Background: Visual Snow Syndrome is a recently recognized neurological condition presenting, continuous, tiny dots across the entire visual field, accompanied by nyctalopia, photophobia and palinopsia that persist for months. It may be part of migraine aura spectrum, yet its definition is still questionable. Diagnostic criteria for Visual Snow Syndrome are included in the supplemental material of ICHD-3. We aimed to summarize recent data to improve the understanding of Visual Snow Syndrome. Methods: After presenting four new cases, we conducted a PRISMA systematic search in PubMed/MEDLINE and Embase databases using the keyword “visual snow” with specific inclusion and exclusion criteria. Results: From the 855 articles identified 30 were included for the qualitative analysis. These reports covered five aspects related to Visual Snow Syndrome: epidemiology, clinical features, comorbidities, pathophysiology, and treatment. We found limited data concerning Visual Snow Syndrome’s epidemiology (one study). Clinical presentation (22 articles) and the comorbidities (migraine with aura and tinnitus most often, five reports) are described in detail. The pathophysiology of Visual Snow Syndrome is only approached with hypotheses, but several neuroimaging studies have been identified (seven articles). Treatment is based on single case reports only. Conclusion: Data for Visual Snow Syndrome are few and not strong enough to support Visual Snow Syndrome as a medical identity. Further investigation is needed.

Cognitive and physical decline, both indicators of aging, seem to be associated with each other. The aim of the present study was to investigate whether physical function parameters (walking time and handgrip strength) are related to cerebrospinal fluid (CSF) biomarkers (amyloid-beta Aβ₄₂, Tau, PhTau) in individuals in the Alzheimer’s disease (AD) continuum. The sample was drawn from the Aiginition Longitudinal Biomarker Investigation of Neurodegeneration study, comprising 163 individuals aged 40–75 years: 112 cognitively normal (CN) and 51 with mild cognitive impairment (MCI). Physical function parameters were measured at baseline, a lumbar puncture was performed the same day and CSF biomarkers were analyzed using automated methods. The association between walking time, handgrip strength and CSF biomarkers was evaluated by linear correlation, followed by multivariate linear regression models adjusted for age, sex, education and APOEe4 genotype. Walking time was inversely related to CSF Aβ₄₂ (lower CSF values correspond to increased brain deposition) in all participants (p < 0.05). Subgroup analysis showed that this association was stronger in individuals with MCI and participants older than 60 years old, a result which remained statistically significant after adjustment for the aforementioned confounding factors. These findings may open new perspectives regarding the role of mobility in the AD continuum.

Background: Research concerning the genetic risk for dementia has recently been headed towards new directions. Novel findings from genome-wide association studies have highlighted the association of Alzheimer’s disease incidence with many gene polymorphisms, apart from the Apolipoprotein-E genotype. The identification of additional genetic risk factors has led to the construction of specific genetic risk scores for dementia, considering many different genetic factors and specific biological pathways related to Alzheimer’s disease. Methods: We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis method, summarizing existing data regarding genetic risk scores for Alzheimer’s disease and dementia, in order to improve the current understanding of the genetic underpinnings of dementia. In specific, five databases (PubMed/MEDLINE, Embase, Scopus, Web of science, and Cochrane Central) were searched using the keywords “genetic risk score”, “Alzheimer’s disease”, and “dementia” with specific inclusion and exclusion criteria. Results: From the 552 articles identified, we finally included 20 studies for the qualitative analysis. These reports were classified in three different categories of genetic scores: “polygenic risk scores (PRSs)” (including 11 studies), “pathway specific polygenic risk scores (p-PRSs)” (5 studies), and “complex genetic risk scores” (4 studies). Conclusions: Existing genetic risk scores have contributed to better dementia prediction and a better understanding of the underlying pathology. Novel approaches integrating multiple polygenic risk scores might ameliorate the accuracy of genetic risk scores. The combination of polygenic risk scores that are specific to related biological pathways or relevant biomarkers is of utmost importance to achieve a better predictive ability.

The present study investigated the association of genetic predisposition for white matter hyperintensities (WMHs) with incident amnestic mild cognitive impairment (aMCI) or Alzheimer’s disease (AD), as well as whether such an association was influenced by age, sex, and cognitive reserve. Overall, 537 individuals without aMCI or dementia at baseline were included. Among them, 62 individuals developed aMCI/AD at follow up. Genetic propensity to WMH was estimated using a polygenic risk score for WMHs (PRS WMH). The association of PRS WMH with aMCI/AD incidence was examined using COX models. A higher PRS WMH was associated with a 47.2% higher aMCI/AD incidence (p = 0.015) in the fully adjusted model. Subgroup analyses showed significant results in the older age group, in which individuals with a higher genetic predisposition for WMHs had a 3.4-fold higher risk for developing aMCI/AD at follow up (p < 0.001), as well as in the lower cognitive reserve (CR, proxied by education years) group, in which individuals with a higher genetic predisposition for WMHs had an over 2-fold higher risk (p = 0.013). Genetic predisposition for WMHs was associated with aMCI/AD incidence, particularly in the group of participants with a low CR. Thus, CR might be a modifier in the relationship between genetic predisposition for WMHs and incident aMCI/AD.

As sleep appears to be closely related to cognitive status, we aimed to explore the association between the percentage of deep sleep, cognitive state, and the cerebrospinal fluid (CSF) biomarker amyloid-beta 42 in non-demented individuals. In this cross-sectional study, 90 non-demented participants from the Aiginition Longitudinal Biomarker Investigation of Neurodegeneration cohort underwent a one-night WatchPAT sleep evaluation. Participants were categorized by cognitive status (patients with mild cognitive impairment [MCI] or cognitively normal [CN] individuals) and CSF Aβ42 status (Aβ42 ≤ 1,030 pg/mL [A+] or Ab42 > 1,030 pg/mL [A−]). After controlling for age, sex, and years of education, a significant inverse association was found between the percentage of deep sleep and the odds of being classified as MCI compared to CN (OR = 0.86, 95% CI [0.76–0.97], p = 0.012). However, a non-significant trend for an inverse association between the percentage of deep sleep and the odds of being classified as A+ was observed (OR = 0.92, 95% CI [0.84–1.01], p = 0.092). This study demonstrates a significant link between deep sleep and MCI. Although more longitudinal studies are needed, deep sleep could potentially serve as a novel biomarker of cognitive decline and an intervention target for dementia prevention.

Background: There is a paucity of evidence on the association between genetic propensity for hippocampal atrophy with cognitive outcomes. Therefore, we examined the relationship of the polygenic risk score for hippocampal atrophy (PRShp) with the incidence of amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) as well as the rates of cognitive decline. Methods: Participants were drawn from the population-based HELIAD cohort. Comprehensive neuropsychological assessments were performed at baseline and at follow-up. PRShp was derived from the summary statistics of a large genome-wide association study for hippocampal volume. Cox proportional hazards models as well as generalized estimating equations (GEEs) were used to evaluate the association of PRShp with the combined incidence of aMCI/AD and cognitive changes over time, respectively. All models were adjusted for age, sex, education, and apolipoprotein E (APOE) genotype. Results: Our analysis included 618 older adults, among whom 73 developed aMCI/AD after an average follow-up of 2.96 ± 0.8 years. Each additional SD of PRShp elevated the relative hazard for incident aMCI/AD by 46%. Participants at the top quartile of PRShp had an almost three times higher risk of converting to aMCI/AD compared to the lowest quartile group. Higher PRShp scores were also linked to steeper global cognitive and memory decline. The impact of PRShp was greater among women and younger adults. Conclusions: Our findings support the association of PRShp with aMCI/AD incidence and with global cognitive and memory decline over time. The PRS association was sex- and age-dependent, suggesting that these factors should be considered in genetic modelling for AD.