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Science Selection June 2018 | Volume 126 | Issue 6

Environ Health Perspect; DOI:10.1289/EHP3445

Particulate Matter and Cognition: Using Brain Imaging to Study Impacts of Air Pollution

Silke Schmidt

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  • Published: 8 June 2018

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Related EHP Article

The Association of Long-Term Exposure to Particulate Matter Air Pollution with Brain MRI Findings: The ARIC Study

Melinda C. Power, Archana P. Lamichhane, Duanping Liao, Xiaohui Xu, Clifford R. Jack, Rebecca F. Gottesman, Thomas Mosley, James D. Stewart, Jeff D. Yanosky, and Eric A. Whitsel

Air pollution is well known to adversely affect lung1,2 and heart3,4 health. Both animal5 and epidemiologic6,7 studies suggest air pollution may also harm cognition. A study in Environmental Health Perspectives sheds some light on the potential mechanism by which air pollution may affect brain health.8

The authors of the study analyzed magnetic resonance imaging (MRI) data for more than 1,700 participants in the Atherosclerosis Risk in Communities (ARIC) study. Since 1987, ARIC has followed almost 16,000 people in Maryland, Minnesota, North Carolina, and Mississippi over time. In 2011, detailed neurological measures were added to exams conducted as part of the study, including MRIs on a subset of participants.9 The present analysis focused on two types of markers of brain damage: brain volume (a nonspecific indicator of multiple kinds of injury), and measures of cerebrovascular health.

Aerial photograph of a busy road lined by apartment buildings
Coauthor Melinda C. Power says it will be important to analyze a wide range of air pollutants with respect to brain health: “Since air pollution is such a ubiquitous exposure, even small effects have big public health implications.” Image: © Hrecheniuk Oleksii/Shutterstock.

The investigators estimated long-term average exposure to air pollution 5–20 years prior to MRI, based on residential histories from 1990 through 2007. They focused on two categories of particulate matter (PM2.5 and PM10), mixtures of solid particles and liquid droplets emitted by vehicles and industrial facilities or formed by chemical reactions in the atmosphere. PM2.5 is assumed to be a greater risk because it can penetrate deep into biological tissue.

According to first author Melinda C. Power, an assistant professor in the Milken Institute School of Public Health, George Washington University, the two leading mechanistic hypotheses for the effect of air pollution on brain health involve either vascular or inflammatory pathways. In this study, none of the markers of cerebrovascular health were associated with PM2.5 in the overall or site-specific study populations.

“We think this result provides another piece of evidence that vascular pathways probably aren’t the primary mechanism, if air pollution really does impact brain health,” Power says. “Even though an association between PM2.5 and stroke is well established, at least for moderate or high short-term exposure, studies looking at the association between air pollution [and] cognition also generally don’t support the idea that vascular pathways are a primary mechanism.”

The brain volume findings, on the other hand, were less consistent. The authors reported weak evidence for an association between higher PM2.5 and volume of deep gray matter (i.e., structures that include the basal ganglia, thalamus, and hypothalamus) when data were pooled across the four sites. Site-specific estimates showed evidence of lower volume with higher PM2.5 in Maryland, Minnesota, and North Carolina; Minnesota was the only site where PM2.5 was associated with significantly lower volume for the total brain as well as specific regions of the brain. For Mississippi, PM2.5 was associated with larger brain volumes, especially in the temporal lobe, but most associations were very weak, and few were significant.

“The effect of air pollution may vary in different parts of the country,” Power says, noting that some of the PM2.5 distributions at the four sites did not even overlap, and that particle composition may vary as well. Site-specific sample sizes were too small to identify weak or nonlinear effects.

Lianne Sheppard, a professor of biostatistics and of environmental and occupational health sciences at the University of Washington, noted the inherent limitation of using a single MRI measurement as the primary outcome. “Since brain volume is really heterogeneous, it is hard to pick up a signal with the cross-sectional design that was used here,” says Sheppard, who was not involved with the study. “A longitudinal design with at least two MRI measurements per person would be much more powerful, especially since effects of air pollution, although real and important, are generally pretty subtle.”

For Jordi Sunyer, however, the MRI data were a strength, given limitations in the exposure assessment from residential histories alone. “I believe part of the reason for the observed weak associations with brain [volume] is that the PM2.5 model did not have enough resolution to accurately estimate long-term exposure, which resulted in limited variability,” says Sunyer, a professor of preventive medicine and public health at Pompeu Fabra University in Barcelona, Spain, who also was not affiliated with the study. “But this is still a very important paper that provides a new piece of the puzzle connecting air pollution to brain health.”

Going forward, analyzing a wide range of air pollution levels will be important, Power says, whether in geographically diverse data sets such as ARIC or with studies focused on smaller areas. “Since air pollution is such a ubiquitous exposure, even small effects have big public health implications,” she says. “Our study has generated some new hypotheses, but more work is definitely needed to connect the dots.”


Silke Schmidt, PhD, writes about science, engineering, and the environment from Madison, Wisconsin.

References

1. Li J, Sun S, Tang R, Qiu H, Huang Q, Mason TG, et al. 2016. Major air pollutants and risk of COPD exacerbations: a systematic review and meta-analysis. Int J Chron Obstruct Pulmon Dis 11:3079–3091, PMID: 28003742, 10.2147/COPD.S122282.

2. Khreis H, Kelly C, Tate J, Parslow R, Lucas K, Nieuwenhuijsen M, et al. 2017. Exposure to traffic-related pollution and risk of development of childhood asthma: a systematic review and meta-analysis. Environ Int 100:1–31, PMID: 27881237, 10.1016/j.envint.2016.11.012.

3. Zhao R, Chen S, Wang W, Huang J, Wang K, Liu L, et al. 2017. The impact of short-term exposure to air pollutants on the onset of out-of-hospital cardiac arrest: a systematic review and meta-analysis. Int J Cardiol 226(1):110–117, PMID: 27806308, 10.1016/j.ijcard.2016.10.053.

4. Shao Q, Liu T, Korantzopoulos P, Zhang Z, Zhao J, Li G. 2016. Association between air pollution and development of atrial fibrillation: a meta-analysis of observational studies. Heart Lung 45(6):557–562, PMID: 27590407, 10.1016/j.hrtlng.2016.08.001.

5. Costa LG, Cole TB, Coburn J, Chang Y-C, Dao K, Roqué PJ. 2017. Neurotoxicity of traffic-related air pollution. Neurotoxicology 59:133–139, PMID: 26610921, 10.1016/j.neuro.2015.11.008.

6. Weuve J, Puett RC, Schwartz J, Yanosky JD, Laden F, Grodstein F. 2012. Exposure to particulate air pollution and cognitive decline in older women. Arch Intern Med 172(3):219–227, PMID: 22332151, 10.1001/archinternmed.2011.683.

7. Power MC, Adar SD, Yanosky JD, Weuve J. 2016. Exposure to air pollution as a potential contributor to cognitive function, cognitive decline, brain imaging, and dementia: a systematic review of epidemiologic research. Neurotoxicology 56:235–253, PMID: 27328897, 10.1016/j.neuro.2016.06.004.

8. Power MC, Lamichhane AP, Liao D, Xu X, Jack CR, Gottesman RF, et al. 2018. The association of long-term exposure to particulate matter air pollution with brain MRI findings: the ARIC study. Environ Health Perspect 126(2):027009, PMID: 29467108, 10.1289/EHP2152.

9. Knopman DS, Griswold ME, Lirette ST, Gottesman RF, Kantarci K, Sharrett AR, et al. 2015. Vascular imaging abnormalities and cognition: mediation by cortical volume in nondemented individuals: atherosclerosis risk in communities-neurocognitive study. Stroke 46(2):433–440, PMID: 25563642, 10.1161/STROKEAHA.114.007847.


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