Environmental Pollution 236 (2018) 850e861

Contents lists available at ScienceDirect

Environmental Pollution
journal homepage: www.elsevier.com/locate/envpol

Adverse metabolic effects in ﬁsh exposed to contaminants of
emerging concern in the ﬁeld and laboratory*,**
James P. Meador a, b, *, Andrew Yeh b, 1, Evan P. Gallagher b, 1
a

Environmental and Fisheries Sciences Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric
Administration, 2725 Montlake Blvd. East, Seattle, WA 98112, USA
b
Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA 98105, USA

a r t i c l e i n f o

a b s t r a c t

Article history:
Received 10 November 2017
Received in revised form
18 January 2018
Accepted 4 February 2018

Several metabolic parameters were assessed in juvenile Chinook salmon (Oncorhynchus tshawytscha) and
staghorn sculpin (Leptocottus armatus) residing in two estuaries receiving wastewater treatment efﬂuent
and one reference estuary. We also conducted a laboratory study with ﬁsh dosed for 32 days with 16 of
the most common contaminants of emerging concern (CECs) detected in feral ﬁsh. Several blood
chemistry parameters and other indicators of health were measured in ﬁsh from the ﬁeld and laboratory
study that were used to assess potential metabolic disruption. The blood chemistry values observed in
feral juvenile Chinook salmon were relatively consistent among ﬁsh collected from efﬂuent-impacted
sites and substantially different compared to reference site ﬁsh. These responses were more pronounced in Chinook salmon, which is supported by the disparity in accumulated CECs. The blood
chemistry results for juvenile Chinook salmon collected at efﬂuent-impacted sites exhibited a pattern
generally consistent with starvation because of similarities to observations from studies of food-deprived
ﬁsh; however, this response is not consistent with physical starvation but may be contaminant induced.
The altered blood chemistry parameters are useful as an early indicator of metabolic stress, even though
organismal characteristics (lipid content and condition factor) were not different among sites indicating
an early response. Evidence of metabolic disruption was also observed in juvenile Chinook salmon that
were exposed in the laboratory to a limited mixture of CECs; however, the plasma parameters were
qualitatively different possibly due to exposure route, season, or the suite of CECs. Growth was impaired
in the high-dose ﬁsh during the dosing phase and the low- and medium-dose ﬁsh assayed after 2 weeks
of depuration. Overall, these results are consistent with metabolic disruption for ﬁsh exposed to CECs,
which may result in early mortality or an impaired ability to compete for limited resources.
Published by Elsevier Ltd.

Keywords:
Metabolic disruption
Emerging contaminants
Chinook salmon
Blood chemistry
Early indicators

1. Introduction
Contaminants of emerging concern (CECs) are frequently

*
This paper has been recommended for acceptance by Dr. Sarah Michelle Harmon.
**
In this study we examined organismal and physiological parameters for feral
ﬁsh exposed to contaminants of emerging concern in WWTP impacted estuaries.
The plasma chemistry parameters were consistent with metabolic disruption for
juvenile Chinook and appear to be useful as early indicators of adverse effects.
* Corresponding author. NOAA Fisheries, 2725 Montlake Blvd. East, Seattle, WA,
USA.
E-mail addresses: james.meador@noaa.gov (J.P. Meador), ayeh3@uw.edu
(A. Yeh), evang3@u.washington.edu (E.P. Gallagher).
1
4225 Roosevelt Way NE, Suite 100, Seattle, WA 98105e6099 USA.

https://doi.org/10.1016/j.envpol.2018.02.007
0269-7491/Published by Elsevier Ltd.

associated with endocrine disruption and reproductive effects
because this broad class of compounds includes very potent natural
and synthetic hormones in addition to hormone mimics (Harding
et al., 2016). In addition to reproductive toxicants, several of these
compounds are potential metabolic disruptors (Casals-Casas and
Desvergne, 2011) and can also cause adverse behavioral and immune system responses in organisms.
Wastewater treatment plants (WWTPs) are known conduits to
receiving waters for a variety of pharmaceuticals, personal care
products, industrial compounds, metals, and legacy compounds.
Several of these chemicals have been shown to affect ﬁsh at very
low concentrations (Fairchild et al., 1999; Daughton and Brooks,
2011; Schultz et al., 2012; Saaristo et al., 2017); however, few data
exist on toxic responses for most of these poorly studied chemicals,
especially as mixtures. To date, most studies conducted on aquatic

 J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861

organisms have assessed reproductive effects or behavioral alterations and very few have focused on metabolic disruption. One
study found reduced growth in male fathead minnow (Pimephales
promelas) exposed to 40,000 ng/L metformin in addition to
disruption of reproductive parameters (Niemuth and Klaper, 2015).
Another study reported that alkylphenols (octylphenol, nonylphenol, and nonylphenol diethoxylate) inhibited growth in
rainbow trout (Oncorhynchus mykiss) at relatively low concentrations in the range of ng/mL (Ashﬁeld et al., 1998). Many of these
compounds can affect multiple physiological pathways for a given
exposure resulting in simultaneous impairment to reproductive,
growth, or behavioral parameters. Additionally, these alterations
may result in indirect effects such as abnormal behavior leading to
reduced feeding and growth or increased predation (Painter et al.,
2009).
For many endocrine disrupting compounds, there is a critical
linkage between endocrine receptor agonism and activation of
metabolic pathways, suggesting a commonality among metabolic
abnormalities and classic endocrine disrupting responses (Chen
et al., 2009). Certainly, many non-endocrine pathways may be
impacted by CECs and other contaminants resulting is disruption of
metabolic homeostasis. Indeed, these compounds may have fairly
high speciﬁcity for their targets based on evolutionary conservation
across vertebrates (Gunnarsson et al., 2008), suggesting conservation of function. Considering the range of compounds detected in
WWTP efﬂuent (Meador et al., 2016), a large number of these are
potential metabolic disruptors in aquatic organisms and may act
directly on metabolic or endocrine pathways, or indirectly via other
receptors.
Our previous study reported a high percentage of analyzed CECs
(61%, n ¼ 150) in efﬂuent, estuary water, or ﬁsh tissue collected
from WWTP impacted estuarine sites (Meador et al., 2016). The
current report presents an evaluation of the potential effects
resulting from exposure to those compounds, which were selected
as a representative group with little data available on occurrence in
marine waters or toxicity for exposed ﬁsh. Our goal for this study
was to assess several metabolic attributes in juvenile Chinook
salmon (Oncorhynchus tshawytscha) and Paciﬁc staghorn sculpin
(Leptocottus armatus) exposed to WWTP efﬂuent in the ﬁeld and
juvenile Chinook exposed in the laboratory to a model mixture of a
select group of CECs quantiﬁed in whole-body feral ﬁsh inhabiting
impacted sites. Our speciﬁc focus was on blood chemistry parameters as potentially useful metrics that could be utilized as early
indicators of metabolic disruption.
2. Methods
2.1. Field study
Details regarding ﬁsh collections, physical-chemical parameters,
and chemical analysis can be found in Meador et al. (2016) and
Table S1. Brieﬂy, ﬁsh were collected from three local Puget Sound,
WA estuaries. Two of the sites (Sinclair Inlet and the Puyallup River
estuary) receive efﬂuent from WWTPs. A minimally contaminated
site, the Nisqually River estuary, was selected for comparison and
served as our reference site. Two ﬁsh species that commonly occur
in Puget Sound estuaries were collected and sampled for blood
plasma. One was a benthic species, Paciﬁc staghorn sculpin, which
is found widely in Puget Sound and U.S. west coast temperate
waters. The other ﬁsh species was juvenile ocean-type Chinook
salmon, which can reside for several weeks in nearshore estuaries
where contaminants are often concentrated. We also collected
several juvenile Chinook salmon from the Voights Creek Hatchery
on the Puyallup River upstream of the estuary on 28 May 2014. As
reported in Meador et al. (2016) only 7 analytes were detected in

851

these ﬁsh, most at relatively low concentrations. All estuarine juvenile Chinook salmon were collected in the estuary within a 10 d
period and were approximately the same age as most were released
from upstream hatcheries approximately 3e5 weeks before capture (Table S1).
2.1.1. Field samples
Fish were collected under a Washington State Scientiﬁc Collection Permit 13e046 and ESA Section 10(a)(1)(A) permit 17798. All
methods for obtaining, transporting, and tissue sampling were
approved by the University of Washington Institutional Animal
Care and Use Committee (protocol number 4096-01). Details of all
sampling methods used in this study were reported in Meador et al.
(2016).
Juvenile Chinook salmon and staghorn sculpin were obtained at
each ﬁeld site with a beach seine. Fish were kept alive after
collection in the ﬁeld and transported to the laboratory for processing in aerated site water that was maintained at 13   C with ice
packs. All samples for chemistry and plasma were taken approximately 3e6 h after capture. Fish were euthanized with tricaine
methanesulfonate (MS-222; Argent Chemical Laboratories, Redmond, WA) for processing. Chemical analyses for CEC analytes were
conducted on composite samples consisting of 3e12 whole-body
salmon or 3e5 whole-body sculpin (Meador et al., 2016).
2.2. Laboratory study
The laboratory study was conducted at the University of
Washington ﬁsh hatchery in Seattle, WA. Approximately 400 juvenile Chinook salmon were received from the Wallace Falls
hatchery (Gold Bar, WA) on 9 Feb 2015. The average individual
weighed approximately 45 g and water temperature at the hatchery was approximately 10   C. These ﬁsh were yearling (1 þ years)
Chinook salmon that were a genetic cross between hatchery and
wild ﬁsh (ﬁrst generation) and were not treated with any chemicals
at the hatchery. No mortality occurred due to handling or transit to
our laboratory holding tanks. Fish (n ¼ 20 per tank) were randomly
distributed to 15 circular tanks each with a 500 L capacity. Lake
Washington was the source of water to the tanks, which was supplied at approximately 1 L/m ﬂow-through at 12   C. Treatments
were assigned at random to tanks and 3 or 4 tank replicates per CEC
dose were tested. An additional tank of ﬁsh was not fed during the
32 d exposure period. Large windows allowed ambient light into
the experimental area and tanks were partially covered with black
plastic to give ﬁsh cover and shield them from artiﬁcial light.
The rationale for selection of the compounds comprising the
CEC mixture was presented in Yeh et al. (2017) and in Table S2.
Concentrated stock solutions for each CEC analyte were generated
by dissolving the compounds in 50e100 mL of absolute ethanol.
Calculated amounts of CEC stock solutions were added to three
separate volumes of 4 L of 100% ethanol in order to generate the
0.3Â (low), 1Â (medium), and 10Â (high) dose CEC mixtures, which
were selected to mimic whole-body concentrations observed in our
ﬁeld-collected ﬁsh. BioClark's Fry 2.5 mm low-fat food pellets (BioOregon, Longview, WA) were dosed with the CEC mixtures by
complete immersion with the ethanol mixture and taken to dryness under a fume hood. Previous studies have shown this to be an
effective method for dosing ﬁsh pellets (Meador et al., 2005, 2006).
The ﬁsh food used in the control diet was treated identically with
the ethanol solvent minus the CEC mixture. Based on previous
studies (Meador et al., 2005, 2006) ﬁsh were fed 2% body weight
(bw) dayÀ1 spread over 2 feedings per day, 5 days per week, from
days 0e32 for a total of 25 daily feedings (50 total). Dietary exposure for toxicity studies is a well-supported approach that is widely
used. The most important aspect for toxicity characterization is the

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J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861

tissue concentration, not the ambient concentration or route of
exposure (Meador et al., 2008).
The rate of dosing for each compound is listed in Table S3. An
unquantiﬁed portion of the food was not consumed hence the true
rate of ingestion by ﬁsh in each tank was unknown. Most ﬁsh
actively fed during the application of food to tanks; however, the
rate was less than anticipated based on previous studies, hence
instead of pair-feeding the ration was considered as ad libitum. An
additional tank of ﬁsh were not fed (food-deprived (fasted) treatment) during the ﬁrst phase (days 0e32). After sampling on day 33,
the remaining live ﬁsh were fed unadulterated ﬁsh pellets once/day
over a two week period, days 34e50 (fed 10 times) at a rate of 2%
bw dayÀ1. The goal was to depurate the ﬁsh and resample for
plasma and liver, which was completed on 6e7 April 2015. Fish in
the food-deprived treatment were also fed this amount.
2.2.1. Fish processing in the laboratory study
All ﬁsh in each tank were weighed individually to generate a
tank mean for day 32 and approximately half of these ﬁsh were
randomly sampled on days 32e33 for liver, plasma, and wholebody chemistry. The weights for ﬁsh not sampled were then used
to determine the tank mean for the start of the depuration phase
(day 34) and these ﬁsh were weighed again on day 50. For both
sampling periods, concentrations of CECs and whole-body lipid
content in lab ﬁsh tissue were determined on composite samples of
6e8 ﬁsh per treatment (2 ﬁsh from each replicate tank/treatment).
The entire alimentary canal was opened and rinsed with distilled
water of all undigested food to avoid bias in the chemical
determinations.
2.3. Plasma samples and metabolic parameters
Whole blood was taken from several ﬁsh by transection of the
caudal peduncle until approximately 1 mL was obtained to form
one composite sample. Pooling samples was necessary due to low
volumes of blood per ﬁsh; therefore, several individuals comprised
each of multiple composites per ﬁeld site (Table S4). For the lab
study, composite samples containing 2 ﬁsh from each tank were
formed for analysis of plasma chemistry that resulted in 3 or 4
independent replicates per treatment depending on the number of
tanks per dose. For all composite samples, individual ﬁsh were
essentially the same weight and contributed similar amounts of
blood. Multiple composite samples containing several ﬁsh for each
site or treatment was advantageous for characterizing the true
mean, minimizing variance, and reducing analytical costs (Bignert
et al., 2014; Heffernan et al., 2014).
Blood from each ﬁsh was collected in a heparinized 1.3 mL
sample vial (heparin grade 1-A, 25 IU). Samples were immediately
centrifuged at 18,800 rpm for 150 s in a Statspin veterinary
centrifuge and then frozen at À80   C until analyzed. Plasma samples were analyzed using an automated blood chemistry analyzer
(Idexx VetTest 8008 Chemistry Analyzer, Idexx Labs, Westbrook,
ME, USA). Blood plasma was analyzed for albumin (ALB), alkaline
phosphatase (ALKP), alanine aminotransferase (ALT), amylase
(AMYL), calcium (CA), cholesterol (CHOL), creatinine (CREA),
glucose (GLU), lipase (LIPA), inorganic phosphate (PHOS), triacylglycerols (TAGs), and total protein (TP). This suite of selected
blood chemistry parameters was based on previous studies
demonstrating their utility for characterizing altered metabolic
homeostasis (Wagner and Congleton, 2004; Meador et al., 2006;
Congleton and Wagner, 2006). A quality control procedure (Idexx
Vetrol control lot number J3910) was conducted prior to analysis of
the test samples to verify both the VetTest optic groups and the
integrity of the test slides. All samples were analyzed in random
order.

2.4. Analytical methods
Concentrations of CEC analytes were determined by AXYS
Analytical, Ltd. (Sidney, British Columbia, Canada) using LC/MS/MS
techniques for the ﬁeld and laboratory study ﬁsh. Meador et al.
(2016) provides a complete list of the 150 different CEC analytes
in feral ﬁsh with their analytical methods, reporting limits, and
observed concentrations. Whole-body lipid content was determined by AXYS Analytical Ltd. using a Soxhlet extraction technique
with dichloromethane as the extraction solvent. A portion of the
extract was used to determine lipid content gravimetrically for the
same composite samples as that for CEC chemistry.
2.5. Statistical analyses
Differences in treatment means for ﬁsh weights and blood
chemistry were tested with Analysis of Variance (ANOVA). Tanks, as
opposed to individual ﬁsh, were treated as the experimental unit
for all ANOVA tests; therefore, treatment differences were based on
mean values for replicate tanks. The hypothesis of equal variance
among tank means (homoscedasticity) was tested with Levene's
test.
Control versus treatment differences were determined with
Fisher's Protected Least Signiﬁcant Difference (PLSD) post-hoc test.
We consider the p-values from the posthoc tests to be an important
indicator of the relationship between observed data and the null
hypothesis of no treatment effect (Hurlbert and Lombardi, 2009;
Wasserstein and Lazar, 2016). The strongest response was noted
for those p-values below 0.05. P-values between 0.05 and 0.15 were
also shown because they may indicate biologically important
trends, especially in light of occasional high variability.
A paired t-test was conducted on replicate tank values for
average ﬁsh weight by treatment on days 0 and 32 and for days 34
and 50 to test the hypothesis of positive ﬁsh growth from one
sampling period to the next. For all data, the standard error of the
mean (SEM), a statistic of the mean, is reported to facilitate comparisons of mean of values. For some results, the standard deviation
was shown to indicate a range in the data. Statistical analyses were
conducted with SYSTAT 11 and Statview 5.0.
The plasma chemistry results were log transformed and autoscaled for multivariate analyses using MetaboAnalyst (Xia and
Wishart, 2016). We generated heatmap plots, dendograms, and
2D scores plots using Partial Least Squares-Discriminant analysis.
Dendograms and heatmaps were constructed using a Euclidean
distance measure and the Ward clustering algorithm.
We calculated the apparent half-life for parent compounds
during the depuration phase (days 34e50) in the lab study when
data were available for both time points. A simple ﬁrst order
elimination equation, as described in Meador (1997), was used as
an approximation for the half-life that was based on minimal data.
Metabolites were not included because of the continual conversion
from parent compound during the depuration phase. An additional
analysis included applying the Fish Plasma Model (FPM) to these
data as described in Meador et al. (2017). We predicted plasma
concentrations with observed whole-body tissue concentrations
and estimates for the volume of distribution. The estimated plasma
concentration for each measured compound was compared to the
1%Cmax total and expressed as the Response Ratio (RRtissue).
3. Results
3.1. Field study
Condition factor (CF) and lipid content were determined for ﬁsh
from each site to assess general health. The CF for juvenile Chinook

 J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861

853

among sites that was based on data from all ﬁsh collected ranged
from 0.92 to 0.96 and while the values for ﬁsh from impacted sites
were slightly lower, the p-values were relatively high (Table S5).
The CF for sculpin was higher for the Puyallup estuary ﬁsh
compared to the Nisqually estuary ﬁsh (p ¼ 0.045) and the reference site ﬁsh were not different compared to the Sinclair Inlet ﬁsh.
The observed whole-body lipid data indicated no differences between samples of juvenile Chinook from the Nisqually estuary and
Sinclair Inlet; however, ﬁsh from the Puyallup River estuary
exhibited a higher mean value (3.8%) (Table S5). The whole-body
lipid content for staghorn sculpin was relatively constant among
sites with values ranging from 1.7% to 1.9%.
3.1.1. Chinook salmon plasma chemistry
The plasma chemistry parameters measured in juvenile Chinook
salmon indicated a number of strong differences (p < 0.05) between the reference site (Nisqually) and the two WWTP-impacted
estuarine sites. For example, lower values were obtained for ALB,
ALKP, ALT, AMYL, CHOL, GLU, LIPA, and TAGs compared to one or
both impacted sites (Fig. 1, Table S6). TAGs were lower for the
Sinclair ﬁsh, but highly elevated for ﬁsh from the Puyallup River
Estuary. Creatinine, a breakdown product of creatine was elevated
for the Puyallup ﬁsh as was CA, GLOB, and TP relative to the
reference ﬁsh. The multivariate results indicate strong differences
among sites as seen in the PLS-DA scores plot (Fig. 2), in addition to
the heatmap and dendogram (Figs. S1 and S2).
3.1.2. Sculpin plasma chemistry
Insufﬁcient plasma was obtained from sculpin collected in Sinclair Inlet precluding analysis for that site. The data for ﬁsh from the
Nisqually and Puyallup River estuaries were analyzed separately by
sex (Table S6, Fig. 1b and Fig. S3). Additionally, 2 large females
(>100 g) were excluded because of concerns related to altered
physiology during the reproductive phase and the remaining
sculpin from both sites were pre-vitellogenic (Gallagher et al.,
2016). The strongest response was for lower levels of albumin in
the Puyallup female sculpin. Additional noteworthy differences
include the generally lower values for GLU and TAGs for the
Puyallup females, which is the same trend observed for juvenile
Chinook. The multivariate results for sculpin indicate only weak
separation among sites for plasma chemistry as seen in the PLS-DA
scores plot (Fig. 3), in addition to the heatmap and dendogram
(Figs. S4 and S5).

200

125
*

100
*
75

*

^

75

*
25
*
*

60

^
^

40

*

20

20

^
0

s
TA
G

S

x1
TP

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C

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A
C

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P

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00

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0

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LI
PA
TA
G
s
TP
x1
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L

x1

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LO
G

O

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AL 100
K
P
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.1

60

50

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25

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B

80

80

40

*

*

100

100

Enzymes U / L

*

AL
B

mg / dL or g / dL

*
*

*

Nisqually
Puyallup

100

150

125

0

120
Females < 100 g

*

*

120

175

150

50

3.2.1. Bioaccumulation
Many of the CECs fed to ﬁsh were found in their tissue at concentrations relevant to those observed in ﬁeld-collected juvenile
Chinook salmon (Table 1). All administered CECs were detected in
whole-body ﬁsh, except for ﬂuocinonide and triclosan that may
have been present but below their analytical reporting limits
(Table 1). A comparison of the observed tissue concentrations for
the laboratory study ﬁsh and those quantiﬁed in ﬁeld-collected ﬁsh
indicated a geometric mean ratio of 0.8, 1.2, and 7.5 when all individual compounds were summed, indicating relatively good

mg / dL or g / dL

175

3.2. Laboratory exposure study

B

200
Nisqually
Sinclair
Puyallup

Enzymes (U / L)

A

Fig. 2. Partial least-squares-discriminant analyses (PLS-DA) scores plots for the
chemical proﬁles from plasma samples for juvenile Chinook salmon collected in the
ﬁeld. Each site highlighted by a 95% conﬁdence ellipse. Nis is the Nisqually reference
site, Sin in Sinclair Inlet, and Puy is the Puyallup River Estuary.

Fig. 1. Blood chemistry parameters. a. Juvenile Chinook salmon. b. Female sculpin <100 g. Mean and standard error of the mean values for plasma chemistry parameters measured
in these species. * represents p-values <0.05 and ^ are p-values between 0.05 and 0.15. Parameters are albumin (ALB), alkaline phosphatase (ALKP), alanine transaminase (ALT),
calcium (CA), cholesterol (CHOL), creatinine (CREA), total globulins (GLOB), glucose (GLU), inorganic phosphate (PHOS), lipase (LIPA), total proteins (TP), and triacylglycerols (TAGs).
Nisqually is the reference site and the others are WWTP-efﬂuent impacted. Composite sample sizes as follows; Nisqually Chinook (n ¼ 5) and sculpin (n ¼ 4), Puyallup Chinook
(n ¼ 4) and sculpin (n ¼ 6), Sinclair Chinook (n ¼ 4). CA, CHOL, CREA, GLU, and TAGs as mg/dL; ALB, GLOB, and TP as g/dL; ALKP, ALT, AMYL, and LIPA as U/L.

 854

J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861

norﬂuoxetine) exhibited increases in concentration during the
depuration phase indicating continued metabolic conversion of the
parent compound. The estimated half-lives for azithromycin, diltiazem, and diphenhydramine determined in the high dose treatment of the present study are similar to other values reported for
ﬁsh (Meador et al., 2016, 2017). In addition, all half-lives reported in
Table 1 are longer than those found in the literature for humans
(except the perﬂuorinated compounds) as summarized in Meador
et al. (2016, 2017). The sum of all observed compounds in wholebody ﬁsh was relatively low ranging from 51 ng/g wet wt. (ww)
(0.14 nmol/g) for the low dose treatment to 794 ng/g ww (2.0 nmol/
g) for the high dose treatment on day 32 (Table 1). Predicted plasma
concentrations based on whole-body concentrations and the model
presented in Meador et al. (2017) are shown in Table S7 along with
predicted response ratios for each compound by treatment.
3.2.2. Plasma parameters
On day 32 (end of dosing) we observed a few changes in blood
chemistry parameters (ALKP, GLOB, LIPA, PHOS, and TP), but
generally in the opposite direction as the ﬁeld-collected ﬁsh (Fig. 4,
Table S8). Even after feeding the remaining ﬁsh clean food from day
34 to day 50 a number of parameters were substantially different
(mostly elevated) on day 50 compared to control ﬁsh (ALB, ALKP,
CA, CHOL, GLOB, and TP) (Fig. S6, Table S9).
Fig. 3. Partial least-squares-discriminant analyses (PLS-DA) scores plots for the
chemical proﬁles from plasma samples for staghorn sculpin salmon collected in the
ﬁeld. Each site highlighted by a 95% conﬁdence ellipse. Nis is the Nisqually reference
site and Puy is the Puyallup River Estuary. F is female and M is male ﬁsh.

agreement for the nominal (0.3Â, 1Â, and 10Â) and observed ratios
among treatments. Noteworthy values that were substantially
higher than anticipated included diltiazem and its metabolite,
PFDA, and PFOSA. It is noteworthy that the CEC metabolites from
the medium dose treatment ﬁsh (desmethyl-diltiazem and

3.2.3. Growth
After 32 days of dietary exposure, the CEC-treated ﬁsh accumulated concentrations of compounds that resulted in differential
growth among treatments (Fig. 5). On day 32 the increase in
average ﬁsh weight for the high dose treatment was substantially
less than that for the control (0.7 g increase compared to 3.1 g,
p ¼ 0.08) (Table 2). A paired t-test comparing ﬁsh weight from day
0 to day 32 for each treatment indicates that the control, low, and
medium dose ﬁsh increased substantially in mass over this time
period, whereas the high dose ﬁsh exhibited weak increases in

Table 1
Whole-body ﬁsh concentrations and half-life for lab study.
Chemical

Whole-body conc ng/g

% Lipid
Amitriptyline
Amlodipine
Azithromycin
Diltiazem
Desmethyl-diltiazem
Diphen hydramine
Fluocinonide
Fluoxetine
Norﬂuoxetine
Gemﬁbrozil
Metformin
Miconazole
PFDA
PFOS
PFOSA
PFHxA
Sertraline
Triclocarban
Triclosan
Sum (ng/g)
Sum (nmol/g)

5.26
<0.1
<0.6
<1.8
<0.1
<0.05
<0.2
<2.2
<0.6
<1
<0.6
<2.9
<0.7
<0.5
<1
<0.6
<0.5
<0.5
<1.2
<24
e
0.14

Half life
(d)

Max WB WB conc. factor (lab/ﬁeld)
conc ﬁeld

D 32 Cont D 32 Low D 32 Med D 32 High D 50 Med D 50 High Med High Salm Scul D 32 Low D 32 Med D 32 High D 50 Med D 50 High
5.51
0.13
1.15
2.84
17.1
7.01
1.81
<2.0
1.4
0.99
<0.6
4.5
1.15
1.31
5.67
6.02
<0.5
<0.5
<1.2
<24
51.1
0.11

5.26
<0.1
1.12
1.75
10.5
13.5
1.16
<3.8
1.04
1.2
<0.6
<4.7
<0.7
2.15
7.48
9.13
<0.5
<0.5
<1.2
<24
49.0
2.0

5.74
0.96
19.5
29
102
162
14.5
<3.0
19.6
17.9
3.34
39.5
13.3
31.1
135
189
<0.5
9.06
8.72
<23
794
0.11

5.19
<0.1
<0.6
2.42
3.79
14.4
<0.2
<2.2
0.91
1.65
<0.6
<11
<0.6
2.05
11.6
15.4
0.49
<0.5
<1.2
<23
52.7
0.95

3.5
<0.1
2.51
24.7
12.9
119
0.58
<2.3
5.61
16.3
<0.6
<2.9
<0.6
14.4
123
123
0.82
<0.5
<1.2
<23
443

e
e
e
12.2
e
e
e
91.2
e
e
e
e
262
e
e
e
e
e
e

e
6.1
77.7
6.0
e
3.9
e
10.0
e
e
e
e
16.2
134
29.0
e
e
e
e

0.68
1.00
1.70
1.60
1.50
2.70
6.50
4.90
3.20
1.30
e
1.80
0.78
33.7
e
e
17.0
6.50
26.4

e
e
e
e
0.08
0.28
e
e
e
e
27.8
e
e
1.4
2.2
e
0.2
e
e

0.19
1.15
1.67
10.7
4.67
0.67
e
0.29
0.31
e
0.16
0.64
1.68
0.17
2.74
e
e
e
e

Geomean 0.8
Median 0.7

e
1.12
1.03
6.56
9.00
0.43
e
0.21
0.38
e
e
e
2.76
0.22
4.15
e
e
e
e

1.41
19.5
17.1
63.8
108
5.37
e
4.00
5.59
2.57
1.42
7.39
39.9
4.01
85.9
e
0.53
1.34
e

e
e
1.42
2.37
9.6
e
e
0.19
0.52
e
e
e
2.63
0.34
7.0
e
e
e
e

e
1.0
0.59
0.63
0.67
0.37
e
0.20
0.31
e
e
e
1.28
0.03
55.9
e
e
e
e

1.2
1.1

7.5
5.5

1.5
1.9

0.6
0.6

Whole-body (WB) concentrations (bold) as ng/g wet weights based on composite samples containing 6e8 ﬁsh per treatment. Bold chemical names indicate metabolites
detected, but not added to food. Reporting limits shown as < values. Geometric mean and median concentration factor ratios between observed values for lab and ﬁeld ﬁsh.
Nominal ratios for lab/ﬁeld were 0.3Â (Low), 1Â (Med), and 10Â (High).

 J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861
175

175
^
Control
Low
Med
High
Fasting

150

^
150

g / dL or mg / dL

^

100

100

75

75

Enzymes (U / L)

125

125

*

*
50

50

*
*

25

25
*^

*
0

0

s
TA
G

S

x1

O

TP

LI
PA

PH

0

LU

x1

G

B

EA
R
C

G

LO

L

x1
00

A

O

C

H
C

x0
.1

YL

P

AL
T
AM

x1
AL
B

AL
K

0

0

Fig. 4. Mean and standard error of the mean values for plasma chemistry parameters
measured in juvenile Chinook salmon on day 32 in laboratory study. * represents pvalues <0.05 and ^ are p-values between 0.05 and 0.15. See Fig. 1 caption for abbreviations and units and Table 2 for composite sample sizes for plasma.

855

control (p ¼ 0.006). For most of the treatments, high variability and
low sample size precluded lower p-values.
In general, the mean CF for each treatment was higher for the
medium dose ﬁsh, which indicates these ﬁsh weighed more for a
given length than ﬁsh in treatments with lower CF values (Table 2).
During the depuration phase (days 34e50) the control ﬁsh
exhibited essentially no growth over this period; however the low,
medium, and starvation ﬁsh all showed substantial reductions in
body mass (Fig. 5). Reductions in average ﬁsh mass were approximately 2 g for each treatment with low p-values (Table 2). Minimal
growth was expected in these ﬁsh due to a lack of strong feeding,
only 10 supplied food rations, and handling stress. The slight
decline in control ﬁsh weight was within the variability expected
due to repeated weighing and variable stomach contents. The
paired t-test for day 50 shows that control and high dose ﬁsh
weight did not change substantially over this period of time,
whereas it did for the low and medium dose ﬁsh (Table 2). Also
noteworthy is the reduction in whole-body lipid content for the
high-dose ﬁsh on day 50 compared to the other treatments
(Table 1).
4. Discussion

Mean change in fish weight (g)

6

4.1. Effects on ﬁsh exposed to CECs in the ﬁeld

Control
Low
Medium
High
Fasting

4

2
p=0.08
p=0.08

0

-2

**

*

**

-4
32

50

Day
Fig. 5. Fish growth in laboratory study. Mean weight change in grams for each
treatment based on tank replicates. Error bars are the standard error of the mean. Data
for both sampling days (Day 32 and 50) shown. * indicates p-value <0.05 for treatment
versus control posthoc comparisons. Additional statistical analysis shown in Table 2.

body mass (p ¼ 0.12) (Table 2). A large reduction in mean weight
was observed for the food-deprived treatment as compared to the

In the current study, we measured a variety of plasma parameters as early indicators of metabolic status along with traditional
ﬁsh health endpoints to ascertain the effects of emerging contaminants on two ﬁsh species with different life-history traits in
Puget Sound. Condition factor (CF) and lipid content are two conventional indicators of ﬁsh health. In the current study, the mean
CFs for juvenile Chinook did not differ among sites. This was also
the case for lipid content for composite samples containing several
ﬁsh from the Nisqually estuary and Sinclair Inlet (2.3 and 2.4%);
while a much higher mean value was observed for the Puyallup
River Estuary ﬁsh (3.8%). The mean values for these ﬁeld-collected
ﬁsh were less than observed for the upstream hatchery collected
ﬁsh, which was expected because juvenile Chinook at this life stage
use stored lipids for smoltiﬁcation (Sheridan, 1988). Both of these
parameters indicate that the ﬁsh appeared to be relatively healthy
and exhibited no obvious site differences, which was also the case
for staghorn sculpin for these two general health parameters.
For ﬁeld studies, it is difﬁcult to know with certainty the
chemicals likely causing adverse effects. A recent study conducted
one year before (2013) the present study reported relatively low
whole-body concentrations for PCBs, PBDEs, DDTs, and other
organochlorine compounds in juvenile Chinook salmon collected in

Table 2
Comparisons of ﬁsh weights and condition factor among treatments for laboratory study.
Dose

Weight change (g)

Post-hoc p-value

Control
Low
Medium
High
Starvation

3.1 (0.76)
4.6 (0.38)
3.5 (1.2)
0.71 (0.27)
À3.1

e
0.25
0.69
0.08
0.006

Control
Low
Medium
High
Starvation

À0.33 (0.25)
À2.3 (0.76)
À1.9 (0.58)
À0.76 (0.43)
À2.0

e
0.02
0.04
0.57
0.16

T-test p-value
Day 32
0.03
0.007
0.06
0.12
e
Day 50
0.28
0.09
0.05
0.22
e

CF
1.08
1.13
1.16
1.06
e
e
e
e
e
e

(0.01)
(0.05)
(0.04)
(0.02)

Post-hoc p-value

N

e
0.29
0.08
0.72
e

4
3
4
3
1

e
e
e
e
e

4
3
4
3
1

Change in mean ﬁsh weight and condition factor (CF) (weight (g)/length3 (cm) *100) for each treatment and the standard error of the mean (SEM). Condition factor based on a
random selection of 6 ﬁsh from each tank. P-value shows the post-hoc comparison after ANOVA between control and treatment for weight change and CF. N shows the number
of replicate tanks per treatment. Paired t-test p-value based on comparing mean ﬁsh weight for replicate tanks within treatments for days 0e32 and days 34e50.

 J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861

Fasting
Puyallup
Sinclair

Increase

TP

TA
G
s

LI
PA

G
LU

O
L
G
LO
B

C
H

AM

YL

Decrease

AL
T

4.1.1. Chinook salmon plasma chemistry
Because most of the sampled juvenile Chinook were recently
released from upstream hatcheries, it is important to note that
hatchery practices for juvenile Chinook in Washington State are
controlled and monitored (HSRG, 2004); hence, similar conditions
were expected for these ﬁsh prior to release. In addition, these
central Puget Sound Chinook are very similar genetically
(Ruckelshaus et al., 2006) and were not expected to exhibit physiological differences. Blood chemistry parameters were not determined for hatchery ﬁsh because values would likely not be
comparable between estuarine ﬁsh and freshwater ﬁsh. Because
these ﬁsh were not exposed to CECs in the hatchery (Meador et al.,
2016) and reared in the estuaries for only a few weeks, the observed
differences are likely a result of estuarine conditions, including
exposure to CECs and possibly other contaminants at impacted
sites.
In general, we did not expect large differences in blood chemistry parameters for juvenile Chinook salmon among sites because
all ﬁsh were collected at the same life stage and age, within a 10day period, and basic water-quality parameters were similar and
not unusual among estuaries (Table S1). Also, most were released
from upstream hatcheries a few weeks prior to capture. In addition,
a previous study (Meador, 2014) concluded that juvenile Chinook
salmon in these estuaries were likely not food deprived, which was
also noted by Olson et al. (2008) for the Puyallup estuary and Fresh
et al. (2006) for Sinclair Inlet, who observed 82e89% of juvenile
Chinook collected with full stomachs. Even though this parameter
was not quantiﬁed in our study, most Chinook and sculpin we
examined contained stomach contents.
Every plasma parameter assayed was altered in juvenile Chinook salmon from the two impacted sites in relation to the reference site and in most cases, similar patterns were observed for ﬁsh
from the two impacted sites (i.e., a decrease over the corresponding
reference site value). The altered parameters were more extreme
for the Puyallup ﬁsh compared to the Sinclair ﬁsh, which was likely
due to the higher accumulation of CECs in the Puyallup ﬁsh. Fish
from the Puyallup estuary contained 27 detected analytes versus 13
for the Sinclair ﬁsh and total CEC concentrations that were 2e3 fold
higher in the Puyallup ﬁsh (Table S5).
Interpreting changes for blood chemistry parameters is difﬁcult
because these can change temporally. For example, short-term responses may include a mobilization of stored lipids (e.g., TAGs) that
occur in the plasma as they are broken down to free fatty acids for
use in generating cellular energy (Sheridan and Mommsen, 1991).
In time, this response would likely show reduced levels of TAGs in
the blood as stored lipids are depleted. Any alteration as compared
to the control or reference condition may result in potential

metabolic disruption, which is likely disadvantageous for ﬁsh
during normal seasonal cycles of growth and energy storage
(Meador et al., 2011).
As far as we know there are no studies demonstrating high
variability or directional changes in the blood parameters we
measured for a given species when exposed to normal environmental conditions. Extreme values may cause physiological stress;
however, we did not observe any such abnormal environmental or
biological conditions or reason to believe these ﬁsh would exhibit
differences. One study of blood chemistry parameters for rainbow
trout over variable temperature, pH, conductivity, and several other
water chemistry parameters found essentially no or low variation
in 10 of the parameters in common with the present study (ALKP,
ALT, ALB, AMYL, CA, CHOL, LIPA, PHOS, TP, TAGs) (Kopp et al., 2011).
Blood chemistry values were obtained from ﬁsh over winter and
summer months for temperatures ranging from 2.5 to 20   C, pH
values from 6.6 to 7.9, and conductivity from 17 to 60 mS mÀ1. One
higher temperature treatment (20   C) did elicit AMYL values about
2Â higher. Another study (Manera and Britti, 2006) observed only
slight variation in 10 blood parameters overlapping with the present study in RBT sampled from MarcheJune with temperatures
ranging from 17 to 22   C. Additionally, Hasler et al. (2011) reported
low variation for CA, CHOL, GLU, PHOS, TAGs, and TP (and others)
from adult migrating Chinook salmon sampled over 3 years at one
location over a similar time frame (JuneeJuly). Also noteworthy
here is the high degree of similarity for many of the blood chemistry parameters from the impacted and reference sites for staghorn
sculpin (Fig. 3 and Fig. S2), which were of unknown age and previous exposure to environmental conditions.
The levels for many of the plasma parameters measured in
Chinook collected from the impacted WWTP sites exhibited a
similar pattern to that observed for food-deprived ﬁsh for various
periods of time (Fig. 6, Table S10). In fact, data from several studies
demonstrated signiﬁcant declines in plasma levels for ALB, ALKP,
ALT (liver), AMYL, CHOL, GLU, TP, and TAGs for ﬁsh starved from 7 to
€ ran et al., 1975; Navarro and Gutierrez, 1995; Congleton
72 days (Go
  et al., 2012; Peres et al.,
and Wagner, 2006; Costas et al., 2011; Furne
2014). Some parameters such as GLOB and TP exhibited increases
due to fasting (Eslamloo et al., 2017) and a few (CHOL, GLU, LIPA,
and TAGs) may exhibit increased levels over the short term, then
decline over longer periods of time, indicating an initial physiological response of mobilized resources followed by depletion

B
AL
KP

the Puyallup estuary and nearshore areas in addition to low levels
of polycyclic aromatic hydrocarbons (PAHs) in stomach contents
(O'Neill et al., 2015). These authors also reported no differences in
gill metals (Cu, Cd, Ni, and Zn) compared to values observed for
Nisqually juvenile Chinook; however, Pb levels were elevated in gill
tissue of the Puyallup ﬁsh. A similar study by Olson et al. (2008) on
juvenile Chinook salmon and staghorn sculpin collected in 2002
and 2003 in the Puyallup River estuary reported similar biliary
concentrations of ﬂuorescent aromatic compounds (FACs) in these
two species, an indicator of PAH exposure. Olson et al. (2008) also
reported higher levels of whole-body PCBs in sculpin (2e3 fold)
compared to juvenile Chinook salmon at sampling sites comparable
to our own. These results for the same species as the present study
in the Puyallup River estuary support our contention that CECs are
important constituents for the observed metabolic responses seen
in juvenile Chinook salmon; hence, PAHs, metals, and legacy contaminants appear to be less of a factor.

AL

856

Fig. 6. Food-deprivation and fasting data are from published laboratory studies
showing substantial (p < 0.05) changes in plasma levels (liver for ALT) from control
values in ﬁsh that were food deprived. Values for WWTP efﬂuent impacted sites (see
Fig. 1a) show direction of change compared to ﬁsh from the reference site (Nisqually)
at p < 0.05. See text for description and Table S10 for details.

 J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861

  et al., 2012). Also note(Sheridan and Mommsen, 1991; Furne
worthy is the increased total protein value for juvenile Chinook that
was mostly a result of increased globulin levels, which has also
been associated with food-deprivation (Eslamloo et al., 2017).
Levels of triacylglycerol lipase increased in plasma under food
deprivation for yearling juvenile Chinook that were migrating
(Congleton and Wagner, 2006); however, Mommsen (1998) noted
that most forms of lipase are severely reduced (70e90%) in ﬁsh
under fasting conditions, which was also determined by Black and
Skinner (1986) and Albalat et al. (2006). Juvenile Chinook in the
estuaries are actively growing and metabolizing stored lipids to
enhance a growth spurt, which is normal for this life stage
(Sheridan, 1988; Higgs et al., 1995). Thus, the high lipase value for
the Nisqually ﬁsh is assumed to be an indication of healthy ﬁsh
metabolizing stored lipids to free fatty acids to enhance rapid
growth. An increase in TAGs can indicate mobilization of stored
lipids for energy or growth and a decrease can result from inhibition of lipolysis or depletion due to food deprivation. Whole-body
lipid content is known to decline in healthy juvenile Chinook during this smoltiﬁcation phase while transitioning from freshwater to
seawater (Sheridan, 1988). The lack of lipase in plasma for the
Puyallup ﬁsh, coupled with high TAG levels and elevated wholebody lipid contents may be an indication of an impaired ability to
utilize lipids at this critical life stage; however further experiments
are needed to test this hypothesis. Overall, it is clear that ﬁsh from
the WWTP efﬂuent-impacted sites did not exhibit the same physiological proﬁle as healthy actively growing ﬁsh from the reference
site.
There are very few studies that examined blood chemistry
constituents for ﬁsh exposed to contaminants, especially CECs. We
compared our results to those of Rodrigues et al. (2015) and
Gunnarsson
et
al.
(2009)
for
CEC
efﬂuent,
and
Muthuviveganandavel et al. (2013) for cypermethrin, which were
all short-term exposures (hours to 5 d). Our observed parameters
generally followed the values reported by these authors, with
consistent increases in CHOL, PHOS, and TAGs and a decrease in
ALT.
An increase in plasma enzymes (e.g., ALKP, ALT, and AMYL) is
usually associated with tissue damage or organ dysfunction (Boyd,
1983); however, declining levels in ﬁsh have rarely been addressed.
Several studies indicate decreases in plasma levels of ALKP and
AMYL (and others) associated with reduced growth or fasting
(Hille, 1984; Sauer and Haider, 1979; Congleton and Wagner, 2006).
Additionally, Sauer and Haider (1979) reported reductions in
plasma levels of lactate dehydrogenase, glutamic oxaloacetic
transaminase, and glutamate dehydrogenase in starved rainbow
trout. Reduced ALT activity in liver was associated with food
 rez-Jime
 nez et al., 2012).
deprivation in ﬁsh (Vijayan et al., 1986; Pe
Reductions in plasma enzymes such as ALT and AMYL have also
been associated with the metabolic disruptors PAHs and TBT
(Meador et al., 2006, 2011) and another study found large reductions in the plasma enzymes ALT, AMYL, and acid phosphatase
in carp (Catla catla) exposed to the pesticide cypermethrin
(Muthuviveganandavel et al., 2013).
We consider these altered blood chemistry parameters as earlywarning indicators of metabolic disruption that may lead to
declining vitality in these ﬁsh over time. This inhibition could result
in decreased growth, which has been associated with decreased
survival for salmonids at this life stage (Beamish and Mahnken,
2001). The reduction in many of these blood chemistry parameters are similar to that described by Meador et al. (2006) for juvenile Chinook exposure to high levels of PAHs, which was
characterized as “toxicant-induced starvation”.

857

4.1.2. Sculpin plasma chemistry
The high variability among sites and sexes for the blood
chemistry parameters for staghorn sculpin indicate no substantial
differences in these parameters between reference and impacted
sites. However, a few parameters (ALB, GLU, and TAGs) were lower
in female ﬁsh from the Puyallup, which is similar to that observed
for feral juvenile Chinook. These parameters were not consistent
between sexes, which may have been a result of several factors
including differential migration, feeding rate, or physiological
condition.
Sculpin bioaccumulated less CECs compared to juvenile Chinook
salmon at these sites (e.g., mean of 25 detected analytes for
Puyallup Chinook compared to 9 analytes for sculpin at this site),
which is likely attributed to location within the estuary, and lower
rates of dietary uptake and water ventilation (Meador et al., 2016).
Even though sculpin, a benthic ﬁsh, was expected to remain in
these local estuaries for an extended period, males and females will
migrate offshore into deeper water (Tasto, 1976) and they can
exhibit differential movement. The lack of substantial differences in
the plasma chemistry parameters for this species between sites was
likely due to uncertain exposure and low concentrations of accumulated CECs, high variability in parameter responses, age, and
uncertainty regarding their residence time in these estuaries.
The most important observation for sculpin is that there were
only weak differences among sites for female ﬁsh as highlighted in
the multivariate plots (Fig. 3, Figs. S4, and S5) collected from the
same estuaries as juvenile Chinook salmon. This is striking given
the unknown age and residence history for these ﬁsh compared to
the well-characterized history for juvenile Chinook, which strongly
supports the observation of site-induced differences for salmon
exposed to these CECs.
4.2. Fish health in the ﬁeld
For the estuaries studied, there are two hatcheries on the Nisqually and Puyallup systems and one hatchery on Sinclair inlet that
can be used to assess survival as determined with the smolt to adult
return ratio (SAR), of ocean-type Chinook as described in Meador
(2014). The previous 12 years of available data were selected
because these provided the greatest overlap among the hatcheries.
The mean (SEM) SAR for the Clear Creek and Kalama hatcheries on
the Nisqually River was 0.92 (0.10) % and 0.75 (0.11) % respectively
for the release years 1999e2010 (n ¼ 12 for both). The mean (SEM)
SAR for the Voight's Creek and Puyallup Tribal hatcheries that
release ﬁsh to the Puyallup River over this same period was 0.46
(0.11) % (n ¼ 8) and 0.21 (0.09) % (n ¼ 3). The mean (SEM) survival
for the Gorst Creek Rearing pond ﬁsh transiting Sinclair Inlet was
0.45 (0.10) % (n ¼ 5) (ANOVA p ¼ 0.007). Based on posthoc tests at
an alpha value of 0.05, the hatcheries were ranked by the SAR (high
to low) as follows: Clear Creek ¼ Kalma > Gorst Creek ¼ Puyallup
tribal ¼ Voight's Creek.
A noteworthy observation from our study concerns the health of
the ﬁsh sampled at these sites. The protocol for capturing and
handling ﬁsh was the same for each site and transit time did not
vary substantially among collection events; however, the Nisqually
ﬁsh were subjected to one extra sorting step for the detection of
coded wire tags. None of the Nisqually or Voight's Creek Hatchery
Chinook died in transit during transport from the ﬁeld to our laboratory. In contrast, approximately 50% of the Puyallup estuary and
Sinclair Inlet ﬁsh died in the transport cooler. These results may be
consistent with a study by Ings et al. (2012) who observed substantial physiological changes in rainbow trout subjected to acute
handling stress after being exposed to WWTP efﬂuent for 14 days.
Fish that were handled exhibited strong increases in cortisol after
4 h and 24 h post handling (up to 60 ng/mL), whereas levels in

 858

J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861

control ﬁsh rapidly declined after a few hours. Sustained elevated
cortisol concentrations in Chinook salmon has been associated with
increased disease and death (Fagerlund, 1967), which has important implications for feral ﬁsh avoiding predation or exposure to
pathogens. Related to this is a study by Varanasi et al. (1993) who
reported statistically signiﬁcant increases in mortality for juvenile
Chinook salmon collected in contaminated estuaries (Puyallup and
Duwamish Rivers) compared to ﬁsh collected from upstream
hatcheries held simultaneously in the laboratory for 40 d (86e88%
survival for hatchery ﬁsh and 56e58% for estuary ﬁsh). No differences were observed between hatchery (88%) and estuary ﬁsh
(81%) from the Nisqually River system, the reference site for this
experiment and the present study.
4.3. Fish health and metabolic parameters due to CEC exposure in
the laboratory
Although the laboratory-exposed ﬁsh consumed less food than
expected, they still bioaccumulated most CEC analytes in the
mixture in this strictly dietary study. The dietary route of exposure
is generally not considered in other studies when evaluating CEC
exposure for feral ﬁsh; however, data from the current study supports inclusion for any such assessment. More importantly, tissue
concentrations of these CECs and plasma levels should be the focal
dose metric for risk assessment (Meador et al., 2008, 2017).
From days 0e32 the high-dose ﬁsh exhibited essentially no increase in body mass relative to the control ﬁsh and were likely
responding to increases in tissue CECs. Interestingly, the mean
weight for the day 50 ﬁsh in the low and medium dose treatments
was substantially lower relative to the control and high dose ﬁsh.
Only minor changes in average ﬁsh mass were expected due to the
short time frame for depuration, which was evident for the control
ﬁsh. Additionally, a number of blood chemistry parameters that
were altered in the day 32 ﬁsh were also altered for the day 50
sampling period including ALB, ALKP, CHOL, CREA, GLOB, TP, and
TAGs. The aforementioned study by Ings et al. (2012) demonstrating increased cortisol after CEC exposure and handling stress
may also be relevant here because ﬁsh in all treatments were
handled (weighed) and increased cortisol is known to inhibit
growth in rainbow trout (Gregory and Wood, 1999).
4.4. Extent of validation for ﬁeld study results in the laboratory
exposures
Comparing blood plasma parameters among ﬁsh under variable
conditions is complex and usually subjected to confounding factors.
In the present study, ﬁeld-collected Chinook clearly exhibited a
pattern of blood chemistry parameters that, in general, reﬂect that
seen for food-deprived ﬁsh. Of the 11 blood chemistry parameters
for feral ﬁsh from impacted sites exhibiting a difference compared
to reference site ﬁsh, 8 of those parameters were consistent with a
pattern indicating a starvation-like response. Fish in the laboratory
study exhibited plasma chemistry values opposite to the ﬁeldexposed ﬁsh with many parameters elevated relative to the control ﬁsh. As reported by Congleton and Wagner (2006), TAGs and
GLU can trend up or not change for the ﬁrst several days of fasting,
then decline as ﬁsh exhaust stored energy. Additionally, migrating
ﬁsh may be somewhat energy depleted compared to laboratoryreared ﬁsh and show a stronger response in blood chemistry due
to contaminant exposure, or fasting as noted by Congleton and
Wagner (2006). In that study, laboratory-reared rainbow trout
(RBT) and juvenile Chinook salmon exhibited large declines in body
mass but little change in many of the same blood chemistry parameters as the present study after food deprivation during winter
months (7e14 d or 35 d during January (RBT) and March,

respectively), which was the time of year for our laboratory study.
Contrary to this, Congleton and Wagner (2006) examined
migrating juvenile Chinook salmon in the laboratory in the spring
(May) and they exhibited strong declines in ALP, CHOL, GLU, TP, and
TAGs, with an increase in LIPA after 8e16 days of food deprivation.
Another important observation from Congleton and Wagner (2006)
is that food-deprived migrating chinook can lose half of their
whole-body lipid content within a few weeks, whereas fed ﬁsh can
increase in lipid content. As seen in the present study, feral juvenile
Chinook did not exhibit differences in whole-body lipids among
sites as might be expected from food-deprived ﬁsh suggesting a
contaminant-induced response rather than physical starvation.
Our ﬁeld data strongly suggest a starvation-like physiological
response in ﬁsh from contaminated estuaries, even though conventional metrics (e.g. whole-body lipid and CF) did not indicate
impairment. The results are less clear for the laboratory-exposed
ﬁsh, which exhibited obvious growth impairment and uncertain
blood chemistry responses. Also noteworthy is the lack of a strong
response in the blood chemistry parameters on day 32 from the
food-deprived ﬁsh even though they lost considerable mass during
this time.
Under conditions of ﬁeld exposure, ﬁsh are exposed to a wide
variety of contaminants that can bioaccumulate via gill ventilation
and ingestion. The ﬁeld-collected Chinook were exposed for a few
weeks, which was similar to that for the lab ﬁsh. It is important to
note that the lab ﬁsh were exposed via diet only and it would likely
take considerably longer for tissue residues of these contaminants
to accumulate compared to ﬁsh exposed to both aqueous and dietary levels. Additionally, the exposure mixture of contaminants for
each group of ﬁsh was substantially different, with the ﬁeld ﬁsh
exposed to a far larger number of CECs (both quantiﬁed and
unmeasured).
Noteworthy is a companion study by Yeh et al. (2017) who reported modulation of liver mitochondrial function in the Chinook
salmon collected in the present study, which is consistent with a
disruption of metabolic processes. Fish collected from the CECimpacted ﬁeld sites and exposed to CECs in the laboratory trended toward reduced liver mitochondrial content and elevated
respiration per mitochondria relative to control and reference ﬁsh.
Moreover, proton leak respiration (i.e. State 4 respiration induced
by oligomycin) was increased by 40e70% relative to controls in the
laboratory-exposed ﬁsh, indicative of mitochondrial uncoupling
and reduced functional efﬁciency. Several of the CECs in this study
including PFOSA and triclosan are known uncouplers of mitochondrial respiration (Schnellmann and Manning, 1990; Shim et al.,
2016).
4.5. Effects of mixture exposures
Exposure to multiple pharmaceuticals at therapeutic doses can
lead to adverse effects in humans due to multi-drug interactions.
Although understudied in ﬁsh, it is possible that similar exacerbation of adverse physiological effects will also occur in ﬁsh from
multiple exposures relative to those from single compounds. Given
the large number of co-occurring compounds in WWTP efﬂuent,
the likelihood of adverse effects or negative interactions is
increased. For the laboratory study, most of the Response Ratios
were due to calcium channel blockers (amlodipine, diltiazem, and
desmethyldiltiazem) and ranged from 87 to 95% of the value for
these doses. There are few studies on the toxicity of these compounds to ﬁsh; however, Kim et al. (2007) observed a 96 h LC50 of
15 mg/L for diltiazem and Steinbach et al. (2016) reported no effects
on growth for rainbow trout exposed at concentrations up to 30 ng/
mL. It is not known if these compounds would impair ﬁsh growth
or alter the plasma parameters examined in the present study. The

 J.P. Meador et al. / Environmental Pollution 236 (2018) 850e861

other compounds with elevated RR values include azithromycin,
diphenhydramine, ﬂuoxetine, metformin, and sertraline. Some of
these (e.g. metformin) may inhibit growth and alter metabolic
pathways. A recent study (Niemuth and Klaper, 2015) demonstrated reduced growth in male fathead minnow (Pimephales
promelas) exposed to metformin at 40 ng/mL, which is essentially
our predicted plasma concentration for the high dose ﬁsh and less
than half the human Cmax value (Schulz et al., 2012). Additionally,
tested compounds in the present study without Cmax values (e.g.,
perﬂuorocarbons) and those below detection but possibly occurring at concentrations considered adverse such as ﬂuocinonide and
triclosan may also cause adverse metabolic effects (Meador et al.,
2017).
5. Conclusions
The present study suggests that exposure to CECs resulted in
adverse physiological effects on the metabolic status of feral juvenile Chinook salmon as seen in blood chemistry parameters serving
as early indicators. Despite the fact that we observed a number of
potential emerging contaminants in the ﬁeld, it is likely that the
juvenile Chinook collected near the two WWTPs were exposed to a
variety of other contaminants including a large number of unmeasured pharmaceuticals, personal care products, and industrial
compounds. Based on recent studies, exposure to metals, PAHs, and
organochlorine compounds were potentially minor for ﬁsh in the
present study and may not have been contributory to the observed
responses. Accordingly, it is unknown what combination of CECs
and other contaminants would be causative for these responses;
however, based on the obvious lack of overt impairment as
measured by the condition factor and total lipid content, it appears
that ﬁsh in the WWTP impacted estuaries exhibited metabolic
dysfunction that appeared to mimic starvation conditions but was
likely toxicant induced. Metabolic disruption was also observed in
laboratory-exposed ﬁsh as noted by changes in ﬁsh mass and some
plasma parameters; however, the responses were qualitatively
different possibly due to differences in exposure route, mixture
composition, life-cycle stage, seasonal changes in physiology, and
the manifestation of responses over time.
A recent study concluded that juvenile Chinook salmon
migrating through contaminated estuaries in Puget Sound exhibited a strong reduction in survival (two-fold) compared to those
migrating through uncontaminated estuaries Meador (2014). Some
of the lowest survival rates for juvenile Chinook occurred in estuaries that have WWTP discharges into the estuary or nearshore
areas where Chinook reside before moving into open water. The
aforementioned study provided data on a few well-known contaminants such as PAHs, butyltins, metals, and PCBs that were
considered as markers of contaminant exposure for these impacted
local estuaries, but not linked causally to adverse effects (Meador,
2014). Given the large number of compounds delivered to these
estuarine areas from WWTPs and other sources and their potential
for adverse effects on several physiological processes, a more
detailed accounting of potential effects and rates of survival for all
biota in these areas is warranted.
Acknowledgements
This work was supported in part by a grant from the Washington
Department of Ecology (G1300089), the National Institute of
Environmental Health Sciences Superfund Research Program [P42ES004696], and the University of Washington Sea Grant Program,
pursuant to NOAA Project R/OCEH-8 [NA10OAR4170057]. Andrew
Yeh was supported in part by the UWNIEHS training grant in
Environmental Pathology/Toxicology (T32ES007032). The authors

859

gratefully acknowledge insightful review comments from Dr. Irvin
Schultz and 3 anonymous reviewers. We also appreciate the technical assistance in the laboratory and ﬁeld provided by University of
Washington personnel from the School of Fisheries and School of
Public Health. Additional thanks to the laboratory staff at AXYS
Analytical Services, Ltd.
Appendix A. Supplementary data
Supplementary data related to this article can be found at
https://doi.org/10.1016/j.envpol.2018.02.007.
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