Background The earliest pathological features of Alzheimer’s disease (AD) appear decades before the clinical symptoms. The pathology affects the brain and the eye, leading to retinal structural changes and functional visual alterations. Healthy individuals at high risk of developing AD present alterations in these ophthalmological measures, as well as in resting-state electrophysiological activity. However, it is unknown whether the ophthalmological alterations are related to the visual-related electrophysiological activity. Elucidating this relationship is paramount to understand the mechanisms underlying the early deterioration of the system and an important step in assessing the suitability of these measures as early biomarkers of disease. Methods In total, 144 healthy subjects: 105 with family history of AD and 39 without, underwent ophthalmologic analysis, magnetoencephalography recording, and genotyping. A subdivision was made to compare groups with less demographic and more risk differences: 28 high-risk subjects (relatives/APOEɛ4 +) and 16 low-risk (non-relatives/APOEɛ4 −). Differences in visual acuity, contrast sensitivity, and macular thickness were evaluated. Correlations between each variable and visual-related electrophysiological measures (M100 latency and time–frequency power) were calculated for each group. Results High-risk groups showed increased visual acuity. Visual acuity was also related to a lower M100 latency and a greater power time–frequency cluster in the high-risk group. Low-risk groups did not show this relationship. High-risk groups presented trends towards a greater contrast sensitivity that did not remain significant after correction for multiple comparisons. The highest-risk group showed trends towards the thinning of the inner plexiform and inner nuclear layers that did not remain significant after correction. The correlation between contrast sensitivity and macular thickness, and the electrophysiological measures were not significant after correction. The difference between the high- and low- risk groups correlations was no significant. Conclusions To our knowledge, this paper is the first of its kind, assessing the relationship between ophthalmological and electrophysiological measures in healthy subjects at distinct levels of risk of AD. The results are novel and unexpected, showing an increase in visual acuity among high-risk subjects, who also exhibit a relationship between this measure and visual-related electrophysiological activity. These results have not been previously explored and could constitute a useful object of research as biomarkers for early detection and the evaluation of potential interventions’ effectiveness.
Background Wide evidence suggests that physical activity (PA) confers protection against Alzheimer’s disease (AD). On the other hand, the apolipoprotein E gene (APOE) ε4 allele represents the greatest genetic risk factor for developing AD. Extensive research has been conducted to determine whether frequent PA can mitigate the increased AD risk associated with APOE ε4. However, thus far, these attempts have produced inconclusive results. In this context, one possible explanation could be that the influence of the combined effect of PA and APOE ε4 carriage might be dependent on the specific outcome measure utilised. Main body. In order to bridge these discrepancies, the aim of this theoretical article is to propose a novel model on the interactive effects of PA and APOE ε4 carriage on well-established mechanisms underlying AD. Available literature was searched to investigate how PA and APOE ε4 carriage, independently and in combination, may alter several molecular pathways involved in AD pathogenesis. The reviewed mechanisms include amyloid beta (Aβ) and tau deposition and clearance, neuronal resilience and neurogenesis, lipid function and cerebrovascular alterations, brain immune response and glucose metabolism. Finally, combining all this information, we have built an integrative model, which includes evidence-based and theoretical synergistic interactions across mechanisms. Moreover, we have identified key knowledge gaps in the literature, providing a list of testable hypotheses that future studies need to address. Conclusions We conclude that PA influences a wide array of molecular targets involved in AD neuropathology. A deeper understanding of where, when and, most importantly, how PA decreases AD risk even in the presence of the APOE ε4 allele will enable the creation of new protocols using exercise along pharmaceuticals in combined therapeutic approaches.
BackgroundAlzheimer’s disease (AD) is tightly associated with sleep alterations: as the disease progresses, sleep quality worsens. Therefore, the study of sleep patterns in interaction with other variables could constitute an early biomarker of AD. It is widely known that sleep alterations lead to an impaired cognitive functioning and performance, and recent studies evidence a positive feedback between amyloid beta (AB) accumulation and sleep. Consequently, sleep could constitute an interesting target for interventions aimed at altering the course of the disease. In the present study, we studied the relationship between self‐reported measures of sleep quality (i.e. number of hours of sleep) and the electrophysiological activity at resting‐state recorded using magnetoencephalography (MEG).MethodThe sample for this study was composed of healthy adults, with varying risks of developing AD (direct relatives vs non‐relatives, and APOE‐E4 carriers vs non‐carriers). All participants completed the Pittsburgh Sleep Quality Index, underwent a MEG scan, and were genotyped for their APOE carriage.ResultPreliminary results show different patterns of brain activation in areas classically associated with the development of AD, in relatives and non‐relatives, in relation with the number of hours of sleep. Non‐relatives present a significant cluster that encompases areas such as the precuneus, where a positive correlation is found between the power in the low beta (12‐20Hz) frequency band and the number of hours of sleep. Relatives do not show clusters where relative power and hours of sleep correlate significantly.ConclusionAlthough further research is needed, a possible interpretation of these results could be the following: non‐relatives’ brain functioning in areas of the default‐mode network, typically associated with AD, are more affected by the number of hours of sleep than relatives, who may not benefit as much due to early damage interfering with the protective effect of sleep.
Purpose: The aim of this work was to analyse in subjects at high risk of developing Alzheimer's disease (AD) the possible correlation between psychophysical tests and magnetoencephalography (MEG) in comparison with control subjects. Methods: Extensive ophthalmological analysis, MEG recording, genotyping and magnetic resonance imaging (MRI) were performed on 149 healthy subjects, of whom 109 had a family history of the disease and 40 did not. This sample was subdivided into subgroups aged 40–60 years with an increased risk of AD based on the presence of the ApoEɛ4 allele (ApoEɛ4+) and family history (FH+). 28 participants as higher risk group (ApoEɛ4+ and FH+) and 16 participants as lower risk group (FH‐ and ApoEɛ4‐). Results: In the ApoEɛ4+ and FH+ group, a significant increase in visual acuity was observed, as well as an increase in some spatial frequencies of contrast sensitivity. In addition, in this group, some areas of the inner plexiform layer and the inner nuclear layer were thinned. Between the risk groups, when directly comparing M100 latency or temporal frequency activity associated with the visual response, no significant differences were found. However, there was an association between higher visual acuity and earlier M100 latency and increased activity in the high‐risk groups. Conclusions: There seems to exist an early hyperactivation of the visual system, which would act as a compensatory mechanism, or be a manifestation of a biological malfunction that ultimately leads to toxicity. This hyperactivation represents the first evidence of the consequences of early retinal damage, associated with genetic risk, on visual processing. These changes observed by readily available and non‐invasive techniques could constitute a set of biomarkers for early detection of the disease and assessment of the efficacy of possible future treatments.
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