Research Spotlights: May 2021

Long-term exposure to traffic-related noise or air pollution further increases risk for cognitive decline in people with metabolic dysfunction

Cognitive impairment has been separately linked to traffic-related air pollution and noise exposure as well as to metabolic syndromes, but the interaction of these two vulnerabilities is not well understood. In a study funded by the NIEHS, NIA, and NIDDK, researchers used 10-year longitudinal data from Mexican American participants to examine whether the presence of metabolic dysfunction modifies associations between air pollution or noise exposures and cognitive impairment, with or without dementia.

Researchers analyzed data from 1,612 older (>60 years of age) Mexican American participants recruited through the Sacramento Area Latino Study on Aging over the span of 10 years. The Mexican American population was studied as this population has a higher prevalence of obesity and diabetes and are among the most highly exposed to traffic-related air pollution and noise. Levels of air pollution were assessed using the Federal Highway Administration Traffic Noise Model through nitrogen oxide levels, and noise exposure were estimated based on participants’ geocoded residential addresses at baseline. Participants were assessed for metabolic dysfunction including obesity, hyperglycemia, and low high-density lipoprotein (HDL) cholesterol. Cognitive function was evaluated using multiple cognitive screening tests at baseline and during each annual follow-up visit.

Findings showed that participants who had hyperglycemia and were also exposed to high levels of air pollution and noise had a 2.4 or 2.2 times higher risk, respectively, of developing cognitive impairment compared to those without metabolic dysfunction and exposed to low levels of traffic-related air pollution or noise. Participants who had low HDL-cholesterol and were exposed to high levels of air pollution and noise had a similarly elevated risk of developing cognitive impairment compared to those without metabolic dysfunction and low levels of exposure—2.5 and 1.8 times higher, respectively.

This study shows that exposure to traffic-related air pollution or noise most strongly increases the risk of cognitive impairment among older Mexican Americans who also exhibit hyperglycemia or low HDL-cholesterol. Chronic conditions such as hyperglycemia and low HDL-cholesterol have been long studied for their impact on other health conditions, but this study emphasizes that environmental risk factors such as pollution and noise can exacerbate the impact of these chronic diseases on other health conditions.

Yu, Yu et al. 2021. Metabolic dysfunction modifies the influence of traffic-related air pollution and noise exposure on late-life dementia and cognitive impairment: A cohort study of older Mexican-Americans, Environ Epidemiol. 4(6):e122. doi: 10.1097/EE9.0000000000000122.

In-person school visits have a marginal impact on COVID-19 transmission

An important concern during the COVID-19 pandemic has been whether reopening schools for in-person visits would increase the risk of COVID-19 infections, leading to a resurgence. Recently published research funded by the NIA and the Conrad N. Hilton Foundation sought to answer this question because children across the nation have been impacted by COVID-19 through altered access to education, food, social services, and their peers.

To address this question, the researchers leveraged two large sources of national data: mobile phone tracking data and medical insurance claims data from the first 46 weeks of 2020. This resulted in 130 million household observations that included COVID-19 diagnoses merged with in-person school visit data from mobile phone geolocation tracking. The mobile phone data was provided by SafeGraph, which collects global positioning system data from approximately 45 million U.S. mobile phones. The researchers used a unique feature of SafeGraph data that links cell phone visits to specific locations such as schools.

The researchers linked the school visit data to medical claims data collected from approximately 7 million individuals (3 million households). As of Dec 9, 2020, they found that almost 93,000 participants had a COVID-19 diagnoses, including close to 10,255 children and 82,180 adults. Further analyses revealed that increases of in-person visits to schools were correlated with an increase in COVID-19 diagnoses among households with children relative to households without school-age children. However, it is important to note that these effects are small in magnitude. Based on the number of school visits, participants in the 75th percentile of in-person school visits compared to the 25th percentile of in-person school visits had a 3.2 percent relative increase in COVID-19 diagnoses. Additionally, the researchers found larger differences in low-income counties, in counties with higher COVID-19 prevalence, and at later stages of the COVID-19 pandemic.

Importantly, these analyses were done prior to access to vaccines, which modify the transmission rate but support that policies for re-opening have an impact and that changes in behavior continue to be important in slowing the spread of the COVID-19 virus.

Bravata D, Cantor JH, Sood N, Whaley CM. 2021. Back to School: The Effect of School Visits During COVID-19 on COVID-19 Transmission. NBER Working Paper; DOI 10.3386/w28645;

Brain proteome-wide association study implicates novel proteins in depression pathogenesis

Depression is a common disease with limited effective treatments for the greater population with therapeutics being effective in only small groups of individuals. In a study funded by the NIA, NINDS, NIMH, Veterans Affairs, and others, researchers hypothesized that specific genetic variants influence depression by altering brain protein expression levels.

The researchers used a study design which combined genome-wide association studies (GWAS) and human brain proteomic data to determine if variations in genes altered brain protein levels and could explain some of the inherited risk for depression. Human brain proteomics and genetic data was collected and examined from 376 participants. To identify new treatment targets for depression, a proteome-wide association study (PWAS) from the 376 individuals in this study was combined with another GWAS study (n = 500,199 participants, 75,607 which self-reported depression) to find whether a protein is differentially expressed as a result of a normal gene versus a genetic variant.

First, the depression PWAS was analyzed to identify potential genetic correlations with depression. To increase confidence, a replication analysis was completed using another human brain proteomic dataset (N=152) and another depression GWAS that used independent data from 23andMe (n = 307,353). Combined with the meta-analysis data, these results showed that 19 genes likely contribute to depression pathogenesis. Based on integration of the depression GWAS with downstream measurements of human brain transcriptomes (n = 888), 11 of the 19 genes also had changes in downstream mRNA levels, indicating a change in protein levels. The replication analysis identified 38 proteins associated with depression and of those, 25 proteins were found to be consistent with being casual.

In conclusion, the researchers identified 19 potentially causal genes that act via modulating their brain protein abundances. Additionally, through a meta-analysis and replication PWAS analyses, they identified 25 brain proteins that were consistent with a causality for depression pathogenesis. In summary, these findings provide promising brain protein targets for further mechanistic and therapeutic studies.

Wingo, T.S., Liu, Y., Gerasimov, E.S. et al. 2021.Brain proteome-wide association study implicates novel proteins in depression pathogenesis. Nat Neurosci.