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Paolillo EW, Casaletto KB, Clark AL, Taylor JC, Heuer HW, Wise AB, Dhanam S, Sanderson-Cimino M, Saloner R, Kramer JH, Kornak J, Kremers W, Forsberg L, Appleby B, Bayram E, Bozoki A, Brushaber D, Darby RR, Day GS, Dickerson BC, Domoto-Reilly K, Elahi F, Fields JA, Ghoshal N, Graff-Radford N, G H Hall M, Honig LS, Huey ED, Lapid MI, Litvan I, Mackenzie IR, Masdeu JC, Mendez MF, Mester C, Miyagawa T, Naasan G, Pascual B, Pressman P, Ramos EM, Rankin KP, Rexach J, Rojas JC, VandeVrede L, Wong B, Wszolek ZK, Boeve BF, Rosen HJ, Boxer AL, Staffaroni AM. Examining Associations Between Smartphone Use and Clinical Severity in Frontotemporal Dementia: Proof-of-Concept Study. JMIR Aging 2024; 7:e52831. [PMID: 38922667 DOI: 10.2196/52831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 02/09/2024] [Accepted: 03/07/2024] [Indexed: 06/27/2024] Open
Abstract
BACKGROUND Frontotemporal lobar degeneration (FTLD) is a leading cause of dementia in individuals aged <65 years. Several challenges to conducting in-person evaluations in FTLD illustrate an urgent need to develop remote, accessible, and low-burden assessment techniques. Studies of unobtrusive monitoring of at-home computer use in older adults with mild cognitive impairment show that declining function is reflected in reduced computer use; however, associations with smartphone use are unknown. OBJECTIVE This study aims to characterize daily trajectories in smartphone battery use, a proxy for smartphone use, and examine relationships with clinical indicators of severity in FTLD. METHODS Participants were 231 adults (mean age 52.5, SD 14.9 years; n=94, 40.7% men; n=223, 96.5% non-Hispanic White) enrolled in the Advancing Research and Treatment of Frontotemporal Lobar Degeneration (ARTFL study) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS study) Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) Mobile App study, including 49 (21.2%) with mild neurobehavioral changes and no functional impairment (ie, prodromal FTLD), 43 (18.6%) with neurobehavioral changes and functional impairment (ie, symptomatic FTLD), and 139 (60.2%) clinically normal adults, of whom 55 (39.6%) harbored heterozygous pathogenic or likely pathogenic variants in an autosomal dominant FTLD gene. Participants completed the Clinical Dementia Rating plus National Alzheimer's Coordinating Center Frontotemporal Lobar Degeneration Behavior and Language Domains (CDR+NACC FTLD) scale, a neuropsychological battery; the Neuropsychiatric Inventory; and brain magnetic resonance imaging. The ALLFTD Mobile App was installed on participants' smartphones for remote, passive, and continuous monitoring of smartphone use. Battery percentage was collected every 15 minutes over an average of 28 (SD 4.2; range 14-30) days. To determine whether temporal patterns of battery percentage varied as a function of disease severity, linear mixed effects models examined linear, quadratic, and cubic effects of the time of day and their interactions with each measure of disease severity on battery percentage. Models covaried for age, sex, smartphone type, and estimated smartphone age. RESULTS The CDR+NACC FTLD global score interacted with time on battery percentage such that participants with prodromal or symptomatic FTLD demonstrated less change in battery percentage throughout the day (a proxy for less smartphone use) than clinically normal participants (P<.001 in both cases). Additional models showed that worse performance in all cognitive domains assessed (ie, executive functioning, memory, language, and visuospatial skills), more neuropsychiatric symptoms, and smaller brain volumes also associated with less battery use throughout the day (P<.001 in all cases). CONCLUSIONS These findings support a proof of concept that passively collected data about smartphone use behaviors associate with clinical impairment in FTLD. This work underscores the need for future studies to develop and validate passive digital markers sensitive to longitudinal clinical decline across neurodegenerative diseases, with potential to enhance real-world monitoring of neurobehavioral change.
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Affiliation(s)
- Emily W Paolillo
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Kaitlin B Casaletto
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Annie L Clark
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Jack C Taylor
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Hilary W Heuer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Amy B Wise
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Sreya Dhanam
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Mark Sanderson-Cimino
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Rowan Saloner
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Joel H Kramer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - John Kornak
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Walter Kremers
- Department of Quantitative Health Sciences, Division of Clinical Trials and Biostatistics, Mayo Clinic, Rochester, MN, United States
| | - Leah Forsberg
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Brian Appleby
- Department of Neurology, Case Western Reserve University, Cleveland, OH, United States
| | - Ece Bayram
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Andrea Bozoki
- Department of Neurology, University of North Carolina, Chapel Hill, NC, United States
| | - Danielle Brushaber
- Department of Quantitative Health Sciences, Division of Clinical Trials and Biostatistics, Mayo Clinic, Rochester, MN, United States
| | - R Ryan Darby
- Department of Neurology, Vanderbilt University, Nashville, TN, United States
| | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, FL, United States
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | | | - Fanny Elahi
- Department of Neurology, The Deane Center for Wellness and Cognitive Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- James J. Peters Veterans Affairs Medical Center, New York, NY, United States
| | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Nupur Ghoshal
- Department of Neurology, Knight Alzheimer's Disease Research Center, Washington University, St. Louis, MO, United States
| | | | - Matthew G H Hall
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Lawrence S Honig
- Department of Neurology, Columbia University, New York, NY, United States
| | - Edward D Huey
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, United States
| | - Maria I Lapid
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Irene Litvan
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Ian R Mackenzie
- Department of Pathology, University of British Columbia, Vancouver, BC, Canada
| | - Joseph C Masdeu
- Stanley H. Appel Department of Neurology, Nantz National Alzheimer Center, Houston Methodist Research Institute, Weill Cornell Medicine, Houston, TX, United States
| | - Mario F Mendez
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Carly Mester
- Department of Quantitative Health Sciences, Division of Clinical Trials and Biostatistics, Mayo Clinic, Rochester, MN, United States
| | - Toji Miyagawa
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Georges Naasan
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Belen Pascual
- Stanley H. Appel Department of Neurology, Nantz National Alzheimer Center, Houston Methodist Research Institute, Weill Cornell Medicine, Houston, TX, United States
| | - Peter Pressman
- Department of Neurology, University of Colorado, Aurora, CO, United States
| | - Eliana Marisa Ramos
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Katherine P Rankin
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Jessica Rexach
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Julio C Rojas
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Lawren VandeVrede
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Bonnie Wong
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Adam L Boxer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Adam M Staffaroni
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
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Soffer M, Butters MA, Herrmann N, Black SE, Kumar S, Pugh B, Rajji TK, Tartaglia MC, Tang-Wai DF, Freedman M. About time: neurocognitive correlates of stimulus-bound and other time setting errors in the Clock Drawing Test. J Int Neuropsychol Soc 2024; 30:471-478. [PMID: 38088261 DOI: 10.1017/s1355617723011396] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/09/2024]
Abstract
OBJECTIVE Previous findings suggest that time setting errors (TSEs) in the Clock Drawing Test (CDT) may be related mainly to impairments in semantic and executive function. Recent attempts to dissociate the classic stimulus-bound error (setting the time to "10 to 11" instead of "10 past 11") from other TSEs, did not support hypotheses regarding this error being primarily executive in nature or different from other time setting errors in terms of neurocognitive correlates. This study aimed to further investigate the cognitive correlates of stimulus-bound errors and other TSEs, in order to trace possible underlying cognitive deficits. METHODS We examined cognitive test performance of participants with preliminary diagnoses associated with mild cognitive impairment. Among 490 participants, we identified clocks with stimulus-bound errors (n = 78), other TSEs (n = 41), other errors not related to time settings (n = 176), or errorless clocks (n = 195). RESULTS No differences were found on any dependent measure between the stimulus-bound and the other TSErs groups. Group comparisons suggested TSEs in general, to be associated with lower performance on various cognitive measures, especially on semantic and working memory measures. Regression analysis further highlighted semantic and verbal working memory difficulties as being the most prominent deficits associated with these errors. CONCLUSION TSEs in the CDT may indicate underlying deficits in semantic function and working memory. In addition, results support previous findings related to the diagnostic value of TSEs in detecting cognitive impairment.
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Affiliation(s)
- Matan Soffer
- Centre for Addiction and Mental Health, Toronto, Canada
| | - Meryl A Butters
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nathan Herrmann
- Toronto Dementia Research Alliance, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Sandra E Black
- Toronto Dementia Research Alliance, Toronto, Canada
- Sunnybrook Health Sciences Centre, Toronto, Canada
- Department of Medicine (Neurology), Unviversity of Toronto, Toronto, Canada
| | - Sanjeev Kumar
- Centre for Addiction and Mental Health, Toronto, Canada
- Toronto Dementia Research Alliance, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Bradley Pugh
- Toronto Dementia Research Alliance, Toronto, Canada
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, ON, Canada
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, Canada
- Toronto Dementia Research Alliance, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Maria Carmela Tartaglia
- Toronto Dementia Research Alliance, Toronto, Canada
- Department of Medicine (Neurology), Unviversity of Toronto, Toronto, Canada
- University Health Network Memory Clinic, Toronto Western Hospital, Toronto, ON, Canada
| | - David F Tang-Wai
- Toronto Dementia Research Alliance, Toronto, Canada
- Department of Medicine (Neurology), Unviversity of Toronto, Toronto, Canada
- University Health Network Memory Clinic, Toronto Western Hospital, Toronto, ON, Canada
| | - Morris Freedman
- Toronto Dementia Research Alliance, Toronto, Canada
- Department of Medicine (Neurology), Unviversity of Toronto, Toronto, Canada
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, ON, Canada
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Illán-Gala I, Lorca-Puls DL, Tee BL, Ezzes Z, de Leon J, Miller ZA, Rubio-Guerra S, Santos-Santos M, Gómez-Andrés D, Grinberg LT, Spina S, Kramer JH, Wauters LD, Henry ML, Boxer AL, Rosen HJ, Miller BL, Seeley WW, Mandelli ML, Gorno-Tempini ML. Clinical dimensions along the non-fluent variant primary progressive aphasia spectrum. Brain 2024; 147:1511-1525. [PMID: 37988272 PMCID: PMC10994525 DOI: 10.1093/brain/awad396] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 10/21/2023] [Accepted: 11/05/2023] [Indexed: 11/23/2023] Open
Abstract
It is debated whether primary progressive apraxia of speech (PPAOS) and progressive agrammatic aphasia (PAA) belong to the same clinical spectrum, traditionally termed non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), or exist as two completely distinct syndromic entities with specific pathologic/prognostic correlates. We analysed speech, language and disease severity features in a comprehensive cohort of patients with progressive motor speech impairment and/or agrammatism to ascertain evidence of naturally occurring, clinically meaningful non-overlapping syndromic entities (e.g. PPAOS and PAA) in our data. We also assessed if data-driven latent clinical dimensions with aetiologic/prognostic value could be identified. We included 98 participants, 43 of whom had an autopsy-confirmed neuropathological diagnosis. Speech pathologists assessed motor speech features indicative of dysarthria and apraxia of speech (AOS). Quantitative expressive/receptive agrammatism measures were obtained and compared with healthy controls. Baseline and longitudinal disease severity was evaluated using the Clinical Dementia Rating Sum of Boxes (CDR-SB). We investigated the data's clustering tendency and cluster stability to form robust symptom clusters and employed principal component analysis to extract data-driven latent clinical dimensions (LCD). The longitudinal CDR-SB change was estimated using linear mixed-effects models. Of the participants included in this study, 93 conformed to previously reported clinical profiles (75 with AOS and agrammatism, 12 PPAOS and six PAA). The remaining five participants were characterized by non-fluent speech, executive dysfunction and dysarthria without apraxia of speech or frank agrammatism. No baseline clinical features differentiated between frontotemporal lobar degeneration neuropathological subgroups. The Hopkins statistic demonstrated a low cluster tendency in the entire sample (0.45 with values near 0.5 indicating random data). Cluster stability analyses showed that only two robust subgroups (differing in agrammatism, executive dysfunction and overall disease severity) could be identified. Three data-driven components accounted for 71% of the variance [(i) severity-agrammatism; (ii) prominent AOS; and (iii) prominent dysarthria]. None of these data-driven LCDs allowed an accurate prediction of neuropathology. The severity-agrammatism component was an independent predictor of a faster CDR-SB increase in all the participants. Higher dysarthria severity, reduced words per minute and expressive and receptive agrammatism severity at baseline independently predicted accelerated disease progression. Our findings indicate that PPAOS and PAA, rather than exist as completely distinct syndromic entities, constitute a clinical continuum. In our cohort, splitting the nfvPPA spectrum into separate clinical phenotypes did not improve clinical-pathological correlations, stressing the need for new biological markers and consensus regarding updated terminology and clinical classification.
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Affiliation(s)
- Ignacio Illán-Gala
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Madrid, 28029, Spain
- Global Brain Health Institute, University of California, San Francisco, CA 94143, USA
| | - Diego L Lorca-Puls
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
- Sección de Neurología, Departamento de Especialidades, Facultad de Medicina, Universidad de Concepción, Concepción, 4070001, Chile
| | - Boon Lead Tee
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Zoe Ezzes
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Jessica de Leon
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Zachary A Miller
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Sara Rubio-Guerra
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, 08025, Barcelona, Spain
| | - Miguel Santos-Santos
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, 08025, Barcelona, Spain
| | - David Gómez-Andrés
- Vall d'Hebron Institut de Recerca (VHIR), Hospital Universitari Vall d'Hebron, 08035, Barcelona, Spain
| | - Lea T Grinberg
- Global Brain Health Institute, University of California, San Francisco, CA 94143, USA
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Salvatore Spina
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Lisa D Wauters
- Department of Communication Sciences and Disorders, University of Texas, Austin, TX 78712-0114, USA
| | - Maya L Henry
- Department of Communication Sciences and Disorders, University of Texas, Austin, TX 78712-0114, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - William W Seeley
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Maria Luisa Mandelli
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
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Nester CO, Gao Q, Wang C, Katz MJ, Lipton RB, Verghese J, Rabin LA. "Cognitive" Criteria in Older Adults With Slow Gait Speed: Implications for Motoric Cognitive Risk Syndrome. J Gerontol A Biol Sci Med Sci 2024; 79:glae038. [PMID: 38349795 PMCID: PMC10943500 DOI: 10.1093/gerona/glae038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Motoric cognitive risk syndrome (MCR) is a predementia condition that combines slow gait speed and subjective cognitive concerns (SCC). The SCC criterion is presently unstandardized, possibly limiting risk detection. We sought to (a) characterize SCC practices through MCR literature review; (b) investigate the ability of SCC in slow gait individuals in predicting the likelihood of cognitive impairment in a demographically diverse sample of community-dwelling, nondemented older adults. METHODS First, we comprehensively reviewed the MCR literature, extracting information regarding SCC measures, items, sources, and cognitive domain. Next, Einstein Aging Study (EAS) participants (N = 278, Mage = 77.22 ± 4.74, %female = 67, Meducation = 15 ± 3.61, %non-Hispanic White = 46.3) completed gait, Clinical Dementia Rating Scale (CDR), and SCC assessment at baseline and annual follow-up (Mfollow-up = 3.5). Forty-two participants met slow gait criteria at baseline. Generalized linear mixed-effects models examined baseline SCC to predict cognitive impairment on CDR over follow-up. RESULTS We reviewed all published MCR studies (N = 106) and documented ambiguity in SCC criteria, with a prevalent approach being use of a single self-reported memory item. In EAS, high SCC endorsement on a comprehensive, validated screen significantly affected the rate of cognitive impairment (CDR; βinteraction = 0.039, p = .018) in slow gait individuals. CONCLUSIONS An assessment approach that queries across numerous SCC domains was found to predict future decline in clinical dementia status in slow gait older adults. Current SCC practices in MCR, which tend to utilize a single-memory item, may not be the optimal approach. We discuss the implications of SCC criteria validation and standardization to enhance early dementia detection in MCR.
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Affiliation(s)
- Caroline O Nester
- Department of Psychology, The Graduate Center, City University of New York, New York, New York, USA
- Department of Psychology, Queens College, City University of New York, Flushing, New York, USA
| | - Qi Gao
- Department of Epidemiology & Public Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Cuiling Wang
- Department of Epidemiology & Public Health, Albert Einstein College of Medicine, Bronx, New York, USA
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Mindy J Katz
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Richard B Lipton
- Department of Epidemiology & Public Health, Albert Einstein College of Medicine, Bronx, New York, USA
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Joe Verghese
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, USA
- Department of Medicine (Geriatrics), Albert Einstein College of Medicine, Bronx, New York, USA
| | - Laura A Rabin
- Department of Psychology, The Graduate Center, City University of New York, New York, New York, USA
- Department of Psychology, Brooklyn College, City University of New York, Brooklyn, New York, USA
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5
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Suchy‐Dicey AM, Longstreth WT, Rhoads K, Umans J, Buchwald D, Grabowski T, Blennow K, Reiman E, Zetterberg H. Plasma biomarkers of Alzheimer's disease and related dementias in American Indians: The Strong Heart Study. Alzheimers Dement 2024; 20:2072-2079. [PMID: 38215191 PMCID: PMC10984473 DOI: 10.1002/alz.13664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 11/16/2023] [Accepted: 12/04/2023] [Indexed: 01/14/2024]
Abstract
INTRODUCTION Identification of Alzheimer's disease (AD) needs inexpensive, noninvasive biomarkers, with validation in all populations. METHODS We collected plasma markers in older American Indian individuals: phosphorylated-tau181 (pTau181); amyloid-beta (Aβ) 40,42; glial fibrillary acidic protein (GFAP); and neurofilament light chain (NfL). Plasma markers were analyzed for discriminant properties with cognitive status and etiology using receiver operating characteristic (ROC) analysis. RESULTS PTau181, GFAP, NfL plasma values were significantly associated with cognition, but Aβ were not. Discriminant performance was moderate for individual markers, with pTau181, GFAP, NfL performing best, but an empirically selected panel of markers (age, sex, education, pTau181, GFAP, NfL, Aβ4240 ratio) had excellent discriminant performance (AUC > 0.8). DISCUSSION In American Indian individuals, pTau181 and Aβ values suggested more common pathology than in majority populations. Aβ was less informative than in other populations; however, all four markers were needed for a best-performing dementia diagnostic model. These data validate utility of AD plasma markers, while suggesting population-specific diagnostic characteristics.
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Affiliation(s)
- Astrid M. Suchy‐Dicey
- Washington State University Elson S Floyd College of MedicineSpokaneWashingtonUSA
- Huntington Medical Research InstitutesPasadenaCaliforniaUSA
- Washington State University Institute for Research and Education to Address Community HealthSeattleWashingtonUSA
- University of Washington Alzheimer's Disease Research CenterSeattleWashingtonUSA
| | - W. T. Longstreth
- Department of NeurologyUniversity of WashingtonSeattleWashingtonUSA
| | - Kristoffer Rhoads
- University of Washington Alzheimer's Disease Research CenterSeattleWashingtonUSA
- Department of NeurologyUniversity of WashingtonSeattleWashingtonUSA
| | - Jason Umans
- MedStar Health Research InstituteHyattsvilleMarylandUSA
| | - Dedra Buchwald
- Washington State University Institute for Research and Education to Address Community HealthSeattleWashingtonUSA
| | - Thomas Grabowski
- University of Washington Alzheimer's Disease Research CenterSeattleWashingtonUSA
- Department of NeurologyUniversity of WashingtonSeattleWashingtonUSA
| | - Kaj Blennow
- Institute of Neuroscience and Physiologythe Sahlgrenska Academy at University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Eric Reiman
- Banner Alzheimer's InstitutePhoenixArizonaUSA
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiologythe Sahlgrenska Academy at University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
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6
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Kiselica AM, Kaser AN, Weitzner DS, Mikula CM, Boone A, Woods SP, Wolf TJ, Webber TA. Development and Validity of Norms for Cognitive Dispersion on the Uniform Data Set 3.0 Neuropsychological Battery. Arch Clin Neuropsychol 2024:acae005. [PMID: 38364295 DOI: 10.1093/arclin/acae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 11/14/2023] [Accepted: 12/15/2023] [Indexed: 02/18/2024] Open
Abstract
OBJECTIVE Cognitive dispersion indexes intraindividual variability in performance across a battery of neuropsychological tests. Measures of dispersion show promise as markers of cognitive dyscontrol and everyday functioning difficulties; however, they have limited practical applicability due to a lack of normative data. This study aimed to develop and evaluate normed scores for cognitive dispersion among older adults. METHOD We analyzed data from 4,283 cognitively normal participants aged ≥50 years from the Uniform Data Set (UDS) 3.0. We describe methods for calculating intraindividual standard deviation (ISD) and coefficient of variation (CoV), as well as associated unadjusted scaled scores and demographically adjusted z-scores. We also examined the ability of ISD and CoV scores to differentiate between cognitively normal individuals (n = 4,283) and those with cognitive impairment due to Lewy body disease (n = 282). RESULTS We generated normative tables to map raw ISD and CoV scores onto a normal distribution of scaled scores. Cognitive dispersion indices were associated with age, education, and race/ethnicity but not sex. Regression equations were used to develop a freely accessible Excel calculator for deriving demographically adjusted normed scores for ISD and CoV. All measures of dispersion demonstrated excellent diagnostic utility when evaluated by the area under the curve produced from receiver operating characteristic curves. CONCLUSIONS Results of this study provide evidence for the clinical utility of sample-based and demographically adjusted normative standards for cognitive dispersion on the UDS 3.0. These standards can be used to guide interpretation of intraindividual variability among older adults in clinical and research settings.
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Affiliation(s)
- Andrew M Kiselica
- Department of Health Psychology, University of Missouri, Columbia, MO, USA
| | - Alyssa N Kaser
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Cynthia M Mikula
- Institute of Human Nutrition, Columbia University, New York, NY, USA
| | - Anna Boone
- Department of Occupational Therapy, University of Missouri, Columbia, MO, USA
| | | | - Timothy J Wolf
- Department of Occupational Therapy, University of Missouri, Columbia, MO, USA
| | - Troy A Webber
- Mental Health Care Line, Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
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7
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Chumin EJ, Cutts SA, Risacher SL, Apostolova LG, Farlow MR, McDonald BC, Wu YC, Betzel R, Saykin AJ, Sporns O. Edge time series components of functional connectivity and cognitive function in Alzheimer's disease. Brain Imaging Behav 2024; 18:243-255. [PMID: 38008852 PMCID: PMC10844434 DOI: 10.1007/s11682-023-00822-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2023] [Indexed: 11/28/2023]
Abstract
Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.
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Affiliation(s)
- Evgeny J Chumin
- Department of Psychological and Brain Sciences, Indiana University (IU), Psychology Building 308, 1101 E 10th St, Bloomington, IN, 47405, USA.
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA.
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA.
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA.
| | - Sarah A Cutts
- Department of Psychological and Brain Sciences, Indiana University (IU), Psychology Building 308, 1101 E 10th St, Bloomington, IN, 47405, USA
- Program in Neuroscience, IU, Bloomington, IN, USA
| | - Shannon L Risacher
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
| | - Liana G Apostolova
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
- Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Martin R Farlow
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Brenna C McDonald
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
- Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
| | - Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University (IU), Psychology Building 308, 1101 E 10th St, Bloomington, IN, 47405, USA
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Program in Neuroscience, IU, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
- Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University (IU), Psychology Building 308, 1101 E 10th St, Bloomington, IN, 47405, USA
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Program in Neuroscience, IU, Bloomington, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
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8
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Zhang X, Lv L, Shen J, Chen J, Zhang H, Li Y. A tablet-based multi-dimensional drawing system can effectively distinguish patients with amnestic MCI from healthy individuals. Sci Rep 2024; 14:982. [PMID: 38200020 PMCID: PMC10781783 DOI: 10.1038/s41598-023-46710-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 11/03/2023] [Indexed: 01/12/2024] Open
Abstract
The population with dementia is expected to rise to 152 million in 2050 due to the aging population worldwide. Therefore, it is significant to identify and intervene in the early stage of dementia. The Rey-Osterreth complex figure (ROCF) test is a visuospatial test scale. Its scoring methods are numerous, time-consuming, and inconsistent, which is unsuitable for wide application as required by the high number of people at risk. Therefore, there is an urgent need for a rapid, objective, and sensitive digital scoring method to detect cognitive dysfunction in the early stage accurately. This study aims to clarify the organizational strategy of aMCI patients to draw complex figures through a multi-dimensional digital evaluation system. At the same time, a rapid, objective, and sensitive digital scoring method is established to replace traditional scoring. The data of 64 subjects (38 aMCI patients and 26 NC individuals) were analyzed in this study. All subjects completed the tablet's Geriatric Complex Figure (GCF) test, including copying, 3-min recall, and 20-min delayed recall, and also underwent a standardized neuropsychological test battery and classic ROCF test. Digital GCF (dGCF) variables and conventional GCF (cGCF) scores were input into the forward stepwise logistic regression model to construct classification models. Finally, ROC curves were made to visualize the difference in the diagnostic value of dGCF variables vs. cGCF scores in categorizing the diagnostic groups. In 20-min delayed recall, aMCI patients' time in air and pause time were longer than NC individuals. Patients with aMCI had more short strokes and poorer ability of detail integration (all p < 0.05). The diagnostic sensitivity of dGCF variables for aMCI patients was 89.47%, slightly higher than cGCF scores (sensitivity: 84.21%). The diagnostic accuracy of both was comparable (dGCF: 70.3%; cGCF: 73.4%). Moreover, combining dGCF variables and cGCF scores could significantly improve the diagnostic accuracy and specificity (accuracy: 78.1%, specificity: 84.62%). At the same time, we construct the regression equations of the two models. Our study shows that dGCF equipment can quantitatively evaluate drawing performance, and its performance is comparable to the time-consuming cGCF score. The regression equation of the model we constructed can well identify patients with aMCI in clinical application. We believe this new technique can be a highly effective screening tool for patients with MCI.
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Affiliation(s)
- Xiaonan Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, China
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, China
| | | | - Jiani Shen
- Department of First Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Jinyu Chen
- Department of First Clinical Medicine, Shanxi Medical University, Taiyuan, China
| | - Hui Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, China.
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, China.
- Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, China.
| | - Yang Li
- Department of Neurology, First Hospital of Shanxi Medical University, Taiyuan, China.
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Rouse HJ, Ismail Z, Andel R, Molinari VA, Schinka JA, Small BJ. Impact of Mild Behavioral Impairment on Longitudinal Changes in Cognition. J Gerontol A Biol Sci Med Sci 2024; 79:glad098. [PMID: 37052173 DOI: 10.1093/gerona/glad098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Indexed: 04/14/2023] Open
Abstract
BACKGROUND To examine cross-sectional differences and longitudinal changes in cognitive performance based on the presence of mild behavioral impairment (MBI) among older adults who are cognitively healthy or have mild cognitive impairment (MCI). METHODS Secondary data analysis of participants (n = 17 291) who were cognitively healthy (n = 11 771) or diagnosed with MCI (n = 5 520) from the National Alzheimer's Coordinating Center database. Overall, 24.7% of the sample met the criteria for MBI. Cognition was examined through a neuropsychological battery that assessed attention, episodic memory, executive function, language, visuospatial ability, and processing speed. RESULTS Older adults with MBI, regardless of whether they were cognitively healthy or diagnosed with MCI, performed significantly worse at baseline on tasks for attention, episodic memory, executive function, language, and processing speed and exhibited greater longitudinal declines on tasks of attention, episodic memory, language, and processing speed. Cognitively healthy older adults with MBI performed significantly worse than those who were cognitively healthy without MBI on tasks of visuospatial ability at baseline and on tasks of processing speed across time. Older adults with MCI and MBI performed significantly worse than those with only MCI on executive function at baseline and visuospatial ability and processing speed tasks across time. CONCLUSIONS This study found evidence that MBI is related to poorer cognitive performance cross-sectionally and longitudinally. Additionally, those with MBI and MCI performed worse across multiple tasks of cognition both cross-sectionally and across time. These results provide support for MBI being uniquely associated with different aspects of cognition.
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Affiliation(s)
- Hillary J Rouse
- School of Aging Studies, University of South Florida, Tampa, Florida, USA
| | - Zahinoor Ismail
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Psychiatry, Clinical Neurosciences, and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Ross Andel
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, USA
- Department of Neurology, Charles University, Prague, Czech Republic
| | - Victor A Molinari
- School of Aging Studies, University of South Florida, Tampa, Florida, USA
| | - John A Schinka
- School of Aging Studies, University of South Florida, Tampa, Florida, USA
| | - Brent J Small
- School of Aging Studies, University of South Florida, Tampa, Florida, USA
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10
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Webber TA, Lorkiewicz SA, Kiselica AM, Woods SP. Ecological validity of cognitive fluctuations in dementia with Lewy bodies. J Int Neuropsychol Soc 2024; 30:35-46. [PMID: 37057867 PMCID: PMC10576013 DOI: 10.1017/s1355617723000255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/15/2023]
Abstract
OBJECTIVES Cognitive fluctuations are a core clinical feature of dementia with Lewy bodies (DLB), but their contribution to the everyday functioning difficulties evident DLB are not well understood. The current study evaluated whether intraindividual variability across a battery of neurocognitive tests (intraindividual variability-dispersion) and daily cognitive fluctuations as measured by informant report are associated with worse daily functioning in DLB. METHODS The study sample included 97 participants with consensus-defined DLB from the National Alzheimer's Coordinating Center (NACC). Intraindividual variability-dispersion was measured using the coefficient of variation, which divides the standard deviation of an individual's performance scores across 12 normed neurocognitive indices from the NACC neuropsychological battery by that individual's performance mean. Informants reported on daily cognitive fluctuations using the Mayo Fluctuations Scale (MFS) and on daily functioning using the functional activities questionnaire (FAQ). RESULTS Logistic regression identified a large univariate association of intraindividual variability-dispersion and presence of daily cognitive fluctuations on the MFS (Odds Ratio = 73.27, 95% Confidence Interval = 1.38, 3,895.05). Multiple linear regression demonstrated that higher intraindividual variability-dispersion and presence of daily cognitive fluctuations as assessed by the MFS were significantly and independently related to worse daily functioning (FAQ scores). CONCLUSIONS Among those with DLB, informant-rated daily cognitive fluctuations and cognitive fluctuations measured in the clinic (as indexed by intraindividual variability-dispersion across a battery of tests) were independently associated with poorer everyday functioning. These data demonstrate ecological validity in measures of cognitive fluctuations in DLB.
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Affiliation(s)
- Troy A. Webber
- Mental Health Care Line, Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Department of Psychiatry/Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Sara A. Lorkiewicz
- Mental Health Care Line, Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | | | - Steven P. Woods
- Department of Psychology, University of Houston, Houston, TX, USA
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11
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Tappen R, Newman D, Rosselli M, Jang J, Furht B, Yang K, Ghoreishi SGA, Zhai J, Conniff J, Jan MT, Moshfeghi S, Panday S, Jackson K, Adonis-Rizzo M. Study protocol for "In-vehicle sensors to detect changes in cognition of older drivers". BMC Geriatr 2023; 23:854. [PMID: 38097931 PMCID: PMC10720160 DOI: 10.1186/s12877-023-04550-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 11/30/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Driving is a complex behavior that may be affected by early changes in the cognition of older individuals. Early changes in driving behavior may include driving more slowly, making fewer and shorter trips, and errors related to inadequate anticipation of situations. Sensor systems installed in older drivers' vehicles may detect these changes and may generate early warnings of possible changes in cognition. METHOD A naturalistic longitudinal design is employed to obtain continuous information on driving behavior that will be compared with the results of extensive cognitive testing conducted every 3 months for 3 years. A driver facing camera, forward facing camera, and telematics unit are installed in the vehicle and data downloaded every 3 months when the cognitive tests are administered. RESULTS Data processing and analysis will proceed through a series of steps including data normalization, adding information on external factors (weather, traffic conditions), and identifying critical features (variables). Traditional prediction modeling results will be compared with Recurring Neural Network (RNN) approach to produce Driver Behavior Indices (DBIs), and algorithms to classify drivers within age, gender, ethnic group membership, and other potential group characteristics. CONCLUSION It is well established that individuals with progressive dementias are eventually unable to drive safely, yet many remain unaware of their cognitive decrements. Current screening and evaluation services can test only a small number of individuals with cognitive concerns, missing many who need to know if they require treatment. Given the increasing number of sensors being installed in passenger vehicles and pick-up trucks and their increasing acceptability, reconfigured in-vehicle sensing systems could provide widespread, low-cost early warnings of cognitive decline to the large number of older drivers on the road in the U.S. The proposed testing and evaluation of a readily and rapidly available, unobtrusive in-vehicle sensing system could provide the first step toward future widespread, low-cost early warnings of cognitive change for this large number of older drivers in the U.S. and elsewhere.
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Affiliation(s)
- Ruth Tappen
- Christine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
| | - David Newman
- Christine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
- Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Monica Rosselli
- Department of Psychology, Florida Atlantic University, 3200 College Ave, Davie, FL, 33314, USA
| | - Jinwoo Jang
- Department of Civil, Environmental, and Geomatics Engineering, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
- I-SENSE, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Borko Furht
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - KwangSoo Yang
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Seyedeh Gol Ara Ghoreishi
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Jiannan Zhai
- I-SENSE, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Joshua Conniff
- Neuropsychology Lab, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Muhammad Tanveer Jan
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Sonia Moshfeghi
- Department of Civil, Environmental, and Geomatics Engineering, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Somi Panday
- Christine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Kelley Jackson
- Christine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Marie Adonis-Rizzo
- Christine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
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12
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Brown JA, Lee AJ, Fernhoff K, Pistone T, Pasquini L, Wise AB, Staffaroni AM, Luisa Mandelli M, Lee SE, Boxer AL, Rankin KP, Rabinovici GD, Luisa Gorno Tempini M, Rosen HJ, Kramer JH, Miller BL, Seeley WW. Functional network collapse in neurodegenerative disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.01.569654. [PMID: 38106054 PMCID: PMC10723363 DOI: 10.1101/2023.12.01.569654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Cognitive and behavioral deficits in Alzheimer's disease (AD) and frontotemporal dementia (FTD) result from brain atrophy and altered functional connectivity. However, it is unclear how atrophy relates to functional connectivity disruptions across dementia subtypes and stages. We addressed this question using structural and functional MRI from 221 patients with AD (n=82), behavioral variant FTD (n=41), corticobasal syndrome (n=27), nonfluent (n=34) and semantic (n=37) variant primary progressive aphasia, and 100 cognitively normal individuals. Using partial least squares regression, we identified three principal structure-function components. The first component showed overall atrophy correlating with primary cortical hypo-connectivity and subcortical/association cortical hyper-connectivity. Components two and three linked focal syndrome-specific atrophy to peri-lesional hypo-connectivity and distal hyper-connectivity. Structural and functional component scores predicted global and domain-specific cognitive deficits. Anatomically, functional connectivity changes reflected alterations in specific brain activity gradients. Eigenmode analysis identified temporal phase and amplitude collapse as an explanation for atrophy-driven functional connectivity changes.
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Affiliation(s)
- Jesse A. Brown
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Alex J. Lee
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Kristen Fernhoff
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Taylor Pistone
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Lorenzo Pasquini
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Amy B. Wise
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Adam M. Staffaroni
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Maria Luisa Mandelli
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Suzee E. Lee
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Adam L. Boxer
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Katherine P. Rankin
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Gil D. Rabinovici
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Maria Luisa Gorno Tempini
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Howard J. Rosen
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Joel H. Kramer
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Bruce L. Miller
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
| | - William W. Seeley
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, San Francisco, CA, USA
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13
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Bufacchi RJ, Battaglia-Mayer A, Iannetti GD, Caminiti R. Cortico-spinal modularity in the parieto-frontal system: A new perspective on action control. Prog Neurobiol 2023; 231:102537. [PMID: 37832714 DOI: 10.1016/j.pneurobio.2023.102537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 08/22/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023]
Abstract
Classical neurophysiology suggests that the motor cortex (MI) has a unique role in action control. In contrast, this review presents evidence for multiple parieto-frontal spinal command modules that can bypass MI. Five observations support this modular perspective: (i) the statistics of cortical connectivity demonstrate functionally-related clusters of cortical areas, defining functional modules in the premotor, cingulate, and parietal cortices; (ii) different corticospinal pathways originate from the above areas, each with a distinct range of conduction velocities; (iii) the activation time of each module varies depending on task, and different modules can be activated simultaneously; (iv) a modular architecture with direct motor output is faster and less metabolically expensive than an architecture that relies on MI, given the slow connections between MI and other cortical areas; (v) lesions of the areas composing parieto-frontal modules have different effects from lesions of MI. Here we provide examples of six cortico-spinal modules and functions they subserve: module 1) arm reaching, tool use and object construction; module 2) spatial navigation and locomotion; module 3) grasping and observation of hand and mouth actions; module 4) action initiation, motor sequences, time encoding; module 5) conditional motor association and learning, action plan switching and action inhibition; module 6) planning defensive actions. These modules can serve as a library of tools to be recombined when faced with novel tasks, and MI might serve as a recombinatory hub. In conclusion, the availability of locally-stored information and multiple outflow paths supports the physiological plausibility of the proposed modular perspective.
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Affiliation(s)
- R J Bufacchi
- Neuroscience and Behaviour Laboratory, Istituto Italiano di Tecnologia, Rome, Italy; International Center for Primate Brain Research (ICPBR), Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Sciences (CAS), Shanghai, China
| | - A Battaglia-Mayer
- Department of Physiology and Pharmacology, University of Rome, Sapienza, Italy
| | - G D Iannetti
- Neuroscience and Behaviour Laboratory, Istituto Italiano di Tecnologia, Rome, Italy; Department of Neuroscience, Physiology and Pharmacology, University College London (UCL), London, UK
| | - R Caminiti
- Neuroscience and Behaviour Laboratory, Istituto Italiano di Tecnologia, Rome, Italy.
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14
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Chumin EJ, Cutts SA, Risacher SL, Apostolova LG, Farlow MR, McDonald BC, Wu YC, Betzel R, Saykin AJ, Sporns O. Edge Time Series Components of Functional Connectivity and Cognitive Function in Alzheimer's Disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.13.23289936. [PMID: 38014005 PMCID: PMC10680898 DOI: 10.1101/2023.05.13.23289936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.
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Affiliation(s)
- Evgeny J. Chumin
- Department of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
| | - Sarah A. Cutts
- Department of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States
- Program in Neuroscience, IU, Bloomington, IN, United States
| | - Shannon L. Risacher
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
| | - Liana G. Apostolova
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
- Department of Neurology, IUSM, Indianapolis, IN, United States
| | - Martin R. Farlow
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Neurology, IUSM, Indianapolis, IN, United States
| | - Brenna C. McDonald
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
- Department of Neurology, IUSM, Indianapolis, IN, United States
| | - Yu-Chien Wu
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
| | - Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Program in Neuroscience, IU, Bloomington, IN, United States
| | - Andrew J. Saykin
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
- Department of Neurology, IUSM, Indianapolis, IN, United States
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Program in Neuroscience, IU, Bloomington, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
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15
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Hammers DB, Nemes S, Diedrich T, Eloyan A, Kirby K, Aisen P, Kramer J, Nudelman K, Foroud T, Rumbaugh M, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu JC, Mendez MF, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha SJ, Turner RS, Weintraub S, Wingo TS, Wolk DA, Wong B, Carrillo MC, Dickerson BC, Rabinovici GD, Apostolova LG. Learning slopes in early-onset Alzheimer's disease. Alzheimers Dement 2023; 19 Suppl 9:S19-S28. [PMID: 37243937 PMCID: PMC10806757 DOI: 10.1002/alz.13159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/16/2023] [Accepted: 02/16/2023] [Indexed: 05/29/2023]
Abstract
OBJECTIVE Investigation of learning slopes in early-onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early-onset dementia with and without β-amyloid positivity METHOD: Data from 310 participants in the Longitudinal Early-Onset Alzheimer's Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determined RESULTS: Worse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric-the learning ratio (LR)-outperformed other learning slope calculations across analyses CONCLUSIONS: Learning slopes appear to be sensitive to early-onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses. HIGHLIGHTS Learning is impaired in amyloid-positive EOAD, beyond cognitive severity scores alone. Amyloid-positive EOAD participants perform worse on learning slopes than amyloid-negative participants. Learning ratio appears to be the learning metric of choice for EOAD participants.
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Affiliation(s)
- Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Sára Nemes
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Taylor Diedrich
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Joel Kramer
- Department of Neurology, University of California, San Francisco, California, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S. Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph C. Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Steve Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon J. Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | | | - Sandra Weintraub
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Thomas S. Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Bonnie Wong
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Maria C. Carrillo
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA
| | - Bradford C. Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gil D. Rabinovici
- Department of Neurology, University of California, San Francisco, California, USA
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
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16
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Kiselica AM, Johnson E, Lewis KR, Trout K. Examining racial disparities in the diagnosis of mild cognitive impairment. APPLIED NEUROPSYCHOLOGY. ADULT 2023; 30:749-756. [PMID: 34554020 PMCID: PMC8940745 DOI: 10.1080/23279095.2021.1976778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Black individuals are less likely to receive an accurate diagnosis of mild cognitive impairment (MCI) than their White counterparts, possibly because diagnoses are typically made by a physician, often without reference to objective neuropsychological test data. We examined racial differences in actuarial MCI diagnoses among individuals diagnosed with MCI via semi-structured clinical interview (the Clinical Dementia Rating) to examine for possible biases in the diagnostic process. Participants were drawn from the National Alzheimer's Coordinating Center Uniform Data Set and included 491 individuals self-identifying as Black and 2,818 individuals self-identifying as White. Chi-square tests were used to examine racial differences in rates of low scores for each cognitive test (domains assessed included attention, processing speed/executive functioning, memory, language, and visual skills). Next, we tested for racial differences in probability of meeting actuarial criteria for MCI by race. Compared to Black participants diagnosed with MCI via clinical interview, White individuals diagnosed with MCI via clinical interview demonstrated significantly higher rates of low demographically-adjusted z-scores on tests of memory, attention, processing speed, and verbal fluency. Furthermore, White individuals were significantly more likely to meet actuarial criteria for MCI (71.60%) than Black individuals (57.90%). Results suggest there may be bias in MCI classification based on semi-structured interview, leading to over diagnosis among Black individuals and/or under diagnosis among White individuals. Examination of neuropsychological test data and use of actuarial approaches may reduce racial disparities in the diagnosis of MCI. Nonetheless, issues related to race-based norming and differential symptom presentations complicate interpretation of results.
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Affiliation(s)
- Andrew M. Kiselica
- Department of Health Psychology, University of Missouri, Columbia, MO, USA
| | - Ellen Johnson
- Department of Health Psychology, University of Missouri, Columbia, MO, USA
- Department of Psychology, Ohio University, Athens, OH, USA
| | - Kaleea R. Lewis
- Department of Public Health, University of Missouri, Columbia, MO, USA
- Department of Women’s and Gender Studies, University of Missouri, Columbia, MO, USA
| | - Kate Trout
- Department of Health Sciences, University of Missouri, Columbia, MO, USA
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17
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Bushnell J, Hammers DB, Aisen P, Dage JL, Eloyan A, Foroud T, Grinberg LT, Iaccarino L, Jack CR, Kirby K, Kramer J, Koeppe R, Kukull WA, La Joie R, Mundada NS, Murray ME, Nudelman K, Rumbaugh M, Soleimani-Meigooni DN, Toga A, Touroutoglou A, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu J, Mendez M, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Carrillo MC, Dickerson BC, Rabinovici GD, Apostolova LG, Clark DG. Influence of amyloid and diagnostic syndrome on non-traditional memory scores in early-onset Alzheimer's disease. Alzheimers Dement 2023; 19 Suppl 9:S29-S41. [PMID: 37653686 PMCID: PMC10855009 DOI: 10.1002/alz.13434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 06/27/2023] [Accepted: 06/28/2023] [Indexed: 09/02/2023]
Abstract
INTRODUCTION The Rey Auditory Verbal Learning Test (RAVLT) is a useful neuropsychological test for describing episodic memory impairment in dementia. However, there is limited research on its utility in early-onset Alzheimer's disease (EOAD). We assess the influence of amyloid and diagnostic syndrome on several memory scores in EOAD. METHODS We transcribed RAVLT recordings from 303 subjects in the Longitudinal Early-Onset Alzheimer's Disease Study. Subjects were grouped by amyloid status and syndrome. Primacy, recency, J-curve, duration, stopping time, and speed score were calculated and entered into linear mixed effects models as dependent variables. RESULTS Compared with amyloid negative subjects, positive subjects exhibited effects on raw score, primacy, recency, and stopping time. Inter-syndromic differences were noted with raw score, primacy, recency, J-curve, and stopping time. DISCUSSION RAVLT measures are sensitive to the effects of amyloid and syndrome in EOAD. Future work is needed to quantify the predictive value of these scores. HIGHLIGHTS RAVLT patterns characterize various presentations of EOAD and EOnonAD Amyloid impacts raw score, primacy, recency, and stopping time Timing-based scores add value over traditional count-based scores.
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Affiliation(s)
- Justin Bushnell
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Jeffrey L. Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Lea T. Grinberg
- Department of Pathology, University of California – San Francisco, San Francisco, California, USA
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Leonardo Iaccarino
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | | | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Joel Kramer
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Renaud La Joie
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Nidhi S. Mundada
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | | | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | - Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S. Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U. Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Steven Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | - Raymond S. Turner
- Department of Neurology, Georgetown University, Washington D.C., USA
| | - Thomas S. Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Maria C. Carrillo
- Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, Illinois, USA
| | - Bradford C. Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gil D. Rabinovici
- Department of Neurology, University of California – San Francisco, San Francisco, California, USA
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - David G. Clark
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
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18
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Andruchow D, Cunningham D, Sharma MJ, Ismail Z, Callahan BL. Characterizing mild cognitive impairment to predict incident dementia in adults with bipolar disorder: What should the benchmark be? Clin Neuropsychol 2023; 37:1455-1478. [PMID: 36308307 PMCID: PMC11128134 DOI: 10.1080/13854046.2022.2135605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 10/07/2022] [Indexed: 11/03/2022]
Abstract
Objective: Although mild cognitive impairment (MCI) is generally considered a risk state for dementia, its prevalence and association with dementia are impacted by the number of tests and cut-points used to assess cognition and define "impairment," and sources of norms. Here, we investigate how these methodological variations impact estimates of incident dementia in adults with bipolar disorder (BD), a vulnerable population with pre-existing cognitive deficits and increased dementia risk. Method: Neuropsychological data from 148 adults with BD and 13,610 healthy controls (HC) were drawn from the National Alzheimer's Coordinating Center. BD participants' scores were standardized against published norms and again using regression-based norms generated from HC within the same catchment area as individual BD patients ("site-specific norms"), varying the number of within-domain tests (one vs. two) and the cut-points (-1 vs. -1.5 SD) used to operationalize MCI. Results: Site-specific norms were more sensitive to incident dementia (88.6%-94.3%) than published norms (74.3%-88.6%), but only when using a "single test" definition of impairment. Specificity (22.1%-74.3%), accuracy (37.8%-68.9%), and positive predictive values (26.1%-38.3%) were overall poor. Applying a "single test" definition of impairment resulted in better negative predictive values using site-specific (92.3%-93.3%) than published norms (83.6%-86.2%), and a substantial increase in relative risk of incident dementia relative to published norms. Conclusions: Neuropsychologists should define "impairment" as scores below -1.0 or -1.5 SD on at least two within-domain measures when using published norms to interpret cognitive performance in adults with BD.
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Affiliation(s)
- Daniel Andruchow
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Daniel Cunningham
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Manu J. Sharma
- Department of Psychology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Calgary, AB, Canada
| | - Zahinoor Ismail
- Hotchkiss Brain Institute, Calgary, AB, Canada
- Departments of Psychiatry, Clinical Neurosciences, and Community Health Sciences, University of Calgary, Calgary, AB, Canada
| | - Brandy L. Callahan
- Department of Psychology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Calgary, AB, Canada
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19
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Marquine MJ, Parks A, Perales-Puchalt J, González DA, Rosado-Bruno M, North R, Pieper C, Werry AE, Kiselica A, Chapman S, Dodge H, Gauthreaux K, Kukull WA, Rascovsky K. Demographically-adjusted normative data among Latinos for the version 3 of the Alzheimer's Disease Centers' Neuropsychological Test Battery in the Uniform Data Set. Alzheimers Dement 2023; 19:4174-4186. [PMID: 37356069 PMCID: PMC10622863 DOI: 10.1002/alz.13313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 05/05/2023] [Accepted: 05/08/2023] [Indexed: 06/27/2023]
Abstract
INTRODUCTION We developed demographically-adjusted normative data for Spanish- and English-speaking Latinos on the Version 3.0 of the National Alzheimer's Coordinating Center Uniform Data Set Neuropsychological Battery (UDS3-NB). METHODS Healthy Latino adults (N = 437) age 50-94 (191 Spanish- and 246 English-speaking) enrolled in Alzheimer's Disease Research Centers completed the UDS3-NB in their preferred language. Normative data were developed via multiple linear regression models on UDS3-NB raw scores stratified by language group with terms for demographic characteristics (age, years of formal education, and sex). RESULTS Younger age and more years of education were associated with better performance on most tests in both language groups, with education being particularly influential on raw scores among Spanish-speakers. Sex effects varied across tests and language groups. DISCUSSION These normative data are a crucial step toward improving diagnostic accuracy of the UDS3-NB for neurocognitive disorders among Latinos in the United States and addressing disparities in Alzheimer's disease and related dementias. HIGHLIGHTS We developed normative data on the UDS3-NB for Latinos in the US ages 50-94. Younger age and more years of education were linked to better raw scores in several cognitive tests. Education was particularly influential on raw scores among Spanish-speakers. Sex effects varied across tests and between English- and Spanish-speaking Latinos. These normative data might improve diagnostic accuracy of the UDS3-NB among Latinos.
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Affiliation(s)
- María J Marquine
- Department of Medicine (Geriatrics Division) and Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina, USA
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, North Carolina, USA
| | - Adam Parks
- Department of Neurology, University of Kansas Medical Center, Fairway, Kansas, USA
| | | | - David A González
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Mónica Rosado-Bruno
- Department of Health Psychology, University of Missouri, Columbia, Missouri, USA
| | - Rebecca North
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, North Carolina, USA
| | - Carl Pieper
- Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, North Carolina, USA
| | - Amy E Werry
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Andrew Kiselica
- Department of Health Psychology, University of Missouri, Columbia, Missouri, USA
| | - Silvia Chapman
- Cognitive Neuroscience Division, Taub Institute for Research on Alzheimer's Disease and Gertrude H. Sergievsky Center, Columbia University, New York, New York, USA
| | - Hiroko Dodge
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Kathryn Gauthreaux
- Department of Epidemiology, National Alzheimer's Coordinating Center, University of Washington, Seattle, Washington, USA
| | - Walter A Kukull
- Department of Epidemiology, National Alzheimer's Coordinating Center, University of Washington, Seattle, Washington, USA
| | - Katya Rascovsky
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, Pennsylvania, USA
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20
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Jiang Z, Seyedi S, Vickers KL, Manzanares CM, Lah JJ, Levey AI, Clifford GD. Disentangling visual exploration differences in cognitive impairment. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.17.23290054. [PMID: 37292683 PMCID: PMC10246124 DOI: 10.1101/2023.05.17.23290054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Objective Compared to individuals without cognitive impairment (CI), those with CI exhibit differences in both basic oculomotor functions and complex viewing behaviors. However, the characteristics of the differences and how those differences relate to various cognitive functions have not been widely explored. In this work we aimed to quantify those differences and assess general cognitive impairment and specific cognitive functions. Methods A validated passive viewing memory test with eyetracking was administered to 348 healthy controls and CI individuals. Spatial, temporal, semantic, and other composite features were extracted from the estimated eye-gaze locations on the corresponding pictures displayed during the test. These features were then used to characterize viewing patterns, classify cognitive impairment, and estimate scores in various neuropsychological tests using machine learning. Results Statistically significant differences in spatial, spatiotemporal, and semantic features were found between healthy controls and individuals with CI. CI group spent more time gazing at the center of the image, looked at more regions of interest (ROI), transitioned less often between ROI yet in a more unpredictable manner, and had different semantic preferences. A combination of these features achieved an area under the receiver-operator curve of 0.78 in differentiating CI individuals from controls. Statistically significant correlations were identified between actual and estimated MoCA scores and other neuropsychological tests. Conclusion Evaluating visual exploration behaviors provided quantitative and systematic evidence of differences in CI individuals, leading to an improved approach for passive cognitive impairment screening. Significance The proposed passive, accessible, and scalable approach could help with earlier detection and a better understanding of cognitive impairment.
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21
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Saari TT, Vuoksimaa E. The role of hand preference in cognition and neuropsychiatric symptoms in neurodegenerative diseases. Brain Commun 2023; 5:fcad137. [PMID: 37265598 PMCID: PMC10231800 DOI: 10.1093/braincomms/fcad137] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/09/2023] [Accepted: 04/21/2023] [Indexed: 06/03/2023] Open
Abstract
Handedness has been shown to be associated with genetic variation involving brain development and neuropsychiatric diseases. Whether handedness plays a role in clinical phenotypes of common neurodegenerative diseases has not been extensively studied. This study used the National Alzheimer's Coordinating Center database to examine whether self-reported handedness was associated with neuropsychological performance and neuropsychiatric symptoms in cognitively unimpaired individuals (n = 17 670), individuals with Alzheimer's disease (n = 10 709), behavioural variant frontotemporal dementia (n = 1132) or dementia with Lewy bodies (n = 637). Of the sample, 8% were left-handed, and 2% were ambidextrous. There were small differences in the handedness distributions across the cognitively unimpaired, Alzheimer's disease, behavioural variant frontotemporal dementia and dementia with Lewy bodies groups (7.2-9.5% left-handed and 0.9-2.2% ambidextrous). After adjusting for age, gender and education, we found faster performance in Trail Making Test A in cognitively unimpaired non-right-handers (ambidextrous and left-handed) compared with right-handers. Excluding ambidextrous individuals, the left-handed cognitively unimpaired individuals had faster Trail Making Test A performance and better Number Span Forward performance than right-handers. Overall, handedness had no effects on most neuropsychological tests and none on neuropsychiatric symptoms. Handedness effect on Trail Making Test A in the cognitively unimpaired is likely to stem from test artefacts rather than a robust difference in cognitive performance. In conclusion, handedness does not appear to affect neuropsychological performance or neuropsychiatric symptoms in common neurodegenerative diseases.
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Affiliation(s)
- Toni T Saari
- Brain Research Unit, Department of Neurology, University of Eastern Finland, Kuopio 70210, Finland
- Department of Neurology, NeuroCenter, Kuopio University Hospital, Kuopio 70210, Finland
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki 00290, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki 00290, Finland
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22
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Ratcliffe LN, McDonald T, Robinson B, Sass JR, Loring DW, Hewitt KC. Classification statistics of the Montreal Cognitive Assessment (MoCA): Are we interpreting the MoCA correctly? Clin Neuropsychol 2023; 37:562-576. [PMID: 35699222 PMCID: PMC10351673 DOI: 10.1080/13854046.2022.2086487] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 06/01/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE The Montreal Cognitive Assessment (MoCA) is a common cognitive screener for detecting mild cognitive impairment (MCI). However, previously suggested cutoff scores of 26/30 and above is often criticized and lacks racial diversity. The purpose of this study is to investigate the potential influence of race on MoCA classification cutoff score accuracy. METHOD Data were obtained from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set and yielded 4,758 total participants. Participants were predominately White (82.8%) and female (61.7%) with a mean age of 69.3 years (SD = 10.3) and education level of 16.3 years (SD = 2.6). Based on NACC's classification, participants were either cognitively normal (n = 3,650) or MCI (n = 1,108). RESULTS Sensitivity and specificity analyses revealed that when using the cutoff score of ≤26/30, the MoCA correctly classified 73.2% of White cognitively normal participants and 83.1% of White MCI participants. In contrast, this criterion correctly classified 40.5% of Black cognitively normal participants and 90.8% of Black MCI participants. Our sample was highly educated; therefore, we did not observe significant differences in scores when accounting for education across race. Classification statistics are presented. CONCLUSIONS Black participants were misclassified at a higher rate than White participants when applying the ≤26/30 cutoff score. We suggest cutoff scores of ≤25/30 be applied to White persons and ≤22/30 for Black persons. These findings highlight the need for racially stratified population-based norms given the high misclassification of Black participants without such adjustment.
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Affiliation(s)
- Lauren N. Ratcliffe
- Department of Clinical Psychology, Mercer University College of Health Professions, Atlanta, GA, USA
| | - Taylor McDonald
- Department of Clinical Psychology, Mercer University College of Health Professions, Atlanta, GA, USA
| | - Brittany Robinson
- Department of Clinical Psychology, Mercer University College of Health Professions, Atlanta, GA, USA
| | - John R. Sass
- Cognitive Rehabilitation of Georgia, Atlanta, GA, USA
- Restore Health Group, Atlanta, GA, USA
| | - David W. Loring
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Kelsey C. Hewitt
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
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23
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Mahoney JR, Blumen HM, De Sanctis P, Fleysher R, Frankini C, Hoang A, Hoptman MJ, Jin R, Lipton M, Nunez V, Twizer L, Uy N, Valdivia A, Verghese T, Wang C, Weiss EF, Zwerling J, Verghese J. Visual-somatosensory integration (VSI) as a novel marker of Alzheimer’s disease: A comprehensive overview of the VSI study. Front Aging Neurosci 2023; 15:1125114. [PMID: 37065459 PMCID: PMC10098130 DOI: 10.3389/fnagi.2023.1125114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/03/2023] [Indexed: 03/31/2023] Open
Abstract
Identification of novel, non-invasive, non-cognitive based markers of Alzheimer’s disease (AD) and related dementias are a global priority. Growing evidence suggests that Alzheimer’s pathology manifests in sensory association areas well before appearing in neural regions involved in higher-order cognitive functions, such as memory. Previous investigations have not comprehensively examined the interplay of sensory, cognitive, and motor dysfunction with relation to AD progression. The ability to successfully integrate multisensory information across multiple sensory modalities is a vital aspect of everyday functioning and mobility. Our research suggests that multisensory integration, specifically visual-somatosensory integration (VSI), could be used as a novel marker for preclinical AD given previously reported associations with important motor (balance, gait, and falls) and cognitive (attention) outcomes in aging. While the adverse effect of dementia and cognitive impairment on the relationship between multisensory functioning and motor outcomes has been highlighted, the underlying functional and neuroanatomical networks are still unknown. In what follows we detail the protocol for our study, named The VSI Study, which is strategically designed to determine whether preclinical AD is associated with neural disruptions in subcortical and cortical areas that concurrently modulate multisensory, cognitive, and motor functions resulting in mobility decline. In this longitudinal observational study, a total of 208 community-dwelling older adults with and without preclinical AD will be recruited and monitored yearly. Our experimental design affords assessment of multisensory integration as a new behavioral marker for preclinical AD; identification of functional neural networks involved in the intersection of sensory, motor, and cognitive functioning; and determination of the impact of early AD on future mobility declines, including incident falls. Results of The VSI Study will guide future development of innovative multisensory-based interventions aimed at preventing disability and optimizing independence in pathological aging.
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Affiliation(s)
- Jeannette R. Mahoney
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
- *Correspondence: Jeannette R. Mahoney,
| | - Helena M. Blumen
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
- Department of Medicine, Division of Geriatrics, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Pierfilippo De Sanctis
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Roman Fleysher
- Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Carolina Frankini
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Alexandria Hoang
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Matthew J. Hoptman
- Division of Clinical Research, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, United States
| | - Runqiu Jin
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Michael Lipton
- Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, NY, United States
- Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
- The Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, United States
- Department of Psychiatry and Behavioral Sciences, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Valerie Nunez
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Lital Twizer
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Naomi Uy
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Ana Valdivia
- Department of Radiology, Division of Nuclear Medicine, Montefiore Medical Center, Bronx, NY, United States
| | - Tanya Verghese
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Cuiling Wang
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Erica F. Weiss
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
- Center of Aging Brain, Montefiore Medical Center, Yonkers, NY, United States
| | - Jessica Zwerling
- Center of Aging Brain, Montefiore Medical Center, Yonkers, NY, United States
| | - Joe Verghese
- Department of Neurology, Division of Cognitive and Motor Aging, Albert Einstein College of Medicine, Bronx, NY, United States
- Department of Medicine, Division of Geriatrics, Albert Einstein College of Medicine, Bronx, NY, United States
- Center of Aging Brain, Montefiore Medical Center, Yonkers, NY, United States
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24
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Jiskoot LC, Russell LL, Peakman G, Convery RS, Greaves CV, Bocchetta M, Poos JM, Seelaar H, Giannini LAA, van Swieten JC, van Minkelen R, Pijnenburg YAL, Rowe JB, Borroni B, Galimberti D, Masellis M, Tartaglia C, Finger E, Butler CR, Graff C, Laforce R, Sanchez-Valle R, de Mendonça A, Moreno F, Synofzik M, Vandenberghe R, Ducharme S, le Ber I, Levin J, Otto M, Pasquier F, Santana I, Cash DM, Thomas D, Rohrer JD. The Benson Complex Figure Test detects deficits in visuoconstruction and visual memory in symptomatic familial frontotemporal dementia: A GENFI study. J Neurol Sci 2023; 446:120590. [PMID: 36812822 DOI: 10.1016/j.jns.2023.120590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 01/24/2023] [Accepted: 02/13/2023] [Indexed: 02/17/2023]
Abstract
OBJECTIVE Sensitive cognitive markers are still needed for frontotemporal dementia (FTD). The Benson Complex Figure Test (BCFT) is an interesting candidate test, as it assesses visuospatial, visual memory, and executive abilities, allowing the detection of multiple mechanisms of cognitive impairment. To investigate differences in BCFT Copy, Recall and Recognition in presymptomatic and symptomatic FTD mutation carriers, and to explore its cognitive and neuroimaging correlates. METHOD We included cross-sectional data from 332 presymptomatic and 136 symptomatic mutation carriers (GRN, MAPT or C9orf72 mutations), and 290 controls in the GENFI consortium. We examined gene-specific differences between mutation carriers (stratified by CDR® NACC-FTLD score) and controls using Quade's / Pearson Χ2 tests. We investigated associations with neuropsychological test scores and grey matter volume using partial correlations and multiple regression models respectively. RESULTS No significant differences were found between groups at CDR® NACC-FTLD 0-0.5. Symptomatic GRN and C9orf72 mutation carriers had lower Copy scores at CDR® NACC-FTLD ≥2. All three groups had lower Recall scores at CDR® NACC-FTLD ≥2, with MAPT mutation carriers starting at CDR® NACC-FTLD ≥1. All three groups had lower Recognition scores at CDR® NACC FTLD ≥2. Performance correlated with tests for visuoconstruction, memory, and executive function. Copy scores correlated with frontal-subcortical grey matter atrophy, while Recall scores correlated with temporal lobe atrophy. CONCLUSIONS In the symptomatic stage, the BCFT identifies differential mechanisms of cognitive impairment depending on the genetic mutation, corroborated by gene-specific cognitive and neuroimaging correlates. Our findings suggest that impaired performance on the BCFT occurs relatively late in the genetic FTD disease process. Therefore its potential as cognitive biomarker for upcoming clinical trials in presymptomatic to early-stage FTD is most likely limited.
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Affiliation(s)
- Lize C Jiskoot
- Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands; Dementia Research Centre, University College London, London, UK.
| | - Lucy L Russell
- Dementia Research Centre, University College London, London, UK.
| | - Georgia Peakman
- Dementia Research Centre, University College London, London, UK.
| | - Rhian S Convery
- Dementia Research Centre, University College London, London, UK.
| | | | | | - Jackie M Poos
- Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands.
| | - Harro Seelaar
- Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands.
| | - Lucia A A Giannini
- Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands.
| | - John C van Swieten
- Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands.
| | - Rick van Minkelen
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, the Netherlands.
| | - Yolande A L Pijnenburg
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands.
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Daniela Galimberti
- University of Milan, Centro Dino Ferrari, Milan, Italy; Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Neurodegenerative Diseases Unit, Milan, Italy.
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada.
| | - Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada..
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada.
| | - Chris R Butler
- Department of Clinical Neurology, University of Oxford, Oxford, UK.
| | - Caroline Graff
- Department of Geriatric Medicine, Karolinska University Hospital-Huddinge, Stockholm, Sweden..
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, Université Laval, Québec, Canada.
| | - Raquel Sanchez-Valle
- Alzheimer's disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain.
| | | | - Fermin Moreno
- Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany; German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium.
| | - Simon Ducharme
- Department of Psychiatry, McGill University Health Centre, McGill University, Montreal, Québec, Canada.
| | - Isabelle le Ber
- Paris Brain Institute - Institut du Cerveau - Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, France; Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, Hôpital Pitié-Salpêtrière, Paris, France; Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany.
| | - Florence Pasquier
- University of Lille, Lille, France; Inserm, 1172 Lille, France; CHU, CNR-MAJ, Labex Distalz, LiCEND, Lille, France.
| | - Isabel Santana
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal.
| | - David M Cash
- Dementia Research Centre, University College London, London, UK.
| | - David Thomas
- Dementia Research Centre, University College London, London, UK.
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25
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Ang LC, Yap P, Tay SY, Koay WI, Liew TM. Examining the Validity and Utility of Montreal Cognitive Assessment Domain Scores for Early Neurocognitive Disorders. J Am Med Dir Assoc 2023; 24:314-320.e2. [PMID: 36758620 PMCID: PMC10123003 DOI: 10.1016/j.jamda.2022.12.028] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/23/2022] [Accepted: 12/31/2022] [Indexed: 02/09/2023]
Abstract
OBJECTIVES Montreal Cognitive Assessment (MoCA) total scores have been widely used to identify individuals with neurocognitive disorders (NCDs), but the utility of its domain-specific scores have yet to be thoroughly interrogated. This study aimed to validate MoCA's 6 domain-specific scores (ie, Memory, Language, Attention, Executive, Visuospatial, and Orientation) with conventional neuropsychological tests and explore whether MoCA domain scores could discriminate between different etiologies in early NCDs. DESIGN Baseline data of a cohort study. SETTING AND PARTICIPANTS Study included 14,571 participants recruited from Alzheimer's Disease Centers across United States, aged ≥50 years, with global Clinical Dementia Rating of ≤1, and mean age of 71.8 ± 8.9 years. METHODS Participants completed MoCA, conventional neuropsychological tests, and underwent standardized assessments to diagnose various etiologies of NCDs. Partial correlation coefficient was used to examine construct validity between Z scores of neuropsychological tests and MoCA domain scores, whereas multinomial logistic regression examined utility of domain scores to differentiate between etiologies of early NCDs. RESULTS MoCA domain scores correlated stronger with equivalent constructs (r = 0.15-0.43, P < .001), and showed divergence from dissimilar constructs on neuropsychological tests. Participants with Alzheimer's disease were associated with greater impairment in Memory, Attention, Visuospatial, and Orientation domains (RRR = 1.13-1.55, P < .001). Participants with Lewy body disease were impaired in Attention and Visuospatial domains (RRR = 1.21-1.47, P < .001); participants with frontotemporal lobar degeneration were impaired in Language, Executive, and Orientation domains (RRR = 1.25-1.75, P < .01); and participants with Vascular disease were impaired in Attention domain (RRR = 1.14, P < .001). CONCLUSIONS AND IMPLICATIONS MoCA domain scores approximate well-established neuropsychological tests and can be valuable in discriminating different etiologies of early NCDs. Although MoCA domain scores may not fully substitute neuropsychological tests, especially in the context of diagnostic uncertainties, they can complement MoCA total scores as part of systematic evaluation of early NCDs and conserve the use of neuropsychological tests to patients who are more likely to require further assessments.
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Affiliation(s)
- Li Chang Ang
- Medicine Academic Clinical Programme, Singapore General Hospital, Singapore
| | - Philip Yap
- Geriatric Medicine, Khoo Teck Puat Hospital, Singapore; Geriatric Education and Research Institute (GERI), Singapore
| | - Sze Yan Tay
- Department of Psychology, Singapore General Hospital, Singapore
| | - Way Inn Koay
- Department of Psychology, Singapore General Hospital, Singapore
| | - Tau Ming Liew
- Department of Psychiatry, Singapore General Hospital, Singapore; SingHealth Duke-NUS Medicine Academic Clinical Programme, Duke-NUS Medical School, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
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26
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Kaser AN, Kaplan DM, Goette W, Kiselica AM. The impact of conventional versus robust norming on cognitive characterization and clinical classification of MCI and dementia. J Neuropsychol 2023; 17:108-124. [PMID: 36124357 PMCID: PMC10006397 DOI: 10.1111/jnp.12289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 07/22/2022] [Indexed: 11/30/2022]
Abstract
We examined the impact of conventional versus robust normative approaches on cognitive characterization and clinical classification of MCI versus dementia. The sample included participants from the National Alzheimer's Coordinating Center Uniform Data Set. Separate demographically adjusted z-scores for cognitive tests were derived from conventional (n = 4273) and robust (n = 602) normative groups. To assess the impact of deriving scores from a conventional versus robust normative group on cognitive characterization, we examined likelihood of having a low score on each neuropsychological test. Next, we created receiver operating characteristic (ROC) curves for the ability of normed scores derived from each normative group to differentiate between MCI (n = 3570) and dementia (n = 1564). We examined the impact of choice of normative group on classification accuracy by comparing sensitivity and specificity values and areas under the curves (AUC). Compared with using a conventional normative group, using a robust normative group resulted in a higher likelihood of low cognitive scores for individuals classified with MCI and dementia. Comparison of the classification accuracy for distinguishing MCI from dementia did not suggest a statistically significant advantage for either normative approach (Z = -0.29, p = .77; AUC = 0.86 for conventional and AUC = 0.86 for robust). In summary, these results indicate that using a robust normative group increases the likelihood of characterizing cognitive performance as low. However, there is not a clear advantage of using a robust over a conventional normative group when differentiating between MCI and dementia.
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Affiliation(s)
- Alyssa N. Kaser
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - David M. Kaplan
- Department of Economics, University of Missouri, Columbia, Missouri, USA
| | - William Goette
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Andrew M. Kiselica
- Department of Health Psychology, University of Missouri, Columbia, Missouri, USA
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27
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Breining BL, Faria AV, Tippett DC, Stockbridge MD, Meier EL, Caffo B, Hermann O, Friedman R, Meyer A, Tsapkini K, Hillis AE. Association of Regional Atrophy With Naming Decline in Primary Progressive Aphasia. Neurology 2023; 100:e582-e594. [PMID: 36319108 PMCID: PMC9946192 DOI: 10.1212/wnl.0000000000201491] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 09/14/2022] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Primary progressive aphasia (PPA) is a neurodegenerative condition that predominantly impairs language. Most investigations of how focal atrophy affects language consider 1 time point compared with healthy controls. However, true atrophy quantification requires comparing individual brains over time. In this observational cohort study, we identified areas where focal atrophy was associated with contemporaneous decline in naming in the same individuals. METHODS Cross-sectional analyses-related Boston Naming Test (BNT) performance and volume in 22 regions of interests (ROIs) at each time point using Least Absolute Shrinkage and Selection Operator (LASSO) regression. Longitudinal analysis evaluated changes in BNT performance and change in volume in the same ROIs. RESULTS Participants (N = 62; 50% female; mean age = 66.8 ± 7.4 years) with PPA completed the BNT and MRI twice (mean = 343.9 ± 209.0 days apart). In cross-sectional left inferior frontal gyrus pars opercularis, superior temporal pole, middle temporal gyrus, and inferior temporal gyrus were identified as critical for naming at all time points. Longitudinal analysis revealed that increasing atrophy in the left supramarginal gyrus and middle temporal pole predicted greater naming decline, as did female sex and longer intervals between time points. DISCUSSION Although cross-sectional analyses identified classic language areas that were consistently related to poor performance at multiple time points, it was not increasing atrophy in these areas that lead to further decline: longitudinal analysis of each person's atrophy over time instead identified nearby but distinct regions where increased atrophy was related to decreasing performance. The results demonstrate that directly examining atrophy (in each individual) over time furthers understanding of decline in PPA and reveal the importance of left supramarginal gyrus and middle temporal pole in maintaining naming when areas normally critical for language degenerate. The novel results provide insight into how the underlying disease progresses to result in the clinical decline in naming, the deficit most common among all 3 PPA variants.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Argye Elizabeth Hillis
- From the Johns Hopkins University School of Medicine (B.L.B., A.V.F., D.C.T., M.D.S., E.L.M., O.H., K.T., A.E.H.), Baltimore, MD; Johns Hopkins University (B.C.), Bloomberg School of Public Health, Baltimore, MD; and Georgetown University (R.F., A.M.), Washington, DC.
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28
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Bernstein JPK, Noland MDW, Dorociak KE, Leese MI, Lee SY, Hughes A. Executive functioning predicts discrepancies between objective and self-reported physical activity in older adults: a pilot study. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2023; 30:124-134. [PMID: 34551679 PMCID: PMC8940743 DOI: 10.1080/13825585.2021.1982857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 09/14/2021] [Indexed: 12/26/2022]
Abstract
Physical activity (PA) has been linked to cognitive functioning and mental health in older adulthood. Multiple subjective (i.e., self-report) and objective measures (e.g., pedometer) have been used to assess PA, however their agreement varies across studies. This pilot study examined cognitive predictors of the agreement between subjective and objectively measured PA. A total of 30 community-dwelling older adults completed a neuropsychological battery, as well as a measure of subjective PA and wore a wristwatch-based pedometer for 30 days to assess objective PA. Greater discrepancy between subjective and objective PA was correlated with poorer executive functioning (r = -.44, p = .02), and this remained true in regression models after controlling for age and education (b = .-54, p = .01). Older adults with lower executive functioning may be more likely to inaccurately report time spent engaging in PA. Future studies should explore whether this relationship holds in larger samples.
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Affiliation(s)
| | | | | | - Mira I Leese
- Rosalind Franklin University of Medicine and Science, Department of Psychology, North Chicago, IL
| | - Samuel Y Lee
- Minneapolis VA Healthcare System, Minneapolis, MN
- University of Minnesota, Department of Psychiatry, Minneapolis, MN
| | - Adriana Hughes
- Minneapolis VA Healthcare System, Minneapolis, MN
- University of Minnesota, Department of Psychiatry, Minneapolis, MN
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29
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Bruner E, Battaglia-Mayer A, Caminiti R. The parietal lobe evolution and the emergence of material culture in the human genus. Brain Struct Funct 2023; 228:145-167. [PMID: 35451642 DOI: 10.1007/s00429-022-02487-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/24/2022] [Indexed: 02/07/2023]
Abstract
Traditional and new disciplines converge in suggesting that the parietal lobe underwent a considerable expansion during human evolution. Through the study of endocasts and shape analysis, paleoneurology has shown an increased globularity of the braincase and bulging of the parietal region in modern humans, as compared to other human species, including Neandertals. Cortical complexity increased in both the superior and inferior parietal lobules. Emerging fields bridging archaeology and neuroscience supply further evidence of the involvement of the parietal cortex in human-specific behaviors related to visuospatial capacity, technological integration, self-awareness, numerosity, mathematical reasoning and language. Here, we complement these inferences on the parietal lobe evolution, with results from more classical neuroscience disciplines, such as behavioral neurophysiology, functional neuroimaging, and brain lesions; and apply these to define the neural substrates and the role of the parietal lobes in the emergence of functions at the core of material culture, such as tool-making, tool use and constructional abilities.
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Affiliation(s)
- Emiliano Bruner
- Centro Nacional de Investigación Sobre la Evolución Humana, Burgos, Spain
| | | | - Roberto Caminiti
- Neuroscience and Behavior Laboratory, Istituto Italiano di Tecnologia (IIT), Roma, Italy.
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30
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Funk-White M, Moore AA, McEvoy LK, Bondi MW, Bergstrom J, Kaufmann CN. Alcohol use and cognitive performance: a comparison between Greece and the United States. Aging Ment Health 2022; 26:2440-2446. [PMID: 34842012 PMCID: PMC9161584 DOI: 10.1080/13607863.2021.1998355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 10/17/2021] [Indexed: 02/01/2023]
Abstract
OBJECTIVES To examine associations between alcohol use and cognitive performance among older adults in Greece and the United States, and assess potential differences due to differing drinking practices in the two countries. METHODS Data came from Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) and National Alzheimer's Coordinating Center Uniform Dataset (NACC). We examined those aged 65-90 years at baseline who had no cognitive impairment and complete data for cognitive and alcohol use variables (N = 1110 from HELIAD; N = 2455 from NACC). We examined associations between current alcohol use and frequency of such use with cognitive performance on various cognitive tasks stratified by gender. RESULTS In NACC, use of alcohol was associated with better cognitive performance. Men drinkers performed better than non-drinkers on Trail A (standardized mean 0.07 vs. -0.24, p<.001), Trail B (0.06 vs. -0.19, p=.001), and women drinkers performed better on Trail A (0.04 vs. -0.09, p=.016), Trail B (0.04 vs. -0.10, p=.005), verbal fluency (Animals: 0.05 vs. -0.13, p<.001; Vegetables: 0.04 vs. -0.09, p=.027), and MoCA (0.03 vs. -0.08, p=.039). In HELIAD, fewer differences were seen with only women drinkers exhibiting better performance than non-drinkers on the Boston Naming Task (0.11 vs. -0.05, p=.016). In general, more frequent drinkers performed better on cognitive tasks than less frequent drinkers, although this was only statistically significant in the NACC dataset. CONCLUSION While drinking alcohol may be associated with better cognitive performance across both the US and Greece, more research is needed to assess the cultural factors that may modify this association.
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Affiliation(s)
- Makaya Funk-White
- San Diego State University/University of California San Diego, San Diego, CA, USA
| | - Alison A. Moore
- Division of Geriatrics, Gerontology and Palliative Care, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Mark W. Bondi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Jaclyn Bergstrom
- Division of Geriatrics, Gerontology and Palliative Care, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Christopher N. Kaufmann
- Division of Epidemiology and Data Science in Gerontology, Department of Aging and Geriatric Research, University of Florida College of Medicine, Gainesville, FL, USA
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Hirsch JA, Michael YL, Moore KA, Melly S, Hughes TM, Hayden K, Luchsinger JA, Jimenez MP, James P, Besser LM, Sánchez B, Diez Roux AV. Longitudinal neighbourhood determinants with cognitive health and dementia disparities: protocol of the Multi-Ethnic Study of Atherosclerosis Neighborhoods and Aging prospective cohort study. BMJ Open 2022; 12:e066971. [PMID: 36368762 PMCID: PMC9660618 DOI: 10.1136/bmjopen-2022-066971] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION The burden of Alzheimer's disease (AD) and AD-related dementias (ADRD) is increasing nationally and globally, with disproportionate impacts on lower-income, lower education and systematically marginalised older adults. Presence of inequalities in neighbourhood factors (eg, social context, physical and built environments) may affect risk of cognitive decline and be key for intervening on AD/ADRD disparities at the population level. However, existing studies are limited by a dearth of longitudinal, detailed neighbourhood measures linked to rich, prospective cohort data. Our main objective is to identify patterns of neighbourhood change related to prevalence of-and disparities in-cognitive decline and dementia. METHODS AND ANALYSES We describe the process of collecting, processing and linking extensive neighbourhood data to the Multi-Ethnic Study of Atherosclerosis (MESA), creating a 25+ years dataset. Within the MESA parent study, the MESA Neighborhoods and Aging cohort study will characterise dynamic, longitudinal neighbourhood social and built environment variables relevant to cognition for residential addresses of MESA participants. This includes administering new surveys, expanding residential address histories, calculating new measures derived from spatial data and implementing novel deep learning algorithms on street-level imagery. Applying novel statistical techniques, we will examine associations of neighbourhood environmental characteristics with cognition and clinically relevant AD/ADRD outcomes. We will investigate determinants of disparities in outcomes by socioeconomic position and race/ethnicity and assess the contribution of neighbourhood environments to these disparities. This project will provide new evidence about pathways between neighbourhood environments and cognitive outcomes, with implications for policies to support healthy ageing. ETHICS AND DISSEMINATION This project was approved by the University of Washington and Drexel University Institutional Review Boards (protocols #00009029 and #00014523, and #180900605). Data will be distributed through the MESA Coordinating Center. Findings will be disseminated in peer-reviewed scientific journals, briefs, presentations and on the participant website.
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Affiliation(s)
- Jana A Hirsch
- Urban Health Collaborative and Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, Pennsylvania, USA
| | - Yvonne L Michael
- Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, Pennsylvania, USA
| | - Kari A Moore
- Urban Health Collaborative, Drexel University, Philadelphia, Pennsylvania, USA
| | - Steven Melly
- Urban Health Collaborative, Drexel University, Philadelphia, Pennsylvania, USA
| | - Timothy M Hughes
- Department of Internal Medicine, Medical Center Boulevard, Winston-Salem, Carolina, USA
| | - Kathleen Hayden
- Department of Social Sciences and Health Policy, Bowman Gray Center for Medical Education, Winston-Salem, Carolina, USA
| | - Jose A Luchsinger
- Department of Medicine, Columbia University, New York, New York, USA
| | - Marcia P Jimenez
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Peter James
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Population Medicine, Harvard TH Chan School of Public Health, Boston, Massachusetts, USA
| | - Lilah M Besser
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Brisa Sánchez
- Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, Pennsylvania, USA
| | - Ana V Diez Roux
- Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, Pennsylvania, USA
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Webber TA, Kiselica AM, Mikula C, Woods SP. Dispersion-based cognitive intra-individual variability in dementia with Lewy bodies. Neuropsychology 2022; 36:719-729. [PMID: 36107707 PMCID: PMC9613596 DOI: 10.1037/neu0000856] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/19/2023] Open
Abstract
OBJECTIVE Cognitive fluctuations are characteristic of dementia with Lewy bodies (DLB) but challenging to measure. Dispersion-based intra-individual variability (IIV-d) captures neurocognitive performance fluctuations across a test battery and may be sensitive to cognitive fluctuations but has not been studied in DLB. METHOD We report on 5,976 participants that completed the uniform data set 3.0 neuropsychological battery (UDS3NB). IIV-d was calculated via the intra-individual standard deviation across 12 primary UDS3NB indicators. Separate models using mean USD3NB score and the Montreal cognitive assessment (MoCA) total score tested the reproducibility of the incremental value of IIV-d over-and-above global cognition. Binary logistic regressions tested whether IIV-d could classify individuals with and without clinician-rated cognitive fluctuations. Multinomial logistic regressions tested whether IIV-d could differentiate participants with DLB, participants with Alzheimer's disease (AD), and participants with healthy cognition (CH), as well as the incremental diagnostic utility of IIV-d over-and-above clinician-rated cognitive fluctuations. RESULTS IIV-d exhibited large univariate associations with clinician-rated and non-clinician-informant reported cognitive fluctuations, which persisted when adjusting for MoCA but not the full battery mean. Of diagnostic relevance, greater IIV-d was consistently associated with DLB and AD relative to CH over-and-above global cognition and clinician-rated cognitive fluctuations. Greater IIV-d was less consistently associated with an increased probability of DLB relative to AD when controlling for global cognition. CONCLUSIONS IIV-d accurately differentiates DLB from CH over-and-above global cognition and clinician-rated cognitive fluctuations. IIV-d may supplement a thorough clinical interview of cognitive fluctuations and serve as a standardized performance-based indicator of this transdiagnostic phenomenon. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
- Troy A. Webber
- Mental Health Care Line, Michael E. DeBakey VA Medical Center, Houston, Texas, United States
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine
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Stiver J, Staffaroni AM, Walters SM, You MY, Casaletto KB, Erlhoff SJ, Possin KL, Lukic S, La Joie R, Rabinovici GD, Zimmerman ME, Gorno-Tempini ML, Kramer JH. The Rapid Naming Test: Development and initial validation in typically aging adults. Clin Neuropsychol 2022; 36:1822-1843. [PMID: 33771087 PMCID: PMC8464629 DOI: 10.1080/13854046.2021.1900399] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Accepted: 03/04/2021] [Indexed: 01/27/2023]
Abstract
ObjectiveProgressive word-finding difficulty is a primary cognitive complaint among healthy older adults and a symptom of pathological aging. Classic measures of visual confrontation naming, however, show ceiling effects among healthy older adults. To address the need for a naming test that is sensitive to subtle, age-related word-finding decline, we developed the Rapid Naming Test (RNT), a computerized, one-minute, speeded visual naming test.MethodFunctionally intact older (n = 145) and younger (n = 69) adults completed the RNT. Subsets of older adults also completed neuropsychological tests, a self-report scale of functional decline, amyloid-β PET imaging, and repeat RNT administration to determine test-retest reliability.ResultsRNT scores were normally distributed and exhibited good test-retest reliability. Younger adults performed better than older adults. Within older adults, lower scores were associated with older age. Higher scores correlated with measures of language, processing speed, and episodic learning and memory. Scores were not correlated with visuospatial or working memory tests. Worse performance was related to subjective language decline, even after controlling for a classic naming test and speed. The RNT was also negatively associated with amyloid-β burden.ConclusionsThe RNT appears to be a reliable test that is sensitive to subtle, age-related word-finding decline. Convergent and divergent validity are supported by its specific associations with measures relying on visual naming processes. Ecological validity is supported by its relationship with subjective real-world language difficulties. Lastly, worse performance was related to amyloid-β deposition, an Alzheimer's disease biomarker. This study represents a key step toward validating a novel, sensitive naming test in typically aging adults.
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Affiliation(s)
- Jordan Stiver
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
- Department of Psychology, Fordham University, New York, NY,
USA
| | - Adam M. Staffaroni
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | - Samantha M. Walters
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
- Department of Psychology, University of California, Los
Angeles, Los Angeles, CA, USA
| | - Michelle Y. You
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | - Kaitlin B. Casaletto
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | - Sabrina J. Erlhoff
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | - Katherine L. Possin
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | - Sladjana Lukic
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | - Gil D. Rabinovici
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | | | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
| | - Joel H. Kramer
- Memory and Aging Center, Department of Neurology, UCSF
Weill Institute for Neurosciences, University of California, San Francisco, San
Francisco, CA, USA
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Oravecz Z, Harrington KD, Hakun JG, Katz MJ, Wang C, Zhaoyang R, Sliwinski MJ. Accounting for retest effects in cognitive testing with the Bayesian double exponential model via intensive measurement burst designs. Front Aging Neurosci 2022; 14:897343. [PMID: 36225891 PMCID: PMC9549774 DOI: 10.3389/fnagi.2022.897343] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 08/23/2022] [Indexed: 11/25/2022] Open
Abstract
Monitoring early changes in cognitive performance is useful for studying cognitive aging as well as for detecting early markers of neurodegenerative diseases. Repeated evaluation of cognition via a measurement burst design can accomplish this goal. In such design participants complete brief evaluations of cognition, multiple times per day for several days, and ideally, repeat the process once or twice a year. However, long-term cognitive change in such repeated assessments can be masked by short-term within-person variability and retest learning (practice) effects. In this paper, we show how a Bayesian double exponential model can account for retest gains across measurement bursts, as well as warm-up effects within a burst, while quantifying change across bursts in peak performance. We also highlight how this approach allows for the inclusion of person-level predictors and draw intuitive inferences on cognitive change with Bayesian posterior probabilities. We use older adults’ performance on cognitive tasks of processing speed and spatial working memory to demonstrate how individual differences in peak performance and change can be related to predictors of aging such as biological age and mild cognitive impairment status.
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Affiliation(s)
- Zita Oravecz
- Department of Human Development and Family Studies, Pennsylvania State University, University Park, PA, United States
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, PA, United States
- Center for Healthy Aging, Pennsylvania State University, University Park, PA, United States
- *Correspondence: Zita Oravecz,
| | - Karra D. Harrington
- Center for Healthy Aging, Pennsylvania State University, University Park, PA, United States
| | - Jonathan G. Hakun
- Center for Healthy Aging, Pennsylvania State University, University Park, PA, United States
- Department of Neurology, Pennsylvania State University, Hershey, PA, United States
- Department of Psychology, Pennsylvania State University, University Park, PA, United States
| | - Mindy J. Katz
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Cuiling Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Ruixue Zhaoyang
- Center for Healthy Aging, Pennsylvania State University, University Park, PA, United States
| | - Martin J. Sliwinski
- Department of Human Development and Family Studies, Pennsylvania State University, University Park, PA, United States
- Center for Healthy Aging, Pennsylvania State University, University Park, PA, United States
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Bernstein JPK, Dorociak K, Mattek N, Leese M, Trapp C, Beattie Z, Kaye J, Hughes A. Unobtrusive, in-home assessment of older adults' everyday activities and health events: associations with cognitive performance over a brief observation period. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2022; 29:781-798. [PMID: 33866939 PMCID: PMC8522171 DOI: 10.1080/13825585.2021.1917503] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 04/11/2021] [Indexed: 12/22/2022]
Abstract
In-home assessment of everyday activities over many months to years may be useful in predicting cognitive decline in older adulthood. This study examined whether a comparatively brief data collection period (3 months) may yield similar diagnostic information. A total of 91 community-dwelling older adults without dementia underwent baseline neuropsychological testing and completed weekly computer-based surveys assessing health-related events/activities. A subset of participants wore fitness tracker watches assessing daily sleep and physical activity patterns, used a sensor-instrumented pillbox, and had their computer use frequency recorded on a daily basis. Similar patterns in computer use, sleep and medication use were noted in comparison to prior literature with more extensive data collection periods. Greater computer use and sleep, as well as self-reported pain and independence, were also linked to better cognition. These activities and symptoms may be useful correlates of cognitive function even when assessed over a relatively brief monitoring period.
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Affiliation(s)
| | - Katherine Dorociak
- Department of Psychology, Palo Alto VA Health Care System, Palo Alto, CA, USA
| | - Nora Mattek
- Oregon Center for Aging & Technology, Portland, OR, USA
| | - Mira Leese
- Department of Psychology, Minneapolis VA Health Care System, Minneapolis, MN, USA
| | - Chelsea Trapp
- Department of Psychology, Minneapolis VA Health Care System, Minneapolis, MN, USA
| | | | - Jeffrey Kaye
- Oregon Center for Aging & Technology, Portland, OR, USA
| | - Adriana Hughes
- Oregon Center for Aging & Technology, Portland, OR, USA
- Department of Psychology, Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
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VandeBunte A, Gontrum E, Goldberger L, Fonseca C, Djukic N, You M, Kramer JH, Casaletto KB. Physical activity measurement in older adults: Wearables versus self-report. Front Digit Health 2022; 4:869790. [PMID: 36120711 PMCID: PMC9470756 DOI: 10.3389/fdgth.2022.869790] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 08/08/2022] [Indexed: 02/02/2023] Open
Abstract
Physical activity (PA) is associated with preserved age-related body and brain health. However, PA quantification can vary. Commercial-grade wearable monitors are objective, low burden tools to capture PA but are less well validated in older adults. Self-report PA questionnaires are widely accepted and more frequently used but carry inherent limitations. We aimed to compare these commonly used PA measures against one another and examine their convergent validity with a host of relevant outcomes. We also examined the factors that drive differences in PA self-reporting styles in older adults. 179 older adults completed 30-day Fitbit Flex2™ monitoring and reported PA levels via two widely used PA questionnaires: PASE and CHAMPS-METs (metabolic expenditure calories burned). Participants also completed measures of cardiometabolic (hypertension diagnosis, resting heart rate, A1C levels), cognitive (memory, processing speed, executive functioning), and brain MRI (medial temporal lobe volume) outcomes. The discrepancy between objective Fitbit monitoring and self-reported PA was evaluated using a sample-based z difference score. There were only modest relationships across all PA metrics. Fitbit step count demonstrated a stronger association with the PASE, whereas Fitbit calories burned was more strongly associated with CHAMPS-MET. Fitbit outcomes had more consistent convergence with relevant outcomes of interest (e.g., cardiometabolic and brain health indices) when compared to subjective measures; however, considerable heterogeneity within these associations was observed. A higher degree of overreporting was associated with worse memory and executive performances, as well as hypertension diagnoses. We build on prior findings that wearable, digital health indicators of PA demonstrate greater construct validity than self-report in older adults. We further show important clinical features (e.g., poorer cognitive status) of older adults that could contribute to a higher level of overreporting on self-report measures. Characterization of what PA measures truly operationalize will help elucidate relationships between most relevant facets of PA and outcomes of interest.
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Affiliation(s)
- Anna VandeBunte
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
- Department of Psychology, Palo Alto University, Palo Alto, CA, United States
| | - Eva Gontrum
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Lauren Goldberger
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Corrina Fonseca
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Nina Djukic
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Michelle You
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Joel H. Kramer
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Kaitlin B. Casaletto
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
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Delgado-Álvarez A, Cabrera-Martín MN, Valles-Salgado M, Delgado-Alonso C, Gil MJ, Díez-Cirarda M, Matías-Guiu J, Matias-Guiu JA. Neural basis of visuospatial tests in behavioral variant frontotemporal dementia. Front Aging Neurosci 2022; 14:963751. [PMID: 36081891 PMCID: PMC9445442 DOI: 10.3389/fnagi.2022.963751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 08/02/2022] [Indexed: 11/30/2022] Open
Abstract
Background Recent models of visuospatial functioning suggest the existence of three main circuits emerging from the dorsal (“where”) route: parieto-prefrontal pathway, parieto-premotor, and parieto-medial temporal. Neural underpinnings of visuospatial task performance and the sparing of visuospatial functioning in bvFTD are unclear. We hypothesized different neural and cognitive mechanisms in visuospatial tasks performance in bvFTD and AD. Methods Two hundred and sixteen participants were enrolled for this study: 72 patients with bvFTD dementia and 144 patients with AD. Visual Object and Space Perception Battery Position Discrimination and Number Location (VOSP-PD and VOSP-NL) and Rey-Osterrieth Complex Figure (ROCF) were administered to examine visuospatial functioning, together with a comprehensive neuropsychological battery. FDG-PET was acquired to evaluate brain metabolism. Voxel-based brain mapping analyses were conducted to evaluate the brain regions associated with visuospatial function in bvFTD and AD. Results Patients with AD performed worst in visuospatial tasks in mild dementia, but not at prodromal stage. Attention and executive functioning tests showed higher correlations in bvFTD than AD with ROCF, but not VOSP subtests. Visuospatial performance in patients with bvFTD was associated with bilateral frontal regions, including the superior and medial frontal gyri, supplementary motor area, insula and middle cingulate gyrus. Conclusion These findings support the role of prefrontal and premotor regions in visuospatial processing through the connection with the posterior parietal cortex and other posterior cortical regions. Visuospatial deficits should be interpreted with caution in patients with bvFTD, and should not be regarded as hallmarks of posterior cortical dysfunction.
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Affiliation(s)
- Alfonso Delgado-Álvarez
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC), Universidad Complutense, Madrid, Spain
| | - María Nieves Cabrera-Martín
- Department of Nuclear Medicine, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC), Universidad Complutense, Madrid, Spain
- *Correspondence: María Nieves Cabrera-Martín,
| | - María Valles-Salgado
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC), Universidad Complutense, Madrid, Spain
| | - Cristina Delgado-Alonso
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC), Universidad Complutense, Madrid, Spain
| | - María José Gil
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC), Universidad Complutense, Madrid, Spain
| | - María Díez-Cirarda
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC), Universidad Complutense, Madrid, Spain
| | - Jorge Matías-Guiu
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC), Universidad Complutense, Madrid, Spain
| | - Jordi A. Matias-Guiu
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC), Universidad Complutense, Madrid, Spain
- Jordi A. Matias-Guiu, ;
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Daigle KM, Pietrzykowski MO, Waters AB, Swenson LP, Gansler DA. Central Executive Network and Executive Function in Patients With Alzheimer's Disease and Healthy Individuals: Meta-Analysis of Structural and Functional MRI. J Neuropsychiatry Clin Neurosci 2022; 34:204-213. [PMID: 35272491 DOI: 10.1176/appi.neuropsych.20110279] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
OBJECTIVE The neural architecture of executive function is of interest given its utility as a transdiagnostic predictor of adaptive functioning. However, a gap exists in the meta-analytic literature assessing this relationship in neuropsychiatric populations, concordance between structural and functional architecture, and the relationship with neuropsychological assessment of executive function. Given the importance of the central executive network (CEN) in Alzheimer's disease, this population may be useful in understanding this relationship in Alzheimer's disease pathology. METHODS A meta-analysis of studies (k=21) was conducted to elucidate the relationship between executive function and CEN for structural architecture (k=10; N=1,027) among patients with Alzheimer's disease (k=6; N=250) and healthy control subjects (HCs) (k=4; N=777) and for functional architecture (k=11; N=522) among patients with Alzheimer's disease (k=6; N=306) and HCs (k=5; N=216). Random-effects modeling was used to increase accuracy of conclusions about population means. RESULTS Analyses revealed a positive brain-behavior relationship (pr=0.032, 95% CI=0.07, 0.54), although there was a lack of statistically significant heterogeneity between functional and structural neuroimaging (Q=9.89, p=0.971, I2=0.00%) and between the Alzheimer's and HC groups in functional (Q=8.18, p=0.612, I2=0.00%) and structural (Q=1.60, p=0.996, I2=0.00%) neuroimaging. Similarly, a lack of statistically significant heterogeneity was revealed between functional and structural neuroimaging among patients with Alzheimer's disease (Q=3.59, p=0.980, I2=0.00%) and HCs (Q=3.67, p=0.885, I2=0.00%). CONCLUSIONS Structural and functional imaging in the CEN are predictive of executive function performance among patients with Alzheimer's disease and HCs. Regardless of how the CEN is affected, behavior is correlated to the degree to which the CEN is affected. Findings are significant in the context of methodological decisions in multimodal neuroimaging research.
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Affiliation(s)
- Katrina M Daigle
- Clinical Neuroscience of Cognitive Control Laboratory, Department of Psychology, Suffolk University, Boston (Daigle, Pietrzykowski, Waters, Gansler); and Department of Psychology, Suffolk University, Boston (Swenson)
| | - Malvina O Pietrzykowski
- Clinical Neuroscience of Cognitive Control Laboratory, Department of Psychology, Suffolk University, Boston (Daigle, Pietrzykowski, Waters, Gansler); and Department of Psychology, Suffolk University, Boston (Swenson)
| | - Abigail B Waters
- Clinical Neuroscience of Cognitive Control Laboratory, Department of Psychology, Suffolk University, Boston (Daigle, Pietrzykowski, Waters, Gansler); and Department of Psychology, Suffolk University, Boston (Swenson)
| | - Lance P Swenson
- Clinical Neuroscience of Cognitive Control Laboratory, Department of Psychology, Suffolk University, Boston (Daigle, Pietrzykowski, Waters, Gansler); and Department of Psychology, Suffolk University, Boston (Swenson)
| | - David A Gansler
- Clinical Neuroscience of Cognitive Control Laboratory, Department of Psychology, Suffolk University, Boston (Daigle, Pietrzykowski, Waters, Gansler); and Department of Psychology, Suffolk University, Boston (Swenson)
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Weintraub S, Karpouzian-Rogers T, Peipert JD, Nowinski C, Slotkin J, Wortman K, Ho E, Rogalski E, Carlsson C, Giordani B, Goldstein F, Lucas J, Manly JJ, Rentz D, Salmon D, Snitz B, Dodge HH, Riley M, Eldes F, Ustsinovich V, Gershon R. ARMADA: Assessing reliable measurement in Alzheimer's disease and cognitive aging project methods. Alzheimers Dement 2022; 18:1449-1460. [PMID: 34786833 PMCID: PMC9110564 DOI: 10.1002/alz.12497] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 07/26/2021] [Accepted: 09/07/2021] [Indexed: 11/07/2022]
Abstract
INTRODUCTION Early detection of cognitive decline in older adults is a public health priority. Advancing Reliable Measurement in Alzheimer's Disease and Cognitive Aging (ARMADA), a multisite study, is validating cognition, emotion, motor, and sensory modules of the National Institutes of Health Toolbox for Assessment of Neurological and Behavioral Function (NIHTB) in the aging spectrum from cognitively normal to dementia of the Alzheimer's type (DAT). METHODS Participants 65 to 85 years old, in demographic groups racially proportional to the general US population, are recruited in one of three groups to validate the NIHTB: cognitively normal, amnestic mild cognitive impairment (aMCI), or mild DAT. Additional special emphasis cohorts include (1) Blacks in the three clinical groups; (2) Spanish-speakers in the three clinical groups; (3) cognitively normal, population-proportional, over age 85. DISCUSSION Longitudinal study will determine whether NIHTB can predict cognitive decline and is associated with Alzheimer's disease biomarkers. Here, we detail the methods for the ARMADA study.
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Affiliation(s)
- Sandra Weintraub
- Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine
| | - Tatiana Karpouzian-Rogers
- Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine
| | - John Devin Peipert
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine
| | - Cindy Nowinski
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine
- Department of Neurology, Northwestern University Feinberg School of Medicine
| | - Jerry Slotkin
- Center for Health Assessment Research and Translation, University of Delaware
| | - Katy Wortman
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine
| | - Emily Ho
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine
| | - Emily Rogalski
- Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine
| | - Cynthia Carlsson
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health and Wisconsin Alzheimer’s Disease Research Center
| | | | | | - John Lucas
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL
| | - Jennifer J. Manly
- Department of Neurology, Columbia University, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University
| | - Dorene Rentz
- Departments of Neurology, Massachusetts General Hospital and Brigham and Women’s Hospital, Harvard Medical School
| | - David Salmon
- Department of Neurosciences, University of California San Diego
| | - Beth Snitz
- Department of Neurology, University of Pittsburgh
| | - Hiroko H. Dodge
- Department of Neurology, Layton Aging and Alzheimer’s disease Center, Oregon Health & Science University
| | - Michaela Riley
- Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine
| | - Fatima Eldes
- Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine
| | - Vitali Ustsinovich
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine
| | - Richard Gershon
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine
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Benge JF, Artz J, Kiselica A. The ecological validity of the Uniform Data Set 3.0 neuropsychological battery in individuals with mild cognitive impairment and dementia. Clin Neuropsychol 2022; 36:1453-1470. [PMID: 33103615 PMCID: PMC8071839 DOI: 10.1080/13854046.2020.1837246] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Objective: Ecological validity refers to the ability of neuropsychological measures to predict real world performance. Questions remain as to the ecological validity of commonly used measures, particularly regarding their relationships to global versus specific activities of daily living among those with neurodegenerative disease. We explored these issues through the lens of the Uniform Data Set 3.0 Neuropsychological battery (UDS3NB) in individuals with mild cognitive impairment and dementia. Method: UDS3NB and informant rated Functional Activities Questionnaire scales were evaluated from 2,253 individuals with mild cognitive impairment and dementia. Ordinal regression equations were used to explore the relationships of demographic and cognitive variables with overall and specific instrumental activities of daily living. Results: Delayed recall for visual and verbal material, and performance on trail making tests were consistent predictors of global and specific functions. Specific skills (i.e. naming or figure copy) showed differential relationships with specific activities, while phonemic fluency was not related to any particular activity. Conclusions: Measures in the UDS3NB predicted activities of daily living in individuals with MCI and dementia, providing initial support for the ecological validity of these tests. Specifically, measures that tap core deficits of Alzheimer's disease, such as delayed recall and sequencing/shifting, are consistent predictors of performance in daily tasks.
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Affiliation(s)
- Jared F. Benge
- Department of Neurology, Baylor Scott and White Health, Temple, TX
- Plummer Movement Disorder Center, BSWH Health, Temple, TX
- Texas A&M College of Medicine, Temple, TX
| | | | - Andrew Kiselica
- Department of Health Psychology, University of Missouri, Columbia, MO
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41
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Alty J, Bai Q, Li R, Lawler K, St George RJ, Hill E, Bindoff A, Garg S, Wang X, Huang G, Zhang K, Rudd KD, Bartlett L, Goldberg LR, Collins JM, Hinder MR, Naismith SL, Hogg DC, King AE, Vickers JC. The TAS Test project: a prospective longitudinal validation of new online motor-cognitive tests to detect preclinical Alzheimer's disease and estimate 5-year risks of cognitive decline and dementia. BMC Neurol 2022; 22:266. [PMID: 35850660 PMCID: PMC9289357 DOI: 10.1186/s12883-022-02772-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 06/27/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The worldwide prevalence of dementia is rapidly rising. Alzheimer's disease (AD), accounts for 70% of cases and has a 10-20-year preclinical period, when brain pathology covertly progresses before cognitive symptoms appear. The 2020 Lancet Commission estimates that 40% of dementia cases could be prevented by modifying lifestyle/medical risk factors. To optimise dementia prevention effectiveness, there is urgent need to identify individuals with preclinical AD for targeted risk reduction. Current preclinical AD tests are too invasive, specialist or costly for population-level assessments. We have developed a new online test, TAS Test, that assesses a range of motor-cognitive functions and has capacity to be delivered at significant scale. TAS Test combines two innovations: using hand movement analysis to detect preclinical AD, and computer-human interface technologies to enable robust 'self-testing' data collection. The aims are to validate TAS Test to [1] identify preclinical AD, and [2] predict risk of cognitive decline and AD dementia. METHODS Aim 1 will be addressed through a cross-sectional study of 500 cognitively healthy older adults, who will complete TAS Test items comprising measures of motor control, processing speed, attention, visuospatial ability, memory and language. TAS Test measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 (p-tau181). Aim 2 will be addressed through a 5-year prospective cohort study of 10,000 older adults. Participants will complete TAS Test annually and subtests of the Cambridge Neuropsychological Test Battery (CANTAB) biennially. 300 participants will undergo in-person clinical assessments. We will use machine learning of motor-cognitive performance on TAS Test to develop an algorithm that classifies preclinical AD risk (p-tau181-defined) and determine the precision to prospectively estimate 5-year risks of cognitive decline and AD. DISCUSSION This study will establish the precision of TAS Test to identify preclinical AD and estimate risk of cognitive decline and AD. If accurate, TAS Test will provide a low-cost, accessible enrichment strategy to pre-screen individuals for their likelihood of AD pathology prior to more expensive tests such as blood or imaging biomarkers. This would have wide applications in public health initiatives and clinical trials. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT05194787 , 18 January 2022. Retrospectively registered.
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Affiliation(s)
- Jane Alty
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia. .,School of Medicine, University of Tasmania, Hobart, Australia. .,Royal Hobart Hospital, Hobart, Tasmania, Australia.
| | - Quan Bai
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Renjie Li
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Katherine Lawler
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.,Royal Hobart Hospital, Hobart, Tasmania, Australia
| | - Rebecca J St George
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.,School of Psychological Sciences, University of Tasmania, Hobart, Australia
| | - Edward Hill
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Aidan Bindoff
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Saurabh Garg
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Xinyi Wang
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Guan Huang
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Kaining Zhang
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Kaylee D Rudd
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Larissa Bartlett
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Lynette R Goldberg
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Jessica M Collins
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Mark R Hinder
- School of Psychological Sciences, University of Tasmania, Hobart, Australia
| | - Sharon L Naismith
- Healthy Brain Ageing Program, University of Sydney, Sydney, Australia
| | - David C Hogg
- School of Computing, University of Leeds, Leeds, UK
| | - Anna E King
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - James C Vickers
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
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Lower White Matter Volume and Worse Executive Functioning Reflected in Higher Levels of Plasma GFAP among Older Adults with and Without Cognitive Impairment. J Int Neuropsychol Soc 2022; 28:588-599. [PMID: 34158138 PMCID: PMC8692495 DOI: 10.1017/s1355617721000813] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE There are minimal data directly comparing plasma neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) in aging and neurodegenerative disease research. We evaluated associations of plasma NfL and plasma GFAP with brain volume and cognition in two independent cohorts of older adults diagnosed as clinically normal (CN), mild cognitive impairment (MCI), or Alzheimer's dementia. METHODS We studied 121 total participants (Cohort 1: n = 50, age 71.6 ± 6.9 years, 78% CN, 22% MCI; Cohort 2: n = 71, age 72.2 ± 9.2 years, 45% CN, 25% MCI, 30% dementia). Gray and white matter volumes were obtained for total brain and broad subregions of interest (ROIs). Neuropsychological testing evaluated memory, executive functioning, language, and visuospatial abilities. Plasma samples were analyzed in duplicate for NfL and GFAP using single molecule array assays (Quanterix Simoa). Linear regression models with structural MRI and cognitive outcomes included plasma NfL and GFAP simultaneously along with relevant covariates. RESULTS Higher plasma GFAP was associated with lower white matter volume in both cohorts for temporal (Cohort 1: β = -0.33, p = .002; Cohort 2: β = -0.36, p = .03) and parietal ROIs (Cohort 1: β = -0.31, p = .01; Cohort 2: β = -0.35, p = .04). No consistent findings emerged for gray matter volumes. Higher plasma GFAP was associated with lower executive function scores (Cohort 1: β = -0.38, p = .01; Cohort 2: β = -0.36, p = .007). Plasma NfL was not associated with gray or white matter volumes, or cognition after adjusting for plasma GFAP. CONCLUSIONS Plasma GFAP may be more sensitive to white matter and cognitive changes than plasma NfL. Biomarkers reflecting astroglial pathophysiology may capture complex dynamics of aging and neurodegenerative disease.
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43
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Ryu J, Torres EB. Motor Signatures in Digitized Cognitive and Memory Tests Enhances Characterization of Parkinson's Disease. SENSORS (BASEL, SWITZERLAND) 2022; 22:4434. [PMID: 35746215 PMCID: PMC9231034 DOI: 10.3390/s22124434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 06/08/2022] [Accepted: 06/09/2022] [Indexed: 06/15/2023]
Abstract
Although interest in using wearable sensors to characterize movement disorders is growing, there is a lack of methodology for developing clinically interpretable biomarkers. Such digital biomarkers would provide a more objective diagnosis, capturing finer degrees of motor deficits, while retaining the information of traditional clinical tests. We aim at digitizing traditional tests of cognitive and memory performance to derive motor biometrics of pen-strokes and voice, thereby complementing clinical tests with objective criteria, while enhancing the overall characterization of Parkinson's disease (PD). 35 participants including patients with PD, healthy young and age-matched controls performed a series of drawing and memory tasks, while their pen movement and voice were digitized. We examined the moment-to-moment variability of time series reflecting the pen speed and voice amplitude. The stochastic signatures of the fluctuations in pen drawing speed and voice amplitude of patients with PD show a higher signal-to-noise ratio compared to those of neurotypical controls. It appears that contact motions of the pen strokes on a tablet evoke sensory feedback for more immediate and predictable control in PD, while voice amplitude loses its neurotypical richness. We offer new standardized data types and analytics to discover the hidden motor aspects within the cognitive and memory clinical assays.
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Affiliation(s)
- Jihye Ryu
- Department of Psychology, Rutgers University, New Brunswick, NJ 08854, USA;
| | - Elizabeth B. Torres
- Rutgers University Center for Cognitive Science, Computational Biomedicine Imaging and Modeling Center at Computer Science Department, Psychology Department, Rutgers University, Piscataway, NJ 08854, USA
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44
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Dahl MJ, Mather M, Werkle-Bergner M, Kennedy BL, Guzman S, Hurth K, Miller CA, Qiao Y, Shi Y, Chui HC, Ringman JM. Locus coeruleus integrity is related to tau burden and memory loss in autosomal-dominant Alzheimer's disease. Neurobiol Aging 2022; 112:39-54. [PMID: 35045380 PMCID: PMC8976827 DOI: 10.1016/j.neurobiolaging.2021.11.006] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 11/17/2021] [Accepted: 11/26/2021] [Indexed: 12/14/2022]
Abstract
Abnormally phosphorylated tau, an indicator of Alzheimer's disease, accumulates in the first decades of life in the locus coeruleus (LC), the brain's main noradrenaline supply. However, technical challenges in in-vivo assessments have impeded research into the role of the LC in Alzheimer's disease. We studied participants with or known to be at-risk for mutations in genes causing autosomal-dominant Alzheimer's disease (ADAD) with early onset, providing a unique window into the pathogenesis of Alzheimer's largely disentangled from age-related factors. Using high-resolution MRI and tau PET, we found lower rostral LC integrity in symptomatic participants. LC integrity was associated with individual differences in tau burden and memory decline. Post-mortem analyses in a separate set of carriers of the same mutation confirmed substantial neuronal loss in the LC. Our findings link LC degeneration to tau burden and memory in Alzheimer's, and highlight a role of the noradrenergic system in this neurodegenerative disease.
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Affiliation(s)
- Martin J Dahl
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
| | - Mara Mather
- Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Markus Werkle-Bergner
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Briana L Kennedy
- Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA; School of Psychological Science, University of Western Australia, Perth, Australia
| | - Samuel Guzman
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kyle Hurth
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Carol A Miller
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yuchuan Qiao
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yonggang Shi
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Helena C Chui
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John M Ringman
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Benatar M, Wuu J, McHutchison C, Postuma RB, Boeve BF, Petersen R, Ross CA, Rosen H, Arias JJ, Fradette S, McDermott MP, Shefner J, Stanislaw C, Abrahams S, Cosentino S, Andersen PM, Finkel RS, Granit V, Grignon AL, Rohrer JD, McMillan CT, Grossman M, Al-Chalabi A, Turner MR. Preventing amyotrophic lateral sclerosis: insights from pre-symptomatic neurodegenerative diseases. Brain 2022; 145:27-44. [PMID: 34677606 PMCID: PMC8967095 DOI: 10.1093/brain/awab404] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 09/16/2021] [Accepted: 10/08/2021] [Indexed: 11/12/2022] Open
Abstract
Significant progress has been made in understanding the pre-symptomatic phase of amyotrophic lateral sclerosis. While much is still unknown, advances in other neurodegenerative diseases offer valuable insights. Indeed, it is increasingly clear that the well-recognized clinical syndromes of Alzheimer's disease, Parkinson's disease, Huntington's disease, spinal muscular atrophy and frontotemporal dementia are also each preceded by a pre-symptomatic or prodromal period of varying duration, during which the underlying disease process unfolds, with associated compensatory changes and loss of inherent system redundancy. Key insights from these diseases highlight opportunities for discovery in amyotrophic lateral sclerosis. The development of biomarkers reflecting amyloid and tau has led to a shift in defining Alzheimer's disease based on inferred underlying histopathology. Parkinson's disease is unique among neurodegenerative diseases in the number and diversity of non-genetic biomarkers of pre-symptomatic disease, most notably REM sleep behaviour disorder. Huntington's disease benefits from an ability to predict the likely timing of clinically manifest disease based on age and CAG-repeat length alongside reliable neuroimaging markers of atrophy. Spinal muscular atrophy clinical trials have highlighted the transformational value of early therapeutic intervention, and studies in frontotemporal dementia illustrate the differential role of biomarkers based on genotype. Similar advances in amyotrophic lateral sclerosis would transform our understanding of key events in pathogenesis, thereby dramatically accelerating progress towards disease prevention. Deciphering the biology of pre-symptomatic amyotrophic lateral sclerosis relies on a clear conceptual framework for defining the earliest stages of disease. Clinically manifest amyotrophic lateral sclerosis may emerge abruptly, especially among those who harbour genetic mutations associated with rapidly progressive amyotrophic lateral sclerosis. However, the disease may also evolve more gradually, revealing a prodromal period of mild motor impairment preceding phenoconversion to clinically manifest disease. Similarly, cognitive and behavioural impairment, when present, may emerge gradually, evolving through a prodromal period of mild cognitive impairment or mild behavioural impairment before progression to amyotrophic lateral sclerosis. Biomarkers are critically important to studying pre-symptomatic amyotrophic lateral sclerosis and essential to efforts to intervene therapeutically before clinically manifest disease emerges. The use of non-genetic biomarkers, however, presents challenges related to counselling, informed consent, communication of results and limited protections afforded by existing legislation. Experiences from pre-symptomatic genetic testing and counselling, and the legal protections against discrimination based on genetic data, may serve as a guide. Building on what we have learned-more broadly from other pre-symptomatic neurodegenerative diseases and specifically from amyotrophic lateral sclerosis gene mutation carriers-we present a road map to early intervention, and perhaps even disease prevention, for all forms of amyotrophic lateral sclerosis.
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Affiliation(s)
- Michael Benatar
- Department of Neurology, University of Miami, Miami, FL, USA
| | - Joanne Wuu
- Department of Neurology, University of Miami, Miami, FL, USA
| | - Caroline McHutchison
- Human Cognitive Neuroscience, Department of Psychology, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, UK
| | - Ronald B Postuma
- Department of Neurology, Montreal Neurological Institute, McGill University, Montreal, Canada
| | | | | | - Christopher A Ross
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Howard Rosen
- Department of Neurology, University of California San Francisco, CA, USA
| | - Jalayne J Arias
- Department of Neurology, University of California San Francisco, CA, USA
| | | | - Michael P McDermott
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.,Department of Neurology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Jeremy Shefner
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ, USA
| | | | - Sharon Abrahams
- Human Cognitive Neuroscience, Department of Psychology, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, UK
| | | | - Peter M Andersen
- Department of Clinical Science, Neurosciences, Umeå University, Sweden
| | - Richard S Finkel
- Department of Pediatric Medicine, Center for Experimental Neurotherapeutics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Volkan Granit
- Department of Neurology, University of Miami, Miami, FL, USA
| | | | - Jonathan D Rohrer
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK
| | - Corey T McMillan
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King's College London, London, UK.,Department of Neurology, King's College Hospital, London, UK
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Tee BL, Watson Pereira C, Lukic S, Bajorek LP, Allen IE, Miller ZA, Casaletto KB, Miller BL, Gorno-Tempini ML. Neuroanatomical correlations of visuospatial processing in primary progressive aphasia. Brain Commun 2022; 4:fcac060. [PMID: 35386217 PMCID: PMC8977647 DOI: 10.1093/braincomms/fcac060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 12/10/2021] [Accepted: 03/10/2022] [Indexed: 11/14/2022] Open
Abstract
Clinical phenotyping of primary progressive aphasia has largely focused on speech and language presentations, leaving other cognitive domains under-examined. This study investigated the diagnostic utility of visuospatial profiles and examined their neural basis among the three main primary progressive aphasia variants. We studied the neuropsychological performances of 118 primary progressive aphasia participants and 30 cognitively normal controls, across 11 measures of visuospatial cognition, and investigated their neural correlates via voxel-based morphometry analysis using visuospatial composite scores derived from principal component analysis. The principal component analysis identified three main factors: visuospatial-executive, visuospatial-memory and visuomotor components. Logopenic variant primary progressive aphasia performed significantly worst across all components; nonfluent/agrammatic variant primary progressive aphasia showed deficits in the visuospatial-executive and visuomotor components compared with controls; and the semantic variant primary progressive aphasia scored significantly lower than nonfluent/agrammatic variant primary progressive aphasia and control in the visuospatial-memory component. Grey matter volumes over the right parieto-occipital cortices correlated with visuospatial-executive performance; volumetric changes in the right anterior parahippocampal gyrus and amygdala were associated with visuospatial-memory function, and visuomotor composite scores correlated significantly with the grey matter volume at the right precentral gyrus. Discriminant function analysis identified three visuospatial measures: Visual Object and Space Perception and Benson figure copy and recall test, which classified 79.7% (94/118) of primary progressive aphasia into their specific variant. This study shows that each primary progressive aphasia variant also carries a distinctive visuospatial cognitive profile that corresponds with grey matter volumetric changes and in turn can be largely represented by their performance on the visuomotor, visuospatial-memory and executive functions.
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Affiliation(s)
- Boon Lead Tee
- Memory and Aging Center, University of California at San Francisco, San Francisco, CA, USA
- Department of Neurology, Dyslexia Center, University of California, San Francisco, CA, USA
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Department of Neurology, Buddhist Tzu Chi General Hospital, Hualien, Taiwan
- Tzu Chi University, No. 701號, Section 3, Zhongyang Rd, Hualien City, Hualien County, Taiwan 970
| | - Christa Watson Pereira
- Memory and Aging Center, University of California at San Francisco, San Francisco, CA, USA
- Department of Neurology, Dyslexia Center, University of California, San Francisco, CA, USA
| | - Sladjana Lukic
- Memory and Aging Center, University of California at San Francisco, San Francisco, CA, USA
- Department of Neurology, Dyslexia Center, University of California, San Francisco, CA, USA
| | - Lynn P. Bajorek
- Memory and Aging Center, University of California at San Francisco, San Francisco, CA, USA
- Department of Neurology, Dyslexia Center, University of California, San Francisco, CA, USA
| | - Isabel Elaine Allen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Zachary A. Miller
- Memory and Aging Center, University of California at San Francisco, San Francisco, CA, USA
- Department of Neurology, Dyslexia Center, University of California, San Francisco, CA, USA
| | - Kaitlin B. Casaletto
- Memory and Aging Center, University of California at San Francisco, San Francisco, CA, USA
| | - Bruce L. Miller
- Memory and Aging Center, University of California at San Francisco, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, University of California at San Francisco, San Francisco, CA, USA
- Department of Neurology, Dyslexia Center, University of California, San Francisco, CA, USA
- Global Brain Health Institute, University of California, San Francisco, CA, USA
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47
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Tsatali M, Avdikou K, Gialaouzidis M, Minopoulou D, Emmanouel A, Kouroundi E, Tsolaki M. The discriminant validity of Rey Complex Figure Test (RCFT) in subjective cognitive decline, mild cognitive impairment (multiple domain) and Alzheimer's disease dementia (ADD; mild stage) in Greek older adults. APPLIED NEUROPSYCHOLOGY. ADULT 2022:1-10. [PMID: 35188843 DOI: 10.1080/23279095.2022.2037089] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Aim: The goal of this study was to determine the discriminant potential of the Rey Complex Figure Test (RCFT) in older adults with Mild Cognitive Impairment multiple domain (mdMCI) and Alzheimer's Disease Dementia (ADD; mild subtype) as compared to older adults with Subjective Cognitive Decline (SCD).Materials and methods: We administered RCFT in 608 older adults, dividing them in three groups (217 individuals with SCD; 304 mdMCI population; 106 people with mild ADD, aged 50-90 years; M = 66.9, SD = 8.4) and a mean education of 10.20 (SD 4.3) years.Results: RCFT subtests have excellent discriminant validity, mainly between people with SCD and those with mild ADD. However, its discriminant validity in detecting older adults with SCD among mdMCI population is still questionable.Discussion: The use of RFCT in discriminating older adults with SCD from those with mild ADD both in research as well as in clinical practice is highly recommended.
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Affiliation(s)
- Marianna Tsatali
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Konstantina Avdikou
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Moses Gialaouzidis
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Despoina Minopoulou
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Anna Emmanouel
- Rehabilitation Center 'Anagennisi', Thessaloniki, Greece
| | - Eleni Kouroundi
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
| | - Magda Tsolaki
- Greek Association of Alzheimer's Disease and Related Disorders (GAADRD), Thessaloniki, Greece
- Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI- AUTh), Thessaloniki, Greece
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Toller G, Zitser J, Sukhanov P, Grant H, Miller BL, Kramer JH, Rosen HJ, Rankin KP, Grinberg LT. Clinical, neuroimaging, and neuropathological characterization of a patient with Alzheimer's disease syndrome due to Pick's pathology. Neurocase 2022; 28:19-28. [PMID: 34402746 PMCID: PMC9472769 DOI: 10.1080/13554794.2021.1936072] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The most common neurodegenerative syndrome associated with Pick's disease pathology (PiD) is behavioral variant frontotemporal dementia (bvFTD), which features profound social behavioral changes. Rarely, PiD can manifest as an Alzheimer's disease (AD)-type dementia with early memory impairment. We describe a patient with AD-type dementia and pure PiD pathology who showed slowly progressive memory impairment, early social changes, and paucity of motor symptoms. Atrophy and PiD were found mainly in frontotemporal regions underlying social behavior. This report may help predict the pathology of patients with atypical AD, which will ultimately be critical for enrolling suitable subjects into disease-modifying clinical trials.
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Affiliation(s)
- Gianina Toller
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Jennifer Zitser
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA.,Movement Disorders Unit, Department of Neurology, Tel Aviv Sourazky Medical Center, Affiliated to the Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Paul Sukhanov
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Harli Grant
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Joel H Kramer
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Howard J Rosen
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Katherine P Rankin
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Lea T Grinberg
- Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
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Distinct roles of right temporoparietal cortex in pentagon copying test. Brain Imaging Behav 2022; 16:1528-1537. [PMID: 35083712 DOI: 10.1007/s11682-021-00607-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/17/2021] [Indexed: 11/02/2022]
Abstract
Pentagon Copying Test (PCT) is commonly used to assess visuospatial deficits, but the neural substrates underlying pentagon copying are not well understood. The Qualitative Scoring Pentagon Test (QSPT), an optimized scoring system, classifies five categories of errors patients make in pentagons copying and grades them depending on the errors' severity. To determine the strategic brain regions involved in the PCT, we applied the QSPT system to evaluate the visuospatial impairment of 136 acute ischemic stroke patients on the PCT and used Support Vector Regression Lesion-Symptom Mapping to investigate relevant brain regions. The total QSPT score was correlated with the right supramarginal gyrus. The angle number errors and closure errors were principally associated with lesions of the posterior temporoparietal cortex, including the right middle occipital gyrus and middle temporal gyrus, while the intersection errors and rotation errors were related to the more anterior part of the right temporoparietal lobe with the additional frontal cortex. In conclusion, the right temporoparietal cortex is the strategic region for pentagon copying tasks. The angle number and closure represent the visuospatial processing of within-object features, while intersection and rotation require between-object manipulation. The posterior-anterior distinction in the right temporoparietal region underlies the differences of within-object and between-object processing.
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Custodio N, Montesinos R, Cruzado L, Alva-Díaz C, Failoc-Rojas VE, Celis V, Cuenca-Alfaro J, Lira D. Comparative study of the word capacity and episodic memory of patients with degenerative dementia. REVISTA COLOMBIANA DE PSIQUIATRIA (ENGLISH ED.) 2022; 51:8-16. [PMID: 35210208 DOI: 10.1016/j.rcpeng.2020.09.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 09/03/2020] [Indexed: 06/14/2023]
Abstract
INTRODUCTION Although the absence of memory impairment was considered among the diagnostic criteria to differentiate Alzheimer's disease (AD) from Behavioural Variant of Frontotemporal Dementia (bvFTD), current and growing evidence indicates that a significant percentage of cases of bvFTD present with episodic memory deficits. In order to compare the performance profile of the naming capacity and episodic memory in patients with AD and bvFTD the present study was designed. METHODS Cross-sectional and analytical study with control group (32 people). The study included 42 people with probable AD and 22 with probable bvFTD, all over 60 years old. Uniform Data Set instruments validated in Spanish were used: Multilingual Naming Test (MINT), Craft-21 history and Benson's complex figure, among others. RESULTS A higher average age was observed among the patients with AD. The naming capacity was much lower in patients with bvFTD compared to patients with AD, measured according to the MINT and the nouns/verbs naming coefficient. All patients with bvFTD, 73.81% of those with AD and only 31.25% of the control group failed to recognise Benson's complex figure. All differences were statistically significant (p < 0.001). RESULTS This study confirms the amnesic profile of patients with AD and reveals the decrease in naming capacity in patients with bvFTD, an area of language that is typically affected early on with executive functions, according to recent findings. CONCLUSIONS Patients with AD perform worse in verbal and visual episodic memory tasks, while patients with bvFTD perform worse in naming tasks. These findings open the possibility of exploring the mechanisms of prefrontal participation in episodic memory, typically attributed to the hippocampus.
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Affiliation(s)
- Nilton Custodio
- Servicio de Neurología, Instituto Peruano de Neurociencias, Lima, Peru; Unidad de Diagnóstico de Deterioro Cognitivo y Prevención de Demencia, Instituto Peruano de Neurociencias, Lima, Peru; Unidad de Investigación, Instituto Peruano de Neurociencias, Lima, Peru.
| | - Rosa Montesinos
- Unidad de Diagnóstico de Deterioro Cognitivo y Prevención de Demencia, Instituto Peruano de Neurociencias, Lima, Peru; Unidad de Investigación, Instituto Peruano de Neurociencias, Lima, Peru; Servicio de Rehabilitación, Instituto Peruano de Neurociencias, Lima, Peru
| | - Lizardo Cruzado
- Unidad de Diagnóstico de Deterioro Cognitivo y Prevención de Demencia, Instituto Peruano de Neurociencias, Lima, Peru; Unidad de Investigación, Instituto Peruano de Neurociencias, Lima, Peru; Servicio de Psiquiatría, Instituto Peruano de Neurociencias, Lima, Peru; Sección Psiquiatría y Salud Mental, Facultad de Medicina, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Carlos Alva-Díaz
- Unidad de Investigación, Instituto Peruano de Neurociencias, Lima, Peru; Universidad Científica del Sur, Facultad de Ciencias de la Salud, Lima, Peru; Servicio de Neurología, Departamento de Medicina y Oficina de Apoyo a la Docencia e Investigación (OADI), Hospital Daniel Alcides Carrión, Callao, Peru
| | - Virgilio E Failoc-Rojas
- Unidad de Investigación, Instituto Peruano de Neurociencias, Lima, Peru; Universidad San Ignacio de Loyola, Lima, Peru
| | - Violeta Celis
- Servicio de Neurología, Hospital Belén, Trujillo, Peru
| | - José Cuenca-Alfaro
- Unidad de Diagnóstico de Deterioro Cognitivo y Prevención de Demencia, Instituto Peruano de Neurociencias, Lima, Peru; Unidad de Investigación, Instituto Peruano de Neurociencias, Lima, Peru; Facultad de Ciencias de la Salud, Departamento de Psicología, Universidad Privada del Norte, Lima, Peru
| | - David Lira
- Servicio de Neurología, Instituto Peruano de Neurociencias, Lima, Peru; Unidad de Diagnóstico de Deterioro Cognitivo y Prevención de Demencia, Instituto Peruano de Neurociencias, Lima, Peru; Unidad de Investigación, Instituto Peruano de Neurociencias, Lima, Peru
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