Melissa A Furlong1, Kimberly C Paul2, Qi Yan2, Yu-Hsuan Chuang2, Myles G Cockburn3, Jeff M Bronstein4, Steve Horvath5, Beate Ritz6. 1. Department of Community, Environment, and Policy, University of Arizona Mel and Enid Zuckerman College of Public Health, Tucson, AZ, USA. Electronic address: mfurlong@email.arizona.edu. 2. Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA. 3. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, CA, USA. 4. Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA. 5. Department of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA; Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, USA. 6. Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA; Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA.
Abstract
BACKGROUND: Pyrethroid pesticide use is increasing worldwide, although the full extent of associated health effects is unknown. An epigenome-wide association study (EWAS) with exploratory pathway analysis may help identify potential pyrethroid-related health effects. METHODS: We performed an exploratory EWAS of chronic ambient pyrethroid exposure using control participants' blood in the Parkinson's Environment and Genes Study in the Central Valley of California (N = 237). We estimated associations of living and working near agricultural pyrethroid pesticide applications in the past 5 years (binary) with site-specific differential methylation, and used a false discovery rate (FDR) cut off of 0.05 for significance. We controlled for age, sex, education, cell count, and an ancestral marker for Hispanic ethnicity. We normalized methylation values for Type I/II probe bias using Beta-Mixture Quantile (BMIQ) normalization, filtered out cross-reactive probes, and evaluated for remaining bias with Surrogate Variable Analysis (SVA). We also evaluated the effects of controlling for cell count and normalizing for Type I/II probe bias by comparing changes in effect estimates and p-values for the top hits across BMIQ and GenomeStudio normalization methods, and controlling for cell count. To facilitate broader interpretation, we annotated genes to the CpG sites and performed gene set overrepresentation analysis, using genes annotated to CpG sites that were associated with pyrethroids at a raw p < 0.05, and controlling for background representation of CpG sites on the chip. We did this for both a biological process context (Gene Ontology terms) using missMethyl, and a disease set context using WebGestalt. For these gene set overrepresentation analyses we also used an FDR cut off of 0.05 for significance of gene sets. RESULTS: After controlling for cell count and applying BMIQ normalization, 4 CpG sites were differentially methylated in relation to pyrethroid exposures. When using GenomeStudio's Illumina normalization, 415 CpG sites were differentially methylated, including all four identified with the BMIQ method. In the gene set overrepresentation analyses, we identified 6 GO terms using BMIQ normalization, and 76 using Illumina normalization, including the 6 identified by BMIQ. For disease sets, we identified signals for Alzheimer's disease, leukemia and several other cancers, diabetes, birth defects, and other diseases, for both normalization methods. We identified minimal changes in effect estimates after controlling for cell count, and controlling for cell count generally weakened p-values. BMIQ normalization, however, resulted in different beta coefficients and weakened p-values. CONCLUSIONS: Chronic ambient pyrethroid exposure is associated with differential methylation at CpG sites that annotate to a wide variety of disease states and biological mechanisms that align with prior research. However, this EWAS also implicates several novel diseases for future investigation, and highlights the relative importance of different background normalization methods in identifying associations.
BACKGROUND: Pyrethroid pesticide use is increasing worldwide, although the full extent of associated health effects is unknown. An epigenome-wide association study (EWAS) with exploratory pathway analysis may help identify potential pyrethroid-related health effects. METHODS: We performed an exploratory EWAS of chronic ambient pyrethroid exposure using control participants' blood in the Parkinson's Environment and Genes Study in the Central Valley of California (N = 237). We estimated associations of living and working near agricultural pyrethroid pesticide applications in the past 5 years (binary) with site-specific differential methylation, and used a false discovery rate (FDR) cut off of 0.05 for significance. We controlled for age, sex, education, cell count, and an ancestral marker for Hispanic ethnicity. We normalized methylation values for Type I/II probe bias using Beta-Mixture Quantile (BMIQ) normalization, filtered out cross-reactive probes, and evaluated for remaining bias with Surrogate Variable Analysis (SVA). We also evaluated the effects of controlling for cell count and normalizing for Type I/II probe bias by comparing changes in effect estimates and p-values for the top hits across BMIQ and GenomeStudio normalization methods, and controlling for cell count. To facilitate broader interpretation, we annotated genes to the CpG sites and performed gene set overrepresentation analysis, using genes annotated to CpG sites that were associated with pyrethroids at a raw p < 0.05, and controlling for background representation of CpG sites on the chip. We did this for both a biological process context (Gene Ontology terms) using missMethyl, and a disease set context using WebGestalt. For these gene set overrepresentation analyses we also used an FDR cut off of 0.05 for significance of gene sets. RESULTS: After controlling for cell count and applying BMIQ normalization, 4 CpG sites were differentially methylated in relation to pyrethroid exposures. When using GenomeStudio's Illumina normalization, 415 CpG sites were differentially methylated, including all four identified with the BMIQ method. In the gene set overrepresentation analyses, we identified 6 GO terms using BMIQ normalization, and 76 using Illumina normalization, including the 6 identified by BMIQ. For disease sets, we identified signals for Alzheimer's disease, leukemia and several other cancers, diabetes, birth defects, and other diseases, for both normalization methods. We identified minimal changes in effect estimates after controlling for cell count, and controlling for cell count generally weakened p-values. BMIQ normalization, however, resulted in different beta coefficients and weakened p-values. CONCLUSIONS: Chronic ambient pyrethroid exposure is associated with differential methylation at CpG sites that annotate to a wide variety of disease states and biological mechanisms that align with prior research. However, this EWAS also implicates several novel diseases for future investigation, and highlights the relative importance of different background normalization methods in identifying associations.
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