| 1. |
- Clerx, Lies, et al.
(författare)
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Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment
- 2013
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Ingår i: Neurobiology of Aging. - : Elsevier BV. - 1558-1497 .- 0197-4580. ; 34:8, s. 2003-2013
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Tidskriftsartikel (refereegranskat)abstract
- Our aim was to compare the predictive accuracy of 4 different medial temporal lobe measurements for Alzheimer's disease (AD) in subjects with mild cognitive impairment (MCI). Manual hippocampal measurement, automated atlas-based hippocampal measurement, a visual rating scale (MTA-score), and lateral ventricle measurement were compared. Predictive accuracy for AD 2 years after baseline was assessed by receiver operating characteristics analyses with area under the curve as outcome. Annual cognitive decline was assessed by slope analyses up to 5 years after baseline. Correlations with biomarkers in cerebrospinal fluid (CSF) were investigated. Subjects with MCI were selected from the Development of Screening Guidelines and Clinical Criteria for Predementia AD (DESCRIPA) multicenter study (n = 156) and the single-center VU medical center (n = 172). At follow-up, area under the curve was highest for automated atlas-based hippocampal measurement (0.71) and manual hippocampal measurement (0.71), and lower for MTA-score (0.65) and lateral ventricle (0.60). Slope analysis yielded similar results. Hippocampal measurements correlated with CSF total tau and phosphorylated tau, not with beta-amyloid 1-42. MTA-score and lateral ventricle volume correlated with CSF beta-amyloid 1-42. We can conclude that volumetric hippocampal measurements are the best predictors of AD conversion in subjects with MCI. (c) 2013 Elsevier Inc. All rights reserved.
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| 2. |
- Hall, Anette, et al.
(författare)
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Predicting Progression from Cognitive Impairment to Alzheimer's Disease with the Disease State Index
- 2015
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Ingår i: Current Alzheimer Research. - : Bentham Science Publishers Ltd.. - 1875-5828 .- 1567-2050. ; 12:1, s. 69-79
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Tidskriftsartikel (refereegranskat)abstract
- We evaluated the performance of the Disease State Index (DSI) method when predicting progression to Alzheimer's disease (AD) in patients with subjective cognitive impairment (SCI), amnestic or non-amnestic mild cognitive impairment (aMCI, naMCI). The DSI model measures patients' similarity to diagnosed cases based on available data, such as cognitive tests, the APOE genotype, CSF biomarkers and MRI. We applied the DSI model to data from the DE-SCRIPA cohort, where non-demented patients (N=775) with different subtypes of cognitive impairment were followed for 1 to 5 years. Classification accuracies for the subgroups were calculated with the DSI using leave-one-out cross-validation. The DSI's classification accuracy in predicting progression to AD was 0.75 (AUC=0.83) in the total population, 0.70 (AUC=0.77) for aMCI and 0.71 (AUC=0.76) for naMCI. For a subset of approximately half of the patients with high or low DSI values, accuracy reached 0.86 (all), 0.78 (aMCI), and 0.85 (naMCI). For patients with MRI or CSF biomarker data available, they were 0.78 (all), 0.76 (aMCI) and 0.76 (naMCI), while for clear cases the accuracies rose to 0.90 (all), 0.83 (aMCI) and 0.91 (naMCI). The results show that the DSI model can distinguish between clear and ambiguous cases, assess the severity of the disease and also provide information on the effectiveness of different biomarkers. While a specific test or biomarker may confound analysis for an individual patient, combining several different types of tests and biomarkers could be able to reveal the trajectory of the disease and improve the prediction of AD progression.
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| 3. |
- Wollmer, M Axel., et al.
(författare)
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Association study of cholesterol-related genes in Alzheimer's disease
- 2007
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Ingår i: Neurogenetics. - : Springer Science and Business Media LLC. - 1364-6745 .- 1364-6753. ; 8:3, s. 179-188
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Tidskriftsartikel (refereegranskat)abstract
- Alzheimer’s disease (AD) is a genetically complex disorder, and several genes related to cholesterol metabolism have been reported to contribute to AD risk. To identify further AD susceptibility genes, we have screened genes that map to chromosomal regions with high logarithm of the odds scores for AD in full genome scans and are related to cholesterol metabolism. In a European screening sample of 115 sporadic AD patients and 191 healthy control subjects, we analyzed single nucleotide polymorphisms in 28 cholesterol-related genes for association with AD. The genes HMGCS2, FDPS, RAFTLIN, ACAD8, NPC2, and ABCG1 were associated with AD at a significance level of P ≤ 0.05 in this sample. Replication trials in five independent European samples detected associations of variants within HMGCS2, FDPS, NPC2, or ABCG1 with AD in some samples (P = 0.05 to P = 0.005). We did not identify a marker that was significantly associated with AD in the pooled sample (n = 2864). Stratification of this sample revealed an APOE-dependent association of HMGCS2 with AD (P = 0.004). We conclude that genetic variants investigated in this study may be associated with a moderate modification of the risk for AD in some samples.
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