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Monitoring of endocrine disruption in different milieu matrices W. Dhooge , F.H. Comhaire, A. Mahmoud, F. Eertmans, J.M. Kaufman Endocrinology/Andrology,

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Presentation on theme: "Monitoring of endocrine disruption in different milieu matrices W. Dhooge , F.H. Comhaire, A. Mahmoud, F. Eertmans, J.M. Kaufman Endocrinology/Andrology,"— Presentation transcript:


2 Monitoring of endocrine disruption in different milieu matrices W. Dhooge , F.H. Comhaire, A. Mahmoud, F. Eertmans, J.M. Kaufman Endocrinology/Andrology, University Hospital Ghent, Belgium  FlandersBio, Belgium

3 Introduction

4 A few facts n Man made chemicals are found everywhere on the planet n Many of these xeno-biotics may interfere with the endocrine system n Mainly with (anti-)estrogenic action n These include PCBs, pesticides, plastics, heavy metals

5 “Possible” effects n Cancers n Obesity, diabetes n Genital tract anomalies n Pubertal disturbances n Infertility

6 Skakkebaek et al (2001), Hum Reprod 16: 972–978 The spectrum of Testicular dysgenesis syndrome

7 Problems of analytical testing n Number of chemicals is growing n It is costly & difficult to test each separately n Frequently, no standard method is available n Analytical tests do not detect mixture effects

8 Biological tests n Receptor-based assays n Sensitive (signal amplification), detect mixture effects n Receptor activation  Signal (color change etc) n Cells expressing receptor (yeast, liver,..)

9 Biological tests n Cell-based assays  possible false negative results (cell toxicity) in heavily polluted environmental samples n Receptor test without a cell !!!

10 Objectives Develop screening tools: n affordable, n sensitive, rapid n biologically relevant Allow screening : n environmental samples n Humans: exogenous, endogenous substances n Low doses of highly active substances (natural estrogens)

11 The Yeast assay (YES)

12 Estrogen inducible expression system in yeast Adapted from Routledge et al., 1996 Nucleus ER Hsp ERE Lac-Z Luc  -Galactosidase Absorbance read at 540 nm

13 Yeast assay as developed by Routledge and Sumpter (1996)

14 Validation of the Yeast assay

15 Detection limit ethanol / DMSO *Significantly different from previous measurement, p<0.005 ** Significantly different from day 2 measurement, p<0.01 Days of incubation Dimethylsulfoxide Ethanol ** * * *  -estradiol (ng/l) Dimethyl sulfoxide Ethanol ** * * *

16 Ringtest The YES was performed according to Routledge and Sumpter (1996). Test plates were incubated for 10 days and absorbances (540 / 620 nm) were measured at regular intervals. 17β-estradiol (E2) was used as a positive control. Relative Potency (RP) = EC 50 (E2) / EC 50 (test compound). Relative Induction Efficiency (RIE) = A max (test compound) / A max (E2), with A max = maximal absorbance. Variability (expressed as coefficient of variation) Intra-lab: 0.52 % % Intra-lab: 1.0 % % Inter-lab: 0.84 % % Inter-lab: 0.6 % - 17 % (except for DDE & lindane) (except for endosulfan) *not tested in lab 1 *not detected in lab 3 *** ** Relative potency

17 Problems with the Yeast assay Toxicity (also with other tests using living organisms) Cell wall permeability Time consuming Development of a receptor-based test system Based on competitive binding of compounds to the ER alpha Receptor production: truncated human estrogen receptor coupled to glutathione sulphotransferase (GST) for purification Large scale production of the protein Receptor test: rationale

18 The Estrogen Receptor Based Assay (ERBA)

19 Principle of the ERBA competitive binding test E E2 ER E2 Anti-GST GST-ER

20 Competition of (xeno-) estrogens with 17  -Estradiol in ERBA

21 17  -Estradiol curve for ERBA Estradiol curve log conc (M) cpm IC 50

22 Relative induction efficiencies (RIE) of tested compounds in the ERBA and YES (n>3 independent experiments) EC50 (GM) YES IC50 (GM) ERBA RIE (AM) YES ERBA 17  -estradiol 2.30E E Bisphenol-A2.83E E ,4’-Biphenol9.87E E n-Octylphenol2.46E E p-Nonylphenol2.21E E Lindane1.10E E ICI E E Methoxy chlore 1.80E-05NA107.9 EC50: 50% effect concentration; RIE: relative induction efficiency; GM: Geometric mean, AM. Arethmatic mean

23 Similar results Negative tests are negative in all systems Positives are positive including: Anti-estrogens Methoxychlor and permethrin (not shown) Absolute sensitivity (EC 50 values) are 3-10x lower than YES Possible toxic effects in cell systems Possible toxic effects in cell systems Substances with low binding affinity in the YES & ERBA yield similar results Receptor Test vs YES

24 Environmental Samples in Different Test Systems CodeSampleERBAYESMVLN 01J 143S water J 142S water J 140S water J 141S water J 145S water J 144S waterout of range B015-2Industry Toxic 02C045S water C169S water C172S water B011-2Industry Toxic 02C046S water C171S water B011-3Industry0.50

25 Competition of environmental sample with 17  - Estradiol for TER-GST J 14301J 14201J 14001J 14101J 14501J B C04502C16902C172 02B C04602C171 02B C044 02B015-3 ERBA YES MVLN

26 Environmental samples in the ERBA test: conclusions ERBA-test can be used for pure substances AND environmental samples Test results are mostly in the same order of magnitude as the YES and MVLN For some samples discripancies may be due to:  Cell toxicity  Mixture of estrogens & anti-estrogens Non-specific binding in ERBA: less likely in view of shape of binding curves

27 Toxicity-guided fractionations

28 Environmental sample filtration dissolved phase Identification of estrogens in active fractions via LC-MS/MS Particulate material YES Fractionation procedure protocol Investigate relationship between concentration of compounds and estrogen activity in different fractions SPE Extract: 250 µl

29 Fractionation of environmental samples

30 A % estrogen activity relative to max E2 standard curve Fraction number LC-MS/MS fr4-6: Polar fraction? fr 7&8: Methyl, ethyl & propylparaben fr9&10: Estron, E2, EE2, Propylparaben fr16-19: 4-n-octylphenol, 4-n- nonylphenol, 4-tertiair octylphenol fr 22-29: apolar substances ? Fractionation of environmental samples

31 Correlation between estrogen activity in fractions & chemical concentration AB conc octyl phenol (as pg E2/L) pg E2/L in fr 17&18 conc methyl parabene (ng/L) pg E2/L in fr 7&

32 Fractionation of Environmental samples Fraction number A % estrogen activity relative to max E2 standard curve Relation between estrogen activity in fraction 7&8 & fr 17&18 with substances present in these fractions Results YES correlates with methyl parabene & octyl phenol

33 Toxicity-guided fractionations n Industrial samples: alkyl phenols up to 54 % of the total estrogenic activity n This is performed on 250µl of the extract n Parabens & alkyl phenols related to surface water estrogenic activity (has never been demonstrated before)

34 Summary fractionation n The developed methods are sensitive, reproducible & effectively detect the cause of estrogen activity (EA). n The most active fractions: fr9&10: natural & synthetic estrogens. No quantitative relation n Interesting: Significant relation between estrogen activity in fr 7&8 & methyl paraben; & fr 17&18 & octyl phenol n The concentrations measured explain 50% of the EA maximum n Further research: other substances? Matrix effects?

35 Studies on Human serum

36 The aromatase study n Placebo-controlled study n Aromatase inhibitor (letrozole) n Testosterone  estradiol n Hormones (classical methods) n Total estrogen load (YES)

37 The aromatase study Mean ng E 2 equiv /LStdev Stdev E2 load before E2 load after Difference % Percentage decline 83.0%10.3% Correlation with decline in E (p=0.003) Detection limit (E2 equivalent) 5

38 The adolescents’ study n 550 adolescent males n Hormones (classical methods) n Total estrogen load (YES)

39 The adolescents’ study AgeWeightBMI E2 (pg/ml) frE2 (pg/ml) logYES- corrected 0.21a 0.12 b 0.05 ns 0.40 a 0.39 a Age 0.24 a 0.06 ns 0.42 a 0.41a Weight 0.84 a 0.45 a 0.53 a Height 0.21 a 0.48 a 0.51 a BMI a 0.37a a: p< , b: p<0.01

40 Prediction of mixture effects

41 n Data from actual combination experiments were compared to theoretical curves assuming additive combination effects (1+1=2) n Deviation from additivity suggests interaction between compounds (1+1=3, synergism) (1+1=3, synergism)

42 Estradiol o,p-DDT Summation Mixture Arbitrary units Observed effect 0.2 mM Expected effect 0.2 mM Effect 0.1 mM Conc. (mM) Effect summation 3Only applicable with linear dose response relationships Cell count

43 E Mix Background 19 nM 39 nM 72 nM 32 nM 16 nM 98 nM 72 nM 52 nM 0.3 pM After Kortenkamp et al., (1999) MCF7 (Br ca) cell growth with a mixture of low level chemicals

44 For p,p’-DDE/E2 ( 41,7 pM) & lindane/E2 mixtures observed effect is higher than predicted But for bisphenol A Observed response after 3 days of incubation compared to the predicted response

45 Special thanks to: n The team of Milieu en Gezondheid (UGent, UIA, VUB, KUL, VITO,....) n A. Bossier, W. Verstraete, LabMeT n S. Stuyvaert, Nick Hendryckx, labo Andrology UZ Gent n Hormonology lab UZ Gent n T. Benijts/ Prof. W. Lambert: Labo Toxicologie FFW Ugent n A. De Winter M. Van Oost VMM Gent

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