Long-Term Ambient Air Pollution Exposures and Brain Imaging Markers in Korean Adults: The Environmental Pollution-Induced Neurological EFfects (EPINEF) Study.

BACKGROUND: Only a limited number of neuroimaging studies have explored the effects of ambient air pollution in adults. The prior studies have investigated only cortical volume, and they have reported mixed findings, particularly for gray matter. Furthermore, the association between nitrogen dioxide (NO2) and neuroimaging markers has been little studied in adults. OBJECTIVES: We investigated the association between long-term exposure to air pollutants (NO2, particulate matter (PM) with aerodynamic diameters of ≤10µm (PM10) and ≤2.5µm (PM2.5), and neuroimaging markers. METHODS: The study included 427 men and 530 women dwelling in four cities in the Republic of Korea. Long-term concentrations of PM10, NO2, and PM2.5 at residential addresses were estimated. Neuroimaging markers (cortical thickness and subcortical volume) were obtained from brain magnetic resonance images. A generalized linear model was used, adjusting for potential confounders. RESULTS: A 10-µg/m3 increase in PM10 was associated with reduced thicknesses in the frontal [-0.02mm (95% CI: -0.03, -0.01)] and temporal lobes [-0.06mm (95% CI: -0.07, -0.04)]. A 10-µg/m3 increase in PM2.5 was associated with a thinner temporal cortex [-0.18mm (95% CI: -0.27, -0.08)]. A 10-ppb increase in NO2 was associated with reduced thicknesses in the global [-0.01mm (95% CI: -0.01, 0.00)], frontal [-0.02mm (95% CI: -0.03, -0.01)], parietal [-0.02mm (95% CI: -0.03, -0.01)], temporal [-0.04mm (95% CI: -0.05, -0.03)], and insular lobes [-0.01mm (95% CI: -0.02, 0.00)]. The air pollutants were also associated with increased thicknesses in the occipital and cingulate lobes. Subcortical structures associated with the air pollutants included the thalamus, caudate, pallidum, hippocampus, amygdala, and nucleus accumbens. DISCUSSION: The findings suggest that long-term exposure to high ambient air pollution may lead to cortical thinning and reduced subcortical volume in adults. https://doi.org/10.1289/EHP7133.

A Validation Study of the Inbrain CST: a Tablet Computer-based Cognitive Screening Test for Elderly People with Cognitive Impairment.

BACKGROUND: Computerized versions of cognitive screening test could have advantages over pencil-and-paper versions by eliminating rater-dependent factors and saving the time required to score the tests and report the results. We developed a computerized cognitive screening test (Inbrain Cognitive Screening Test [Inbrain CST]) that takes about 30 minutes to administer on a touchscreen computer and is composed of neuropsychological tests already shown to be sensitive in detecting early cognitive decline in Alzheimer's disease (AD). The aims of this study were to 1) introduce normative data for Inbrain CST, 2) verify its reliability and validity, 3) assess clinical usefulness, and 4) identify neuroanatomical correlates of Inbrain CST. METHODS: The Inbrain CST runs on the Microsoft Windows 10 operating system and comprises 7 subtests that encompass 5 cognitive domains: attention, language, visuospatial, memory, and executive functions. First, we recruited 480 cognitively normal elderly people (age 50-90) from communities nationwide to establish normative data for Inbrain CST. Second, we enrolled 97 patients from our dementia clinic (26 with subjective cognitive decline [SCD], 42 with amnestic mild cognitive impairment [aMCI], and 29 with dementia due to AD) and investigated sensitivity and specificity of Inbrain CST for discriminating cognitively impaired patients from those with SCD using receiver operating characteristic (ROC) curve analyses. Third, we compared the Inbrain CST scores with those from another neuropsychological test battery to obtain concurrent validity and assessed test-retest reliability. Finally, magnetic resonance imaging (MRI)-based cortical thickness analyses were performed to provide anatomical substrates for performances on the Inbrain CST. RESULTS: First, in the normative sample, the total score on the Inbrain CST was significantly affected by age, years of education, and gender. Second, Inbrain CST scores among the three patient groups decreased in the order of SCD, aMCI, and AD dementia, and the ROC curve analysis revealed that Inbrain CST had good discriminative power for differentiating cognitively impaired patients from those with SCD. Third, the Inbrain CST subtests had high concurrent validity and test-retest reliability. Finally, in the cortical thickness analysis, each cognitive domain score and the total score of Inbrain CST showed distinct patterns of anatomical correlates that fit into the previously known brain-behavior relationship. CONCLUSION: Inbrain CST had good validity, reliability, and clinical usefulness in detecting cognitive impairment in the elderly. Furthermore, it showed neuroanatomical validity through MRI cortical thinning patterns. These results suggest that Inbrain CST is a useful cognitive screening tool with efficiency and validity to detect mild impairments in cognition in clinical settings.

Association between exposure to polycyclic aromatic hydrocarbons and brain cortical thinning: The Environmental Pollution-Induced Neurological EFfects (EPINEF) study.

BACKGROUND: Although some studies have suggested that exposure to polycyclic aromatic hydrocarbons (PAHs) induces neurodevelopmental disturbances in children and neurodegeneration in animals, the neurotoxic effect of PAH exposure is unclear in adults. The aim was to examine the associations of PAH exposure with brain structure and neuropsychological function in adults without known neurological diseases. METHODS: This study included 421 men and 528 women dwelling in four cities in the Republic of Korea. Urinary concentrations of four PAH metabolites (1-hydroxypyrene, 2-naphthol, 1-hydroxyphenanthrene, and 2-hydroxyfluorene) were obtained. Participants underwent brain 3 T magnetic resonance imaging and neuropsychological tests. Cortical thickness and volume were estimated using the region-of-interest method. Separate generalized linear models were constructed for each sex, adjusting for age, years of education, cohabitation status, income, tobacco use, alcohol consumption, and vascular risk factors. RESULTS: The mean (standard deviation) age was 68.3 (6.6) years in men and 66.4 (6.1) years in women. In men, those in quartile 4 (versus quartile 1, the lowest) of urinary 2-naphthol concentration had cortical thinning in the global (ß = -0.03, P = .02), parietal (ß = -0.04, P = .01), temporal (ß = -0.06, P < .001), and insular lobes (ß = -0.05, P = .02). Higher quartiles of urinary 2-naphthol concentration were associated with cortical thinning in the global (P = .01), parietal (P = .004), temporal (P < .001), and insular lobes (P = .01). In women, those in quartile 4 (versus quartile 1) of urinary 1-hydroxypyrene concentration had cortical thinning in the frontal (ß = -0.03, P = .006) and parietal lobes (ß = -0.03, P = .003). Higher quartiles of urinary 1-hydroxypyrene concentration were associated with cortical thinning in the frontal (P = .006) and parietal lobes (P = .001). In both sexes, verbal learning and memory scores significantly declined with an increase in quartile of urinary 1-hydroxypyrene concentration. CONCLUSIONS: PAH exposure was associated with cortical thinning and decline in verbal learning and memory function in cognitively healthy adults. This suggests PAHs as an environmental risk factor for neurodegeneration.

Machine Learning-based Individual Assessment of Cortical Atrophy Pattern in Alzheimer's Disease Spectrum: Development of the Classifier and Longitudinal Evaluation.

To develop a new method for measuring Alzheimer's disease (AD)-specific similarity of cortical atrophy patterns at the individual-level, we employed an individual-level machine learning algorithm. A total of 869 cognitively normal (CN) individuals and 473 patients with probable AD dementia who underwent high-resolution 3T brain MRI were included. We propose a machine learning-based method for measuring the similarity of an individual subject's cortical atrophy pattern with that of a representative AD patient cohort. In addition, we validated this similarity measure in two longitudinal cohorts consisting of 79 patients with amnestic-mild cognitive impairment (aMCI) and 27 patients with probable AD dementia. Surface-based morphometry classifier for discriminating AD from CN showed sensitivity and specificity values of 87.1% and 93.3%, respectively. In the longitudinal validation study, aMCI-converts had higher atrophy similarity at both baseline (p < 0.001) and first year visits (p < 0.001) relative to non-converters. Similarly, AD patients with faster decline had higher atrophy similarity than slower decliners at baseline (p = 0.042), first year (p = 0.028), and third year visits (p = 0.027). The AD-specific atrophy similarity measure is a novel approach for the prediction of dementia risk and for the evaluation of AD trajectories on an individual subject level.