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Memory Concerns, Memory Performance and Risk of Dementia in Patients with Mild Cognitive Impairment
(2014)
Background: Concerns about worsening memory (“memory concerns”; MC) and impairment in memory performance are both predictors of Alzheimer's dementia (AD). The relationship of both in dementia prediction at the pre-dementia disease stage, however, is not well explored. Refined understanding of the contribution of both MC and memory performance in dementia prediction is crucial for defining at-risk populations. We examined the risk of incident AD by MC and memory performance in patients with mild cognitive impairment (MCI).
Methods: We analyzed data of 417 MCI patients from a longitudinal multicenter observational study. Patients were classified based on presence (n = 305) vs. absence (n = 112) of MC. Risk of incident AD was estimated with Cox Proportional-Hazards regression models.
Results: Risk of incident AD was increased by MC (HR = 2.55, 95%CI: 1.33–4.89), lower memory performance (HR = 0.63, 95%CI: 0.56–0.71) and ApoE4-genotype (HR = 1.89, 95%CI: 1.18–3.02). An interaction effect between MC and memory performance was observed. The predictive power of MC was greatest for patients with very mild memory impairment and decreased with increasing memory impairment.
Conclusions: Our data suggest that the power of MC as a predictor of future dementia at the MCI stage varies with the patients' level of cognitive impairment. While MC are predictive at early stage MCI, their predictive value at more advanced stages of MCI is reduced. This suggests that loss of insight related to AD may occur at the late stage of MCI.
Background: The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia.
Methods: We used 115 complete datasets from MCI patients of the "Dementia Competence Network", a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%.
Results: Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four-parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone.
Conclusion: A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.
Background: Autobiographical memory (AM) changes are the hallmark of Alzheimer's disease (AD) and mild cognitive impairment (MCI). In recent neuroimaging studies, AM changes have been associated with numerous cerebral sites, such as the frontal cortices, the mesial temporal lobe, or the posterior cingulum. Regional glucose uptake in these sites was investigated for underlying subdimensions using factor analysis. Subsequently, the factors were examined with respect to AM performance in a subgroup of patients.
Methods: Data from 109 memory clinic referrals, who presented with MCI (n = 60), mild AD (n = 49), or were cognitively intact, were analyzed. The glucose metabolic rates determined by positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) in 34 cerebral sites important for AM were investigated for underlying subdimensions by calculating factor analysis with varimax rotation. Subsequently, the respective factor scores were correlated with the episodic and semantic AM performance of 22 patients, which was measured with a semi-structured interview assessing episodic memories (characterized by event-related emotional, sensory, contextual, and spatial–temporal details) and personal semantic knowledge from three periods of life (primary school, early adulthood, and recent years).
Results: Factor analysis identified seven factors explaining 69% of the variance. While patients with MCI and AD showed lower values than controls on the factors frontal cortex, mesial temporal substructures, and occipital cortex, patients with MCI presented with increased values on the factors posterior cingulum and left temporo-prefrontal areas. The factors anterior cingulum and right temporal cortex showed only minor, non-significant group differences. Solely, the factor mesial temporal substructures was significantly correlated with both episodic memories (r = 0.424, p < 0.05) and personal semantic knowledge (r = 0.547, p < 0.01) in patients with MCI/AD.
Conclusions: The factor structure identified corresponds by large to the morphological and functional interrelations of the respective sites. While reduced glucose uptake on the factors frontal cortex, mesial temporal substructures, and occipital cortex in the patient group may correspond to neurodegenerative changes, increased values on the factors posterior cingulum and left temporo-prefrontal areas in MCI may result from compensatory efforts. Interestingly, changes of the mesial temporal substructures were correlated with both semantic and episodic AM. Our findings suggest that AM deficits do not only reflect neurodegenerative changes but also refer to compensatory mechanisms as they involve both quantitative losses of specific memories and qualitative changes with a semantization of memories.