This multicenter study examined ¹⁸F-FDG PET measures in the differential diagnosis of Alzheimer's disease (AD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB) from normal aging and from each other and the relation of disease-specific patterns to mild cognitive impairment (MCI). Methods: We examined the ¹⁸F-FDG PET scans of 548 subjects, including 110 healthy elderly individuals (“normals” or NLs), 114 MCI, 199 AD, 98 FTD, and 27 DLB patients, collected at 7 participating centers. Individual PET scans were Z scored using automated voxel-based comparison with generation of disease-specific patterns of cortical and hippocampal ¹⁸F-FDG uptake that were then applied to characterize MCI. Results: Standardized disease-specific PET patterns were developed that correctly classified 95% AD, 92% DLB, 94% FTD, and 94% NL. MCI patients showed primarily posterior cingulate cortex and hippocampal hypometabolism (81%), whereas neocortical abnormalities varied according to neuropsychological profiles. An AD PET pattern was observed in 79% MCI with deficits in multiple cognitive domains and 31% amnesic MCI. ¹⁸F-FDG PET heterogeneity in MCI with nonmemory deficits ranged from absent hypometabolism to FTD and DLB PET patterns. Conclusion: Standardized automated analysis of ¹⁸F-FDG PET scans may provide an objective and sensitive support to the clinical diagnosis in early dementia.

FDG-PET shows that microglial activation might drive cerebral glucose uptake in mice and patients with AD.

We assessed the geographical distribution of C9orf72 G₄C₂ expansions in a pan‐European frontotemporal lobar degeneration (FTLD) cohort (n = 1,205), ascertained by the European Early‐Onset Dementia (EOD) consortium. Next, we performed a meta‐analysis of our data and that of other European studies, together 2,668 patients from 15 Western European countries. The frequency of the C9orf72 expansions in Western Europe was 9.98% in overall FTLD, with 18.52% in familial, and 6.26% in sporadic FTLD patients. Outliers were Finland and Sweden with overall frequencies of respectively 29.33% and 20.73%, but also Spain with 25.49%. In contrast, prevalence in Germany was limited to 4.82%. In addition, we studied the role of intermediate repeats (7–24 repeat units), which are strongly correlated with the risk haplotype, on disease and C9orf72 expression. In vitro reporter gene expression studies demonstrated significantly decreased transcriptional activity of C9orf72 with increasing number of normal repeat units, indicating that intermediate repeats might act as predisposing alleles and in favor of the loss‐of‐function disease mechanism. Further, we observed a significantly increased frequency of short indels in the GC‐rich low complexity sequence adjacent to the G₄C₂ repeat in C9orf72 expansion carriers (P < 0.001) with the most common indel creating one long contiguous imperfect G₄C₂ repeat, which is likely more prone to replication slippage and pathological expansion.

Background: the impact of cognitive impairment on activities of daily living (ADL) is being used as a major criterion for differentiating between mild cognitive impairment (MCI) and dementia. The concept of an ADL threshold that separates MCI from dementia, however, appears to be improbable for several reasons. Objectives: to determine whether complex ADL are impaired in patients with MCI; to examine the usefulness of the assessment of ADL impairment for the diagnosis of MCI; to explore whether both cognitive testing and assessment of impaired ADL are significant predictors of the diagnosis according to the diagnostic gold standard of MCI. Design: cross-sectional study. Setting: university-based outpatient clinic. Subjects: a total of 45 elderly MCI patients diagnosed according to research diagnostic criteria and 30 age-matched cognitively unimpaired controls. Methods: clinical assessment – Alzheimer’s disease Assessment scale, cognitive subscale (ADAS-cog) for the assessment of cognitive functions, Alzheimer’s disease Cooperative Study scale for ADL in MCI (ADCS-MCI-ADL) for the assessment of impairments of complex ADL. Statistical evaluation – Mann–Whitney U tests for significant differences on measures of cognition and everyday functioning. Non-parametric correlations for associations between ADL and cognitive ability. Receiver operator curve (ROC) analyses to identify optimal cut-off scores on the ADCS-MCI-ADL and ADAS-cog scales to differentiate between MCI patients and controls. Binary logistic regression analyses to predict the diagnosis of MCI on the basis of the above-mentioned instruments. Results: patients scored significantly higher than controls on the ADAS-cog scale and significantly lower on the ADCS-MCI-ADL scale. There was a significant negative correlation of the above-mentioned scales in MCI patients (r = −0.46, P<0.01). Both instruments discriminated well between patients and controls (ADCS-MCI-ADL: optimal cut-off 52 points, sensitivity 0.89, specificity 0.97; ADAS-cog: optimal cut-off 10 points, sensitivity 0.78, specificity 1.0). With regard to the linear predictor in the logistic regression built, both instruments were strong predictors of the diagnosis according to the diagnostic gold standard (ADCS-MCI-ADL: P = 0.002; ADAS-cog: P = 0.041). Conclusion: impairment of ADL is already present in MCI. Therefore, intact ADL cannot be used as a criterion to define the syndrome of MCI and to distinguish it from mild dementia. The assessment of complex ADL is probably useful for the diagnosis of MCI.