Meditation and Cognitive Outcomes: A Longitudinal Analysis Using Data From the Health and Retirement Study 2000-2016.

Objective: We aimed to assess the association between meditation practice and cognitive function over time among middle-aged and older adults. Method: We included Health and Retirement Study (HRS) participants assessed for meditation practice in the year 2000 as part of the HRS alternative medicine module (n = 1,160) and were followed up for outcomes over 2000-2016 period. We examined the association between meditation ≥ twice a week vs none/less frequent practice and changes in the outcomes of recall, global cognitive function, and quantitative reasoning using generalized linear regression models. Stratified analyses among persons with/without self-reported baseline depressive symptoms were conducted to assess the link between meditation and cognitive outcomes. Results: Among our full study sample, meditation ≥ twice a week was not significantly associated with total recall [ß; 95% CI: -0.97, 0.57; p = 0.61], global cognitive function [ß; 95% CI: -1.01, 1.12; p = 0.92], and quantitative reasoning [ß; 95% CI: -31.27, 8.32; p = 0.26]. However, among those who did not have self-reported depressive symptoms at baseline, meditation ≥ twice a week was associated with improvement in cognitive outcomes such as total recall [ß; 95% CI: 0.03, 0.18; p = 0.01] and global cognitive function [ß; 95% CI: 0.05, 0.40; p = 0.01] over time. Conclusions: Frequent meditation practice might have a protective effect on cognitive outcomes over time, but this protection could be limited to those without self-reported baseline depressive symptoms. Future studies could incorporate more precise meditation practice assessment, investigate the effect of meditation on cognitive outcomes over time, and include more rigorous study designs with randomized group assignment. Pre-registration: This study is not preregistered.

Nutrition state of science and dementia prevention: recommendations of the Nutrition for Dementia Prevention Working Group.

Observational studies suggest that nutritional factors have a potential cognitive benefit. However, systematic reviews of randomised trials of dietary and nutritional supplements have reported largely null effects on cognitive outcomes and have highlighted study inconsistencies and other limitations. In this Personal View, the Nutrition for Dementia Prevention Working Group presents what we consider to be limitations in the existing nutrition clinical trials for dementia prevention. On the basis of this evidence, we propose recommendations for incorporating dietary patterns and the use of genetic, and nutrition assessment tools, biomarkers, and novel clinical trial designs to guide future trial developments. Nutrition-based research has unique challenges that could require testing both more personalised interventions in targeted risk subgroups, identified by nutritional and other biomarkers, and large-scale and pragmatic study designs for more generalisable public health interventions across diverse populations.

Dietary factors and MRI metrics in early Multiple Sclerosis.

BACKGROUND: Despite significant interest in diet by the MS community, research on this topic is limited; there are no published studies evaluating associations between diet and neuroimaging in MS. METHODS: We utilized baseline data from the RADIEMS cohort of early MS (diagnosed <5.0 years, n=180). Participants underwent brain MRIs to derive normalized total gray and thalamic volumes, T2 lesion volume, and white matter microstructural integrity of normal appearing white matter (NAWM). Participants completed food frequency questionnaires (FFQ) from which we calculated adherence scores to pre-specified dietary patterns including the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet. We evaluated intake of the following pre-specified dietary components: fruits, vegetables, legumes, nuts, whole grains, dairy, fried foods, processed meats, and fat intake. We used multivariable-adjusted linear regression to evaluate MRI metrics versus dietary measures. RESULTS: MIND diet score was associated with thalamic volume; individuals in the highest quartile of MIND diet scores had greater thalamic volumes versus those in the lowest quartile (Q4 vs. Q1: 1.03mL; 95%CI: 0.26mL, 1.79mL; p<0.01). For individual food/nutrients, higher intakes of full-fat dairy were associated with lower T2 lesion volumes (Q4 vs. Q1: -0.93mL; 95%CI: -1.51mL, -0.35ml; p<0.01). Higher intakes of marine omega-3 fatty acids were associated with greater NAWM microstructural integrity (Q4 vs. Q1: 0.40; 95%CI: 0.03, 0.76; p=0.04). Other foods/nutrients were not associated with MRI outcomes. CONCLUSIONS: In this first study focused on neuroimaging and diet in MS, we note significant associations in a cross-sectional early MS cohort. Longitudinal follow-up of imaging/clinical outcomes will provide additional insights.

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.

Rhizosphere protists are key determinants of plant health.

BACKGROUND: Plant health is intimately influenced by the rhizosphere microbiome, a complex assembly of organisms that changes markedly across plant growth. However, most rhizosphere microbiome research has focused on fractions of this microbiome, particularly bacteria and fungi. It remains unknown how other microbial components, especially key microbiome predators-protists-are linked to plant health. Here, we investigated the holistic rhizosphere microbiome including bacteria, microbial eukaryotes (fungi and protists), as well as functional microbial metabolism genes. We investigated these communities and functional genes throughout the growth of tomato plants that either developed disease symptoms or remained healthy under field conditions. RESULTS: We found that pathogen dynamics across plant growth is best predicted by protists. More specifically, communities of microbial-feeding phagotrophic protists differed between later healthy and diseased plants at plant establishment. The relative abundance of these phagotrophs negatively correlated with pathogen abundance across plant growth, suggesting that predator-prey interactions influence pathogen performance. Furthermore, phagotrophic protists likely shifted bacterial functioning by enhancing pathogen-suppressing secondary metabolite genes involved in mitigating pathogen success. CONCLUSIONS: We illustrate the importance of protists as top-down controllers of microbiome functioning linked to plant health. We propose that a holistic microbiome perspective, including bacteria and protists, provides the optimal next step in predicting plant performance. Video Abstract.

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 > or = 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, omega-3 polyunsaturated fatty acids, omega-6 polyunsaturated fatty acids, vitamin E, vitamin B(12), 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.