Nutritional status and structural brain changes in Alzheimer's disease: The NUDAD project

Causal Effect of the 25-Hydroxyvitamin D Concentration on Cerebral Small Vessel Disease: A Mendelian Randomization Study

BACKGROUND

Previous observational studies reported that a lower serum 25-hydroxyvitamin D [25(OH)D] concentration is associated with a higher burden of cerebral small vessel disease (cSVD). The causality of this association is uncertain, but it would be clinically important, given that 25(OH)D can be a target for intervention. We tried to examine the causal effect of 25(OH)D concentration on cSVD-related phenotypes using a Mendelian randomization approach.

METHODS

Genetic instruments for each serum 25(OH)D concentration and cSVD-related phenotypes (lacunar stroke, white matter hyperintensity, cerebral microbleeds, and perivascular spaces) were derived from large-scale genome-wide association studies. We performed 2-sample Mendelian randomization analyses with multiple post hoc sensitivity analyses. A bidirectional Mendelian randomization approach was also used to explore the possibility of reverse causation.

RESULTS

We failed to find any significant causal effect of 25(OH)D concentration on cSVD-related phenotypes (odds ratio [95% CI], 1.00 [0.87-1.16], 1.01 [0.96-1.07], 1.06 [0.85-1.33], 1.00 [0.97-1.03], 1.02 [0.99-1.04], 1.01 [0.99-1.04] for lacunar stroke, white matter hyperintensity, cerebral microbleeds, and white matter, basal ganglia, hippocampal perivascular spaces, respectively). These results were reproduced in the sensitivity analyses accounting for genetic pleiotropy. Conversely, when we examined the effects of cSVD phenotypes on 25(OH)D concentration, cerebral microbleeds were negatively associated with 25(OH)D concentration (0.94 [0.92-0.96]).

CONCLUSIONS

Given the adequate statistical power (>0.8) of the analyses, our findings suggest that the previously reported association between 25(OH)D concentration and cSVD phenotypes might not be causal and partly attributed to reverse causation.

Alcohol and the central nervous system

Ethanol use is common to most cultures but with varying doses and to varying extents. While research has focused on the effects on the liver, alcohol exerts a range of actions on the function and structure of the nervous system. In the central nervous system (CNS) it can provoke or exacerbate neurological and psychiatric disease; its effects on the peripheral nervous system are not included in this review. Sustained alcohol intake can predispose to acute neurochemical changes which, with continued ingestion and incomplete treatment, can lead to chronic structural changes in the CNS: these include generalised cortical and cerebellar atrophy, amnesic syndromes such as Korsakoff's syndrome, and specific white matter disorders such as central pontine myelinolysis and Marchiafava-Bignami syndrome. Alcohol in pregnancy commonly and significantly affects fetal health, though this receives less medical and political attention than other causes of fetal harm. This review looks at the range of disorders that can follow acute or chronic alcohol use, and how these should be managed, and we provide a practical overview on how neurologists might diagnose and manage alcohol addiction.

Estimation of Human Cerebral Atrophy Based on Systemic Metabolic Status Using Machine Learning

Background

Based on the assumption that systemic metabolic disorders affect cognitive function, we have developed a deep neural network (DNN) model that can estimate cognitive function based on basic blood test data that do not contain dementia-specific biomarkers. In this study, we used the same DNN model to assess whether basic blood data can be used to estimate cerebral atrophy.

Methods

We used data from 1,310 subjects (58.32 ± 12.91years old) enrolled in the Brain Doc Bank. The average Mini Mental State Examination score was 28.6 ± 1.9. The degree of cerebral atrophy was determined using the MRI-based index (GM-BHQ). First, we evaluated the correlations between the subjects' age, blood data, and GM-BHQ. Next, we developed DNN models to assess the GM-BHQ: one used subjects' age and blood data, while the other used only blood data for input items.

Results

There was a negative correlation between age and GM-BHQ scores (r = -0.71). The subjects' age was positively correlated with blood urea nitrogen (BUN) (r = 0.40), alkaline phosphatase (ALP) (r = 0.22), glucose (GLU) (r = 0.22), and negative correlations with red blood cell counts (RBC) (r = −0.29) and platelet counts (PLT) (r = −0.26). GM-BHQ correlated with BUN (r = −0.30), GLU (r = −0.26), PLT (r = 0.26), and ALP (r = 0.22). The GM-BHQ estimated by the DNN model with subject age exhibited a positive correlation with the ground truth GM-BHQ (r = 0.70). Furthermore, even if the DNN model without subject age was used, the estimated GM-BHQ showed a significant positive correlation with ground truth GM-BHQ (r = 0.58). Age was the most important variable for estimating GM-BHQ.

Discussion

Aging had the greatest effect on cerebral atrophy. Aging also affects various organs, such as the kidney, and causes changes in systemic metabolic status, which may contribute to cerebral atrophy and cognitive impairment. The DNN model may serve as a new screening test for dementia using basic blood tests for health examinations. Finally, the blood data reflect systemic metabolic disorders in each subject—this method may thus contribute to personalized care.

Relationship between weight loss and regular dental management of older adults residing in long-term care facilities: a 1-year multicenter longitudinal study

PURPOSE

This study aimed to determine the association between home visits by a dentist and regular oral hygiene management by a dental hygienist (regular dental management: RDM) and weight loss among older adults in long-term care facilities.

METHODS

A total of 468 older residents from 26 Japanese long-term care facilities participated in two surveys in 2018 and 2019. Participants were divided into two groups based on their diet during the baseline survey (regular diet, n = 256; dysphagia diet, n = 212). Participants with a regular diet were further divided into those who exhibited a weight loss ≥ 5% over 1 year (weight loss group: n = 77) and those with a weight loss < 5% (consistent weight group: n = 179). The explanatory variables were age, sex, baseline weight, Barthel index, and clinical dementia rating, as well as the patients' medical history of pneumonia, stroke, diabetes, and depression (which is reportedly associated with weight). Additionally, a Poisson regression with robust standard error, was carried out to analyze the explanatory variables, namely the prevalence of RDM noted during the study and functional teeth (which seemed to affect weight loss).

RESULTS

A multivariate analysis revealed that older residents' lack of RDM, clinical dementia assessment, and their history of pneumonia (prevalence rate ratio: 0.35, 95% confidence interval 0.24-0.95) were all significantly associated with weight loss when on a regular diet.

CONCLUSION

Thus, weight loss and RDM were related to each other. Weight loss may be suppressed by incorporating RDMs during the early nursing care for older residents on regular diets.

Cyanobacteria, Cyanotoxins, and Neurodegenerative Diseases: Dangerous Liaisons

The prevalence of neurodegenerative disease (ND) is increasing, partly owing to extensions in lifespan, with a larger percentage of members living to an older age, but the ND aetiology and pathogenesis are not fully understood, and effective treatments are still lacking. Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis are generally thought to progress as a consequence of genetic susceptibility and environmental influences. Up to now, several environmental triggers have been associated with NDs, and recent studies suggest that some cyanotoxins, produced by cyanobacteria and acting through a variety of molecular mechanisms, are highly neurotoxic, although their roles in neuropathy and particularly in NDs are still controversial. In this review, we summarize the most relevant and recent evidence that points at cyanotoxins as environmental triggers in NDs development.

Association between Geriatric Nutritional Risk Index and Post-Stroke Cognitive Outcomes

Background: It is not yet clear whether nutritional status is associated with post-stroke cognitive impairment (PSCI). We examined the geriatric nutritional risk index (GNRI) on the domain-specific cognitive outcomes 3 months after a stroke. Methods: A total of 344 patients with acute ischemic stroke were included for the analysis. The GNRI was calculated as 1.489 × serum albumin (g/L) + 41.7 × admission weight (kg)/ideal body weight (kg) and was dichotomized according to the prespecified cut-off points for no risk and any risks. The primary outcome was PSCI, defined as having adjusted z-scores of less than −2 standard deviations in at least one cognitive domain: executive/activation, memory, visuospatial and language. Multiple logistic regression and linear regression analyses were performed to investigate the association between the GNRI and cognitive outcomes. Results: Seventy (20.3%) patients developed PSCI 3 months after a stroke. The mean GNRI was 106.1 ± 8.6, and 59 (17.2%) patients had low (<98) GNRI scores. A low GNRI was independently associated with the PSCI after adjusting for age, sex, education, initial stroke severity, stroke mechanism and left hemispheric lesion (odds ratio, 2.04; 95% confidence interval, 1.00–4.14). The GNRI scores were also significantly associated with the z-scores from the mini-mental status examination and the frontal domain (β = 0.04, p-value = 0.03; β = 0.03, p-value = 0.03, respectively). Conclusions: A low GNRI was independently associated with the development of PSCI at 3 months after an ischemic stroke. The GNRI scores were specifically associated with the z-scores of the global cognition and frontal domain cognitive outcomes.

The Other Side of Alzheimer's Disease: Influence of Metabolic Disorder Features for Novel Diagnostic Biomarkers

Nowadays, the amyloid cascade hypothesis is the dominant model to explain Alzheimer's disease (AD) pathogenesis. By this hypothesis, the inherited genetic form of AD is discriminated from the sporadic form of AD (SAD) that accounts for 85-90% of total patients. The cause of SAD is still unclear, but several studies have shed light on the involvement of environmental factors and multiple susceptibility genes, such as Apolipoprotein E and other genetic risk factors, which are key mediators in different metabolic pathways (e.g., glucose metabolism, lipid metabolism, energetic metabolism, and inflammation). Furthermore, growing clinical evidence in AD patients highlighted the presence of affected systemic organs and blood similarly to the brain. Collectively, these findings revise the canonical understating of AD pathogenesis and suggest that AD has metabolic disorder features. This review will focus on AD as a metabolic disorder and highlight the contribution of this novel understanding on the identification of new biomarkers for improving an early AD diagnosis.