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 dwalker@ag.arizona.edu2 USGS., WRD, 520 N. Park Ave, Suite 221, Tucson, AZ 85719 nvp@email.arizona.edu3 USGS-Florida Caribbean Science Center, 7920 NW 71st St., Gainesville Florida, 32653 tim_s_gross@usgs.gov 4 USGS, National Water Quality Laboratory, Denver Federal Center, P.O. Box 25046, MS 407, Lakewood, CO 80225-0046 efurlong@usgs.gov 5 USGS, WRD, P.O. Box 1230, Iowa City, IA 52240 dwkolpin@usgs.gov6 Delaware State University, 1200 N. DuPont Highway Dover, DE 19901 dmcintosh@desu.edu

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?