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Babulal GM, Chen L, Murphy SA, Carr DB, Morris JC. Predicting Driving Cessation Among Cognitively Normal Older Drivers: The Role of Alzheimer Disease Biomarkers and Clinical Assessments. Neurology 2024; 102:e209426. [PMID: 38776513 PMCID: PMC11226325 DOI: 10.1212/wnl.0000000000209426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 03/11/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND AND OBJECTIVES With the aging US population and increasing incidence of Alzheimer disease (AD), understanding factors contributing to driving cessation among older adults is crucial for clinicians. Driving is integral for maintaining independence and functional mobility, but the risk factors for driving cessation, particularly in the context of normal aging and preclinical AD, are not well understood. We studied a well-characterized community cohort to examine factors associated with driving cessation. METHODS This prospective, longitudinal observation study enrolled participants from the Knight Alzheimer Disease Research Center and The DRIVES Project. Participants were enrolled if they were aged 65 years or older, drove weekly, and were cognitively normal (Clinical Dementia Rating [CDR] = 0) at baseline. Participants underwent annual clinical, neurologic, and neuropsychological assessments, including β-amyloid PET imaging and CSF (Aβ42, total tau [t-Tau], and phosphorylated tau [p-Tau]) collection every 2-3 years. The primary outcome was time from baseline visit to driving cessation, accounting for death as a competing risk. The cumulative incidence function of driving cessation was estimated for each biomarker. The Fine and Gray subdistribution hazard model was used to examine the association between time to driving cessation and biomarkers adjusting for clinical and demographic covariates. RESULTS Among the 283 participants included in this study, there was a mean follow-up of 5.62 years. Driving cessation (8%) was associated with older age, female sex, progression to symptomatic AD (CDR ≥0.5), and poorer performance on a preclinical Alzheimer cognitive composite (PACC) score. Aβ PET imaging did not independently predict driving cessation, whereas CSF biomarkers, specifically t-Tau/Aβ42 (hazard ratio [HR] 2.82, 95% CI 1.23-6.44, p = 0.014) and p-Tau/Aβ42 (HR 2.91, 95% CI 1.28-6.59, p = 0.012) ratios, were independent predictors in the simple model adjusting for age, education, and sex. However, in the full model, progression to cognitive impairment based on the CDR and PACC score across each model was associated with a higher risk of driving cessation, whereas AD biomarkers were not statistically significant. DISCUSSION Female sex, CDR progression, and neuropsychological measures of cognitive functioning obtained in the clinic were strongly associated with future driving cessation. The results emphasize the need for early planning and conversations about driving retirement in the context of cognitive decline and the immense value of clinical measures in determining functional outcomes.
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Affiliation(s)
- Ganesh M Babulal
- From the Department of Neurology (G.M.B., S.A.M., J.C.M.), Division of Biostatistics (L.C.), and Department of Medicine (D.B.C.), Washington University School of Medicine, St. Louis, MO
| | - Ling Chen
- From the Department of Neurology (G.M.B., S.A.M., J.C.M.), Division of Biostatistics (L.C.), and Department of Medicine (D.B.C.), Washington University School of Medicine, St. Louis, MO
| | - Samantha A Murphy
- From the Department of Neurology (G.M.B., S.A.M., J.C.M.), Division of Biostatistics (L.C.), and Department of Medicine (D.B.C.), Washington University School of Medicine, St. Louis, MO
| | - David B Carr
- From the Department of Neurology (G.M.B., S.A.M., J.C.M.), Division of Biostatistics (L.C.), and Department of Medicine (D.B.C.), Washington University School of Medicine, St. Louis, MO
| | - John C Morris
- From the Department of Neurology (G.M.B., S.A.M., J.C.M.), Division of Biostatistics (L.C.), and Department of Medicine (D.B.C.), Washington University School of Medicine, St. Louis, MO
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Xu C, Acevedo P, Lu Y, Su BB, Ozuna K, Padilla V, Karithara A, Mao C, Navia RO, Piamjariyakul U, Wang K. Racial differences in the effect of APOE-ε4 genotypes on trail making test B in Alzheimer's disease: A longitudinal study. Int J Geriatr Psychiatry 2023; 38:e6037. [PMID: 38100638 DOI: 10.1002/gps.6037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 11/28/2023] [Indexed: 12/17/2023]
Abstract
OBJECTIVES The trail making test part B (TMT-B) evaluates executive functions, memory, and sensorimotor functions. No previous study was found to examine the longitudinal effect of APOE-ε4 genotypes on the TMT-B scores in Alzheimer's disease (AD) across racial groups. METHODS This study used the data from Alzheimer's Disease Neuroimaging Initiative (ADNI): 382 participants with AD, 503 with cognitive normal (CN), 1293 with mild cognitive impairment (MCI) at baseline and follow-up of four years. The multivariable linear mixed model was used to investigate the effect of APOE-ε4 genotypes on changes in TMT-B scores. RESULTS Compared with Whites, African Americans (AA) and Hispanics had higher TMT-B scores (poor cognitive function). Furthermore, Whites subjects with 1 or 2 APOE-ε4 alleles had significantly higher TMT-B scores compared with individuals without APOE-ε4 allele at baseline and four follow-up visits; however, no differences in TMT-B were found between APOE-ε4 alleles in the Hispanic and AA groups. No APOE-ε4 by visit interactions was found for 3 racial groups. Stratified by AD diagnosis, the APOE-ε4 allele was associated with TMT-B scores only in the MCI group, while there were significant interactions for visit by education, APOE-ε4 allele, and the Mini Mental State Examination (MMSE) score in the MCI group. In addition, TMT-B was significantly correlated with the MMSE, AD Assessment Scale-cognitive subscale 13 (ADAS13), tTau, pTau, Aβ42, and hippocampus. CONCLUSIONS APOE-ɛ4 allele is associated with TMT-B scores in Whites subjects, but not in the Hispanic and AA groups. APOE-ε4 showed interaction with visit in the MCI group.
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Affiliation(s)
- Chun Xu
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - Priscila Acevedo
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - Yongke Lu
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, West Virginia, USA
| | - Brenda Bin Su
- Department of Pediatrics - Allergy and Immunology, Baylor College of Medicine, Houston, Texas, USA
| | - Kaysie Ozuna
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - Victoria Padilla
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - Annu Karithara
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - ChunXiang Mao
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - R Osvaldo Navia
- Department of Medicine and Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, USA
| | - Ubolrat Piamjariyakul
- School of Nursing, Health Sciences Center, West Virginia University, Morgantown, West Virginia, USA
| | - Kesheng Wang
- School of Nursing, Health Sciences Center, West Virginia University, Morgantown, West Virginia, USA
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Grober E, Petersen KK, Lipton RB, Hassenstab J, Morris JC, Gordon BA, Ezzati A. Association of Stages of Objective Memory Impairment With Incident Symptomatic Cognitive Impairment in Cognitively Normal Individuals. Neurology 2023; 100:e2279-e2289. [PMID: 37076305 PMCID: PMC10259282 DOI: 10.1212/wnl.0000000000207276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 02/23/2023] [Indexed: 04/21/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Increasing evidence indicates that a subset of cognitively normal individuals has subtle cognitive impairment at baseline. We sought to identify them using the Stages of Objective Memory Impairment (SOMI) system. Symptomatic cognitive impairment was operationalized by a Clinical Dementia Rating (CDR) ≥0.5. We hypothesized that incident impairment would be higher for participants with subtle retrieval impairment (SOMI-1), higher still for those with moderate retrieval impairment (SOMI-2), and highest for those with storage impairment (SOMI-3/4) after adjusting for demographics and APOE ε4 status. A secondary objective was to determine whether including biomarkers of β-amyloid, tau pathology, and neurodegeneration in the models affect prediction. We hypothesized that even after adjusting for in vivo biomarkers, SOMI would remain a significant predictor of time to incident symptomatic cognitive impairment. METHODS Among 969 cognitively normal participants, defined by a CDR = 0, from the Knight Alzheimer Disease Research Center, SOMI stage was determined from their baseline Free and Cued Selective Reminding Test scores, 555 had CSF and structural MRI measures and comprised the biomarker subgroup, and 144 of them were amyloid positive. Cox proportional hazards models tested associations of SOMI stages at baseline and biomarkers with time to incident cognitive impairment defined as the transition to CDR ≥0.5. RESULTS Among all participants, the mean age was 69.35 years, 59.6% were female, and mean follow-up was 6.36 years. Participants in SOMI-1-4 had elevated hazard ratios for the transition from normal to impaired cognition in comparison with those who were SOMI-0 (no memory impairment). Individuals in SOMI-1 (mildly impaired retrieval) and SOMI-2 (moderately impaired retrieval) were at nearly double the risk of clinical progression compared with persons with no memory problems. When memory storage impairment emerges (SOMI-3/4), the hazard ratio for clinical progression increased approximately 3 times. SOMI stage remained an independent predictor of incident cognitive impairment after adjusting for all biomarkers. DISCUSSION SOMI predicts the transition from normal cognition to incident symptomatic cognitive impairment (CDR ≥0.5). The results support the use of SOMI to identify those cognitively normal participants most likely to develop incident cognitive impairment who can then be referred for biomarker screening.
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Affiliation(s)
- Ellen Grober
- From the Saul R. Korey (E.G., K.K.P., R.B.L., A.E.), Department of Neurology, Albert Einstein College of Medicine, Bronx, NY; and Department of Neurology (J.H., J.C.M., B.A.G.), Washington University School of Medicine, St. Louis, MO.
| | - Kellen K Petersen
- From the Saul R. Korey (E.G., K.K.P., R.B.L., A.E.), Department of Neurology, Albert Einstein College of Medicine, Bronx, NY; and Department of Neurology (J.H., J.C.M., B.A.G.), Washington University School of Medicine, St. Louis, MO
| | - Richard B Lipton
- From the Saul R. Korey (E.G., K.K.P., R.B.L., A.E.), Department of Neurology, Albert Einstein College of Medicine, Bronx, NY; and Department of Neurology (J.H., J.C.M., B.A.G.), Washington University School of Medicine, St. Louis, MO
| | - Jason Hassenstab
- From the Saul R. Korey (E.G., K.K.P., R.B.L., A.E.), Department of Neurology, Albert Einstein College of Medicine, Bronx, NY; and Department of Neurology (J.H., J.C.M., B.A.G.), Washington University School of Medicine, St. Louis, MO
| | - John C Morris
- From the Saul R. Korey (E.G., K.K.P., R.B.L., A.E.), Department of Neurology, Albert Einstein College of Medicine, Bronx, NY; and Department of Neurology (J.H., J.C.M., B.A.G.), Washington University School of Medicine, St. Louis, MO
| | - Brian A Gordon
- From the Saul R. Korey (E.G., K.K.P., R.B.L., A.E.), Department of Neurology, Albert Einstein College of Medicine, Bronx, NY; and Department of Neurology (J.H., J.C.M., B.A.G.), Washington University School of Medicine, St. Louis, MO
| | - Ali Ezzati
- From the Saul R. Korey (E.G., K.K.P., R.B.L., A.E.), Department of Neurology, Albert Einstein College of Medicine, Bronx, NY; and Department of Neurology (J.H., J.C.M., B.A.G.), Washington University School of Medicine, St. Louis, MO
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Kim H, Devanand DP, Carlson S, Goldberg TE. Apolipoprotein E Genotype e2: Neuroprotection and Its Limits. Front Aging Neurosci 2022; 14:919712. [PMID: 35912085 PMCID: PMC9329577 DOI: 10.3389/fnagi.2022.919712] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/09/2022] [Indexed: 11/21/2022] Open
Abstract
In this review, we comprehensively, qualitatively, and critically synthesized several features of APOE-e2, a known APOE protective variant, including its associations with longevity, cognition, and neuroimaging, and neuropathology, all in humans. If e2’s protective effects—and their limits—could be elucidated, it could offer therapeutic windows for Alzheimer’s disease (AD) prevention or amelioration. Literature examining e2 within the years 1994–2021 were considered for this review. Studies on human subjects were selectively reviewed and were excluded if observation of e2 was not specified. Effects of e2 were compared with e3 and e4, separately and as a combined non-e2 group. Our examination of existing literature indicated that the most robust protective role of e2 is in longevity and AD neuropathologies, but e2’s effect on cognition and other AD imaging markers (brain structure, function, and metabolism) were inconsistent, thus inconclusive. Notably, e2 was associated with greater risk of non-AD proteinopathies and a disadvantageous cerebrovascular profile. We identified multiple methodological shortcomings of the literature on brain function and cognition that could have contributed to inconsistent and potentially misleading findings. We make careful interpretations of existing findings and provide directions for research strategies that could effectively examine the independent and unbiased effect of e2 on AD risk.
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Affiliation(s)
- Hyun Kim
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
| | - Davangere P. Devanand
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, United States
| | - Scott Carlson
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
| | - Terry E. Goldberg
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
- Department of Anesthesiology, Columbia University Irving Medical Center, New York, NY, United States
- *Correspondence: Terry E. Goldberg,
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Cersonsky TE, Mechery S, Carper MM, Thompson L, Lee A, Alber J, Sarkar IN, Brick LAD. Using the Montreal cognitive assessment to identify individuals with subtle cognitive decline. Neuropsychology 2022; 36:373-383. [PMID: 35511561 PMCID: PMC9912279 DOI: 10.1037/neu0000820] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVE Dementia is a devastating neurological disease that may be better managed if diagnosed earlier when subclinical neurodegenerative changes are already present, including subtle cognitive decline and mild cognitive impairment. In this study, we used item-level performance on the Montreal Cognitive Assessment (MoCA) to identify individuals with subtle cognitive decline. METHOD Individual MoCA item data from the Alzheimer's Disease Neuroimaging Initiative was grouped using k-modes cluster analysis. These clusters were validated and examined for association with convergent neuropsychological tests. The clusters were then compared and characterized using multinomial logistic regression. RESULTS A three-cluster solution had 77.3% precision, with Cluster 1 (high performing) displaying no deficits in performance, Cluster 2 (memory deficits) displaying lower memory performance, and Cluster 3 (compound deficits) displaying lower performance on memory and executive function. Age at MoCA (older in compound deficits), gender (more females in memory deficits), and marital status (fewer married in compound deficits) were significantly different among clusters. Age was not associated with increased odds of membership in the high-performing cluster compared to the others. CONCLUSIONS We identified three clusters of individuals classified as cognitively unimpaired using cluster analysis. Individuals in the compound deficits cluster performed lower on the MoCA and were older and less often married than individuals in other clusters. Demographic analyses suggest that cluster identity was due to a combination of both cognitive and clinical factors. Identifying individuals at risk for future cognitive decline using the MoCA could help them receive earlier evidence-based interventions to slow further cognitive decline. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
- Tess E.K. Cersonsky
- Warren Alpert Medical School of Brown University, Providence, RI, USA.,Center for Biomedical Informatics, Brown University, Providence, RI, USA
| | - Shanti Mechery
- Memory and Aging Program, Butler Hospital, Providence, RI, USA
| | - Matthew M. Carper
- Warren Alpert Medical School of Brown University, Providence, RI, USA.,Quantitative Sciences Program, Department of Psychiatry and Neurology, Warren Alpert Medical School of Brown University, Providence, RI, USA,Emma Pendleton Bradley Hospital, Riverside, RI, USA
| | - Louisa Thompson
- Warren Alpert Medical School of Brown University, Providence, RI, USA.,Memory and Aging Program, Butler Hospital, Providence, RI, USA
| | - Athene Lee
- Warren Alpert Medical School of Brown University, Providence, RI, USA.,Memory and Aging Program, Butler Hospital, Providence, RI, USA.,Quantitative Sciences Program, Department of Psychiatry and Neurology, Warren Alpert Medical School of Brown University, Providence, RI, USA,Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Jessica Alber
- Memory and Aging Program, Butler Hospital, Providence, RI, USA.,Department of Biomedical and Pharmaceutical Sciences, George & Anne Ryan Institute for Neuroscience, University of Rhode Island, Kingston, RI, USA
| | - Indra Neil Sarkar
- Warren Alpert Medical School of Brown University, Providence, RI, USA.,Center for Biomedical Informatics, Brown University, Providence, RI, USA.,School of Public Health, Brown University, Providence, RI, USA.,Rhode Island Quality Institute, Providence, RI, USA
| | - Leslie Ann D. Brick
- Warren Alpert Medical School of Brown University, Providence, RI, USA.,Quantitative Sciences Program, Department of Psychiatry and Neurology, Warren Alpert Medical School of Brown University, Providence, RI, USA
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Koo YS, An S, Kim MJ, Kim HW, Lee SA. Psychomotor Speed Predicts Outcome in Patients with Acute Meningitis and Encephalitis: A Prospective Observational Study. Clin EEG Neurosci 2022; 53:229-237. [PMID: 34255579 DOI: 10.1177/15500594211031137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose. Although acute meningitis and encephalitis are known to cause cognitive dysfunction, the prognostic values of neuropsychological and neurophysiological tests in predicting clinical outcomes are seldom studied. We investigated specific neurocognitive dysfunction and event-related potentials (ERPs), which can predict functional outcomes in patients with acute meningitis and encephalitis. Methods. We enrolled consecutive adult patients with acute meningitis and encephalitis and performed neuropsychological tests and ERP studies using a passive auditory oddball paradigm at enrollment. Patient functional outcomes were assessed using the Glasgow Outcome Scale at 6 (GOS6) months after discharge. Results. Twenty-two patients were included in the study. Among 21 patients who performed neuropsychological tests, Korean-Trail Making Test-Elderly's version, Part A time (TMT-A time) correlated with GOS6, which remained significant even after controlling for age. We identified a significant association between TMT-A time and P3a latency. Post-hoc analysis showed that patients with longer TMT-A time (≥23 s) tended to have longer P3a latency than those with shorter TMT-A time. Conclusions. Decreased psychomotor speed predicted poor clinical outcomes. Because TMT-A time can be performed at the bedside in a relatively short time, this might be a useful neuropsychological biomarker to predict or monitor clinical outcomes. Furthermore, passive oddball P3a may be useful in patients with more severe disease who are unable to perform the TMT task.
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Affiliation(s)
| | - Soyeon An
- 65526Asan Medical Center, Seoul, South Korea
| | - Min-Ju Kim
- 65526Asan Medical Center, Seoul, South Korea
| | - Hyun-Woo Kim
- 194197Pusan National University Yangsan Hospital, Yangsan, South Korea
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Concordance of Alzheimer’s Disease Subtypes Produced from Different Representative Morphological Measures: A Comparative Study. Brain Sci 2022; 12:brainsci12020187. [PMID: 35203950 PMCID: PMC8869952 DOI: 10.3390/brainsci12020187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 01/20/2022] [Accepted: 01/25/2022] [Indexed: 11/17/2022] Open
Abstract
Background: Gray matter (GM) density and cortical thickness (CT) obtained from structural magnetic resonance imaging are representative GM morphological measures that have been commonly used in Alzheimer’s disease (AD) subtype research. However, how the two measures affect the definition of AD subtypes remains unclear. Methods: A total of 180 AD patients from the ADNI database were used to identify AD subgroups. The subtypes were identified via a data-driven strategy based on the density features and CT features, respectively. Then, the similarity between the two features in AD subtype definition was analyzed. Results: Four distinct subtypes were discovered by both density and CT features: diffuse atrophy AD, minimal atrophy AD (MAD), left temporal dominant atrophy AD (LTAD), and occipital sparing AD. The matched subtypes exhibited relatively high similarity in atrophy patterns and neuropsychological and neuropathological characteristics. They differed only in MAD and LTAD regarding the carrying of apolipoprotein E ε2. Conclusions: The results verified that different representative morphological GM measurement methods could produce similar AD subtypes. Meanwhile, the influences of apolipoprotein E genotype, asymmetric disease progression, and their interactions should be considered and included in the AD subtype definition. This study provides a valuable reference for selecting features in future studies of AD subtypes.
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Bayat S, Babulal GM, Schindler SE, Fagan AM, Morris JC, Mihailidis A, Roe CM. GPS driving: a digital biomarker for preclinical Alzheimer disease. Alzheimers Res Ther 2021; 13:115. [PMID: 34127064 PMCID: PMC8204509 DOI: 10.1186/s13195-021-00852-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 05/31/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND Alzheimer disease (AD) is the most common cause of dementia. Preclinical AD is the period during which early AD brain changes are present but cognitive symptoms have not yet manifest. The presence of AD brain changes can be ascertained by molecular biomarkers obtained via imaging and lumbar puncture. However, the use of these methods is limited by cost, acceptability, and availability. The preclinical stage of AD may have a subtle functional signature, which can impact complex behaviours such as driving. The objective of the present study was to evaluate the ability of in-vehicle GPS data loggers to distinguish cognitively normal older drivers with preclinical AD from those without preclinical AD using machine learning methods. METHODS We followed naturalistic driving in cognitively normal older drivers for 1 year with a commercial in-vehicle GPS data logger. The cohort included n = 64 individuals with and n = 75 without preclinical AD, as determined by cerebrospinal fluid biomarkers. Four Random Forest (RF) models were trained to detect preclinical AD. RF Gini index was used to identify the strongest predictors of preclinical AD. RESULTS The F1 score of the RF models for identifying preclinical AD was 0.85 using APOE ε4 status and age only, 0.82 using GPS-based driving indicators only, 0.88 using age and driving indicators, and 0.91 using age, APOE ε4 status, and driving. The area under the receiver operating curve for the final model was 0.96. CONCLUSION The findings suggest that GPS driving may serve as an effective and accurate digital biomarker for identifying preclinical AD among older adults.
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Affiliation(s)
- Sayeh Bayat
- Institute of Biomedical Engineering, University of Toronto, 550 University Avenue, Toronto, ON, M5G 1X5, Canada.
- KITE Research Institute, Toronto Rehabilitation Institute, Toronto, ON, Canada.
| | - Ganesh M Babulal
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychology, University of Johannesburg, Johannesburg, South Africa
| | - Suzanne E Schindler
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Physical Therapy, Washington University School of Medicine, St. Louis, MO, USA
- Department of Occupational Science & Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA
| | - Alex Mihailidis
- Institute of Biomedical Engineering, University of Toronto, 550 University Avenue, Toronto, ON, M5G 1X5, Canada
- KITE Research Institute, Toronto Rehabilitation Institute, Toronto, ON, Canada
- Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, ON, Canada
| | - Catherine M Roe
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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Narbutas J, Chylinski D, Van Egroo M, Bahri MA, Koshmanova E, Besson G, Muto V, Schmidt C, Luxen A, Balteau E, Phillips C, Maquet P, Salmon E, Vandewalle G, Bastin C, Collette F. Positive Effect of Cognitive Reserve on Episodic Memory, Executive and Attentional Functions Taking Into Account Amyloid-Beta, Tau, and Apolipoprotein E Status. Front Aging Neurosci 2021; 13:666181. [PMID: 34122044 PMCID: PMC8194490 DOI: 10.3389/fnagi.2021.666181] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/20/2021] [Indexed: 01/01/2023] Open
Abstract
Studies exploring the simultaneous influence of several physiological and environmental factors on domain-specific cognition in late middle-age remain scarce. Therefore, our objective was to determine the respective contribution of modifiable risk/protective factors (cognitive reserve and allostatic load) on specific cognitive domains (episodic memory, executive functions, and attention), taking into account non-modifiable factors [sex, age, and genetic risk for Alzheimer's disease (AD)] and AD-related biomarker amount (amyloid-beta and tau/neuroinflammation) in a healthy late-middle-aged population. One hundred and one healthy participants (59.4 ± 5 years; 68 women) were evaluated for episodic memory, executive and attentional functioning via neuropsychological test battery. Cognitive reserve was determined by the National Adult Reading Test. The allostatic load consisted of measures of lipid metabolism and sympathetic nervous system functioning. The amyloid-beta level was assessed using positron emission tomography in all participants, whereas tau/neuroinflammation positron emission tomography scans and apolipoprotein E genotype were available for 58 participants. Higher cognitive reserve was the main correlate of better cognitive performance across all domains. Moreover, age was negatively associated with attentional functioning, whereas sex was a significant predictor for episodic memory, with women having better performance than men. Finally, our results did not show clear significant associations between performance over any cognitive domain and apolipoprotein E genotype and AD biomarkers. This suggests that domain-specific cognition in late healthy midlife is mainly determined by a combination of modifiable (cognitive reserve) and non-modifiable factors (sex and age) rather than by AD biomarkers and genetic risk for AD.
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Affiliation(s)
- Justinas Narbutas
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - Daphne Chylinski
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Maxime Van Egroo
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Mohamed Ali Bahri
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Ekaterina Koshmanova
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Gabriel Besson
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Vincenzo Muto
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Christina Schmidt
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - André Luxen
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Evelyne Balteau
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Christophe Phillips
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Pierre Maquet
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Department of Neurology, CHU de Liège, Liège, Belgium
| | - Eric Salmon
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
- Department of Neurology, CHU de Liège, Liège, Belgium
| | - Gilles Vandewalle
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Christine Bastin
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - Fabienne Collette
- GIGA Institute, Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
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10
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Babulal GM, Roe CM, Stout SH, Rajasekar G, Wisch JK, Benzinger TLS, Morris JC, Ances BM. Depression is Associated with Tau and Not Amyloid Positron Emission Tomography in Cognitively Normal Adults. J Alzheimers Dis 2021; 74:1045-1055. [PMID: 32144985 DOI: 10.3233/jad-191078] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Depression is also common with older age. Alzheimer's disease (AD) studies suggest that both cerebrospinal fluid and positron emission tomography (PET) amyloid biomarkers are associated with more depressive symptoms in cognitively normal older adults. The recent availability of tau radiotracers offers the ability to examine in vivo tauopathy. It is unclear if the tau biomarker is associated with depression diagnosis. OBJECTIVE We examined if tau and amyloid imaging were associated with a depression diagnosis among cognitively normal adults (Clinical Dementia Rating = 0) and whether antidepressants modified this relationship. METHODS Among 301 participants, logistic regression models evaluated whether in vivo PET tau was associated with depression, while another model tested the interaction between PET tau and antidepressant use. A second set of models substituted PET amyloid for PET tau. A diagnosis of depression (yes/no) was made during an annual clinical assessment by a clinician. Antidepressant use (yes/no) was determined by comparing medications the participants used to a list of 30 commonly used antidepressants. All models adjusted for age, sex, education, race, and apolipoprotein ɛ4. Similar models explored the association between the biomarkers and depressive symptoms. RESULTS Participants with elevated tau were twice as likely to be depressed. Antidepressant use modified this relationship where participants with elevated tau who were taking antidepressants had greater odds of being depressed. Relatedly, elevated amyloid was not associated with depression. CONCLUSIONS Our results demonstrate that tau, not amyloid, was associated with a depression diagnosis. Additionally, antidepressant use interacts with tau to increase the odds of depression among cognitively normal adults.
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Affiliation(s)
- Ganesh M Babulal
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Catherine M Roe
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sarah H Stout
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ganesh Rajasekar
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Julie K Wisch
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Physical Therapy, Washington University School of Medicine, St. Louis, MO, USA.,Department of Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA
| | - Beau M Ances
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
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11
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Babulal GM, Johnson A, Fagan AM, Morris JC, Roe CM. Identifying Preclinical Alzheimer's Disease Using Everyday Driving Behavior: Proof of Concept. J Alzheimers Dis 2021; 79:1009-1014. [PMID: 33361605 DOI: 10.3233/jad-201294] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We examined whether driving behavior can predict preclinical Alzheimer's disease (AD). Data from 131 cognitively normal older adults with cerebrospinal fluid (CSF) and/or positron emission tomography (PET) biomarkers were examined with naturalistic driving behavior. Receiver operating characteristic curves were used to predict the highest 10%, 25%, and 50% of values for CSF tau/Aβ42, ptau181/Aβ42, or amyloid PET. Six in vivo driving variables alone yielded area under the curves (AUC) from 0.64-0.82. Addition of age, Apolipoprotein ɛ4, and neuropsychological measures to the models improved the AUC (0.81 to 0.90). Driving can be used as novel neurobehavioral marker to identify presence of preclinical AD.
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Affiliation(s)
- Ganesh M Babulal
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ann Johnson
- Center for Clinical Studies, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.,Departments of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Physical Therapy, Washington University School of Medicine, St. Louis, MO, USA.,Department of Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA
| | - Catherine M Roe
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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12
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Xie L, Wisse LEM, Das SR, Vergnet N, Dong M, Ittyerah R, de Flores R, Yushkevich PA, Wolk DA. Longitudinal atrophy in early Braak regions in preclinical Alzheimer's disease. Hum Brain Mapp 2020; 41:4704-4717. [PMID: 32845545 PMCID: PMC7555086 DOI: 10.1002/hbm.25151] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/10/2020] [Accepted: 07/18/2020] [Indexed: 01/01/2023] Open
Abstract
A major focus of Alzheimer's disease (AD) research has been finding sensitive outcome measures to disease progression in preclinical AD, as intervention studies begin to target this population. We hypothesize that tailored measures of longitudinal change of the medial temporal lobe (MTL) subregions (the sites of earliest cortical tangle pathology) are more sensitive to disease progression in preclinical AD compared to standard cognitive and plasma NfL measures. Longitudinal T1-weighted MRI of 337 participants were included, divided into amyloid-β negative (Aβ-) controls, cerebral spinal fluid p-tau positive (T+) and negative (T-) preclinical AD (Aβ+ controls), and early prodromal AD. Anterior/posterior hippocampus, entorhinal cortex, Brodmann areas (BA) 35 and 36, and parahippocampal cortex were segmented in baseline MRI using a novel pipeline. Unbiased change rates of subregions were estimated using MRI scans within a 2-year-follow-up period. Experimental results showed that longitudinal atrophy rates of all MTL subregions were significantly higher for T+ preclinical AD and early prodromal AD than controls, but not for T- preclinical AD. Posterior hippocampus and BA35 demonstrated the largest group differences among hippocampus and MTL cortex respectively. None of the cross-sectional MTL measures, longitudinal cognitive measures (PACC, ADAS-Cog) and cross-sectional or longitudinal plasma NfL reached significance in preclinical AD. In conclusion, longitudinal atrophy measurements reflect active neurodegeneration and thus are more directly linked to active disease progression than cross-sectional measurements. Moreover, accelerated atrophy in preclinical AD seems to occur only in the presence of concomitant tau pathology. The proposed longitudinal measurements may serve as efficient outcome measures in clinical trials.
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Affiliation(s)
- Long Xie
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Laura E M Wisse
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Diagnostic Radiology, Lund University, Lund, Sweden
| | - Sandhitsu R Das
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nicolas Vergnet
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mengjin Dong
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robin de Flores
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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13
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Vermunt L, Dicks E, Wang G, Dincer A, Flores S, Keefe SJ, Berman SB, Cash DM, Chhatwal JP, Cruchaga C, Fox NC, Ghetti B, Graff-Radford NR, Hassenstab J, Karch CM, Laske C, Levin J, Masters CL, McDade E, Mori H, Morris JC, Noble JM, Perrin RJ, Schofield PR, Xiong C, Scheltens P, Visser PJ, Bateman RJ, Benzinger TLS, Tijms BM, Gordon BA. Single-subject grey matter network trajectories over the disease course of autosomal dominant Alzheimer's disease. Brain Commun 2020; 2:fcaa102. [PMID: 32954344 PMCID: PMC7475695 DOI: 10.1093/braincomms/fcaa102] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 05/25/2020] [Accepted: 06/18/2020] [Indexed: 12/12/2022] Open
Abstract
Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer's disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer's disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset -9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer's disease, which is alike sporadic Alzheimer's disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer's disease.
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Affiliation(s)
- Lisa Vermunt
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam, UMC, VU University, Netherlands
| | - Ellen Dicks
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam, UMC, VU University, Netherlands
| | - Guoqiao Wang
- Division of Biostatistics, Washington University in St. Louis, MO, USA
| | - Aylin Dincer
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA
| | - Shaney Flores
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA
| | - Sarah J Keefe
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA
| | - Sarah B Berman
- Department of Neurology, Alzheimer’s Disease Research Center, Pittsburgh, PA
- Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh, Pittsburgh, PA
| | - David M Cash
- UCL Queen Square Institute of Neurology, London, UK
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University in St. Louis, MO, USA
- Hope Center for Neurological Disorders, . Washington University in St. Louis, MO, USA
- NeuroGenomics and Informatics, Washington University in St. Louis, St. Louis, MO, USA
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UK
- Dementia Research Institute at UCL, UCL Institute of Neurology, London, UK
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University, IN, USA
| | | | - Jason Hassenstab
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, MO, USA
- Department of Psychological & Brain Sciences, Washington University in St. Louis, MO, USA
| | - Celeste M Karch
- Department of Psychiatry, Washington University in St. Louis, MO, USA
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Germany
| | | | - Colin L Masters
- Florey Institute, Melbourne, Australia
- The University of Melbourne, Melbourne, Australia
| | - Eric McDade
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, MO, USA
| | - Hiroshi Mori
- Department of Clinical Neuroscience, Osaka City University Medical School, Japan
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, MO, USA
| | - James M Noble
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, GH Sergievsky Center, Columbia University Medical Center, NY, USA
| | - Richard J Perrin
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO, USA
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis MO, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, UNSW Sydney, Sydney, Australia
| | - Chengjie Xiong
- Division of Biostatistics, Washington University in St. Louis, MO, USA
| | - Philip Scheltens
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam, UMC, VU University, Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam, UMC, VU University, Netherlands
- Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Netherlands
| | - Randall J Bateman
- Department of Psychiatry, Washington University in St. Louis, MO, USA
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, MO, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO, USA
| | - Betty M Tijms
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam, UMC, VU University, Netherlands
| | - Brian A Gordon
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, MO, USA
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO, USA
- Department of Psychological & Brain Sciences, Washington University in St. Louis, MO, USA
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14
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Hadjichrysanthou C, Evans S, Bajaj S, Siakallis LC, McRae-McKee K, de Wolf F, Anderson RM. The dynamics of biomarkers across the clinical spectrum of Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2020; 12:74. [PMID: 32534594 PMCID: PMC7293779 DOI: 10.1186/s13195-020-00636-z] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 05/20/2020] [Indexed: 12/20/2022]
Abstract
Background Quantifying changes in the levels of biological and cognitive markers prior to the clinical presentation of Alzheimer’s disease (AD) will provide a template for understanding the underlying aetiology of the clinical syndrome and, concomitantly, for improving early diagnosis, clinical trial recruitment and treatment assessment. This study aims to characterise continuous changes of such markers and determine their rate of change and temporal order throughout the AD continuum. Methods The methodology is founded on the development of stochastic models to estimate the expected time to reach different clinical disease states, for different risk groups, and synchronise short-term individual biomarker data onto a disease progression timeline. Twenty-seven markers are considered, including a range of cognitive scores, cerebrospinal (CSF) and plasma fluid proteins, and brain structural and molecular imaging measures. Data from 2014 participants in the Alzheimer’s Disease Neuroimaging Initiative database is utilised. Results The model suggests that detectable memory dysfunction could occur up to three decades prior to the onset of dementia due to AD (ADem). This is closely followed by changes in amyloid-β CSF levels and the first cognitive decline, as assessed by sensitive measures. Hippocampal atrophy could be observed as early as the initial amyloid-β accumulation. Brain hypometabolism starts later, about 14 years before onset, along with changes in the levels of total and phosphorylated tau proteins. Loss of functional abilities occurs rapidly around ADem onset. Neurofilament light is the only protein with notable early changes in plasma levels. The rate of change varies, with CSF, memory, amyloid PET and brain structural measures exhibiting the highest rate before the onset of ADem, followed by a decline. The probability of progressing to a more severe clinical state increases almost exponentially with age. In accordance with previous studies, the presence of apolipoprotein E4 alleles and amyloid-β accumulation can be associated with an increased risk of developing the disease, but their influence depends on age and clinical state. Conclusions Despite the limited longitudinal data at the individual level and the high variability observed in such data, the study elucidates the link between the long asynchronous pathophysiological processes and the preclinical and clinical stages of AD.
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Affiliation(s)
| | - Stephanie Evans
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.,Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
| | - Sumali Bajaj
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Loizos C Siakallis
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, UK
| | - Kevin McRae-McKee
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Frank de Wolf
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Roy M Anderson
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
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15
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Koychev I, Vaci N, Bilgel M, An Y, Muniz GT, Wong DF, Gallacher J, Mogekhar A, Albert M, Resnick SM. Prediction of rapid amyloid and phosphorylated‐Tau accumulation in cognitively healthy individuals. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2020; 12:e12019. [PMID: 32211504 DOI: 10.1002/dad2.12019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/31/2020] [Accepted: 02/03/2020] [Indexed: 11/06/2022]
Abstract
Objective To test the hypothesis that among cognitively healthy individuals, distinct groups exist in terms of amyloid and phosphorylated-tau accumulation rates; that if rapid accumulator groups exist, their membership can be predicted by Alzheimer's disease (AD) risk factors, and that time points of significant increase in AD protein accumulation will be evident. Methods The analysis reports data from 263 individuals from the BIOCARD and 184 individuals from the Baltimore Longitudinal Study of Aging with repeated cerebrospinal fluid (CSF) and positron emission tomography (PET) sampling, respectively. We used latent class mixed-effect models to identify distinct classes of amyloid (CSF and PET) and p-Tau (CSF) accumulation rates and generalized additive modeling to investigate non-linear changes to AD biomarkers. Results For both amyloid and p-Tau latent class models we confirmed the existence of two separate classes: accumulators and non-accumulators. The accumulator and non-accumulator groups differed significantly in terms of baseline AD protein levels and slope of change. APOE ε4 carrier status and episodic memory predicted amyloid class membership. Non-linear models revealed time points of significant increase in the rate of amyloid and p-Tau accumulation whereby APOE ε4 carrier status associated with earlier age at onset of rapid accumulation. Conclusions The current analysis demonstrates the existence of distinct classes of amyloid and p-Tau accumulators. Predictors of class membership were identified but the overall accuracy of the models was modest, highlighting the need for additional biomarkers that are sensitive to early disease phenotypes.
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Affiliation(s)
- Ivan Koychev
- Department of Psychiatry University of Oxford Oxford UK
| | - Nemanja Vaci
- Department of Psychiatry University of Oxford Oxford UK
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health Baltimore Maryland
| | - Yang An
- Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health Baltimore Maryland
| | | | - Dean F Wong
- Department of Radiology Johns Hopkins School of Medicine Baltimore Maryland
| | | | - Abhay Mogekhar
- Department of Neurology Johns Hopkins School of Medicine Baltimore Maryland
| | - Marilyn Albert
- Department of Neurology Johns Hopkins School of Medicine Baltimore Maryland
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health Baltimore Maryland
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16
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Thomas KR, Bangen KJ, Weigand AJ, Edmonds EC, Wong CG, Cooper S, Delano-Wood L, Bondi MW. Objective subtle cognitive difficulties predict future amyloid accumulation and neurodegeneration. Neurology 2020; 94:e397-e406. [PMID: 31888974 PMCID: PMC7079691 DOI: 10.1212/wnl.0000000000008838] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 08/16/2019] [Indexed: 02/07/2023] Open
Abstract
OBJECTIVE To determine the temporal sequence of objectively defined subtle cognitive difficulties (Obj-SCD) in relation to amyloidosis and neurodegeneration, the current study examined the trajectories of amyloid PET and medial temporal neurodegeneration in participants with Obj-SCD relative to cognitively normal (CN) and mild cognitive impairment (MCI) groups. METHOD A total of 747 Alzheimer's Disease Neuroimaging Initiative participants (305 CN, 153 Obj-SCD, 289 MCI) underwent neuropsychological testing and serial amyloid PET and structural MRI examinations. Linear mixed effects models examined 4-year rate of change in cortical 18F-florbetapir PET, entorhinal cortex thickness, and hippocampal volume in those classified as Obj-SCD and MCI relative to CN. RESULT Amyloid accumulation was faster in the Obj-SCD group than in the CN group; the MCI and CN groups did not significantly differ from each other. The Obj-SCD and MCI groups both demonstrated faster entorhinal cortical thinning relative to the CN group; only the MCI group exhibited faster hippocampal atrophy than CN participants. CONCLUSION Relative to CN participants, Obj-SCD was associated with faster amyloid accumulation and selective vulnerability of entorhinal cortical thinning, whereas MCI was associated with faster entorhinal and hippocampal atrophy. Findings suggest that Obj-SCD, operationally defined using sensitive neuropsychological measures, can be identified prior to or during the preclinical stage of amyloid deposition. Further, consistent with the Braak neurofibrillary staging scheme, Obj-SCD status may track with early entorhinal pathologic changes, whereas MCI may track with more widespread medial temporal change. Thus, Obj-SCD may be a sensitive and noninvasive predictor of encroaching amyloidosis and neurodegeneration, prior to frank cognitive impairment associated with MCI.
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Affiliation(s)
- Kelsey R Thomas
- From Veterans Affairs San Diego Healthcare System (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.); Department of Psychiatry (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.), University of California, San Diego, School of Medicine, La Jolla; and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology (A.J.W.)
| | - Katherine J Bangen
- From Veterans Affairs San Diego Healthcare System (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.); Department of Psychiatry (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.), University of California, San Diego, School of Medicine, La Jolla; and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology (A.J.W.)
| | - Alexandra J Weigand
- From Veterans Affairs San Diego Healthcare System (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.); Department of Psychiatry (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.), University of California, San Diego, School of Medicine, La Jolla; and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology (A.J.W.)
| | - Emily C Edmonds
- From Veterans Affairs San Diego Healthcare System (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.); Department of Psychiatry (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.), University of California, San Diego, School of Medicine, La Jolla; and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology (A.J.W.)
| | - Christina G Wong
- From Veterans Affairs San Diego Healthcare System (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.); Department of Psychiatry (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.), University of California, San Diego, School of Medicine, La Jolla; and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology (A.J.W.)
| | - Shanna Cooper
- From Veterans Affairs San Diego Healthcare System (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.); Department of Psychiatry (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.), University of California, San Diego, School of Medicine, La Jolla; and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology (A.J.W.)
| | - Lisa Delano-Wood
- From Veterans Affairs San Diego Healthcare System (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.); Department of Psychiatry (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.), University of California, San Diego, School of Medicine, La Jolla; and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology (A.J.W.)
| | - Mark W Bondi
- From Veterans Affairs San Diego Healthcare System (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.); Department of Psychiatry (K.R.T., K.J.B., A.J.W., E.C.E., C.G.W., S.C., L.D.-W., M.W.B.), University of California, San Diego, School of Medicine, La Jolla; and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology (A.J.W.).
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17
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Wisch JK, Roe CM, Babulal GM, Schindler SE, Fagan AM, Benzinger TL, Morris JC, Ances BM. Resting State Functional Connectivity Signature Differentiates Cognitively Normal from Individuals Who Convert to Symptomatic Alzheimer's Disease. J Alzheimers Dis 2020; 74:1085-1095. [PMID: 32144983 PMCID: PMC7183885 DOI: 10.3233/jad-191039] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Changes in resting state functional connectivity (rs-fc) occur in Alzheimer's disease (AD), but few longitudinal rs-fc studies have been performed. Most studies focus on single networks and not a global measure of rs-fc. Although the amyloid tau neurodegeneration (AT(N)) framework is increasingly utilized by the AD community, few studies investigated when global rs-fc signature changes occur within this model. OBJECTIVE 1) Identify a global rs-fc signature that differentiates cognitively normal (CN) individuals from symptomatic AD. 2) Assess when longitudinal changes in rs-fc occur relative to conversion to symptomatic AD. 3) Compare rs-fc with amyloid, tau, and neurodegeneration biomarkers. METHODS A global rs-fc signature composed of intra-network connections was longitudinally evaluated in a cohort of cognitively normal participants at baseline (n = 335). Biomarkers, including cerebrospinal fluid (Aβ42 and tau), structural magnetic resonance imaging, and positron emission tomography were obtained. RESULTS Global rs-fc signature distinguished CN individuals from individuals who developed symptomatic AD. Changes occurred nearly four years before conversion to symptomatic AD. The global rs-fc signature most strongly correlated with markers of neurodegeneration. CONCLUSION The global rs-fc signature changes near symptomatic onset and is likely a neurodegenerative biomarker. Rs-fc changes could serve as a biomarker for evaluating potential therapies for symptomatic conversion to AD.
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Affiliation(s)
- Julie K Wisch
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Catherine M Roe
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Ganesh M Babulal
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Hope Center, Washington University in Saint Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L Benzinger
- Department of Radiology, Washington University in St. Louis St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Beau M Ances
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis St. Louis, MO, USA
- Hope Center, Washington University in Saint Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
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18
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Haller S, Montandon ML, Rodriguez C, Garibotto V, Herrmann FR, Giannakopoulos P. Hippocampal Volume Loss, Brain Amyloid Accumulation, and APOE Status in Cognitively Intact Elderly Subjects. NEURODEGENER DIS 2019; 19:139-147. [PMID: 31846965 DOI: 10.1159/000504302] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 10/21/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Hippocampal volume loss (HVL), PET-documented brain amyloid accumulation, and APOE-ε4 status are predictive biomarkers of the transition from mild cognitive impairment to Alzheimer disease (AD). In asymptomatic cases, the role of these biomarkers remains ambiguous. In contrast to the idea that HVL occurs in late phases of neurodegeneration, recent contributions indicate that it might occur before abnormal amyloid PET occurrence in elderly subjects and that its severity could be only marginally related to APOE variants. Using a longitudinal design, we examined the determinants of HVL in our sample, i.e., brain amyloid burden and the presence of APOE-ε4, and made a longitudinal assessment of cognitive functions. METHODS We performed a 4.5-year longitudinal study on 81 elderly community dwellers (all right-handed;, 48 (59.3%) women; mean age 73.7 ± 3.7 years) including MRI at baseline and follow-up, PET amyloid during follow-up, neuropsychological assessment at 18 and 54 months, and APOE genotyping. All cases were assessed using a continuous cognitive score (CCS) that took into account the global evolution of neuropsychological performance. Linear regression models were used to identify predictors of HVL. RESULTS There was a negative association between the CCS and HVL bilaterally. In multivariate models adjusting for demographic variables, the presence of APOE-ε4 was related to increased HVL bilaterally. A trend of significance was observed with respect to the impact of amyloid positivity on HVL in the left hemisphere. No significant interaction was found between amyloid positivity and the APOE-ε4 allele. CONCLUSION The progressive decrement of neuropsychological performance is associated with HVL long before the emergence of clinically overt symptoms. In this cohort of healthy individuals, the presence of the APOE-ε4 allele was shown to be an independent predictor of worst hippocampal integrity in asymptomatic cases independently of amyloid positivity.
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Affiliation(s)
- Sven Haller
- CIRD Centre d'Imagerie Rive Droite, Geneva, Switzerland, .,Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden, .,Faculty of Medicine, University of Geneva, Geneva, Switzerland,
| | - Marie-Louise Montandon
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.,Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Cristelle Rodriguez
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Division of Institutional Measures, Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - Valentina Garibotto
- Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland
| | - François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Panteleimon Giannakopoulos
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Division of Institutional Measures, Medical Direction, Geneva University Hospitals, Geneva, Switzerland
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19
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Chen H, Shi M, Zhang H, Zhang YD, Geng W, Jiang L, Wang Z, Chen YC, Yin X. Different Patterns of Functional Connectivity Alterations Within the Default-Mode Network and Sensorimotor Network in Basal Ganglia and Pontine Stroke. Med Sci Monit 2019; 25:9585-9593. [PMID: 31838483 PMCID: PMC6929567 DOI: 10.12659/msm.918185] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Background The aim of this study was to investigate whether patients with basal ganglia stroke and patients with pontine stroke have different types of functional connectivity (FC) alterations in the early chronic phase. Material/Methods We included 14 patients with pontine stroke, 17 patients with basal ganglia stroke, and 20 well-matched healthy controls (HCs). All of them underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. The independent component analysis (ICA) approach was applied to extract information regarding the default-mode network (DMN), including anterior DMN (aDMN) and posterior DMN (pDMN) components and the sensorimotor network (SMN). Results Compared with HCs, patients with basal ganglia stroke exhibited significantly reduced FC in the left precuneus of the pDMN, right supplementary motor area (SMA), and right superior frontal gyrus (SFG) of the SMN. Additionally, FC in the left medial prefrontal gyrus (MFG) of the aDMN, right precuneus and right posterior cingulate cortex (PCC) of the pDMN, and left middle cingulate gyrus (mid-CC) of the SMN decreased in patients with pontine stroke. Conclusions The different patterns of FC damage in patients with basal ganglia stroke and patients with pontine stroke in the early chronic phase may provide a new method for investigating lesion-induced network plasticity.
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Affiliation(s)
- Huiyou Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
| | - Mengye Shi
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
| | - Hong Zhang
- Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
| | - Ying-Dong Zhang
- Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
| | - Wen Geng
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
| | - Liang Jiang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
| | - Zhengqian Wang
- Department of Radiology, Lianshui County People's Hospital, Huai'an, Jiangsu, China (mainland)
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
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