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Akinci M, Sánchez-Benavides G, Brugulat-Serrat A, Peña-Gómez C, Palpatzis E, Shekari M, Deulofeu C, Fuentes-Julian S, Salvadó G, González-de-Echávarri JM, Suárez-Calvet M, Minguillón C, Fauria K, Molinuevo JL, Gispert JD, Grau-Rivera O, Arenaza-Urquijo EM, Beteta A, Cacciaglia R, Cañas A, Cumplido I, Dominguez R, Emilio M, Falcon C, Hernandez L, Huesa G, Huguet J, Marne P, Menchón T, Operto G, Polo A, Rodríguez-Fernández B, Pradas S, Sadeghi I, Soteras A, Stankeviciute L, Vilanova M, Vilor-Tejedor N. Subjective cognitive decline and anxious/depressive symptoms during the COVID-19 pandemic: what is the role of stress perception, stress resilience, and β-amyloid? Alzheimers Res Ther 2022; 14:126. [PMID: 36068641 PMCID: PMC9446623 DOI: 10.1186/s13195-022-01068-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 08/28/2022] [Indexed: 11/10/2022]
Abstract
Abstract
Background
The COVID-19 pandemic may worsen the mental health of people reporting subjective cognitive decline (SCD) and therefore their clinical prognosis. We aimed to investigate the association between the intensity of SCD and anxious/depressive symptoms during confinement and the underlying mechanisms.
Methods
Two hundred fifty cognitively unimpaired participants completed the Hospital Anxiety and Depression Scale (HADS) and SCD-Questionnaire (SCD-Q) and underwent amyloid-β positron emission tomography imaging with [18F] flutemetamol (N = 205) on average 2.4 (± 0.8) years before the COVID-19 confinement. During the confinement, participants completed the HADS, Perceived Stress Scale (PSS), Brief Resilience Scale (BRS), and an ad hoc questionnaire on worries (access to primary products, self-protection materials, economic situation) and lifestyle changes (sleep duration, sleep quality, eating habits). We investigated stress-related measurements, worries, and lifestyle changes in relation to SCD. We then conducted an analysis of covariance to investigate the association of SCD-Q with HADS scores during the confinement while controlling for pre-confinement anxiety/depression scores and demographics. Furthermore, we introduced amyloid-β positivity, PSS, and BRS in the models and performed mediation analyses to explore the mechanisms explaining the association between SCD and anxiety/depression.
Results
In the whole sample, the average SCD-Q score was 4.1 (± 4.4); 70 (28%) participants were classified as SCD, and 26 (12.7%) were amyloid-β-positive. During the confinement, participants reporting SCD showed higher PSS (p = 0.035) but not BRS scores (p = 0.65) than those that did not report SCD. No differences in worries or lifestyle changes were observed. Higher SCD-Q scores showed an association with greater anxiety/depression scores irrespective of pre-confinement anxiety/depression levels (p = 0.002). This association was not significant after introducing amyloid-β positivity and stress-related variables in the model (p = 0.069). Amyloid-β positivity and PSS were associated with greater HADS irrespective of pre-confinement anxiety/depression scores (p = 0.023; p < 0.001). The association of SCD-Q with HADS was mediated by PSS (p = 0.01).
Conclusions
Higher intensity of SCD, amyloid-β positivity, and stress perception showed independent associations with anxious/depressive symptoms during the COVID-19 confinement irrespective of pre-confinement anxiety/depression levels. The association of SCD intensity with anxiety/depression was mediated by stress perception, suggesting stress regulation as a potential intervention to reduce affective symptomatology in the SCD population in the face of stressors.
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Lorenzini L, Ansems LT, Lopes Alves I, Ingala S, Vállez García D, Tomassen J, Sudre C, Salvadó G, Shekari M, Operto G, Brugulat-Serrat A, Sánchez-Benavides G, ten Kate M, Tijms B, Wink AM, Mutsaerts HJMM, den Braber A, Visser PJ, van Berckel BNM, Gispert JD, Barkhof F, Collij LE, Beteta A, Brugulat A, Cacciaglia R, Cañas A, Deulofeu C, Cumplido I, Dominguez R, Emilio M, Fauria K, Fuentes S, Hernandez L, Huesa G, Huguet J, Marne P, Menchón T, Polo A, Pradas S, Rodriguez-Fernandez B, Sala-Vila A, Sánchez-Benavides G, Soteras A, Vilanova M. Regional associations of white matter hyperintensities and early cortical amyloid pathology. Brain Commun 2022; 4:fcac150. [PMID: 35783557 PMCID: PMC9246276 DOI: 10.1093/braincomms/fcac150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 04/11/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
White matter hyperintensities (WMHs) have a heterogeneous aetiology, associated with both vascular risk factors and amyloidosis due to Alzheimer’s disease. While spatial distribution of both amyloid and WM lesions carry important information for the underlying pathogenic mechanisms, the regional relationship between these two pathologies and their joint contribution to early cognitive deterioration remains largely unexplored.
We included 662 non-demented participants from three Amyloid Imaging to Prevent Alzheimer’s disease (AMYPAD)-affiliated cohorts: EPAD-LCS (N = 176), ALFA+ (N = 310), and EMIF-AD PreclinAD Twin60++ (N = 176). Using PET imaging, cortical amyloid burden was assessed regionally within early accumulating regions (medial orbitofrontal, precuneus, and cuneus) and globally, using the Centiloid method. Regional WMH volume was computed using Bayesian Model Selection. Global associations between WMH, amyloid, and cardiovascular risk scores (Framingham and CAIDE) were assessed using linear models. Partial least square (PLS) regression was used to identify regional associations. Models were adjusted for age, sex, and APOE-e4 status. Individual PLS scores were then related to cognitive performance in 4 domains (attention, memory, executive functioning, and language).
While no significant global association was found, the PLS model yielded two components of interest. In the first PLS component, a fronto-parietal WMH pattern was associated with medial orbitofrontal–precuneal amyloid, vascular risk, and age. Component 2 showed a posterior WMH pattern associated with precuneus-cuneus amyloid, less related to age or vascular risk. Component 1 was associated with lower performance in all cognitive domains, while component 2 only with worse memory.
In a large pre-dementia population, we observed two distinct patterns of regional associations between WMH and amyloid burden, and demonstrated their joint influence on cognitive processes. These two components could reflect the existence of vascular-dependent and -independent manifestations of WMH-amyloid regional association that might be related to distinct primary pathophysiology.
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Affiliation(s)
- Luigi Lorenzini
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Loes T Ansems
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Isadora Lopes Alves
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Silvia Ingala
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - David Vállez García
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Jori Tomassen
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
| | - Carole Sudre
- Centre for Medical Image Computing (CMIC), Departments of Medical Physics & Biomedical Engineering and Computer Science, University College London , UK
- MRC Unit for Lifelong Health and Ageing - University College London , UK
- School of Biomedical Engineering , King’s College London UK
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Universitat Pompeu Fabra , Barcelona , Spain
| | - Gregory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES) , Madrid , Spain
| | - Anna Brugulat-Serrat
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES) , Madrid , Spain
- Atlantic Fellow for Equity in Brain Health at the University of California San Francisco , SanFrancisco, California , USA
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES) , Madrid , Spain
| | - Mara ten Kate
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
| | - Betty Tijms
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
| | - Alle Meije Wink
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Henk J M M Mutsaerts
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Anouk den Braber
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
- Department. of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam , Amsterdam , The Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC , Amsterdam , The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University , Maastricht , The Netherlands
| | - Bart N M van Berckel
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation , Barcelona , Spain
- IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Spain
- Universitat Pompeu Fabra , Barcelona , Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales Y Nanomedicina , Madrid , Spain
| | - Frederik Barkhof
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London , London , UK
| | - Lyduine E Collij
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience , Amsterdam , The Netherlands
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