Sex-Specific Associations between Particulate Matter Exposure and Gene Expression in Independent Discovery and Validation Cohorts of Middle-Aged Men and Women

中年男性和女性独立发现队列和验证队列中颗粒物暴露与基因表达的性别特异性关联

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Abstract

BACKGROUND: Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. OBJECTIVES: Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. METHODS: Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM(10) in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM(2.5) and PM(10) exposures over 2-years were estimated for each participant's residential address using spatiotemporal interpolation in combination with a dispersion model. RESULTS: Average long-term PM(10) was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m(3) in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM(10) and the expression of individual genes differed by sex. In the validation cohort, long-term PM(10) was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 (p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM(10) in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM(10) exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). CONCLUSIONS: Expression of the sex-specific candidate genes identified in the discovery population predicted PM(10) exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects.

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