Briseis Aschebrook-Kilfoy

Aims: The oral microbiome is at the frontline for environmental exposure and plays an important role in human metabolism. This study explores the relationship between PM _2.5 exposure, the oral microbiome, and metabolic biomarkers including ghrelin, resistin, and insulin. Methods: Data from 473 adult participants (97.7% Black; median age: 53.6) were analyzed. PM _2.5 exposure was retrospectively assigned based on residential addresses, metabolic biomarkers were measured from blood samples, and oral microbiome profiles were obtained from saliva samples. Multivariate linear regression, weighted quantile sum regression, and high‐dimensional mediation analysis were employed to estimate microbiome‐biomarker associations, the association of the oral microbiome mixture, and mediation effects for PM _2.5 exposure. Results: A total of 20 oral microbiome taxa were significantly associated with at least one biomarker, with genus Atopobium linked to all three. Insulin demonstrated the strongest sensitivity to the oral microbiome influence. Genera in phyla Actinomycetota and Bacillota played key roles in the relationship between the oral microbiome and metabolic biomarkers. Mediation analysis revealed that the oral microbiome mediated 16.5% and 11.1% of PM _2.5 's associations with resistin and insulin, respectively. Conclusion: This study suggests potential mechanisms regarding how the oral microbiome influences metabolic biomarkers and mediates the metabolic effects of PM _2.5 exposure.

Radon, a naturally occurring radioactive gas, is ubiquitous in the environment. Little is known about radon’s impact on cardiovascular disease (CVD).

The chemical composition of PM_2.5 differentially influences cardiovascular risk, but evidence integrating clinical and subclinical end points is limited. Here, we evaluated the long-term exposure to seven PM_2.5 components in 255,394 All of Us participants (2017–2022) for incident myocardial infarction (MI) and stroke, and in 648 COMPASS participants (2015–2019) for troponin, TNF-α, and MCP-1. Our findings revealed that organic matter (OM), sulfate (SO₄ ^2–), and sea-salt (SS) showed consistent associations. For instance, per interquartile-range OM: hazard ratios of 1.33 (95% CI, 1.07–1.67) for MI and 1.40 (95% CI, 1.08–1.81) for stroke; odds ratio of 1.40 (95% CI, 1.01–1.94) for troponin elevation and 1.40 (95% CI, 1.03–1.90) for TNF-α elevation; linear coefficient of 0.40 (95% CI, 0.18–0.61) for MCP-1. In mixture analysis, OM, SO₄ ^2–, and SS each contributed ≥ 19% of the overall association for all outcomes. We found that long-term exposure to specific PM_2.5 components, particularly OM, SO₄ ^2–, and SS, is associated with increased cardiovascular risk and subclinical dysfunction, underscoring the need for component-based air quality regulation.

Importance: Lithium is a naturally occurring element in drinking water and is commonly used as a mood-stabilizing medication. Although clinical studies have reported associations between receiving lithium treatment and reduced cancer risk among patients with bipolar disorder, to our knowledge, the association between environmental lithium exposure and cancer risk has never been studied in the general population.Objectives: To evaluate the association between exposure to lithium in drinking groundwater and cancer risk in the general population.Design, Setting, and Participants: This cohort study included participants with electronic health record and residential address information but without cancer history at baseline from the All of Us Research Program between May 31, 2017, and June 30, 2022. Participants were followed up until February 15, 2023. Statistical analysis was performed from September 2023 through October 2024.Exposure: Lithium concentration in groundwater, based on kriging interpolation of publicly available US Geological Survey data on lithium concentration for 4700 wells across the contiguous US between May 12, 1999, and November 6, 2018.Main Outcome and Measures: The main outcome was cancer diagnosis or condition, obtained from electronic health records. Stratified Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% CIs for risk of cancer overall and individual cancer types for increasing quintiles of the estimated lithium exposure in drinking groundwater, adjusting for socioeconomic, behavioral, and neighborhood-level variables. The analysis was further conducted in the western and eastern halves of the US and restricted to long-term residents living at their current address for at least 3 years.Results: A total of 252 178 participants were included (median age, 52 years [IQR, 36-64 years]; 60.1% female). The median follow-up time was 3.6 years (IQR, 3.0-4.3 years), and 7573 incident cancer cases were identified. Higher estimated lithium exposure was consistently associated with reduced cancer risk. Compared with the first (lowest) quintile of lithium exposure, the HR for all cancers was 0.49 (95% CI, 0.31-0.78) for the fourth quintile and 0.29 (95% CI, 0.15-0.55) for the fifth quintile. These associations were found for all cancer types investigated in both females and males, among long-term residents, and in both western and eastern states. For example, for the fifth vs first quintile of lithium exposure for all cancers, the HR was 0.17 (95% CI, 0.07-0.42) in females and 0.13 (95% CI, 0.04-0.38) in males; for long-term residents, the HR was 0.32 (95% CI, 0.15-0.66) in females and 0.24 (95% CI, 0.11-0.52) in males; and the HR was 0.01 (95% CI, 0.00-0.09) in western states and 0.34 (95% CI, 0.21-0.57) in eastern states.Conclusions and Relevance: In this cohort study of 252 178 participants, estimated lithium exposure in drinking groundwater was associated with reduced cancer risk. Given the sparse evidence and unknown mechanisms of this association, follow-up investigation is warranted.

Purpose: To assess household air pollution levels in urban Chicago households and examine how socioeconomic factors influence these levels. Methods: We deployed wireless air monitoring devices to 244 households in a diverse population in Chicago to continuously record household fine particulate matter (PM_2.5) concentration. We calculated hourly average PM_2.5 concentration in a 24-hour cycle. Four factors—race, household income, area deprivation, and exposure to smoking—were considered in this study. Results: A total of 93085 h of exposure data were recorded. The average household PM_2.5 concentration was 43.8 μg m⁻³. We observed a significant difference in the average household PM_2.5 concentrations between Black/African American and non-Black/African American households (46.3 versus 31.6 μg m⁻³), between high-income and low-income households (18.2 versus 52.5 μg m⁻³), and between smoking and non-smoking households (69.7 versus 29.0 μg m⁻³). However, no significant difference was observed between households in less and more deprived areas (43.7 versus 43.0 μg m⁻³). Implications: Household air pollution levels in Chicago households are much higher than the recommended level, challenging the hypothesis that household air quality is adequate for populations in high income nations. Our results indicate that it is the personal characteristics of participants, rather than the macro environments, that lead to observed differences in household air pollution.

Environmental health research has suggested that fine particulate matter (PM_2.5) exposure can lead to high blood pressures, but it is unclear whether the impacts remain the same for systolic and diastolic blood pressures (SBP and DBP). This study aimed to examine whether the effects of PM_2.5 exposure on SBP and DBP differ using data from a predominantly non-Hispanic Black cohort collected between 2013 and 2019 in the US. PM_2.5 exposure was assessed based on a satellite-derived model across exposure durations from 1 to 36 months. The average PM_2.5 exposure level was between 9.5 and 9.8 μg/m³ from 1 through 36 months. Mixed effects models were used to estimate the association of PM_2.5 with SBP, DBP, and related hypertension types, adjusted for potential confounders. A total of 6381 participants were included. PM_2.5 exposure was positively associated with both SBP and DBP. The association magnitudes depended on exposure durations. The association with SBP was null at the 1-month duration (β = 0.05, 95% CI: − 0.23, 0.33), strengthened as duration increased, and plateaued at the 24-month duration (β = 1.14, 95% CI: 0.54, 1.73). The association with DBP started with β = 0.29 (95% CI: 0.11, 0.47) at the 1-month duration, and plateaued at the 12-month duration (β = 1.61, 95% CI: 1.23, 1.99). PM_2.5 was associated with isolated diastolic hypertension (12-month duration: odds ratio = 1.20, 95% CI: 1.07, 1.34) and systolic–diastolic hypertension (12-month duration: odds ratio = 1.18, 95% CI: 1.10, 1.26), but not with isolated systolic hypertension. The findings suggest DBP is more sensitive to PM_2.5 exposure and support differing effects of PM_2.5 exposure on SBP and DBP. As elevation of SBP and DBP differentially predict CVD outcomes, this finding is relevant for prevention and treatment.

Importance: Socioeconomically disadvantaged subpopulations are more vulnerable to fine particulate matter (PM_2.5) exposure. However, as prior studies focused on individual-level socioeconomic characteristics, how contextual deprivation modifies the association of PM_2.5 exposure with cardiovascular health remains unclear.Objective: To assess disparities in PM_2.5 exposure association with cardiovascular disease among subpopulations defined by different socioeconomic characteristics.Design, Setting, and Participants: This cohort study used longitudinal data on participants with electronic health records (EHRs) from the All of Us Research Program between calendar years 2016 and 2022. Statistical analysis was performed from September 25, 2023, through February 23, 2024.Exposure: Satellite-derived 5-year mean PM_2.5 exposure at the 3-digit zip code level according to participants’ residential address.Main Outcome and Measures: Incident myocardial infarction (MI) and stroke were obtained from the EHRs. Stratified Cox proportional hazards regression models were used to estimate the hazard ratio (HR) between PM_2.5 exposure and incident MI or stroke. We evaluated subpopulations defined by 3 socioeconomic characteristics: contextual deprivation (less deprived, more deprived), annual household income (≥$50 000, <$50 000), and race and ethnicity (non-Hispanic Black, non-Hispanic White). We calculated the ratio of HRs (RHR) to quantify disparities between these subpopulations.Results: A total of 210 554 participants were analyzed (40% age >60 years; 59.4% female; 16.7% Hispanic, 19.4% Non-Hispanic Black, 56.1% Non-Hispanic White, 7.9% other [American Indian, Asian, more than 1 race and ethnicity]), among whom 954 MI and 1407 stroke cases were identified. Higher PM_2.5 levels were associated with higher MI and stroke risks. However, disadvantaged groups (more deprived, income <$50 000 per year, Black race) were more vulnerable to high PM_2.5 levels. The disparities were most pronounced between groups defined by contextual deprivation. For instance, increasing PM_2.5 from 6 to 10 μg/m³, the HR for stroke was 1.13 (95% CI, 0.85-1.51) in the less-deprived vs 2.57 (95% CI, 2.06-3.21) in the more-deprived cohort; 1.46 (95% CI, 1.07-2.01) in the $50 000 or more per year vs 2.27 (95% CI, 1.73-2.97) in the under $50 000 per year cohort; and 1.70 (95% CI, 1.35-2.16) in White individuals vs 2.76 (95% CI, 1.89-4.02) in Black individuals. The RHR was highest for contextual deprivation (2.27; 95% CI, 1.59-3.24), compared with income (1.55; 95% CI, 1.05-2.29) and race and ethnicity (1.62; 95% CI, 1.02-2.58).Conclusions and Relevance: In this cohort study, while individual race and ethnicity and income remained crucial in the adverse association of PM_2.5 with cardiovascular risks, contextual deprivation was a more robust socioeconomic characteristic modifying the association of PM_2.5 exposure.