Common classification schemes for PCB congeners and the gene expression of CYP17, CYP19, ESR1 and ESR2

Science of the Total Environment 414 (2012) 81–89

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Common classification schemes for PCB congeners and the gene expression of CYP17, CYP19, ESR1 and ESR2 Jillian Warner a, Janet Rose Osuch b, f,⁎, Wilfried Karmaus c, Jeffrey R. Landgraf d, Bonita Taffe e, Michael O'Keefe e, Dorota Mikucki f, Pam Haan b, f a

Wayne State University School of Medicine, Detroit, MI, United States Department of Surgery, College of Human Medicine, Michigan State University, East Lansing, Michigan, United States Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States d Research Technology Support Facility, Michigan State University, East Lansing, MI, United States e Bureau of Laboratories, Michigan Department of Community Health, East Lansing, MI, United States f Department of Epidemiology, College of Human Medicine, Michigan State University, East Lansing, MI, United States b c

a r t i c l e

i n f o

Article history: Received 13 December 2010 Received in revised form 17 October 2011 Accepted 21 October 2011 Available online 25 November 2011 Keywords: Gene expression Women PCB congeners

a b s t r a c t Background: Reliable techniques to measure polychlorinated biphenyl (PCB) congeners make the clearer definition of their effects on human health possible. Given that PCBs are classified as endocrine disrupters, we sought to explore the expression of some key genes involved in sex steroid metabolism. Objectives: To examine common classification schemes of PCB congeners and determine whether exposure to groups classified by mechanism of action alter the gene expression (GE) of CYP17, CYP19, and ESR1 and ESR2. Methods: GE and exposure to various classifications of lipid-adjusted PCB congeners were examined in 139 daughters of the Michigan Fisheaters' Cohort. Using mixed models analyses and adjusting for age, menopausal status, and current use of oral contraceptives and hormone replacement therapy, GE data were regressed on exposure to PCB congener groupings based on mechanism of action. Results: Three novel findings are elucidated: first, that up-regulation of CYP19 expression is associated with exposure to PCB groupings containing dioxin-like, potentially anti-estrogenic, immunotoxic congeners, including PCB IUPAC #74, #105, #118, #138, #156, #157, #158, #167, and #170 from this cohort. Second, that exposure to similar congeners (PCB IUPAC #105, #156, #157, #158, and #167 in this cohort) but using a classification based solely on hormonal mechanisms of action is associated with increased expression of ESR2. Third, that increased expression of CYP17 is of borderline significance when associated with exposure to PCB IUPAC #118, #138, and #156. Conclusions: These findings are both counter-intuitive and intriguing. Rather than exhibiting anti-estrogenic effects alone, they suggest that these congeners up-regulate the major enzyme involved in estrogen synthesis and tend to confirm previous findings of links between AhR and ER signaling pathways. Replication of these findings, expansion of the number of genes examined, exploration of mixtures of environmental chemicals, and subsequent study of health outcomes in a larger cohort are future priorities. © 2011 Elsevier B.V. All rights reserved.

1. Introduction 1.1. PCB characteristics, uses, and sources of environmental exposure

Abbreviations: Ct, cycle counts at which the fluorescence crosses the threshold; CYP17, cytochrome P450, subfamily XVII (17-α-hydroxylase); CYP19, cytochrome P450, subfamily XIX (CYP19); ESR1, Estrogen receptor alpha (ER-α): nuclear receptor subfamily 3, group A, member 1; ESR2., Estrogen receptor beta (ER-β): nuclear receptor subfamily 3, group A, member 2; GE, gene expression; LOD, Limit of Detection; MDCH, Michigan Department of Community Health; PCBs, polychlorinated biphenyls. ⁎ Corresponding author at: Department of Surgery and Epidemiology, 632 West Fee, College of Human Medicine, Michigan State University, East Lansing, MI 48824, United States. Tel.: + 1 517 353 5440x1; fax: + 1 517 432 1130. E-mail address: [email protected] (J.R. Osuch). 0048-9697/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.scitotenv.2011.10.044

PCBs are synthetic organic chemicals that consist of 209 different compounds, or congeners (Pliskova et al., 2005). Because of their properties, including non-flammability and chemical stability, PCBs have been used in a variety of commercial products including transformers and capacitors, insulating material including fiberglass and foam, carbonless copy paper, and plastics (Longnecker et al., 1997; U.S. Environmental Protection Agency, 2009). PCBs were banned from manufacture in the United States in 1977 when it was found that they harmed humans and wildlife. However, because they are not readily biodegradable, PCBs persist in the environment and can

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be currently found in the air, seawater and river sediments (He et al., 2001; Li et al., 2009; Sun et al., 2007). Because PCBs accumulate in fatty tissues of living organisms, the consumption of fish and meat contaminated with PCBs are the main sources of human exposure. In addition, mothers pass PCBs to their offspring in-utero and when nursing, as evidenced by measurement of the chemicals in the placenta and umbilical cord blood at the time of delivery, and in breast milk during lactation (Andric et al., 2000; Darnerud et al., 2010; Donato et al., 2006; La Rocca and Mantovani, 2006; Turrio-Baldassarri et al., 2007). 1.2. Toxicity of PCB congeners PCBs have been shown to exhibit a broad range of toxic effects, and numerous studies have shown that PCBs can disrupt the actions of the endocrine system in humans and other species (Garritano et al., 2006; Negri-Cesi et al., 2008; Pliskova et al., 2005). In particular, PCB exposure has been classically thought to alter normal endocrine signaling by mimicking endogenous hormone action by binding to hormone receptors, blocking receptors, or through interference with steroid metabolism (Brouwer et al., 1999; Ma and Sassoon, 2006; Wang et al., 2006). Recently, there has been increasing attention to associations between environmental chemicals and gene regulation through epigenetic and other effects (Edwards and Myers, 2007). Existing studies of PCB exposure and reproductive function in humans have demonstrated a variety of health effects, including decreased sperm motility (Meeker and Hauser, 2010), decrease in fecundity (Faroon et al., 2001), earlier menarche (Schell and Gallo, 2010), and altered sex ratio (Karmaus et al., 2002) in those exposed to higher levels in-utero or in early life. 1.3. Chemical structure, mechanisms of action, and classifications of PCB congeners The structure of a PCB congener largely determines the nature of the biochemical and toxic responses in living organisms and different structural classes of congeners can express diverse effects and sometimes completely conflicting actions (Safe et al., 1985; Safe, 1994). In general, lower molecular weight PCBs have been found to exhibit estrogenic activity, while higher molecular weight PCBs are considered anti-estrogenic (Pliskova et al., 2005). However, there are exceptions to this generalization. PCB congeners can be grouped into categories with similar characteristics based on degree of chlorination, degree and type of enzyme induction, estrogenic and anti-estrogenic activities, prevalence in the environment, abundance in animal tissue and other toxicological characteristics. Factor analysis has also been utilized to group PCBs. The results of these categorizations have been compiled in several ways (Cooke et al., 2001; Kannan and Petrick, 2009; McFarland and Clarke, 1989; Moysich et al., 1999; Ritchie et al., 2005; Wolff et al., 1997), and because of improvements in analytical techniques (Kannan and Petrick, 2009), classifications continue to evolve. Moysich has studied the various approaches to PCB congener classification and has concluded that the degree of chlorination and classifications based on enzyme induction and toxicological aspects represented the most useful way to classify them (Moysich et al., 1999). PCBs are metabolized via the cytochrome P450 monooxygenase enzyme system, in particular affecting the CYPIA and CYPIIB subfamilies, which are dependent on the degree and positions of chlorination of the congener (Kannan and Petrick, 2009). The classification of PCBs by mechanism of action is most commonly based on the metabolic properties of each congener. Classification schemes include pure cytochrome P450 IA inducers (Methylcholanthrine, MC-type inducers), which have physiological effects similar to dioxin, pure cytochrome P450 CYPIIB inducers, which induce Phenobarbital metabolism, and various classifications of mixtures of the two or those classified with

no or no known activity(Kannan and Petrick, 2009). PCB congeners can also be classified according to estrogenic or anti-estrogenic activity (Cooke et al., 2001), which is somewhat, but not completely, independent of metabolic classification schemes. It has become increasingly important to elucidate the mechanism of action by which PCB exposure exerts its adverse health effects at the molecular level. One possible molecular mechanism is by altering the gene expression (GE) of enzymes and receptors involved in sex steroid metabolism. In particular, four genes: CYP19, encoding aromatase, CYP17, encoding 17-α-hydroxylase, and ESR1 and ESR2, encoding estrogen receptor alpha and beta respectively, have been shown to be affected by PCB exposure in the form of Aroclor or other commercially available mixtures of PCBs (Andric et al., 2000; Bonefeld-Jorgensen et al., 2001; Ceccatelli et al., 2006; Drenth et al., 1998; Korach et al., 1988; Li, 2007; Mortensen and Arukwe, 2008; Murugesan et al., 2008; Oh et al., 2007; Salama et al., 2003; Tavolari et al., 2006; U.S.Environmental Protection Agency, 2008; Woodhouse and Cooke, 2004; Xu et al., 2006). Understanding the association between exposure to varying mixtures and concentrations of PCB congeners and altered gene expression may provide insights into the varying health effects that can become manifested. 1.4. Purpose The purpose of this study is to examine the association between groupings of PCB congeners based on mechanism of action and the expression of CYP17, CYP19, and ESR1 and ESR2 in the daughters of the original Michigan Fisheaters' Cohort. 2. Methods 2.1. Description of the population The Michigan Fisheaters' Cohort was established by the Michigan Department of Community Health (MDCH) to study the effects of organochlorine exposure on human health. MDCH recruited anglers and their spouses living in western Michigan who fished in Lake Michigan or its tributaries between 1973 and 1991(Humphrey and Budd, 1996). In 2000, after approval by the institutional review boards of both Michigan State University and MDCH, we asked the participants of this cohort who had agreed to be recontacted when necessary to identify the addresses of their daughters and sons. 2.2. Participant recruitment Because we found that daughters were more willing to enroll, we focused our recruitment on female offspring. We developed a brochure and newsletter explaining the study and mailed it to potential participants. Telephone calls were placed two weeks after the initial packet was sent to explain the study further and respond to questions. Participation involved a one-hour telephone interview and a one hour home (or alternative site of the participant's choosing) visit to draw blood and obtain anthropomorphic measurements. $100 compensation was offered for participation. If a respondent agreed to participate, a consent form was mailed and upon its return, appointments made for the interview and home visit. 2.3. Conduct of study Interviews were conducted by telephone to ascertain information regarding demographic characteristics, menstrual, pregnancy, and breastfeeding histories, as well as oral contraceptive and hormone replacement therapy use and used a standardized questionnaire and script. Two research assistants were present for each interview, the first who administered the questionnaire and recorded responses directly into an Access database, and the second who recorded

J. Warner et al. / Science of the Total Environment 414 (2012) 81–89

responses onto a hard copy of the questionnaire. Following the interview, responses were compared and if a discrepancy was found, it was resolved by either placing a telephone call immediately or during the in-person visit. Specifics of the anthropomorphic measurements obtained during the in-person visit have been published previously (Osuch et al., 2010). Non-fasting blood for determination of the exposure (PCB congeners) and the outcomes (GE of CYP17, CYP19, and ESR1 and ESR2) was collected during the in-person visit. Serum for PCB congeners and plasma for GE analysis were stored at −20 °C following specimen collection. Plasma for GE analysis was collected in PAXgene Blood RNA Tubes (PreAnalitiX, Plymouth, UK). In premenopausal participants blood was collected during days 3–10 of the menstrual cycle; otherwise blood was collected at random times of the month. This is important because GE varies throughout the ovulatory cycle (Castles et al., 1997; Vottero et al., 2006).

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the Δ Ct between the housekeeping gene and the target gene, the greater the activity of the target gene. In a few cases gene expression was very low and did not generate a Ct value because the curve did not cross the threshold within the amplification cycles of the assay. In these cases two measurements were averaged instead of three. 2.6. PCB congener classifications according to mechanism of action We examined several published PCB congener classification groupings, including those of Wolff (Wolff et al., 1997), Moysich (Moysich et al., 1999), McFarland (McFarland and Clarke, 1989), Cooke (Cooke et al., 2001) and Kannan (Kannan and Petrick, 2009). Because not all classifications included each congener, we combined them into an overall grouping by mechanism of action, entitled “Combined”. In the rare circumstance when conflict existed between classifications, we used the most recent publication's classification to assign the congener in the “combined” classification scheme.

2.4. Determination of serum PCB congeners 2.7. Statistical analyses The Analytical Chemistry Section laboratory at MDCH performed serum analysis for congener-specific PCBs using modifications of procedures originally described by Najam (Najam et al., 1999) and modified by the U.S. Environmental Protection Agency. Serum and quality control samples were extracted into diethyl ether–hexane (1:1 v/v), evaporated to dryness, and the lipid containing PCBs resuspended in hexane. This extract was fractionated over a Florisil column. The 6% (v/v) diethyl ether in hexane fraction collected from the Florisil column was passed over a 3% deactivated silica gel 60 column to generate the PCB fraction. Two 2 μL aliquots of fraction II (containing the PCB congeners) were analyzed by dual column high-resolution capillary gas chromatography with electron capture detection. The first column determined 63 congeners with a total of 73 congeners determined using the dual column approach. Serum concentrations of PCBs were based on total serum lipids, determined using gravimetric methods and PCB congeners were reported as ng/g lipid. Laboratory values reported as less than the limit of detection (0.031, 0.0625, or 0.125 μg/kg, depending on the congener) were assigned a value half that of the limit of detection for statistical analysis. 2.5. Determination of gene expression The collected plasma was stored at −20 °C until analyzed. Gene expression was determined after preparing RNA from blood leukocytes using the PAXgene Blood RNA Kit (Qiagen, Hilden, Germany). The quality of the isolated RNA was assessed using an Agilent Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA). Purified RNA was converted to cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA). The resulting cDNA was then profiled for the expression of the individual genes utilizing the appropriate Taqman assay on an ABI 7900ht Sequence Detection System (Applied Biosystems, Foster City, CA). Gene expression of CYP17, CYP19, and ESR1 and ESR2 was determined using Applied Biosystems Taqman assay ID Hs00164375, Hs00240671, Hs00174860, and Hs00230957, respectively. After being run in triplicate, GE assay results were averaged and normalized to GE results in two housekeeping genes, RNA Polymerase II and 18S ribosomal RNA, which served as control or reference genes. The latter housekeeping gene has been found to exhibit less variation than the former in our lab. The number of cycles required to detect an exponential increase in fluorescence (and therefore cDNA) was measured and named Ct (cycle count). The Ct of the target gene was then subtracted from that of the housekeeping gene and expressed as Δ Ct (Pfaffl, 2001). The difference in the amount of fluorescence (Δ Ct) between the control (housekeeping gene) and the sample RNA represents the level of expression of a particular gene. Housekeeping genes are ubiquitously expressed and therefore have a relatively low Ct value; the smaller

We used a repeated measurement model to adjust for measurement error using mixed models in SAS (Version 9.2; Statistical Analysis System, Cary, NC) to account for multiple measurements. In addition, mixed models also accounted for the fact that some of the participants were offspring from the same mother. We adjusted within the mixed models for the housekeeping gene and target genes of interest. In epidemiological studies using housekeeping genes as controls, it is necessary for them to be unregulated by exposures thought to affect the target gene. If affected, adjusting would mask changes in target gene expression and produce false negative findings. Therefore, we initially tested whether expression of RNA Polymerase II and 18S Ribosomal RNA were associated with serum concentrations of PCB congener groups and planned to discard the affected housekeeping gene if it was affected. Multivariate mixed models were adjusted for the following confounders: age (continuous variable), current use of oral contraceptives (yes/no) or hormone replacement therapy (yes/no), and menopausal status (premenopausal vs. postmenopausal). Women were considered to be premenopausal if they had experienced a period in the prior 12 months, or if b50 years of age if she had had a hysterectomy but still had one ovary. If a woman had been on hormone replacement therapy for more than a year, she was defined as postmenopausal. 3. Results 3.1. Description of participants Of 259 daughters identified as offspring of the Michigan Fisheaters' Cohort, we were able to contact 213, 149 of whom agreed to participate, and 139 in whom we obtained blood samples for PCB congener analysis. These participants were birthed by 93 different mothers. Characteristics for these participants, including age, education, height, and weight, body mass index (BMI), and birth weight, age at menarche, menopausal status, smoking status, and current use of oral contraceptives or hormone replacement therapy are described in Table 1. 3.2. PCB congeners measured Seventy-three individual PCB congeners were measured in our population. In addition, there were three co-elutants (PCB IUPAC #66 + 95, #138 + 163, and #196 + 203) measured. Twenty-eight congeners, including two co-elutants, were above the limits of detection (LOD) for at least one participant, and 12 were above the LOD for >20% of participants. In decreasing order of frequency with relative percentages in parentheses, these were PCB IUPAC #180 (92.1),

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Table 1 Characteristics of 139 daughters of the Michigan Fisheaters' Cohort. Continuous variables

Number

Mean

Minimum

Maximum

Age at interview (years) Height in cm Weight in kg Body Mass Index (kg/m2) Birth weight (kg) Age at menarche (years) Lipid weight (g)

139 138 138 138 138 139 139

40.0 167.5 76.5 27.2 3.397 12.2 0.022

20.2 151.3 46.0 17.7 1.219 7.0 0.010

52.5 188.2 144.5 51.0 5.443 21.0 0.047

Categorical variables Breastfed* No Yes Missing Menopausal status Pre Peri Post Missing Current oral contraceptive use Current hormone replacement therapy use Smoking status Current Former Non-smoker High school graduate or less Associate degree/some college/technical school College graduate or graduate school?

Number

Percent

57 53 29

48.2 51.8

105 11 24 9 37 17

75.0 7.9 17.4 24.8 11.4

38 16 85 15 37

27.3 11.5 61.2 10.8 26.6

87

62.6

*The source of breastfeeding data was maternal recall; duration was not recorded.

#153 (83.4), #137 (82.0), #158 (79.9), #170 (67.6), #138 + 163 (54.7), #201 (48.9), #194 (45.3), #156 (40.3), #118 (32.4), #187 (27.3), and #196 + 203 (21.6). The median, minimum and maximum values for each of the lipid-adjusted PCB congeners expressed in ng/g lipid are listed in Table 2, which also indicates the percentage of participants in whom each congener was detected above the LOD. The various PCB groupings found in the literature based on mechanism of action are listed in Table 3. The end of the table lists five groupings classified as “Combined”, representing combinations of the previous classifications by mechanism of action. The medians and minimum and maximum values for the various classifications are listed in Table 4. 3.3. The association of PCB congener groupings with GE of CYP17, CYP19, ESR1 and ESR2 The results of the multiple regression models for the association between PCB congener groupings and the GE of CYP17, CYP19, ESR1 and ESR2, adjusted for age, current use of oral contraceptives or hormone replacement therapy, and menopausal status are demonstrated in Table 5. The results show three findings: first, that CYP19 expression is significantly up-regulated by exposure to PCB congener groupings Wolff IIA, McFarland groups 1B, and 4, Moysich mixed-type, Kannan 3A and 3B, and Combined Classification 3-MC Inducers and Combined Classification–Mixed Inducers. The congeners contributing to these findings in this cohort include PCB IUPAC #74, #105, #118, #138, #156, #167, and #170 as represented in three classifications, in addition to # 157 and #158, which were only measured in the classification scheme of McFarland. Second, that ESR2 is significantly upregulated by exposure to the PCB congener groupings of McFarland Group 4 and the Cooke Non-Estrogenic Group. The congeners contributing to these findings in this cohort include PCB IUPAC #157, #158, #167 from McFarland's classification and #105 and #156 from Cooke's. Finally, that increased expression of CYP17 is of borderline significance when associated with exposure to PCB IUPAC #118, #138, and

Table 2 Median, minimum and maximum values for lipid-adjusted PCB congeners expressed in μg/L (ppb) serum lipid weight in 139 daughters of the Michigan Fisheaters' Cohort, including the percent of participants above the limit of detection. PCB IUPAC congener #

Number

Median

Minimum

Maximum

Percent above limits of detection

17 18 22 25 26 28 31 32 33 40 42 44 45 47 49 52 56 63 64 66 + 95 70 71 74 77 82 84 87 90 91 92 97 99 100 101 105 110 118 126 128 130 132 135 136 137 138 + 163 141 144 146 149 151 153 156 157 158 167 170 171 172 174 175 177 179 180 183 185 187 190 193 194 195 196 + 203 198

139 139 139 139 139 139 139 139 139 139 139 139 110 138 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 139 138 139 139 132 139 139 139 139 139 139 134 139 139

11.42 11.42 6.96 11.42 11.42 11.42 11.42 11.42 11.42 11.42 11.42 11.42 11.47 11.42 11.42 11.42 5.75 5.75 5.75 22.83 11.42 11.42 11.90 11.42 5.75 11.42 5.75 5.86 11.42 11.42 5.75 11.90 11.42 11.42 5.97 5.75 6.63 11.42 2.83 5.80 5.75 5.75 11.42 3.00 25.47 5.75 5.75 6.11 11.51 5.75 39.89 3.44 2.92 2.87 5.83 10.40 5.81 2.95 5.75 2.84 5.83 2.83 31.39 5.94 2.83 6.33 2.83 2.95 4.00 2.94 6.21 2.83

5.32 5.32 2.92 5.32 5.32 5.32 5.32 5.32 5.32 5.32 5.32 5.32 5.32 5.32 5.32 5.32 2.68 2.68 2.68 10.64 5.32 5.32 5.79 5.32 2.68 5.32 2.68 2.68 5.32 5.32 2.68 5.79 5.32 5.32 2.92 2.68 2.92 5.32 1.32 2.92 2.68 2.68 5.32 1.46 5.79 2.68 2.68 2.92 5.36 2.68 2.92 1.44 1.44 1.34 2.92 1.44 2.68 1.44 2.68 1.44 2.92 1.32 1.44 2.92 1.32 2.92 1.32 1.44 1.44 1.44 2.92 1.32

21.55 21.55 16.67 21.55 21.55 21.55 21.55 21.55 21.55 21.55 21.55 21.55 21.55 21.55 21.55 21.55 10.86 10.86 10.86 43.10 21.55 21.55 30.74 21.55 10.86 21.55 10.86 10.86 21.55 21.55 10.86 36.89 21.55 21.55 20.64 10.86 66.13 21.55 5.34 10.86 10.86 10.86 21.55 13.46 212.06 10.86 10.86 45.31 21.72 10.86 193.47 62.81 21.70 5.43 21.59 95.83 20.72 19.22 10.86 5.34 18.87 5.34 159.60 28.08 5.34 93.02 5.34 15.58 50.31 17.68 56.61 5.34

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8.6 0 0 0 0 7.2 0 0 0 7.2 0 0 5.8 0 32.4 0 0 1.4 0 0 0 82.0 54.7 0 0 16.5 0 0 83.4 40.3 6.5 79.9 2.9 67.6 1.4 12.2 0 0 2.2 0 92.1 5.8 0 27.3 0 11.5 45.3 6.5 21.6 0

J. Warner et al. / Science of the Total Environment 414 (2012) 81–89 Table 2 (continued) PCB IUPAC congener #

Number

Median

Minimum

Maximum

Percent above limits of detection

199 201 205 206

139 139 139 139

2.84 4.43 2.83 3.00

1.32 1.44 1.32 1.44

5.34 61.65 5.34 20.35

0.7 48.9 0 13.6

#156 (Moysich mixed type classification). ESR1 expression did not show an association with any of the congener classifications. No correlations were found between gene expression and blood lipid content for either housekeeping genes (data not shown). The Ct of the RNA Polymerase II transcript was related to the lipidadjusted Moysich Phenobarbital-type inducer grouping as well as the combined Phenobarbital-type inducer grouping, which disqualified this housekeeping gene as a point of reference for this part of the analysis.

Table 3 PCB congener groupings. Congener group Wolff groupings Group 1A — Potentially estrogenic, weak phenobarbital inducers, not persistent Group 1B — Potentially estrogenic, weak phenobarbital inducers, persistent Group 2A — Potentially anti-estrogenic and immunotoxic, dioxin-like nonortho and mono-ortho substituted; moderately persistent Group 2B — Potentially anti-estrogenic and immunotoxic, dioxin-like but limited dioxin activity — di-ortho substituted; persistent Group 3 — Phenobarbital, CYP1A and CYP1B inducers, biologically persistent Moysich groupings PB-type

4. Discussion 4.1. Results summary This is the first study in humans to demonstrate an association between in vivo exposure to specific PCB congeners and an increased expression of two key genes, CYP19 and ESR2, involved in sex steroid metabolism. The congeners associated with an up-regulation of CYP19 in this cohort have been classified as dioxin-like, potentially anti-estrogenic, and immunotoxic by multiple authors and include PCB IUPAC #74, #105, #118, #138, #156, # 157, #158, #167 and #170. The congeners associated with an up-regulation of ESR2 are of similar classification and include PCB IUPAC #105, #156, #157, #158 and #167. The increased gene expression of CYP17 was of only borderline significance when exposed to PCB IUPAC #118, #138, and #156, and ESR1 expression did not show an association with any of the congener classifications.

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3-MC type Mixed-type No known activity

McFarland groupings Group 1A — Pure microsomal mixed function oxidase MFO inducing congeners, toxic but not abundant Group 1B — Mixed-type inducers, abundant Group 2 — Phenobarbital-type inducers, abundant Group 3 — Weak or non-Inducers, frequent in fish Group 4 — Mixed-type, infrequent, potentially toxic

PCB IUPAC Congener #s 31, 44, 49, 52, 70 101, 174, 177, 187, 201 66a, 74, 77, 105, 118, 126, 156, 167, 169

128, 138b, 170

99, 153, 180, 183, 196c, 203c

15+17d, 52, 66+95, 87, 99, 101, 136, 82+151e, 153, 180, 183, 194, 195, 203+ 196, 205, 206 77 + 110f 118, 128, 138b, 156 + 171g 6, 7+9, 16+32h, 18, 19, 22, 25+50i, 31+28j, 33, 40, 45, 47+48k, 49, 55, 42+ 59l, 60, 70, 97, 129, 134, 135, 141+ 179m, 147, 149, 176, 177, 185, 187, 188, 200

77, 126, 169

105, 118, 128, 138b, 156, 170 87, 99, 101, 153, 180, 183, 194 18, 44, 49, 52, 70, 74, 151, 177, 187, 201 37, 81, 114, 119, 123, 157, 158, 167, 168, 189

4.2. Interpretation of results and speculations about GE and cell-signaling The results appear counter-intuitive at first glance, given that 1) aromatase, the protein product of CYP19, functions as the major enzyme allowing for the conversion of androstenedione and testosterone to estradiol, the most active form of estrogen in humans, and 2) chemicals that bind to the AhR receptor are commonly viewed as anti-estrogenic. However, they are particularly intriguing, given the increasing evidence for cross-talk between the estrogen receptor (ER) and the aryl hydrocarbon receptor (AhR) signaling pathways demonstrated over the past 20 years. (Cooke et al., 2008; Swedenborg and Pongratz, 2010) Dioxin-like chemicals in the environment have been demonstrated to exert their anti-estrogenic effects by binding to the AhR,

Notes to Table 3: PCB IUPAC numbers in bold indicate that they were measured in our cohort. a PCB IUPAC #66 co-eluted with #95 in our cohort. b PCB IUPAC #138 co-eluted with #163 in our cohort. c PCB IUPAC #196 co-eluted with #203 in our cohort. d PCB IUPAC #15 + 17 not measured in our cohort, both measured separately. e PCB IUPAC #82 + 151 not measured in our cohort; both measured separately. f PCB IUPAC #77 + 110 not measured in our cohort; both measured separately. g PCB IUPAC #156 and 171 not measured in our cohort; both measured separately. h PCB IUPAC #16 + 32 not measured in our cohort; #32 measured. i PCB IUPAC #25 + 50 not measured in our cohort; #25 measured. j PCB IUPAC #31 + 28 not measured in our cohort; both measured separately. k PCB IUPAC #47 + 48 not measured in our cohort; #47 measured. l PCB IUPAC #42 + 59 not measured in our cohort; #42 measured. m PCB IUPAC #141 + 179 not measured in our cohort; both measured separately. n PCB UIPAC #77 and #126 are listed in both estrogenic and anti-estrogenic categories.

Cooke groupings Estrogenic

Anti-estrogenic Kannan groupings Group 1 — Non-metabolizable → persistent Group 2A — Pure or weak PB type enzyme inducers Group 2B — Weak PB type inducers Group 3A — Strong inducers and substrates for MC type enzymes Group 3B — MC type inducers but there are weak or pure PB type inducers as well (99 and 177) Combined groupings Combined Group 1: 3-methylcholanthrene inducers; CYP IA inducers/substrates Combined Group 2: Mixed type

1, 3, 4, 8, 15, 18, 21, 31, 44, 47, 48, 49, 52, 54, 61, 70, 75, 77n, 80, 95, 99, 101, 104, 110, 126n, 136, 153, 155, 184, 188 37, 77n, 81, 105, 114, 126n, 155, 156, 169

153, 178, 180, 183, 187, 193, 194, 199, 201, 202 52, 92, 97, 101, 110, 129, 141 91, 95, 132, 136, 149, 151, 174, 179 66a, 70, 74, 77, 105, 107, 118, 126, 156 99, 128, 138b, 170, 171, 177

66a, 70, 74, 77, 105, 107, 110, 118, 126, 156, 167

99, 128, 138b, 157, 158, 167, 170, 171, 177 Combined Group 3: Phenobarbital-type 17, 31, 44, 49, 52, 82, 87, 91, 92, 95, 97, inducers: CYP IIB inducers 99, 101, 110, 132, 136, 141, 149, 151, 153, 174, 177, 179, 180, 183, 187, 193, 194, 195, 196–203, 199, 201, 205, 206 Combined Group 4: No known induction 18, 22, 25, 28, 32, 33, 40, 42, 45, 47, 135, activity 185 Combined Group others (Measured in 26, 56, 63, 64, 71, 84, 90, 100, 130, 137, our cohort; not otherwise classified) 144, 146, 172, 175, 198

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Table 4 Median, minimum and maximum values for lipid-adjusted PCB congener groupings expressed in μg/L (ppb) serum lipid weight in 139 daughters of the Michigan Fisheaters' Cohort.

Table 5 Multiple regression model for the association between PCB congener groupings and the gene expression of CYP19, CYP 17, ESR1 and ESR2 without adjustment for DDE levels. Βeta estimate

PCB congener grouping

Number

Median

Minimum

Maximum

Variable

McFarland Group 1A McFarland Group 1B McFarland Group 2 McFarland Group 3 McFarland Group 4 Wolff Group 1A Wolff Group 1B Wolff Group 2A Wolff Group 2B Wolff Group 3 Moysich PB-inducers Moysich 3-MC inducers Moysich mixed inducers Moysich no known activity Cooke estrogenic Cooke anti-estrogenic Kannan Group I Kannan Group IIA Kannan Group IIB Kannan Group IIIA Kannan Group IIIB Combined 3-MC inducers Combined mixed inducers Combined PB-inducers Combined no known activity Combined Group others

139 139 131 139 139 139 139 139 139 131 126 139 139 109 137 139 132 139 139 139 138 139 139 126 109 138

22.83 58.49 110.69 98.48 11.68 57.08 37.77 86.13 40.13 95.84 202.34 17.17 46.45 197.70 186.90 34.50 100.85 51.51 54.43 92.08 62.19 104.12 74.34 306.64 118.70 101.48

10.64 15.93 23.19 44.91 5.81 26.60 15.97 39.12 8.67 15.97 65.19 8.00 14.49 95.65 75.28 15.93 15.93 24.00 25.36 41.99 20.28 47.82 26.09 114.54 57.19 49.33

43.10 458.78 477.04 250.14 44.59 107.76 186.07 221.61 309.21 470.80 623.81 32.41 344.99 356.21 339.49 94.08 603.77 97.24 102.76 205.37 363.55 229.61 408.15 871.46 221.03 192.06

McFarland Group IA — Pure microsomal mixed function oxidase MFO inducing congeners, toxic but not abundant RNA Polymerase II − 0.0163 0.0225 0.4703 18S ribosomal RNA 0.0210 0.0240 0.3811 CYP19 − 0.0192 0.0385 0.6184 CYP17 − 0.0171 0.0226 0.4439 ESR1 0.0072 0.0116 0.5358 ESR2 0.0240 0.0158 0.1314

probably through one or both of the following mechanisms: 1) by inhibiting the ER signaling pathway in a variety of ways, including inhibition of liganded ER to bind to estrogen response elements, thereby decreasing the availability of estrogen receptor alpha, or 2) by occupying the ER and preventing binding of estradiol, its most potent ligand, to it (Cooke et al., 2008). However, most of the experimental evidence leading to the anti-estrogenic effects of dioxin-like chemicals has been demonstrated in either uterine tissue or in cell lines. It is possible that liganded AhR could have estrogenic, rather than anti-estrogenic effects in human tissues not yet examined. Similar to the drug Tamoxifen, which is anti-estrogenic in the breast and estrogenic in the uterus, the effects of dioxin-like PCB congeners bound to AhR could be tissue-specific. If so, this could explain the upregulation of CYP19 in our study as a tissue-specific effect in white cells. Alternatively, or in addition, our understanding of the mechanisms by which environmental pollutants behave after binding to AhR may not be complete, and that AHR binding induces more than simple anti-estrogen activity. This perspective is further strengthened when considering our finding that ESR2 activity is up-regulated by exposure to some of the same congeners as CYP19. Although the biologic activity of estrogen receptor β, the protein product of ESR2, is poorly defined, its link with exposure to congeners that are also associated with increased CYP19 activity offer some intriguing speculations about its role in sex steroid metabolism regulation. In particular, Ohtake demonstrated that an AhR–3-MC bound complex could activate both ER alpha and beta in the absence of its major ligand, estradiol, resulting in estrogenic effects in MCF-7 breast cancer cells (Ohtake et al., 2003). Our study appears to corroborate these findings. 4.3. Study strengths Strengths of this study include the measurement of a large and representative number of PCB congeners in a certified laboratory using advanced techniques with dual-column gas chromatography. The recent NHANES data for premenopausal females measured 12 PCB congeners (Axelrad et al., 2009), 9 of which were also measured

Standard error

Probability > F

McFarland Group IB — Mixed-type inducers, abundant RNA Polymerase II − 0.0020 0.0018 18S ribosomal RNA − 0.0021 0.0019 CYP19 0.0067 0.0030 CYP17 0.0030 0.0017 ESR1 0.0009 0.0009 ESR2 0.0010 0.0012

0.2721 0.2741 0.0251* 0.0913 0.3097 0.4177

McFarland Group 2 — Phenobarbital-type inducers, abundant RNA Polymerase II − 0.0023 0.0016 18S ribosomal RNA − 0.0027 0.0017 CYP19 0.0037 0.0027 CYP17 0.0025 0.0016 ESR1 0.0009 0.0008 ESR2 0.0004 0.0011

0.1628 0.1188 0.1684 0.1197 0.2977 0.7482

McFarland Group 3 — Weak or non-inducers, frequent in fish RNA Polymerase II − 0.0036 0.0040 18S ribosomal RNA − 0.0012 0.0043 CYP19 0.0041 0.0068 CYP17 0.0034 0.0039 ESR1 0.0019 0.0021 ESR2 0.0042 0.0028 McFarland Group 4 — Mixed type, infrequent, potentially toxic RNA Polymerase II − 0.0494 0.0270 18S ribosomal RNA − 0.0272 0.0290 CYP19 0.0944 0.0452 CYP17 0.0038 0.0265 ESR1 0.0092 0.0141 ESR2 0.0399 0.0190 Wolff Group IA — Potentially estrogenic, persistent RNA Polymerase II − 0.0065 18S ribosomal RNA 0.0084 CYP19 − 0.0077 CYP17 − 0.0069 ESR1 0.0029 ESR2 0.0096

0.3703 0.7749 0.5516 0.3842 0.3687 0.1434 0.0681 0.3503 0.0393* 0.8864 0.5166 0.0377*

weak phenobarbital inducers, not 0.0090 0.0096 0.0154 0.0089 0.0047 0.0063

0.4703 0.3811 0.6184 0.4439 0.5358 0.1314

Wolff Group IB — Potentially estrogenic, weak phenobarbital inducers, persistent RNA Polymerase II − 0.0035 0.0053 0.5083 18S ribosomal RNA − 0.0044 0.0056 0.4327 CYP19 0.0046 0.0090 0.6111 CYP17 0.0054 0.0052 0.2976 ESR1 0.0017 0.0027 0.5289 ESR2 0.0032 0.0038 0.3964 Wolff Group 2A — Potentially anti-estrogenic and immunotoxic, dioxin-like nonortho and mono-ortho substituted; moderately persistent RNA Polymerase II − 0.0056 0.0044 0.2075 18S ribosomal RNA − 0.0018 0.0047 0.6993 CYP19 0.0192 0.0073 0.0096* CYP17 0.0068 0.0043 0.1212 ESR1 0.0027 0.0023 0.2443 ESR2 0.0059 0.0031 0.0570 Wolff Group 2B — Potentially anti-estrogenic and immunotoxic, limited dioxin activity, di-ortho substituted; persistent RNA Polymerase II − 0.0027 0.0024 18S ribosomal RNA − 0.0029 0.0026 CYP19 0.0076 0.0041 CYP17 0.0036 0.0024 ESR1 0.0013 0.0013

dioxin-like but 0.2643 0.2610 0.0653 0.1374 0.3050

J. Warner et al. / Science of the Total Environment 414 (2012) 81–89 Table 5 (continued)

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Table 5 (continued)

Variable

Βeta estimate

Standard error

Probability > F

Variable

Βeta estimate

Standard error

Probability > F

ESR2

0.0011

0.0017

0.5194

CYP19 CYP17 ESR1 ESR2

− 0.0080 − 0.0070 0.0030 0.0099

0.0162 0.0093 0.0049 0.0066

0.6196 0.4527 0.5465 0.1373

Wolff Group 3 — Phenobarbital, CYP1A and CYP1B inducers, biologically persistent RNA Polymerase II − 0.0022 0.0016 0.1764 18S ribosomal RNA − 0.0028 0.0017 0.1019 CYP19 0.0039 0.0027 0.1466 CYP17 0.0026 0.0016 0.0966 ESR1 0.0009 0.0008 0.3041 ESR2 0.0003 0.0012 0.7772 Moysich phenobarbital-type induction group RNA Polymerase II − 0.0033 0.0014 18S ribosomal RNA − 0.0018 0.0016 CYP19 0.0022 0.0024 CYP17 0.0009 0.0014 ESR1 0.0006 0.0008 ESR2 0.0006 0.0011

0.0269* 0.2635 0.3623 0.5291 0.4415 0.5697

Moysich 3-methylcholanthrene-type induction group RNA Polymerase II − 0.0216 0.0299 18S ribosomal RNA 0.0280 0.0318 CYP19 − 0.0256 0.0512 CYP17 − 0.0228 0.0296 ESR1 0.0096 0.0155 ESR2 0.0319 0.0211

0.4703 0.3811 0.6184 0.4439 0.5358 0.1314

Moysich mixed type induction group RNA Polymerase II − 0.0026 0.0023 18S ribosomal RNA − 0.0027 0.0024 CYP19 0.0095 0.0038 CYP17 0.0044 0.0022 ESR1 0.0012 0.0012 ESR2 0.0013 0.0016 Moysich no known induction activity group RNA Polymerase II − 0.0019 0.0030 18S ribosomal RNA 0.0023 0.0029 CYP19 − 0.0037 0.0048 CYP17 − 0.0012 0.0030 ESR1 0.0009 0.0014 ESR2 0.0026 0.0022 Cook estrogenic classification RNA Polymerase II − 0.0032 18S ribosomal RNA − 0.0012 CYP19 0.0024 CYP17 0.0015 ESR1 0.0016 ESR2 0.0022 Cook non-estrogenic classification RNA Polymerase II − 0.0132 18S ribosomal RNA − 0.0019 CYP19 0.0238 CYP17 0.0016 ESR1 0.0075 ESR2 0.0162

0.0023 0.0025 0.0039 0.0023 0.0012 0.0011

0.0108 0.0116 0.0184 0.0108 0.0056 0.0076

Kannan Group 1 — Non-metabolizable and persistent RNA Polymerase II − 0.0016 0.0013 18S ribosomal RNA − 0.0021 0.0014 CYP19 0.0024 0.0022 CYP17 0.0018 0.0013 ESR1 0.0006 0.0007 ESR2 0.0001 0.0009

0.2528 0.2681 0.0125* 0.0504* 0.3106 0.4232 0.0885 0.4168 0.4496 0.6762 0.5291 0.2409

0.1727 0.6335 0.5437 0.5036 0.1936 0.1873

0.2243 0.8683 0.1996 0.8830 0.1824 0.0348*

0.2325 0.1299 0.2690 0.1582 0.4077 0.8873

Kannan Group 2A — Pure or weak phenobarbital-type enzyme inducers RNA Polymerase II − 0.0072 0.0100 0.4703 18S ribosomal RNA 0.0093 0.0106 0.3811 CYP19 − 0.0085 0.0171 0.6184 CYP17 − 0.0076 0.0099 0.4439 ESR1 0.0032 0.0052 0.5358 ESR2 0.1065 0.0070 0.1314 Kannan Group 2B — Weak phenobarbital inducers RNA Polymerase II 0.0066 0.0094 18S ribosomal RNA 0.0089 0.0100

0.4854 0.3754 (continued on next page)

Kannan Group 3A — Strong inducers/substrates for 3-methylcholanthrene-type enzymes RNA Polymerase II − 0.0055 0.0045 0.2209 18S ribosomal RNA − 0.0012 0.0048 0.8026 CYP19 0.0184 0.0075 0.0149* CYP17 0.0066 0.0044 0.1368 ESR1 0.0028 0.0023 0.2272 ESR2 0.0061 0.0031 0.0538 Kannan Group 3B — Mixed inducers RNA Polymerase II − 0.0026 18S ribosomal RNA − 0.0027 CYP19 0.0074 CYP17 0.0035 ESR1 0.0012 ESR2 0.0014

0.0022 0.0023 0.0036 0.0021 0.0011 0.0016

0.2309 0.2521 0.0440* 0.1025 0.2758 0.3816

0.0041 0.0044

0.2024 0.8079

0.0040 0.0021 0.0029

0.1857 0.2408 0.0475*

Combined classification — Mixed inducers RNA Polymerase II − 0.0027 18S ribosomal RNA − 0.0026

0.0021 0.0022

0.2025 0.2484

CYP19 CYP17 ESR1 ESR2

0.0020 0.0011 0.0015

0.1226 0.2808 0.3262

0.0011 0.0012 0.0018 0.0010 0.0006 0.0008

0.0337* 0.3527 0.4332 0.6244 0.4943 0.4689

Combined classification RNA Polymerase II 18S ribosomal RNA CYP19 CYP17 ESR1 ESR2

— 3-MC inducers − 0.0052 − 0.0011 0.0054 0.0025 0.0058

0.0031 0.0012 0.0015

Combined classification RNA Polymerase II 18S ribosomal RNA CYP19 CYP17 ESR1 ESR2

— PB-inducers − 0.0024 − 0.0011 0.0014 0.0005 0.0004 0.0006

Combined classification RNA Polymerase II 18S ribosomal RNA CYP19 CYP17 ESR1 ESR2

— No known activity − 0.0035 0.0049 0.0049 0.0047 − 0.0080 0.0078 − 0.0032 0.0048 0.0015 0.0023 0.0027 0.0035

0.4731 0.2928 0.3072 0.5046 0.5223 0.4418

Combined classification RNA Polymerase II 18S ribosomal RNA CYP19 CYP17 ESR1 ESR2

— Others 0.0012 0.0049 − 0.0058 − 0.0015 0.0010 0.0022

0.7890 0.2883 0.4550 0.7399 0.6559 0.4639

0.0043 0.0049 0.0077 0.0044 0.0022 0.0030

in our cohort. Compared with that data, the median value of five of the congeners in our cohort was at least one and one-half times the 50% percentile measurement (PCB IUPAC #138, #153, #170, #180, and #196 + 203), but none was twice as high as in the national dataset, making generalizability of results, especially in premenopausal women, reasonable. Another strength is the use of a quantitative method to measure gene expression, rather than obtaining estimates of activity. This indicates the effect of PCBs as being targeted to changes at the transcriptional level rather than a secondary effect on protein activity.

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4.4. Study limitations

Acknowledgments

In previous work, we demonstrated that current adult levels of total PCBs in this same population were modestly correlated (rSpearman = 0.29, p = 0.0002 n = 119) with maternal serum total PCBs measured as close to the pregnancy as possible and extrapolated to estimate prenatal exposure levels. Unfortunately, we do not have data on PCB congeners in the maternal population that we can apply to this study because at the time that PCB blood levels were measured in the parents, laboratory technology was available only to measure PCB levels against an Aroclor standard, and not individual congeners. However, the modest correlation between prenatal and current PCB levels demonstrated previously suggest that no more than approximately 10% of variance of the current findings would be accounted for by prenatal exposures. We explored whether total prenatal PCB exposure was correlated with the various classification schemes reported here and found wide variations, with no correlation higher than rSpearman =0.32. Importantly however, those classified of mixed type in the combined classification had the highest correlation (rSpearman =0.32, p=0.0003), whereas those in the 3-MC classification were not significant. The positive correlation between prenatal PCB exposures in the mixed type grouping in the combined classification suggest that the congeners in this group may have a longer half-life, whereas other congeners may result from more recent exposure. Another limitation is that the Moysich phenobarbital-type inducer group results using Ribosomal Polymerase II as the housekeeping gene should be interpreted with caution since this congener group may have had an influence on the expression of this housekeeping gene. Alternatively, the results could be a result of random error, which often occurs when multiple measures in a dataset are being examined. Our population was restricted to women, most of whom were premenopausal. This will compromise the generalizability of the results to other populations. In addition, the phase of the menstrual cycle has to be considered. Although it would be considered strength that blood was collected in the follicular phase of the menstrual cycle in all menstruating women, we do not know how GE may be affected by other menstrual cycle phases. Another limitation is that we measured GE in circulating white cells, which may not reflect organ-specific effects that may be mechanistic in disease etiology. The obvious reason for this is the accessibility of obtaining specimens in humans, but we acknowledge that as this field advances, measurement of tissue-specific GE will become necessary. In addition, circulating blood leukocytes interact with virtually every organ and tissue. Because a majority of genes encoded in the human genome have detectable gene expression in leukocytes, these cells are considered to function as sentinels (Liew et al., 2006)

This research was supported by a grant from the Agency for Toxic Substances and Disease Registry (R01 TS000069).

5. Conclusions In this cohort, the GE of CYP19 and ESR2 is associated with exposure to dioxin-like, potentially anti-estrogenic, immunotoxic PCB congeners. These findings are both counter-intuitive and intriguing. Rather than exhibiting anti-estrogenic effects alone, they suggest that these congeners up-regulate the major enzyme involved in estrogen synthesis and tend to confirm previous findings of links between AhR and ER signaling pathways. Replication of these findings, expansion of the number of genes examined in the sex steroid pathway, exploration of whether mixtures of other environmental chemicals influence these results, and subsequent association with health outcomes in a larger cohort are priorities for future work. Conflict of interest The authors declare no competing interests.

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