Murine roseolovirus does not accelerate amyloid-β pathology and human roseoloviruses are not over-represented in Alzheimer disease brains

Background The role of viral infection in Alzheimer Disease (AD) pathogenesis is an area of great interest in recent years. Several studies have suggested an association between the human roseoloviruses, HHV-6 and HHV-7, and AD. Amyloid-β (Aβ) plaques are a hallmark neuropathological finding of AD and were recently proposed to have an antimicrobial function in response to infection. Identifying a causative and mechanistic role of human roseoloviruses in AD has been confounded by limitations in performing in vivo studies. Recent -omics based approaches have demonstrated conflicting associations between human roseoloviruses and AD. Murine roseolovirus (MRV) is a natural murine pathogen that is highly-related to the human roseoloviruses, providing an opportunity to perform well-controlled studies of the impact of roseolovirus on Aβ deposition. Methods We utilized the 5XFAD mouse model to test whether MRV induces Aβ deposition in vivo. We also evaluated viral load and neuropathogenesis of MRV infection. To evaluate Aβ interaction with MRV, we performed electron microscopy. RNA-sequencing of a cohort of AD brains compared to control was used to investigate the association between human roseolovirus and AD. Results We found that 5XFAD mice were susceptible to MRV infection and developed neuroinflammation. Moreover, we demonstrated that Aβ interacts with viral particles in vitro and, subsequent to this interaction, can disrupt infection. Despite this, neither peripheral nor brain infection with MRV increased or accelerated Aβ plaque formation. Moreover, −omics based approaches have demonstrated conflicting associations between human roseoloviruses and AD. Our RNA-sequencing analysis of a cohort of AD brains compared to controls did not show an association between roseolovirus infection and AD. Conclusion Although MRV does infect the brain and cause transient neuroinflammation, our data do not support a role for murine or human roseoloviruses in the development of Aβ plaque formation and AD.

Severe Hypoglycemia Increases Dementia Risk and Related Mortality: A Nationwide, Population-Based Cohort Study

Context There are few studies focused on the relationship between hypoglycemia and new-onset dementia in patients with type 2 diabetes and no study regarding mortality of dementia after hypoglycemia. Objective We investigated the effect of severe hypoglycemia on dementia subtypes and its relation to overall mortality in patients with type 2 diabetes. Methods We evaluated incident dementia, including Alzheimer disease and vascular dementia, among health checkup participants aged 40 years or older in the National Health Insurance System in Korea from January 2009 to December 2015. Episodes of severe hypoglycemia were examined for 3 years before the date of the health checkup. Results Among 2 032 689 participants (1 172 271 men, 860 418 women), 14 443 (0.7%) experienced severe hypoglycemia, during a mean follow-up period of 6.9 ± 1.7 years. Individuals in the severe hypoglycemia group were more likely to be diagnosed with dementia compared to individuals without severe hypoglycemia (23.3% vs 7.3%; P < .001) and the overall incidence of Alzheimer disease was higher than vascular dementia. Dementia risk rose with increasing number of severe hypoglycemic episodes (1 episode [hazard ratio (HR) = 1.54; 95% CI, 1.48-1.60], 2 or more episodes [HR = 1.80; 95% CI, 1.66-1.94]). Overall mortality was higher in participants with dementia, but without severe hypoglycemia (HR = 2.03; 95% CI, 1.96-2.10) and severe hypoglycemia, but without dementia (HR = 4.24; 95% CI, 4.29-4.40), and risk of death was highest in those with both severe hypoglycemia and dementia (HR = 5.08; 95% CI, 4.83-5.35). Conclusion Severe hypoglycemia is associated with dementia, especially Alzheimer disease and mortality; together, they have an additive effect on overall mortality.

Unsupervised high-frequency smartphone-based cognitive assessments are reliable, valid, and feasible in older adults at risk for Alzheimer disease.

Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer disease (AD) in older adults. The Ambulatory Research in Cognition (ARC) smartphone application is based on principles from ecological momentary assessment (EMA) and administers brief tests of associative memory, processing speed, and working memory up to 4 times per day over 7 consecutive days. ARC was designed to be administered unsupervised using participants’ personal devices in their everyday environments. We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65-97) and 22 individuals with very mild dementia (ages 61-88). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau PET, and structural MRI studies. First, results indicated that ARC tasks were reliable as between person reliability across the 7-day cycle and test-retest reliabilities at 6-month and 1-year follow-ups all exceeded 0.85. Second, ARC demonstrated construct validity as evidenced by correlations with conventional cognitive measures (r = 0.53 between composite scores). Third, ARC measures correlated with AD biomarker burden at baseline to a similar degree as conventional cognitive measures. Finally, the intensive 7-day cycle indicated that ARC was feasible (86.50% approached chose to enroll), well tolerated (80.42% adherence, 4.83% dropout), and was rated favorably by older adult participants. Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD.

Advances in Deep Neuropathological Phenotyping of Alzheimer Disease: Past, Present, and Future

Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the presence of neurofibrillary tangles and amyloid beta (Aβ) plaques in the brain. The disease was first described in 1906 by Alois Alzheimer, and since then, there have been many advancements in technologies that have aided in unlocking the secrets of this devastating disease. Such advancements include improving microscopy and staining techniques, refining diagnostic criteria for the disease, and increased appreciation for disease heterogeneity both in neuroanatomic location of abnormalities as well as overlap with other brain diseases; for example, Lewy body disease and vascular dementia. Despite numerous advancements, there is still much to achieve as there is not a cure for AD and postmortem histological analyses is still the gold standard for appreciating AD neuropathologic changes. Recent technological advances such as in-vivo biomarkers and machine learning algorithms permit great strides in disease understanding, and pave the way for potential new therapies and precision medicine approaches. Here, we review the history of human AD neuropathology research to include the notable advancements in understanding common co-pathologies in the setting of AD, and microscopy and staining methods. We also discuss future approaches with a specific focus on deep phenotyping using machine learning.

CLEANING THE BRAIN THROUGH TURBULENT GLYMPHATIC FLOW: THE WASHING MACHINE HYPOTHESIS

LYMPHSPIRATION: In a thought experiment, a "washing machine" model is proposed based on turbulent flow from complex multi-dimensional forces to characterize fluid dynamics in the brain. The glymphatic system's hypothetical role in this system is illustrated in a series of diagrams. Implications of this model are discussed in terms of normal physiology and a variety of pathologic conditions such as brain atrophy and Alzheimer disease.