Lipophilic Environmental Chemicals and Endometriosis
Lipophilic Environmental Chemicals and Endometriosis
A matched cohort design was used to estimate endometriosis in two cohorts. The operative cohort comprised menstruating women 18–44 years of age scheduled for a laparoscopy or laparotomy irrespective of indication at one of 14 participating hospital surgical centers located in the Salt Lake City, Utah, or San Francisco, California, areas between 2007 and 2009. Women were eligible to participate if they had no history of surgically visualized endometriosis (to reduce the likelihood of prevalent disease), no injectable hormone treatment within the past 2 years, not breast-feeding for ≥ 6 months, and no history of cancer. The operative cohort was matched to a population cohort on age and residence within a 50-mile geographic catchment area of the participating surgical centers. The sampling framework for the California site was sampled from the white pages of the telephone directory for the targeted geographic area by Genesys Sampling Systems (Horsham, PA), and the Utah site relied on the Utah Population Database (Huntsman Cancer Institute 2012), which represents 94% of state residents. Women were eligible if they were currently menstruating and did not have a history of visualized endometriosis. The population recruitment strategy located women "at risk" for endometriosis (menstruating) and its diagnosis at one of the participating hospitals for the operative cohort (residence). In both cohorts, a letter of introduction preceded telephone screening and eventual recruitment. Statistical power was determined a priori as requiring 450 women in the operative cohort based on a reported endometriosis prevalence of 38% and a 20% relative difference in mean serum PCBs concentrations by endometriosis status (Louis et al. 2005) at the time the study was designed. Given the absence of previous population cohort studies, its size was based upon published studies that reported differences in POPs by endometriosis status.
In-person baseline interviews were conducted with women, followed by anthropometric assessment using standardized portable stadiometers and electronic scales (Lohman et al. 1988) approximately 2 months before surgery, or 2 months before magnetic resonance imaging (MRI) for the population cohort. For women in the operative cohort, surgeons completed standardized data collection instruments on operative findings, diagnoses, and staging of endometriosis using the revised American Society for Reproductive Medicine classification (ASRM 1997). An algorithm was used to automatically calculate endometriosis severity ranging from minimal to severe (stage 1–4) to avoid bidirectional (over- and understaging severity) errors associated with clinical reporting (Buchweitz et al. 2005; Buck Louis et al. 2011; Weijenborg et al. 2007).
In both cohorts, nonfasting blood (~ 24 mL) and urine (~ 120 mL) specimens were obtained for all women using collection kits determined to be free of POPs. For logistical reasons, we did not require fasting blood specimens. Blank containers were periodically sent to the analytical laboratory to check for contamination; none was found. Depending upon availability and clinical judgment about patient safety, 1–5 g omental fat was obtained from women in the operative cohort by surgeons. At the Utah site, Harmonic® ACE 36P shears and scalpel blades (donated by Ethicon Endo-Surgery, LLC, Cincinnati, OH) were used; primarily, bipolar electrocautery and scissors were used at the California site. Fat specimens were placed into Wheaton brown glass bottles that were cleaned with acetone and hexane before use. Epiploica appendiceal fat was obtained in lieu of omental fat for four women, two from each study site.
Institutional review board approval was obtained from all participating study sites. The women provided full consent before any data were collected, and all were remunerated for their time and travel. A more complete description of the study is provided elsewhere (Buck Louis et al. 2011).
Endometriosis is defined in the operative cohort using the gold standard of visualization (ASRM 2006; Kennedy et al. 2005) and further qualified by histologic confirmation (endometrial glands or stroma and/or hemosiderin-laden macrophages). In the population cohort, endometriosis diagnosed by MRI was mainly ovarian endometriomas.
Definitions for relevant covariates were as follows. Body mass index (BMI) was estimated by dividing measured weight in kilograms by height in meters squared and categorized as underweight (< 18.5), normal (18.5–24.9), overweight (25.0–29.9), obese class I (30.0–34.9), and obese class II+ (≥ 35.0) (National Heart, Lung, and Blood Institute 1998). Income was estimated using Department of Health and Human Services Poverty Guidelines (2007) for the 48 contiguous states and the District of Columbia. Breast-feeding history was derived as a conditional variable based upon parity (nulliparous/parous) and categorized as no prior birth, prior birth but no breast-feeding, and prior birth with breast-feeding.
One laboratory processed and quantified all compounds using gas chromatography (GC)/mass spectrometry (MS) with GC/electron capture detector and GC/high-resolution MS (HRMS) (Johnson-Restrepo et al. 2005, 2007; Sjödin et al. 2004). Serum and fat samples were analyzed for three chemical classes of lipophilic persistent pollutants: a) OCPs [hexachlorobenzene (HCB), hexachlorocyclohexane (HCH) and its isomers γ-HCH and β-HCH, oxychlordane, cis- and trans-nonachlor, cis- and trans-chlordane, and p,p′-dichlorodiphenyltrichloroethane (p,p′-DDT) and its metabolites p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE) and o,p′-DDT]; b) polybrominated diphenyl ether (PBDE) congeners 47, 99, 100, 153, 154, and 209; and c) PCB congeners 18, 28, 44, 49, 52, 66, 74, 87, 99, 101, 114, 118, 128, 138, 146, 149, 151, 153, 156, 157, 167, 170, 172, 177, 178, 180, 183, 187, 189, 194, 195, 196, 201, 206, and 209. Briefly, serum samples were fortified with isotopically labeled internal standards along with the addition of formic acid (80%) and water for denaturation and dilution of samples using a Gilson 215 liquid hander (Gilson Inc., Middleton, WI).
The samples were extracted by solid-phase extraction (SPE) using a Rapid Trace (Caliper Life Science, Hopkinton, MA) modular SPE system. Removal of coextracted lipids was performed on a silica: silica/sulfuric acid column using Rapid Trace equipment for automation. Final analytical determination of the target analytes was performed by GC/isotope-dilution HRMS employing a Thermo Finnigan MAT95XP (Thermo Fisher Scientific, Bremen, Germany). External calibration standards were analyzed with every set of samples, and recoveries of internal standards were checked against external calibration standards. Three blanks were included in every batch comprising 30 samples. Fat samples were extracted by the Soxhlet extraction procedure, and further details of the methods are given elsewhere (Johnson-Restrepo et al. 2005, 2007).
All concentrations are reported in nanograms per gram of fat or serum after subtracting background. All machine-observed concentrations were used without any substitution of concentrations below the limits of detection (LODs) to avoid introducing biases (Guo et al. 2010; Richardson and Ciampi 2003; Schisterman et al. 2006). Serum lipids were analyzed with enzymatic methods (Akins et al. 1989). Total serum lipids (TL) were estimated as
TL = (2.27 × TC) + TG + 62.3 mg/dL,
where TC denotes total cholesterol and TG denotes triglycerides, and were reported in milligrams per deciliter (Philips et al. 1989). Serum cotinine was quantified using high-performance liquid chromatography/tandem MS using an isotope dilution method and external standard calibration plots (Bernert et al. 2009). Serum cotinine was further categorized as noted above to help identify passive and active exposure using established cut-points (Wall et al. 1988).
The distributions of all chemicals were inspected and summarized by geometric means and 95% confidence intervals (CIs) and percentiles (median, 75th, 95th). Comparisons of select variables by cohort and endometriosis status were made to assess a priori defined select variables (i.e., age, BMI, serum cotinine, and lipids) for the analytic phase. Statistical significance (p < 0.05) was determined using the chi-square statistic for categorical data and Student's t-test or Wilcoxon nonparametric test for continuous data.
Logistic regression was used to estimate the unadjusted odds ratio (OR) and corresponding 95% CI for each chemical by biological medium and cohort. CIs that excluded 1 were considered significant. All chemical concentrations were first log (X + 1)-transformed to achieve normality and then rescaled by their standard deviations so that ORs could be interpreted per 1-SD change in the log-transformed chemical concentration. All analyses used wet-weight concentrations. Adjusted models included age (in years), breast-feeding history (conditional categorical), BMI (continuous), and cotinine (continuous) (Hediger et al. 2005; Nelson et al. 2006; Sasamoto et al. 2006; Zeyneloglu et al. 1997). Serum lipids (milligrams per deciliter) were also entered into serum models to minimize potential biases associated with automatic lipid adjustment (Schisterman et al. 2005). We also adjusted for breast-feeding conditional on parity, given its uncertain relation with endometriosis. In addition, we conducted a number of sensitivity analyses to assess the consistency of findings by removing parity and breast-feeding from models, varying the diagnostic criteria to require both histologic and visualized disease, restricting diagnosis to endometriosis stages 3–4, and restricting the comparison group to women with a postoperative diagnosis of a normal pelvis in the operative cohort. All analyses were conducted using SAS software (version 9.2; SAS Institute Inc., Cary, NC).
Materials and Methods
Study Design and Populations
A matched cohort design was used to estimate endometriosis in two cohorts. The operative cohort comprised menstruating women 18–44 years of age scheduled for a laparoscopy or laparotomy irrespective of indication at one of 14 participating hospital surgical centers located in the Salt Lake City, Utah, or San Francisco, California, areas between 2007 and 2009. Women were eligible to participate if they had no history of surgically visualized endometriosis (to reduce the likelihood of prevalent disease), no injectable hormone treatment within the past 2 years, not breast-feeding for ≥ 6 months, and no history of cancer. The operative cohort was matched to a population cohort on age and residence within a 50-mile geographic catchment area of the participating surgical centers. The sampling framework for the California site was sampled from the white pages of the telephone directory for the targeted geographic area by Genesys Sampling Systems (Horsham, PA), and the Utah site relied on the Utah Population Database (Huntsman Cancer Institute 2012), which represents 94% of state residents. Women were eligible if they were currently menstruating and did not have a history of visualized endometriosis. The population recruitment strategy located women "at risk" for endometriosis (menstruating) and its diagnosis at one of the participating hospitals for the operative cohort (residence). In both cohorts, a letter of introduction preceded telephone screening and eventual recruitment. Statistical power was determined a priori as requiring 450 women in the operative cohort based on a reported endometriosis prevalence of 38% and a 20% relative difference in mean serum PCBs concentrations by endometriosis status (Louis et al. 2005) at the time the study was designed. Given the absence of previous population cohort studies, its size was based upon published studies that reported differences in POPs by endometriosis status.
Data Collection
In-person baseline interviews were conducted with women, followed by anthropometric assessment using standardized portable stadiometers and electronic scales (Lohman et al. 1988) approximately 2 months before surgery, or 2 months before magnetic resonance imaging (MRI) for the population cohort. For women in the operative cohort, surgeons completed standardized data collection instruments on operative findings, diagnoses, and staging of endometriosis using the revised American Society for Reproductive Medicine classification (ASRM 1997). An algorithm was used to automatically calculate endometriosis severity ranging from minimal to severe (stage 1–4) to avoid bidirectional (over- and understaging severity) errors associated with clinical reporting (Buchweitz et al. 2005; Buck Louis et al. 2011; Weijenborg et al. 2007).
In both cohorts, nonfasting blood (~ 24 mL) and urine (~ 120 mL) specimens were obtained for all women using collection kits determined to be free of POPs. For logistical reasons, we did not require fasting blood specimens. Blank containers were periodically sent to the analytical laboratory to check for contamination; none was found. Depending upon availability and clinical judgment about patient safety, 1–5 g omental fat was obtained from women in the operative cohort by surgeons. At the Utah site, Harmonic® ACE 36P shears and scalpel blades (donated by Ethicon Endo-Surgery, LLC, Cincinnati, OH) were used; primarily, bipolar electrocautery and scissors were used at the California site. Fat specimens were placed into Wheaton brown glass bottles that were cleaned with acetone and hexane before use. Epiploica appendiceal fat was obtained in lieu of omental fat for four women, two from each study site.
Institutional review board approval was obtained from all participating study sites. The women provided full consent before any data were collected, and all were remunerated for their time and travel. A more complete description of the study is provided elsewhere (Buck Louis et al. 2011).
Operational Definitions
Endometriosis is defined in the operative cohort using the gold standard of visualization (ASRM 2006; Kennedy et al. 2005) and further qualified by histologic confirmation (endometrial glands or stroma and/or hemosiderin-laden macrophages). In the population cohort, endometriosis diagnosed by MRI was mainly ovarian endometriomas.
Definitions for relevant covariates were as follows. Body mass index (BMI) was estimated by dividing measured weight in kilograms by height in meters squared and categorized as underweight (< 18.5), normal (18.5–24.9), overweight (25.0–29.9), obese class I (30.0–34.9), and obese class II+ (≥ 35.0) (National Heart, Lung, and Blood Institute 1998). Income was estimated using Department of Health and Human Services Poverty Guidelines (2007) for the 48 contiguous states and the District of Columbia. Breast-feeding history was derived as a conditional variable based upon parity (nulliparous/parous) and categorized as no prior birth, prior birth but no breast-feeding, and prior birth with breast-feeding.
Toxicologic Analysis
One laboratory processed and quantified all compounds using gas chromatography (GC)/mass spectrometry (MS) with GC/electron capture detector and GC/high-resolution MS (HRMS) (Johnson-Restrepo et al. 2005, 2007; Sjödin et al. 2004). Serum and fat samples were analyzed for three chemical classes of lipophilic persistent pollutants: a) OCPs [hexachlorobenzene (HCB), hexachlorocyclohexane (HCH) and its isomers γ-HCH and β-HCH, oxychlordane, cis- and trans-nonachlor, cis- and trans-chlordane, and p,p′-dichlorodiphenyltrichloroethane (p,p′-DDT) and its metabolites p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE) and o,p′-DDT]; b) polybrominated diphenyl ether (PBDE) congeners 47, 99, 100, 153, 154, and 209; and c) PCB congeners 18, 28, 44, 49, 52, 66, 74, 87, 99, 101, 114, 118, 128, 138, 146, 149, 151, 153, 156, 157, 167, 170, 172, 177, 178, 180, 183, 187, 189, 194, 195, 196, 201, 206, and 209. Briefly, serum samples were fortified with isotopically labeled internal standards along with the addition of formic acid (80%) and water for denaturation and dilution of samples using a Gilson 215 liquid hander (Gilson Inc., Middleton, WI).
The samples were extracted by solid-phase extraction (SPE) using a Rapid Trace (Caliper Life Science, Hopkinton, MA) modular SPE system. Removal of coextracted lipids was performed on a silica: silica/sulfuric acid column using Rapid Trace equipment for automation. Final analytical determination of the target analytes was performed by GC/isotope-dilution HRMS employing a Thermo Finnigan MAT95XP (Thermo Fisher Scientific, Bremen, Germany). External calibration standards were analyzed with every set of samples, and recoveries of internal standards were checked against external calibration standards. Three blanks were included in every batch comprising 30 samples. Fat samples were extracted by the Soxhlet extraction procedure, and further details of the methods are given elsewhere (Johnson-Restrepo et al. 2005, 2007).
All concentrations are reported in nanograms per gram of fat or serum after subtracting background. All machine-observed concentrations were used without any substitution of concentrations below the limits of detection (LODs) to avoid introducing biases (Guo et al. 2010; Richardson and Ciampi 2003; Schisterman et al. 2006). Serum lipids were analyzed with enzymatic methods (Akins et al. 1989). Total serum lipids (TL) were estimated as
TL = (2.27 × TC) + TG + 62.3 mg/dL,
where TC denotes total cholesterol and TG denotes triglycerides, and were reported in milligrams per deciliter (Philips et al. 1989). Serum cotinine was quantified using high-performance liquid chromatography/tandem MS using an isotope dilution method and external standard calibration plots (Bernert et al. 2009). Serum cotinine was further categorized as noted above to help identify passive and active exposure using established cut-points (Wall et al. 1988).
Statistical Analysis
The distributions of all chemicals were inspected and summarized by geometric means and 95% confidence intervals (CIs) and percentiles (median, 75th, 95th). Comparisons of select variables by cohort and endometriosis status were made to assess a priori defined select variables (i.e., age, BMI, serum cotinine, and lipids) for the analytic phase. Statistical significance (p < 0.05) was determined using the chi-square statistic for categorical data and Student's t-test or Wilcoxon nonparametric test for continuous data.
Logistic regression was used to estimate the unadjusted odds ratio (OR) and corresponding 95% CI for each chemical by biological medium and cohort. CIs that excluded 1 were considered significant. All chemical concentrations were first log (X + 1)-transformed to achieve normality and then rescaled by their standard deviations so that ORs could be interpreted per 1-SD change in the log-transformed chemical concentration. All analyses used wet-weight concentrations. Adjusted models included age (in years), breast-feeding history (conditional categorical), BMI (continuous), and cotinine (continuous) (Hediger et al. 2005; Nelson et al. 2006; Sasamoto et al. 2006; Zeyneloglu et al. 1997). Serum lipids (milligrams per deciliter) were also entered into serum models to minimize potential biases associated with automatic lipid adjustment (Schisterman et al. 2005). We also adjusted for breast-feeding conditional on parity, given its uncertain relation with endometriosis. In addition, we conducted a number of sensitivity analyses to assess the consistency of findings by removing parity and breast-feeding from models, varying the diagnostic criteria to require both histologic and visualized disease, restricting diagnosis to endometriosis stages 3–4, and restricting the comparison group to women with a postoperative diagnosis of a normal pelvis in the operative cohort. All analyses were conducted using SAS software (version 9.2; SAS Institute Inc., Cary, NC).
