DNA methylation changes in whole blood is associated with exposure to the environmental contaminants, mercury, lead, cadmium and bisphenol A, in women undergoing ovarian stimulation for IVF

Abstract

Background: Changes in DNA methylation may play an important role in the deleterious reproductive effects reported in association with exposure to environmental pollutants. In this pilot study, we identify candidate methylation changes associated with exposure to pollutants in women undergoing in vitro fertilization (IVF).

Methods: Blood and urine were collected from women on the day of oocyte retrieval. Whole blood was analyzed for mercury and lead, and urine for cadmium using inductively coupled plasma mass spectrometry. Unconjugated bisphenol A (BPA) was analyzed in serum using high-performance liquid chromatography with Coularray detection. Participants were dichotomized as higher or lower exposure groups by median concentrations. Using the Illumina GoldenGate Methylation Cancer Panel I, DNA methylation in whole blood from 43 women was assessed at 1505 CpG sites for association with exposure levels of each pollutant. Candidate CpG sites were identified using a Diff Score >|13| (P< 0.05) and an absolute difference >10% which were confirmed using bisulfite pyrosequencing.

Results: Methylation of the GSTM1/5 promoter was increased for women with higher mercury exposure (P= 0.04); however, no correlation was observed (r= 0.17, P= 0.27). Reduced methylation was detected in the COL1A2 promoter in women with higher exposure to lead (P= 0.004), and an inverse correlation was observed (r = - 0.45, P= 0.03). Lower methylation of a promoter CpG site at the TSP50 gene was detected in women with higher BPA exposure (P= 0.005), and again an inverse correlation was identified (r = - 0.51, P= 0.001).

Conclusions: Altered DNA methylation at various CpG sites was associated with exposure to mercury, lead or BPA, providing candidates to be investigated using a larger study sample, as the results may reflect an independently associated predictor (e.g. socioeconomic status, diet, genetic variants, altered blood cell composition). Further studies accommodating variations in these factors will be needed to confirm these associations and identify their underlying causes.

Figure 1

(a) GSTM1_P266 methylation (%) compared between lower (n = 21) and higher (n = 22) mercury exposure groups (P= 0.04), ‘X’ indicates mean value; (b) correlation between GSTM1_P266 methylation (%) and the log of blood mercury concentrations (µg/l), (r= 0.17; P= 0.27); (c) mercury levels (µg/l) compared between women with GSTM1 null (n = 20) and reference (n = 23) genotypes (P= 0.36) and (d) GSTM1_P266 methylation (%) compared between higher and lower mercury exposure groups in women with null GSTM1 genotype (left panel; n = 11 and n = 9, respectively; P= 0.09) or reference GSTM1 genotype (right panel; n = 10 and n = 13, respectively; P= 0.50), ‘X’ indicates mean value.

Figure 2

(a) COL1A2_P407 methylation (%) compared between lower (n = 13) and higher (n = 11) lead exposure groups (P= 0.004), ‘X’ indicates mean value, and (b) correlation between COL1A2_P407 methylation (%) and the log of blood lead concentrations (µg/dl; r= − 0.45; P= 0.03).

Figure 3

(a) TSP50_P137 methylation (%) compared between lower (n = 17) and higher (n = 18) BPA exposure groups (P= 0.005), ‘X’ indicates mean value and (b) correlation between TSP50_P137 methylation (%) and the log of serum BPA concentrations (µg/l; r= − 0.51; P= 0.001).