Mediterranean Diet, Inflammatory and Metabolic Biomarkers, and Risk of Alzheimer's Disease

We aimed to investigate the association between adherence to the Mediterranean diet (MeDi) and Alzheimer's disease (AD) risk in a prospective study. Specifically, we analyzed reduced inflammation and improved metabolic profile as a potential medium through which the MeDi reduced the risk of AD. During a 4-year follow-up, 118 incident AD cases were identified among the 1219 non-demented elderly (age ⩾ 65) subjects who provided dietary information and blood samples at baseline. We used high-sensitivity C-reactive protein (hsCRP) as an index of systemic inflammation, and fasting insulin and adiponectin as indexes of metabolic profile. We investigated whether there was a change in the association between MeDi and incident AD risk when the biomarkers were introduced into multivariable adjusted COX models. Better adherence to MeDi was associated with lower level of hsCRP (p =0.003), but not fasting insulin or adiponectin. Better adherence to MeDi was significantly associated with lower risk for AD: compared to those in the lowest tertile of MeDi, subjects in the highest tertile had a 34% less risk of developing AD (p-for-trend =0.04). Introduction of the hsCRP, fasting insulin, adiponectin, or combinations of them into the COX model did not change the magnitude of the association between MeDi and incident AD. Ultimately, the favorable association between better adherence to MeDi and lower risk of AD did not seem to be mediated by hsCRP, fasting insulin, or adiponectin. Other aspects of inflammatory and metabolic pathways not captured by these biomarkers, or non-inflammatory or non-metabolic pathways, may be relevant to the MeDi-AD association

Mediterranean Diet, Inflammatory and Metabolic Biomarkers, and Risk of Alzheimer's Disease

We aimed to investigate the association between adherence to the Mediterranean diet (MeDi) and Alzheimer's disease (AD) risk in a prospective study. Specifically, we analyzed reduced inflammation and improved metabolic profile as a potential medium through which the MeDi reduced the risk of AD. During a 4-year follow-up, 118 incident AD cases were identified among the 1219 non-demented elderly (age ⩾ 65) subjects who provided dietary information and blood samples at baseline. We used high-sensitivity C-reactive protein (hsCRP) as an index of systemic inflammation, and fasting insulin and adiponectin as indexes of metabolic profile. We investigated whether there was a change in the association between MeDi and incident AD risk when the biomarkers were introduced into multivariable adjusted COX models. Better adherence to MeDi was associated with lower level of hsCRP (p =0.003), but not fasting insulin or adiponectin. Better adherence to MeDi was significantly associated with lower risk for AD: compared to those in the lowest tertile of MeDi, subjects in the highest tertile had a 34% less risk of developing AD (p-for-trend =0.04). Introduction of the hsCRP, fasting insulin, adiponectin, or combinations of them into the COX model did not change the magnitude of the association between MeDi and incident AD. Ultimately, the favorable association between better adherence to MeDi and lower risk of AD did not seem to be mediated by hsCRP, fasting insulin, or adiponectin. Other aspects of inflammatory and metabolic pathways not captured by these biomarkers, or non-inflammatory or non-metabolic pathways, may be relevant to the MeDi-AD association

Food Combination and Alzheimer Disease Risk: A Protective Diet

Objective: To assess the association between food combination and Alzheimer disease (AD) risk. Because foods are not consumed in isolation, dietary pattern (DP) analysis of food combination, taking into account the interactions among food components, may offer methodological advantages. Design: Prospective cohort study. Setting: Northern Manhattan, New York, New York. Patients or Other Participants: Two thousand one hundred forty-eight community-based elderly subjects (aged ≥65 years) without dementia in New York provided dietary information and were prospectively evaluated with the same standardized neurological and neuropsychological measures approximately every 1.5 years. Using reduced rank regression, we calculated DPs based on their ability to explain variation in 7 potentially AD-related nutrients: saturated fatty acids, monounsaturated fatty acids, ω-3 polyunsaturated fatty acids, ω-6 polyunsaturated fatty acids, vitamin E, vitamin B12, and folate. The associations of reduced rank regression–derived DPs with AD risk were then examined using a Cox proportional hazards model. Main Outcome Measure: Incident AD risk. Results: Two hundred fifty-three subjects developed AD during a follow-up of 3.9 years. We identified a DP strongly associated with lower AD risk: compared with subjects in the lowest tertile of adherence to this pattern, the AD hazard ratio (95% confidence interval) for subjects in the highest DP tertile was 0.62 (0.43-0.89) after multivariable adjustment (P for trend = .01). This DP was characterized by higher intakes of salad dressing, nuts, fish, tomatoes, poultry, cruciferous vegetables, fruits, and dark and green leafy vegetables and a lower intake of high-fat dairy products, red meat, organ meat, and butter. Conclusion: Simultaneous consideration of previous knowledge regarding potentially AD-related nutrients and multiple food groups can aid in identifying food combinations that are associated with AD risk

Thin-Shell Object Manipulations With Differentiable Physics Simulations

In this work, we aim to teach robots to manipulate various thin-shell materials. Prior works studying thin-shell object manipulation mostly rely on heuristic policies or learn policies from real-world video demonstrations, and only focus on limited material types and tasks (e.g., cloth unfolding). However, these approaches face significant challenges when extended to a wider variety of thin-shell materials and a diverse range of tasks. While virtual simulations are shown to be effective in diverse robot skill learning and evaluation, prior thin-shell simulation environments only support a subset of thin-shell materials, which also limits their supported range of tasks. We introduce ThinShellLab - a fully differentiable simulation platform tailored for robotic interactions with diverse thin-shell materials possessing varying material properties, enabling flexible thin-shell manipulation skill learning and evaluation. Our experiments suggest that manipulating thin-shell objects presents several unique challenges: 1) thin-shell manipulation relies heavily on frictional forces due to the objects' co-dimensional nature, 2) the materials being manipulated are highly sensitive to minimal variations in interaction actions, and 3) the constant and frequent alteration in contact pairs makes trajectory optimization methods susceptible to local optima, and neither standard reinforcement learning algorithms nor trajectory optimization methods (either gradient-based or gradient-free) are able to solve the tasks alone. To overcome these challenges, we present an optimization scheme that couples sampling-based trajectory optimization and gradient-based optimization, boosting both learning efficiency and converged performance across various proposed tasks. In addition, the differentiable nature of our platform facilitates a smooth sim-to-real transition.Comment: ICLR 202

Use and Cost of Hospitalization in Dementia: Longitudinal Results from a Community-Based Study

OBJECTIVES: The aim of this study is to examine the relative contribution of functional impairment and cognitive deficits on risk of hospitalization and costs. METHODS: A prospective cohort of Medicare beneficiaries aged 65 and older who participated in the Washington Heights-Inwood Columbia Aging Project (WHICAP) were followed approximately every 18 months for over 10 years (1805 never diagnosed with dementia during study period, 221 diagnosed with dementia at enrollment). Hospitalization and Medicare expenditures data (1999-2010) were obtained from Medicare claims. Multivariate analyses were conducted to examine (1) risk of all-cause hospitalizations, (2) hospitalizations from ambulatory care sensitive (ACSs) conditions, (3) hospital length of stay (LOS), and (4) Medicare expenditures. Propensity score matching methods were used to reduce observed differences between demented and non-demented groups at study enrollment. Analyses took into account repeated observations within each individual. RESULTS: Compared to propensity-matched individuals without dementia, individuals with dementia had significantly higher risk for all-cause hospitalization, longer LOS, and higher Medicare expenditures. Functional and cognitive deficits were significantly associated with higher risks for hospitalizations, hospital LOS, and Medicare expenditures. Functional and cognitive deficits were associated with higher risks of for some ACS but not all admissions. CONCLUSIONS: These results allow us to differentiate the impact of functional and cognitive deficits on hospitalizations. To develop strategies to reduce hospitalizations and expenditures, better understanding of which types of hospitalizations and which disease characteristics impact these outcomes will be critical

Change in Body Mass Index before and after Alzheimer's Disease Onset

OBJECTIVES: A high body mass index (BMI) in middle-age or a decrease in BMI at late-age has been considered a predictor for the development of Alzheimer's disease (AD). However, little is known about the BMI change close to or after AD onset. METHODS: BMI of participants from three cohorts, the Washington Heights and Inwood Columbia Aging Project (WHICAP; population-based) and the Predictors Study (clinic-based), and National Alzheimer's Coordinating Center (NACC; clinic-based) were analyzed longitudinally. We used generalized estimating equations to test whether there were significant changes of BMI over time, adjusting for age, sex, education, race, and research center. Stratification analyses were run to determine whether BMI changes depended on baseline BMI status. RESULTS: BMI declined over time up to AD clinical onset, with an annual decrease of 0.21 (p=0.02) in WHICAP and 0.18 (p=0.04) kg/m2 in NACC. After clinical onset of AD, there was no significant decrease of BMI. BMI even increased (b=0.11, p=0.004) among prevalent AD participants in NACC. During the prodromal period, BMI decreased over time in overweight (BMI>/=25 and /=30) NACC participants. After AD onset, BMI tended to increase in underweight/normal weight (BMI<25) patients and decrease in obese patients in all three cohorts, although the results were significant in NACC study only. CONCLUSIONS: Our study suggests that while BMI declines before the clinical AD onset, it levels off after clinical AD onset, and might even increase in prevalent AD. The pattern of BMI change may also depend on the initial BMI

Reproducibility of serum cytokines in an elderly population

Background It is important to assess the temporal reproducibility of circulating cytokines for their utility in epidemiological studies. However, existing evidence is limited and inconsistent, especially for the elderly population. Methods Sixty-five elderly (mean age = 77.89 ± 6.14 years) subjects were randomly selected from an existing prospective cohort study. Levels of 41 cytokines in 195 serum samples, collected at three separate visits that were up to 15.26 years apart, were measured by the Luminex technology. The temporal reproducibility of cytokines was estimated by the intraclass correlation coefficient (ICC) calculated using a mixed-effects model. In addition, data analyses were stratified by the median (4.49 years) of time intervals across sample collection. Sensitivity analyses were performed when excluding subjects with undetectable samples. Results A total of 23 cytokines were detectable in more than 60% of samples. Fair to good (ICC = 0.40 to 0.75) and excellent (ICC > 0.75) reproducibility was found in 10 (Eotaxin, VEGF, FGF-2, G-CSF, MDC, GM-CSF, TGFα, IP-10, MIP-1β, IL-1RA) and 5 (GRO, IFNγ, IL-17, PDGF-AA, IL-4) cytokines, respectively. The results were not changed dramatically in the stratification and sensitivity analyses. Conclusions Serum levels of the selected 15 cytokines measured with Luminex technology displayed fair to excellent within-person temporal reproducibility among elderly population

Misidentification of dementia in Medicare claims and related costs

Objectives: To examine how misidentification of dementia affects estimation of Medicare costs in a largely minority cohort of participants for whom accurate in‐person diagnoses are available. Design: Prospective cohort study. Setting: Washington Heights‐Inwood Columbia Aging Project, a multiethnic, population‐based, prospective study of cognitive aging of Medicare beneficiaries aged 65 and older. Participants: Individuals clinically diagnosed with dementia (n=495) and individuals clinically diagnosed without dementia (n=1,701). Measurements: Medicare claims‐identified dementia was defined according to the presence of any International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes for Alzheimer's disease and related dementias in all available claims during the study period. Participant characteristics associated with claims misidentification of dementia were estimated using logistic regression. Effects of dementia misidentification on Medicare expenditures were estimated using generalized linear models. Results: Medicare claims correctly identified 250 of the 495 (51%) dementia cases and 1,565 of the 1,701 (92%) nondementia cases. Sensitivity of claims‐identified dementia was 0.51, and specificity was 0.92. Average annual Medicare expenditures were $14,721 for a beneficiary with a clinical diagnosis of dementia, and$18,208 for a beneficiary with claim‐identified dementia, suggesting an overestimation of $3,487 per person per year when Medicare claims were used to identify dementia. Total annual expenditures for all beneficiaries with claims‐identified dementia were$258,707 lower than that for all those who were clinically diagnosed, suggesting an overall underestimation of total Medicare expenditures if Medicare claims were used to identify dementia. Different types of misidentification have different effects on dementia‐related cost estimates. Average annual expenditures per person were highest for false positives. Conclusion: Misidentification of dementia in Medicare claims is common. Using claims to identify dementia may result in significantly biased estimates of the cost of dementia

Medicaid Contributes Substantial Costs to Dementia Care in an Ethnically Diverse Community

Objectives: The main objective of this study was to estimate effects of dementia on Medicaid expenditures in an ethnically diverse community. Methods: The sample included 1,211 Medicare beneficiaries who did not have any Medicaid coverage and 568 who additionally had full Medicaid coverage enrolled in the Washington Heights-Inwood Columbia Aging Project (WHICAP), a multiethnic, population-based, prospective study of cognitive aging in northern Manhattan (1999–2010). Individuals’ dementia status was determined using a rigorous clinical protocol. Relationship between dementia and Medicaid coverage and expenditures were estimated using a two-part model. Results: In participants who had full Medicaid coverage, average annual Medicaid expenditures were substantially higher for those with dementia than those without dementia ($50,270 vs.$21,966, p < .001), but Medicare expenditures did not differ by dementia status ($8,458 vs.$9,324, p = .19). In participants who did not have any Medicaid coverage, average annual Medicare expenditures were substantially higher for those with dementia than those without dementia ($12,408 vs.$8,113, p = .02). In adjusted models, dementia was associated with a $6,278 increase in annual Medicaid spending per person after controlling for other characteristics. Discussion: Results highlight Medicaid’s contribution to covering the cost of dementia care in addition to Medicare. Studies that do not include Medicaid are unlikely to accurately reflect the true cost of dementia

Dependence Clusters in Alzheimer Disease and Medicare Expenditures: A Longitudinal Analysis From the Predictors Study

Introduction: Dependence in Alzheimer disease has been proposed as a holistic, transparent, and meaningful representation of disease severity. Modeling clusters in dependence trajectories can help understand changes in disease course and care cost over time. Methods: Sample consisted of 199 initially community-living patients with probable Alzheimer disease recruited from 3 academic medical centers in the United States followed for up to 10 years and had ≥2 Dependence Scale recorded. Nonparametric K-means cluster analysis for longitudinal data (KmL) was used to identify dependence clusters. Medicare expenditures data (1999-2010) were compared between clusters. Results: KmL identified 2 distinct Dependence Scale clusters: (A) high initial dependence, faster decline, and (B) low initial dependence, slower decline. Adjusting for patient characteristics, 6-month Medicare expenditures increased over time with widening between-cluster differences. Discussion: Dependence captures dementia care costs over time. Better characterization of dependence clusters has significant implications for understanding disease progression, trial design and care planning