A metabolome-wide case-control study of african american breast cancer patients.

BACKGROUND: Breast cancer survivors face long-term sequelae compared to the general population, suggesting altered metabolic profiles after breast cancer. We used metabolomics approaches to investigate the metabolic differences between breast cancer patients and women in the general population, aiming to elaborate metabolic changes among breast cancer patients and identify potential targets for clinical interventions to mitigate long-term sequelae. METHODS: Serum samples were retrieved from 125 breast cancer cases recruited from the Chicago Multiethnic Epidemiologic Breast Cancer Cohort (ChiMEC), and 125 healthy controls selected from Chicago Multiethnic Prevention and Surveillance Study (COMPASS). We used liquid chromatography-high resolution mass spectrometry to obtain untargeted metabolic profiles and partial least squares discriminant analysis (PLS-DA) combined with fold change to select metabolic features associated with breast cancer. Pathway analyses were conducted using Mummichog to identify differentially enriched metabolic pathways among cancer patients. As potential confounders we included age, marital status, tobacco smoking, alcohol drinking, type 2 diabetes, and area deprivation index in our model. Random effects of residence for intercept was also included in the model. We further conducted subgroup analysis by treatment timing (chemotherapy/radiotherapy/surgery), lymph node status, and cancer stages. RESULTS: The entire study participants were African American. The average ages were 57.1 for cases and 58.0 for controls. We extracted 15,829 features in total, among which 507 features were eventually selected by our criteria. Pathway enrichment analysis of these 507 features identified three differentially enriched metabolic pathways related to prostaglandin, leukotriene, and glycerophospholipid. The three pathways demonstrated inconsistent patterns. Metabolic features in the prostaglandin and leukotriene pathways exhibited increased abundances among cancer patients. In contrast, metabolic intensity in the glycerolphospholipid pathway was deregulated among cancer patients. Subgroup analysis yielded consistent results. However, changes in these pathways were strengthened when only using cases with positive lymph nodes, and attenuated when only using cases with stage I disease. CONCLUSION: Breast cancer in African American women is associated with increase in serum metabolites involved in prostaglandin and leukotriene pathways, but with decrease in serum metabolites in glycerolphospholipid pathway. Positive lymph nodes and advanced cancer stage may strengthen changes in these pathways.

Household air pollution disparities between socioeconomic groups in Chicago.

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 (PM2.5) concentration. We calculated hourly average PM2.5 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 PM2.5 concentration was 43.8 µg m-3. We observed a significant difference in the average household PM2.5 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.