Rationale: Basic research implicates alveolar endothelial cell apoptosis in the pathogenesis of chronic obstructive pulmonary disease (COPD) and emphysema. However, information on endothelial microparticles (EMPs) in mild COPD and emphysema is lacking. Objectives: We hypothesized that levels of CD311 EMPs phenotypic for endothelial cell apoptosis would be elevated in COPD and associated with percent emphysema on computed tomography (CT). Associations with pulmonary microvascular blood flow (PMBF), diffusing capacity, and hyperinflation were also examined. Methods: The Multi-Ethnic Study of Atherosclerosis COPD Study recruited participants with COPD and control subjects age 50-79 years with greater than or equal to 10 pack-years without clinical cardiovascular disease. CD311 EMPs were measured using flow cytometry in 180 participants who also underwent CTs and spirometry. CD62E1 EMPs phenotypic for endothelial cell activation were also measured. COPD was defined by standard criteria. Percent emphysema was defined as regions less than 2950 Hounsfield units on full-lung scans. PMBF was assessed on gadolinium-enhanced magnetic resonance imaging. Hyperinflation was defined as residual volume/total lung capacity. Linear regression was used to adjust for potential confounding factors. Measurements and Main Results: CD311 EMPs were elevated in COPD compared with control subjects (P ¼ 0.03) and were notably increased in mild COPD (P ¼ 0.03). CD311 EMPs were positively related to percent emphysema (P ¼ 0.045) and were inversely associated with PMBF (P ¼ 0.047) and diffusing capacity (P ¼ 0.01). In contrast, CD62E1 EMPs were elevated in severe COPD (P ¼ 0.003) and hyperinflation (P ¼ 0.001). Conclusions: CD311 EMPs, suggestive of endothelial cell apoptosis, were elevated in mild COPD and emphysema. In contrast, CD62E 1 EMPs indicative of endothelial activation were elevated in severe COPD and hyperinflation.Keywords: chronic obstructive pulmonary disease; emphysema; antigens, CD31; endothelium; pulmonary disease Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the United States (1) and is projected to be the third leading cause of death worldwide by 2020 (2). COPD is defined as airflow obstruction that is not fully reversible (3). Many patients with COPD have emphysema, which is characterized by the destruction of alveolar walls with permanent loss of lung architecture and parenchyma (4).Cigarette smoking, the primary cause of COPD (3), is known to cause endothelial dysfunction (5). Cigarette smoke is delivered directly to pulmonary endothelial cells and contains multiple factors including acrolein that cause endothelial apoptosis (6). Increased endothelial cell apoptosis has been observed in the lung tissue of patients with emphysema compared with control subjects (7,8). Additionally, reductions in vascular endothelial growth factor (VEGF) and its receptor have been noted Prior research using animal models has implicated the primary destruction of the pulmonary capillary bed in the patho...

Introduction: We investigated whether monthly assessments of a computerized cognitive composite (C3) could aid in the detection of differences in practice effects (PE) in clinically unimpaired (CU) older adults, and whether diminished PE were associated with Alzheimer's disease (AD) biomarkers and annual cognitive decline.Materials and Methods:N = 114 CU participants (age 77.6 ± 5.0, 61% female, MMSE 29 ± 1.2) from the Harvard Aging Brain Study completed the self-administered C3 monthly, at-home, on an iPad for one year. At baseline, participants underwent in-clinic Preclinical Alzheimer's Cognitive Composite-5 (PACC5) testing, and a subsample (n = 72, age = 77.8 ± 4.9, 59% female, MMSE 29 ± 1.3) had 1-year follow-up in-clinic PACC5 testing available. Participants had undergone PIB-PET imaging (0.99 ± 1.6 years before at-home baseline) and Flortaucipir PET imaging (n = 105, 0.62 ± 1.1 years before at-home baseline). Linear mixed models were used to investigate change over months on the C3 adjusting for age, sex, and years of education, and to extract individual covariate-adjusted slopes over the first 3 months. We investigated the association of 3-month C3 slopes with global amyloid burden and tau deposition in eight predefined regions of interest, and conducted Receiver Operating Characteristic analyses to examine how accurately 3-month C3 slopes could identify individuals that showed >0.10 SD annual decline on the PACC-5.Results: Overall, individuals improved on all C3 measures over 12 months (β = 0.23, 95% CI [0.21–0.25], p < 0.001), but improvement over the first 3 months was greatest (β = 0.68, 95% CI [0.59–0.77], p < 0.001), suggesting stronger PE over initial repeated exposures. However, lower PE over 3 months were associated with more global amyloid burden (r = −0.20, 95% CI [−0.38 – −0.01], p = 0.049) and tau deposition in the entorhinal cortex (r = −0.38, 95% CI [−0.54 – −0.19], p < 0.001) and inferior-temporal lobe (r = −0.23, 95% CI [−0.41 – −0.02], p = 0.03). 3-month C3 slopes exhibited good discriminative ability to identify PACC-5 decliners (AUC 0.91, 95% CI [0.84–0.98]), which was better than baseline C3 (p < 0.001) and baseline PACC-5 scores (p = 0.02).Conclusion: While PE are commonly observed among CU adults, diminished PE over monthly cognitive testing are associated with greater AD biomarker burden and cognitive decline. Our findings imply that unsupervised computerized testing using monthly retest paradigms can provide rapid detection of diminished PE indicative of future cognitive decline in preclinical AD.

Michael J Fox Foundation, National Institutes of Health, and Pacific Alzheimer Research Foundation.

Spatial patterns of radiotracer binding in positron emission tomography (PET) images may convey information related to the disease topology. However, this information is not captured by the standard PET image analysis that quantifies the mean radiotracer uptake within a region of interest (ROI). On the other hand, spatial analyses that use more advanced radiomic features may be difficult to interpret. Here we propose an alternative data-driven, voxel-based approach to spatial pattern analysis in brain PET, which can be easily interpreted. We apply principal component analysis (PCA) to identify voxel covariance patterns, and optimally combine several patterns using the least absolute shrinkage and selection operator (LASSO). The resulting models predict clinical disease metrics from raw voxel values, allowing for inclusion of clinical covariates. The analysis is performed on high-resolution PET images from healthy controls and subjects affected by Parkinson’s disease (PD), acquired with a pre-synaptic and a post-synaptic dopaminergic PET tracer. We demonstrate that PCA identifies robust and tracer-specific binding patterns in sub-cortical brain structures; the patterns evolve as a function of disease progression. Principal component LASSO (PC-LASSO) models of clinical disease metrics achieve higher predictive accuracy compared to the mean tracer binding ratio (BR) alone: the cross-validated test mean squared error of adjusted disease duration (motor impairment score) was 16.3 ± 0.17 years2 (9.7 ± 0.15) with mean BR, versus 14.4 ± 0.18 years2 (8.9 ± 0.16) with PC-LASSO. We interpret the best-performing PC-LASSO models in the spatial sense and discuss them with reference to the PD pathology and somatotopic organization of the striatum. PC-LASSO is thus shown to be a useful method to analyze clinically-relevant tracer binding patterns, and to construct interpretable, imaging-based predictive models of clinical metrics.