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Principal Investigator  
Principal Investigator's Name: Maowen Ba
Institution: Yantai Yuhuangding Hospital
Department: Neurology
Proposed Analysis: The rapidly progressive Alzheimer's disease (rpAD) has been observed in some studies. Yet, the prevalence of rpAD vary greatly. Little is known about detailed biomarkers characteristic of rpAD. A reliable result is crucial for further interventions and clinical trials design. In the present study, we applied the high-quality Alzheimer’s Disease Neuroimaging Initiative (ADNI) database to investigate the prevalence of rpAD and its biomarkers characteristic.
Additional Investigators  
Investigator's Name: chunhua zhang
Proposed Analysis: The apolipoprotein E (ApoE) is a major risk factor for the development of Alzheimer's disease (AD). The interaction between gender and ApoE on AD risk remains currently an area of intense investigation. We hypothesized that sex modulates ApoE ε4 on brain structure and metabolism in prodromal AD.
Investigator's Name: Hongchun Wei
Proposed Analysis: According to the amyloid, tau, neurodegeneration research framework classification, amyloid and tau positive (A+T+) mild cognitive impairment (MCI) individuals are defined as prodromal Alzheimer disease. This study was designed to compare the clinical and biomarker features between A+T+MCI individuals who progressed to progressive MCI (pMCI) and those who remained stable MCI (sMCI), and to identify relevant baseline clinical biomarker and features that could be used to predict progression to dementia within 2 years. We stratified 197 A+T+MCI individuals into pMCI (n = 64) and sMCI (n = 133) over 2 years. Demographics and cognitive assessment scores, cerebrospinal fluid (CSF), and neuroimaging biomarkers (florbetapir positron emission tomography mean standardized uptake value ratios [SUVR] and structural magnetic resonance imaging [MRI]) were compared between pMCI and sMCI at baseline, 12- and 24-month follow-up. Logistic regression models then were used to evaluate clinical baseline and biomarker features that predicted dementia progression in A+T+MCI.