Publications (390) View all
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Article: Single-Domain Amnestic Mild Cognitive Impairment Identified by Cluster Analysis Predicts Alzheimer's Disease in the European Prospective DESCRIPA Study.
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ABSTRACT: Background/Aims: To identify prodromal Alzheimer's disease (AD) subjects using a data-driven approach to determine cognitive profiles in mild cognitive impairment (MCI). Methods: A total of 881 MCI subjects were recruited from 20 memory clinics and followed for up to 5 years. Outcome measures included cognitive variables, conversion to AD, and biomarkers (e.g. CSF, and MRI markers). Two hierarchical cluster analyses (HCA) were performed to identify clusters of subjects with distinct cognitive profiles. The first HCA included all subjects with complete cognitive data, whereas the second one selected subjects with very mild MCI (MMSE ≥28). ANOVAs and ANCOVAs were computed to examine whether the clusters differed with regard to conversion to AD, and to AD-specific biomarkers. Results: The HCAs identified 4-cluster solutions that best reflected the sample structure. One cluster (aMCIsingle) had a significantly higher conversion rate (19%), compared to subjective cognitive impairment (SCI, p < 0.0001), and non-amnestic MCI (naMCI, p = 0.012). This cluster was the only one showing a significantly different biomarker profile (Aβ42, t-tau, APOE ε4, and medial temporal atrophy), compared to SCI or naMCI. Conclusion: In subjects with mild MCI, the single-domain amnestic MCI profile was associated with the highest risk of conversion, even if memory impairment did not necessarily cross specific cut-off points. A cognitive profile characterized by isolated memory deficits may be sufficient to warrant applying prevention strategies in MCI, whether or not memory performance lies below specific z-scores. This is supported by our preliminary biomarker analyses. However, further analyses with bigger samples are needed to corroborate these findings.Dementia and Geriatric Cognitive Disorders 05/2013; 36(1-2):1-19. · 2.14 Impact Factor -
Article: Relevance of magnetic resonance imaging for early detection and diagnosis of Alzheimer disease.
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ABSTRACT: Magnetic resonance imaging (MRI)-based indicators of regional and global brain atrophy and more advanced measures of cortical functional and structural connectivity are among the most promising imaging biomarkers for the characterization of preclinical and prodromal stages of Alzheimer disease (AD). This review presents the current status of available and evolving MRI-based technologies for the early asymptomatic and predementia diagnosis of AD, including high-resolution structural MRI of global and regional brain atrophy, diffusion tensor imaging of structural cortical connectivity, and functional MRI during rest and task performance. The selection of an appropriate technique needs to consider its suitability for specific applications.The Medical clinics of North America 05/2013; 97(3):399-424. · 2.18 Impact Factor -
Article: Measurements of medial temporal lobe atrophy for prediction of AD in subjects with MCI
Neurobiology of Aging 03/2013; · 6.19 Impact Factor -
Article: Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment.
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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.Neurobiology of aging 03/2013; · 5.94 Impact Factor -
Article: Have we learnt all we need to know from genetic studies - is genetics over in Alzheimer's disease?
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ABSTRACT: BACKGROUND: Alzheimer's disease (AD) pathophysiology is mostly (>95%) not inherited in a Mendelian fashion. Such sporadic AD (sAD) forms do not exhibit familial aggregation and are characterized by complex genetic inheritance. Growing evidence indicates that multiple genes contribute to sAD-characteristic endophenotypes, molecular mechanisms, signaling pathways and biomarker signatures either individually or through complex gene-gene interactions, lifestyle and the environment. DISCUSSION: Under the hypothesis that low-prevalence variants showing moderate-to-high effect size may be associated with risk for sAD, two independent research groups have demonstrated that a rare variant (rs75932628, encoding a substitution of arginine by histidine at residue 47 (R47H), in the TREM2 gene, which encodes the triggering receptor expressed on myeloid cells 2) is significantly associated with an increased susceptibility to sAD. Another study has provided intriguing evidence that a low-frequency variant (rs63750847) in the APP gene is associated with a reduced risk of developing AD and a lower likelihood of age-related cognitive decline in elderly subjects without AD. SUMMARY: Recent years have witnessed tremendous development in genetics technology that has allowed full individualized genome-wide or genomic screening embracing all of the risk and protective variants for sAD, both across populations and within individuals. Hopefully, the integration of neurogenetics with systems biology and high-throughput genotyping will further pave the way to decipher all of the related causes, mechanisms, and biomarkers across the spectrum of distinct AD forms. After an almost lost apprentice decade in AD therapy development, the epoch of individualized asymptomatic screening and progress in primary and secondary prevention of sAD is probably at its dawn. Even though we are more at the beginning than at the end of sAD genetics, there is some reason for optimism given the recent identification of novel risk or protective variants (such as rare TREM2 and APP mutations) showing strong statistical associations with sAD.Alzheimer's Research and Therapy 03/2013; 5(2):11.
