effects of complex organohalogen contaminant mixtures on thyroid homeostasis in hooded seal...
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Chemosphere 92 (2013) 828–842
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Effects of complex organohalogen contaminant mixtures on thyroidhomeostasis in hooded seal (Cystophora cristata) mother–pup pairs
0045-6535/$ - see front matter � 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.chemosphere.2013.04.036
⇑ Corresponding author. Present address: University of Oslo, Department ofBiosciences, 0316 Oslo, Norway. Tel.: +47 22 85 56 00; fax: +47 22 85 47 26.
E-mail addresses: [email protected], [email protected] (G.D. Villanger).1 Present address: Department of Neuroscience, Norwegian University of Science
and Technology, 7491 Trondheim, Norway.
Gro D. Villanger a,⇑, Kristin M. Gabrielsen a, Kit M. Kovacs b, Christian Lydersen b, Elisabeth Lie c,Mahin Karimi c, Eugen G. Sørmo a,1, Bjørn M. Jenssen a
a Department of Biology, Norwegian University of Science and Technology, N-7491 Trondheim, Norwayb Norwegian Polar Institute, Fram Centre, N-9296 Tromsø, Norwayc Norwegian School of Veterinary Science, Department for Food Safety and Infection Biology, P.O. Box 8146 Dep., N-0033 Oslo, Norway
h i g h l i g h t s
� Organohalogen contaminants in nursing hooded seal mothers and pups were reported.� Multivariate associations between thyroid hormones and contaminants were shown.� Specific contaminants appear to affect thyroid homeostasis in mothers and pups.� Similar thyroid responses may reflect linked mother–pup exposure or thyroid effects.� Some contaminants may have higher thyroid disruptive potency in pups (e.g. OH-PCBs).
a r t i c l e i n f o
Article history:Received 26 September 2012Received in revised form 7 April 2013Accepted 8 April 2013Available online 29 May 2013
Keywords:ContaminantsEndocrine disruptionMaternal transferNeonatesPinnipedsThyroid hormones
a b s t r a c t
Many lipid-soluble and phenolic compounds present in the complex mixture of orgaohalogen contami-nants (OHCs) that arctic wildlife is exposed to have the ability to interfere with the thyroid hormone(TH) system. The aim of this study was to identify compounds that might interfere with thyroid homeo-stasis in 14 nursing hooded seal (Cystophora cristata) mothers and their pups (1–4 d old) sampled in theWest Ice in March 2008. Multivariate modelling was used to assess the potential effects of measuredplasma levels of OHCs on circulating TH levels of the measured free (F) and total (T) levels of triidothyrine(T3) and thyroxine (T4). Biological factors were important in all models (e.g. age and sex). In both moth-ers and pups, TT3:FT3 ratios were associated with a- and b-hexachlorocyclohexane (HCH), ortho-PCBs,chlordanes and DDTs. The similarities between the modelled TT3:FT3 responses to OHC levels in hoodedseal mothers and pups most probably reflects similar exposure patterns, but could also indicate intercon-nected TH responses. There were some differences in the modelled TH responses of mothers and pups.Most importantly, the negative relationships between many OH-PCBs (particularly 3’-OH-CB138) andTT3:FT3 ratio and the positive relationships between TT4:FT4 ratios and polybrominated diphenyl ether[PBDE]-99, -100 and 4-OH-CB107 in pups, which was not found in mothers. Although statistical associ-ations are not evidence per se of biological cause–effect relationships, the results suggest that thyroidhomeostasis is affected in hooded seals, and that the inclusion of the fullest possible OHC mixture isimportant when assessing TH related effects in wildlife.
� 2013 Elsevier Ltd. All rights reserved.
1. Introduction
Maternal transfer of environmental contaminants via the pla-centa or milk in mammals can result in young neonates havinghigh levels of exposure (Polischuk et al., 1995; Wolkers et al.,
2006; Polder et al., 2008; Needham et al., 2011). This is of greatconcern for both wildlife and humans since developing mammalshave reduced ability to metabolise and excrete xenobiotics andare generally considered to be more susceptible to toxic effectscompared to adults (Milsap and Jusko, 1994; Grandjean and Landr-igan, 2006; Wolkers et al., 2009). Many environmental contami-nants have been shown to have endocrine disruptive capabilitiesand pre- and postnatal contaminant exposure might differentiallyaffect endocrine regulation during early developmental stages. Pre-and postnatal exposure to endocrine disruptors can also result inserious fitness-related impairments that become evident during
G.D. Villanger et al. / Chemosphere 92 (2013) 828–842 829
adolescence or adulthood (Colborn et al., 1993; Darnerud, 2008;Nichols et al., 2011).
The thyroid hormone (TH) system is an important endocrinetarget for many organohalogen contaminants (OHCs). These in-clude e.g. polychlorinated biphenyls (PCBs), organochlorine pesti-cides (OCPs, e.g. hexachlorobenzene [HCB]), polybrominateddiphenyl ethers (PBDEs) and their phenolic metabolites, whichare formed during biotransformation mediated by cytochromeP450 (CYP) enzymes (e.g. hydroxylated [OH]-PCBs, pentachloro-phenol [PCP] and OH-PBDEs) (Brouwer et al., 1998; Letcher et al.,2000; Boas et al., 2006; Jugan et al., 2010).
Tetraiodothyronine (T4, thyroxine) is produced and released bythe thyroid gland in much larger quantities than triiodothyronine(T3) and deiodination of T4 in extra-thyroidal tissues is the mainsupplier of the biologically more active hormone, T3 (McNabb,1992; Hadley, 1996). THs are required in vertebrates to regulatea wide range of physiological processes related to growth, energymetabolism, temperature regulation and general physiologicalhomeostasis (McNabb, 1992; Zoeller et al., 2007). Thyroid hor-mones are also essential for foetal and postnatal development ofthe brain and nervous system, and are also important for control-ling sexual development (Cooke et al., 2004; Santisteban andBernal, 2005; Ahmed et al., 2008). Maternal and foetal/neonataldisruption of TH balance can cause permanent developmental neu-rocognitive and motor deficits, alter behaviour and disturb sexualdevelopment in offspring, as shown in experimental animals andindicated in human studies (Brouwer et al., 1998; Pop et al.,1999; Porterfield, 2000; Zoeller et al., 2007; Darras, 2008; Juganet al., 2010).
OHCs and their metabolites (e.g. OH-PCBs, OH-PBDEs) can affectmany target points in the hypothalamic–pituitary–thyroid (HPT)axis, sometimes as a consequence of their structural resemblanceto natural hormones. However, the possible mechanisms of disrup-tion by OHCs and metabolites are multiple and may involve inter-ference with the thyroid gland’s production and release ofhormones, negative feed-back regulation, binding to TH transportproteins in blood (e.g. transthyretin [TTR], thyroxine binding glob-ulin [TBG] and albumin) and enzymatic metabolism and excretionof hormones. Also, some OHCs can bind to the thyroid hormonereceptor (TR) and inhibit or facilitate TR-mediated gene expressionand thus interfere with the many biological effects of THs (Lanset al., 1993; Brouwer et al., 1998; Howdeshell, 2002; Zoeller,2005; Boas et al., 2006; Hamers et al., 2006; Langer et al., 2007;Pearce and Braverman, 2009).
The ice-breeding hooded seal (Cystophora cristata) is a goodmammalian-model for studying trans-generational effects ofmaternally transferred environmental contaminants. This pinnipedspecies feeds high in the arctic marine food chain and accumulateshigh levels of lipid-soluble OHCs in its blubber lipid-reservoirs,which are readily transferred from mother to pup via the placentaand the extremely lipid-rich milk (>60%) that the pup consumesduring an intensive 3–4 day nursing period (Bowen et al., 1985;Kovacs and Lavigne, 1992; Espeland et al., 1997; Lydersen et al.,1997; Lydersen and Kovacs, 1999; Wolkers et al., 2006). This spe-cies also has the enzymatic ability to biotransform contaminants(Wolkers et al., 2009); the recently reported OH-PCBs in plasmaof hooded seals are thought to originate from endogenous bio-transformation of PCBs (Gabrielsen et al., 2011).
Studies of wild seal populations and exposure studies with sealsgiven naturally contaminated fish-diets in captivity have demon-strated the potential for TH disruption due to OHC exposure (e.g.Brouwer et al., 1989; Jenssen et al., 1995; Hall et al., 2003; Debieret al., 2005; Sørmo et al., 2005; Routti et al., 2010). These studieshave generally focused on the associative relationships betweenTH levels and total levels of OHC groups measured in blood orblubber. However, it is increasingly acknowledged that environ-
mental OHC mixtures may act on the HPT axis via additive or evensynergistic effects among the individual contaminants (e.g. Hall-gren and Darnerud, 2002; Crofton et al., 2005; Villanger et al.,2011a). In seals and other wildlife species there is a lack of knowl-edge regarding the effects of individual compounds in OHC mix-tures and their potential combined effects. There is a particularneed for more knowledge regarding early-stage thyroid disruptiveeffects through maternally transferred contaminants in wildlifespecies. In a recent study of the same hooded seal mother–puppairs investigated herein, some OH-PCBs appeared to be negativelyassociated with plasma TH ratios of pups but not in their mothers(Gabrielsen et al., 2011). Thus, the thyroid-related effects of OH-PCBs could be dependent on stage of development.
The aim of the present study was to examine the composition ofthe complex OHC mixture (including previously reported OH-PCBs) and identify the most potent contaminants influencing circu-lating thyroid hormone levels or ratios in hooded seal mothers andtheir pups. This study builds upon that of Gabrielsen et al. (2011)where principal component analysis (PCA) was used to demon-strate associative relationships between OH-PCBs, thyroid hor-mones and biological factors. Only a few of the strongestassociations identified by PCA were confirmed by subsequent uni-variate tests (Gabrielsen et al., 2011). Recent multivariate regres-sion modelling of TH levels of polar bears (Ursus maritimus) andwhite whales (Delphinapterus leucas) showed that they were asso-ciated with levels of lipid-soluble OHCs as well as biological factors(Villanger et al., 2011a,b). The models also identified the specificcontaminants that were most important in explaining TH levels.In the present study, plasma from hooded seal mothers and pupswas analysed for OCPs, PCBs, PBDEs and other brominated flameretardants (BFRs). Together with OH-PCBs and biological data fromGabrielsen et al. (2011), these new contaminant data were used inmultivariate models to explore associations and thus potential ef-fects on TH levels and ratios. The inclusion of a larger range of con-taminants was expected to increase explanatory power regardingimpacts of these contaminants on thyroid status and to provide amore complete picture of the role of OH-PCBs as thyroid disrup-tors, relative to other compounds in the measured OHC mixture.Also, by investigating hooded seal mother–pup pairs during thenursing period knowledge was gained regarding potential thyroiddisruptive effects of maternally transferred OHCs in the pups rela-tive to their mothers.
2. Methods
2.1. Sampling
Lactating hooded seal mothers and their recently born pups (1–4 d old) were live-captured in March 2008 in the West Ice, East ofGreenland (approximately 73.30�N, 14.50�W). The pups had fedonly on milk. Blood was collected and spun to prepare plasma andserum samples. Estimated pup age (d) based on developmentalstage (Kovacs and Lavigne, 1992), sex of the pups and body masses(BMs) of pups and mothers were recorded. Procedures for capturingand sampling are described in more detail in Gabrielsen et al. (2011).
Blood was used for measurements of OHCs in the present studybecause it reflects the on-going mobilisation and transfer of pheno-lic and lipid-soluble OHCs from mother to pup via the milk. Circu-lating OHCs may have the potential to affect important TH targetpoints in blood and reach other targets in the HPT axis.
2.2. Analyses of organohalogen contaminants
Chemical analyses of OHCs were performed at the Laboratory ofEnvironmental Toxicology at the Norwegian School of Veterinary
830 G.D. Villanger et al. / Chemosphere 92 (2013) 828–842
Science, Oslo, Norway. Merged plasma/serum samples of individ-ual hooded seals, henceforth referred to as plasma, were analysedfor the following contaminants: a-, b- and c-hexachlorocyclohex-ane (HCH), HCB, oxychlordane, trans-chlordane, cis-chlordane,trans-nonachlor, cis-nonachlor, 1,1-dichloro-2,2-bis(4-chloro-phenyl) ethylene (p,p’-DDE), 1,1-dichloro-2,2-bis(4-chlorophenyl)ethane (p,p’-DDD), 1,1,1-trichloro-2,2-bis(4-chlorophenyl) ethane(p,p’-DDT), 1,1,1-trichloro-2-(o-chlorophenyl)-2-(p-chlorophenyl)-ethane (o,p’-DDT), 1,1-dichloro-2-(o-chlorophenyl)-2-(p-chloro-phenyl)ethane (o,p’-DDD), Mirex, PCB congeners IUPAC nos. 28,31, 47, 52, 56, 66, 74, 87, 99, 101, 105, 110, 114, 118, 128, 137,136, 138, 141, 149, 151, 153, 156, 157, 170, 180, 183, 187, 189,194, 196, 199, 206 and 209, and the BFRs pentabromotoluene(PBT), 1,2-Bis(2,4,6-tribromophenoxy)ethane (BTBPE), hexabromo-cyclododecane (HBCD; sum of a-, b- and c-HBCD), hexabromoben-zene (HBB), pentabromoethylbenzene (PBEB), 2,3-dibromopropyl2,4,6-tribromophenyl ether (DPTE), PBDE congeners IUPAC nos.28, 47, 99, 100, 153, 154, 183, 206, 207, 208 and 209, and thephenolic metabolites or compounds 4-OH-CB106, 4-OH-CB107,4’-OH-CB108, 3-OH-CB118, 4’-OH-CB130, 3’-OH-CB138, 4-OH-CB146, 4’-OH-CB159, 4’-OH-CB172, 3’-OH-CB180, 4-OH-CB187,4-OH-BDE42, 3-OH-BDE47, 6-OH-BDE47, 4’-OH-BDE49, 2’-OH-BDE68, PCP, and 2,4,6-tribromophenol (TBP). The methods forextraction and sample clean-up are described in Brevik (1978)with modifications described in Gabrielsen et al. (2011) and refer-ences therein. Gabrielsen et al. (2011) reports OH-PCBs from thesame sample extracts as those used in this study. In short, internalstandards (PCB-29, -112, and -207; PBDE-77, -119, -181, 13C12-209;4’-OH-13C12-CB159 and 4-OH-13C12-CB187) were added to plasmasamples which then were extracted twice with acetone and cyclo-hexane (2:3). The subsequent clean-up was done with sulphuricacid (H2SO4). Lipid determination was done gravimetrically usingthe whole extract.
For analyses of BFRs (except for nona -and deca-BDEs), 1 ll ex-tract was injected into a GC (Agilent 6890 Series, Agilent Technol-ogies, Avondale, PA, USA) coupled to a Mass Spectrometer (MS)(Agilent 5973 N, Agilent Technologies) operated in negative chem-ical ionisation (NCI) mode with selected ion monitoring (SIM).PBDEs, HBCD, PBT, PBEB and PTBPE were monitored at m/z 79/
Table 1Concentrations (ng g�1 w.w.) of brominated contaminants in plasma of nursing hooded sdetection (LOD), mean values and standard deviation (SD) are presented, as well as median
LODa
(ng g�1 w.w.)Pup (n = 14)
n > LOD Mean SD Median Min
HBCD 0.17 3b 0.24 0.09 0.20 0.17PBT 0.01 0b . . . .PBEB 0.01 0b . . . .DPTE 0.01 0b . . . .HBB 0.01 0b . . . .BTBPE 0.03 0b . . . .BDE-28 0.02 0b . . . .BDE- 47 0.02 14c 0.16 0.13 0.10 0.03BDE-99 0.02 10c 0.04 0.04 0.03 0.01BDE- 100 0.01 10c 0.02 0.03 0.02 0.00BDE-153 0.01 13c 0.06 0.05 0.04 0.00BDE-154 0.01 14c 0.09 0.08 0.06 0.01BDE-183 0.09 4b 0.19 0.09 0.19 0.09BDE-206 0.12 0b . . . .BDE-207 0.02 4b 0.06 0.03 0.06 0.03BDE-208 0.01 2b 0.01 0.001 0.01 0.01BDE-209 0.11 2b 0.21 0.01 0.21 0.20RPBDEsd 14 0.37 0.31 0.24 0.05
a Limit of detection (LOD) is calculated as three times the noise levels in the chromatb OHC detected <60% of the individuals in each group are classified as not detected (nc OHC detected in P60% of individuals in each group, and missing values were givend RPBDEs includes PBDE-47, -99, -100, -153, and -154 (PBDE-28, -183, -206, 207, 208, a
and assigned the values of zero in calculation of RPBDEs).
81, whereas HBB and DPTE were monitored at m/z 79/551 and79/160, respectively. The nona -and deca-BDEs (PBDE-206, -207,-208 and -209) were analysed by GC–MS, operated in NCI-SIMmode, using a similar method to that described above, except thata programmable temperature vaporisation (PTV) injector (AgilentTechnologies) and an injection volume of 10 ll were used in thiscase. Nona- and deca-BDEs were monitored at m/z 486.8. Detailson the separation and detection of all BFRs can be found in Sørmoet al. (2006).
The GC–MS analyses of phenolic OHCs (OH-PBDEs, PCP, andTBP) followed the method for OH-PCBs described in Gabrielsenet al. (2011). The OH-PBDEs and TBP were monitored at m/z 79/81 and PCP was monitored at m/z 256/308. PCBs and OCPs wereanalysed on a GC (Agilent 6890 Series, Agilent Technologies) withdual column (SPB-5 and SPB-1701, Supelco Inc., Bellefonte, PA,USA) and coupled to a 63NI electron capture detector, followingthe method described in Murvoll et al. (2006).
The analytical laboratory has been accredited since 1996 (Nor-wegian Accreditation, Kjeller, Norway) as a testing laboratory thatmeets the requirements of NS-EN ISO/IEC 17025 (Test 137). Theanalysis of phenolic OHCs is not accredited for this laboratory,but these analyses were performed and validated following thesame principals as the accredited methods. The laboratory has par-ticipated in several interlaboratory tests with approved results forthe quantification of OCPs, PCBs and BFRs (QUASIMEME LaboratoryPerformance studies and AMAP [Arctic Monitoring and AssessmentProgram] ring test for persistent organic pollutants in human ser-um). For each analytical run, standard procedures were used to en-sure adequate quality and control, and that the accuracy, linearityand sensitivity were within the laboratory’s accreditation require-ments. Limit of detection (LOD) was defined as three times theaverage background noise in the chromatograms of the sample ex-tracts. Quantifications were done within the linear ranges of thecalibration curves (R P 0.985). LOD ranged from 0.01 to 0.05 nano-gram per gram wet weight (ng g�1 w.w.) for PCBs, 0.78–1.91 ng g�1
w.w. for HCHs, 1.38–1.49 ng g�1 w.w. for chlordanes (CHLs), 1.49–10.2 ng g�1 w.w. for dichlorodiphenyltrichloroethane related com-pounds (DDTs), 0.06–0.08 ng g�1 w.w. for OH-PBDEs, 0.56 ng g�1
w.w. for PCP and 0.03 ng g�1 w.w. for TBP. LODs for BFRs are given
eal (Cystophora cristata) pups and their mothers from the West Ice (2008). Limit of, minimum and maximum values. Contaminants above LOD are indicated in bold type.
Mother (n = 14)
. Max. n > LOD Mean SD Median Min. Max.
0.34 0b . . . . .. 0 b . . . . .. 0b . . . . .. 0 b . . . . .. 0b . . . . .. 0b . . . . .. 0b . . . . .0.44 13c 0.04 0.02 0.04 0.003 0.070.14 3b 0 . . . .
0 0.10 5b 0 . . . .4 0.16 12c 0.02 0.01 0.02 0.01 0.04
0.29 14c 0.02 0.01 0.02 0.01 0.040.30 3b 0.14 0.08 0.10 0.09 0.22. 1b 0.52 . . . .0.09 5b 0.05 0.04 0.031 0.02 0.120.01 3b 0.02 0.003 0.02 0.01 0.020.21 3b 0.22 0.10 0.18 0.14 0.341.07 14 0.08 0.02 0.08 0.03 0.12
ograms, or as mean blank levels plus two times SD (for PBDE-183, -207 and -209)..d.) and values presented are based on the number of individuals with levels > LOD.a random value between zero and LOD and included in the presented statistics.nd -209 were n.d. in pups and mothers, and PBDE-99 and -100 were n.d. in mothers
G.D. Villanger et al. / Chemosphere 92 (2013) 828–842 831
in Table 1. For PBDE-183, -207 and -209 there were inconsistentcontamination of blank samples and LODs were therefore calcu-lated using mean blank levels plus two times the standard devia-tion (Table 1). The relative recoveries for spiked sheep bloodsamples were; PCBs: 81–135%, HCHs: 41–70%, CHLs: 69–95%,DDTs: 93–131%, HCB: 83%, Mirex: 84%, nona- and decaBDE-206,207, 208 and 209: 126–144%, remaining PBDEs: 88–105%, PBT,PBEB, DPTE, HBB, HBCD and BTBPE: 96–103%, and phenolic OHCs(OH-PBDEs, PCP, and TBP): 39–86%. LODs and quality assurancefor OH-PCB analyses are described in Gabrielsen et al. (2011).
2.3. Analyses of thyroid hormones
Analysis of total and free T3 and T4 (TT3, FT3, TT4 and FT4) inhooded seal plasma was performed using commercially availablesolid-phase 125I radioimmunoassay (RIA) kits (Coat-A-Count TT3,
Table 2Lipid content and concentrations (ng g�1 w.w.) of organochlorine contaminants in plasma(2008). Mean values and standard deviation (SD) are presented, as well as median, minim
Contaminant Pup (n = 14)
Mean SD Median Min. M
Lipid%a 1.5 0.7 1.2 0.8 2HCB 0.20 0.14 0.15 0.07 0a-HCH 0.06 0.05 0.04 0.02 0b-HCH 0.08 0.08 0.05 0.03 0RHCHsb 0.14 0.12 0.09 0.05 0Oxychlordane 0.74 0.48 0.56 0.31 1Cis-chlordane 0.20 0.18 0.13 0.06 0trans-nonachlor 1.53 1.17 1.14 0.46 3cis-nonachlor 0.36 0.27 0.24 0.09 0RCHLsc 2.83 2.00 2.01 0.92 6Mirex 0.30 0.21 0.23 0.06 0p,p’-DDE 6.59 4.37 5.09 1.64 1p,p’-DDD 0.14 0.12 0.09 0.03 0p,p’-DDT 0.88 0.64 0.61 0.19 2RDDTsd 7.61 5.12 5.78 1.86 1PCB-52 0.44 0.29 0.32 0.17 1PCB-74 0.07 0.08 0.03 0.003 0PCB-99 0.84 0.53 0.62 0.23 2PCB-101 1.05 0.76 0.63 0.42 2PCB-110 0.37 0.32 0.20 0.08 1PCB-118 0.35 0.27 0.21 0.08 0PCB-137 0.07 0.05 0.05 0.004 0PCB-138 1.81 1.12 1.53 0.48 4PCB-141 0.08 0.08 0.04 0.03 0PCB-149 0.67 0.50 0.37 0.18 1PCB-153 3.63 2.14 3.09 0.81 7PCB-156 0.08 0.06 0.06 0.01 0PCB-170 0.44 0.28 0.38 0.08 1PCB-180 1.45 0.89 1.30 0.25 3PCB-183 0.32 0.20 0.29 0.06 0PCB-187 0.62 0.38 0.51 0.12 1PCB-189 0.03 0.02 0.02 0.002 0PCB-194 0.21 0.15 0.17 0.03 0PCB-206 0.10 0.06 0.07 0.02 0PCB-209 0.09 0.06 0.08 0.03 0RPCBsf 12.7 7.83 9.89 3.11 24-OH-CB107 0.575 0.222 0.641 0.115 03’-OH-CB138 0.013 0.009 0.016 0.001 04-OH-CB146 0.019 0.010 0.019 0.002 04’-OH-CB172 0.014 0.009 0.013 0.003 04-OH-CB187 0.061 0.046 0.045 0.015 0ROH-PCBsg 0.683 0.276 0.721 0.141 1
a Lipid content (lipid%) of plasma/serum samples was determined gravimetrically.b RHCHs include a-HCH and b-HCH (c-HCH was n.d in pups and mothers).c RCHLs include oxychlordane, cis-chlordane, trans-nonachlor and cis-nonachlor (trand RDDT include p,p’-DDE, p,p’-DDD and p,p’-DDT (o,p’-DDD and o,p’-DDT were n.d. ine OHC below limit of detection (LOD) in more than 60% of the individuals in each grof RPCBs include PCB-52, -74 (only pups), -99, -101, -110, -118,- 137, -138, -141, -149,
31, -47, -56, -66, -87, -105, -114, -128, -136, -151, -157, -196, -199 were n.d. in pups ang ROH-PCBs include 4-OH-CB107, 3’-OH-CB138, 4-OH-CB146, 4’-OH-CB172, 4-OH-CB
OH-CB180 were n.d. in pups and mothers). The levels of individual OH-PCBs and ROH-P
Coat-A-Count FT3, Coat-A-Count TT4, Coat-A-Count FT4, SiemensMedical Solutions Diagnostics, Los Angeles, CA, USA) at the Depart-ment of Biology, Norwegian University of Science and Technology,Trondheim, Norway. The standard test protocols for these RIA kitswere followed (Siemens, 2006a,b,c,d). A more detailed descriptionof the analytical procedures is presented in Gabrielsen et al. (2011).
2.4. Data analyses
All contaminant results (lipid-soluble and phenolic OHCs) areexpressed in ng g�1 w.w. The following contaminants had concen-trations above LOD in less than 60% of the samples from pups ormothers and were noted as not detected (n.d.) and excluded fromstatistical analysis in either or both of the groups: PCB-28, -31, -47,-56, -66, -74 (only mothers) -87, -105, -114, -128, -136, -151, -157,-189 (only mothers), -196, -199, c-HCH, trans-chlordane, o,p’-DDT,
of nursing hooded seal (Cystophora cristata) pups and their mothers from the West Iceum and maximum values.
Mother (n = 14)
ax. Mean SD Median Min. Max.
.9 0.7 0.2 0.7 0.5 1.0
.63 0.09 0.03 0.08 0.05 0.16
.19 0.02 0.01 0.02 0.004 0.03
.27 0.03 0.01 0.03 0.004 0.05
.46 0.05 0.02 0.05 0.02 0.08
.99 0.22 0.07 0.20 0.09 0.40
.61 0.06 0.03 0.06 0.03 0.12
.92 0.40 0.18 0.35 0.13 0.79
.90 0.13 0.04 0.12 0.06 0.21
.56 0.80 0.29 0.73 0.30 1.44
.80 0.10 0.05 0.08 0.02 0.225.3 1.55 0.52 1.48 0.40 2.44.37 0.03 0.01 0.03 0.01 0.06.13 0.23 0.07 0.22 0.07 0.357.8 1.82 0.59 1.72 0.48 2.83.22 0.20 0.03 0.20 0.17 0.27.26 (n.d.)e . . . ..02 0.25 0.07 0.23 0.08 0.38.61 0.32 0.08 0.31 0.15 0.48.15 0.12 0.03 0.12 0.06 0.18.83 0.10 0.03 0.11 0.03 0.16.18 0.03 0.01 0.03 0.01 0.04.10 0.55 0.22 0.52 0.17 0.97.26 0.03 0.01 0.03 0.01 0.05.71 0.17 0.05 0.17 0.07 0.24.93 1.09 0.34 1.03 0.27 1.70.19 0.03 0.01 0.03 0.01 0.05.11 0.14 0.07 0.12 0.03 0.26.51 0.43 0.22 0.38 0.08 0.91.77 0.10 0.05 0.09 0.01 0.18.39 0.18 0.07 0.17 0.05 0.29.05 (n.d.)e . . . ..57 0.06 0.04 0.05 0.01 0.14.20 0.03 0.01 0.03 0.02 0.06.20 0.03 0.02 0.04 0.001 0.086.7 3.84 1.22 3.74 1.27 5.83.848 1.175 0.474 1.213 0.265 1.785.027 0.013 0.008 0.015 0.000 0.027.034 0.041 0.019 0.038 0.015 0.069.033 0.024 0.014 0.020 0.007 0.057.140 0.142 0.083 0.110 0.043 0.289.059 1.395 0.543 1.408 0.339 2.042
s-chlordane were n.d. in pups and mothers).pups and mothers).up are noted as not detected (n.d.).-153, -156, -170, -183, -180, -187, -189 (only pups), -194, -206, and -209 (PCB-28, -d mothers, and PCB-74 and -189 were n.d. only in mothers).
187 (3-OH-CB118, 4’-OH-CB106, 4’-OH-CB108, 4’-OH-CB130, 4’-OH-CB159, and 3’-CBs were first reported in Gabrielsen et al. (2011).
-0.40
-0.35
-0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
α-H
CH
PCB-
141
β -H
CH
Pup
age
PCB-
149
PCB-
52
PCB-
110
PBD
E-15
4
HC
B
PCB-
209
PCB-
101
p,p-
DD
D
Mire
x
PCB-
194
PBD
E-47
PCB-
137
PCB-
187
PCB-
180
PCB-
156
PCB-
183
PCB-
170
4-O
H-C
B146
PCB-
153
PCB-
118
4'-O
H-C
B172
PCB-
99
4-O
H-C
B187
trans
-non
achl
orBM
oxyc
hlor
dane
PCB-
138
Lipi
d%
p,p’
-DD
T
p,p’
-DD
E
PBD
E-15
3
Coe
ffCS
(TT3
:FT3
)
PCB-
206
3'-O
H-C
B138
4-O
H-C
B107
cis-
chlo
rdan
e
cis-
nona
chlo
r-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
-1.1 -1.0 -0.7 -0.6 -0.5 -0.4-0.9 -0.8 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
BM
Pup age
Lipid%
PCB-52
PCB-99
PCB-101
PCB-110
PCB-118
PCB-137
PCB-138
PCB-141
PCB-149
PCB-153
PCB-156PCB-170PCB-183
PCB-180PCB187
PCB-194PCB-206PCB-209
HCB
α-HCH
β-HCH
oxychlordane
cis-chlordane
trans-nonachlor
cis-nonachlorMirex
p,p'-DDE
p,p'-DDD
p,p'-DDT
PBDE-47
PBDE-153
PBDE-154
4-OH-CB1073'-OH-CB138
4-OH-CB1464'-OH-CB172
4-OH-CB187
TT3:FT3
Mother_E
Mother_E
Mother_E
Mother_E
Mother_E
Mother_E
Mother_E
Mother_E
Mother_LMother_L
Mother_L
Mother_L
Mother_L
Mother_L
PLS component 1
PL
S co
mpo
nent
2
(a) Mothers Y=TT3:FT3 (Loading bi-plot)
(b) Mothers Y=TT3:FT3 (Regression coefficient plot)
X-variables Y-variable
Fig. 1. (a) Bi-plot showing scores and loadings (PLS weights: w�c) of the significant PLS model between Y = TT3:FT3 and 40 X-variables (37 individual OHCs in plasma (ng g�1
w.w.), lipid%, BM, and pup age) of 14 lactating hooded seal (Cystophora cristata) females. The scores are grouped into early lactation stage (Mothers_E; pup age < 3 d) and latelactation stage mothers (Mothers_L; pup age P 3 d). The PLS model had two significant components: R2X = 0.58, R2Y = 0.74, and Q2 = 0.40. (b) Regression coefficient plot of thePLS model. All bars show regression coefficient (CoeffCS) values of each variable indicating the direction and strength of the relationships between individual X-variables andY = TT3:FT3. The error bars represent the 95% confidence intervals. The dark grey bars present CoeffCS values of variables with VIP values P 1, which indicate high importancefor the model. (c) All bars show variable importance for the projection (VIP) values that summarises the importance of the variables in explaining the X-matrix and tocorrelate with Y = TT3:FT3. The error bars represent 95% confidence intervals. VIPs P 1 indicate important X-variables (dark grey bars).
832 G.D. Villanger et al. / Chemosphere 92 (2013) 828–842
o,p’-DDD, PBDE-28, -99 (only mothers), -100 (only mothers), -183,-206, 207, 208, -209, PBT, PBEB, DPTE, HBB, PTBPE, HBCD, PCP, TBP
and all OH-PBDEs. Contaminants with concentrations above LOD inP60% of pups or mothers were used in statistical analyses, and
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0α-
HC
HPC
B-14
1
p,p’
-DD
E
p,p’
-DD
T
PCB-
149
β-H
CH
PBD
E-15
3
PCB-
138
PCB-
110
Pup
age
PBD
E-15
4
PCB-
99
cis-
chlo
rdan
e
3'-O
H-C
B138
PCB-
52
PCB-
153
PCB-
187
Lipi
d%
PCB-
209
PCB-
101
PCB-
183
trans
-non
achl
or
PCB-
118
PCB-
206
PCB-
170
Mire
x
PBD
E-47
oxyc
hlor
dane
p,p’
-DD
D
PCB-
180
PCB-
194
4-O
H-C
B187
HC
B
4-O
H-C
B107
PCB-
156
4'-O
H-C
B172 BM
4-O
H-C
B146
PCB-
137
VIP
cis -
nona
chlo
r
(c) Mothers Y=TT3:FT3 (VIP plot)
Fig. 1. (continued)
G.D. Villanger et al. / Chemosphere 92 (2013) 828–842 833
missing values (i.e. below LOD) were assigned a random value be-tween the LOD and zero; PCB-137, -141, -156, -183, -189 (onlypups), -194, -209, a-HCH, b-HCH, PBDE-47, -99 (only pups), -100(only pups) and -153. Male and female pups were grouped to-gether because there were no differences in concentrations of ma-jor OHC groups or TH levels (p > 0.05, t-test on log10-data)according to sex. Thus, data consisted of two groups – mothers(adult females, n = 14) and pups (female and male pups, n = 14).
Multivariate analyses were performed using the software Sim-ca-P+ (Version 12.0, Umetrics AB, Umeå, Sweden). Projections tolatent structures by means of partial least squares (PLS – Erikssonet al., 2006) was applied to investigate the multivariate relation-ships between the X-variables (contaminants, biological data)and their unidirectional, statistical influence on the Y-variables(TH levels and ratios). This multivariate regression method hasbeen applied in several recent wildlife studies (Jenssen et al.,2010; Villanger et al., 2011a,b; Bechshøft et al., 2012). SeparatePLS models were developed for pups and mothers. The originalmodels consisted of 8 Y-variables (TT4, FT4, TT3, FT3, TT4:FT4,TT3:FT3, TT4:TT3, FT4:FT3) and 40 X-variables in mothers (37OHCs including 5 OH-PCB, BM, plasma lipid content [lipid%], andpup age) and 46 X-variables in pups (41 OHCs including 5 OH-PCBs, BM, lipid%, pup age, pup sex – male and female). Even thoughTH and OHC levels did not differ between male and female pups,sex was included as a qualitative X-variable to investigate poten-tial gender differences in TH responses to contaminants, whichhave been shown in humans and wildlife such as polar bears(Gochfeld, 2007; Abdelouahab et al., 2008; Villanger et al.,2011a). Variables that were identified as being skewed werelog10-transformed (Umetrics, 2008). All variables were centredand scaled (to variance 1) and significance level was set to 0.05(Umetrics, 2008). PLS modelling was validated by the explainedvariation in the X-matrix (R2X), explained variance of the Y-vari-ables by the X-matrix (goodness of fit, R2Y), goodness of prediction(Q2) obtained by cross-validation and permutation analyses (20
permutations). The models were developed by successively remov-ing Y-variables with the lowest R2Y and Q2 from the model to im-prove validation parameters until the best models were obtained.The importance of individual X-variables in explaining the X- andY-matrix were evaluated using the variable importance for theregression (VIP) values. A VIP value >1 denotes high importancefor the model and a VIP < 0.5 indicates low or no importance(Umetrics, 2008). When required, further optimising of the PLSmodel was done by removing X-variables with low VIP values. An-other evaluation parameter used herein is the regression coeffi-cient (CoeffCS) value, which shows the correlative relationship(strength and direction) between each X-variable with Y (Umetrics,2008; more details regarding PLS can be found in Wold et al., 2001;Eriksson et al., 2006; Umetrics, 2008).
Univariate statistical analyses (SPSS Version 16, standard ver-sion, SPSS Inc., Chicago, IL, USA) were performed on log10-trans-formed data. Student t-test was employed to test groupdifferences in OHC and TH levels. The most important findingsfrom the PLS models were further analysed by univariate regres-sion: general linear modelling (GLM, type III sum of squares) withbackward selection or multiple linear regression (MLR, backwardselection mode). Significance level was set to p 6 0.05; p-valuesare two-tailed.
3. Results
3.1. Analytical results
The plasma concentrations of brominated and organochlorinecontaminants, in hooded seal pups and mothers, are presented inTables 1 and 2, respectively. Table 2 also includes levels of OH-PCBs reported by Gabrielsen et al. (2011) for comparative context.Previously reported plasma concentrations and ratios of THs, BM inpups and mothers (Gabrielsen et al., 2011), and estimated pup ageare summarised in Supplementary material Table S1.
-0.35
-0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
0.30
-0.17 -0.16 -0.15 -0.12-0.14 -0.13 -0.11 -0.10 -0.09 -0.08 -0.07 -0.06 -0.05 -0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22
PLS
com
pone
nt 2
BMPup age
Sex(Female)
Sex(Male)
Lipid%
PCB-52
PCB-74
PCB-99
PCB-101
PCB-110
PCB-118
PCB-137
PCB-138
PCB-141
PCB-149
PCB-153
PCB-156
PCB-170PCB-183
PCB-180
PCB187
PCB-189
PCB-194
PCB-206
PCB-209
HCB α-HCH
β-HCH
oxychlordane
cis-chlordane
trans-nonachlor
cis-nonachlor
Mirex
p,p'-DDE
p,p'-DDD
p,p'-DDT
PBDE-47
PBDE-99
PBDE-100
PBDE-153PBDE-154
4-OH-CB1073'-OH-CB138
4-OH-CB146
4'-OH-CB172
4-OH-CB187
TT3:FT3
PLS component 1
-0.12
-0.10
-0.08
-0.06
-0.04
-0.02
-0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
3'-O
H-C
B138
4-O
H-C
B146
4-O
H-C
B107
4-O
H-C
B187
PBD
E-10
0
Pup
age
4'-O
H-C
B172 BM
PBD
E-99
PCB-
194
PCB-
180
PCB-
170
PCB-
183
Mire
x
Sex(
Mal
e)
PCB-
189
PBD
E-15
3
PBD
E-15
4
PBD
E-47
PCB-
138
PCB1
87
trans
-non
achl
or
PCB-
153
PCB-
206
PCB-
74
PCB-
209
PCB-
156
PCB-
110
cis-
nona
chlo
r
p,p-
‘DD
E
PCB-
99
PCB-
118
cis-
chlo
rdan
e
PCB-
101
p,p-
DD
T
PCB-
149
PCB-
137
PCB-
52
oxyc
hlor
dane
p,p’
-DD
D
PCB-
141
Lipi
d% HC
B
α-H
CH
β-H
CH
Coe
ffCS
(TT3
:FT3
)
(b) Pups Y= TT3:FT3 (Regression coefficient plot)
X-variables Y-variable (a) Pups Y= TT3:FT3 (Loading plot)
Sex(
Fem
ale)
Fig. 2. (a) Plot showing loadings (PLS weights: w�c) of the significant PLS model between Y = TT3:FT3 and 46 X-variables (41 individual OHCs in plasma (ng g�1 w.w.), lipid%,BM, and pup age and sex [male and female]) of 14 nursing hooded seal (Cystophora cristata) pups. The PLS model had two significant components: R2X = 0.81, R2Y = 0.76, andQ2 = 0.63. (b) Regression coefficient plot of the PLS model. All bars show regression coefficient (CoeffCS) values of each X-variable indicating the direction and strength of therelationships with Y = TT3:FT3. The error bars represent the 95% confidence intervals. The dark grey bars present CoeffCS values of variables with VIP values P 1, whichindicate high importance for the model. (c) All bars show variable importance for the projection (VIP) values that summarises the importance of the variables in explainingthe X-matrix and to correlate with Y = TT3:FT3. The error bars represent 95% confidence intervals. VIP P 1 indicates important X-variables (dark grey bars).
834 G.D. Villanger et al. / Chemosphere 92 (2013) 828–842
-0.6
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0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
β-H
CH
3'-O
H-C
B138
α-H
CH
Lipi
d%
p,p’
-DD
D
HC
B
oxyc
hlor
dane
PCB-
52
PCB-
141
p,p-
DD
T
PCB-
118
PCB-
149
PCB-
99
PCB-
101
p,p’
-DD
E
cis-
nona
chlo
r
PCB-
110
PCB-
137
PCB-
156
PCB-
138
PCB-
209
PCB-
187
PCB-
153
4-O
H-C
B107
PCB-
206
PBD
E-47
PCB-
183
Mire
x
PCB-
189
PCB-
180
PCB-
170
PBD
E-15
4
4-O
H-C
B187
PCB-
74
PCB-
194
PBD
E-10
0
Pup
age
PBD
E-99
4'-O
H-C
B172 BM
VIP
4-O
H-C
B146
cis-
chlo
rdan
e
trans
-non
achl
or
PBD
E-15
3
Sex(
Mal
e)
Sex(
Fem
ale)
(c) Pups Y= TT3:FT3 (VIP plot)
Fig. 2. (continued)
G.D. Villanger et al. / Chemosphere 92 (2013) 828–842 835
3.2. Modelled effects of contaminants on thyroid hormones
3.2.1. MothersThe best PLS model for the mothers was obtained with
Y = TT3:FT3 (2 PLS components: R2X = 0.58, R2Y = 0.74, Q2 = 0.40).R2Y and Q2 were within values that define a good or acceptablemodel using biological data; R2Y > 0.7 and Q2 > 0.4 (Lundstedtet al., 1998). The permutation analyses confirmed the validity ofthe model with the TT3:FT3 intercepts R2Y = (0.0, 0.548) andQ2 = (0.0, �0.179). The TT3:FT3 ratio was negatively influencedmainly by a-HCH, PCB-141 and b-HCH, and positively influencedparticularly by p,p’-DDE, p,p’-DDT, and PCB-138 (Fig. 1a–c).Although PBDE-153 appeared to be important for the TT3:FT3 ratiobecause of high VIP and CoeffCS values, the large 95% confidenceinterval in Fig. 1b implies a lot of uncertainty with respect to thedirection of its influence. Additionally, PCB-149, cis-chlordane,PCB-52, 3’-OH-CB138, PCB-110, and PBDE-154 were negativelyassociated with TT3:FT3 ratios (Fig. 1a and b). The most influentialbiological variables were pup age and lipid%, which were nega-tively and positively associated, respectively, with TT3:FT3 ratios(Fig. 1a and b). Pup age had a higher VIP value than lipid%(Fig. 1c). The influence of pup age, and thus time into the nursingperiod, also became evident when using early lactation stage(pup age < 3 d: Mothers_E) and late lactation stage mothers (pupage P 3 d: Mothers_L) as grouping variables for model outputscores (see Fig. 1a). Mothers_L were situated closer to the majorityof the contaminants than Mothers_E. This means that motherssampled late in the nursing period had higher contaminant levelsin plasma than the mothers sampled early. Further testing withbackward MLR of log10-transformed data resulted in a significantprediction of TT3:FT3 ratio (R2 = 0.47, F3,11 = 3.939, p = 0.043), witha-HCH (t = �3.162, p = 0.010; Fig. 4a), p,p’-DDE (t = 2.446,p = 0.035) and PCB-141 (t = �2.232, p = 0.050) as significant predic-tors. Pup age and PBDE-153 were selected out of the regression,which implies that they have less influence on TT3:FT3 ratio.
3.2.2. PupsThe best PLS models for pups were obtained for Y = TT3:FT3 (2
PLS components; R2X = 0.81, R2Y = 0.76, Q2 = 0.63) and forY = TT4:FT4 (2 PLS components; R2X = 0.82, R2Y = 0.69, Q2 = 0.39).The latter model was achieved by step-wise removal of X-variableswith the lowest VIP values (4-OH-CB146, 4-OH-CB187, 4’-OH-CB-172, 3’-OH-CB138, lipid%, a-HCH, and HCB). No X-variables wereremoved from the Y = TT3:FT3 model. Both models had R2Y andQ2 values similar to or above values that define a good model usingbiological data; R2Y > 0.7 and Q2 > 0.4 (Lundstedt et al., 1998). Thepermutation analyses also confirmed the validity of the models:TT3:FT3 intercepts: R2Y = (0.0, 0.378), Q2 = (0.0, �0.186) andTT4:FT4 intercepts: R2Y = (0.0, 0.417), Q2 = (0.0, �0.0959).
The most important variables explaining TT3:FT3 ratios in pupswere 3’-OH-CB138 and 4-OH-CB146, which were negatively corre-lated with TT3:FT3, as well as b-HCH, a-HCH, and HCB which werepositively correlated with TT3:FT3 (Fig. 2a–c). The model alsoshowed that TT3:FT3 ratios were positively influenced by severalother contaminant variables (Fig. 2a and b), such as p,p’-DDD,p,p’-DDT, p,p’-DDE, oxychlordane, cis-chlordane, PCB-118 (amono-ortho, dioxin-like PCB) as well as many low to medium-chlorinated non-dioxin-like ortho-PCBs (e.g. PCB-52, -99, -141,137, and -149). TT3:FT3 ratios in pups were also influenced by bio-logical variables, most importantly lipid%, which was positivelycorrelated with TT3:FT3 (Fig. 2b). Further testing with backwardMLR using 3’-OH-CB138, 4-OH-CB146, a-HCH, b-HCH and lipid%as independent variables resulted in a significant prediction ofY = TT3:FT3 (R2 = 0.89, F2,12 = 20.470, p = 0.0001) with b-HCH beingthe most important predictor (t = 2.964, p = 0.013; Fig. 4b); thenext best predictor, lipid%, was not significant (t = 1.824, p = 0.095).
PLS modelling indicated that the contaminants with the great-est positive influence on TT4:FT4 ratios in pups were PBDE-99,but also 4-OH-CB107, PBDE-100 and -154; several high-chlori-nated PCBs (e.g. PCB-189, 206 and 209) also affected TT4:FT4 ratiosin a positive direction. PCB-74 had a negative influence on TT4:FT4
836 G.D. Villanger et al. / Chemosphere 92 (2013) 828–842
ratios (Fig. 3a–c). Sex was the most important biological variable inthe TT4:FT4 PLS model. The positive contribution of pup age andBM on TT4:FT4 ratio was less important than sex (Fig. 3b and c).GLM testing with TT4:FT4 as a dependent variable, with sex
-0.30
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0.00
0.05
0.10
0.15
0.20
0.25
0.30
Sex(
Fem
ale)
PCB-
74
PCB-
153
PCB-
137
PCB-
52
PCB-
99
oxyc
hlor
dane
p,p’
-DD
E
cis-
nona
chlo
r
PCB-
183
PBD
E-15
3
PCB-
110
PCB-
180
PCB-
138
PCB-
170
trans
-non
achl
or
p,p-
DD
T
pp-D
DD
PBD
E-47
Coe
ffCS
(TT4
:FT4
)
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0.9
1.0
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Sex(Male)
PupF
PupFPupF
PupF
PupM
PupM
PupM
PupMPu
PLS com
PL
S co
mpo
nent
2
(a) Pups Y= TT4:FT4 (Loading bi-plot)
(b) Pups Y= TT4:FT4 (Regression coefficient plot)
Fig. 3. (a) Bi-plot showing scores and loadings (PLS weights: w�c) of the significant PLS mw.w.), BM, and pup age and sex [male and female]) of 14 nursing hooded seal (CystophoraPLS model had two significant components: R2X = 0.82, R2Y = 0.69, and Q2 = 0.39. (b) Regrevalues of each X-variable indicating the direction and strength of the relationships with Ypresent CoeffCS values of variables with VIP values P 1, which indicate high importancethat summarises the importance of the variables in explaining the X-matrix and to corrindicates important X-variables (dark grey bars).
(group) and age as covariates showed that PBDE-99 (F1,13 = 7.195,p = 0.023; Fig. 4c) was significant and more important than sex(F = 3.279; p = 0.078) and 4-OH-CB107 (F = 1.181; p = 0.303), aswell as PCB-74 and pup age (both removed by backward selection),
PCB-
118
PCB-
101
Mire
x
cis-
chlo
rdan
e
PCB-
187
PCB-
156
PCB-
149
PCB-
141
β-H
CH
PCB-
194
PBD
E-15
4
PCB-
206
PCB-
189
PCB-
209
PBD
E-10
0
4-O
H-C
B107 BM
PBD
E-99
Pup
age
Sex(
Mal
e)
.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
BMPup age
Sex(Female)
PCB-52PCB-74 PCB-99
PCB-101
PCB-110PCB-118
PCB-137
PCB-138
PCB-141
PCB-149
PCB-153
PCB-156
PCB-170PCB-183
PCB-180
PCB187PCB-189
PCB-194
PCB-206
PCB-209
β-HCH
oxychlordane
cis-chlordane
cis-nonachlor
Mirex
p,p'-DDEp,p'-DDD p,p'-DDT
PBDE-47
PBDE-99PBDE-100
PBDE-154
4-OH-CB107
TT4:FT4
PupF
PupF
PupF
PupF
PupMpM
ponent 1
X-variables Y-variable
odel between Y = TT4:FT4 and 39 X-variables (35 individual OHCs in plasma (ng g�1
cristata) pups. The scores are grouped into female (PupF) and male (PupM) pups. Thession coefficient plot of the PLS model. All bars show regression coefficient (CoeffCS)= TT4:FT4. The error bars represent the 95% confidence intervals. The dark grey barsfor the model. (c) All bars show variable importance for the projection (VIP) valueselate with Y = TT4:FT4. The error bars represent 95% confidence intervals. VIP P 1
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5Se
x(Fe
mal
e)
Sex(
Mal
e)
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age
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PCB-
74
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BM
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PBD
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99
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52
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PCB1
87
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p,p’
-DD
E
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138
PCB-
156
PCB-
101
PBD
E-47
p,p’
-DD
T
PCB-
183
Mire
x
PCB-
118
oxyc
hlor
dane
PCB-
110
β-H
CH
p,p’
-DD
D
cis-
nona
chlo
r
cis-
chlo
rdan
e
PCB-
180
PCB-
170
PCB-
141
PBD
E-15
3
trans
-non
achl
o r
VIP
(c) Pups Y= TT4:FT4 (VIP plot)
Fig. 3. (continued)
G.D. Villanger et al. / Chemosphere 92 (2013) 828–842 837
in explaining the variation of TT4:FT4 (GLM; R2 = 0.537,F3,11 = 3.864, p = 0.045).
3.2.3. Comparing pups and mothersSince no X-variables were removed in the PLS models for
Y = TT3:FT3 for either pups or mothers, it was possible to qualita-tively compare which variables were most influential in bothgroups. OH-PCBs were more important as predictors of TT3:FT3in pups compared to mothers (Figs. 1b and c and 2b and c). Fur-thermore, the loading bi-plot showed that the OH-PCBs weregrouped together with the OHCs in the mothers (Fig. 1a), indicatingpositive correlations between these two contaminant groups in themothers. In contrast, the OH-PCBs in the pups were negatively cor-related with OHCs on the first and the second PLS components(Fig. 2a). Furthermore, OH-PCBs were positively correlated withpup age and BM (Fig. 2a). This suggests that OH-PCB levels increasethrough the nursing period in pups, and that the negative associa-tions between OH-PCBs and OHCs increase with age, and concom-itantly with BM (i.e. through the nursing period).
The PLS model showed that a- and b-HCH, and several low tomedium-chlorinated ortho-PCBs (e.g. PCB-52, -141, 149), werethe major contaminants influencing TT3:FT3 ratios in both moth-ers and pups. However, the directions of the correlations toTT3:FT3 were inversely related in the two groups (Figs. 1b and2b). DDTs and CHLs (e.g. oxychlordane and cis-chlordane) alsoinfluenced TT3:FT3 ratios in both pups and mothers. However,DDTs, particularly p,p’-DDE, seemed to be more important in themothers than in the pups (Figs. 1c and 2c). In pups, HCB andPCB-118 seemed to be more important for TT3:FT3 than in moth-ers. In addition to specific contaminants, pup age and lipid% werethe two most important biological variables explaining TT3:FT3 ra-tios in the PLS models of both pups and mothers.
Sex was important for the TT4:FT4 ratio in pups, but not for theTT3:FT3 ratio. When tested in univariate regression analysis (GLMor MLR) with the most important biological variables as covariates,the contaminants still showed significant regressions with TH ra-
tios, thus confirming the major findings of the PLS models. Someof these relationships are presented in Fig. 4a–c.
4. Discussion
The PLS models in the present study showed that TT3:FT3 ratiosin hooded seal pups and mothers and TT4:FT4 ratios in hooded sealpups were associated with the levels of circulating OHCs (Figs. 1–3); both negative and positive relationships with TH ratios werefound. Although statistical modelling does not prove biologicalcause-effect relationships per se, the modelled relationships hereinsuggest that the natural homeostasis between protein-bound andfree TH levels in blood might be affected by specific contaminantsin hooded seal females and their pups. This is in accordance withprevious studies on seals, which have shown OHC-associated dis-turbances on TH homeostasis (Brouwer et al., 1989; De Swartet al., 1995; Jenssen et al., 1995; Chiba et al., 2001; Hall et al.,2003; Sørmo et al., 2005; Tabuchi et al., 2006; Hall and Thomas,2007; Routti et al., 2008a,b, 2010). In several of these studies, T3homeostasis (TT3, FT3, or TT3:FT3) seemed to be most affected(Sørmo et al., 2005; Hall and Thomas, 2007; Routti et al.,2008a,b, 2010), suggesting that T3 homeostasis might be particu-larly susceptible to contaminant disruption in seals.
Both TT3:FT3 and TT4:FT4 ratios were correlated with OHC lev-els in pups, as opposed to only the TT3:FT3 ratio in mothers. Thismight be due to the 1.1–2.5 times higher plasma levels of lipid-sol-uble OHCs in pups compared to the mothers, even when the two-fold higher lipid% of pup plasma was taken into account (Tables 1and 2). The plasma levels of lipid-soluble OHCs reported in thepresent study were within the range reported in other arctic mar-ine mammals (de Wit et al., 2010; Letcher et al., 2010), includingprevious studies of hooded seals and other pinniped species (Espe-land et al., 1997; Sørmo et al., 2003; Wolkers et al., 2004, 2006).These earlier phocid seal studies have also demonstrated substan-tial maternal transfer of OHCs to pups via milk.
There are only a few studies reporting new BFRs in arctic biota.The detection of some of these compounds in marine mammals
-2.6 -2.4 -2.2 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.62.8
3.0
3.2
3.4
3.6
3.8Mothers Pups
log10 α-HCH (ng/g w.w.)
log 10
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FT3
ratio
-2.5 -2.0 -1.5 -1.0 -0.5 0.02.8
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3.2
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log10 β-HCH (ng/g w.w.)
log 10
TT3
:FT3
ratio
(a)
(b)
-2.4 -2.2 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.63.30
3.35
3.40
3.45
3.50
3.55
3.60
3.65
3.70Pups
log 10
TT4:
FT4
ratio
log10PBDE-99 (ng/g w.w.)
(c)
Fig. 4. Circulating TT3:FT3 ratio vs plasma levels (ng g�1 w.w.) of (a) a-HCH and (b)b-HCH in hooded seal (Cyctophora cristata) mothers (n = 14) and pups (n = 14) fromthe West Ice. (c) Circulating TT4:FT4 ratio vs plasma levels (ng g�1 w.w.) of PBDE-99in hooded seal pups (n = 14). These scatter-plots show the most importantrelationships from the PLS models. The directions of the relationships foundsignificant in univariate regression analyses are illustrated by the best-fit regressionlines (dashed lines) through the data points in the plots.
838 G.D. Villanger et al. / Chemosphere 92 (2013) 828–842
and seabirds indicates their presence in the Arctic and the poten-tial for bioaccumulation in higher trophic predators (as reviewedin de Wit et al., 2010). However, the new BFRs (BPT, HBB, BTBPE,PBEB and PBT) were below detection in hooded seal plasma inthe present study (Table 1).
Among the phenolic OHCs that were analysed in hooded sealplasma, the only group detected was OH-PCBs (Table 2). In mam-mals, including seals, OH-PCBs are thought to originate fromendogenous biotransformation of dietary PCBs (Letcher et al.,2000; Routti et al., 2008a,b). This probably explains the high plas-ma levels of OH-PCBs reported in hooded seal females (Gabrielsenet al., 2011). The OH-PCBs in pup plasma probably results frommaternal transfer and to a lesser degree biotransformation of PCBs.For a detailed discussion on levels and patterns of these com-pounds, see Gabrielsen et al. (2011). The lack of detectable levelsof OH-PBDEs and PCP in hooded seals is in accordance with the re-ported low, or not detected, concentrations in other arctic wildlife(Letcher et al., 2009; Routti et al., 2009; Letcher et al., 2010). Stud-ies have demonstrated a slow in vitro biotransformation of PBDEsto OH-PBDEs in wildlife tissues and a general lack of correlationsbetween PBDEs and OH-PBDEs in marine organisms (Verreaultet al., 2005; Letcher et al., 2009; Wiseman et al., 2011). This indi-cates that dietary OH-PBDEs from non-PBDE sources could be animportant input of these compounds (Wiseman et al., 2011).
Gabrielsen et al. (2011) reported that 3’-OH-CB138 and 4-OH-CB107 were negatively correlated with TT3:FT3 and FT4:FT3 ratios,respectively, in hooded seal pups. These compounds remainedimportant in the broader analyses herein, but 4-OH-CB146, 4-OH-CB107 and 4-OH-CB187 were also important OHCs, whichshowed negative relationships with TT3:FT3 ratios in pups(Fig. 2b). The results of the present PLS models confirmed that inthe total mixture of lipid-soluble and phenolic OHCs, OH-PCBs playan important role in depressing TT3:FT3 ratios in hooded seal pups.This was not found to be the case in the hooded seal mothers, de-spite their two-times higher levels of ROH-PCBs compared to theirpups (Table 2; Gabrielsen et al., 2011) This suggests that seal pupsmay have a higher susceptibility to potential effects of OH-PCBs onTH homeostasis than their mothers (also see Gabrielsen et al.,2011).
The present study found that, in addition to the negative asso-ciations between OH-PCBs and TH ratios, other OHCs were alsoimportant determinants for TH homeostasis in hooded seals(Figs. 1–3). TH balance in hooded seals was best explained by themultivariate relationships of several lipid-soluble and phenolicOHCs. This demonstrates the importance of integrating the com-plex mixture of contaminants when assessing TH-related effectsin wildlife. It is possible that the PLS models herein reflect the mul-ti-level interactions of OHCs and their metabolites on the HPT axisin hooded seals. These compounds might act in combination, withadditive or even synergistic effects as shown in vivo for several ofthe OHCs reported in the present study (Hallgren and Darnerud,2002; Wade et al., 2002; Crofton et al., 2005; Gauger et al.,2007). Other contaminants such as mercury and perfluoroalkylsubstances might also be present in the sampled seals and thesecompounds could also act on the HPT axis (Kim et al., 2011; Knottet al., 2011; Bytingsvik et al., 2012a,b). In the present study we fo-cused on the compounds that are most commonly reported to beassociated with TH disruption in wildlife (e.g. Braathen et al.,2004; Routti et al., 2010; Letcher et al., 2010). Future studies ofTH disruption in wildlife should attempt to account for the fullcomplexity of environmental contaminants in their subjectspecies.
TT3:FT3 ratios in hooded seal pups were positively associatedwith b-HCH, a-HCH, HCB, PCB-118 and many low to medium-chlo-rinated ortho-PCBs (e.g. PCB-52, -141, -110, -149), as well as CHLs(especially oxychlordane and cis-nonachlor) and DDTs (p,p’-DDT,
p,p’-DDE, and p,p’-DDD). Thus, increasing levels of these contami-nants seem to be linked to a lowered free T3 fraction relative tothe bound T3 fraction in the blood. In contrast, TT3:FT3 ratios inmothers were mostly negatively associated with these OHCs, ex-cept for DDTs which were positively associated with TT3:FT3 inboth mothers and pups (Figs. 1a and b and 2a and b). Furthermore,DDTs and particularly p,p’-DDE, appeared to be more important forTT3:FT3 ratios in mothers than in pups, whereas HCB and PCB-118seemed to be more important in pups (Figs. 1c and 2c). The impor-tance of p,p’-DDE levels for TH homeostasis has been reported in
G.D. Villanger et al. / Chemosphere 92 (2013) 828–842 839
polar bears from East Greenland (adult females) and Svalbard (cor-rected for age and sex) and also in a study of adult men and women(Skaare et al., 2001; Langer et al., 2007; Villanger et al., 2011a).
b-HCH was the most important OHC with respect to explainingTT3:FT3 ratios in hooded seal pups (Figs. 2c and 4b). This is inaccordance with human studies where prenatal b-HCH exposurewas suggested to affect TH homeostasis in newborns and youngchildren (Ribas-Fito et al., 2003; Alvarez-Pedrerol et al., 2008a,b).Although b-HCH is a commonly found insecticide in biota, thereis a lack of knowledge about its toxic effects in wildlife and hu-mans. The results of the present study add to the weight of evi-dence that suggest that b-HCH might affect TH-balance in youngmammals. This subject warrants further investigation.
PBDE-99 levels were highly correlated with TT4:FT4 ratios inpups (Figs. 3b and c, and 4c). Other PBDEs (e.g. PBDE-100 and-153), high-chlorinated PCBs and 4-OH-CB107 were also positivelyassociated with TT4:FT4 in the PLS model, but with less importancethan PBDE-99 (Fig. 3c). When focusing only on OH-PCBs, Gabriel-sen et al. (2011) reported a negative association between 4-OH-CB107 and FT4:FT3. But, when assessing the effects of the morecomplex OHC mixture in the current study, other contaminants,particularly PBDE-99, appeared to be more important for T4-bal-ance than 4-OH-CB107 (Fig. 3b and c). This coincides with theknown thyroid disruptive abilities of PBDEs, especially the moretoxic penta-BDE-99 and-100 (Darnerud et al., 2001; Darnerud,2003; Hamers et al., 2006). Similar associations between PBDEs(particularly PBDE-99 and -100) and THs have been reported innewborn children (Herbstman et al., 2008; Roze et al., 2009), sub-adult polar bears (Villanger et al., 2011a) and beluga whales(subadults and adult males; Villanger et al., 2011b), as well as inrodent in vivo studies (Eriksson et al., 2001; Darnerud, 2003; Kuriy-ama et al., 2005). Hall et al. (2003) reported a positive correlationbetween RPBDEs in blubber and circulating TT4 levels in weanedgrey seal (Halichoreus grypus) pups, with a concurrent positive cor-relation between RPBDEs in blubber and circulating albumin andcholesterol concentrations. It was suggested that the positive rela-tionship between TT4 and RPBDEs may be related to increased lev-els of TH binding proteins in the blood (Hall et al., 2003). Thesimilar findings in the present study of hooded seal pups, withan increased fraction of bound T4 relative to the free T4 fractionin blood associated with increased plasma PBDE levels, lends fur-ther support to earlier findings.
Sex-specific differences in TH responses to OHC exposure, asfound for TT4:FT4 ratio in pups herein, have been reported in hu-man, experimental and wildlife studies (Braathen et al., 2004;Gochfeld, 2007; Abdelouahab et al., 2008; Villanger et al., 2011a).In addition to the influence of sex hormones, sex-dependent expo-sure and genetics (e.g. CYP enzymes) can cause sex-specific differ-ence in toxicokinetics and toxicodynamics, and thus toxicresponses to xenobiotics. Sex-specific responses to toxicants canalready be manifested in foetuses (Mugford and Kedderis, 1998;Gochfeld, 2007; Vahter et al., 2007). These findings, including thoseof the present study, show the importance of including sex as apossible confounding variable when assessing the relationships be-tween OHCs and THs, even in early stages of development.
Effects of other biological factors on THs, such as pup age, plas-ma lipid% and BM, were difficult to discern from potential effectscaused by OHCs on TH homeostasis, although biological factorshave been shown to be important for TH status in other contami-nant studies conducted on seal mothers and pups (Hall et al.,2003; Sørmo et al., 2005; Hall and Thomas, 2007). Differences inphysiology (e.g. lipid metabolism) and blood biochemistry (e.g. li-pid constituents) between lactating, fasting hooded seal femalesand their suckling, growing pups (Lydersen et al., 1997; Boilyet al., 2006) probably cause differences in toxicokinetics and toxi-codynamics of OHCs. The opposite relationships between the same
compounds (b-HCH, a-HCH, HCB, low to medium-chlorinatedortho-PCBs; Fig. 4a and b) and TT3:FT3 ratios in mothers and pups(Figs. 1 and 2), respectively, might be due to differences in toxic-okinetics of OHCs between these two groups. But, these less lipo-philic OHCs have been shown to be more easily liberated frommaternal blubber to blood and thus become incorporated intomilk, resulting in a relatively higher transfer rate to the pups thanthe more lipophilic OHCs (Sørmo et al., 2003; Wolkers et al., 2006).This could alternatively explain the apparently opposing results inpups and mothers with respect to these OHCs. Whatever thesource of the differences between pups and mothers, the fact thatmany of these compounds were identified as important predictorsfor the TT3:FT3 ratios in both hooded seal mothers and their pups,can be considered to be a strong indication of their influence onthyroid properties.
The contaminants identified as potential TH disrupters in thepresent study may have the ability to act on one or several differ-ent target-points in the HPT axis, possibly with overlappingmechanisms and thus there is a potential for combined effects.PBDE-99 and other PBDEs, as well as several HCB and PCBs,may induce uridin diphosphate glucoronyltransferase (UDPGT),thus increasing biliary excretion of T4 which in turn will lowercirculating T4 levels (Vanraaij et al., 1993; Hallgren et al., 2001;Zhou et al., 2001). DDTs, ortho-PCBs and CHLs may induce deio-dinase 1 level/activity in extra-thyroidal tissues resulting in in-creased conversion of T4 to T3 (Kato et al., 2004; Sakai et al.,2009; Routti et al., 2010). Potential mechanisms of disruption ofTH balance by OH-PCBs in pups could include TTR-binding orinterfering with deidoinases or sulfotransferases (see Gabrielsenet al., 2011). Sulfotransferases assist sulfation which is importantin inactivation and excretion of THs and may be essential for reg-ulating free levels of TH, especially FT3 levels, during foetal devel-opment (Santini et al., 1992; Visser, 1994; Schuur et al., 1998).Many OH-PCBs have been reported to inhibit TH sulfationin vitro (Schuur et al., 1999). This particular mechanism has beensuggested as an explanation for the associations between ROH-PCBs in umbilical cord plasma and TH levels in human newborns(Otake et al., 2007). It is therefore possible that this mechanism isrelevant for explaining the decreased levels of FT3 relative to TT3associated with increasing circulating OH-PCBs levels in the sealpups in this study.
The similarities between the PLS modelled responses of TT3:FT3to plasma OHC levels in both hooded seal mothers and pups ismost likely due to similarities in their contaminant exposures. Dis-turbances of maternal TH homeostasis might also directly affect THlevels in foetuses and neonates (Brouwer et al., 1998; Pop et al.,1999, 2003; Miodovnik, 2011). Thus, the results in the presentstudy may also indicate a linked thyroid disruption between themothers and their offspring. But, there is little knowledge regard-ing how maternal and foetal/neonatal TH levels are co-regulated(McNabb, 1992; Brouwer et al., 1998; Ahmed et al., 2008). Themost important contaminants associated with TH balance inhooded seal mothers and pups (e.g. ortho-PCBs, PCB-118, DDTs,HCHs, CHLs, HCB, PBDE-99), have also been associated with mater-nal TH homeostasis in humans and linked to effects on TH balanceas well as neurodevelopment in human newborns and children(Nagayama et al., 1998, 2007; Ribas-Fito et al., 2003; Alvarez-Pedr-erol et al., 2008a,b; Roze et al., 2009; Herbstman et al., 2010). Be-cause effects on TH homeostasis in foetuses or neonates can bemanifested in later life stages (Arena et al., 2003; Kuriyama et al.,2005, 2007; Alvarez-Pedrerol et al., 2008b; Langer et al., 2008;Kirkegaard et al., 2011), TH disruption and health-effects in thehooded seal pups might become more apparent with increasingage. Additionally, pups of this species fast for 4–6 weeks followingweaning and will utilise energy stored in blubber lipids during thistime (Bowen et al., 1987; Lydersen et al., 1997). This will liberate
840 G.D. Villanger et al. / Chemosphere 92 (2013) 828–842
lipid-soluble OHCs stored in blubber into the circulation, with in-creased risk of TH-related effects in weaned hooded seal pups.
5. Conclusion
The multivariate regression models used in this study revealedthat TT3:FT3 ratios in nursing hooded seal pups were negativelyassociated with many OH-PCBs, particularly 3’-OH-CB138. In thesepups, TT3:FT3 was correlated positively with b-HCH and alsoa-HCH, PCB-118, ortho-PCBs (e.g. PCB-52, 141, 149), CHLs andDDTs. Similar combinations of chemicals (except for the OH-PCBs),seemed to vary with maternal TT3:FT3 ratios, mostly in a negativedirection. In pups, TT4:FT4 ratios were positively associated withknown TH disruptive contaminants (e.g. PBDE-99 and 4-OH-CB107). Sex was also an important determinant for TT4:FT4 inpups. TT4:FT4 ratios were not associated with contaminants exam-ined in hooded seal mothers. The present study has demonstratedthe importance of including the fullest possible OHC mixture (li-pid-soluble and phenolic metabolites) found in wild animals whenassessing potential effects on TH-homeostasis. OHC mixtures likelyhave multiple target points in the HPT axis and thus there is poten-tial for combined effects. The similarities between the PLS mod-elled responses of TT3:FT3 to plasma OHC levels in both hoodedseal mothers and pups are most likely explained by comparableexposure patterns, but it is also possible that their TH responsescould be interconnected. The contaminants suggested by statisticalmodelling to interfere with TH ratios in hooded seal mother–puppairs are chemicals that have been shown to affect TH homeostasisand possibly neurodevelopment in human newborns and children.
Acknowledgements
The field sampling for this study was conducted within theInternational Polar Year (2007–2008) project ‘‘Marine MammalExploration of the Oceans Pole to Pole’’ (MEOP) lead by the Norwe-gian Polar Institute and financed by the Norwegian Research Coun-cil. The study was also financed by the Norwegian University ofScience and Technology and the Norwegian School of VeterinarySciences. The authors thank the crew of RV Lance, Lutz Bachmann,Jørgen Berge, Øystein Wiig, Hans Wolkers and Renè Swift for assis-tance in the field and note the partnership of Dr. Tore Haug of theMarine Research Institute in the broader MEOP research pro-gramme. We also thank Grethe Stavik Eggen at the Departmentof Biology at the Norwegian University of Science and Technologyfor assistance during thyroid hormone analyses, and Katharina B.Løken and the rest of the staff at the Laboratory of EnvironmentalToxicology, Norwegian School of Veterinary Science, for assistancewith the contaminant analyses.
Appendix A. Supplementary material
Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.chemosphere.2013.04.036.
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