Cardiorespiratory fitness and risk of Alzheimer's disease and related dementias among American veterans.

INTRODUCTION: Cardiorespiratory fitness (CRF) is associated with improved health and survival. Less is known about its association with Alzheimer's disease and related dementias (ADRD). METHODS: We identified 649,605 US veterans 30 to 95 years of age and free of ADRD who completed a standardized exercise tolerance test between 2000 and 2017 with no evidence of ischemia. We examined the association between five age- and sex-specific CRF categories and ADRD incidence using multivariate Cox regression models. RESULTS: During up to 20 (median 8.3) years of follow-up, incident ADRD occurred in 44,105 (6.8%) participants, with an incidence rate of 7.7/1000 person-years. Compared to the least-fit, multivariable-adjusted hazard ratios (95% confidence intervals) for incident ADRD were: 0.87 (0.85-0.90), 0.80 (0.78-0.83), 0.74 (0.72-0.76), and 0.67 (0.65-0.70), for low-fit, moderate-fit, fit, and high-fit individuals, respectively. DISSCUSSION: These findings demonstrate an independent, inverse, and graded association between CRF and incident ADRD. Future studies may determine the amount and duration of physical activity needed to optimize ADRD risk reduction.

Neuropathological Findings in Parkinson's Disease With Mild Cognitive Impairment.

OBJECTIVE: There are few neuropathological studies on Parkinson's disease with mild cognitive impairment (PD-MCI). Those published reveal coexisting Lewy body and Alzheimer's disease pathology. Our objective is to determine the pathology that underlies PD-MCI. METHODS: We used data from the Arizona Study of Aging and Neurodegenerative Disorders, a longitudinal clinicopathological study. Of 736 autopsied subjects with standardized movement and cognitive assessments, 25 had PD-MCI. Neuropathological findings, including Lewy body and Alzheimer's disease pathology, were compared in PD subjects with amnestic MCI (A-MCI) and nonamnestic MCI (NA-MCI). RESULTS: Significant pathological heterogeneity within PD-MCI was found. This included varying Lewy body stages, Alzheimer's disease pathology, and cerebral amyloid angiopathy. There was a significant increase in the severity of Lewy body pathology (meeting The Unified Staging System for Lewy Body disorders neocortical stage) in nonamnestic MCI (7/1, 63%) when compared with amnestic MCI (3/14, 21%, P = 0.032). CONCLUSION: Although a small study, distinct pathological changes may contribute to PD-MCI phenotype. © 2020 International Parkinson and Movement Disorder Society.

Lewy body pathology in Alzheimer's disease: A clinicopathological prospective study.

OBJECTIVE: Identify clinical features predictive of Lewy body pathology in Alzheimer's disease (AD) patients in an ongoing longitudinal clinicopathologic study. MATERIAL AND METHODS: We queried the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) database for dementia cases with AD pathology (1997-2015). Subjects received longitudinal comprehensive clinical evaluations including motor/neuropsychological assessment and Apo-E4 genotyping. All cases were autopsied and had standard neuropathological assessments for AD and Lewy-type synucleinopathy (LTS). Subjects were categorized based on standardized pathological criteria with AD cases that had LTS but did not meet DLB pathologic criteria being categorized as ADLB. We performed pairwise comparison between the different diagnoses and multivariable modelling to identify clinical symptoms that predict the pathological diagnosis. RESULTS: We identified 32 DLB/AD, 54 ADLB, 70 AD only and 41 PDD/AD cases. AD subjects with LTS pathology had higher UPDRS II and III total scores as well as generally higher individual scores compared to AD alone. While depression scales and Trail-making Test A correlated significantly with LTS, other neuropsychological variables were not significantly different. Apo E4 occurrence was similar in all groups (40%-49%). CONCLUSIONS: Our study suggests that the presence (or absence) of LTS influences motor and non-motor clinical findings in AD patients. These findings may lead to biomarkers that allow for more targeted treatment of AD.

Trajectory and variability characterization of the Montreal cognitive assessment in older adults.

BACKGROUND: The Montreal cognitive assessment (MoCA) has become one of the most widely used cognitive screening instruments since its initial publication. To date, only a handful of studies have explored longitudinal characteristics of the MoCA. AIM: The aim of this study is to characterize the trajectory of MoCA performance across a broad age continuum of older adults. METHODS: Data from 467 cognitively normal participants were used in this analysis. The sample was grouped into four strata based on the participants' age at baseline (60-69, 70-79, 80-89, and 90-99). Mixed model repeated measures (MMRM) analysis and mixed-effects spline models were used to characterize the trajectory of MoCA scores in each age stratum and in the entire sample. Intrasubject standard deviation (ISD) was used to characterize the natural variability of individual MoCA performance over time. RESULTS: The ISD values for each of the age strata indicated that year-to-year individual variation on the MoCA ranged from zero to three points. MMRM analysis showed that the 60-69 stratum remained relatively stable over time while the 70-79 and 80-89 strata both showed notable decline relative to baseline performance. The mixed-effects spline model showed that MoCA performance declines linearly across the older adult age span. DISCUSSION: Among cognitively normal older adults MoCA performance remains relatively stable over time, however across the older adult age-span MoCA performance declines in a linear fashion. These results will help clinicians better understand the normal course of MoCA change in older adults while researchers may use these results to inform sample size estimates for intervention studies. CONCLUSION: This study provides an enhanced view of the MoCA's intraindividual trajectory in normal elderly aged 60 and older.

Added value and limitations of amyloid-PET imaging: review and analysis of selected cases of mild cognitive impairment and dementia.

Amyloid-positron emission tomography (PET) imaging of the brain detects elevated amyloid-beta (amyloid-ß) neuritic plaques in vivo, which can be helpful in appropriately selected cases of mild cognitive impairment (MCI) and dementia, when Alzheimer's disease remains a possible etiology, after a comprehensive clinical evaluation. We reviewed cases of cognitively impaired patients who underwent amyloid-PET imaging because of diagnostic uncertainty. Pre- and post-PET elements of diagnosis and management were first compared, to assess impact of scan results on clinical decision-making, and then an analysis of those decisions was undertaken in appropriate clinical situations, to delineate the added value and limitations of amyloid-PET imaging. The potential benefits and limitations of this diagnostic tool are important to understand in an era when the utility of such scans in clinical practice is evolving.

Frailty assessment in older adults using upper-extremity function: index development.

BACKGROUND: Numerous multidimensional assessment tools have been developed to measure frailty; however, the clinical feasibility of these tools is limited. We previously developed and validated an upper-extremity function (UEF) assessment method that incorporates wearable motion sensors. The purpose of the current study was to: 1) cross-sectionally validate the UEF method in a larger sample in comparison with the Fried index; 2) develop a UEF frailty index to predict frailty categories including non-frail, pre-frail, and frail based on UEF parameters and demographic information, using the Fried index as the gold standard; and 3) develop a UEF continuous score (points scores for each UEF parameter and a total frailty score) based on UEF parameters and demographic information, using the Fried index as the gold standard. METHODS: We performed a cross-sectional validation and index development study within the Banner Medical Center, Tucson, and Banner Sun Health Research Institute, Sun City, Arizona. Community-dwelling and outpatient older adults (≥60 years; n = 352; 132 non-frail, 175 pre-frail, and 45 frail based on Fried criteria) were recruited. For the UEF test, each participant performed a 20-s elbow flexion, within which they repetitively and rapidly flexed and extended their dominant elbow. Using elbow motion outcomes two UEF indexes were developed (categorical and score). The Fried index was measured as the gold standard. RESULTS: For the categorical index, speed of elbow flexion, elbow range of motion, elbow moment, number of flexion, speed variability and reduction within 20 s, as well as body mass index (BMI) were included as the pre-frailty/frailty predictor parameters. Results from 10-fold cross-validation showed receiver operator characteristic area under the curve of 0.77 ± 0.07 and 0.80 ± 0.12 for predicting Fried pre-frailty and frailty, respectively. UEF score (0.1 to 1.0) was developed using similar UEF parameters. CONCLUSIONS: We present an objective, sensor-based frailty assessment tool based on physical frailty features including slowness, weakness, exhaustion (muscle fatigue), and flexibility of upper-extremity movements. Within the current study, the method was validated cross-sectionally using the Fried index as the gold standard and the UEF categorical index and UEF frailty score were developed for research purposes and potentially for future clinical use.

Sociolinguistic reflection on neuropsychological assessment: an insight into selected culturally adapted battery of Lebanese Arabic cognitive testing.

Neuropsychological tests (NPTs) are highly dependent on education, culture differences as well as age and sex. It is therefore essential to take these factors into consideration when translating NPTs to be used in screening for cognitive impairment. Translations into Arabic must respect the principles of linguistic relativity and cultural specificity of the population under study. The objective is to assess feasibility and outcome of translating neuropsychological tests to Arabic. A team of Lebanese professionals selected a battery of screening NPTs. These tests were translated into Arabic and independently back translated by a team of sociolinguists and cultural specialists. The translations were adapted to suit the Lebanese culture. The final NPT translated versions were reached by consensus of an expert panel and tested on a group of independently living community-dwelling elderly. Translated items had to be modified when: (1) terms could not be translated using one word as required by the test; (2) Concepts were foreign to the culture; (3) Translated words carried multiple meanings; (4) Words were rarely used in Lebanon; (5) Sentences did not have an equivalent; and (6) Words had letters pronounced differently by subgroups in Lebanon. Despite all measures to maintain cultural sensitivity in translations, non-linguistic challenges remained. A battery of cognitive screening tests were translated into Arabic and adapted for the Lebanese population. These adaptations allow for a better assessment of cognitive abilities since they reflect the thought patterns of the population. The challenge is to establish local normative data.

Relationship between Cerebral Microinfarcts and Dementia by Sex: Findings from a community-based Autopsy Study.

Cerebral microinfarcts are common in older adults and are associated with cognitive impairment. Less is known about sex-related variation in the relationship between cerebral microinfarcts and dementia in older adults, the examination of which was the objective of this study. This case-control study was based on the 727 participants (419 women) in the Adult Changes in Thought (ACT) autopsy data. Microinfarcts were ascertained by blinded board-certified neuropathologists, and dementia diagnoses were made by the ACT Consensus Diagnosis Conference per DSM-IV. Multivariable logistic regression models were used to estimate adjusted odds ratio (aOR) and 95% confidence interval (CI). Microinfarcts were present in 49% (356/727) of the participants, which was numerically higher in women: 51% (213/419) vs 46% (143/308). aOR (95% CI) for dementia associated with any microinfarct for female and male participants were 1.45 (0.91-2.30) and 1.24 (0.75-2.06), respectively (p for interaction, 0.34). Respective aORs (95%CIs) associated with ≥2 microinfarcts were 1.37 (0.79-2.36) and 1.53 (0.84-2.78), with interaction p, 0.84. Subcortical microinfarcts were present in 36% (138/381) and 23% (78/346) of patients with and without dementia (aOR, 1.65; 95% CI, 1.14-2.38). Respective aOR (95% CI) in female and male participants were 1.70 (1.03-2.82) and 1.59 (0.90-2.80), (p for interaction, 0.55). There was no association with cortical microinfarcts (aOR, 1.19; 95% CI, 0.83-1.69). These findings suggest that association between microinfarcts and dementia is primarily mediated by subcortical microinfarcts, but we found no evidence of sex-related variation. Future studies with greater power are needed to determine if the associations we found are replicable.

A Novel Explainable AI Method to Assess Associations between Temporal Patterns in Patient Trajectories and Adverse Outcome Risks: Analyzing Fitness as a Risk Factor of ADRD.

We present a novel explainable artificial intelligence (XAI) method to assess the associations between the temporal patterns in the patient trajectories recorded in longitudinal clinical data and the adverse outcome risks, through explanations for a type of deep neural network model called Hybrid Value-Aware Transformer (HVAT) model. The HVAT models can learn jointly from longitudinal and non-longitudinal clinical data, and in particular can leverage the time-varying numerical values associated with the clinical codes or concepts within the longitudinal data for outcome prediction. The key component of the XAI method is the definitions of two derived variables, the temporal mean and the temporal slope, which are defined for the clinical concepts with associated time-varying numerical values. The two variables represent the overall level and the rate of change over time, respectively, in the trajectory formed by the values associated with the clinical concept. Two operations on the original values are designed for changing the values of the two derived variables separately. The effects of the two variables on the outcome risks learned by the HVAT model are calculated in terms of impact scores and impacts. Interpretations of the impact scores and impacts as being similar to those of odds ratios are also provided. We applied the XAI method to the study of cardiorespiratory fitness (CRF) as a risk factor of Alzheimer's disease and related dementias (ADRD). Using a retrospective case-control study design, we found that each one-unit increase in the overall CRF level is associated with a 5% reduction in ADRD risk, while each one-unit increase in the changing rate of CRF over time is associated with a 1% reduction. A closer investigation revealed that the association between the changing rate of CRF level and the ADRD risk is nonlinear, or more specifically, approximately piecewise linear along the axis of the changing rate on two pieces: the piece of negative changing rates and the piece of positive changing rates.

Stroke Incidence in Patients With Hypertension According to Cardiorespiratory Fitness.

BACKGROUND: Hypertension and physical inactivity are risk factors for stroke. The effect of cardiorespiratory fitness (CRF) on stroke risk in patients with hypertension has not been assessed. We evaluated stroke incidence in patients with hypertension according to CRF and changes in CRF. METHODS: We included 483 379 patients with hypertension (mean age±SD; 59.4±9.0 years) and no evidence of unstable cardiovascular disease as indicated by a standardized exercise treadmill test. Patients were assigned to 5 age- and sex-specific CRF categories based on peak metabolic equivalents achieved at the initial exercise treadmill test and in 4 categories based on metabolic equivalent changes over time (n=110 576). Multivariable Cox models, adjusted for age, and comorbidities were used to estimate hazard ratios and 95% CIs for stroke risk. RESULTS: During a median follow-up of 10.6 (interquartile range, 6.6-14.6) years, 15 925 patients developed stroke with an average yearly rate of 3.1 events/1000 person-years. Stroke risk declined progressively with higher CRF and was 55% lower for the High-fit individuals (hazard ratio, 0.45 [95% CI, 0.42-0.48]) compared with the Least-fit. Similar associations were observed across the race, sex, and age spectra. Poor CRF was the strongest predictor of stroke risk of all comorbidities studied (hazard ratio, 2.24 [95% CI, 2.10-2.40]). Changes in CRF reflected inverse and proportional changes in stroke risk. CONCLUSIONS: Poor CRF carried a greater risk than any of the cardiac risk factors in patients with hypertension, regardless of age, race, or sex. The lower stroke risk associated with improved CRF suggests that increasing physical activity, even later in life, may reduce stroke risk.

Relationships between Cerebral Vasculopathies and Microinfarcts in a Community-Based Cohort of Older Adults.

Cerebral microinfarcts are associated with cognitive impairment and dementia. Small vessel diseases such as cerebral arteriolosclerosis and cerebral amyloid angiography (CAA) have been found to be associated with microinfarcts. Less is known about the associations of these vasculopathies with the presence, numbers, and location of microinfarcts. These associations were examined in the clinical and autopsy data of 842 participants in the Adult Changes in Thought (ACT) study. Both vasculopathies were categorized by severity (none, mild, moderate, and severe) and region (cortical and subcortical). Odds ratios (OR) and 95% CIs for microinfarcts associated with arteriolosclerosis and CAA adjusted for possible modifying covariates such as age at death, sex, blood pressure, APOE genotype, Braak, and CERAD were estimated. 417 (49.5%) had microinfarcts (cortical, 301; subcortical, 249), 708 (84.1%) had cerebral arteriolosclerosis, 320 (38%) had CAA, and 284 (34%) had both. Ors (95% CI) for any microinfarct were 2.16 (1.46-3.18) and 4.63 (2.90-7.40) for those with moderate (n = 183) and severe (n = 124) arteriolosclerosis, respectively. Respective Ors (95% CI) for the number of microinfarcts were 2.25 (1.54-3.30) and 4.91 (3.18-7.60). Similar associations were observed for cortical and subcortical microinfarcts. Ors (95% Cis) for the number of microinfarcts associated with mild (n = 75), moderate (n = 73), and severe (n = 15) amyloid angiopathy were 0.95 (0.66-1.35), 1.04 (0.71-1.52), and 2.05 (0.94-4.45), respectively. Respective Ors (95% Cis) for cortical microinfarcts were 1.05 (0.71-1.56), 1.50 (0.99-2.27), and 1.69 (0.73-3.91). Respective Ors (95% Cis) for subcortical microinfarcts were 0.84 (0.55-1.28), 0.72 (0.46-1.14), and 0.92 (0.37-2.28). These findings suggest a significant association of cerebral arteriolosclerosis with the presence, number, and location (cortical and subcortical) of microinfarcts, and a weak and non-significant association of CAA with each microinfarct, highlighting the need for future research to better understand the role of small vessel diseases in the pathogenesis of cerebral microinfarcts.

Anti-Amyloid Therapy, AD, and ARIA: Untangling the Role of CAA.

Anti-amyloid therapies (AATs), such as anti-amyloid monoclonal antibodies, are emerging treatments for people with early Alzheimer's disease (AD). AATs target amyloid ß plaques in the brain. Amyloid-related imaging abnormalities (ARIA), abnormal signals seen on magnetic resonance imaging (MRI) of the brain in patients with AD, may occur spontaneously but occur more frequently as side effects of AATs. Cerebral amyloid angiopathy (CAA) is a major risk factor for ARIA. Amyloid ß plays a key role in the pathogenesis of AD and of CAA. Amyloid ß accumulation in the brain parenchyma as plaques is a pathological hallmark of AD, whereas amyloid ß accumulation in cerebral vessels leads to CAA. A better understanding of the pathophysiology of ARIA is necessary for early detection of those at highest risk. This could lead to improved risk stratification and the ultimate reduction of symptomatic ARIA. Histopathological confirmation of CAA by brain biopsy or autopsy is the gold standard but is not clinically feasible. MRI is an available in vivo tool for detecting CAA. Cerebrospinal fluid amyloid ß level testing and amyloid PET imaging are available but do not offer specificity for CAA vs amyloid plaques in AD. Thus, developing and testing biomarkers as reliable and sensitive screening tools for the presence and severity of CAA is a priority to minimize ARIA complications.

Relationships between Late-Life Blood Pressure and Cerebral Microinfarcts in Octogenarians: An Observational Autopsy Study.

Mid-life high blood pressure (BP) is a risk factor for cerebral microinfarcts. Less is known about the relationship between late-life BP and cerebral microinfarcts, the examination of which is the objective of the current study. This case-control study analyzed data from 551 participants (94.6% aged ≥80 years; 58.6% women) in the Adult Changes in Thought (ACT) study who had autopsy data on microinfarcts and four values of systolic and diastolic blood pressure (SBP and DBP) before death. Using the average of four values, SBP was categorized using 10 mmHg intervals; a trend was defined as a ≥10 mmHg rise or fall from the first to fourth values (average gap of 6.5 years). Multivariable-adjusted regression models were used to examine the associations of BP and microinfarcts, adjusting for age, sex, last BP-to-death time, APOE genotype, and antihypertensive medication use. Microinfarcts were present in 274 (49.7%) participants; there were multiple in 51.8% of the participants, and they were located in cortical areas in 40.5%, subcortical areas in 29.6%, and both areas in 29.9% of the participants. All SBP categories (reference of 100-119 mmHg) and both SBP trends were associated with higher odds of both the presence and number of microinfarcts. The magnitude of these associations was numerically greater for subcortical than cortical microinfarcts. Similar associations were observed with DBP. These hypothesis-generating findings provide new information about the overall relationship between BP and cerebral microinfarcts in octogenarians.

Enhancing Clinical Data Analysis by Explaining Interaction Effects between Covariates in Deep Neural Network Models.

Deep neural network (DNN) is a powerful technology that is being utilized by a growing number and range of research projects, including disease risk prediction models. One of the key strengths of DNN is its ability to model non-linear relationships, which include covariate interactions. We developed a novel method called interaction scores for measuring the covariate interactions captured by DNN models. As the method is model-agnostic, it can also be applied to other types of machine learning models. It is designed to be a generalization of the coefficient of the interaction term in a logistic regression; hence, its values are easily interpretable. The interaction score can be calculated at both an individual level and population level. The individual-level score provides an individualized explanation for covariate interactions. We applied this method to two simulated datasets and a real-world clinical dataset on Alzheimer's disease and related dementia (ADRD). We also applied two existing interaction measurement methods to those datasets for comparison. The results on the simulated datasets showed that the interaction score method can explain the underlying interaction effects, there are strong correlations between the population-level interaction scores and the ground truth values, and the individual-level interaction scores vary when the interaction was designed to be non-uniform. Another validation of our new method is that the interactions discovered from the ADRD data included both known and novel relationships.

Characteristics and Predictors of Alzheimer's Disease Resilience Phenotype.

Alzheimer's disease (AD) is characterized by cognitive impairment in the presence of cerebral amyloid plaques and neurofibrillary tangles. Less is known about the characteristics and predictors of resilience to cognitive impairment in the presence of neuropathological evidence of AD, the focus of this study. Of 3170 adults age ≥65 years in the National Alzheimer's Coordinating Center (NACC) brain autopsy cohort, 1373 had evidence of CERAD level moderate to frequent neuritic plaque density and Braak stage V-VI neurofibrillary tangles. Resilience was defined by CDR-SOB and CDR-Global scores of 0-2.5 and 0-0.5, respectively, and non-resilience, CDR-SOB and CDR-Global scores >2.5 and >0.5, respectively. Multivariable logistic regression models were used to examine the independent associations of patient characteristics with resilience. There were 62 participants (4.8%) with resilience. Those with resilience were older (mean age, 88.3 vs. 82.4 years), more likely to be women (61.3% vs. 47.3%) and had a lower prevalence of the APOE-e4 carrier (41.9% vs. 56.2%). They also had a higher prevalence of hypertension, heart failure, atrial fibrillation, diuretic use, beta-blocker use, and APOE-e2 carrier status. Greater age at death, diuretic use, and APOE-e2 were the only characteristics independently associated with higher odds of the AD resilience phenotype (adjusted OR, 1.09; 95% CI, 1.05-1.13; p < 0.01; 2.00 (1.04-3.87), p = 0.04, 2.71 (1.31-5.64), p < 0.01, respectively). The phenotype of resilience to cognitive impairment is uncommon in older adults who have neuropathological evidence of AD.

Hybrid Value-Aware Transformer Architecture for Joint Learning from Longitudinal and Non-Longitudinal Clinical Data.

Transformer is the latest deep neural network (DNN) architecture for sequence data learning, which has revolutionized the field of natural language processing. This success has motivated researchers to explore its application in the healthcare domain. Despite the similarities between longitudinal clinical data and natural language data, clinical data presents unique complexities that make adapting Transformer to this domain challenging. To address this issue, we have designed a new Transformer-based DNN architecture, referred to as Hybrid Value-Aware Transformer (HVAT), which can jointly learn from longitudinal and non-longitudinal clinical data. HVAT is unique in the ability to learn from the numerical values associated with clinical codes/concepts such as labs, and in the use of a flexible longitudinal data representation called clinical tokens. We have also trained a prototype HVAT model on a case-control dataset, achieving high performance in predicting Alzheimer's disease and related dementias as the patient outcome. The results demonstrate the potential of HVAT for broader clinical data-learning tasks.

Hybrid Value-Aware Transformer Architecture for Joint Learning from Longitudinal and Non-Longitudinal Clinical Data.

Transformer is the latest deep neural network (DNN) architecture for sequence data learning that has revolutionized the field of natural language processing. This success has motivated researchers to explore its application in the healthcare domain. Despite the similarities between longitudinal clinical data and natural language data, clinical data presents unique complexities that make adapting Transformer to this domain challenging. To address this issue, we have designed a new Transformer-based DNN architecture, referred to as Hybrid Value-Aware Transformer (HVAT), which can jointly learn from longitudinal and non-longitudinal clinical data. HVAT is unique in the ability to learn from the numerical values associated with clinical codes/concepts such as labs, and also the use of a flexible longitudinal data representation called clinical tokens. We trained a prototype HVAT model on a case-control dataset, achieving high performance in predicting Alzheimer’s disease and related dementias as the patient outcome. The result demonstrates the potential of HVAT for broader clinical data learning tasks.

Medication-Wide Association Study Plus (MWAS+): A Proof of Concept Study on Drug Repurposing.

The high cost and time for developing a new drug or repositioning a partially-developed drug has fueled interest in "repurposing" drugs. Drug repurposing is particularly of interest for Alzheimer's disease (AD) or AD-related dementias (ADRD) because there are no unrestricted disease-modifying treatments for ADRD. We have designed and pilot tested a 3-Step Medication-Wide Association Study Plus (MWAS+) approach to rigorously accelerate the identification of drugs with a high potential to be repurposed for delaying and preventing AD/ADRD: Step 1 is a hypothesis-free exploration; Step 2 is mechanistic filtering; And Step 3 is hypothesis testing using observational data and prospective cohort design. Our results demonstrated the feasibility of the MWAS+ approach. The Step 1 analysis identified potential candidate drugs including atorvastatin and GLP1. The literature search in Step 2 found evidence supporting the mechanistic plausibility of the statin-ADRD association. Finally, Step 3 confirmed our hypothesis that statin may lower the risk of incident ADRD, which was statistically significant using a target trial design that emulated randomized controlled trials.

Alzheimer's Disease and Alzheimer's Disease-Related Dementias in Older African American and White Veterans.

BACKGROUND: Racial disparity in the epidemiology of Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) has been reported. However, less is known about this disparity among Veterans. OBJECTIVE: To estimate the racial disparity in AD/ADRD among the Veterans. METHODS: Of the 5,413,418 Veterans≥65 years receiving care at the Veterans Health Administration (1999-2016), 4,045,269 were free of prevalent AD/ADRD, schizophrenia, or bipolar disorder at baseline. Of these, 432,469 were African American. Race was self-identified and incident AD/ADRD during 20 (median 6.7) years of follow-up was ascertained using International Classification of Diseases codes. RESULTS: Patients had a mean age of 70.4 (±6.6) years and 97.8% were men. Age-sex-adjusted incidence of AD/ADRD per 1,000 person-year was 19.3 and 10.8 for African American and white Veterans, respectively (age-sex-adjusted hazard ratio associated with African American race, 1.77; 95% confidence interval, 1.75-1.79; p < 0.0001). This association remained essentially unchanged after multivariable adjustment (hazard ratio, 1.67; 95% confidence interval, 1.65-1.69; p < 0.0001). Among the key baseline characteristics that were significant predictors of AD/ADRD in both races, stroke was a significantly stronger predictor among African Americans, and Hispanic ethnicity and depression among whites (p-value for all interaction,<0.0001). CONCLUSION: The findings of a higher incidence of AD/ADRD among African American Veterans is consistent with the findings in the general population reported in the literature, although the overall incidence appears to be lower than that in the general population. Future studies need to examine this disparity in incidence as well as the between-race heterogeneity in AD/ADRD risk.

Can motor function uncertainty and local instability within upper-extremity dual-tasking predict amnestic mild cognitive impairment and early-stage Alzheimer's disease?

In this study, we examined the uncertainty and local instability of motor function for cognitive impairment screening using a previously validated upper-extremity function (UEF). This approach was established based upon the fact that elders with an impaired executive function have trouble in the simultaneous execution of a motor and a cognitive task (dual-tasking). Older adults aged 65 years and older were recruited and stratified into 1) cognitive normal (CN), 2) amnestic MCI of the Alzheimer's type (aMCI), and 3) early-stage Alzheimer's Disease (AD). Participants performed normal-paced repetitive elbow flexion without counting and while counting backward by ones and threes. The influence of cognitive task on motor function was measured using uncertainty (measured by Shannon entropy), and local instability (measured by the largest Lyapunov exponent) of elbow flexion and compared between cognitive groups using ANOVAs, while adjusting for age, sex, and BMI. We developed logistic ordinal regression models for predicting cognitive groups based on these nonlinear measures. A total of 81 participants were recruited, including 35 CN (age = 83.8 ± 6.9), 30 aMCI (age = 83.9 ± 6.9), and 16 early AD (age = 83.2 ± 6.6). Uncertainty of motor function demonstrated the strongest associations with cognitive impairment, with an effect size of 0.52, 0.88, and 0.51 for CN vs. aMCI, CN vs. AD, and aMCI vs. AD comparisons, respectively. Ordinal logistic models predicted cognitive impairment (aMCI and AD combined) with a sensitivity and specificity of 0.82. The findings accentuate the potential of employing nonlinear dynamical features of motor functions during dual-tasking, especially uncertainty, in detecting cognitive impairment.