To establish the diagnostic and prognostic models that could help the preclinical identification of subjects at higher risk of clinical progression to mild cognitive impairment and dementia based on combined features of baseline demographic, cognitive, behavioral, multimodal MRI, genetic, and plasma data.
The inclusion criteria were 50-79 years old and having 8 or more years of education.
Participants with a history of stroke, other neurological disorders that could lead to cognitive impairment (Parkinson's disease, encephalitis, epilepsy, brain tumors, etc.), severe anxiety or depression, and contraindications for magnetic resonance imaging (MRI) were not enrolled.
Chinese Han nationality
Case-control
Prospective
Multimodal magnetic resonance imaging scanning, behavioral, genetic and plasma biomarker testing
Other interventionMultimodal magnetic resonance imaging scanning, including 3DT1, 3DT2, 3DFLAIR, functional MRI, DTI, NODDI, ASL, QSM behavioral testing, such as olfaction and spatial navigation genetic testing, such as APOE, BDNF plasma biomarker testing, such as ptau, Aβ42/40、NfL、GFAP
the area under the curve of the classification analysis between progressors and nonprogressors
We'll measure the area under the curve of the ROC curves based on combined features of baseline demographic, cognitive, behavioral, multimodal MRI, genetic, and plasma data in discriminating those convert to MCI or AD (progressors) from those do not convert (nonprogressors)
mediation effects of MRI on the associations between gene/plasma biomarker and cognition/behavior
We'll explore whether MRI features could act as mediators between genetic factors and cognition or behavior, as well as between plasma biomarkers and cognition or behavior.
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