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Brain connectivity and metacognition in persons with subjective cognitive decline (COSCODE): rationale and study design

Authors :
Federica Ribaldi
Christian Chicherio
Daniele Altomare
Marta Martins
Szymon Tomczyk
Ileana Jelescu
Enrique Maturana
Max Scheffler
Sven Haller
Karl-Olof Lövblad
Michela Pievani
Valentina Garibotto
Matthias Kliegel
Giovanni B. Frisoni
Source :
Alzheimer’s Research & Therapy, Vol 13, Iss 1, Pp 1-8 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract Background Subjective cognitive decline (SCD) is the subjective perception of a decline in memory and/or other cognitive functions in the absence of objective evidence. Some SCD individuals however may suffer from very early stages of neurodegenerative diseases (such as Alzheimer’s disease, AD), minor psychiatric conditions, neurological, and/or somatic comorbidities. Even if a theoretical framework has been established, the etiology of SCD remains far from elucidated. Clinical observations recently lead to the hypothesis that individuals with incipient AD may have overestimated metacognitive judgements of their own cognitive performance, while those with psychiatric disorders typically present underestimated metacognitive judgements. Moreover, brain connectivity changes are known correlates of AD and psychiatric conditions and might be used as biomarkers to discriminate SCD individuals of different etiologies. The aim of the COSCODE study is to identify metacognition, connectivity, behavioral, and biomarker profiles associated with different etiologies of SCD. Here we present its rationale and study design. Methods COSCODE is an observational, longitudinal (4 years), prospective clinical cohort study involving 120 SCD, and 80 control study participants (40 individuals with no cognitive impairment, and 40 living with mild cognitive impairment - MCI, or dementia due to AD), all of which will undergo diffusion magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) as well as behavioral and biomarker assessments at baseline and after 1 and 2 years. Both hypothesis-driven and data-driven cluster analysis approaches will be used to identify SCD sub-types based on metacognition, connectivity, behavioral, and biomarker features. Conclusion COSCODE will allow defining and interpreting the constellation of signs and symptoms associated with different etiologies of SCD, paving the way to the development of cost-effective risk assessment and prevention protocols.

Details

Language :
English
ISSN :
17589193
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Alzheimer’s Research & Therapy
Publication Type :
Academic Journal
Accession number :
edsdoj.45b6f8ce22d4e0ba60b93884f217cd6
Document Type :
article
Full Text :
https://doi.org/10.1186/s13195-021-00846-z