Relative Effect Potency Estimates of Dioxin-like Activity for Dioxins, Furans, and Dioxin-like PCBs in Adults Based on Two Thyroid Outcomes

Slovak Medical University, Bratislava, Slovakia.
Environmental Health Perspectives (Impact Factor: 7.98). 05/2013; 121(8). DOI: 10.1289/ehp.1205739
Source: PubMed
Background: Toxic equivalency factors (TEFs) are an important component in the risk assessment of dioxin-like human exposures. At present, this concept is based mainly on in vivo animal experiments using oral dosage. Consequently, the current human TEFs derived from mammalian experiments are applicable only for exposure situations in which oral ingestion occurs. Nevertheless, these “intake” TEFs are commonly—but incorrectly—used by regulatory authorities to calculate “systemic” toxic equivalents (TEQs) based on human blood and tissue concentrations, which are used as biomarkers for either exposure or effect.
Objectives: We sought to determine relative effect potencies (REPs) for systemic human concentrations of dioxin-like mixture components using thyroid volume or serum free thyroxine (FT4) concentration as the outcomes of interest.
Methods: We used a benchmark concentration and a regression-based approach to compare the strength of association between each dioxin-like compound and the thyroid end points in 320 adults residing in an organochlorine-polluted area of eastern Slovakia.
Results: REPs calculated from thyroid volume and FT4 were similar. The regression coefficient (β)-derived REP data from thyroid volume and FT4 level were correlated with the World Health Organization (WHO) TEF values (Spearman r = 0.69, p = 0.01 and r = 0.62, p = 0.03, respectively). The calculated REPs were mostly within the minimum and maximum values for in vivo REPs derived by other investigators.
Conclusions: Our REPs calculated from thyroid end points realistically reflect human exposure scenarios because they are based on chronic, low-dose human exposures and on biomarkers reflecting body burden. Compared with previous results, our REPs suggest higher sensitivity to the effects of dioxin-like compounds.


Available from: Kinga Lancz, Jan 27, 2015
volume 121
number 8
August 2013
Environmental Health Perspectives
All EH P content is accessible to individuals with disabilities. A fully accessible (Section 508compliant)
HTML version of this article is available at
Polychlorinated dibenzo-p-dioxins (PCDDs,
dioxins), polychlorinated dibenzofurans
(PCDFs, furans), and polychlorinated biphe-
nyls (PCBs) are ubiquitous environmental
compounds. PCDDs and PCDFs are com-
bustion or industrial by-products with no
commercial use, whereas PCBs have been
frequently used in a variety of commercial
applications, such as coolants and lubricants
in transformers, capacitors, and other electri-
cal equipment. Some PCBs act in a manner
mechanistically similar to that of 2,3,7,8-tetra-
chloro dibenzo-p-dioxin (TCDD); these PCBs
are usually referred to as dioxin-like PCBs
(DL-PCBs). PCDDs, PCDFs, and PCBs are
commonly found in mixtures in the environ-
ment and human food chain, usually contain-
ing a large number of congeners, such that
each mixture has its own degree of dioxin-
like toxicity. For risk assessment purposes, the
World Health Organization (WHO) assigned
each of these individual compounds a toxic
equivalency factor (TEF) value relative to
the toxicity of TCDD (Van den Berg et al.
2006). This factor indicates a relative toxic-
ity compared to the most toxic con gener,
TCDD, which is given a reference value
of 1. Prerequisites for this TEF concept are
the exclusive inclusion of toxic effects that are
mediated via the aryl hydrocarbon receptor
(AhR) and an additive mechanism of action
for mixtures of these compounds. Otherwise,
mediated toxic effects of PCDDs, PCDFs, and
PCBs cannot be quantified for risk assessment
by this method.
e reevaluation of TEF values for these
compounds has become a continuous process
based on available results from in vivo and
in vitro studies. Although many studies using
human cell lines or primary cells have been
published to date (Haws et al. 2006), human
in vivo data that may contribute to the TEF
concept have not been published previously.
In an attempt to fill this gap, we examined
cross-sectional data on thyroid impairment in
a population exposed to a mixture of organo-
chlorines to identify relationships between
individual mixture components and thyroid
volume and free thyroxine (FT
). Based on
these results, we estimated the relative poten-
cies (REPs) of PCDD, PCDF, and DL-PCB
congeners in adult humans.
Materials and Methods
Participants. Our initial sample of 2,047
adults was drawn from a population living
in the towns and villages of the Michalovce,
Svidnik, and Stropkov districts in eastern
Slovakia, an area known to be contaminated
by a mixture of organo chlorines (Jursa et al.
2006; Langer et al. 2007c; Petrik et al. 2006).
Adult participants were recruited between
August 2001 and February 2002 with the help
of primary care physicians, who randomly
selected names from alphabetical lists of their
patients; nearly all those approached agreed to
participate. We have complied with all appli-
cable requirements of U.S. and international
and national regulations. e study protocol
was approved by the institutional review board
of the Slovak Medical University. All human
participants gave written informed consent
prior to the study.
Address correspondence to T. Trnovec, Slovak
Medical University, Limbová 12, 83303 Bratislava,
Slovakia. Telephone: 4212 59370225. E-mail:
Supplemental Material is available online (http://
We acknowledge L.L. Aylward (Summit
Toxicology, Falls Church, VA) for suggestions and
ideas in the initial stages of our research.
is work was supported by the European Union
(EU) 5th Framework Programme, project PCBRISK
(Evaluating Human Health Risk from Low-dose and
Long-term PCB Exposure; QLK4-CT-2000-00488);
the EU 7th Framework Programme project SYSTEQ
[e Development, Validation and Implementation
of Human Systemic Toxic Equivalencies (TEQs)
as Biomarkers for Dioxin Like Compounds; grant
FP7-ENV-226694]; and the Competence Center for
SMART Technologies for Electronics and Informatics
Systems and Services, ITMS 26240220072, funded by
the Research & Development Operational Programme
from the ERDF and Scientific Grant Agency VEGA
(Bratislava, Slovakia), grant 1/0120/12. is research
also received support from the Intramural Research
Program of the National Institute of Environmental
Health Sciences, National Institutes of Health.
e authors declare they have no actual or potential
competing financial interests.
Received 10 July 2012; accepted 1 May 2013.
Relative Effect Potency Estimates of Dioxin-like Activity for Dioxins, Furans,
and Dioxin-like PCBs in Adults Based on Two Thyroid Outcomes
Tomáš Trnovec,
Todd A. Jusko,
Eva Šovˇcíková,
Kinga Lancz,
Jana Chovancová,
Henrieta Patayová,
Beata Drobná,
Pavel Langer,
Martin Van den Berg,
Ladislav Dedik,
and SoˇnaWimmerová
Slovak Medical University, Bratislava, Slovakia;
Epidemiology Branch, National Institute of Environmental Health Sciences, National
Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA;
Institute of Experimental
Endocrinology, Slovak Academy of Sciences, Bratislava, Slovakia;
Institute for Risk Assessment Sciences, Utrecht University, Utrecht,
the Netherlands;
Faculty of Mechanical Engineering, Slovak University of Technology in Bratislava, Bratislava, Slovakia
Background: Toxic equivalency factors (TEFs) are an important component in the risk assess-
ment of dioxin-like human exposures. At present, this concept is based mainly on in vivo animal
experiments using oral dosage. Consequently, the current human TEFs derived from mammalian
experiments are applicable only for exposure situations in which oral ingestion occurs. Nevertheless,
these “intake” TEFs are commonly—but incorrectly—used by regulatory authorities to calculate
“systemic” toxic equivalents (TEQs) based on human blood and tissue concentrations, which are
used as biomarkers for either exposure or effect.
oBjectives: We sought to determine relative effect potencies (REPs) for systemic human concen-
trations of dioxin-like mixture components using thyroid volume or serum free thyroxine (FT
concentration as the outcomes of interest.
Methods: We used a benchmark concentration and a regression-based approach to compare
the strength of association between each dioxin-like compound and the thyroid end points in
320 adults residing in an organochlorine-polluted area of eastern Slovakia.
results: REPs calculated from thyroid volume and FT
were similar. e regression coefficient
(β)-derived REP data from thyroid volume and FT
level were correlated with the World Health
Organization (WHO) TEF values (Spearman r = 0.69, p = 0.01 and r = 0.62, p = 0.03, respectively).
The calculated REPs were mostly within the minimum and maximum values for in vivo REPs
derived by other investigators.
conclusions: Our REPs calculated from thyroid end points realistically reflect human exposure
scenarios because they are based on chronic, low-dose human exposures and on biomarkers reflecting
body burden. Compared with previous results, our REPs suggest higher sensitivity to the effects of
dioxin-like compounds.
key words: dioxin-like polychlorinated biphenyl (DL-PCB), free thyroxine (FT
), polychlorinated
dibenzo-p-dioxins (PCDDs), polychlorinated dibenzo-p-furans (PCDFs), relative effect potency
(REP), thyroid volume, toxic equivalency factor (TEF).
Environ Health Perspect 121:886–892 (2013). [Online
10 May 2013]
Page 1
Relative effect potencies of dioxin-like compounds
Environmental Health Perspectives
volume 121
number 8
August 2013
Although we did not collect data on
place of birth, we assumed that all partici-
pants spent most of their adult life residing
in these districts, which is in agreement with
low labor mobility in Slovakia. Individuals
having a mild, chronic controlled illness
(e.g., rheumatic diseases, hypertension, dia-
betes, thyroid disorders, non-morbid obesity,
allergy) were not excluded from the study. At
enrollment, partici pants were given a physical
examination by our field medical staff, and
socio demographic and medical questionnaires
were completed (Langer 2010; Langer et al.
2006, 2007a, 2007b, 2007c, 2008; Rádiková
et al. 2008; Ukropec et al. 2010).
Whole blood samples were collected from
fasting participants into anticoagulant-free
Vacutainer™ tubes (S-Monovette; Sarstedt,
Nürnberg, Germany); after clotting, samples
were centrifuged at 3,000 rpm for 15 min.
e serum was frozen in glass vials and stored
at –18°C.
Chemical analyses. Of the 2,047 adults
selected, 320 were willing to provide 90 mL
of blood for analysis of PCDDs, PCDFs,
and PCBs. The serum samples were treated
using a modified version of the method by
Turner et al. (1994). Each thawed serum
sample (5–30 mL) was spiked with
labeled standards [15 2,3,7,8-substituted
PCDDs/PCDFs, 12 DL-PCBs, and 11
non-dioxin-like (NDL)-PCBs (Cambridge
Isotope Laboratories Inc., Andover, MA,
USA; Wellington Laboratories Inc., Ontario,
Canada)] 24 hr before sample processing. After
the serum was treated with diluted formic
acid, the analytes were isolated by solid phase
extraction using a 10-g C18 column (UCT
Inc., Bristol, PA, USA). A hexane extract was
cleaned on a Power-PREP™ semi automated
clean-up system (FMS Inc., Waltham, MA,
USA) with prepacked disposable silica,
alumina, and carbon columns. A combined
dichloromethane/n-hexane (2:98, vol/vol) and
dichloromethane/n-hexane (50:50, vol/vol)
eluate fraction contained mono-ortho and
NDL-PCBs. A toluene eluate fraction
contained PCDDs/PCDFs and non-ortho
PCBs. e eluate fractions were concentrated
and then diluted with
-labeled recovery
We used an HP 6890 Plus gas chromato-
graph (Hewlett-Packard, Palo Alto, CA,
USA) coupled with an MAT 95XL mass
spectrometer (Thermo Finnigan, Bremen,
Germany) operating at a 10% valley resolu-
tion of 10,000 in the selected ion moni-
toring mode to identify and measure
2,3,7,8-substituted PCDDs/PCDFs and
PCBs. PCDD/PCDF and non-ortho-
PCB con geners were separated on a 30 m
× 0.25 mm × 0.25 µm DB-5ms capillary
column (J&W Scientific, Folsom, CA, USA),
and mono-ortho and NDL-PCB congeners
were separated on a 60 m × 0.25 mm
× 0.25 µm DB-5ms capil lary column (J&W
Scientific). The qualita tive and quantitative
analyses were carried out using U.S.
Environmental Protection Agency (EPA)
isotope dilution methods 1613 (U.S. EPA
1994) and 1668 (U.S. EPA 1999). Two
congeners [1,2,3,7,8,9-hexa chlorinated CDF
(HxCDF) and PCB 77] were not included
in the statistical analysis: 1,2,3,7,8,9-HxCDF
because concentrations were below the limit
of detection (LOD; 0.22–3.1 pg/g lipid) in all
analyzed samples, and PCB 77 because of high
background levels in laboratory blanks.
All analytical measurements were car-
ried out at the National Reference Centre
for Dioxins and Related Compounds
(Department of Toxic Organic Pollutants,
Slovak Medical University), which has been
certified by the Slovak National Accreditation
Service (ISO/IEC 17 025:2005, certifica-
tion No. S-111) and regularly participates in
inter laboratory studies and proficiency tests
on dioxins and PCBs in food and feed. Each
analysis batch consisted of 14 serum samples,
1 method blank, and 1 quality control (QC)
sample (porcine serum spiked with native
PCDD, PCDF, and PCB congeners as an
in-house reference material). Certified human
serum [SRM (standard reference mate-
rial) 1589a; National Institute of Standards
and Technology, Gaithersburg, MD, USA]
was analyzed in each third batch (Kočan et al.
2004). Control charts were plotted for QC
samples, blanks, and verification calibration
standards to check accuracy, precision, and
reliability of the analytical process.
We used an enzymatic method based on
the determination of total cholesterol, free
cholesterol, phospholipids, and tri glycerides
(Akins et al. 1989) to determine total lipids
in all of the serum samples analyzed. We used
these values to present the organo chlorine
concentrations on a lipid weight basis.
Assessment of thyroid outcomes. yroids
were examined and measured using a por-
table Sonoline SI-400 diagnostic ultra sound
device (Siemens, North Rhine-Westphalia,
Germany) with a 7.5-MHz linear transducer.
For thyroid measurement, each participant
lay supine with the neck hyper extended.
e thyroid volume (in milli liters) for each
lobe was calculated according to the fol-
lowing ellipsoid formula: width (in centi-
meters) × length (in centi meters) × thickness
(in centi meters) × a correction factor of
0.479 (Brunn et al. 1981). All measure-
ments were performed by the same physi-
cian who had long-term experience in field
surveys and clini cal ultrasound diagnostics.
e physician was unaware of toxicant con-
centrations among participants. We estimated
the intra observer variation as described by
(Ozgen et al. 1999) using three separate
measurements of 50 thyroid volumes (repre-
senting 50 participants) that ranged from 3.0
to 20.5 mL; the mean ± SD was 3.9 ± 3.5%,
and the median was 6.2 mL.
was determined in stored serum
specimens using an automated electro-
chemiluminescent immuno assay system
(Elecsys system; Roche, Basel, Switzerland), as
described previously (Langer et al. 2005).
Statistical analysis. We used two
approaches to estimate the relative potencies
of individual components of the mixture.
e first approach, as suggested previously by
Fattore et al. (2004) and Yang et al. (2010),
was based on a comparison of benchmark
concentrations (BMCs) calculated for thy-
roid outcomes as a function of organo chlorine
serum concentrations. e second approach
was based on comparing the magnitude of
the regression coefficient (β) for thyroid vol-
ume or FT
serum concentration regressed
on the serum concentration of the individ-
ual congeners, simi lar to the study by Brown
et al. (2001). Participant’s sex and age at
blood draw, as well as PCDDs, PCDFs, and
PCBs determined in the exposure mixture
were potential confounders. us, in multi-
variable regression to calculate REPs, we
adjusted for sex, age, and presence of other
organochlorines. For confirmation of TCDD
as an index (reference) congener (U.S. EPA
2000), we used multiple regression with
backward elimination (variable removal at
p > 0.1). We compared the REPs resulting
from both approaches with published data on
REPs for DLCs (Haws et al. 2006) and with
WHO-TEF values (Van den Berg et al. 2006).
Estimation of REPs through comparison
of BMCs. For each individual PCDD, PCDF,
and DL-PCB congener, we calculated the
BMC (Crump 1995) for thyroid volume
and FT
serum concentration end points,
using CTDB_BMD software (Dedik 2012).
We adjusted for sex and age in all statistical
models. The BMCs for changes in thyroid
volume and serum FT
associated with
TCDD concentration were compared with
the BMCs of individual congeners and used
to derive the congener-specific REPs. Thus,
is the relative potency
) for the ith congener, relative to TCDD.
Estimation of REPs through comparison of
regression coefficients. We calculated the regres-
sion coefficient (β) for each congener from all
concentration data > LOD. We considered sex
and age, along with PCDD, PCDF, and PCB
congeners identified in the mixture, as con-
founding variables. We calculated the BMCs
for the most probable combinations of con-
founders [see Supplemental Material, Table S1
( for
a list of those with the greatest influence on
BMCs]. However, because the addition of
other organo chlorines had negligible influence
Page 2
Trnovec et al.
volume 121
number 8
August 2013
Environmental Health Perspectives
on model data, we present results with adjust-
ment only for age and sex. The REPs of the
individual congeners were calculated as the
ratio of β coefficient obtained for the ith con-
gener to βcoefficient for TCDD: β
Participant characteristics. The subgroup
of 320 participants with complete data con-
sisted of 203 males 44.9 ± 11.47 years
of age (mean ± SD; median, 48 years) and
127 females 47.3 ± 9.24 years of age (median
48 years), with an overall mean age of
45.8 ± 10.7 years (median, 48 years). Among
males, the age range was 20–75 years, and in
females 21–70 years. e median and mean
serum concentrations (in picograms WHO
TEQ per gram lipid) of DLCs in these partici-
pants are shown in Supplemental Material,
Table S2 (
ehp.1205739). Data on mean and median
serum concentrations of PCDDs, PCDFs,
DL-PCB congeners, and the most abun-
dant NDL-PCB congeners from samples
with concentrations > LOD are shown in
Supplemental Material, Table S3. e median
concentrations of individual congeners with
concentrations > LOD correlated with median
concentrations over lapping with TCDD
> LOD (r = 0.998). Thus, we assumed that
parameters calculated from samples over-
lapping with TCDD > LOD well represent
those from samples > LOD.
For males and females, the mean (± SD)
of volume of the thyroid gland were
11.56 ± 4.42 mL (median, 10.20) and
9.49 ± 4.75 mL (median, 8.35), respectively.
Mean (± SD) serum concentrations of FT
males and females were 16.93 ± 2.65 pmol/L
(median, 16.7) and 15.72 ± 3.22 pmol/L
(median, 15.39), respectively.
Identification of the index congener. ere
is general agreement that an index compound
should be the most well-studied member of
its class and that it should provide the largest
body of acceptable scientific data (U.S. EPA
2000). At the same time, an index chemical
should be potent with regard to the expected
end point. We used multiple regression with
backward elimi nation to query the selection
of TCDD as the index congener in concur-
rence with other PCDD or PCDF congeners.
We created four models (A–D) for this pur-
pose. When we entered thyroid volume as the
dependent variable and concentrations of the
seven most toxic PCDD congeners [TCDD,
1,2,3,7,8-penta chlorinated CDD (PeCDD),
1,2,3,4,7,8-HxCDD, 1,2,3,6,7,8-HxCDD,
1,2,3,7,8,9-HxCDD, 1,2,3,4,6,7,8-hepta-
chlorinated CDD (HpCDD), and octa-
chlorinated CDD (OCDD)] as independent
variables, cross-tabulation for samples > LOD
reduced the number of individuals to an insuf-
ficient 25. If we omitted the two HxCDD
congeners with relatively low concentra-
tions (1,2,3,4,7,8-HxCDD and 1,2,3,7,8,9-
HxCDD), the study population increased
to 62 individuals. Model A showed that
with respect to thyroid volume reduction,
TCDD was the most potent congener [see
Supplemental Material, Table S4 (http://]. In
model D, with FT
as the end point of inter-
est, multiple regression eliminated four PCDF
congeners when they were combined with
TCDD (see Supplemental Material, Table S4).
However, multiple regression did not confirm
the role of TCDD with FT
as the dependent
variable and PCDD congeners as the indepen-
dent variable (see Model B in Supplemental
Material, Table S4) or with thyroid volume as
the dependent variable and PCDF congeners
as the independent variable (see Model C in
Supplemental Material, Table S4).
Assessment of REPs for PCDDs, PCDFs,
and DL-PCBs. Data in Table 1 show that
PCDDs were associated with a decrease in
both thyroid volume and FT
level. e asso-
ciation between thyroid volume and diox-
ins decreased with the increasing number of
chlorine substitutes in the compound, except
for 1,2,3,7,8,9-HxCDD. The PCDFs were
associated with a decrease in thyroid volume
in a similar manner except for two com-
pounds (1,2,3,4,7,8-HxCDF and OCDF).
With respect to FT
, we observed a mixed
response: There was a negative association
with 2,3,7,8-tetraCDF (TCDF), 2,3,4,7,8-
PeCDF, 1,2,3,4,6,7,8-HpCDF, and OCDF
and a positive association with 1,2,3,7,8-
PeCDF and the three HxDF congeners
(1,2,3,4,7,8-HxCDF, 1,2,3,6,7,8-HxCDF,
and 2,3,4,6,7,8-HxCDF). e DL-PCBs were
related to an increase in both thyroid volume
and FT
serum level, except for the non-
ortho-substituted congener PCB 81 for both
thyroid volume and FT
and the mono-ortho-
substituted congener PCB 105 for FT
. Of
all the congeners, TCDD was most strongly
associated with a decrease of thyroid volume
and FT
level. NDL-PCBs were associated
with slight changes, compared with TCDD,
appearing as increases with the most abundant
PCB congeners [see Supplemental Material,
Table S5 (
ehp.1205739)]. To comply with the assump-
tion that congeners have a similar mode of
action (U.S. EPA 2000), we calculated the
REPs only for those acting in the same direc-
tion as the index chemical. us, congeners
associated with an increase of thyroid volume
or FT
level were not further analyzed.
Sex and age were included as confound-
ers (confounders 1 and 2) in all analyses. To
assess the effect of confounding by other DLC
congeners identified in the exposure mixture
coefficients, we computed BMCs for
thyroid volume decrease related to the serum
concentration of individual congeners and
entered the various combinations of congener
confounders. We set both p
(the background
risk at zero concentration) and benchmark
response (BMR) at 0.1, which translates to an
increase in risk of 200% (Crump 1995). Based
on the Akaike information criterion, we used
these two regression models: f (t) = a
+ a
and f (t) = a
+ a
We observed that the BMC and the BMC
lower confidence limit (BMCL) for TCDD
were slightly influenced by the presence
of other congeners in the exposure mixture
[see Supplemental Material, Table S1, con-
founders 3–6 (
ehp.1205739)]. In addition, when TCDD
was entered as a confounder in combination
with other congeners (e.g., with the second
most potent congener, 1,2,3,7,8-PeCDD),
we obtained similar results. Neither of these
adjustments for PCB congeners affected the
BMC and BMCL value of TCDD. erefore,
in Table 1, we present REPs that were derived
after adjusting only for sex and age.
e REPs in Table 1 were calculated as the
relation of the individual congener β
of to the β
, or
, respectively, of the index chemi-
cal. e REPs calculated using β coefficient,
BMC, and BMCL data correlated strongly
between themselves (all r-values were > 0.903,
p < 0.0001). Moreover, we observed a strong
correlation between the REPs calculated from
the largely independent thyroid volume and
data. The Spearman correlations (r
for REPs were derived from thyroid volume
and FT
data using the β
= 0.81,
p = 0.015), BMC (r
= 0.786, p = 0.021), and
= 0.857, p = 0.007) approaches.
As shown in Figure 1, the β coefficient–
derived REP data for thyroid volume and
level (β
column in Table 1)
correlated significantly with the WHO TEF
values (Van den Berg et al. 2006) (thyroid vol-
ume, r
= 0.693, p = 0.009; FT
, r
= 0.616,
p = 0.033), The best fit is logREP = 0.566,
logTEF = –0.229 for thyroid volume and
logREP = 0.363, logTEF = –0.399 FT
According to our estimates, the potencies of
congeners above the central axis are greater
than the TEFs, and vice versa. e BMC- and
BMCL-derived REP data correlated less sig-
nificantly with the WHO TEF values (data
not shown).
To show our REPs in a broader con-
text, we included in Table 1 the minimum,
maximum, and median values published for
in vivo REPs in the REP
database (see
Table 8 of Haws et al. 2006). Our REPs for
all PCDD congeners studied and thyroid vol-
ume outcome [note that data on 1,2,3,6,7,8-
HxCDD were not included by Haws et al.
(2006)], irrespective of the method of
derivation, are between the maximum and
Page 3
Relative effect potencies of dioxin-like compounds
Environmental Health Perspectives
volume 121
number 8
August 2013
minimum values estimated by other research-
ers, except for those of OCDD. Our REPs
for 1,2,3,4,7,8-HxCDD and 1,2,3,7,8,9-
HxCDD, where FT
is the outcome, were
higher than the published maximum esti-
mates (Haws et al. 2006). Of the three REP
values (β
, BMCL, and BMC) for
1,2,3,4,6,7,8-HpCDD, the β
(0.029) is smaller than the published maxi-
mum estimate (0.035) (Haws et al. 2006).
For PCDF congeners associated with thyroid
volume, the REPs were close to the maxi-
mum values determined by other investiga-
tors, except for 2,3,4,7,8-PeCDF, which is
higher than the minimum reported value of
0.0065 (Haws et al. 2006). We calculated
REPs for four PCDF congeners with FT
as an outcome; for two of them (2,3,7,8-
TCDF and 1,2,3,4,6,7,8-HpCDF), values
were unavailable for comparison. However,
the REP for 2,3,4,7,8-PeCDF fits within
the range published by Haws et al. (2006),
whereas the REP for OCDF is an outlier with
regard to TEFs.
When analyzing the relative magni-
tude of thyroid effects of PCB congeners,
we included both DL-PCB and NDL-PCB
congeners. Figure 2 shows plotted β val-
ues for PCB congeners for thyroid volume
against those for FT
serum level shown in
Table 1 [see also Supplemental Material,
Table S5 (
ehp.1205739)]. The β-coefficients for the
Table1. The calculated REPs of PCDD, PCDF, and DL-PCB congeners.
Congener n
Thyroid volume FT
BMC Minimum Median Maximum
2,3,7,8-TCDD 70 –1.101 1 1 1 –0.508 1 1 1 1
1,2,3,7,8-PeCDD 132 –0.45 0.432 0.143 0.325 –0.24 0.471 0.907 0.847 1 0.044 0.4 1.5
1,2,3,4,7,8-HxCDD 81 –0.283 0.257 0.237 0.332 –0.409 0.805 1.413 0.981 0.1 0.0076 0.059 0.35
1,2,3,6,7,8-HxCDD 286 –0.091 0.082 0.049 0.085 –0.064 0.126 0.238 0.256 0.1
1,2,3,7,8,9-HxCDD 76 0.146 –0.245 0.482 1.603 0.853 0.1 0.029 0.029 0.029
1,2,3,4,6,7,8-HpCDD 316 –0.009 0.008 0.014 0.011 –0.015 0.029 0.065 0.068 0.01 0.001 0.01 0.035
OCDD 319 –0.003 0.003 0.002 0.001 0.002 0.0003 0.00025 0.00025 0.00025
2,3,7,8-TCDF 43 –0.912 0.828 0.629 0.635 –0.051 0.1 0.685 0.128 0.1
1,2,3,7,8-PeCDF 13 –0.382 0.347 0.657 0.03 0.0027 0.022 0.95
2,3,4,7,8-PeCDF 314 –0.019 0.016 0.011 0.016 –0.01 0.02 0.02 0.03 0.3 0.0065 0.2 3.7
1,2,3,4,7,8-HxCDF 311 0.023 0.043 0.1 0.014 0.05 0.16
1,2,3,6,7,8-HxCDF 312 –0.161 0.146 0.067 0.091 0.012 0.1 0.0031 0.081 0.16
2,3,4,6,7,8-HxCDF 51 –0.86 0.78 0.257 0.322 1.084 0.1 0.015 0.018 0.1
1,2,3,4,6,7,8-HpCDF 314 –0.059 0.054 0.083 0.132 –0.027 0.053 0.194 0.083 0.01
OCDF 80 0.127 –0.19 0.373 0.367 0.136 0.0003 0.000004 0.000077 0.0016
PCB 81 234 –0.0111 0.01 0.011 0.025 –0.009 0.017 0.041 0.05 0.0003
PCB 126 319 0.0009 0.000040 0.1 0.000067 0.1 0.86
PCB 169 320 0.0034 0.0022 0.03 0.0000018 0.019 0.74
PCB 105
276 0.0096 –0.0009 0.0000019
0.00003 0.00000047 0.000042 0.0022
PCB 114
315 0.063 0.0213 0.00003 0.0002 0.00034 0.00048
PCB 118
301 0.0032 0.0005 0.00003 0.00000042 0.00002 0.0023
PCB 123
276 0.033 0.022 0.00003 0.000034 0.000044 0.000055
PCB 156
315 0.0075 0.0022 0.00003 0.0000021 0.000055 0.42
PCB 157
315 0.0291 0.0087 0.00003 0.000420 0.0011 0.0017
PCB 167
315 0.0192 0.0027 0.00003
PCB 189
315 0.0265 0.0117 0.00003 0.000037 0.000055 0.00018
Abbreviations: BMC, benchmark concentration; BMCL, benchmark concentration lower confidence limit; DL-PCB, dioxin-like PCB; REP, relative effect potency. β, BMCL, and BMC
values were adjusted for sex and age. All REPs were calculated from data in picograms per gram.
Data from Haws etal. (2006).
Calculated as the ratio of the β of the individual chemical to that of TCDD.
Calculated as the ratio of the BMCL of the individual chemical to that of
Calculated as the ratio of the BMC of the individual chemical to that of TCDD.
Data from VandenBerg etal. (2006).
All β values were calculated from data in picograms per
gram except for mono-ortho-substituted PCBs, which were in nanograms per gram.
Calculated from data in picograms per gram.
Figure1. Relationship between βcoefficient–derived REPs for individual mixture components and the published WHO TEFs (VandenBerg etal. 2006), as measured
by (A)thyroid volume and (B)serum FT
PCB 81
PCB 105
PCB 81
–6 –5 –4 –3 –2 –1 0
LogREP (thyroid volume)
–5 –4 –3 –2 –1 0
Page 4
Trnovec et al.
volume 121
number 8
August 2013
Environmental Health Perspectives
three non-ortho-substituted PCB congeners
(PCB 81, PCB 126, and PCB 169) were not
plotted with regard to a high proportion of
samples with concentrations < LOD. The
mono-ortho-substituted PCBs (congeners
105, 156, 167, 189, 157, 123, and 114; TEFs
= 0.00003) are distributed along the line
of best fit (y = 0.461x – 0.003; R
= 0.797;
p = 0.001). When we included β-coefficients
for both PCB and TCDD (coordinates
–1.101 for thyroid volume and –0.508 for
), we obtained the equation y = 0.459x
– 0.003 (R
= 0.999; p = 0.001). e slopes
of these two equations were not statistically
different, meaning that the lower end of the
PCB best fit has a value similar to that of
TCDD. This analysis suggests continuity
between a dioxin-like and a non-dioxin-like
effect. This conforms with the four orders
of magnitude difference between TEFs for
TCDD and most DL-PCBs.
Although some potential environmental
hazards involve significant exposure to
only a single compound, most instances of
environ mental contamination involve con-
current or sequential exposures to a mixture,
which may induce similar or dis similar effects
over exposure periods ranging from short-
term to lifelong (U.S. EPA 2000). Interest
in the potential effect of chemical mixtures
has increased significantly in the last decade
(European Commission 2010; International
Programme on Chemical Safety 2009;
Kortenkamp et al. 2007). In this context,
study tools such as the relative potency factor
method have been developed. is approach
uses empirically derived scaling factors based
on toxicity studies of the effect in combina-
tion with exposure conditions of interest in
the assessment (U.S. EPA 2000) and is the
backbone of our study. e TEF method is a
variation of the relative potency factor method
(U.S. EPA 2000) and deals with the mix-
ture toxicity of DLCs. e DLCs may serve
as a prototype example of mixture toxicity
(Van den Berg et al. 2006). Relevant stud-
ies with DLCs were reviewed extensively by
Haws et al. (2006) within the framework of
the TEF concept. One of the aims of the pres-
ent study was to place our results in context of
this vast body of scientific knowledge. As far as
we know, the present study is the first human
in vivo analysis of REPs of individual mixture
components after exposure to DLCs.
Our study has several unique methodo-
logi cal aspects. First, for most congeners
evaluated, we obtained six REP values,
which were derived from the BMC, BMCL,
and regression coefficient (β) approach for
two end points, thyroid volume and serum
concentration. The results of the three
approaches are so closely interrelated that
any of them can be used. A second aspect is
that the potential effects of mixture compo-
nents need to be accounted for. Multivariable
regression analysis showed that the contribu-
tion of confounding congeners to the final
outcome was negligible. erefore, we did not
adjust for the confounding congeners when
calculating REPs (we adjusted only for age
and sex). is approach is supported by dif-
ferences in congener-specific mechanisms of
action leading to their independent action.
With regard to our study design, several
issues should be considered, the first of which
is the selection of end points for exposure–
effect analysis. We chose two thyroid bio-
markers, serum FT
concentration and
thyroid volume, because thyroid pathology
is the most prominent of the specific toxi-
cological and biological non cancer health
effects reported in DLC-exposed animals and
humans (Boas et al. 2009; Crofton et al. 2005;
Langer 2010; Rádiková et al. 2008; Zoeller
2007, 2010; Zoeller et al. 2002). Yang et al.
(2010) suggested using a decrease in T
as a
prospective biomarker for generating a new
human TEF scheme for DL-PCBs, noting
that a decrease in circulating T
is the only
consistent biomarker for both DL- and
NDL-PCBs. is is important because non-
coplanar PCBs elicit a diverse spectrum of
non-AhR–mediated toxic responses in
humans and animals (Yang et al. 2010). In
agreement with this, our results (Figure 2)
demonstrate the association between the two
thyroid end points using both DL-PCB and
NDL-PCB data. Another issue to consider
is dose additivity, which is assumed by the
TEF method. In a short-term study using
thyroid hormone–disrupting chemicals in rats,
Crofton et al. (2005) observed both dose addi-
tivity and synergism depending on chemi-
cal dose. However, it is not known whether
this would apply to our long-term, low-dose,
human exposure scenario.
e second thyroid biomarker we evalu-
ated in the present study is thyroid size.
Estimation of thyroid volume is generally con-
sidered to be important in several pathologic
situations, such as iodine deficiency goiter,
thyroiditis, and multi nodular goiter (Hegedüs
1990). In a study by Hansen et al. (2004),
regression analysis suggested that serum
thyroid-stimulating hormone, serum FT
sex, age, smoking, and body mass index each
played a small but significant role in variation
of thyroid volume. We have been the only
group that has extensively exploited this bio-
marker in studying effects of PCBs in humans
(Langer 2010; Rádiková et al. 2008); thus,
using thyroid volume in the present study was
a logical continuation of our previous studies.
A significant finding in the present study
is that the exposure to the index chemical,
TCDD, and most DLCs was associated with
a decrease in both thyroid volume and serum
concentration. e FT
shift is consistent
with an observation in a community exposed
to dioxin-like congeners (Bloom et al. 2006).
In contrast, in our study, associations with
PCB exposure varied slightly and were
much smaller in magnitude. e parameter
increases we observed for the most abundant
NDL-PCBs agree with our previous results
for FT
and thyroid volume (Langer 2010;
Rádiková et al. 2008) and for FT
in anglers
(Bloom et al. 2009).
Figure2. Plot of regression coefficients [β; listed in Table1; see also Supplemental Material, TableS5
(] for thyroid volume vs. PCB congener concentration (x-axis) against
those for FT
serum concentration vs. PCB congener concentration (y-axis).
Thyroid volume (β)
–0.02 –0.01 0.01 0.02
0.04 0.05 0.06
Page 5
Relative effect potencies of dioxin-like compounds
Environmental Health Perspectives
volume 121
number 8
August 2013
A second important issue is the mode
of action of the index chemical and of the
congeners studied. In REP studies, simi larity
of the mode of action justifies the inclu-
sion of a compound in the TEF concept for
DLCs. e inclusion criteria include a struc-
tural relation ship to TCDD, binding to the
AhR, an AhR-mediated biological or toxic
response, and persistence and accumu la tion
in the food chain (Van den Berg et al. 2006).
However, at present, there is no published evi-
dence that long-term morphological changes
of the thyroid gland and hormonal shifts—
chosen as end points in this study—are exclu-
sively AhR–mediated processes. We previously
described a biphasic association between
serum concentration of a mixture of PCBs
and FT
(i.e., negative association in the cate-
gory of PCB levels < 530 ng/g vs. a positive
association in the category of PCB levels of
531–25,000 ng/g) (Langer et al. 2007c); that
association make even more diffi cult assigning
a mode of action in humans exposed to com-
plex environmental mixtures of DLCs and
NDL-PCBs. In addition, there is no agree-
ment on the presence of possible effects of
DLCs on thyroid function at environmental
exposure levels (Johnson et al. 2001; Pavuk
et al. 2003).
In the present study, the REPs calculated
via two different approaches—one based on
thyroid morphology and the other on thy-
roid hormonal end point—showed consis-
tent results. In spite of using a design different
from those of published REP studies, as well
as the unique scenario of our study, most of
our REPs, especially those for dioxins and
thyroid volume, fit well within the ranges of
published REPs (Haws et al. 2006) (Table 1).
In plots of log REPs for thyroid volume
(Figure 1A) or FT
(Figure 1B) versus log
TEFs, however, the best fit is markedly shifted
in the direction of our REPs. is is more pro-
nounced for FT
, which may be interpreted
as a greater sensitivity of this end point com-
pared with thyroid volume or with end points
leading to the assigned TEF values.
One strength of our study is that it
is based on changes of two human thyroid
parameters with apparently completely dif-
ferent patho genesis, but whose results largely
agree. Another strength is that we used actual
serum concentrations of compounds that reli-
ably reflect systemic body burden, rather than
data on daily intake. A weakness of our study
is that we worked with exposure to a mix-
ture of chemicals with different potencies and
likely different modes of action, compared
with an exposure scenario under laboratory
conditions that takes into account a single
chemical. Further, single time exposure data
does not necessarily reflect the whole exposure
history of each participant. Another weak-
ness of our study was that the prevalence of
concentrations < LOD was high for some
compounds, and this likely limited our sta-
tistical precision. In spite of the short comings
of this study, the REPs we determined should
be considered in updating the present TEFs
with regard to long-term, low-dose exposure
of humans instead of relatively short-term
animal studies.
In the manuscript originally published
online, several errors resulted from the
incorrect calculation of β coefficients.
a) PCB 105 data for FT
in Table 1 and
Figure 1B were based on β coefficients
calcu lated from concentrations given in
nanograms per gram and compared with
the β coefficient for TCDD, which was
calcu lated from concentrations in picograms
per gram. b) In Figure 2, the β coefficients
for PCB 181, PCB 126, and PCB 169
were calculated from picograms per gram
units instead of nanograms per gram units;
the correct values were extremely low and
have thus been omitted. ese errors have
been corrected here and do not affect the
conclusions of the paper.
Akins JR, Waldrep KJT, Bernert JR. 1989. The estimation of
total serum lipids by a completely enzymatic ‘summation’
method. Clin Chim Acta 184:219–226.
Bloom M, Vena J, Olson J, Moysich K. 2006. Chronic exposure
to dioxin-like compounds and thyroid function among New
York anglers. Environ Toxicol Pharmacol 21:260–267.
Bloom MS, Vena JE, Olson JR, Kostyniak PJ. 2009. Assessment
of polychlorinated biphenyl congeners, thyroid stimulat-
ing hormone, and free thyroxine among New York State
anglers. Int J Hyg Environ Health 212:599–611.
Boas M, Main KM, Feldt-Rasmussen U. 2009. Environmental
chemicals and thyroid function: an update. Curr Opin
Endocrinol Diabetes Obes 16:385–391.
Brown DJ, Chu M, Van Overmeire I, Chu A, Clark GC. 2001.
Determination of REP values for the Calux® bioassay
and comparison to the WHO TEF values. Organohalogen
Compounds 53:211–214.
Brunn J, Block U, Ruf G, Bos I, Kunze WP, Scriba PC. 1981.
Volumetrie der Schilddrüsenlappen mittels real-time
Sonographie [Volumetric analysis of thyroid lobes by real-
time ultrasound; in German]. Dtsch Med Wochenschr
Crofton KM, Craft ES, Hedge JM, Gennings C, Simmons JE,
CarchmanRA, etal. 2005. Thyroid-hormone-disrupting
chemicals: evidence for dose-dependent additivity or
synergism. Environ Health Perspect 113:1549–1554;
doi:10.1289/ehp.8195 [Online 21July 2005].
Crump KS. 1995. Calculation of benchmark doses from continuous
data. Risk Anal 15:79–89.
Dedik L. 2012. CTDB_BMD (Clinical Trials Database– Benchmark
Dose). Available:
BMD_inst.exe [accessed 16April 2013].
European Commission. 2010. State of the Art Report on Mixture
Toxicity: Final Report. Study Contract No. 070307/2007/
485103/ETU/D.1. Brussels:Directorate General Environment,
European Commission. Available:
[accessed 16April 2013].
Fattore E, Chu I, Sand S, Fanelli R, Falk-Filippson A, HåkanssonH.
2004. Dose-response assessment using the benchmark
dose approach of changes in hepatic EROD activity for indi-
vidual polychlorinated biphenyl congeners. Organohalogen
Compounds 66:3402–3407.
Hansen PS, Brix TH, Bennedbaek FN, Bonnema SJ, Kyvik KO,
Hegedüs L. 2004. Genetic and environmental causes of
individual differences in thyroid size: a study of healthy
Danish twins. J Clin Endocrinol Metab 89:2071–2077.
Haws LC, Su SH, Harris M, Devito MJ, Walker NJ, FarlandWH,
etal. 2006. Development of a refined database of mammalian
relative potency estimates for DLCs. Toxicol Sci 89:4–30.
Hegedüs L. 1990. Thyroid size determined by ultrasound.
Influence of physiological factors and non-thyroidal disease.
Dan Med Bull 37:249–263.
International Programme on Chemical Safety. 2009. Assessment
of Combined Exposures to Multiple Chemicals: Report of a
WHO/IPCS International Workshop. Harmonization Project
Document 7. Geneva:World Health Organization, Available:
workshopreportdocument7.pdf [accessed 16 April 2013].
Johnson E, Shorter C, Bestervelt L, Patterson D, Needham L,
PiperW, etal. 2001. Serum hormone levels in humans with
low serum concentrations of 2,3,7,8-TCDD. Toxicol Ind
Health 17:105–112.
Jursa S, Chovancová J, Petrík J, Lokša J. 2006. Dioxin-like and
non-dioxin-like PCBs in human serum of Slovak population.
Chemosphere 64:686–691.
Koˇcan A, Drobna B, Petrik J, Jursa S, Chovancova J, ConkaK,
etal. 2004. Human exposure to PCBs and some other
organochlorines in Eastern Slovakia as a consequence
of former PCB production. Organohalogen Compounds
Kortenkamp A, Faust M, Scholze M, Backhaus T. 2007. Low-level
exposure to multiple chemicals: reason for human health
concerns? Environ Health Perspect 115(suppl1):106–114;
doi:10.1289/ehp.9358 [Online 8June 2007].
Langer P. 2010. The impacts of organochlorines and other per-
sistent pollutants on thyroid and metabolic health. Front
Neuroendocrinol 31:497–518.
Langer P, Koˇcan A, Tajtáková M, Koška J, Rádiková Z,
KšinantováL, etal. 2008. Increased thyroid volume, preva-
lence of thyroid antibodies and impaired fasting glucose in
young adults from organochlorine cocktail polluted area:
outcome of transgenerational transmission? Chemosphere
Langer P, Koˇcan A, Tajtakova M, Petrik J, Chovancova J,
DrobnaB, etal. 2005. Human thyroid in the population
exposed to high environmental pollution by organo-
chlorinated pollutants for several decades. Endocr Regul
Langer P, Koˇcan A, Tajtaková M, Petrík J, Chovancová J,
DrobnáB, etal. 2007a. Fish from industrially polluted fresh-
water as the main source of organochlorinated pollu-
tants and increased frequency of thyroid disorders and
dysglycemia. Chemosphere 67:379–385.
Langer P, Koˇcan A, Tajtáková M, Rádiková Z, Petrík J, KoskaJ,
etal. 2007b. Possible effects of persistent organo chlorinated
pollutants cocktail on thyroid hormone levels and pituitary–
thyroid interrelations. Chemosphere 70:110–118.
Langer P, Tajtáková M, Koˇcan A, Petrík J, Koška J, KšinantováL,
etal. 2007c. Thyroid ultrasound volume, structure and
function after long-term high exposure of large popula-
tion to polychlorinated biphenyls, pesticides and dioxin.
Chemosphere 69:118–127.
Langer P, Tajtaková M, Koˇcan A, Vlcek M, Petrik J,
ChovancovaJ, etal. 2006. Multiple organochlorine pollution
and the thyroid. Endocr Reg 40:46–52.
Ozgen A, Erol C, Kaya A, Ozmen MN, Akata D, Akhan O. 1999.
Interobserver and intraobserver variations in sonographic
measurement of thyroid volume in children. Eur J Endocrinol
Pavuk M, Schecter, AJ, Akhtar FZ, Michalek JE. 2003. Serum
2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) levels and thyroid
function in Air Force veterans of the Vietnam War. Ann
Epidemiol 13:335–343.
Petrik J, Drobna B, Pavuk M, Jursa S, Wimmerova S,
ChovancovaJ. 2006. Serum PCBs and organochlorine pesti-
cides in Slovakia: age, gender, and residence as deter-
minants of organochlorine concentrations. Chemosphere
Rádiková Z, Tajtáková M, Koˇcan A, Trnovec T, Seböková E,
etal. 2008. Possible effects of environmental nitrates and
toxic organochlorines on human thyroid in highly polluted
areas in Slovakia. Thyroid 18:353–362.
Turner WE, DiPietro ES, Cash TP, McClure PC, PattersonDG,
ShirkanH. 1994. An improved SPE extraction and auto-
mated sample cleanup method for serum PCDDs, PCDFs,
and coplanar PCBs. Organohalogen Compounds 19:31–35.
Ukropec J, Radikova Z, Huckova M, Koska J, Koˇcan A,
Page 6
Trnovec et al.
volume 121
number 8
August 2013
Environmental Health Perspectives
SebokovaE, etal. 2010. High prevalence of prediabetes
and diabetes in a population exposed to high levels of an
organochlorine cocktail. Diabetologia 53:899–906.
U.S. EPA (U.S. Environmental Protection Agency). 1994. Method
1613: Tetra- through Octa-Chlorinated Dioxins and Furans
by Isotope Dilution HRGC/HRMS (Revision B). Available:
4d!OpenDocument [accessed 16 April 2013].
U.S. EPA (U.S. Environmental Protection Agency). 1999. Method
1668, Revision A: Chlorinated Biphenyl Congeners in Water,
Soil, Sediment, and Tissue by HRGC/HRMS. Available:
[accessed 16April 2013].
U.S. EPA (U.S. Environmental Protection Agency). 2000.
Supplementary Guidance for Conducting Health Risk
Assessment of Chemical Mixtures. EPA/630/R-00/002.
cfm?deid=20533 [accessed 16 April 2013].
VandenBerg M, Birnbaum LS, Denison M, De Vito M, FarlandW,
Feeley M, etal. 2006. The 2005 World Health Organization
reevaluation of human and mammalian toxic equivalency
factors for dioxins and dioxin-like compounds. Toxicol Sci
Yang JM, Salmon AG, Marty MA. 2010. Development of TEFs for
PCB congeners by using an alternative biomarker—thyroid
hormone levels. Regul Toxicol Pharmacol 56:225–236.
Zoeller TR. 2007. Environmental chemicals impacting the thyroid:
targets and consequences. Thyroid 17:811–817.
Zoeller TR. 2010. Environmental chemicals targeting thyroid.
Hormones 9:28–40.
Zoeller TR, Dowling AL, Herzig CT, Iannacone EA, Gauger KJ,
BansalR. 2002. Thyroid hormone, brain development, and
the environment. Environ Health Perspect 110:355–361.
Page 7
  • Source
    • "Dose-dependent trends of PCBs' thyroid effects have also been identified in animal models with various NOAELs/LOAELs (Crofton et al., 2005; Martin et al., 2010). However, limited number of studies has applied BMD method to quantify the toxic responses of PCBs (Jacobson et al., 2002; Kalantari et al., 2013) and even fewer studies use BMD approach focusing on thyroid disruption of PCBs (Buha et al., 2013; Esteban et al., 2014; Trnovec et al., 2013); the existing studies were conducted either with co-exposure of other EDCs or focusing only on one single endpoint. Thus, there is a urgent need to calculate a more convinciable BMD of PCBs by comprehensively comparing BMD results from different endpoints. "
    [Show abstract] [Hide abstract] ABSTRACT: Polychlorinated biphenyls (PCBs) are proved endocrine disrupting potentials. Reference points (RP) for PCBs are derived from dose-response relationship analysis by using the traditional no observed adverse effect or lowest observed adverse effect level (NOAEL/LOAEL) methods, or a more advanced benchmark dose (BMD) method. In present study, toxicological RP for PCBs' thyroid disruption was established and compared between NOAEL/LOAEL and BMD method in an ovariectomized (OVX) rat model. Sham and OVX controls were given corn oil while other OVX groups were administered with 0.1, 1.0, 5.0, and 10.0mg/kgbw of PCBs (aroclor 1254) respectively by gavage. Body weight change, liver type I 5'-deiodinase (5'-DI) activity, serum total thyroxine (tT4), triiodothyroxine (tT3), thyroid stimulating hormones (TSH), and thyroid histopathological changes were measured and analyzed. In PCBs-treated groups, serum tT4, tT3, TSH, and histopathological examinations showed significant changes with a dose-dependent manner compared with those in OVX control (P<0.05). The toxicological RP for PCBs affecting thyroid function of OVX rats was 0.02mg/kg'bw based on BMD analysis.
    Full-text · Article · Oct 2015
    • "To evaluate the confounding effect of mixture components on cochlear status, we proceeded in a similar way as when we have treated a mixture effect of PCDD/Fs and DL-PCBs on thyroid volume and FT 4 (Trnovec et al. 2013). For this purpose, we calculated the benchmark concentrations (BMCs) for the effect on DPOAEs (combined for both sexes and for the left and right ears) for each OCP without and in presence of the most probable combinations of potentially ototoxic organochlorine confounders using CTDB_BMD software (Dedík 2012). "
    [Show abstract] [Hide abstract] ABSTRACT: The aim of this study was to examine the hypothesis that organochlorine pesticides (OCPs), hexachlorobenzene (HCB), β-hexachlorocyclohexane (β-HCH), and 1,1,1-trichloro-2,2-bis(4-chlorophenyl)ethane (p,p'-DDT) and its metabolite 1,1-dichloro-2,2-bis(4-chlorophenyl)ethylene (p,p'- DDE) are ototoxic to humans. A multivariate general linear model was designed, in which the statistical relation between blood serum concentrations of HCB, β-HCH, p,p'-DDT, or p,p'-DDE at different ages (at birth, 6, 16, and 45 months) and the distortion product otoacoustic emissions (DPOAEs) was treated as multivariate outcome variables. Polychlorinated biphenyl (PCB) congeners and OCPs were strongly correlated in serum of children from our cohort. To ascertain that the association between DPOAEs at a given frequency and concentration of a pesticide is not influenced by PCBs or other OCP also present in serum, we calculated benchmark concentrations (BMCs) relating DPOAEs to a serum pesticide alone and in presence of confounding PCB-153 or other OCPs. We found that BMCs relating DPOAEs to serum pesticides are not affected by confounders. DPOAE amplitudes were associated with serum OCPs at all investigated time intervals, however, in a positive way with prenatal exposure and in a negative way with all postnatal exposures. We observed tonotopicity in the association of pesticides with amplitude of DPOAEs as its strength was frequency dependent. We conclude that exposure to OCPs in infancy at environmental concentrations may be associated with hearing deficits.
    No preview · Article · May 2015 · Environmental Science and Pollution Research
  • Source
    • "Various attempts have been made to establish the biomarkers that can reflect the specific toxic effects based upon the body burden of exposure to chemicals, e.g., Toxic Equivalency Factors (TEFs),113114115. Some studies have also targeted some specific genes and their transcriptomic changes in relation to such environmental exposures [33,116117118119 . "
    [Show abstract] [Hide abstract] ABSTRACT: Recently the prevalence of obesity has increased dramatically across much of the world. Obesity, as a complex, multifactorial disease, and its health consequences probably result from the interplay of environmental, genetic, and behavioral factors. Several lines of evidence support the theory that obesity is programmed during early development and that environmental exposures can play a key role. We therefore hypothesize that the current epidemic might associated with the influence of chemical exposures upon genetically controlled developmental pathways, leading to metabolic disorders. Some environmental chemicals, such as PCBs and pesticide residues, are widespread in food, drinking water, soil, and they exert multiple effects including estrogenic on cellular processes; some have been shown to affect the development of obesity, insulin resistance, type 2 diabetes, and metabolic syndrome. To bring these lines of evidence together and address an important health problem, this narrative review has been primarily designed to address PCBs exposures that have linked with human disease, obesity in particular, and to assess the effects of PCBs on gene expression in a highlyexposed population. The results strongly suggest that further research into the specific mechanisms of PCBs-associated diseases is warranted.
    Full-text · Article · Nov 2014 · Current Pharmaceutical Biotechnology
Show more