Gene expression profile in circulating mononuclear cells after exposure to ultrafine carbon particles

Abstract

Context: Exposure to particulate matter (PM) is associated with systemic health effects, but the cellular and molecular mechanisms are unclear. Objective: We hypothesized that, if circulating mononuclear cells play an important role in mediating systemic effects of PM, they would show gene expression changes following exposure. Materials and methods: Peripheral blood samples were collected before (0 h) and at 24 h from healthy subjects exposed to filtered air (FA) and ultrafine carbon particles (UFPs, 50 μg/m³) for 2 h in a previous study (n = 3 each). RNA from mononuclear cell fraction (>85% lymphocytes) was extracted, amplified and hybridized to Affymetrix HU133 plus 2 microarrays. Selected genes were confirmed in five additional subjects from the same study. Results: We identified 1713 genes (UFP 24 h vs. FA 0 and 24 h, P < 0.05, false discovery rate of 0.01). The top 10 upregulated genes (fold) were CDKN1C (1.86), ZNF12 (1.83), SRGAP2 (1.82), FYB (1.79), LSM14B (1.79), CD93 (1.76), NCSTN (1.70), DUSP6 (1.69), TACC1 (1.68), and H2AFY (1.68). Upregulation of CDKN1C and SRGAP2 was confirmed by real-time-PCR. We entered 1020 genes with a ratio >1.1 or <−1.1 into the Ingenuity Pathway Analysis and identified pathways related to inflammation, tissue growth and host defense against environmental insults, such as, insulin growth factor 1 signaling, insulin receptor signaling and NF-E2-related factor-2-mediated oxidative stress response pathway. Discussion and conclusions: Two-hour exposures to UFP produced gene expression changes in circulating mononuclear cells. These gene changes provide biologically plausible links to PM-induced systemic health effects, especially those in the cardiovascular system and glucose metabolism.

Keywords::

• Gene expression
• glucose metabolism
• microarray
• oxidative stress
• particulate matter
• ultrafine particles

Acknowledgements

We thank Dr. Zhengzheng Wei of the Duke Institute of Genomic Sciences and Policy for analyzing the genomic data.

Declaration of interest

This work was supported by contract 98-19 from the Health Effects Institute (HEI); US Environmental Protection Agency (EPA) assistance agreements R826781-01 and R827354-01; grants RO1 ES011853, RR00044, and ES01247 from the National Institutes of Health; and grant 4913-ERTER-ES-99 from the New York State Energy Research and Development Authority. The genomic research described in this article was supported by the intramural funding of the US EPA. The contents of this article do not necessarily reflect the views of the HEI, nor do they necessarily reflect the policies of the U.S. EPA.