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Abstract
Objective To examine whether late-life exposure to PM2.5 (particulate matter with aerodynamic diameters <2.5 µm) contributes to progressive brain atrophy predictive of Alzheimer disease (AD) using a community-dwelling cohort of women (age 70–89 years) with up to 2 brain MRI scans (MRI-1, 2005–2006; MRI-2, 2010–2011).
Methods AD pattern similarity (AD-PS) scores, developed by supervised machine learning and validated with MRI data from the Alzheimer’s Disease Neuroimaging Initiative, were used to capture high-dimensional gray matter atrophy in brain areas vulnerable to AD (e.g., amygdala, hippocampus, parahippocampal gyrus, thalamus, inferior temporal lobe areas, and midbrain). Using participants' addresses and air monitoring data, we implemented a spatiotemporal model to estimate 3-year average exposure to PM2.5 preceding MRI-1. General linear models were used to examine the association between PM2.5 and AD-PS scores (baseline and 5-year standardized change), accounting for potential confounders and white matter lesion volumes.
Results For 1,365 women 77.9 ± 3.7 years of age in 2005 to 2006, there was no association between PM2.5 and baseline AD-PS score in cross-sectional analyses (β = −0.004; 95% confidence interval [CI] −0.019 to 0.011). Longitudinally, each interquartile range increase of PM2.5 (2.82 µg/m3) was associated with increased AD-PS scores during the follow-up, equivalent to a 24% (hazard ratio 1.24, 95% CI 1.14–1.34) increase in AD risk over 5 years (n = 712, age 77.4 ± 3.5 years). This association remained after adjustment for sociodemographics, intracranial volume, lifestyle, clinical characteristics, and white matter lesions and was present with levels below US regulatory standards (<12 µg/m3).
Conclusions Late-life exposure to PM2.5 is associated with increased neuroanatomic risk of AD, which may not be explained by available indicators of cerebrovascular damage.
Glossary
- AD=
- Alzheimer disease;
- ADNI=
- Alzheimer's Disease Neuroimaging Initiative;
- AD-PS=
- AD pattern similarity;
- BME=
- Bayesian Maximum Entropy;
- BMI=
- body mass index;
- CI=
- confidence interval;
- CTM=
- chemical transport model;
- EN-RLR=
- elastic net regularized logistic regression;
- EPA=
- Environmental Protection Agency;
- GLM=
- general linear model;
- ICV=
- intracranial volume;
- IQR=
- interquartile range;
- PM2.5=
- particulate matter with aerodynamic diameters <2.5 µm;
- WHIMS=
- Women's Health Initiative Memory Study
Footnotes
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
Co-investigators are listed at http://links.lww.com/WNL/B287
- Received August 20, 2019.
- Accepted in final form October 20, 2020.
- © 2020 American Academy of Neurology
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