The study will investigate the biomarkers of Aβ and Tau seeds in plasma detected by Alzheimer's disease (AD) related seeds quantitative detector (AD-seeds-detector), and their sensitivity and specificity in diagnosing AD, compared with those from age-matched cognitively normal controls, and those with other types of dementia. To perform a high throughput analysis of the amount of Aβ and Tau seeds, the investigators have developed an AD-seeds-detector, in which a fluorescence microplate reader was combined with an oscillating mixer or water-bath-type ultrasonicator.
Aβ and Tau seeds have the potential to serve as biomarkers for AD. The AD-seeds-detector could detect small quantities of Aβ and Tau seeds by taking advantage of their ability to nucleate and enhance aggregation, enabling a very high amplification of the signal. This study examines the effectiveness of using the AD-seeds-detector as a novel technique for discriminating AD from cognitively normal control and non-AD dementia by detecting small Aβ and Tau seeds in plasma. This will be an observational study aiming at using the AD-seeds-detector to detect minute amounts of Aβ and Tau seeds in plasma as novel biomarkers with high sensitivity and specificity for the accurate diagnosis of AD. To achieve this goal, the investigators will conduct two studies using the AD-seeds-detector to detect the Aβ and Tau seeds in the plasma samples. Study one: A single-center cohort that consists of well-characterized AD patients (n=150), cognitively normal controls (n=100) and non-AD dementia patients (n=50). Study two: A multi-center cohort with well-characterized AD patients (n=400), cognitively normal controls (n=400) and non-AD dementia patients (n=400).
Study Type
OBSERVATIONAL
Enrollment
1,500
Xuanwu Hospital of Capital Medical University
Beijing, Beijing Municipality, China
RECRUITINGThe area under curve of the AD-seeds-detector for the accurate diagnosis of AD
The area under curve is used to show the ability of the AD-seeds-detector to diagnose AD. The value of area under curve is higher, then the ability of the AD-seeds-detector to diagnose AD is stronger.
Time frame: two years
The sensitivity
The sensitivity is used to show the ability of the AD-seeds-detector to diagnose AD patients, and is represented by true positive/ (true positive +false negative).
Time frame: two years
The specificity
The specificity is used to show the ability of the AD-seeds-detector to avoid false AD patients and rule out AD patients, and is represented by true negative/ (false positive + true negative).
Time frame: two years
The positive predictive value
The positive predictive value is used to show the ability of the AD-seeds-detector to correctly label AD patients who test positive, and is represented by true positive / (true positive + false positive)
Time frame: two years
The negative predictive value
The negative predictive value is used to show the ability of the AD-seeds-detector to correctly label people who test negative, and is represented by true negative / (false negative + true negative)
Time frame: two years
Cellular toxcity of Aβ seeds protein
Toxcity of Aβ seeds protein on cells
Time frame: two years
Morphology and structure of Aβ
Comparison of Morphology and structure of beta-amyloid protein between difference groups
Time frame: two years
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.