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The Ecological Effects of Endocrine Disruption Dr. David Walker University of Arizona. David Walker 1 , Nick Paretti 2 , Gail Cordy 2 , Timothy S. Gross 3 , Edward T. Furlong 4 , Dana W. Kolpin 5 , and Dennis McIntosh 6 - PowerPoint PPT Presentation
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The Ecological Effects of Endocrine Disruption
Dr. David WalkerUniversity of Arizona
David Walker1, Nick Paretti2, Gail Cordy2, Timothy S. Gross3, Edward T. Furlong4, Dana W. Kolpin5, and Dennis McIntosh6
1 University of Arizona, Environmental Research Laboratory, 2601 E. Airport Dr., Tucson, AZ 85706 [email protected] USGS., WRD, 520 N. Park Ave, Suite 221, Tucson, AZ 85719 [email protected] USGS-Florida Caribbean Science Center, 7920 NW 71st St., Gainesville Florida, 32653 [email protected] 4 USGS, National Water Quality Laboratory, Denver Federal Center, P.O. Box 25046, MS 407, Lakewood, CO 80225-0046 [email protected] 5 USGS, WRD, P.O. Box 1230, Iowa City, IA 52240 [email protected] Delaware State University, 1200 N. DuPont Highway Dover, DE 19901 [email protected]
For Our Purposes…• An endocrine disruptor is a synthetic
(anthropogenic) chemical that when absorbed into the body mimics, blocks, or otherwise alters hormone level, function, or binding and subsequently disrupts normal bodily functions including behavioral and/or strictly physiologic responses.
Aquatic Ecology and Endocrine Disruption
• An individual organisms ability to better-exploit a resource (or group of resources) in the face of environmental stress and inter-specific competition, coupled with conservation of the genetic material enabling this exploitation, is what drives speciation.
• Genetic conservation of traits is initiated, and sustained by, subtle behavioral cues for mating, spawning, aggression, territoriality, avoidance, etc.
• Any impairment of these behavioral cues or manifestation into physiological or morphological changes has the capability to stunt speciation by lowering fertility and fecundity.
Endocrine Disrupting Compounds
• FAR more than what can be included in this presentation.
• By the time breakdown products and metabolites are added to the mix, iterations become astronomical.
Just a Few Examples by Use Category
• Detergent Metabolites• Fire/Flame Retardants• Fragrances/Flavors• Fuels/PAH’s• Herbicides/Insecticides• Household Wastewater Compounds• Non-Prescription Drugs• Plasticizers/Antioxidants• Prescription Drugs• Steroids
At the landscape scale, those compounds known to be “powerful” EDC’s, but are not environmentally-persistent, exert less of an effect than those persistent, but relatively weaker, compounds.
Quantification and Research Design Issues; One Size Does Not Fit All
Mechanistic U
nderstanding
Ecological Significance
Genetic
Biochemical
Physiological
Behavioral
Reproductive
Assemblages
Histopathological
Immunological
Bioenergetic
Populations
Observational versus Controlled Studies
• True control and replication is not possible in the field.
• Laboratory studies with control and replication give up some ecological significance.
Exposure and Causation• Several studies have examined the
effect of one or a very few EDC’s on the physiological response of an organism.
• The vast magnitude of compounds in a matrix makes assumptions about individual compounds difficult to ascertain.
• Non-monotonic dose-response curves
With new and emerging contaminants found almost on a daily basis, making assumptions about exposure and physiologic response must always carry the caveat “of the compounds we analyzed for”…
Grab, Composite, or Integrated Samples?
• Problems associated with not knowing long-term exposure to fish or other organisms.
Passive Organic Chemical Integrative Sampler (POCIS) and/or Semi-Permeable Membrane
Devices (SPMD’s aka “fatbags”)
Of all the tools at our disposal to study complex environmental issues in aquatic ecosystems, a sound understanding of ecological principles as they pertain to these ecosystems is the most essential.
Quantifying Endocrine Disruption in a Threatened and Endangered Fish
Species
• Unlike semi-arid or north-temperate regions, effluent-dependent water’s (EDW’s) in arid regions usually contain 100% effluent year-round.
The Santa Cruz River Near Tucson, Arizona
• Flows from Mexico near Nogales, Sonora northward to Tucson, Arizona.•The only sections with flowing water are those due to discharge from WWTP’s.
Roger Road WWTP• Built in 1951.• Treated effluent is discharged into the
Santa Cruz River or diverted into the city’s reclaimed water system.
• Treats the wastewater generated by a population of about 419,000.
• A capacity of 41 mgd and treated an average of 38 mgd from 2004 to 2005.
• Produces secondarily-treated wastewater
Roger Road WWTP
Tucson
Santa Cruz River
0
5
10
15
20
25
30
35
40
Time
Leve
lsTemp (C)DO (mg/L)
This Study• Laboratory study with controls,
replicates, and randomization.• Use fish native to the region (largely
pollution-tolerant).• Framework or foundation for refinement
of future studies.• Varying doses of effluent (“treatments”).• Concentrate on long-term, persistent
compounds.
Bonytail Chub (Gila elegans)
Treatment Treatment
Control
Control
Water temperature maintained between 25-29o C.Photoperiod was maintained at 12 hours of light and dark
Treatment/Dosages• Fish in raceways exposed for 3 months
per treatment• 1st treatment = 1/3 by volume treated
ww and 2/3 water treated by RO• 2nd treatment = 2/3 by volume treated
ww and 1/3 water treated by RO• 3rd treatment = full strength treated
ww
Results
Compounds Detected in the Treatment and Control Tanks
0.00000.10000.20000.30000.40000.50000.6000
N,N
-di
ethy
ltolu
amid
e(D
EE
T)
Caf
fein
e
Cho
lest
erol
Cot
inin
e
Tri (
2-ch
loro
ethy
l)ph
osph
ate
Trib
rom
omet
hane
Trip
heny
lph
osph
ate
Compounds
(μg/
L)
Control-Dose 1Treatment-Dose 1Control-Dose 2Treatment-Dose 2Control-Dose 3Treatment-Dose 3
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Dose 2Dose1 Dose 3
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Dose 1 Dose 2 Dose 3
Detergent Metabolites
Fire/Flame Retardants
Fragrances/flavors
Fuels/PAHs
Plasticizers/antioxidants
Herbicides/insecticides
Non-prescription drugs
Prescription Drugs SteroidsHousehold Wastewater Compounds
Males - Overall
17β-EstradiolControl (n = 6): 217.3
Treatment (n = 13): = 547.4
11-ketotestosteroneControl (n = 6): = 820.8
Treatment (n = 13): = 473.5
VitellogeninControl (n = 6): = 0.09
Treatment (n = 13): = 0.32
17-B
ETA
(pg/
ml)
100
200
300
400
500
600
700
800
900
1000
1100
Control Treatment
T/C
11-K
ETO
(pg
/ml)
0
200
400
600
800
1000
1200
1400
Control Treatment
T/C
VIT
ELL
O (
pg/m
l)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Control Treatment
T/C
Females - Overall
17β-EstradiolControl (n = 54): 568.2
Treatment (n = 47): 403.7
11-ketotestosteroneControl (n = 54): 591.3
Treatment (n = 47): 530.4
VitellogeninControl (n = 54): 0.18
Treatment (n = 47): 0.18
17-B
ETA
(pg
/ml)
0
200
400
600
800
1000
1200
Control Treatment
T/C
Missing Rows 25
Oneway Anova
Oneway Analysis of 17-BETA (pg/ml) By T/C
11-K
ETO
(pg/
ml)
100200300400500600700800900
1000110012001300
Control Treatment
T/C
Missing Rows 25
Oneway Anova
Oneway Analysis of 11-KETO (pg/ml) By T/C
VIT
ELL
O (pg
/ml)
-0.1
0.1
0.3
0.5
0.7
0.9
1.1
Control Treatment
T/C
Missing Rows 25
Oneway Anova
Oneway Analysis of VITELLO (pg/ml) By T/C
CONTROL FEMALE
TREATMENT MALE
CONTROL FEMALE
TREATMENT MALE
CONTROL FEMALE
TREATMENT MALE1/
32/
33/
3
Trea
tmen
t Sex
/Con
trol S
ex w
ithin
DO
SE
0 200 400 600 800Mean(17-BETA (pg/ml))
CONTROL FEMALE
TREATMENT MALE
CONTROL FEMALE
TREATMENT MALE
CONTROL FEMALE
TREATMENT MALE1/
32/
33/
3
Trea
tmen
t Sex
/Con
trol S
ex w
ithin
DO
SE
.0 .1 .2 .3 .4 .5Mean(VITELLO (pg/ml))
Synergistic Effects
• Ratios of primary male and female sex hormones, in “undisturbed” populations would be expected to have an inverse relationship i.e. as one increased, the other would decrease.
• We could therefore assume that major deviations from this inverse relationship between male and female primary sex hormones, could be attributed to impairment.
5
5.5
6
6.5
7
6
6.25
6.5
6.75
7
7.25
0.1
0.3
0.5
0.7
0.9
ln 17-beta
5 5.5 6 6.5 7
ln 11-keto
6 6.25 6.5 6.75 7 7.25
sqrtvitello
.1 .2 .3 .4 .5 .6 .7 .8 .9 1
5.5
6
6.5
7
5.5
6
6.5
7
0.1
0.2
0.3
0.4
0.5
0.6
0.7
ln 17ß
5.5 6 6.5 7
ln 11Kt
5.5 6 6.5 7
ln vtg
.1 .2 .3 .4 .5 .6 .7
ln 17β ln 11-keto
ln Vtg
ln 17β 1.00 -0.89 0.74ln 11-keto
-0.89 1.00 -0.73
ln Vtg 0.74 -0.73 1.00
Control Males Treatment Malesln 17β ln 11-
ketoln Vtg
ln 17β 1.00 -0.50 0.69ln 11-keto
-0.50 1.00 -0.28
ln Vtg 0.69 -0.28 1.00
5
5.5
6
6.5
7
5
5.5
6
6.5
7
0.1
0.3
0.5
0.7
0.9
ln 17ß
5 5.5 6 6.5 7
ln 11Kt
5 5.5 6 6.5 7
ln vtg
.1 .2 .3 .4 .5 .6 .7 .8 .9 1
5
5.5
6
6.5
7
5
5.5
6
6.5
7
0.1
0.3
0.5
0.7
0.9
ln 17ß
5 5.5 6 6.5 7
ln 11Kt
5 5.5 6 6.5 7
ln vtg
.1 .2 .3 .4 .5 .6 .7 .8 .9 1
ln 17β ln 11-keto
ln Vtg
ln 17β 1.00 -0.67 0.52ln 11-keto
-0.67 1.00 -0.70
ln Vtg 0.52 -0.70 1.00
Control Females Treatment Femalesln 17β ln 11-
ketoln Vtg
ln 17β 1.00 0.11 0.28ln 11-keto
0.11 1.00 -0.36
ln Vtg 0.28 -0.36 1.00
• Synergism, feedback mechanisms, and non-linearity of bio-markers makes data reduction necessary to determine trends.
• Ordination is a good statistical tool but still assumes some degree of linear correlation as would occur with a typical dose-response curve.
Eigenvalue 2.4994 1.5983 1.3520 0.7843 0.4364 0.2306 0.0990
Percent 35.7059 22.8328 19.3145 11.2038 6.2341 3.2950 1.4140
Eigenvectors
Impairment 0.03207 0.47871 -0.59971 0.03198 0.52405 -0.28832 -0.22668
Det. Met -0.02386 -0.69182 -0.12719 0.13721 0.65181 0.20503 0.13755
Fire Ret. 0.27206 0.14664 0.48835 0.74288 0.19262 -0.10884 -0.25528
Fragrances -0.45315 0.45851 0.06826 0.20318 0.17053 0.60972 0.37099
Herbicides -0.24354 0.13071 0.61232 -0.51883 0.45492 -0.26042 -0.06864
HH Waste 0.59204 0.16867 0.05748 -0.08259 0.11987 -0.15914 0.75579
Plasticizers 0.55607 0.12227 0.05280 -0.33315 0.11409 0.63094 -0.38854
Males
17ß-11KT Impair
Detergent Met.
Fire/Flame Ret.
Fragrances
Herbicides
Household Waste
Plasticizers
x
y
z
Eigenvalue 2.5424 1.3785 1.1161 0.9430 0.6582 0.2760 0.0858
Percent 36.3199 19.6952 15.9440 13.4710 9.4030 3.9433 1.2262
Eigenvectors
Impairment 0.29245 0.18743 -0.64153 0.25736 0.51884 -0.35362 -0.08546
Det. Met 0.05636 -0.56419 0.38059 0.43444 0.55723 0.18017 0.04430
Fire Ret. 0.04197 0.51151 0.47240 0.59978 -0.16230 -0.31014 -0.17655
Fragrances -0.43453 0.42877 -0.21006 0.27596 0.17682 0.66476 0.18408
Herbicides -0.26875 0.34161 0.37217 -0.51933 0.59522 -0.22040 -0.00263
HH Waste 0.57808 0.21846 0.15670 -0.06981 0.01724 0.10029 0.76047
Plasticizers 0.56064 0.19147 0.11504 -0.18590 0.09008 0.49575 -0.58936
17ß-11KT Impair
Detergent Met.
Fire/Flame Ret.
FragrancesHerbicides
Household Waste
Plasticizers
x
y
z
Females
Summary• Significant hormonal impairment of
both sexes, as compared to controls, at very low concentration of compounds.
• This impairment could never have been determined in a field study.
• Commonly-used parametric analyses are often inadequate in determining impairment.
Summary (cont)
• Determination of either hormonal impairment or endocrine disruption requires using phased biomarkers.– Phase 1: Aromatase/GnRH– Phase 2: GtH I, GtH II– Phase 3: Sex hormones– Phase 4: Protein development (vtg,
oocyte, spermiation)– Phase 5: Intersex
Current and Future Research• Fertility/fecundity and sex
ratio/development of F2 generation.
• Behavior.• Treatments using streambed
sediment from affected EDW’s.
This study is highly representative of the biological effect of endocrine-disrupting
compounds at the landscape scale.
Questions?