FACEHBI: A PROSPECTIVE STUDY OF RISK FACTORS, BIOMARKERS AND COGNITION IN A COHORT OF INDIVIDUALS WITH SUBJECTIVE COGNITIVE DECLINE. STUDY RATIONALE AND RESEARCH PROTOCOLS

2016 ◽  
pp. 1-9
Author(s):  
O. Rodriguez-Gomez ◽  
A. Sanabria ◽  
A. Perez-Cordon ◽  
D. Sanchez-Ruiz ◽  
C. Abdelnour ◽  
...  
Keyword(s):  
Risk Factor ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Diffusion Tensor ◽  
Subjective Cognitive Decline ◽  
Long Term Study ◽  
Research Protocols ◽  
Preclinical Ad ◽  
Multimodal Biomarkers

Background: Long-term longitudinal studies with multimodal biomarkers are needed to delve into the knowledge of preclinical AD. Subjective cognitive decline has been proposed as a risk factor for the development of cognitive impairment. Thus, including individuals with SCD in observational studies may be a cost-effective strategy to increase the prevalence of preclinical AD in the sample. Objectives: To describe the rationale, research protocols and baseline characteristics of participants in the Fundació ACE Healthy Brain Initiative (FACEHBI). Design: FACEHBI is a clinical trial (EudraCT: 2014-000798-38) embedded within a long-term observational study of individuals with SCD. Setting: Participants have been recruited at the memory clinic of Fundació ACE (Barcelona) from two different sources: patients referred by a general practitioner and individuals from an Open House Initiative. Participants: 200 individuals diagnosed with SCD with a strictly normal performance in a comprehensive neuropsychological battery. Measurements: Individuals will undergo an extensive neuropsychological protocol, risk factor assessment and a set of multimodal biomarkers including florbetaben PET, structural and functional MRI, diffusion tensor imaging, determination of amyloid species in plasma and neurophthalmologic assessment with optical coherence tomography. Results: Two hundred individuals have been recruited in 15 months. Mean age was 65.9 years; mean MMSE was 29.2 with a mean of 14.8 years of education. Conclusions: FACEHBI is a long-term study of cognition, biomarkers and lifestyle that has been designed upon an innovative symptom-based approach using SCD as target population. It will shed light on the pathophysiology of preclinical AD and the role of SCD as a risk marker for the development of cognitive impairment.

Long-Term Blood Pressure Variability Increases Risks of Dementia and Cognitive Decline: A Meta-Analysis of Longitudinal Studies

Hypertension ◽  
2021 ◽  
Author(s):  
Pingping Jia ◽  
Helen W.Y. Lee ◽  
Joyce Y.C. Chan ◽  
Karen K.L. Yiu ◽  
Kelvin K.F. Tsoi
Keyword(s):  
Blood Pressure ◽  
Risk Factor ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Longitudinal Studies ◽  
Meta Analysis ◽  
Hazard Ratio ◽  
Literature Searches ◽  
Meta Regression

High blood pressure (BP) is considered as an important risk factor for cognitive impairment and dementia. BP variability (BPV) may contribute to cognitive function decline or even dementia regardless of BP level. This study aims to investigate whether BPV is an independent predictor for cognitive impairment or dementia. Literature searches were performed in MEDLINE, Embase, PsycINFO, CINAHL, and Web of Science to May 2021. Longitudinal studies that assessed the risk of dementia or cognitive impairment with BPV as the predictor was included. Meta-analysis and meta-regression were performed to evaluate the effect of BPV on the risk of dementia or cognitive impairment. A total of 5919 papers were identified, and 16 longitudinal studies were included, which had >7 million participants and a median age from 50.9 to 79.9 years and a median follow-up of around 4 years. Thirteen studies reported visit-to-visit BPV and concluded that systolic BPV increases the risk of dementia with a pooled hazard ratio of 1.11 (95% CI, 1.05–1.17), and increases the risk of cognitive impairment with a pooled hazard ratio of 1.10 (95% CI, 1.06–1.15). Visit-to-visit diastolic BPV also increased the risk of dementia and cognitive decline. A meta-regression revealed a linear relationship between higher BPV and risks of dementia and cognitive impairment. Similar findings were observed in the studies with day-to-day BPV. This study suggests that long-term BPV is an independent risk factor for cognitive impairment or dementia, so an intervention plan for reducing BPV can be a target for early prevention of dementia.

scholarly journals Memorability of photographs in subjective cognitive decline and mild cognitive impairment: implications for cognitive assessment

2019 ◽  
Author(s):  
Wilma A. Bainbridge ◽  
David Berron ◽  
Hartmut Schütze ◽  
Arturo Cardenas-Blanco ◽  
Coraline Metzger ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Visual Recognition ◽  
Subjective Cognitive Decline ◽  
Long Term Memory ◽  
Healthy Sample ◽  
Image Set ◽  
Stimulus Features

AbstractINTRODUCTIONImpaired long-term memory is a defining feature of Mild Cognitive Impairment (MCI). We tested whether this impairment is item-specific, limited to some memoranda whereas some remain consistently memorable.METHODSWe conducted item-based analyses of long-term visual recognition memory. 394 participants (healthy controls (HC), Subjective Cognitive Decline (SCD), and MCI) in the multicentric DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) were tested with images from a pool of 835 photographs.RESULTSWe observed consistent memorability for images in HCs, SCDs, and MCI, predictable by a neural network trained on another healthy sample. Looking at memorability differences between groups, we identified images that could successfully categorize group membership with higher success and a substantial image reduction than the original image set.DISCUSSIONIndividuals with SCD and MCI show consistent memorability for specific items, while other items show significant diagnosticity. Certain stimulus features could optimize diagnostic assessment, while others could support memory.

scholarly journals Disrupted Dynamic Functional Connectivity in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment Based on the Triple-Network Model

2021 ◽  
Vol 13 ◽  
Author(s):  
Chen Xue ◽  
Wenzhang Qi ◽  
Qianqian Yuan ◽  
Guanjie Hu ◽  
Honglin Ge ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Cognitive Decline ◽  
Amnestic Mild Cognitive Impairment ◽  
Subjective Cognitive Decline ◽  
Preclinical Ad ◽  
Spectrum Disorders

Background: Subjective cognitive decline and amnestic mild cognitive impairment (aMCI) were widely thought to be preclinical AD spectrum disorders, characterized by aberrant functional connectivity (FC) within the triple networks of the default mode network (DMN), the salience network (SN), and the executive control network (ECN). Dynamic FC (DFC) analysis can capture temporal fluctuations in brain FC during the scan, which static FC analysis cannot. The purpose of the current study was to explore the changes in dynamic FC within the triple networks of the preclinical AD spectrum and further reveal their potential diagnostic value in diagnosing preclinical AD spectrum disorders.Methods: We collected resting-state functional magnetic resonance imaging data from 44 patients with subjective cognitive decline (SCD), 49 with aMCI, and 58 healthy controls (HCs). DFC analysis based on the sliding time-window correlation method was used to analyze DFC variability within the triple networks in the three groups. Then, correlation analysis was conducted to reveal the relationship between altered DFC variability within the triple networks and a decline in cognitive function. Furthermore, logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in patients with SCD and aMCI.Results: Compared with the HC group, the groups with SCD and aMCI both showed altered DFC variability within the triple networks. DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within the ECN were significantly different between patients with SCD and aMCI. Moreover, the altered DFC variability in the left IFG within the ECN was obviously associated with a decline in episodic memory and executive function. The logistic regression analysis showed that multivariable analysis had high sensitivity and specificity for diagnosing SCD and aMCI.Conclusions: Subjective cognitive decline and aMCI showed varying degrees of change in DFC variability within the triple networks and altered DFC variability within the ECN involved episodic memory and executive function. More importantly, altered DFC variability and the triple-network model proved to be important biomarkers for diagnosing and identifying patients with preclinical AD spectrum disorders.

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