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Neurodegenerative diseases show an increase in prevalence and incidence, with the most prominent example being Alzheimer's disease. DNA damage has been suggested to play a role in the pathogenesis, but the exact mechanisms remain elusive. We enrolled 425 participants with and without neurodegenerative diseases and analyzed DNA damage in the form of micronuclei in buccal mucosa samples. In addition, other parameters such as binucleated cells, karyolytic cells, and karyorrhectic cells were quantified. No relevant differences in DNA damage and cytotoxicity markers were observed in patients compared to healthy participants. Furthermore, other parameters such as lifestyle factors and diseases were also investigated. Overall, this study could not identify a direct link between changes in buccal cells and neurogenerative diseases, but highlights the influence of lifestyle factors and diseases on the human buccal cytome.
Apolipoprotein-E4 (APOE-E4) is a major genetic risk factor for developing Alzheimer’s disease (AD). The verbal fluency task (VFT), especially the subtask category fluency, has shown to provide a good discrimination between cognitively normal controls and subjects with AD. Interestingly, APOE-E4 seems to have no effect on the behavioral performance during a VFT in healthy elderly. Thus, the purpose of the present study was to reveal possible compensation mechanisms by investigating the effect of APOE-E4 on the hemodynamic response in non-demented elderly during a VFT by using functional near-infrared spectroscopy (fNIRS). We compared performance and hemodynamic response of high risk APOE-E4/E4, -E3/E4 carriers with neutral APOE-E3/E3 non-demented subjects (N = 288; 70–77 years). No difference in performance was found. APOE-E4/E4, -E3/E4 carriers had a decreased hemodynamic response in the right inferior frontal junction (IFJ) with a corresponding higher response in the left middle frontal gyrus (MFG) during category fluency. Performance was correlated with the hemodynamic response in the MFG. We assume a compensation of decreased IFJ brain activation by utilizing the MFG during category fluency and thus resulting in no behavioral differences between APOE-groups during the performance of a VFT.
Although posttraumatic stress disorder (PTSD; DSM-V 309.82) and anxiety disorders (DSM-V 300.xx) are widely spread mental disorders, the effectiveness of their therapy is still unsatisfying. Non-invasive brain-stimulation techniques like transcranial direct current stimulation (tDCS) might be an option to improve extinction learning, which is a main functional factor of exposure-based therapy for anxiety disorders. To examine this hypothesis, we used a fear conditioning paradigm with female faces as conditioned stimuli (CS) and a 95-dB female scream as unconditioned stimulus (UCS). We aimed to perform a tDCS of the ventromedial prefrontal cortex (vmPFC), which is mainly involved in the control of extinction-processes. Therefore, we applied two 4 × 4 cm electrodes approximately at the EEG-positions F7 and F8 and used a direct current of 1.5 mA. The 20-min stimulation was started during a 10-min break between acquisition and extinction and went on overall extinction-trials. The healthy participants were randomly assigned in two double-blinded process into two sham stimulation and two verum stimulation groups with opposite current flow directions. To measure the fear reactions, we used skin conductance responses (SCR) and subjective ratings. We performed a generalized estimating equations model for the SCR to assess the impact of tDCS and current flow direction on extinction processes for all subjects that showed a successful conditioning (N = 84). The results indicate that tDCS accelerates early extinction processes with a significantly faster loss of CS+/CS- discrimination. The discrimination loss was driven by a significant decrease in reaction toward the CS+ as well as an increase in reaction toward the CS- in the tDCS verum groups, whereas the sham groups showed no significant reaction changes during this period. Therefore, we assume that tDCS of the vmPFC can be used to enhance early extinction processes successfully. But before it should be tested in a clinical context further investigation is needed to assess the reason for the reaction increase on CS-. If this negative side effect can be avoided, tDCS may be a tool to improve exposure-based anxiety therapies.
Objective
Alzheimer’s disease (AD) is a growing challenge worldwide, which is why the search for early-onset predictors must be focused as soon as possible. Longitudinal studies that investigate courses of neuropsychological and other variables screen for such predictors correlated to mild cognitive impairment (MCI). However, one often neglected issue in analyses of such studies is measurement invariance (MI), which is often assumed but not tested for. This study uses the absence of MI (non-MI) and latent factor scores instead of composite variables to assess properties of cognitive domains, compensation mechanisms, and their predictability to establish a method for a more comprehensive understanding of pathological cognitive decline.
Methods
An exploratory factor analysis (EFA) and a set of increasingly restricted confirmatory factor analyses (CFAs) were conducted to find latent factors, compared them with the composite approach, and to test for longitudinal (partial-)MI in a neuropsychiatric test battery, consisting of 14 test variables. A total of 330 elderly (mean age: 73.78 ± 1.52 years at baseline) were analyzed two times (3 years apart).
Results
EFA revealed a four-factor model representing declarative memory, attention, working memory, and visual–spatial processing. Based on CFA, an accurate model was estimated across both measurement timepoints. Partial non-MI was found for parameters such as loadings, test- and latent factor intercepts as well as latent factor variances. The latent factor approach was preferable to the composite approach.
Conclusion
The overall assessment of non-MI latent factors may pose a possible target for this field of research. Hence, the non-MI of variances indicated variables that are especially suited for the prediction of pathological cognitive decline, while non-MI of intercepts indicated general aging-related decline. As a result, the sole assessment of MI may help distinguish pathological from normative aging processes and additionally may reveal compensatory neuropsychological mechanisms.
Dementia, including Alzheimer's disease, is a growing problem worldwide. Prevention or early detection of the disease or a prodromal cognitive decline is necessary. By means of our long-term follow-up ‘Vogel study’, we aim to predict the pathological cognitive decline of a German cohort (mean age was 73.9 ± 1.55 years at first visit) with three measurement time points within 6 years per participant. Especially in samples of the elderly and subjects with chronic or co-morbid diseases, dropouts are one of the biggest problems of long-term studies. In contrast to the large number of research articles conducted on the course of dementia, little research has been done on the completion of treatment. To ensure unbiased and reliable predictors of cognitive decline from study completers, our objective was to determine predictors of dropout. We conducted multivariate analyses of covariance and multinomial logistic regression analyses to compare and predict the subject's dropout behaviour at the second visit 3 years after baseline (full participation, partial participation and no participation/dropout) with neuropsychiatric, cognitive, blood and lifestyle variables. Lower performance in declarative memory, attention and visual–spatial processing predicted dropout rather than full participation. Lower performance in visual–spatial processing predicted partial participation as opposed to full participation. Furthermore, lower performance in mini-mental status examination predicted whether subjects dropped out or participated partially instead of full participation. Baseline cognitive parameters are associated with dropouts at follow-up with a loss of impaired participants. We expect a bias into a healthier sample over time.