sensory-motor deficits in AD may enhance patient function as AD progresses.

Published
2015

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