The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global ...perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression.
Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ identification and quantification p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and "asymptomatic Alzheimer's disease" (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes-sphingolipids and glycerophospholipids-that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer's Disease Neuroimaging Initiative ADNI, N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that summarized the relative importance of each metabolite to severity of AD pathology and disease progression (Endophenotype Association Score in Early Alzheimer's Disease EASE-AD). Finally, we mapped the main metabolite classes emerging from our analyses to key biological pathways implicated in AD pathogenesis. We found that distinct sphingolipid species including sphingomyelin (SM) with acyl residue sums C16:0, C18:1, and C16:1 (SM C16:0, SM C18:1, SM C16:1) and hydroxysphingomyelin with acyl residue sum C14:1 (SM (OH) C14:1) were consistently associated with severity of AD pathology at autopsy and AD progression across prodromal and preclinical stages. Higher log-transformed blood concentrations of all four sphingolipids in cognitively normal individuals were significantly associated with increased risk of future conversion to incident AD: SM C16:0 (hazard ratio HR = 4.430, 95% confidence interval CI = 1.703-11.520, p = 0.002), SM C16:1 (HR = 3.455, 95% CI = 1.516-7.873, p = 0.003), SM (OH) C14:1 (HR = 3.539, 95% CI = 1.373-9.122, p = 0.009), and SM C18:1 (HR = 2.255, 95% CI = 1.047-4.855, p = 0.038). The sphingolipid species identified map to several biologically relevant pathways implicated in AD, including tau phosphorylation, amyloid-β (Aβ) metabolism, calcium homeostasis, acetylcholine biosynthesis, and apoptosis. Our study has limitations: the relatively small number of brain tissue samples may have limited our power to detect significant associations, control for heterogeneity between groups, and replicate our findings in independent, autopsy-derived brain samples.
We present a novel framework to identify biologically relevant brain and blood metabolites associated with disease pathology and progression during the prodromal and preclinical stages of AD. Our results show that perturbations in sphingolipid metabolism are consistently associated with endophenotypes across preclinical and prodromal AD, as well as with AD pathology at autopsy. Sphingolipids may be biologically relevant biomarkers for the early detection of AD, and correcting perturbations in sphingolipid metabolism may be a plausible and novel therapeutic strategy in AD.
There is growing evidence that Alzheimer disease (AD) is a pervasive metabolic disorder with dysregulation in multiple biochemical pathways underlying its pathogenesis. Understanding how ...perturbations in metabolism are related to AD is critical to identifying novel targets for disease-modifying therapies. In this study, we test whether AD pathogenesis is associated with dysregulation in brain transmethylation and polyamine pathways.
We first performed targeted and quantitative metabolomics assays using capillary electrophoresis-mass spectrometry (CE-MS) on brain samples from three groups in the Baltimore Longitudinal Study of Aging (BLSA) (AD: n = 17; Asymptomatic AD ASY: n = 13; Control CN: n = 13) (overall 37.2% female; mean age at death 86.118 ± 9.842 years) in regions both vulnerable and resistant to AD pathology. Using linear mixed-effects models within two primary brain regions (inferior temporal gyrus ITG and middle frontal gyrus MFG), we tested associations between brain tissue concentrations of 26 metabolites and the following primary outcomes: group differences, Consortium to Establish a Registry for Alzheimer's Disease (CERAD) (neuritic plaque burden), and Braak (neurofibrillary pathology) scores. We found significant alterations in concentrations of metabolites in AD relative to CN samples, as well as associations with severity of both CERAD and Braak, mainly in the ITG. These metabolites represented biochemical reactions in the (1) methionine cycle (choline: lower in AD, p = 0.003; S-adenosyl methionine: higher in AD, p = 0.005); (2) transsulfuration and glutathione synthesis (cysteine: higher in AD, p < 0.001; reduced glutathione GSH: higher in AD, p < 0.001); (3) polyamine synthesis/catabolism (spermidine: higher in AD, p = 0.004); (4) urea cycle (N-acetyl glutamate: lower in AD, p < 0.001); (5) glutamate-aspartate metabolism (N-acetyl aspartate: lower in AD, p = 0.002); and (6) neurotransmitter metabolism (gamma-amino-butyric acid: lower in AD, p < 0.001). Utilizing three Gene Expression Omnibus (GEO) datasets, we then examined mRNA expression levels of 71 genes encoding enzymes regulating key reactions within these pathways in the entorhinal cortex (ERC; AD: n = 25; CN: n = 52) and hippocampus (AD: n = 29; CN: n = 56). Complementing our metabolomics results, our transcriptomics analyses also revealed significant alterations in gene expression levels of key enzymatic regulators of biochemical reactions linked to transmethylation and polyamine metabolism. Our study has limitations: our metabolomics assays measured only a small proportion of all metabolites participating in the pathways we examined. Our study is also cross-sectional, limiting our ability to directly test how AD progression may impact changes in metabolite concentrations or differential-gene expression. Additionally, the relatively small number of brain tissue samples may have limited our power to detect alterations in all pathway-specific metabolites and their genetic regulators.
In this study, we observed broad dysregulation of transmethylation and polyamine synthesis/catabolism, including abnormalities in neurotransmitter signaling, urea cycle, aspartate-glutamate metabolism, and glutathione synthesis. Our results implicate alterations in cellular methylation potential and increased flux in the transmethylation pathways, increased demand on antioxidant defense mechanisms, perturbations in intermediate metabolism in the urea cycle and aspartate-glutamate pathways disrupting mitochondrial bioenergetics, increased polyamine biosynthesis and breakdown, as well as abnormalities in neurotransmitter metabolism that are related to AD.
Gravitational waves carry energy, angular momentum, and linear momentum. In generic binary black hole mergers, the loss of linear momentum imparts a recoil velocity, or a "kick," to the remnant black ...hole. We exploit recent advances in gravitational waveform and remnant black hole modeling to extract information about the kick from the gravitational wave signal. Kick measurements such as these are astrophysically valuable, enabling independent constraints on the rate of second-generation merger. Further, we show that kicks must be factored into future ringdown tests of general relativity with third-generation gravitational wave detectors to avoid systematic biases. We find that, although little information can be gained about the kick for existing gravitational wave events, interesting measurements will soon become possible as detectors improve. We show that, once LIGO and Virgo reach their design sensitivities, we will reliably extract the kick velocity for generically precessing binaries-including the so-called superkicks, reaching up to 5000 km/s.
We present accurate fits for the remnant properties of generically precessing binary black holes, trained on large banks of numerical-relativity simulations. We use Gaussian process regression to ...interpolate the remnant mass, spin, and recoil velocity in the seven-dimensional parameter space of precessing black-hole binaries with mass ratios q≤2, and spin magnitudes χ_{1}, χ_{2}≤0.8. For precessing systems, our errors in estimating the remnant mass, spin magnitude, and kick magnitude are lower than those of existing fitting formulae by at least an order of magnitude (improvement is also reported in the extrapolated region at high mass ratios and spins). In addition, we also model the remnant spin and kick directions. Being trained directly on precessing simulations, our fits are free from ambiguities regarding the initial frequency at which precessing quantities are defined. We also construct a model for remnant properties of aligned-spin systems with mass ratios q≤8, and spin magnitudes χ_{1}, χ_{2}≤0.8. As a byproduct, we also provide error estimates for all fitted quantities, which can be consistently incorporated into current and future gravitational-wave parameter-estimation analyses. Our model(s) are made publicly available through a fast and easy-to-use Python module called surfinBH.
Abstract Advancements in accelerometer analytic and visualization techniques allow researchers to more precisely identify and compare critical periods of physical activity (PA) decline by age across ...the lifespan, and describe how daily PA patterns may vary across age groups. We used accelerometer data from the 2003–2006 cohorts of the National Health and Nutrition Examination Survey (NHANES) (n = 12,529) to quantify total PA as well as PA by intensity across the lifespan using sex-stratified, age specific percentile curves constructed using generalized additive models. We additionally estimated minute-to-minute diurnal PA using smoothed bivariate surfaces. We found that from childhood to adolescence (ages 6–19) across sex, PA is sharply lower by age partially due to a later initiation of morning PA. Total PA levels, at age 19 are comparable to levels at age 60. Contrary to prior evidence, during young adulthood (ages 20–30) total and light intensity PA increases by age and then stabilizes during midlife (ages 31–59) partially due to an earlier initiation of morning PA. We additionally found that males compared to females have an earlier lowering in PA by age at midlife and lower total PA, higher sedentary behavior, and lower light intensity PA in older adulthood; these trends seem to be driven by lower PA in the afternoon compared to females. Our results suggest a re-evaluation of how emerging adulthood may affect PA levels and the importance of considering time of day and sex differences when developing PA interventions.
Alzheimer's disease (AD) is a neurodegenerative disease that results in severe disability. Very few studies have explored changes in daily physical activity patterns during early stages of AD when ...components of physical function and mobility may be preserved.
Our study explored differences in daily physical activity profiles, independent of the effects of non-cognitive factors including physical function and age, among individuals with mild AD compared to controls.
Patients with mild AD and controls (n = 92) recruited from the University of Kansas Alzheimer's Disease Center Registry, wore the Actigraph GT3X+ for seven days, and provided objective physical function (VO2 max) and mobility data. Using multivariate linear regression, we explored whether individuals with mild AD had different daily average and diurnal physical activity patterns compared to controls independent of non-cognitive factors that may affect physical activity, including physical function and mobility.
We found that mild AD was associated with less moderate-intensity physical activity (p < 0.05), lower peak activity (p < 0.01), and lower physical activity complexity (p < 0.05) particularly during the morning. Mild AD was not associated with greater sedentary activity or less lower-intensity physical activity across the day after adjusting for non-cognitive covariates.
These findings suggest that factors independent of physical capacity and mobility may drive declines in moderate-intensity physical activity, and not lower-intensity or sedentary activity, during the early stage of AD. This underscores the importance of a better mechanistic understanding of how cognitive decline and AD pathology impact physical activity. Findings emphasize the potential value of designing and testing time-of-day specific physical activity interventions targeting individuals in the early stages of AD, prior to significant declines in mobility and physical function.
We present an analytical waveform family describing gravitational waves (GWs) from the inspiral, merger, and ringdown of nonspinning black-hole binaries including the effect of several nonquadrupole ...modes (ℓ=2,m=±1),(ℓ=3,m=±3),(ℓ=4,m=±4) apart from (ℓ=2,m=±2). We first construct spin-weighted spherical harmonics modes of hybrid waveforms by matching numerical-relativity simulations (with mass ratio 1–10) describing the late inspiral, merger, and ringdown of the binary with post-Newtonian/effective-one-body waveforms describing the early inspiral. An analytical waveform family is constructed in frequency domain by modeling the Fourier transform of the hybrid waveforms making use of analytical functions inspired by perturbative calculations. The resulting highly accurate, ready-to-use waveforms are highly faithful (unfaithfulness ≃10−4–10−2) for observation of GWs from nonspinning black-hole binaries and are extremely inexpensive to generate.
The goal of the study was to examine barriers and facilitators to clinical research participation among African Americans, as well as recommendations for overcoming these.
Eight focus groups were ...conducted consisting of 64 individuals. These focus groups targeted 2 groups of individuals: (a) community members, including both individuals involved in research and individuals not involved in research, and (b) community leaders, including clergy, community health care providers and service providers who may influence decisions to participate in research.
Among participants in both groups, the most common barriers to participation included fear and mistrust of research due to multiple factors, such as a lack of information about research and prevailing knowledge of historical occurrences. Facilitators to research participation included intrinsic factors, such as a desire to help others, and extrinsic factors, such as familiarity with the research recruiter. The focus groups also directly engaged participants in discussions of strategies that might improve recruitment, such as the importance of providing personal stories that enable community members to understand the potential benefits of research.
Findings from these focus groups address the mandate from funding agencies that emphasize the importance of including racially diverse populations in clinical research studies, and offer potential solutions for increasing the recruitment and retention of minority participants.
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