Vulnerability to Hypertension Is a Major Determinant of Racial Disparities in Alzheimer's Disease Risk

Exploring the neuroprotective role of physical activity in cerebral small vessel disease

Cerebral small vessel disease (cSVD) is a common neurological finding characterized by abnormalities of the small blood vessels in the brain. Previous research has established a strong connection between cSVD and stroke, as well as neurodegenerative disorders, notably Alzheimer's disease (AD) and other dementias. As the search for effective interventions continues, physical activity (PA) has emerged as a potential preventative and therapeutic avenue. This review synthesizes the human and animal literature on the influence of PA on cSVD, highlighting the importance of determining optimal exercise protocols, considering aspects such as intensity, duration, timing, and exercise type. Furthermore, the necessity of widening the age bracket in research samples is discussed, ensuring a holistic understanding of the interventions across varying pathological stages of the disease. The review also suggests the potential of exploring diverse biomarkers and risk profiles associated with clinically significant outcomes. Moreover, we review findings demonstrating the beneficial effects of PA in various rodent models of cSVD, which have uncovered numerous mechanisms of neuroprotection, including increases in neuroplasticity and integrity of the vasculature and white matter; decreases in inflammation, oxidative stress, and mitochondrial dysfunction; and alterations in amyloid processing and neurotransmitter signaling. In conclusion, this review highlights the potential of physical activity as a preventive strategy for addressing cSVD, offering insights into the need for refining exercise parameters, diversifying research populations, and exploring novel biomarkers, while shedding light on the intricate mechanisms through which exercise confers neuroprotection in both humans and animal models.

Racial/Ethnic Disparities in Use of Angiotensin II Receptor Type 2/4 Stimulatory Vs. Inhibitory Antihypertensive Among Hypertensive Adults in the USA

OBJECTIVES

Studies showed angiotensin II type 2 receptor/angiotensin II type 4 receptor (AT2R/AT4R) stimulatory antihypertensive was associated with a lower risk of dementia and cognitive impairment compared to the inhibitory one. This study aimed to identify the racial and ethnic differences in using these agents among the USA adults with hypertension.

METHODS

A cross-sectional study was conducted using data from the Medical Expenditure Panel Survey (MEPS, 2016-2019). Individuals with a diagnosis of hypertension or self-reported hypertension and without dementia or Alzheimer's disease diagnosis were included in the analysis. We applied two multivariable logistic regressions to compare racial/ethnic differences in AT2R/AT4R stimulatory antihypertensive use and AT2R/AT4R inhibitory antihypertensive use, adjusting for covariates.

RESULTS

Twenty-four thousand five hundred eighty-one individuals with hypertension and without dementia or Alzheimer's disease were identified. Among non-Hispanic Whites, 72.39% were using AT2R/AT4R inhibitory antihypertensive agents, vs. 66.97% using AT2R/AT4R stimulatory antihypertensive agents. In contrast, both non-Hispanic Black and Asian Americans were using more AT2R/AT4R stimulatory agents than inhibitory ones (16.40% vs. 12.16% and 4.79% vs. 3.43%, respectively). Compared to non-Hispanic White, non-Hispanic Black (OR 1.980, 95% CI 1.839-2.132) and non-Hispanic Asian Americans (OR 1.545, 95% CI 1.356-1.761) were significantly associated with higher odds of prescribing AT2R/AT4R stimulatory agents, while Hispanics (OR 0.744, 95% CI 0.685-0.808) were associated with lower odds of prescribing AT2R/AT4R inhibitory agents compared to non-Hispanic Whites.

CONCLUSIONS

The results showed that the high-dementia risk populations like non-Hispanic Black and Asian American races are proportionally prescribed with higher use of low-dementia risk antihypertensive agents, compared to non-Hispanic Whites.

Genome-Related Mechanisms Contributing to Differences in Alzheimer's Disease Incidence Between White and Black Older US Adults

In this manuscript, we leverage a modified GWAS algorithm adapted for use with multidimensional Cox models and data from the Health and Retirement Study to explore how genetic variation influences the size of the disparity in Alzheimer's disease (AD) incidence between older Black and White US adults. We identified four loci that were associated with higher AD incidence levels in older Black adults: (1) rs11077034 (hazard ratio (HR), 4.98) from the RBFOX1 gene; (2) rs7144494 (HR, 1.68) from the HISLA gene; (3) rs7660552 (HR, 3.07) from the SLC25A4 gene; and (4) rs12599485 (HR, 3.181) from the NIP30 gene. The RBFOX1, HISLA, SLC25A4, and NIP30 genes are known to be associated with AD (RBFOX1, NIP30) directly, and also influence the risk of AD risk-related morbidities such as hypertension (RBFOX1, SLC25A4), depression (SLC25A4), and certain cancers (HISLA, SLC25A4). A likely disparity-generating mechanism may lie in endocytosis and abnormal tissue growing mechanisms, depending on inherited gene mutations and the structure of proxies as well as gene-environment interactions with other risk factors such as lifestyle, education level, and access to adequate medical services.

Decomposition of disparities in life expectancy with applications to administrative health claims and registry data

Research shows that geographic disparities in life expectancy between leading and lagging states are increasing over time while racial disparities between Black and White Americans have been going down. In the 65+ age strata morbidity is the most common cause of death, making differences in morbidity and associated adverse health-related outcomes between advantaged and disadvantaged groups an important aspect of disparities in life expectancy at age 65 (LE65). In this study, we used Pollard's decomposition to evaluate the disease-related contributions to disparities in LE65 for two types of data with distinctly differing structures: population/registry and administrative claims. To do so, we analyzed Pollard's integral, which is exact by construction, and developed exact analytic solutions for both types of data without the need for numerical integration. The solutions are broadly applicable and easily implemented. Applying these solutions, we found that the largest relative contributions to geographic disparities in LE65 were chronic lower respiratory diseases, circulatory diseases, and lung cancer; and, to racial disparities: arterial hypertension, diabetes mellitus, and cerebrovascular diseases. Overall, the increase in LE65 observed over 1998-2005 and 2010-2017 was primarily due to a reduction in the contributions of acute and chronic ischemic diseases; this was partially offset by increased contributions of diseases of the nervous system including dementia and Alzheimer's disease.

Use of Antihypertensives, Blood Pressure, and Estimated Risk of Dementia in Late Life: An Individual Participant Data Meta-Analysis

Importance

The utility of antihypertensives and ideal blood pressure (BP) for dementia prevention in late life remains unclear and highly contested.

Objectives

To assess the associations of hypertension history, antihypertensive use, and baseline measured BP in late life (age >60 years) with dementia and the moderating factors of age, sex, and racial group.

Data Source and Study Selection

Longitudinal, population-based studies of aging participating in the Cohort Studies of Memory in an International Consortium (COSMIC) group were included. Participants were individuals without dementia at baseline aged 60 to 110 years and were based in 15 different countries (US, Brazil, Australia, China, Korea, Singapore, Central African Republic, Republic of Congo, Nigeria, Germany, Spain, Italy, France, Sweden, and Greece).

Data Extraction and Synthesis

Participants were grouped in 3 categories based on previous diagnosis of hypertension and baseline antihypertensive use: healthy controls, treated hypertension, and untreated hypertension. Baseline systolic BP (SBP) and diastolic BP (DBP) were treated as continuous variables. Reporting followed the Preferred Reporting Items for Systematic Review and Meta-Analyses of Individual Participant Data reporting guidelines.

Main Outcomes and Measures

The key outcome was all-cause dementia. Mixed-effects Cox proportional hazards models were used to assess the associations between the exposures and the key outcome variable. The association between dementia and baseline BP was modeled using nonlinear natural splines. The main analysis was a partially adjusted Cox proportional hazards model controlling for age, age squared, sex, education, racial group, and a random effect for study. Sensitivity analyses included a fully adjusted analysis, a restricted analysis of those individuals with more than 5 years of follow-up data, and models examining the moderating factors of age, sex, and racial group.

Results

The analysis included 17 studies with 34 519 community dwelling older adults (20 160 [58.4%] female) with a mean (SD) age of 72.5 (7.5) years and a mean (SD) follow-up of 4.3 (4.3) years. In the main, partially adjusted analysis including 14 studies, individuals with untreated hypertension had a 42% increased risk of dementia compared with healthy controls (hazard ratio [HR], 1.42; 95% CI 1.15-1.76; P = .001) and 26% increased risk compared with individuals with treated hypertension (HR, 1.26; 95% CI, 1.03-1.53; P = .02). Individuals with treated hypertension had no significant increased dementia risk compared with healthy controls (HR, 1.13; 95% CI, 0.99-1.28; P = .07). The association of antihypertensive use or hypertension status with dementia did not vary with baseline BP. There was no significant association of baseline SBP or DBP with dementia risk in any of the analyses. There were no significant interactions with age, sex, or racial group for any of the analyses.

Conclusions and Relevance

This individual patient data meta-analysis of longitudinal cohort studies found that antihypertensive use was associated with decreased dementia risk compared with individuals with untreated hypertension through all ages in late life. Individuals with treated hypertension had no increased risk of dementia compared with healthy controls.

Forecasting prevalence and mortality of Alzheimer's disease using the partitioning models

OBJECTIVES

Health forecasting is an important aspect of ensuring that the health system can effectively respond to the changing epidemiological environment. Common models for forecasting Alzheimer's disease and related dementias (AD/ADRD) are based on simplifying methodological assumptions, applied to limited population subgroups, or do not allow analysis of medical interventions. This study uses 5 %-Medicare data (1991-2017) to identify, partition, and forecast age-adjusted prevalence and incidence-based mortality of AD as well as their causal components.

METHODS

The core underlying methodology is the partitioning analysis that calculates the relative impact each component has on the overall trend as well as intertemporal changes in the strength and direction of these impacts. B-spline functions estimated for all parameters of partitioning models represent the basis for projections of these parameters in future.

RESULTS

Prevalence of AD is predicted to be stable between 2017 and 2028 primarily due to a decline in the prevalence of pre-AD-diagnosis stroke. Mortality, on the other hand, is predicted to increase. In all cases the resulting patterns come from a trade-off of two disadvantageous processes: increased incidence and disimproved survival. Analysis of health interventions demonstrates that the projected burden of AD differs significantly and leads to alternative policy implications.

DISCUSSION

We developed a forecasting model of AD/ADRD risks that involves rigorous mathematical models and incorporation of the dynamics of important determinative risk factors for AD/ADRD risk. The applications of such models for analyses of interventions would allow for predicting future burden of AD/ADRD conditional on a specific treatment regime.

Comorbidities Incorporated to Improve Prediction for Prevalent Mild Cognitive Impairment and Alzheimer's Disease in the HABS-HD Study

BACKGROUND

Blood biomarkers have the potential to transform Alzheimer's disease (AD) diagnosis and monitoring, yet their integration with common medical comorbidities remains insufficiently explored.

OBJECTIVE

This study aims to enhance blood biomarkers' sensitivity, specificity, and predictive performance by incorporating comorbidities. We assess this integration's efficacy in diagnostic classification using machine learning, hypothesizing that it can identify a confident set of predictive features.

METHODS

We analyzed data from 1,705 participants in the Health and Aging Brain Study-Health Disparities, including 116 AD patients, 261 with mild cognitive impairment, and 1,328 cognitively normal controls. Blood samples were assayed using electrochemiluminescence and single molecule array technology, alongside comorbidity data gathered through clinical interviews and medical records. We visually explored blood biomarker and comorbidity characteristics, developed a Feature Importance and SVM-based Leave-One-Out Recursive Feature Elimination (FI-SVM-RFE-LOO) method to optimize feature selection, and compared four models: Biomarker Only, Comorbidity Only, Biomarker and Comorbidity, and Feature-Selected Biomarker and Comorbidity.

RESULTS

The combination model incorporating 17 blood biomarkers and 12 comorbidity variables outperformed single-modal models, with NPV12 at 92.78%, AUC at 67.59%, and Sensitivity at 65.70%. Feature selection led to 22 chosen features, resulting in the highest performance, with NPV12 at 93.76%, AUC at 69.22%, and Sensitivity at 70.69%. Additionally, interpretative machine learning highlighted factors contributing to improved prediction performance.

CONCLUSIONS

In conclusion, combining feature-selected biomarkers and comorbidities enhances prediction performance, while feature selection optimizes their integration. These findings hold promise for understanding AD pathophysiology and advancing preventive treatments.

Expanding the scope of health disparities research in Alzheimer's disease and related dementias: Recommendations from the "Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias" Workshop Series

Topics discussed at the "Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias" workshop, held by Duke University and the Alzheimer's Association with support from the National Institute on Aging, are summarized.  Ways in which existing data resources paired with innovative applications of both novel and well-known methodologies can be used to identify the effects of multi-level societal, community, and individual determinants of race/ethnicity, sex, and geography-related health disparities in Alzheimer's disease and related dementia are proposed.  Current literature on the population analyses of these health disparities is summarized with a focus on identifying existing gaps in knowledge, and ways to mitigate these gaps using data/method combinations are discussed at the workshop.  Substantive and methodological directions of future research capable of advancing health disparities research related to aging are formulated.