Study population and amniotic fluid samples. We used amniotic fluid samples from a Danish biobank maintained at the State Serum Institute in Copenhagen. The biobank holds samples from a pregnancy screening registry including both amniotic fluid and maternal serum samples from > 100,000 pregnancies covering the period 1979 through 2004 (amniotic fluid samples 1980–1996). The amniotic fluid samples were centrifuged before routine diagnostic analyses and the supernatants were kept frozen at –20°C until the present analyses were carried out. The samples were from Sealand (Copenhagen hospitals and Hillerød Hospital) and from Southern Jutland (Sønderborg and Kolding Hospitals). The main indication for amniocentesis was age ≥ 35 years, but some samples were from women with increased risk of severe malformations or Down syndrome based on results from maternal serum analyses.
Each mother’s personal identification number (unique to each Danish citizen) was recorded in the pregnancy screening registry and also identified her amniotic fluid sample. We used the unique identifiers of all women in the pregnancy screening registry to obtain obstetric data on all their pregnancies from the Danish Medical Birth Registry (Knudsen and Olsen 1998
), including gestational age at birth, singleton or multiple birth, maternal parity, and birth weight and Apgar score of the infant. In addition, we used the unique identifiers in the Danish Civil Registration System to identify each mother’s children (Pedersen et al. 2006
). We included only live-born boys because this study was part of a larger study on male urogenital anomalies. To verify that the amniotic fluid sample and the identified boy originated from the same pregnancy, we selected only those where the amniocentesis had been performed between 10 and 30 weeks from the estimated date of conception, defined by subtracting the gestational age at birth from the date of birth. We then followed the identified boys in the Danish National Patient Registry until November 2008 to obtain records of urogenital anomalies and other congenital malformations, including chromosomal abnormalities [International Classification of Diseases, 8th Revision
(ICD-8; World Health Organization 1969
), codes 74000–75999; ICD-10 (10th Revision
; World Health Organization 1993
) codes Q00–Q99] (Andersen et al. 1999
). We selected a random sample for this study among all live-born singleton boys born to women registered in the pregnancy-screening registry and with complete obstetric data.
The gestational age at birth was determined by last menstrual period and corrected by ultrasound according to local guidelines if necessary. Obstetric ultrasound became increasingly available in Denmark during the study period and was performed on approximately 93% of all pregnant women by 1995 (Jørgensen 1999
). We calculated gestational week of amniocentesis as the distance between the estimated date of conception (defined above) and the date of amniocentesis.
The Danish Regional Ethics Committee, the Danish National Board of Health, and the Danish Data Protection Agency approved the study. The use of the biobank for research purposes has been approved, and additional informed consent from the study subjects for this specific project was neither recommended nor required.
We assayed the di(2-ethylhexyl) phthalate (DEHP) metabolites mono(2-ethyl-5-hydroxylhexyl) phthalate (5OH-MEHP), mono(2-ethyl-5-oxohexyl) phthalate (5oxo-MEHP), and mono(2-ethyl-5-carboxypentyl) phthalate (5cx-MEPP) and the diisononyl phthalate (DiNP) metabolites mono(4-methyl-7-hydroxyoctyl) phthalate (7OH-MMeOP), mono(4-methyl-7-oxooctyl) phthalate (7oxo-MMeOP), and mono(4-methyl-7-carboxyheptyl) phthalate (7cx-MMeHP), as well as PFOS and cotinine, in the amniotic fluid samples during the summer and fall of 2010. We detected 5cx-MEPP, 7cx-MMeHP, PFOS, and cotinine, and the method had good reproducibility as determined from duplicate samples analyzed at different days. Coefficients of variation were between 9% and 16%, and we achieved rather low limits of detection (LOD), which were determined as the concentrations corresponding to three times the standard deviation of the responses in chemical blanks [for more details, see Supplemental Material, Table S1
)]. We monitored the quality by analyzing chemical blanks and in-house quality-control samples in all batches.
We added 10 μL 1 M ammonia acetate and 10 μL glucoronidase from Escherichia coli to aliquots of 100 μL amniotic fluid. After mixing, we incubated the samples at 37°C for 90 min. We prepared standards from amniotic fluid added with known amounts of phthalate metabolites, PFOS, and cotinine in 25 μL of a 50:50 solution of water and acetonitrile. We added 25 μL of the same solution but without the compounds to the samples, and then added 25-μL aliquots of a 50:50 water:acetonitrile solution of 13C- and 2H-labeled internal standards for all analyzed compounds. We precipitated the proteins by adding 150 μL acetonitrile and vigorously shaking for 30 min, and afterward we centrifuged the samples and transferred them to autosampler vials.
We analyzed the samples using a liquid chromatograph (LC; model UFLCXR, Shimadzu Corp., Kyoto, Japan). In the analysis of the phthalates, we injected aliquots of 5 μL on a C18 column (4 μm, 2.1 mm inner diameter × 50 mm GENISIS; Grace Vydac, Hesperia, CA, USA). The mobile phases consisted of 0.08% formic acid in water and acetonitrile. The separation started at 20% acetonitrile, followed by a linear gradient of acetonitrile to 75% in 3 min. We washed the column by 95% acetonitrile and then equilibrated in 20% acetonitrile during 2 min. In the analysis of PFOS, we injected aliquots of 3 μL on a C18 column (4 μm, 2.1 mm inner diameter × 50 mm GENISIS). The mobile phases consisted of 0.1% ammonia in water and acetonitrile. The separation started with a 5-min isocratic step at 30% acetonitrile, followed by a linear gradient of acetonitrile to 95% in 2 min. We then equilibrated the column in 30% acetonitrile for 2 min. In the analysis of cotinine, we injected aliquots of 3 μL on a C18 Hypersil GOLD column (5 μm, 3 mm inner diameter × 150 mm; Thermo Scientific, Waltham, MA, USA). The mobile phases consisted of 0.1% ammonia in water and acetonitrile. The separation started with a 1-min isocratic step at 25% acetonitrile, followed by a linear gradient of acetonitrile to 95% for 3 min. We then equilibrated the column in 25% acetonitrile for 2 min. The LC was connected to a hybrid triple quadrupole linear ion trap tandem mass spectrometer (LC/MS/MS) equipped with a turbo ion spray source (QTRAP 5500; AB Sciex, Foster City, CA, USA). For technical parameters and for sample chromatograms, see Supplemental Material, Table S2 and Figures S1, S2
Recent participation in interlaboratory urine sample control programs of several phthalate metabolites, including 5cx-MEPP and 7cx-MMeHP, and of cotinine yielded results good enough for the laboratory to become a reference laboratory in a large European biomonitoring program [Consortium to Perform Human Biomonitoring on a European Scale (COPHES) 2012]. Furthermore, the laboratory’s analyses of PFOS in serum and of 5cx-MEPP and cotinine in urine are part of the Round Robin intercomparison program (H. Drexler, Institute and Out-Patient Clinic for Occupational, Social and Environmental Medicine, University of Erlangen-Nuremberg, Germany), with results within the tolerance limits.
Statistical analysis. We compared pregnancy characteristics by amniotic fluid sample availability to evaluate potential selection bias. We tabulated proportions or means and used Pearson’s chi-square test for categorical variables and the t-test for continuous variables when comparing the groups.
Less than 5% of the values from the chemical assays of the four detected environmental pollutants were below the LOD, and they were imputed with a random value between LOD and LOD/2. For each pollutant we present the LOD, the proportion of samples above LOD and the 10th, 25th, 50th, 75th, and 100th percentiles.
We estimated potential associations of calendar year, gestational age, and maternal age and parity at amniocentesis with each pollutant in generalized linear regression models with squared terms of the numerical explanatory variables to estimate deviations from linearity. We transformed the environmental pollutant measures by the natural logarithm (ln) to normalize the distribution of residuals, and we consequently exponentiated the differences estimated on the ln scale to obtain ratios of the medians. We present these ratios as crude and adjusted percent change per unit of the explanatory variable with 95% confidence intervals (CIs). In addition, we present associations with the numerical explanatory variables as scatter plots with unadjusted linear regression lines. We made mutual adjustments for calendar year of amniocentesis (1980–1984, 1985–1990, 1991–1996), gestational age at amniocentesis (< 15, 15–17, ≥ 17 weeks), maternal age at amniocentesis (< 30, 30–34, ≥ 35 years), maternal smoking estimated by cotinine levels [“nonsmoker” < 25, “passive smoker” 25–85, “active smoker” ≥ 85 ng/mL amniotic fluid (Jauniaux et al. 1999
)], and maternal parity (0, 1, ≥ 2 prior births). We estimated correlation coefficients between the ln-transformed environmental pollutants with p
-values from Spearman rank correlations. All p
-values were estimated by two-tailed tests, and we considered an α-level of 0.05 statistically significant. Statistical analyses were performed using STATA software (version 11; StataCorp, College Station, TX, USA).