| 1. |
- De Meyer, Geert, et al.
(författare)
-
Diagnosis-independent Alzheimer disease biomarker signature in cognitively normal elderly people.
- 2010
-
Ingår i: Archives of neurology. - : American Medical Association (AMA). - 1538-3687 .- 0003-9942. ; 67:8, s. 949-56
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To identify biomarker patterns typical for Alzheimer disease (AD) in an independent, unsupervised way, without using information on the clinical diagnosis. DESIGN: Mixture modeling approach. SETTING: Alzheimer's Disease Neuroimaging Initiative database. Patients or Other PARTICIPANTS: Cognitively normal persons, patients with AD, and individuals with mild cognitive impairment. MAIN OUTCOME MEASURES: Cerebrospinal fluid-derived beta-amyloid protein 1-42, total tau protein, and phosphorylated tau(181P) protein concentrations were used as biomarkers on a clinically well-characterized data set. The outcome of the qualification analysis was validated on 2 additional data sets, 1 of which was autopsy confirmed. RESULTS: Using the US Alzheimer's Disease Neuroimaging Initiative data set, a cerebrospinal fluid beta-amyloid protein 1-42/phosphorylated tau(181P) biomarker mixture model identified 1 feature linked to AD, while the other matched the "healthy" status. The AD signature was found in 90%, 72%, and 36% of patients in the AD, mild cognitive impairment, and cognitively normal groups, respectively. The cognitively normal group with the AD signature was enriched in apolipoprotein E epsilon4 allele carriers. Results were validated on 2 other data sets. In 1 study consisting of 68 autopsy-confirmed AD cases, 64 of 68 patients (94% sensitivity) were correctly classified with the AD feature. In another data set with patients (n = 57) with mild cognitive impairment followed up for 5 years, the model showed a sensitivity of 100% in patients progressing to AD. CONCLUSIONS: The mixture modeling approach, totally independent of clinical AD diagnosis, correctly classified patients with AD. The unexpected presence of the AD signature in more than one-third of cognitively normal subjects suggests that AD pathology is active and detectable earlier than has heretofore been envisioned.
|
|
| 2. |
- De Meyer, Geert, et al.
(författare)
-
Diagnosis-Independent Alzheimer Disease Biomarker Signature in Cognitively Normal Elderly People
- 2010
-
Ingår i: Archives of Neurology. - 0003-9942. ; 67:8, s. 949-956
-
Tidskriftsartikel (refereegranskat)abstract
- Objective: To identify biomarker patterns typical for Alzheimer disease (AD) in an independent, unsupervised way, without using information on the clinical diagnosis. Design: Mixture modeling approach. Setting: Alzheimer's Disease Neuroimaging Initiative database. Patients or Other Participants: Cognitively normal persons, patients with AD, and individuals with mild cognitive impairment. Main Outcome Measures: Cerebrospinal fluid derived p-amyloid protein 1-42, total tau protein, and phosphorylated tau(181p) protein concentrations were used as biomarkers on a clinically well-characterized data set. The outcome of the qualification analysis was validated on 2 additional data sets, 1 of which was autopsy confirmed. Results: Using the US Alzheimer's Disease Neuroimaging Initiative data set, a cerebrospinal fluid beta-amyloid protein 1-42/phosphorylated tau(181P) biomarker mixture model identified 1 feature linked to AD, while the other matched the "healthy" status. The AD signature was found in 90%, 72%, and 36% of patients in the AD, mild cognitive impairment, and cognitively normal groups, respectively. The cognitively normal group with the AD signature was enriched in apolipoprotein E 64 allele carriers. Results were validated on 2 other data sets. In 1 study consisting of 68 autopsy-confirmed AD cases, 64 of 68 patients (94% sensitivity) were correctly classified with the AD feature. In another. data set with patients (n=57) with mild cognitive impairment followed up for 5 years, the model showed a sensitivity of 100% in patients progressing to AD. Conclusions: The mixture modeling approach, totally independent of clinical AD diagnosis, correctly classified patients with AD. The unexpected presence of the AD signature in more than one-third of cognitively normal subjects suggests that AD pathology is active and detectable earlier than has heretofore been envisioned.
|
|
