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Du Y, Nie J, Zhang J, Fang Y, Wei W, Wang J, Zhang S, Wang J, Li X. Disrupted topological organization of the default mode network in mild cognitive impairment with subsyndromal depression: A graph theoretical analysis. CNS Neurosci Ther 2024; 30:e14547. [PMID: 38105496 PMCID: PMC11017411 DOI: 10.1111/cns.14547] [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: 12/03/2022] [Revised: 10/26/2023] [Accepted: 11/20/2023] [Indexed: 12/19/2023] Open
Abstract
AIMS Subsyndromal depression (SSD) is common in mild cognitive impairment (MCI). However, the neural mechanisms underlying MCI with SSD (MCID) are unclear. The default mode network (DMN) is associated with cognitive processes and depressive symptoms. Therefore, we aimed to explore the topological organization of the DMN in patients with MCID. METHODS Forty-two MCID patients, 34 MCI patients without SSD (MCIND), and 36 matched healthy controls (HCs) were enrolled. The resting-state functional connectivity of the DMN of the participants was analyzed using a graph theoretical approach. Correlation analyses of network topological metrics, depressive symptoms, and cognitive function were conducted. Moreover, support vector machine (SVM) models were constructed based on topological metrics to distinguish MCID from MCIND. Finally, we used 10 repeats of 5-fold cross-validation for performance verification. RESULTS We found that the global efficiency and nodal efficiency of the left anterior medial prefrontal cortex (aMPFC) of the MCID group were significantly lower than the MCIND group. Moreover, small-worldness and global efficiency were negatively correlated with depressive symptoms in MCID, and the nodal efficiency of the left lateral temporal cortex and left aMPFC was positively correlated with cognitive function in MCID. In cross-validation, the SVM model had an accuracy of 0.83 [95% CI 0.79-0.87], a sensitivity of 0.88 [95% CI 0.86-0.90], a specificity of 0.75 [95% CI 0.72-0.78] and an area under the curve of 0.88 [95% CI 0.85-0.91]. CONCLUSIONS The coexistence of MCI and SSD was associated with the greatest disrupted topological organization of the DMN. The network topological metrics could identify MCID and serve as biomarkers of different clinical phenotypic presentations of MCI.
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Affiliation(s)
- Yang Du
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Jing Nie
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Jian‐Ye Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yuan Fang
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Wen‐Jing Wei
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Jing‐Hua Wang
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Shao‐Wei Zhang
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
| | - Jin‐Hong Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Xia Li
- Department of Geriatric Psychiatry, Shanghai Mental Health CenterShanghai Jiao Tong University School of MedicineShanghaiChina
- Alzheimer's Disease and Related Disorders CenterShanghai Jiao Tong UniversityShanghaiChina
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Hsieh CJ, Chiou JM, Chen TF, Chen YC, Chen JH. Association of subclinical depressive symptoms and sleep with cognition in the community-dwelling older adults. J Formos Med Assoc 2023:S0929-6646(23)00072-4. [PMID: 36964100 DOI: 10.1016/j.jfma.2023.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 02/11/2023] [Accepted: 03/07/2023] [Indexed: 03/26/2023] Open
Abstract
BACKGROUND /Purpose: This study aimed to explore the association of subclinical depressive symptoms and sleep with cognition in community-dwelling Taiwanese older adults. METHODS This four-year prospective cohort study (2015-2019) included 379 participants aged 65 years or older from the annual senior health checkup program at National Taiwan University Hospital who were followed up two years later. Global and domain cognitive functions were assessed using validated neuropsychological tests. Depressive symptoms were evaluated using the Center for Epidemiologic Studies Depression (CES-D) Scale. Sleep quality was evaluated using the Pittsburg Sleep Quality Index (PSQI). Excessive daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS). Generalized linear mixed models were used to explore the associations of subclinical depressive symptoms and sleep variables with cognition, adjusting for important covariates. Stratification analyses were performed using the sleep variables. RESULTS Over time, depressive symptoms were associated with poor performance of memory (βˆ = 0.24, P = 0.04) and executive function (βˆ = -0.24, P = 0.03). Poor sleep quality (elevated PSQI score) was associated with poor memory performance (βˆ = -0.04 to -0.03, P < 0.05). Excessive daytime sleepiness (elevated ESS score) was associated with poor performance of memory (βˆ = -0.02, P < 0.05) and executive function (βˆ = -0.02, P = 0.001). At baseline, better sleep quality and no excessive daytime sleepiness were associated with better memory performance over time. CONCLUSION Subclinical depressive symptoms, worse sleep quality, and excessive daytime sleepiness were differentially associated with impairment of cognitive domains (mainly memory and executive function).
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Affiliation(s)
- Ching-Jow Hsieh
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Taoyuan Psychiatric Center, Ministry of Health and Welfare, Taoyuan, Taiwan
| | - Jeng-Min Chiou
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Ta-Fu Chen
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Yen-Ching Chen
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan.
| | - Jen-Hau Chen
- Department of Geriatrics and Gerontology, National Taiwan University Hospital, Taipei, Taiwan; Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
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Yoon EJ, Lee JY, Kwak S, Kim YK. Mild behavioral impairment linked to progression to Alzheimer's disease and cortical thinning in amnestic mild cognitive impairment. Front Aging Neurosci 2023; 14:1051621. [PMID: 36688162 PMCID: PMC9846631 DOI: 10.3389/fnagi.2022.1051621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 11/28/2022] [Indexed: 01/06/2023] Open
Abstract
Background Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of sustained neuropsychiatric symptoms, as an at-risk state for dementia. However, the associations between MBI and a risk of progression to Alzheimer's disease (AD) and its neuroanatomical correlates in mild cognitive impairment (MCI) are still unclear. Method A total 1,184 older adults with amnestic MCI was followed for a mean of 3.1 ± 2.0 years. MBI was approximated using a transformation algorithm for the Neuropsychiatric Inventory at baseline. A two-step cluster analysis was used to identify subgroups of individuals with amnestic MCI based on profiles of 5 MBI domain symptoms (decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, abnormal perception/thought content). A Cox regression analysis was applied to investigate differences in the risk of progression to AD between subgroups. A subset of participants (n = 202) underwent 3D T1-weighted MRI scans at baseline and cortical thickness was compared between the subgroups of amnestic MCI patients. Result The cluster analysis classified the patients into 3 groups: (1) patients without any MBI domain symptoms (47.4%, asymptomatic group); (2) those with only affective dysregulation (29.4%, affective dysregulation group); (3) those with multiple MBI domain symptoms, particularly affective dysregulation, decreased motivation and impulse dyscontrol (23.2%, complex group). Compared to the asymptomatic group, the complex group was associated with a higher risk of progression to AD (hazard ratio = 2.541 [1.904-3.392], p < 0.001), but the affective dysregulation group was not (1.214 [0.883-1.670], p = 0.232). In cortical thickness analysis, the complex group revealed cortical thinning bilaterally in the inferior parietal, lateral occipital, lateral superior temporal, and frontopolar regions compared with the affective dysregulation group. Conclusion The multiple co-occuring MBI domains in individuals with amnestic MCI are associated with a higher risk of progression to AD and cortical thinning in temporal, parietal and frontal areas. These results suggest that evaluation of MBI could be useful for risk stratification for AD and appropriate intervention in MCI individuals.
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Affiliation(s)
- Eun Jin Yoon
- Memory Network Medical Research Center, Seoul National University, Seoul, South Korea,Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Jun-Young Lee
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea,Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea,Department of Medical Device Development, Seoul National University College of Medicine, Seoul, South Korea
| | - Seyul Kwak
- Department of Psychology, Pusan National University, Busan, South Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea,Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, South Korea,*Correspondence: Yu Kyeong Kim,
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Du Y, Yan F, Zhao L, Fang Y, Qiu Q, Wei W, Wang J, Tang Y, Lin X, Li X. Depression symptoms moderate the relationship between gray matter volumes and cognitive function in patients with mild cognitive impairment. J Psychiatr Res 2022; 151:516-522. [PMID: 35636026 DOI: 10.1016/j.jpsychires.2022.05.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 04/22/2022] [Accepted: 05/19/2022] [Indexed: 10/18/2022]
Abstract
Previous studies have demonstrated that decreased gray matter volume (GMV) correlates with cognitive function in elderly patients with mild cognitive impairment (MCI). However, it is unclear whether those correlations are present in MCI patients with depressive symptoms (MCID). This study investigated the association among depressive symptoms, GMV and cognitive function. We included 210 participants, namely, 70 elderly MCID patients, 70 MCI patients without depressive symptoms (MCIND) and 70 healthy controls (HCs). Voxel-based morphometry (VBM) was used to investigate the structural disruptions among the patients in the three groups, and correlation analysis was performed between the GMV of regions showing group differences and cognitive function. Moderation analyses were conducted to verify the conditional effect of depressive symptoms on the relationship between structural changes and cognitive function. We found decreased GMV in the bilateral fusiform gyrus, inferior temporal gyrus, parahippocampal gyrus, and hippocampus in the MCIND group compared to the HC group. Moreover, we identified decreased GMV in the bilateral fusiform gyrus in the elderly MCID patients compared with the elderly MCIND patients, which provides further insights into the neural mechanisms of depressive symptoms in patients with MCID. Most importantly, the severity of depressive symptoms moderated the positive correlation between the GMV of abnormal brain regions and cognitive function. Furthermore, this study is the first report of the moderating effect of depressive symptoms on the GMV of abnormal brain areas and cognitive function in patients with MCID, indicating the significance of clinical intervention in elderly MCI patients with depressive symptoms.
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Affiliation(s)
- Yang Du
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Feng Yan
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Lu Zhao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Yuan Fang
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Qi Qiu
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Wenjing Wei
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Jinghua Wang
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiang Lin
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China.
| | - Xia Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China.
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Barca ML, Alnæs D, Engedal K, Persson K, Eldholm RS, Siafarikas N, Selseth Almdahl I, Stylianou-Korsnes M, Saltvedt I, Selbæk G, Westlye LT. Brain Morphometric Correlates of Depressive Symptoms among Patients with and without Dementia. Dement Geriatr Cogn Dis Extra 2022; 12:107-114. [PMID: 35950148 PMCID: PMC9251457 DOI: 10.1159/000521114] [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: 11/15/2021] [Accepted: 11/21/2021] [Indexed: 12/02/2022] Open
Abstract
Introduction Findings regarding brain morphometry among patients with dementia and concomitant depressive symptoms have been inconsistent. Thus, the aim of the present study was to test the hypothesis that dementia and concomitant depressive symptoms are associated with structural brain changes in the temporal lobe measured with structural magnetic resonance imaging (MRI). Methods A sample of 492 patients from Norwegian memory clinics (n = 363) and Old Age Psychiatry services (n = 129) was studied. The assessment included the Cornell Scale for Depression in Dementia (CSDD), Instrumental Activities of Daily Living Scale, Mini Mental State Examination, and MRI of the brain, processed with FreeSurfer to derive ROI measures of cortical thickness, volume, and area using the Desikan-Killiany parcellation, as well as subcortical volumes. Dementia was diagnosed according to ICD-10 research criteria. Correlates of brain morphometry using multiple linear regression were examined. Results Higher scores on the CSDD were associated with larger cortical volume (β = 0.125; p value = 0.003) and area of the left isthmus of the cingulate gyrus (β = 0.151; p value = <0.001) across all patients. Inclusion of an interaction term (dementia × CSDD) revealed a smaller area in the left temporal pole (β = −0.345; p value = 0.001) and right-transverse temporal cortex (β = −0.321; p value = 0.001) in patients with dementia and depressive symptoms. Discussion/Conclusion We confirm the previous findings of structural brain changes in temporal regions among patients with dementia and concomitant depressive symptoms. This may contribute to a better understanding of the mechanisms underlying depression in dementia. To the best of our knowledge, this is the largest study conducted on this topic to date.
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Affiliation(s)
- Maria Lage Barca
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- *Maria Lage Barca,
| | - Dag Alnæs
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Bjørknes College, Oslo, Norway
| | - Knut Engedal
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Karin Persson
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Rannveig Sakshaug Eldholm
- Department of Neuromedicine and Movement Science, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Nikias Siafarikas
- Department of Geriatric Psychiatry, Akershus University Hospital, Lørenskog, Norway
| | - Ina Selseth Almdahl
- Department of Old Age Psychiatry, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Maria Stylianou-Korsnes
- Department of Old Age Psychiatry, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ingvild Saltvedt
- Department of Neuromedicine and Movement Science, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Geriatric Department, St. Olav Hospital, University Hospital of Trondheim, Trondheim, Norway
| | - Geir Selbæk
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Lars T. Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
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6
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Roberto N, Portella MJ, Marquié M, Alegret M, Hernández I, Mauleón A, Rosende-Roca M, Abdelnour C, Esteban de Antonio E, Tartari JP, Vargas L, López-Cuevas R, Bojaryn U, Espinosa A, Ortega G, Pérez-Cordón A, Sanabria Á, Orellana A, de Rojas I, Moreno-Grau S, Montrreal L, Alarcón-Martín E, Ruíz A, Tárraga L, Boada M, Valero S. Neuropsychiatric Profile as a Predictor of Cognitive Decline in Mild Cognitive Impairment. Front Aging Neurosci 2021; 13:718949. [PMID: 34955804 PMCID: PMC8693625 DOI: 10.3389/fnagi.2021.718949] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 10/28/2021] [Indexed: 11/13/2022] Open
Abstract
Introduction: Mild cognitive impairment is often associated with affective and other neuropsychiatric symptoms (NPS). This co-occurrence might have a relevant impact on disease progression, from MCI to dementia. Objective: The aim of this study was to explore the trajectories of cognitive decline in an MCI sample from a memory clinic, taking into consideration a perspective of isolated cognitive functions and based on NPS clusters, accounting for the different comorbid symptoms collected at their baseline visit. Methods: A total of 2,137 MCI patients were monitored over a 2.4-year period. Four clusters of NPS (i.e., Irritability, Apathy, Anxiety/Depression and Asymptomatic) were used to run linear mixed models to explore the interaction of cluster with time on cognitive trajectories using a comprehensive neuropsychological battery (NBACE) administered at baseline and at the three subsequent follow-ups. Results: A significant interaction between cluster and time in cognitive decline was found when verbal learning and cued-recall were explored (p = 0.002 for both memory functions). For verbal learning, the Irritability cluster had the largest effect size (0.69), whereas the Asymptomatic cluster showed the smallest effect size (0.22). For cued-recall, the Irritability cluster had the largest effect size among groups (0.64), and Anxiety/Depression had the smallest effect size (0.21). Conclusions: In MCI patients, the Irritability and Apathy NPS clusters shared similar patterns of worsening in memory functioning, which could point to these NPS as risk factors of a faster cognitive decline, acting as early prognostic markers and helping in the diagnostic process.
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Affiliation(s)
- Natalia Roberto
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Maria J Portella
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain.,Department of Psychiatry, Institut d'Investigació Biomèdica Sant Pau (IIB Sant Pau), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.,Networking Research Center on Mental Health (CIBERSAM), Madrid, Spain
| | - Marta Marquié
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Montserrat Alegret
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Isabel Hernández
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Ana Mauleón
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Maitee Rosende-Roca
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Carla Abdelnour
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | | | - Juan P Tartari
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Liliana Vargas
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Rogelio López-Cuevas
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Urszula Bojaryn
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Ana Espinosa
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Gemma Ortega
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Alba Pérez-Cordón
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Ángela Sanabria
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Adelina Orellana
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Itziar de Rojas
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Sonia Moreno-Grau
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Laura Montrreal
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Emilio Alarcón-Martín
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Agustín Ruíz
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Lluís Tárraga
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Mercè Boada
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Sergi Valero
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Networking Research Center on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
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Achour M, Ferdousi F, Sasaki K, Isoda H. Luteolin Modulates Neural Stem Cells Fate Determination: In vitro Study on Human Neural Stem Cells, and in vivo Study on LPS-Induced Depression Mice Model. Front Cell Dev Biol 2021; 9:753279. [PMID: 34790666 PMCID: PMC8591246 DOI: 10.3389/fcell.2021.753279] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 10/11/2021] [Indexed: 11/23/2022] Open
Abstract
Luteolin is a natural flavone with neurotrophic effects observed on different neuronal cell lines. In the present study, we aimed to assess the effect of luteolin on hNSCs fate determination and the LPS-induced neuroinflammation in a mouse model of depression with astrocytogenesis defect. hNSCs were cultured in basal cell culture medium (control) or medium supplemented with luteolin or AICAR, a known inducer of astrogenesis. A whole-genome transcriptomic analysis showed that luteolin upregulated the expressions of genes related to neurotrophin, dopaminergic, hippo, and Wnt signaling pathways, and downregulated the genes involved in p53, TNF, FOXO, and Notch signaling pathways. We also found that astrocyte-specific gene GFAP, as well as other genes of the key signaling pathways involved in astrogenesis such as Wnt, BMP, and JAK-STAT pathways were upregulated in luteolin-treated hNSCs. On the other hand, neurogenesis and oligodendrogenesis-related genes, TUBB3, NEUROD 1 and 6, and MBP, were downregulated in luteolin-treated hNSCs. Furthermore, immunostaining showed that percentages of GFAP+ cells were significantly higher in luteolin- and AICAR-treated hNSCs compared to control hNSCs. Additionally, RT-qPCR results showed that luteolin upregulated the expressions of GFAP, BMP2, and STAT3, whereas the expression of TUBB3 remained unchanged. Next, we evaluated the effects of luteolin in LPS-induced mice model of depression that represents defects in astrocytogenesis. We found that oral administration of luteolin (10 mg/Kg) for eight consecutive days could decrease the immobility time on tail suspension test, a mouse behavioral test measuring depression-like behavior, and attenuate LPS-induced inflammatory responses by significantly decreasing IL-6 production in mice brain-derived astrocytes and serum, and TNFα and corticosterone levels in serum. Luteolin treatment also significantly increased mature BDNF, dopamine, and noradrenaline levels in the hypothalamus of LPS-induced depression mice. Though the behavioral effects of luteolin did not reach statistical significance, global gene expression analyses of mice hippocampus and brain-derived NSCs highlighted the modulatory effects of luteolin on different signaling pathways involved in the pathophysiology of depression. Altogether, our findings suggest an astrocytogenic potential of luteolin and its possible therapeutic benefits in neuroinflammatory and neurodegenerative diseases. However, further studies are required to identify the specific mechanism of action of luteolin.
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Affiliation(s)
- Mariem Achour
- Laboratory of Metabolic Biophysics and Applied Pharmacology, Faculty of Medicine of Sousse, University of Sousse, Sousse, Tunisia.,Alliance for Research on the Mediterranean and North Africa (ARENA), University of Tsukuba, Tsukuba, Japan
| | - Farhana Ferdousi
- Alliance for Research on the Mediterranean and North Africa (ARENA), University of Tsukuba, Tsukuba, Japan.,Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan.,National Institute of Advanced Industrial Science and Technology (AIST)-University of Tsukuba Open Innovation Laboratory for Food and Medicinal Resource Engineering (FoodMed-OIL), University of Tsukuba, Tsukuba, Japan
| | - Kazunori Sasaki
- Alliance for Research on the Mediterranean and North Africa (ARENA), University of Tsukuba, Tsukuba, Japan.,National Institute of Advanced Industrial Science and Technology (AIST)-University of Tsukuba Open Innovation Laboratory for Food and Medicinal Resource Engineering (FoodMed-OIL), University of Tsukuba, Tsukuba, Japan
| | - Hiroko Isoda
- Alliance for Research on the Mediterranean and North Africa (ARENA), University of Tsukuba, Tsukuba, Japan.,Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan.,National Institute of Advanced Industrial Science and Technology (AIST)-University of Tsukuba Open Innovation Laboratory for Food and Medicinal Resource Engineering (FoodMed-OIL), University of Tsukuba, Tsukuba, Japan
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8
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Oh DJ, Han JW, Bae JB, Kim TH, Kwak KP, Kim BJ, Kim SG, Kim JL, Moon SW, Park JH, Ryu SH, Youn JC, Lee DY, Lee DW, Lee SB, Lee JJ, Jhoo JH, Kim KW. Chronic subsyndromal depression and risk of dementia in older adults. Aust N Z J Psychiatry 2021; 55:809-816. [PMID: 33198490 DOI: 10.1177/0004867420972763] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVES Subsyndromal depression is prevalent and associated with poor outcomes in late life, but its effect on the risk of dementia has barely been investigated. This study is aimed to investigate the effect of subsyndromal depression on dementia risk in cognitively normal older adults and patients with mild cognitive impairment. METHODS Data were collected from a nationwide, population-based, prospective cohort study on a randomly sampled Korean elderly population aged 60 years or older, which has been followed every 2 years. Using 6-year follow-up data of 4456 non-demented elderly, the authors examined the risk of dementia associated with late-onset subsyndromal depression using multivariate Cox proportional hazard models. After standardized diagnostic interviews, subsyndromal depression and dementia were diagnosed by the operational diagnostic criteria and Diagnostic and Statistical Manual of Mental Disorders, 4th edition criteria, respectively. RESULTS Subsyndromal depression tripled the risk of dementia in non-demented elderly individuals (hazard ratio = 3.02, 95% confidence interval = [1.56, 5.85], p < 0.001). In subgroup analyses, subsyndromal depression was associated with the risk of dementia in cognitively normal participants only (hazard ratio = 4.59, 95% confidence interval = [1.20, 17.54], p = 0.026); chronic/recurrent subsyndromal depression with increasing severity during the follow-up period was associated with the risk of dementia (hazard ratio = 15.34, 95% confidence interval = [4.19, 56.18], p < 0.001). CONCLUSION Late-onset subsyndromal depression is a potential predictor of incident dementia when it is chronic or recurrent with increasing severity in cognitively normal older adults.
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Affiliation(s)
- Dae Jong Oh
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, South Korea.,Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggido, South Korea
| | - Jong Bin Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggido, South Korea
| | - Tae Hui Kim
- Department of Psychiatry, Yonsei University Wonju Severance Christian Hospital, Wonju, South Korea
| | - Kyung Phil Kwak
- Department of Psychiatry, Dongguk University Gyeongju Hospital, Gyeongju, South Korea
| | - Bong Jo Kim
- Department of Psychiatry, School of Medicine, Gyeongsang National University, Jinju, South Korea
| | - Shin Gyeom Kim
- Department of Neuropsychiatry, Soonchunhyang University Bucheon Hospital, Bucheon, South Korea
| | - Jeong Lan Kim
- Department of Psychiatry, School of Medicine, Chungnam National University, Daejeon, South Korea
| | - Seok Woo Moon
- Department of Psychiatry, School of Medicine, Konkuk University, Konkuk University Chungju Hospital, Chungju, South Korea
| | - Joon Hyuk Park
- Department of Neuropsychiatry, Jeju National University Hospital, Jeju, South Korea
| | - Seung-Ho Ryu
- Department of Psychiatry, School of Medicine, Konkuk University, Konkuk University Medical Center, Seoul, South Korea
| | - Jong Chul Youn
- Department of Neuropsychiatry, Kyunggi Provincial Hospital for the Elderly, Yongin, South Korea
| | - Dong Young Lee
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, South Korea.,Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | - Dong Woo Lee
- Department of Neuropsychiatry, Inje University Sanggye Paik Hospital, Seoul, South Korea
| | - Seok Bum Lee
- Department of Psychiatry, Dankook University Hospital, Cheonan, South Korea
| | - Jung Jae Lee
- Department of Psychiatry, Dankook University Hospital, Cheonan, South Korea
| | - Jin Hyeong Jhoo
- Department of Psychiatry, School of Medicine, Kangwon National University, Chuncheon, South Korea
| | - Ki Woong Kim
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, South Korea.,Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggido, South Korea.,Department of Brain and Cognitive Science, College of Natural Sciences, Seoul National University, Seoul, South Korea
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9
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Mackin RS, Insel PS, Landau S, Bickford D, Morin R, Rhodes E, Tosun D, Rosen HJ, Butters M, Aisen P, Raman R, Saykin A, Toga A, Jack C, Koeppe R, Weiner MW, Nelson C. Late-Life Depression Is Associated With Reduced Cortical Amyloid Burden: Findings From the Alzheimer's Disease Neuroimaging Initiative Depression Project. Biol Psychiatry 2021; 89:757-765. [PMID: 32980132 PMCID: PMC10165941 DOI: 10.1016/j.biopsych.2020.06.017] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 05/26/2020] [Accepted: 06/09/2020] [Indexed: 11/12/2022]
Abstract
BACKGROUND We evaluated the role of cortical amyloid deposition as a factor contributing to memory dysfunction and increased risk of dementia associated with late-life depression (LLD). METHODS A total of 119 older adult participants with a current diagnosis of major depression (LLD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) Depression Project study and 119 nondepressed (ND) cognitively unimpaired participants matched on age, sex, and APOE genotype were obtained from the ADNI database. RESULTS Thirty-three percent of LLD participants met ADNI criteria for mild cognitive impairment. Compared with ND individuals, the LLD group exhibited less global amyloid beta (Aβ) accumulation (p = .05). The proportion of amyloid positivity in the LLD group was 19.3% compared with 31.1% for the ND participants (p = .02). Among LLD participants, global Aβ was not associated with lifetime number of depressive episodes, lifetime length of depression, length of lifetime selective serotonin reuptake inhibitor use, or lifetime length of untreated depression (p > .21 for all). Global Aβ was associated with worse memory performance (p = .05). Similar results were found in secondary analyses restricting comparisons to the cognitively unimpaired LLD participants as well as when comparing the LLD group with an ND group that included participants with mild cognitive impairment. CONCLUSIONS Contrary to expectation, the LLD group showed less Aβ deposition than the ND group and Aβ deposition was not associated with depression history characteristics. Aβ was associated with memory, but this relationship did not differ between LLD and ND. Our results suggest that memory deficits and accelerated cognitive decline reported in previous studies of LLD are not due to greater cortical Aβ accumulation.
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Affiliation(s)
- R Scott Mackin
- Department of Psychiatry, University of California, San Francisco, California; Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, California.
| | - Philip S Insel
- Department of Psychiatry, University of California, San Francisco, California; Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, California
| | - David Bickford
- Department of Psychiatry, University of California, San Francisco, California
| | - Ruth Morin
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, California
| | - Emma Rhodes
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, California
| | - Duygu Tosun
- Department of Radiology, University of California, San Francisco, California; Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, California
| | - Howie J Rosen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, California
| | - Meryl Butters
- Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Paul Aisen
- Department of Neurology, University of Southern California, San Diego, California; Alzheimer's Therapeutic Research Institute, San Diego, California
| | - Rema Raman
- Department of Neurology, University of Southern California, San Diego, California; Alzheimer's Therapeutic Research Institute, San Diego, California
| | - Andrew Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana
| | - Arthur Toga
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California
| | | | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Michael W Weiner
- Department of Psychiatry, University of California, San Francisco, California; Department of Radiology, University of California, San Francisco, California; Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, California
| | - Craig Nelson
- Department of Psychiatry, University of California, San Francisco, California
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10
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Lang M, Rosselli M, Greig MT, Torres VL, Vélez-Uribe I, Arruda F, Barker WW, Garcia P, Loewenstein DA, Curiel RE, Duara R. Depression and the Diagnosis of MCI in a Culturally Diverse Sample in the United States. Arch Clin Neuropsychol 2021; 36:214-230. [PMID: 31729523 PMCID: PMC7881973 DOI: 10.1093/arclin/acz043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Revised: 04/10/2019] [Accepted: 07/30/2019] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE To analyze (1) whether there are ethnic differences in the severity of depressive symptoms between groups of elders classified as cognitively normal (CN) or amnestic mild cognitive impairment (aMCI) and (2) the influence of depressive symptoms on specific cognitive performance by ethnicity across diagnoses, controlling for covariates. METHODS 164 Hispanics residing in the United States (HAs) and European Americans (EAs) (100 women; Mage = 72.1, SD = 8.0) were diagnosed as either CN or aMCI. Depressive symptoms were measured with the Geriatric Depression Scale (GDS-15). Cognition was assessed using the Loewenstein-Acevedo Scales for Semantic Interference and Learning (semantic memory), Multilingual Naming Test (confrontation naming), and the Stroop Test (Color-Word condition; executive function). A 2 × 2 univariate ANCOVA as well as linear and logistic regressions explored differences in depressive symptoms among diagnostic and ethnic groups. RESULTS Higher depression was seen in aMCI compared to the CN group for both ethnicities, after controlling for age, education, gender, and Mini-Mental State Examination score. Greater levels of depression also predicted lower scores in confrontation naming and semantic memory for only the EA group and marginally in scores of executive function for HA participants. GDS-15 scores of ≤ 4 also predicted less likelihood of aMCI diagnosis. CONCLUSIONS Severity of depressive symptoms was associated with greater cognitive impairment, independent of ethnicity. Significant results suggest detrimental effects of depression on clinical diagnoses most evidently for subjects from the EA group.
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Affiliation(s)
- Merike Lang
- Department of Psychology, Florida Atlantic University, Davie, FL, USA
| | - Mónica Rosselli
- Department of Psychology, Florida Atlantic University, Davie, FL, USA
- Florida Alzheimer’s Disease Research Center, Miami Beach, FL, USA
| | - Maria T Greig
- Florida Alzheimer’s Disease Research Center, Miami Beach, FL, USA
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Valeria L Torres
- Department of Psychology, Florida Atlantic University, Davie, FL, USA
| | - Idaly Vélez-Uribe
- Department of Psychology, Florida Atlantic University, Davie, FL, USA
| | - Fernanda Arruda
- Department of Psychology, Florida Atlantic University, Davie, FL, USA
| | - Warren W Barker
- Florida Alzheimer’s Disease Research Center, Miami Beach, FL, USA
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Patricia Garcia
- Florida Alzheimer’s Disease Research Center, Miami Beach, FL, USA
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - David A Loewenstein
- Florida Alzheimer’s Disease Research Center, Miami Beach, FL, USA
- Center for Cognitive Neuroscience and Aging and the Department of Psychiatry & Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Rosie E Curiel
- Florida Alzheimer’s Disease Research Center, Miami Beach, FL, USA
- Center for Cognitive Neuroscience and Aging and the Department of Psychiatry & Behavioral Sciences, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Ranjan Duara
- Florida Alzheimer’s Disease Research Center, Miami Beach, FL, USA
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
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11
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Agüera-Ortiz L, García-Ramos R, Grandas Pérez FJ, López-Álvarez J, Montes Rodríguez JM, Olazarán Rodríguez FJ, Olivera Pueyo J, Pelegrin Valero C, Porta-Etessam J. Depression in Alzheimer's Disease: A Delphi Consensus on Etiology, Risk Factors, and Clinical Management. Front Psychiatry 2021; 12:638651. [PMID: 33716830 PMCID: PMC7953133 DOI: 10.3389/fpsyt.2021.638651] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/27/2021] [Indexed: 12/21/2022] Open
Abstract
Background: Alzheimer's disease (AD) and other forms of dementia are among the most common causes of disability in the elderly. Dementia is often accompanied by depression, but specific diagnostic criteria and treatment approaches are still lacking. This study aimed to gather expert opinions on dementia and depressed patient management to reduce heterogeneity in everyday practice. Methods: Prospective, multicenter, 2-round Modified Delphi survey with 53 questions regarding risk factors (11), signs and symptoms (7), diagnosis (8), and treatment (27) of depression in dementia, with a particular focus on AD. The questionnaire was completed by a panel of 37 expert physicians in neurodegenerative diseases (19 neurologists, 17 psychiatrists, and 1 geriatrician). Results: Consensus was achieved in 40 (75.5%) of the items: agreement in 33 (62.3%) and disagreement in 7 (13.2%) of them. Among the most relevant findings, depression in the elderly was considered an early sign (prodromal) and/or a dementia risk factor, so routine cognitive check-ups in depressed patients should be adopted, aided by clinical scales and information from relatives. Careful interpretation of neuropsychological assessment must be carried out in patients with depression as it can undermine cognitive outcomes. As agreed, depression in early AD is characterized by somatic symptoms and can be differentiated from apathy by the presence of sadness, depressive thoughts and early-morning awakening. In later-phases, symptoms of depression would include sleep-wake cycle reversal, aggressive behavior, and agitation. Regardless of the stage of dementia, depression would accelerate its course, whereas antidepressants would have the opposite effect. Those that improve cognitive function and/or have a dual or multimodal mode of action were preferred: Duloxetine, venlafaxine/desvenlafaxine, vortioxetine, tianeptine, and mirtazapine. Although antidepressants may be less effective than in cognitively healthy patients, neither dosage nor treatment duration should differ. Anti-dementia cholinesterase inhibitors may have a synergistic effect with antidepressants. Exercise and psychological interventions should not be applied alone before any pharmacological treatment, yet they do play a part in improving depressive symptoms in demented patients. Conclusions: This study sheds light on several unresolved clinical challenges regarding depression in dementia patients. Further studies and specific recommendations for this comorbid patient population are still needed.
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Affiliation(s)
- Luis Agüera-Ortiz
- Service of Psychiatry, Instituto de Investigación i+12, Hospital Universitario 12 de Octubre, Madrid, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Rocío García-Ramos
- Movement Disorders Unit, Hospital Clínico San Carlos, Complutense University, Madrid, Spain
| | - Francisco J Grandas Pérez
- Service of Neurology, Hospital General Universitario Gregorio Marañón, Complutense University, Madrid, Spain
| | - Jorge López-Álvarez
- Service of Psychiatry, Instituto de Investigación i+12, Hospital Universitario 12 de Octubre, Madrid, Spain
| | | | - F Javier Olazarán Rodríguez
- Service of Neurology, HGU Gregorio Marañón, Madrid, Spain.,Memory Disorders Unit, HM Hospitales, Madrid, Spain
| | | | - Carmelo Pelegrin Valero
- Service of Psychiatry, Hospital Universitario San Jorge, Huesca, Spain.,University of Zaragoza Associate Professor, Zaragoza, Spain
| | - Jesús Porta-Etessam
- Service of Neurology, Instituto de Neurociencias, Hospital Clínico San Carlos, San Carlos, IdISSC, Madrid, Spain
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12
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Gonzales MM, Samra J, O’Donnell A, Mackin RS, Salinas J, Jacob M, Satizabal CL, Aparicio HJ, Thibault EG, Sanchez JS, Finney R, Rubinstein ZB, Mayblyum DV, Killiany RJ, Decarli CS, Johnson KA, Beiser AS, Seshadri S. Association of Midlife Depressive Symptoms with Regional Amyloid-β and Tau in the Framingham Heart Study. J Alzheimers Dis 2021; 82:249-260. [PMID: 34024836 PMCID: PMC8900661 DOI: 10.3233/jad-210232] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND Depressive symptoms predict increased risk for dementia decades before the emergence of cognitive symptoms. Studies in older adults provide preliminary evidence for an association between depressive symptoms and amyloid-β (Aβ) and tau accumulation. It is unknown if similar alterations are observed in midlife when preventive strategies may be most effective. OBJECTIVE The study aim was to evaluate the association between depressive symptoms and cerebral Aβ and tau in a predominately middle-aged cohort with examination of the apolipoprotein (APOE) ɛ4 allele as a moderator. METHODS Participants included 201 adults (mean age 53±8 years) who underwent 11C-Pittsburgh Compound B amyloid and 18F-Flortaucipir tau positron emission tomography (PET) imaging. Depressive symptoms were evaluated with the Center for Epidemiological Studies Depression Scale (CES-D) at the time of PET imaging, as well as eight years prior. Associations between depressive symptoms at both timepoints, as well as depression (CES-D≥16), with regional Aβ and tau PET retention were evaluated with linear regression adjusting for age and sex. Interactions with the APOE ɛ4 allele were explored. RESULTS Depressive symptoms and depression were not associated with PET outcomes in the overall sample. However, among APOE ɛ4 allele carriers, there was a significant cross-sectional association between depressive symptoms and increased tau PET uptake in the entorhinal cortex (β= 0.446, SE = 0.155, p = 0.006) and amygdala (β= 0.350, SE = 0.133, p = 0.012). CONCLUSION Although longitudinal studies are necessary, the results suggest that APOE ɛ4 carriers with depressive symptoms may present with higher susceptibility to early tau accumulation in regions integral to affective regulation and memory consolidation.
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Affiliation(s)
- Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center, San Antonio, TX, USA
| | - Jasmeet Samra
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Adrienne O’Donnell
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - R. Scott Mackin
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
- Center for Imaging of Neurodegenerative Disease, Veteran Affairs Administration, San Francisco, CA, USA
| | - Joel Salinas
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA
| | - Mini Jacob
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- The Framingham Heart Study, Framingham, MA, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- The Framingham Heart Study, Framingham, MA, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Hugo J. Aparicio
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Emma G. Thibault
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Justin S. Sanchez
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Zoe B. Rubinstein
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle V. Mayblyum
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ron J. Killiany
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Charlie S. Decarli
- Department of Neurology, University of California Davis, Davis, CA, USA
- Center for Neuroscience, University of California Davis, Davis, CA, USA
| | - Keith A. Johnson
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Alexa S. Beiser
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center, San Antonio, TX, USA
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
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13
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Morin RT, Insel P, Bickford D, Nelson C, Mackin RS. Depression Severity, but Not Cognitive Impairment or Frailty, is Associated with Disability in Late-Life Depression. Clin Gerontol 2020; 43:411-419. [PMID: 31865868 PMCID: PMC9187219 DOI: 10.1080/07317115.2019.1699882] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVES Assess the relationship of cognitive impairment to disability, accounting for depression severity and frailty, among older adults with late-life depression (LLD). METHODS Data were analyzed from 78 community-dwelling older adults with LLD and without dementia (age M = 71.9; SD = 6.1). Cognitive functioning was assessed using a comprehensive neuropsychological battery. Depression severity was measured using the 17-item Hamilton Depression Rating Scale (HDRS; cutoff ≥15). Frailty was assessed using several motor tests. The World Health Organization Disability Assessment Schedule (WHO-DAS) measured disability status. A linear regression analysis was performed to identify relationships of cognition, frailty and depression severity with disability. RESULTS The average number of impaired cognitive tests was 2.0 (SD = 1.9), with 28.2% of participants showing no impaired scores. On average participants reported depression severity of 17.3 (SD = 3.6), and disability total score of 15.1 (SD = 6.9). The regression model accounted for 25.1% of the variance in disability, with only depression severity significantly predicting disability status. Burden of cognitive impairment and frailty were not predictive of disability in this sample. CONCLUSIONS In this sample, only depression severity was associated with increased disability. CLINICAL IMPLICATIONS These findings have implications for intervention in LLD, as depression severity may represent a more modifiable risk factor for disability.
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Affiliation(s)
- Ruth T Morin
- Mental Health Service, Detroit VA Medical Center , Detroit, Michigan, USA
| | - Philip Insel
- Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center , San Francisco, California, USA.,Faculty of Medicine, Clinical Memory Research Unit, Lund University , Lund, Sweden
| | - David Bickford
- Department of Medicine, Medical College of Wisconsin , Milwaukee, Wisconsin, USA
| | - Craig Nelson
- Department of Psychiatry, University of California San Francisco , San Francisco, California, USA
| | - R Scott Mackin
- Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center , San Francisco, California, USA.,Department of Psychiatry, University of California San Francisco , San Francisco, California, USA.,MentalHealth Service, San Francisco VA Medical Center , San Francisco, California, USA
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14
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Fortinsky RH, Kuchel GA, Steffens DC, Grady J, Smith M, Robison JT. Clinical trial testing in-home multidisciplinary care management for older adults with cognitive vulnerability: Rationale and study design. Contemp Clin Trials 2020; 92:105992. [PMID: 32194252 DOI: 10.1016/j.cct.2020.105992] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 03/01/2020] [Accepted: 03/12/2020] [Indexed: 12/13/2022]
Abstract
Care management approaches are being widely tested in the Medicare-eligible population to manage chronic conditions, but few have focused on cognitive vulnerability as the pathway to optimizing independence in the community-dwelling older population. Cognitive vulnerability refers to living with dementia, depression, and/or a history of delirium. Many studies have shown that cognitive vulnerability is associated with poor health-related outcomes in community-dwelling older adults, raising the health policy importance of finding evidence-based approaches to improve outcomes for this target population. Moreover, very little is known about effects of care management approaches in the rapidly growing Medicare Advantage population. In response to these knowledge gaps, we are testing the efficacy of an in-home, nurse practitioner-led care management team for adults age ≥ 65 with cognitive vulnerability in a Medicare Advantage population. Older adults and family caregivers randomized either to this multidisciplinary care management team, or to a telephonic care management program routinely offered by our Medicare Advantage partner. The intervention period is 12 months and the primary outcome is any emergency department visit or hospitalization over the 12-month period. In this paper, we report on the rationale for testing a multidisciplinary care management intervention for this target population, and explain how a university-based research team collaborated with a Medicare Advantage insurer to conceptualize and implement the clinical trial. We also provide details on study design, and on components of the in-home and telephonic care management interventions. We conclude with a synopsis of recruitment progress along with selected baseline characteristics of the study cohort.
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Affiliation(s)
- Richard H Fortinsky
- UConn Center on Aging, University of Connecticut School of Medicine, 263 Farmington Ave, Farmington, CT 06030-5215, USA.
| | - George A Kuchel
- UConn Center on Aging, University of Connecticut School of Medicine, 263 Farmington Ave, Farmington, CT 06030-5215, USA
| | - David C Steffens
- Department of Psychiatry, University of Connecticut School of Medicine, 263 Farmington Ave, Farmington, CT 06030-1410, USA
| | - James Grady
- Department of Public Health Sciences, University of Connecticut School of Medicine, 263 Farmington Ave, Farmington, CT 06030-6325, USA
| | - Marie Smith
- Department of Pharmacy Practice, School of Pharmacy, University of Connecticut, 69 North Eagleville Road, Storrs, CT 06269-3092, USA
| | - Julie T Robison
- UConn Center on Aging, University of Connecticut School of Medicine, 263 Farmington Ave, Farmington, CT 06030-5215, USA
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15
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Neuropsychiatric symptoms as predictors of conversion from MCI to dementia: a machine learning approach. Int Psychogeriatr 2020; 32:381-392. [PMID: 31455461 DOI: 10.1017/s1041610219001030] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVES To use a Machine Learning (ML) approach to compare Neuropsychiatric Symptoms (NPS) in participants of a longitudinal study who developed dementia and those who did not. DESIGN Mann-Whitney U and ML analysis. Nine ML algorithms were evaluated using a 10-fold stratified validation procedure. Performance metrics (accuracy, recall, F-1 score, and Cohen's kappa) were computed for each algorithm, and graphic metrics (ROC and precision-recall curves) and features analysis were computed for the best-performing algorithm. SETTING Primary care health centers. PARTICIPANTS 128 participants: 78 cognitively unimpaired and 50 with MCI. MEASUREMENTS Diagnosis at baseline, months from the baseline assessment until the 3rd follow-up or development of dementia, gender, age, Charlson Comorbidity Index, Neuropsychiatric Inventory-Questionnaire (NPI-Q) individual items, NPI-Q total severity, and total stress score and Geriatric Depression Scale-15 items (GDS-15) total score. RESULTS 30 participants developed dementia, while 98 did not. Most of the participants who developed dementia were diagnosed at baseline with amnestic multidomain MCI. The Random Forest Plot model provided the metrics that best predicted conversion to dementia (e.g. accuracy=.88, F1=.67, and Cohen's kappa=.63). The algorithm indicated the importance of the metrics, in the following (decreasing) order: months from first assessment, age, the diagnostic group at baseline, total NPI-Q severity score, total NPI-Q stress score, and GDS-15 total score. CONCLUSIONS ML is a valuable technique for detecting the risk of conversion to dementia in MCI patients. Some NPS proxies, including NPI-Q total severity score, NPI-Q total stress score, and GDS-15 total score, were deemed as the most important variables for predicting conversion, adding further support to the hypothesis that some NPS are associated with a higher risk of dementia in MCI.
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16
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Wise EA, Rosenberg PB, Lyketsos CG, Leoutsakos JM. Time course of neuropsychiatric symptoms and cognitive diagnosis in National Alzheimer's Coordinating Centers volunteers. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2019; 11:333-339. [PMID: 31024987 PMCID: PMC6476801 DOI: 10.1016/j.dadm.2019.02.006] [Citation(s) in RCA: 84] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
INTRODUCTION Neuropsychiatric symptoms (NPSs) are nearly universal in cognitive disorders. The mild behavioral impairment construct postulates that NPS may be the first symptom of impending dementia. METHODS Participants were cognitively normal volunteers followed up approximately annually at Alzheimer's Disease Centers, who were assessed on the Neuropsychiatric Inventory and had at least one follow-up visit during which they were diagnosed with mild cognitive impairment (MCI) or dementia. Descriptive statistics were used to determine sequencing of NPS presence with cognitive diagnoses. RESULTS Data were available for 1998 participants who progressed to MCI or dementia. Over 59% developed NPS before the diagnosis of any cognitive disorder. Depression and irritability were the most common NPSs to precede cognitive diagnoses (24 and 21%, respectively). DISCUSSION NPSs precede a cognitive diagnosis in most people who develop cognitive decline, both MCI and dementia. These individuals are an important group to focus clinical and research efforts.
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Affiliation(s)
| | | | | | - Jeannie-Marie Leoutsakos
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins Bayview, Johns Hopkins University, Baltimore, Md
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17
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Sun Z, Wang Z, Xu L, Lv X, Li Q, Wang H, Yu X. Characteristics of Cognitive Deficit in Amnestic Mild Cognitive Impairment With Subthreshold Depression. J Geriatr Psychiatry Neurol 2019; 32:344-353. [PMID: 31480987 DOI: 10.1177/0891988719865943] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
It is widely recognized that depression may precipitate the incidence of dementia in the elderly individuals and individuals with amnestic mild cognitive impairment (aMCI) in particular. However, the association between subthreshold depression (SD) and cognitive deficits in patients with aMCI remains unclear. To address this, we collected demographic information and conducted a battery of neuropsychological cognitive assessments in 33 aMCI participants with SD (aMCI/SD+), 33 nondepressed aMCI participants (aMCI/SD-), and 53 normal controls (NC). Both aMCI groups showed significantly poorer performance in most cognitive domains relative to the NC group (ie, memory, language, processing speed, and executive function). Notably, the aMCI/SD+ group showed significantly poorer attention/working memory compared with the aMCI/SD- group. Multiple linear regression analyses revealed a significant negative association between the severity of depressive symptoms and attention/working memory capacity (β = - .024, P = .024), accounting for 8.28% of the variations in this cognitive domain. All statistical analyses were adjusted by age, sex, and years of education. A logistic regression model had an accuracy of 72.4% in discriminating between the aMCI/SD+ and aMCI/SD- groups based on individual cognitive profiles over 6 domains. Our findings indicate that patients with aMCI with and without SD have distinct patterns of cognitive impairment. This finding may facilitate the diagnosis and treatment of SD in patients with aMCI.
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Affiliation(s)
- Zhiyu Sun
- 1 School of Mental Health, Wenzhou Medical University, Wenzhou, China.,2 Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,3 National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China.,4 Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Zhijiang Wang
- 2 Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,3 National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China.,4 Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China.,5 Center for Advanced Medical Imaging Sciences, NMMI, Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Lujie Xu
- 1 School of Mental Health, Wenzhou Medical University, Wenzhou, China.,2 Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,3 National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China.,4 Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Xiaozhen Lv
- 2 Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,3 National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China.,4 Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Quanzheng Li
- 5 Center for Advanced Medical Imaging Sciences, NMMI, Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Huali Wang
- 2 Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,3 National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China.,4 Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Xin Yu
- 1 School of Mental Health, Wenzhou Medical University, Wenzhou, China.,2 Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.,3 National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China.,4 Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
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Kueper JK, Speechley M, Montero-Odasso M. The Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog): Modifications and Responsiveness in Pre-Dementia Populations. A Narrative Review. J Alzheimers Dis 2019; 63:423-444. [PMID: 29660938 PMCID: PMC5929311 DOI: 10.3233/jad-170991] [Citation(s) in RCA: 169] [Impact Index Per Article: 33.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The Alzheimer’s Disease Assessment Scale–Cognitive Subscale (ADAS-Cog) was developed in the 1980s to assess the level of cognitive dysfunction in Alzheimer’s disease. Advancements in the research field have shifted focus toward pre-dementia populations, and use of the ADAS-Cog has extended into these pre-dementia studies despite concerns about its ability to detect important changes at these milder stages of disease progression. If the ADAS-Cog cannot detect important changes, our understanding of pre-dementia disease progression may be compromised and trials may incorrectly conclude that a novel treatment approach is not beneficial. The purpose of this review was to assess the performance of the ADAS-Cog in pre-dementia populations, and to review all modifications that have been made to the ADAS-Cog to improve its measurement performance in dementia or pre-dementia populations. The contents of this review are based on bibliographic searches of electronic databases to locate all studies using the ADAS-Cog in pre-dementia samples or subsamples, and to locate all modified versions. Citations from relevant articles were also consulted. Overall, our results suggest the original ADAS-Cog is not an optimal outcome measure for pre-dementia studies; however, given the prominence of the ADAS-Cog, care must be taken when considering the use of alternative outcome measures. Thirty-one modified versions of the ADAS-Cog were found. Modification approaches that appear most beneficial include altering scoring methodology or adding tests of memory, executive function, and/or daily functioning. Although modifications improve the performance of the ADAS-Cog, this is at the cost of introducing heterogeneity that may limit between-study comparison.
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Affiliation(s)
- Jacqueline K Kueper
- Department of Epidemiology and Biostatistics, The University of Western Ontario, London, ON, Canada
| | - Mark Speechley
- Department of Epidemiology and Biostatistics, The University of Western Ontario, London, ON, Canada.,Schulich Interfaculty Program in Public Health, The University of Western Ontario, London, ON, Canada
| | - Manuel Montero-Odasso
- Department of Epidemiology and Biostatistics, The University of Western Ontario, London, ON, Canada.,Department of Medicine, Division of Geriatric Medicine, The University of Western Ontario, London, ON, Canada.,Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, ON, Canada
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19
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Abstract
Depression is a common disorder in late life that is associated with poor quality of life, increased disability, and increased all-cause mortality. Rates of completed suicide are the highest in older depressed men compared with any other age group. In this age group, depression is often concurrent with medical illness and it can aggravate the course of medical illness. Cognitive impairment is frequently present and may be the result of the depression itself or may be the consequence of a neurodegenerative disorder such as Alzheimer's disease. Evidence-based psychotherapies, antidepressants, and somatic treatments such as electroconvulsive therapy are employed in the treatment of older depressed adults. Treatment may be complicated by the presence of cognitive impairment, other comorbid medical disorders, and medications used to treat these disorders. Certain safety issues such as increased bleeding risk, hyponatremia, decreased bone density and falls may be associated with antidepressant treatment, may be more common in older depressed adults, and their consequences may be more severe in late life. These risks, however, need to be weighed against the hazards of untreated depression. With appropriate care, most older depressed patients can be successfully treated and a positive outcome can have a significant effect on the patient's quality of life.
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Affiliation(s)
- J Craig Nelson
- Leon J. Epstein Professor of Psychiatry, University of California San Francisco, San Francisco, CA, USA.
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20
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Gonzales MM, Insel PS, Nelson C, Tosun D, Schöll M, Mattsson N, Sacuiu S, Bickford D, Weiner MW, Mackin RS. Chronic depressive symptomatology and CSF amyloid beta and tau levels in mild cognitive impairment. Int J Geriatr Psychiatry 2018; 33:1305-1311. [PMID: 29953668 DOI: 10.1002/gps.4926] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Accepted: 05/04/2018] [Indexed: 11/10/2022]
Abstract
OBJECTIVES To investigate the association between chronic subsyndromal symptoms of depression (SSD), cerebrospinal fluid (CSF) biomarkers, and neuropsychological performance in individuals with mild cognitive impairment (MCI). METHODS Participants included 238 older adults diagnosed with MCI from the Alzheimer's Disease Neuroimaging Initiative repository with cognitive and CSF amyloid beta (Aβ1-42 ), total tau (t-tau), and phosphorylated tau (p-tau) data. The Neuropsychiatric Inventory identified individuals with chronic endorsement (SSD group N = 80) or no endorsement (non-SSD group N = 158) of depressive symptoms across timepoints. CSF biomarker and cognitive performance were evaluated with linear regression models adjusting for age, education, gender, APOE genotype, global cognitive status, and SSD group. RESULTS As compared to the non-SSD group, the SSD group displayed lower CSF Aβ1-42 levels (β = -24.293, S.E. = 6.345, P < 0.001). No group differences were observed for CSF t-tau (P = 0.497) or p-tau levels (P = 0.392). Lower CSF Aβ1-42 levels were associated with poorer performance on learning (β = 0.041, S.E. = 0.018, P = 0.021) and memory (β = -0.012, S.E. = 0.005, P = 0.031) measures, whereas higher CSF t-tau levels were associated with poorer performance on measures of global cognition (β = 0.022, S.E = 0.008, P = 0.007) and language (β = -0.010, S.E = 0.004, P = 0.019). SSD was independently associated with diminished global cognition, learning and memory, language, and executive function performance over and above the effects of CSF biomarkers (all P < 0.05). CONCLUSIONS MCI participants with SSD displayed diminished CSF Aβ1-42 levels but did not differ from non-SSD controls in CSF tau levels. Additionally, CSF biomarkers and SSD independently accounted for variance in cognitive performance, suggesting that these factors may uniquely confer cognitive risk in MCI.
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Affiliation(s)
- Mitzi M Gonzales
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Philip S Insel
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA, USA
| | - Craig Nelson
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Duygu Tosun
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA, USA.,Department of Radiology, University of California, San Francisco, CA, USA
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine and the Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden.,Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Niklas Mattsson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.,Department of Neurology, Skane University Hospital, Lund, Sweden
| | - Simona Sacuiu
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
| | - David Bickford
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Michael W Weiner
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA, USA.,Department of Psychiatry, University of California, San Francisco, CA, USA.,Department of Radiology, University of California, San Francisco, CA, USA.,Department of Medicine, University of California, San Francisco, CA, USA
| | - R Scott Mackin
- Center for Imaging of Neurodegenerative Diseases, Veterans Administration Medical Center, San Francisco, CA, USA.,Department of Psychiatry, University of California, San Francisco, CA, USA
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21
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Sigström R, Waern M, Gudmundsson P, Skoog I, Östling S. Depressive spectrum states in a population-based cohort of 70-year olds followed over 9 years. Int J Geriatr Psychiatry 2018; 33:1028-1037. [PMID: 29785803 DOI: 10.1002/gps.4888] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 03/26/2018] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Depression may be understood as a spectrum of more or less symptomatic states. Little is known about the long-term course of these states in older populations. We examined the prevalence and course of depressive states of different severity in a Swedish population sample of older people followed over 9 years. METHODS A population-based sample of 70-year olds without dementia (N = 563, response rate 71.1%) underwent a psychiatric examination; 450 survivors without dementia were reexamined at ages 75 and/or 79 years. Three depressive spectrum states were defined: major depression (MD), minor depression (MIND), and subsyndromal depression (SSD). RESULTS The cumulative 9-year prevalence of any depressive spectrum state was 55.3% (MD 9.3%, MIND 27.6%, SSD 30.9%). The cross-sectional prevalence increased with age, especially for MIND and SSD. Among those with baseline MD and MIND, 75.0% and 66.7%, respectively, had MD or MIND during follow-up. Among those with SSD, 47.2% had SSD also during follow-up and 36.1% had MD or MIND. Among those with MD during follow-up, 63.1% were in a depressive spectrum state at baseline. The corresponding proportion was 30% for those with MIND (but no MD) during follow-up. CONCLUSION In this population-based sample, over half experienced some degree of depression during their eighth decade of life. The findings give some support for the validity of a depressive spectrum in older adults. Most new episodes of major depression occurred in people who were in a depressive spectrum state already at baseline, which may have implications for late-life depression prevention strategies.
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Affiliation(s)
- Robert Sigström
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Margda Waern
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Pia Gudmundsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Ingmar Skoog
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Svante Östling
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
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22
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Altered Intrinsic Coupling between Functional Connectivity Density and Amplitude of Low-Frequency Fluctuation in Mild Cognitive Impairment with Depressive Symptoms. Neural Plast 2018; 2018:1672708. [PMID: 30002672 PMCID: PMC5996451 DOI: 10.1155/2018/1672708] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 03/06/2018] [Accepted: 05/07/2018] [Indexed: 12/27/2022] Open
Abstract
Neuroimaging studies have demonstrated that major depressive disorder increases the risk of dementia in older individuals with mild cognitive impairment. We used resting-state functional magnetic resonance imaging to explore the intrinsic coupling patterns between the amplitude and synchronisation of low-frequency brain fluctuations using the amplitude of low-frequency fluctuations (ALFF) and the functional connectivity density (FCD) in 16 patients who had mild cognitive impairment with depressive symptoms (D-MCI) (mean age: 69.6 ± 6.2 years) and 18 patients with nondepressed mild cognitive impairment (nD-MCI) (mean age: 72.1 ± 9.7 years). Coupling was quantified as the correlations between the ALFF values and their associated FCDs. The results showed that the ALFF values in the D-MCI group were higher in the left medial prefrontal cortex (mPFC) and lower in the right precentral gyrus (preCG), and the FCD values were higher in the left medial temporal gyrus (MTG) than those in the nD-MCI group. Further, correlation analyses demonstrated that, in the D-MCI group, the mPFC was negatively correlated with the MTG. These findings may relate to the characteristics of mood disorders in patients with MCI, and they offer further insight into the neuropathophysiology of MCI with depressive symptoms.
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Affective and emotional dysregulation as pre-dementia risk markers: exploring the mild behavioral impairment symptoms of depression, anxiety, irritability, and euphoria. Int Psychogeriatr 2018; 30:185-196. [PMID: 28899446 DOI: 10.1017/s1041610217001880] [Citation(s) in RCA: 123] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Affective and emotional symptoms such as depression, anxiety, euphoria, and irritability are common neuropsychiatric symptoms (NPS) in pre-dementia and cognitively normal older adults. They comprise a domain of Mild Behavioral Impairment (MBI), which describes their emergence in later life as an at-risk state for cognitive decline and dementia, and as a potential manifestation of prodromal dementia. This selective scoping review explores the epidemiology and neurobiological links between affective and emotional symptoms, and incident cognitive decline, focusing on recent literature in this expanding field of research. METHODS Existing literature in prodromal and dementia states was reviewed, focusing on epidemiology, and neurobiology. Search terms included: "mild cognitive impairment," "dementia," "prodromal dementia," "preclinical dementia," "Alzheimer's," "depression," "dysphoria," "mania," "euphoria," "bipolar disorder," and "irritability." RESULTS Affective and emotional dysregulation are common in preclinical and prodromal dementia syndromes, often being harbingers of neurodegenerative change and progressive cognitive decline. Nosological constraints in distinguishing between pre-existing psychiatric symptomatology and later life acquired NPS limit historical data utility, but emerging research emphasizes the importance of addressing time frames between symptom onset and cognitive decline, and age of symptom onset. CONCLUSION Affective symptoms are of prognostic utility, but interventions to prevent dementia syndromes are limited. Trials need to assess interventions targeting known dementia pathology, toward novel pathology, as well as using psychiatric medications. Research focusing explicitly on later life onset symptomatology will improve our understanding of the neurobiology of NPS and neurodegeneration, enrich the study sample, and inform observational and clinical trial design for prevention and treatment strategies.
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Springate BA, Steffens DC. Editorial Comment: Is It Time to Take the "Sub" Out of Subsyndromal Depression? Am J Geriatr Psychiatry 2017; 25:992-993. [PMID: 28600124 DOI: 10.1016/j.jagp.2017.05.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 05/19/2017] [Indexed: 10/19/2022]
Affiliation(s)
- Beth A Springate
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT
| | - David C Steffens
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT.
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