A bloodâ based nutritional risk index explains cognitive enhancement and decline in the multidomain Alzheimer prevention trial

IntroductionMultinutrient approaches may produce more robust effects on brain health through interactive qualities. We hypothesized that a bloodâ based nutritional risk index (NRI) including three biomarkers of diet quality can explain cognitive trajectories in the multidomain Alzheimer prevention trial (MAPT) over 3â years.MethodsThe NRI included erythrocyte nâ 3 polyunsaturated fatty acids (nâ 3 PUFA 22:6nâ 3 and 20:5nâ 3), serum 25â hydroxyvitamin D, and plasma homocysteine. The NRI scores reflect the number of nutritional risk factors (0â 3). The primary outcome in MAPT was a cognitive composite Z score within each participant that was fit with linear mixedâ effects models.ResultsEighty percent had at lease one nutritional risk factor for cognitive decline (NRI â ¥1: 573 of 712). Participants presenting without nutritional risk factors (NRI=0) exhibited cognitive enhancement (β = 0.03 standard units [SU]/y), whereas each NRI point increase corresponded to an incremental acceleration in rates of cognitive decline (NRIâ 1: β = â 0.04 SU/y, P = .03; NRIâ 2: β = â 0.08 SU/y, P < .0001; and NRIâ 3: β = â 0.11 SU/y, P = .0008).DiscussionIdentifying and addressing these wellâ established nutritional risk factors may reduce ageâ related cognitive decline in older adults; an observation that warrants further study.Highlightsâ ¢Multiâ nutrient approaches may produce more robust effects through interactive propertiesâ ¢Nutritional risk index can objectively quantify nutritionâ related cognitive changesâ ¢Optimum nutritional status associated with cognitive enhancement over 3â yearsâ ¢Suboptimum nutritional status associated with cognitive decline over 3â yearsâ ¢Optimizing this nutritional risk index may promote cognitive health in older adultsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152935/1/trc2jtrci201911004.pd

Prospective association of white matter hyperintensity volume and frailty in older adults

BACKGROUND: Frailty is a prevalent geriatric condition and its association with brain health is still weakly investigated. The objective of this study was to examine whether brain white matter hyperintensities (WMH) were related to longitudinal changes in frailty severity in community-dwelling older adults. METHODS: 113 community-dwelling older adults, aged 70years and over, enrolled in the placebo group from the 3-year Multidomain Alzheimer's Preventive Trial (MAPT). Frailty was assessed using Fried's frailty phenotype as an ordinal variable (range from 0 to 5, higher is worse) at baseline, 6, 12, 24 and 36months. We obtained brain WMH data using magnetic resonance imaging (MRI) at the first and last year of the trial. The progression of WMH volume was evaluated. RESULTS: We included 113 baseline and 83 follow-up MRIs in this study. The median baseline WMH volume was 10.6 (6.0, 15.0) cm(3) and the median progression of WMH was 1.1 (-0.3, 2.2) cm(3). Our results indicate that people with higher baseline WMH had a 6% increased likelihood of increasing their frailty phenotype score (adjusted OR: 1.06, (1.00-1.12, p=0.036)). No associations were found between the progression of WMH (slow vs. fast) volume accumulation and frailty severity. CONCLUSION: WMH were associated with frailty severity over time. Why the progression of WMH was not associated with changes in frailty severity requires further investigation

Cognitive Event-Related Potential, an Early Diagnosis Biomarker in Frail Elderly Subjects: The ERP-MAPT-PLUS Ancillary Study

International audienc

Cross-sectional Associations of Fatigue with Cerebral β-Amyloid in Older Adults at Risk of Dementia

Fatigue is a common symptom in the elderly and has also been associated with impaired cognition in older adults. Hence, we sought to explore the cross-sectional relationship between fatigue and cerebral β-amyloid (Aβ) in 269 elderly individuals reporting subjective memory complaints from the Multidomain Alzheimer Preventive Trial. Standard uptake value ratios (SUVRs) were generated by [18F] florbetapir positron emission tomography (PET) using the cerebellum as a reference. Cortical-to-cerebellar SUVRs (cortical-SUVRs) were obtained using the mean signal from the frontal cortex, temporal cortex, parietal cortex, precuneus, anterior cingulate, and posterior cingulate. Other brain regions independently assessed were the anterior cingulate, anterior putamen, caudate, hippocampus, medial orbitofrontal cortex, occipital cortex, parietal cortex, pons, posterior cingulate, posterior putamen, precuneus, semioval center, and temporal cortex. Fatigue was defined according to two questions retrieved from the Center for Epidemiological Studies-Depression scale. Chronic fatigue was defined as meeting fatigue criteria at two consecutive clinical visits 6 months apart between study baseline and 1 year (visits were performed at baseline, 6 months and 1 year then annually). Cross-sectional associations between fatigue variables and cerebral Aβ were explored using fully adjusted multiple linear regression models. We found no statistically significant cross-sectional associations between fatigue assessed at the clinical visit closest to PET and Aβ in any brain region. Similarly, chronic fatigue was not significantly associated with Aβ load. Sensitivity analysis in subjects with a Clinical Dementia Rating of 0.5 showed that fatigue reported at the clinical visit closest to PET was, however, weakly associated with increased Aβ in the hippocampus (B-coefficient: 0.07, 95% CI: 0.01, 0.12, p = 0.016). These preliminary results suggest that fatigue might be associated with Aβ in brain regions associated with Alzheimer’s disease in subjects in the early stages of disease