Journal
MOLECULAR NEURODEGENERATION
Volume 15, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s13024-020-00395-3
Keywords
subjective cognitive decline; Alzheimer's disease; neuroimaging; multimodal MRI; PET
Categories
Funding
- National Key Research and Development Program of China [2016YFC1306300, 2018YFC1312001]
- National Natural Science Foundation of China [61633018, 81671761, 81871425]
- Beijing Municipal Commission of Health and Family Planning [PXM2020_026283_000002]
- Beijing Nature Science Foundation [7161009]
- Fundamental Research Funds for the Central University [2017XTCX04]
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Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer's disease (AD) continuum. Investigating populations with SCD is important for understanding the early pathological mechanisms of AD and identifying SCD-related biomarkers, which are critical for the early detection of AD. With the advent of advanced neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), accumulating evidence has revealed structural and functional brain alterations related to the symptoms of SCD. In this review, we summarize the main imaging features and key findings regarding SCD related to AD, from local and regional data to connectivity-based imaging measures, with the aim of delineating a multimodal imaging signature of SCD due to AD. Additionally, the interaction of SCD with other risk factors for dementia due to AD, such as age and theApolipoprotein E(ApoE) e4 status, has also been described. Finally, the possible explanations for the inconsistent and heterogeneous neuroimaging findings observed in individuals with SCD are discussed, along with future directions. Overall, the literature reveals a preferential vulnerability of AD signature regions in SCD in the context of AD, supporting the notion that individuals with SCD share a similar pattern of brain alterations with patients with mild cognitive impairment (MCI) and dementia due to AD. We conclude that these neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential for identifying the underlying pathological alterations associated with SCD. More longitudinal studies with larger sample sizes combined with more advanced imaging modeling approaches such as artificial intelligence are still warranted to establish their clinical utility.
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