Association between multimorbidity status and incident dementia: a prospective cohort study of 245,483 participants

Crosstalk between bone and brain in Alzheimer's disease: Mechanisms, applications, and perspectives

Alzheimer's disease (AD) is a neurodegenerative disease that involves multiple systems in the body. Numerous recent studies have revealed bidirectional crosstalk between the brain and bone, but the interaction between bone and brain in AD remains unclear. In this review, we summarize human studies of the association between bone and brain and provide an overview of their interactions and the underlying mechanisms in AD. We review the effects of AD on bone from the aspects of AD pathogenic proteins, AD risk genes, neurohormones, neuropeptides, neurotransmitters, brain-derived extracellular vesicles (EVs), and the autonomic nervous system. Correspondingly, we elucidate the underlying mechanisms of the involvement of bone in the pathogenesis of AD, including bone-derived hormones, bone marrow-derived cells, bone-derived EVs, and inflammation. On the basis of the crosstalk between bone and the brain, we propose potential strategies for the management of AD with the hope of offering novel perspectives on its prevention and treatment. HIGHLIGHTS: The pathogenesis of AD, along with its consequent changes in the brain, may involve disturbing bone homeostasis. Degenerative bone disorders may influence the progression of AD through a series of pathophysiological mechanisms. Therefore, relevant bone intervention strategies may be beneficial for the comprehensive management of AD.

Echocardiographic measures of the left heart and cerebrospinal fluid biomarkers of Alzheimer's disease pathology in cognitively intact adults: The CABLE study

INTRODUCTION

This study delineated the interrelationships between subclinical alterations in the left heart, cerebrospinal fluid (CSF), Alzheimer's disease (AD) biomarkers, and cognition.

METHODS

Multiple linear regressions were conducted in 1244 cognitively normal participants (mean age = 65.5; 43% female) who underwent echocardiography (left atrial [LA] and left ventricular [LV] morphologic or functional parameters) and CSF AD biomarkers measurements. Mediating effects of AD pathologies were examined. Differences in cardiac parameters across ATN categories were tested using analysis of variance (ANOVA) and logistic regressions.

RESULTS

LA or LV enlargement (characterized by increased diameters and volumes) and LV hypertrophy (increased interventricular septal or posterior wall thickness and ventricular mass) were associated with higher CSF phosphorylated (p)-tau and total (t)-tau levels, and poorer cognition. Tau pathologies mediated the heart-cognition relationships. Cardiac parameters were higher in stage 2 and suspected non-Alzheimer's pathology groups than controls.

DISCUSSION

These findings suggested close associations of subclinical cardiac changes with tau pathologies and cognition.

HIGHLIGHTS

Various subclinical alterations in the left heart related to poorer cognition. Subclinical cardiac changes related to tau pathologies in cognitively normal adults. Tau pathologies mediated the heart-cognition relationships. Subclinical cardiac changes related to the AD continuum, especially to stage 2. The accumulation of cardiac alterations magnified their damage to the brain.

Characteristics of Older Adults with Alzheimer's Disease Who Were Hospitalized during the COVID-19 Pandemic: A Secondary Data Analysis

We aim to investigate the relationships between the population characteristics of patients with Alzheimer's Disease (AD) and their Healthcare Utilization (HU) during the COVID-19 pandemic. Electronic health records (EHRs) were utilized. The study sample comprised those with ICD-10 codes G30.0, G30.1, G30.8, and G30.9 between 1 January 2020 and 31 December 2021. Pearson's correlation and multiple regression were used. The analysis utilized 1537 patient records with an average age of 82.20 years (SD = 7.71); 62.3% were female. Patients had an average of 1.64 hospitalizations (SD = 1.18) with an average length of stay (ALOS) of 7.45 days (SD = 9.13). Discharge dispositions were primarily home (55.1%) and nursing facilities (32.4%). Among patients with multiple hospitalizations, a negative correlation was observed between age and both ALOS (r = -0.1264, p = 0.0030) and number of hospitalizations (r = -0.1499, p = 0.0004). Predictors of longer ALOS included male gender (p = 0.0227), divorced or widowed (p = 0.0056), and the use of Medicare Advantage and other private insurance (p = 0.0178). Male gender (p = 0.0050) and Black race (p = 0.0069) were associated with a higher hospitalization frequency. We recommend future studies including the co-morbidities of AD patients, larger samples, and longitudinal data.

A machine learning algorithm based on circulating metabolic biomarkers offers improved predictions of neurological diseases

BACKGROUND AND AIMS

A machine learning algorithm based on circulating metabolic biomarkers for the predictions of neurological diseases (NLDs) is lacking. To develop a machine learning algorithm to compare the performance of a metabolic biomarker-based model with that of a clinical model based on conventional risk factors for predicting three NLDs: dementia, Parkinson's disease (PD), and Alzheimer's disease (AD).

MATERIALS AND METHODS

The eXtreme Gradient Boosting (XGBoost) algorithm was used to construct a metabolic biomarker-based model (metabolic model), a clinical risk factor-based model (clinical model), and a combined model for the prediction of the three NLDs. Risk discrimination (c-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index values were determined for each model.

RESULTS

The results indicate that incorporation of metabolic biomarkers into the clinical model afforded a model with improved performance in the prediction of dementia, AD, and PD, as demonstrated by NRI values of 0.159 (0.039-0.279), 0.113 (0.005-0.176), and 0.201 (-0.021-0.423), respectively; and IDI values of 0.098 (0.073-0.122), 0.070 (0.049-0.090), and 0.085 (0.068-0.101), respectively.

CONCLUSION

The performance of the model based on circulating NMR spectroscopy-detected metabolic biomarkers was better than that of the clinical model in the prediction of dementia, AD, and PD.

Long-term ambient air pollution and the risk of musculoskeletal diseases: A prospective cohort study

Evidence of the associations of air pollution and musculoskeletal diseases is inconsistent. This study aimed to examine the associations between air pollutants and the risk of incident musculoskeletal diseases, such as degenerative joint diseases (n = 38,850) and inflammatory arthropathies (n = 20,108). An air pollution score was constructed to assess the combined effect of PM2.5, PM2.5-10, NO2, and NOX. Cox proportional hazard model was applied to assess the relationships between air pollutants and the incidence of each musculoskeletal disease. The air pollution scores exhibited the modest association with an increased risk of osteoporosis (HR = 1.006, 95% CI: 1.002-1.011). Among the individual air pollutants, PM2.5 and PM2.5-10 exhibited the most significant effect on elevated risk of musculoskeletal diseases, such as PM2.5 on osteoporosis (HR = 1.064, 95% CI: 1.020-1.110), PM2.5-10 on inflammatory arthropathies (HR = 1.059, 95% CI: 1.037-1.081). Females were found to have a higher risk of incident musculoskeletal diseases when exposed to air pollutants. Individuals with extreme BMI or lower socioeconomic status had a higher risk of developing musculoskeletal diseases. Our findings reveal that long-term exposure to ambient air pollutants may contribute to an increased risk of musculoskeletal diseases.

Associations between multimorbidity burden and Alzheimer's pathology in older adults without dementia: the CABLE study

Studies have shown that multimorbidity may be associated with the Alzheimer's disease (AD) stages, but it has not been fully characterized in patients without dementia. A total of 1402 Han Chinese older adults without dementia from Chinese Alzheimer's Biomarker and LifestylE (CABLE) study were included and grouped according to their multimorbidity patterns, defined by the number of chronic disorders and cluster analysis. Multivariable linear regression models were used to detect the associations with AD-related cerebrospinal fluid (CSF) biomarkers. Multimorbidity and severe multimorbidity (≥4 chronic conditions) were significantly associated with CSF amyloid and tau levels (pFDR < 0.05). Metabolic patterns were significantly associated with higher levels of CSF Aβ40 (β = 0.159, pFDR = 0.036) and tau (P-tau: β = 0.132, pFDR = 0.035; T-tau: β = 0.126, pFDR = 0.035). The above associations were only significant in the cognitively normal (CN) group. Multimorbidity was associated with brain AD pathology before any symptomatic evidence of cognitive impairment. Identifying such high-risk groups might allow tailored interventions for AD prevention.

Prevalence of Dementia among Patients Hospitalized with Type 2 Diabetes Mellitus in Spain, 2011-2020: Sex-Related Disparities and Impact of the COVID-19 Pandemic

(1) Background: To assess changes in the prevalence of dementia among patients hospitalized with type 2 diabetes (T2DM), to analyze the effects of dementia on in-hospital mortality (IHM) in this population, to evaluate sex differences, and to determine the impact of the COVID-19 pandemic on these parameters. (2) Methods: We used a nationwide discharge database to select all patients with T2DM aged 60 years or over admitted to Spanish hospitals from 2011 to 2020. We identified those with all-cause dementia, Alzheimer's disease (AD), and vascular dementia (VaD). The effect of sex, age, comorbidity, and COVID-19 on the prevalence of dementia subtypes and on IHM was assessed using multivariable logistic regression. (3) Results: We identified 5,250,810 hospitalizations with T2DM. All-cause dementia was detected in 8.31%, AD in 3.00%, and VaD in 1.55%. The prevalence of all subtypes of dementia increased significantly over time. After multivariable adjustment, higher values were observed in women for all-cause dementia (OR 1.34; 95% CI 1.33-1.35), AD (OR 1.6; 95% CI 1.58-1.62), and VaD (OR 1.12; 95% CI 1.11-1.14). However, female sex was a protective factor for IHM in patients with all-cause dementia (OR 0.90; 95% CI 0.89-0.91), AD (OR 0.89; 95% CI 0.86-0.91), and VaD (OR 0.95; 95% CI 0.91-0.99). IHM among patients with dementia remained stable over time, until 2020, when it increased significantly. Higher age, greater comorbidity, and COVID-19 were associated with IHM in all dementia subtypes. (4) Conclusions: The prevalence of dementia (all-cause, AD, and VaD) in men and women with T2DM increased over time; however, the IHM remained stable until 2020, when it increased significantly, probably because of the COVID-19 pandemic. The prevalence of dementia is higher in women than in men, although female sex is a protective factor for IHM.