Gene Expression Changes in Healthy Volunteers after Exposure to Traffic Related Air Pollution and Physical Activity

摘要

Background:Gene-expression enlarges the scope of conventional health effect research to the identification of potential early health biomarkers and biological mechanisms underlying pathologic responses to air pollution exposure. Aims:This study was to determine gene-expression changes in a healthy population following traffic air pollution exposures, and potential effect modification by moderate physical activity. Methods: Well controlled crossover study comparing whole blood gene-expressions pre- and 40 minutes post exposure in healthy non-smoking subjects. Exposure was for 2 hours to contrasting pollution levels while either cycling or resting. Each volunteer was to undergo four conditions (high vs. low exposure; cycling vs. resting). Microarray expression profiles were obtained using the GeneChip PrimeView Human Gene-Expression Array (Affymetrix,CA) and the GCS3000 Affymetrix platform.Microarray data were normalized using rma method. Statistical analyses were performed using limma package; enrichment analysis using Gene Ontoloty (GO). Results: Ultrafine particles, elemental carbon, and nitric oxides levels at the high exposure site were on average 5, 7, and 10 times higher than the low exposure site, respectively. Twenty-eight volunteers completed all 4 exposure combinations (53,6% females; mean age 34,4 years). At 10% FDR cycling in low air pollution led to a deregulation of 224 genes, while cycling in high air pollution to 55 genes. No gene deregulation was found as a consequence of air pollution in either scenario (resting or cycling). Enrichment analysis for exercise in low pollution levels revealed several over-represented GO categories including lymphocyte activation, muscular activity response or muscle tissue development. Conclusions: Preliminary analysis suggests that gene-expression deregulations can be attributed to the exercise rather than to the air pollution. Ongoing statistical analysis is expected to verify findings and to inform about specific pathways.