Council Regulation (EC) No 440/2008 of 30 May 2008 laying down test methods pursuant to Regulation (EC) No 1907/2006 of the European Parliament and of the Council on the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) (Text with EEA relevance)

If a solvent is used, then both a dilution water control and a solvent control should be included. The two controls should be compared for each response and combined for statistical analysis if no significant difference is found between the controls. Otherwise, the solvent control should be used for NOEC determination or ECx estimation and the water control is not used. See restriction in the validity criteria (Paragraph 7)

For length, weight, proportion of egg hatch or larval mortality or abnormal larvae, and first or last day of hatch or swim-up, a T-test or Mann-Whitney test should be used to compare the dilution water- control and the solvent control at the 0,05 significance level, ignoring all treatment groups. The results of these tests should be reported.

Size Measurements (length and weight)

Individual fish length and weight values can be normally or log-normally distributed. In either case, the replicate mean values tend to be normally distributed by virtue of the Central Limit Theorem and confirmed from data from well over 100 ELS studies of three freshwater species. Alternatively, where the data or historical databases suggest a log-normal distribution for individual fish size values, the replicate mean logarithm of the individual fish values can be calculated and the data for analysis can then be the anti-logs of these replicate mean logarithms.

Data should be evaluated for consistency with a normal distribution and variance homogeneity. For this purpose, the residuals from an ANOVA model with concentration as the single explanatory class variable should be used. Visual determination from scatterplots and histograms or stem-and-leaf plots can be used. Alternatively, a formal test such as the Shapiro-Wilk or Anderson-Darling can be used. Consistency with variance homogeneity can be assessed from a visual examination of the same scatter plot or formally from Levene's test. Only parametric tests (e.g. Williams, Dunnett) need be evaluated for normality or variance homogeneity.

Attention should be paid to possible outliers and their effect on analysis. Tukey's outlier test and visual inspection of the same plots of residuals described above can be used. It should be recalled that observations are entire replicates, so omitting an outlier from analysis should be done only after careful consideration.

The statistical tests that make use of the characteristics of the experimental design and biological expectation are step-down trend tests, such as Williams and Jonckheere-Terpstra. These tests assume a monotone concentration-response and the data should be assessed for consistency with that assumption. This can be done visually from a scatter plot of the replicate means against test concentration. It will be helpful to overlay that scatter plot with a piecewise linear plot connecting the concentration means weighted by replicate sample size. Great deviation of this piecewise linear plot from monotonicity would indicate a possible need to use non-trend tests. Alternatively, formal tests can be used. A simple formal test is to compute linear and quadratic contrasts of the concentration means. If the quadratic contrast is significant and the linear contrast is not significant that is an indication of a possible problem with monotonicity which should be further evaluated from plots. Where normality or variance homogeneity may be an issue, these contrasts can be constructed from rank-order transformed data. Alternative procedures, such as Bartholomew's test for monotonicity can be used, but add complexity.

Figure 2

NOEC Flow-Chart Size Measurements (length and weight)

Image omitted; see official source

Text of image

Variances stabilising transform?

Normalising transform?

Tamhane-Dunnett test

Dunnett test

Transform to normal, homogenous?

Step-down Williams or Jonckherre

Rep means normal, homogenous?

Yes

Are data consistent with monotone concentration-response?

Rep means normal?

Variances equal?

If % effect at NOEC is large of % effect at LOEC is small, then try ECx

Step-down Jonckherre

No

Dunn or Mann-Whitney test

No

No

No

No

No

No

Yes

Yes

Yes

Yes

Yes

Yes

Dashed figures are paths for 1st and last day of hatch or swimup (*) or abnormal larvae

(*) These responses never satisfy assumptions for parametric analysis or models.

Unless the data are not consistent with the requirements for these tests, the NOEC is determined by a step-down application of Williams' or the Jonckheere-Terpstra test. OECD (2006) provides details on these procedures. For data not consistent with the requirements for a step-down trend test, Dunnett's test or the Tamhane-Dunnett (T3) test can be used, both of which have built-in adjustments for multiplicity. These tests assume normality and, in the case of Dunnett, variance homogeneity. Where those conditions are not satisfied, Dunn's non-parametric test can be used. OECD (2006) contains details for all of these tests. Figure 2 is giving an overview, how to find the test of choice.

Egg Hatch and Larval Survival

The data are proportions of eggs that hatch or larvae that survive in individual replicates. These proportions should be assessed for extra-binomial variance, which is common but not universal for such measurements. The flowchart in figure 3 is guidance for the test of choice; see text for detailed descriptions.

Two tests are commonly used. These are Tarone's C(α) test (Tarone, 1979) and chi-squared tests, each applied separately to every test concentration. If extra-binomial variance is found in even one test concentration, then methods that accommodate that should be used.

Formula 1

Tarone's C (α) test (Tarone 1979)

Image omitted; see official source

Where ̂p̂ is the mean proportion for a given concentration, m is the number of replicate tanks, nj is the number of subjects in replicate j, and xj is the number of subjects in that replicate responding, e.g. not hatched or dead. This test is applied to each concentration separately. This test can be seen as an adjusted chi-squared test, but limited power simulations done by Tarone have shown it to be more powerful than a chi-squared test.

Figure 3

NOEC Flow Chart for Egg Hatch and Larval Mortality

Image omitted; see official source

Text of image

Yes

Yes

Yes

No

Are data (*) consistent with a monotone concentration-response?

Step-down Rao-Scott Cochran-Armitage or Jonckheere test or, after arc-sin square-root transform, Williams test

Step-down Cochran-Armitage or Jonckheere test or, after arc-sin square-root transform, Williams test

Dunnett test

Dunn test or Mann-Whitney

No

Data normally distributed, homogenous after arc-sin square-root transform?

C(α) or chi-squared Test for extra-binominal Variance significant?

No

(*) Data are replicate proportion.

Where there is no significant evidence of extra-binomial variance, the step-down Cochran-Armitage test can be used. This test ignores replicates, so where there is such evidence, the Rao-Scott adjustment to the Cochran-Armitage test (RSCA) takes replicates, replicate sizes, and extra-binomial variance into account and is recommended. Alternative tests include the step-down Williams and Jonckheere-Terpstra tests and Dunnett's test as described for size measurements. These tests apply whether or not there is extra-binomial variance, but have somewhat lower power (Agresti 2002, Morgan 1992, Rao and Scott 1992, 1999, Fung et al. 1994, 1996).

First or Last Day of Hatch or Swim-up

The response is an integer, giving the test day on which the indicated observation is observed for a given replicate tank. The range of values is generally very limited and there are often high proportions of tied values, e.g. the same first day of hatch is observed in all control replicates and, perhaps in one or two low test concentrations. Parametric tests such as Williams and Dunnett are not appropriate for such data. Unless there is evidence on serious non-monotonicity, the step-down Jonckheere-Terpstra test is very powerful for detecting effects of the test chemical. Otherwise, Dunn's test can be used.

Larval Abnormalities

The response is the count of larvae found to be abnormal in some way. This response is frequently of low incidence and has some of the same problems as first day of hatch, as well as sometimes exhibiting erratic in concentration-response. If the data at least roughly follow a monotone concentration shape, the step-down Jonckheere-Terpstra test is powerful for detecting effects. Otherwise, Dunn's test can be used.

REFERENCES:

Agresti, A. (2002); Categorical Data Analysis, second edition, Wiley, Hoboken.

Dunnett C. W. (1955); A multiple comparison procedure for comparing several treatments with a control, J. American Statistical Association 50, 1096-1121.

Dunn O. J. (1964 ); Multiple Comparisons Using Rank Sums, Technometrics 6, 241-252.

Dunnett C. W. (1964); New tables for multiple comparisons with a control, Biometrics 20, 482-491.

Fung, K.Y., D. Krewski, J.N.K. Rao, A.J. Scott (1994); Tests for Trend in Developmental Toxicity Experiments with Correlated Binary Data, Risk Analysis 14, 639-648.

Fung, K.Y, D. Krewski, R.T. Smythe (1996); A comparison of tests for trend with historical controls in carcinogen bioassay, Canadian Journal of Statistics 24, 431-454.

Hochberg, Y. and A. C. Tamhane (1987); Multiple Comparison Procedures, Wiley, New York.

Hsu, J.C. (1996); Multiple Comparisons: Theory and Methods; Chapman and Hall/CRC Press, Boca Raton.

Jonckheere A. R. (1954); A distribution-free k-sample test against ordered alternatives, Biometrika 41, 133.

Morgan, B.J.T. (1992); Analysis of Quantal Response Data, Chapman and Hall, London.

OECD (2006). Current approaches in the statistical analysis of ecotoxicity data: A guidance to application. Series on Testing and Assessment, No. 54. Organisation for Economic Co-operation and Development, OECD, Paris..

Rao J.N.K. and Scott A.J. (1992) — A simple method for the analysis of clustered binary data, Biometrics 48, 577-585.

Rao J.N.K. and Scott A.J. (1999) — A simple method for analyzing overdispersion in clustered Poisson data, Statistics in Medicine 18, 1373-1385.

Robertson, T., Wright F.T. and Dykstra R.L. (1988); Order restricted statistical inference, Wiley.

Tarone, R.E. (1979); Testing the goodness of fit of the Binomial distribution, Biometrika 66, 585-590.

Williams D.A. (1971); A test for differences between treatment means when several dose levels are compared with a zero dose control, Biometrics 27, 103-117.

Williams D.A. (1972); The comparison of several dose levels with a zero dose control, Biometrics 28, 519-531.

Williams D. A. (1975); The Analysis of Binary Responses from Toxicological Experiments Involving Reproduction and Teratotlogy, Biometrics 31, 949-952.

Williams D.A. (1977); Some inference procedures for monotonically ordered normal means, Biometrika 64, 9-14.

Appendix 6

STATISTICAL GUIDANCE FOR REGRESSION ESTIMATES

General

The observations used to fit a model are replicate means (length and weight) or replicate proportions (egg hatch and larval mortality) (OECD 2006).

Weighted regression using replicate sample size as weight is generally advised. Other weighting schemes are possible, such as weighting by predicted mean response or a combination of this and replicate sample size. Weighting by reciprocal of within-concentration sample variance is not recommended (Bunke et al. 1999, Seber and Wild, 2003, Motulsky and Christopoulos 2004, Huet et al. 2003).

Any transformation of responses prior to analysis should preserve the independence of the observations and ECx and its confidence bounds should be expressed in the original units of measurement, rather than in transformed units. For example, a 20 % change in the logarithm of length is not equivalent to a 20 % change in length (Lyles et.al 2008, Draper and Smith 1999).

The flowchart in figure 4 gives an overview for ECx estimations. The details are described in the text below.

Figure 4

Flow chart for ECx Estimation of Replicate Mean Length, Weight, or Proportion of Egg Hatch or Larval Mortality, see text for more details

Image omitted; see official source

Text of image

Select a larget value of x or a different model

Is (a) predicted response at ECx within CI for control, or (b) predicted response within CI for predicted response at ECx or (c) CI for ECx too wide?

Compute 95 % CI for predicted response at control and at Ecx, Compute 95 % CI for ECx.

Compare models using AICc criteria or professional judgement and select best fit

Assess goodness of fit of models: (a) visually, (b) compare predicted % effect to observed % effect, (c) compare control mean response to predicted mean response, (d) compare regression residual SS to pure error SS using F-test. Reject poorly fitting models.

8 or more concentrations plus control

6 or 7 concentrations plus control

5 concentrations plus control

Report model, ECx and its CI

If no model and acceptable x can be found, report NOEC

No

Yes

If no indication of extra-binominal variance, probit model can be fit to proportion data

Also fit Brain-Cousins Hormetic model

Also fit OECD 4 & 5, Hill, Michaelis-Menton or other 3-5 parm model

For Bruce-Versteeg, simple exponential (OECD2), simple exponential w/shape parameter (OECD3) or other 2-3 parm model

Considerations for Egg Hatch and Larval Mortality

For egg hatch and larval mortality, it is generally best to fit a decreasing model unless one is fitting a probit model as described below. That is, one should model the proportion of eggs that do not hatch or larvae that die. The reason for this is that ECx refers to a concentration at which there is a change equal to x % of the control mean response. If there are 5 % control eggs that fail to hatch and one models failure to hatch, then EC20 refers to a concentration at which there is a change equal to 20 % of the 5 % control failure to hatch, and that is a change of 0,2 × 0,05 = 0,01 or 1 percentage point to 6 % failure to hatch. Such a small change cannot be estimated in any meaningful way from the data available and is not biologically important. Whereas if one models the proportion of eggs that hatch, the control proportion would be 95 % in this example and a 20 % reduction from the control mean would be a change of 0,95 × 0,2 = 0,18, so from 95 % hatch success to 77 % (= 95 – 18) hatching success and that effects concentration can be estimated and is presumably of greater interest. This is not an issue with size measurements, though adverse effects on size generally mean a decrease in size.

Models for Size (length or weight) and Egg Hatch Success or Larval Survival.

Except for the Brain-Cousens hormetic model, all of these models are described and recommended in OECD (2006). What are called OECD 2-5, are also discussed for ecotoxicity experiments in Slob (2002). There are, of course, many other models that might be useful. Bunke, et al. (1999) lists numerous models not included here and references to other models are plentiful. Those listed below are suggested as particularly appropriate in ecotoxicity experiments and widely used.

With 5 test concentrations plus control

• — Bruce-Versteeg

• — Simple Exponential (OECD 2)

• — Exponential with shape parameter (OECD 3)

• — Simple Exponential with Lower Bound (OECD 4)

With 6 or more test concentrations plus control

• — Exponential with shape parameter and lower bound (OECD 5)

• — Michaelis-Menten

• — Hill

Where there is visual evidence of hormesis (unlikely with egg hatch success or larval survival, but sometimes observed in size observations)

- — Brain-Cousens Hormetic; Brain and Cousens (1989)

Alternative models for egg hatch failure and larval mortality

- — Increasing models for these responses can be fit by probit (or logistic) models if there is no evidence of extra-binomial variance and control incidence is estimated in the model fit. This is not the preferred method, as it treats the individual, not the replicate, as the unit of analysis (Morgan 1992, O'Hara Hines and Lawless 1993, Collett 2002, 2003).

Goodness of fit of a single model

• — Visually compare observed and predicted percent decrease at each test concentration (Motulsky and Christopoulos 2004, Draper and Smith 1999).

• — Compare regression error mean square against the pure error mean square using an F-test (Draper and Smith 1999).

• — Check that every term in the model is significantly different from zero (i.e., determine whether all model terms are important), (Motulsky and Christopoulos 2004).

• — Plots of residuals from regression vs. test concentration, possibly on a log(conc) scale. There should be no pattern to this plot; the points should be randomly scattered about a horizontal line at zero height.

• — The data should be evaluated for normality and variance homogeneity in the same way as indicated in Appendix 5.

- — In addition, normality of the residuals about the regression model should be assessed using the same methods indicated in Appendix 5 for the residuals from ANOVA

Compare models

• — Use Akiake's AICc criteria. Smaller AICc values denote better fits and if AICc(B)-AICc(A)≥10, the model A is almost certainly better than model B (Motulsky and Christopoulos (2004).

• — Compare the two models visually by how well they meet the single model criteria above.

- — The parsimony principal is advised, whereby the simplest model that fits the data reasonably well is used (Ratkowsky 1993, Lyles et.al 2008).

Quality of ECx estimate

The confidence interval (CI) for ECx should not be too wide. Statistical judgment is needed in deciding how wide the confidence interval can be and ECx still be useful. Simulations for regression models fit to egg hatching and size data show that about 75 % of confidence intervals for ECx (x = 10, 20 or 30) span no more than two test concentrations. This provides a general guide for what is acceptable and a practical guide for what is achievable. Numerous authors assert the need to report confidence intervals for all model parameters and that wide confidence intervals for model parameters indicate unacceptable models (Ott and Longnecker 2008, Alvord and Rossio 1993, Motulsky and Christopoulos 2004, Lyles et al. 2008, Seber and Wild 2003, Bunke et al. 1999, Environment Canada 2005).

The CI for ECx (or any other model parameter) should not contain zero (Motulsky and Christopoulos 2004). This is the regression equivalent the minimum significant difference that is often cited in hypothesis testing approaches (e.g. Wang et al 2000). It also corresponds to the confidence interval for the mean responses at the LOEC not contain the control mean. One should wonder whether the parameter estimates are scientifically plausible. E.g. if the confidence interval for y0 is ± 20 %, no EC10 estimate is plausible. If the model predicts a 20 % effect at a concentration C and the maximum observed effect at C and lower concentrations is 10 %, then the EC20 is not plausible (Motulsky and Christopoulos 2004, Wang et al. 2000, Environment Canada 2005).

ECx should not require extrapolation outside the range of positive concentrations (Draper and Smith 1999, OECD 2006). For example, a general guide might be for ECx to be no more than about 25 % below the lowest tested concentration or above the highest tested concentration.

REFERENCES:

Alvord, W.G., Rossio, J.L. (1993); Determining confidence limits for drug potency in immunoassay, Journal of Immunological Methods 157, 155-163.

Brain P. and Cousens R. (1989); An equation to describe dose responses where there is stimulation of growth at low doses. Weed res. 29: 93-96.

Bunke, O., Droge, B. and Polzehl, J. (1999). Model selection, transformations and variance estimation in nonlinear regression. Statistics 33, 197-240.

Collett, D. (2002); Modelling Binary Data, second edition, Chapman and Hall, London.

Collett, D. (2003); Modelling Survival Data in Medical Research, second edition, Chapman and Hall, London.

Draper, N.R. and Smith, H. (1999); Applied Regression Analysis, third edition. New York: John Wiley & Sons.

Environment Canada (2005); Guidance Document on Statistical Methods for Environmental Toxicity Tests, Report EPS 1/RM/46

Huet, S., A. Bouvier, M.-A. Poursat, E. Jolivet (2003); Statistical Tools for Nonlinear Regression: A Practical Guide with S-PLUS and R Examples, Springer Series in Statistics, New York.

Lyles, R. H., C. Poindexter, A. Evans, M. Brown, and C.R. Cooper (2008); Nonlinear Model-Based Estimates of IC50 for Studies Involving Continuous Therapeutic Dose-Response Data, Contemp Clin Trials. 2008 November; 29(6): 878–886.

Morgan, B.J.T. (1992); Analysis of Quantal Response Data, Chapman and Hall, London.

Motulsky, H., A. Christopoulos (2004); Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting, Oxford University Press, USA.

O'Hara Hines, R. J. and J. F. Lawless (1993); Modelling Overdispersion in Toxicological Mortality Data Grouped over Time, Biometrics Vol. 49, pp. 107-121

OECD (2006); Current approaches in the statistical analysis of ecotoxicity data: A guidance to application. Series Testing and Assessment, No. 54, Organisation for Economic Co-operation and Development, OECD, Paris.

Ott, R.L., M.T. Longnecker, An Introduction to Statistical Methods and Data Analysis, sixth edition, 2008, Brooks-Cole, Belmont, CA

Ratkowsky, D.A. (1993); Principles of nonlinear regression, Journal of Industrial Microbiology 12, 195-199.

Seber, G.A.F., C.J. Wild, Nonlinear Regression, Wiley, 2003

Slob W. (2002); Dose-response modelling of continuous endpoints. Toxicol. Sci., 66, 298-312

Wang, Q., D.L. Denton, and R. Shukla (2000); Applications and Statistical Properties Of Minimum Significant Difference-Based Criterion Testing In a Toxicity Testing Program, Environmental Toxicology and Chemistry, Vol. 19, pp. 113–117, 2000.

C.48.   FISH SHORT TERM REPRODUCTION ASSAY

INTRODUCTION

• 1.This test method is equivalent to OECD test guideline (TG) 229 (2012). The need to develop and validate a fish assay capable of detecting endocrine active chemicals originates from the concerns that environmental levels of chemicals may cause adverse effects in both humans and wildlife due to the interaction of these chemicals with the endocrine system. In 1998, the OECD initiated a high-priority activity to revise existing guidelines and to develop new guidelines for the screening and testing of potential endocrine disruptors. One element of the activity was to develop a test guideline for the screening of chemicals active on the endocrine system of fish species. The Fish Short Term Reproduction Assay underwent an extensive validation programme consisting of inter-laboratory studies with selected chemicals to demonstrate the relevance and reliability of the assay for the detection of chemicals that impact reproduction in fish by various mechanisms including endocrine modalities (1, 2, 3, 4, 5). All endpoints of the OECD test guideline have been validated on the fathead minnow, and a subset of endpoints has been validated in the Japanese medaka (i.e. vitellogenin and secondary sex characteristics) and the zebrafish (i.e. vitellogenin). The validation work has been peer-reviewed by a panel of experts nominated by the National Coordinators of the OECD Test Guideline Programme (6) in part, and by an independent panel of experts commissioned by the United States Environmental Protection Agency (29). The assay is not designed to identify specific mechanisms of hormonal disruption because the test animals possess an intact hypothalamic-pituitary-gonadal (HPG) axis, which may respond to chemicals that impact on the HPG axis at different levels.

• 2.This test method describes an in vivo screening assay where sexually mature male and spawning female fish are held together and exposed to a chemical during a limited part of their life-cycle (21 days). At termination of the 21-day exposure period, two biomarker endpoints are measured in males and females as indicators of endocrine activity of the test chemical; these endpoints are vitellogenin and secondary sexual characteristics. Vitellogenin is measured in fathead minnow, Japanese medaka and zebrafish, whereas secondary sex characteristics are measured in fathead minnow and Japanese medaka. Additionally, quantitative fecundity is monitored daily throughout the test. Gonads are also preserved and histopathology may be evaluated to assess the reproductive fitness of the test animals and to add to the weight of evidence of other endpoints.

- 3.This bioassay serves as an in vivo reproductive screening assay and its application should be seen in the context of the ‘OECD Conceptual Framework for the Testing and Assessment of Endocrine Disrupting Chemicals’ (30). In this Conceptual Framework the Fish Short Term Reproduction Assay is proposed at Level 3 as an in vivo assay providing data about selected endocrine mechanism(s)/pathway(s).

INITIAL CONSIDERATIONS AND LIMITATIONS

• 4.Vitellogenin (VTG) is normally produced by the liver of female oviparous vertebrates in response to circulating endogenous oestrogen. It is a precursor of egg yolk proteins and, once produced in the liver, travels in the bloodstream to the ovary, where it is taken up and modified by developing eggs. Vitellogenin is almost undetectable in the plasma of immature female and male fish because they lack sufficient circulating oestrogen; however, the liver is capable of synthesising and secreting vitellogenin in response to exogenous oestrogen stimulation.

• 5.The measurement of vitellogenin serves for the detection of chemicals with various oestrogenic modes of action. The detection of oestrogenic chemicals is possible via the measurement of vitellogenin induction in male fish, and it has been abundantly documented in the scientific peer-reviewed literature (e.g. (7)). Vitellogenin induction has also been demonstrated following exposure to aromatisable androgens (8, 9). A reduction in the circulating level of oestrogen in females, for instance through the inhibition of the aromatase converting the endogenous androgen to the natural oestrogen 17β-estradiol, causes a decrease in the VTG level which is used to detect chemicals having aromatase inhibiting properties (10, 11). The biological relevance of the vitellogenin response following oestrogenic/aromatase inhibition is established and has been broadly documented. However, it is possible that production of VTG in females can also be affected by general toxicity and non-endocrine toxic modes of action, e.g. hepatotoxicity.

• 6.Several measurement methods have been successfully developed and standardised for routine use. This is the case of species-specific Enzyme-Linked Immunosorbent Assay (ELISA) methods using immunochemistry for the quantification of VTG produced in small blood or liver samples collected from individual fish (12, 13, 14, 15, 16, 17, 18). Fathead minnow blood, zebrafish blood or head/tail homogenate, and medaka liver are sampled for VTG measurement. In medaka, there is a good correlation between VTG measured from blood and from liver (19). Appendix 6 provides the recommended procedures for sample collection for VTG analysis. Kits for the measurement of VTG are widely available; such kits should be based on a validated species-specific ELISA method.

• 7.Secondary sex characteristics in male fish of certain species are externally visible, quantifiable and responsive to circulating levels of endogenous androgens; this is the case for the fathead minnow and the medaka — but not for zebrafish which does not possess quantifiable secondary sex characteristics. Females maintain the capacity to develop male secondary sex characteristics, when they are exposed to androgenic chemicals in water. Several studies are available in the scientific literature to document this type of response in fathead minnow (20) and medaka (21). A decrease in secondary sex characteristics in males should be interpreted with caution because of low statistical power, and should be based on expert judgement and weight of evidence. There are limitations to the use of zebrafish in this assay, due to the absence of quantifiable secondary sex characteristics responsive to androgenic acting chemicals.

• 8.In the fathead minnow, the main indicator of exogenous androgenic exposure is the number of nuptial tubercles located on the snout of the female fish. In the medaka, the number of papillary processes constitutes the main marker of exogenous exposure to androgenic chemicals in female fish. Appendix 5A and Appendix 5B indicate the recommended procedures to follow for the evaluation of sex characteristics in fathead minnow and in medaka, respectively.

• 9.The 21-day fish assay includes the evaluation of quantitative egg production and preservation of gonads for optional histopathology examination. Some regulatory authorities may require this additional endpoint for a more complete evaluation of the reproductive fitness of the test animals, or in cases where vitellogenin and secondary sex characteristics did not respond to the chemical exposure. Although some endpoints may be highly diagnostic (e.g. VTG induction in males and tubercle formation in females), not all endpoints (e.g. fecundity and gonad histopathology) in the assay are intended to unequivocally identify specific cellular mechanisms of action. Rather, the suite of endpoints, collectively, allows inferences to be made with regard to possible endocrine disturbances and thus provide guidance for further testing. Although not endocrine specific, fecundity, due to its demonstrated sensitivity across known endocrine active chemicals (5), is an important endpoint to include because when it and other endpoints are unaffected one is more confident that a compound is not likely endocrine active. However, when fecundity is affected it will contribute heavily in weight of evidence inferences. Guidance on data interpretation and acceptance of test results is provided further in this test method.

- 10.Definitions used in this test method are given in Appendix 1.

PRINCIPLE OF THE TEST

• 11.In the assay, male and female fish in a reproductive status are exposed together in test vessels. Their adult and reproductive status enables a clear differentiation of each sex, and thus a sex-related analysis of each endpoint, and ensures their sensitivity towards exogenous chemicals. At test termination, sex is confirmed by macroscopic examination of the gonads following ventral opening of the abdomen with scissors. An overview of the relevant bioassay conditions are provided in Appendix 2. The assay is normally initiated with fish sampled from a population that is in spawning condition; senescent animals should not be used. Guidance on the age of fish and on the reproductive status is provided in the section on Selection of fish. The assay is conducted using three chemical exposure concentrations as well as a water control, and a solvent control if necessary. Two vessels or replicates per treatment are used for zebrafish (each vessel containing 5 males and 5 females). Four vessels or replicates per treatment are used for fathead minnow (each vessel containing 2 males and 4 females). This is to accommodate the territorial behaviour of male fathead minnow while maintaining sufficient power of the assay. Four vessels or replicates per treatment are used for medaka (each vessel containing 3 males and 3 females). The exposure is conducted for 21-days and sampling of fish is performed at day 21 of exposure. Quantitative fecundity is monitored daily.

- 12.On sampling at day 21, all animals are killed humanely. Secondary sex characteristics are measured in fathead minnow and medaka (see Appendix 5A and Appendix 5B); blood samples are collected for determination of VTG in zebrafish and fathead minnow, alternatively head/tail can be collected for the determination of VTG in zebrafish (Appendix 6); liver is collected for VTG analysis in medaka (Appendix 6); gonads are fixed either in whole or dissected for potential histopathological evaluation (22).

TEST ACCEPTANCE CRITERIA

• 13.For the test results to be acceptable the following conditions apply:

• — the mortality in the water (or solvent) controls should not exceed 10 per cent at the end of the exposure period;

• — the dissolved oxygen concentration should be at least 60 per cent of the air saturation value (ASV) throughout the exposure period;

• — the water temperature should not differ by more than ± 1,5 °C between test vessels at any one time during the exposure period and be maintained within a range of 2 °C within the temperature ranges specified for the test species (Appendix 2);

• — evidence should be available to demonstrate that the concentrations of the test chemical in solution have been satisfactorily maintained within ±20 % of the mean measured values;

- — evidence that fish are actively spawning in all replicates prior to initiating chemical exposure and in control replicates during the test.

DESCRIPTION OF THE METHOD

Apparatus

• 14.Normal laboratory equipment and especially the following:

• (a) oxygen and pH meters;

• (b) equipment for determination of water hardness and alkalinity;

• (c) adequate apparatus for temperature control and preferably continuous monitoring;

• (d) tanks made of chemically inert material and of a suitable capacity in relation to the recommended loading and stocking density (see Appendix 2);

• (e) spawning substrate for fathead minnow and zebrafish, Appendix 4 gives the necessary details.

- (f) suitably accurate balance (i.e. accurate to ± 0,5 mg).

Water

- 15.Any water in which the test species shows suitable long-term survival and growth may be used as test water. It should be of constant quality during the period of the test. The pH of the water should be within the range 6,5 to 8,5, but during a given test it should be within a range of ± 0,5 pH units. In order to ensure that the dilution water will not unduly influence the test result (for example by complexion of test chemical); samples should be taken at intervals for analysis. Measurements of heavy metals (e.g. Cu, Pb, Zn, Hg, Cd, and Ni), major anions and cations (e.g. Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl^–, and SO4

^2–), pesticides (e.g. total organophosphorus and total organochlorine pesticides), total organic carbon and suspended solids should be made, for example, every three months where dilution water is known to be relatively constant in quality. If water quality has been demonstrated to be constant over at least one year, determinations can be less frequent and intervals extended (e.g. every six months). Some chemical characteristics of acceptable dilution water are listed in Appendix 3.

Test solutions

• 16.Test solutions of the chosen concentrations are prepared by dilution of a stock solution. The stock solution should preferably be prepared by simply mixing or agitating the test chemical in dilution water by using mechanical means (e.g. stirring or ultrasonication). Saturation columns (solubility columns) can be used for achieving a suitable concentrated stock solution. The use of a solvent carrier is not recommended. However, in case a solvent is necessary, a solvent control should be run in parallel, at the same solvent concentration as the chemical treatments. For difficult to test chemicals, a solvent may be technically the best solution; the OECD guidance document on aquatic toxicity testing of difficult substances and mixtures should be consulted (23). The choice of solvent will be determined by the chemical properties of the substance or mixture. The OECD guidance document recommends a maximum of 100 μl/l, which should be observed. However a recent review (24) highlighted additional concerns when using solvents for endocrine activity testing. Therefore it is recommended that the solvent concentration, if necessary, is minimised wherever technically feasible (dependent on the physical-chemical properties of the test chemical).

- 17.A flow-through test system will be used. Such a system continually dispenses and dilutes a stock solution of the test chemical (e.g. metering pump, proportional diluter, saturator system) in order to deliver a series of concentrations to the test chambers. The flow rates of stock solutions and dilution water should be checked at intervals, preferably daily, during the test and should not vary by more than 10 % throughout the test. Care should be taken to avoid the use of low-grade plastic tubing or other materials that may contain biologically active chemicals. When selecting the material for the flow-through system, possible adsorption of the test chemical to this material should be considered.

Holding of fish

• 18.Test fish should be selected from a laboratory population, preferably from a single stock, which has been acclimated for at least two weeks prior to the test under conditions of water quality and illumination similar to those used in the test. It is important that the loading rate and stocking density (for definitions, see Appendix 1) be appropriate for the test species used (see Appendix 2).

• 19.Following a 48-hour settling-in period, mortalities are recorded and the following criteria applied:

• — mortalities of greater than 10 % of population in seven days: reject the entire batch;

• — mortalities of between 5 % and 10 % of population: acclimation for seven additional days; if more than 5 % mortality during second seven days, reject the entire batch;

• — mortalities of less than 5 % of population in seven days: accept the batch.

- 20.Fish should not receive treatment for disease during the acclimation period, in the pre-exposure period, or during the exposure period.

Pre-exposure and selection of fish

- 21.The one to two-week pre-exposure period is recommended with animals placed in vessels similar to the actual test. Fish should be fed ad libitum throughout the holding period and during the exposure phase. The exposure phase is started with sexually dimorphic adult fish from a laboratory supply of reproductively mature animals (e.g. with clear secondary sexual characteristics visible as far as fathead minnow and medaka are concerned), and actively spawning. For general guidance only (and not to be considered in isolation from observing the actual reproductive status of a given batch of fish), fathead minnows should be approximately 20 (± 2) weeks of age, assuming they have been cultured at 25 ± 2 °C throughout their lifespan. Japanese medaka should be approximately 16 (± 2) weeks of age, assuming they have been cultured at 25 ± 2 °C throughout their lifespan. Zebrafish should be approximately 16 (± 2) weeks of age, assuming they have been cultured at 26 ± 2 °C throughout their lifespan. Egg production should be assessed daily during the pre-exposure phase. It is recommended that spawning be observed in all replicate tanks prior to inclusion in the exposure phase of the assay. Quantitative guidance on desirable daily egg production cannot be provided at this stage, but it is relatively common to observe average spawns of > 10 eggs/female/day for each species. A randomised block design according to egg production output should be used to allocate replicates to the various experimental levels to ensure balanced distribution of replicates.

TEST DESIGN

• 22.Three concentrations of the test chemical, one control (water) and, if needed, one solvent control are used. The data may be analysed in order to determine statistically significant differences between treatment and control responses. These analyses will inform whether further longer term testing for adverse effects (namely, survival, development, growth and reproduction) is required for the chemical, rather than for use in risk assessment (25).

- 23.For zebrafish, on day 21 of the experiment, males and females from each treatment level (5 males and 5 females in each of the two replicates) and from the control(s) are sampled for the measurement of vitellogenin. For medaka, on day 21 of the experiment, males and females from each treatment level (3 males and 3 females in each of the four replicates) and from the control(s) are sampled for the measurement of vitellogenin and secondary sex characteristics. For fathead minnow, on day 21 of exposure, males and females (2 males and 4 females in each of the four replicates) and from the control(s) are sampled for the measurement of vitellogenin and secondary sex characteristics. Quantitative assessment of fecundity is required, and gonadal tissues should be fixed in whole or dissected for potential histopathological evaluation, if required.

Selection of test concentrations

• 24.For the purposes of this test, the highest test concentration should be set by the maximum tolerated concentration (MTC) determined from a range finder or from other toxicity data, or 10 mg/l, or the maximum solubility in water, whichever is lowest. The MTC is defined as the highest test concentration of the chemical which results in less than 10 % mortality. Using this approach assumes that there are existing empirical acute toxicity data or other toxicity data from which the MTC can be estimated. Estimating the MTC can be inexact and typically requires some professional judgment.

- 25.Three test concentrations, spaced by a constant factor not exceeding 10, and a dilution-water control (and solvent control if necessary) are required. A range of spacing factors between 3,2 and 10 is recommended.

PROCEDURE

Selection and weighing of test fish

- 26.It is important to minimise variation in weight of the fish at the beginning of the assay. Suitable size ranges for the different species recommended for use in this test are given in Appendix 2. For the whole batch of fish used in the test, the range in individual weights for male and female fish at the start of the test should be kept, if possible, within ± 20 % of the arithmetic mean weight of the same sex. It is recommended to weigh a subsample of the fish stock before the test in order to estimate the mean weight.

Conditions of exposure

Duration

- 27.The test duration is 21 days, following a pre-exposure period. The recommended pre-exposure period is one to two weeks.

Feeding

• 28.Fish should be fed ad libitum with an appropriate food (Appendix 2) at a sufficient rate to maintain body condition. Care should be taken to avoid microbial growth and water turbidity. As a general guidance, the daily ration may be divided into two or three equal portions for multiple feeds per day, separated by at least three hours between each feed. A single larger ration is acceptable particularly for weekends. Food should be withheld from the fish for 12 hours prior to sampling/necropsy.

• 29.Fish food should be evaluated for the presence of contaminants such as organochlorine pesticides, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs). Food with an elevated level of phytoestrogens that would compromise the response of the assay to known oestrogen agonist (e.g. 17β- estradiol) should be avoided.

- 30.Uneaten food and faecal material should be removed from the test vessels at least twice weekly, e.g. by carefully cleaning the bottom of each tank using a siphon.

Light and temperature

- 31.The photoperiod and water temperature should be appropriate for the test species (see Appendix 2).

Frequency of analytical determinations and measurements

• 32.Prior to initiation of the exposure period, proper function of the chemical delivery system should be ensured. All analytical methods needed should be established, including sufficient knowledge on the chemical stability in the test system. During the test, the concentrations of the test chemical are determined at regular intervals, as follows: the flow rates of diluent and toxicant stock solution should be checked preferably daily but as a minimum twice per week, and should not vary by more than 10 % throughout the test. It is recommended that the actual test chemical concentrations be measured in all vessels at the start of the test and at weekly intervals thereafter.

• 33.It is recommended that results be based on measured concentrations. However, if concentration of the test chemical in solution has been satisfactorily maintained within ±20 % of the nominal concentration throughout the test, then the results can either be based on nominal or measured values.

• 34.Samples may need to be filtered (e.g. using a 0,45 μm pore size) or centrifuged. If needed, then centrifugation is the recommended procedure. However, if the test material does not adsorb to filters, filtration may also be acceptable.

- 35.During the test, dissolved oxygen, temperature, and pH should be measured in all test vessels at least once per week. Total hardness and alkalinity should be measured in the controls and one vessel at the highest concentration at least once per week. Temperature should preferably be monitored continuously in at least one test vessel.

Observations

- 36.A number of general (e.g. survival) and biological responses (e.g. VTG levels) are assessed over the course of the assay or at termination of the assay. The daily quantitative monitoring of fecundity is required. Measurement and evaluation of these endpoints and their utility are described below.

Survival

- 37.Fish should be examined daily during the test period and any mortality should be recorded and the dead fish removed as soon as possible. Dead fish should not be replaced in either the control or treatment vessels. Sex of fish that die during the test should be determined by macroscopic evaluation of the gonads.

Behaviour and appearance

• 38.Any abnormal behaviour (relative to controls) should be noted; this might include signs of general toxicity including hyperventilation, uncoordinated swimming, loss of equilibrium, and atypical quiescence or feeding. Additionally external abnormalities (such as haemorrhage, discoloration) should be noted. Such signs of toxicity should be considered carefully during data interpretation since they may indicate concentrations at which biomarkers of endocrine activity are not reliable. Such behavioural observations may also provide useful qualitative information to inform potential future fish testing requirements. For example, territorial aggressiveness in normal males or masculinised females has been observed in fathead minnows under androgenic exposure; in zebrafish, the characteristic mating and spawning behaviour after the dawn onset of light is reduced or hindered by oestrogenic or anti-androgenic exposure.

- 39.Because some aspects of appearance (primarily colour) can change quickly with handling, it is important that qualitative observations be made prior to removal of animals from the test system. Experience to date with fathead minnows suggests that some endocrine active chemicals may initially induce changes in the following external characteristics: body colour (light or dark), coloration patterns (presence of vertical bands), and body shape (head and pectoral region). Therefore observations of physical appearance of the fish should be made over the course of the test, and at conclusion of the study

Fecundity

- 40.Daily quantitative observations of spawning should be recorded on a replicate basis. Egg production should be recorded as the number of eggs/surviving female/day on a replicate basis. Eggs will be removed daily from the test chambers. Spawning substrates should be placed in the test chamber for the fathead minnow and zebrafish to enable fish to spawn in normal conditions. Appendix 4 gives further details of recommended spawning substrates for zebrafish (Appendix 4A) and fathead minnow (Appendix 4B). It is not considered necessary to provide spawning substrate for medaka.

Humane killing of fish

- 41.At day 21, i.e. at termination of the exposure, the fish should be euthanised with appropriate amounts of Tricaine (Tricaine methane sulfonate, Metacain, MS-222 (CAS.886-86-2), 100-500 mg/l buffered with 300 mg/l NaHCO3 (sodium bicarbonate, CAS.144-55-8) to reduce mucous membrane irritation; blood or tissue is then sampled for VTG determination, as explained in the vitellogenin section.

Observation of secondary sex characteristics

- 42.Some endocrine active chemicals may induce changes in specialised secondary sex characteristics (number of nuptial tubercles in male fathead minnow, papillary processes in male medaka). Notably, chemicals with certain modes of action may cause abnormal occurrence of secondary sex characteristic in animals of the opposite sex; for example, androgen receptor agonists, such as trenbolone, methyltestosterone and dihydrotestosterone, can cause female fathead minnows to develop pronounced nuptial tubercles or female medaka to develop papillary processes (11, 20, 21). It also has been reported that oestrogen receptor agonists can decrease nuptial tubercle numbers and size of the dorsal nape pad in adult males of fathead minnow (26, 27). Such gross morphological observations may provide useful qualitative and quantitative information to inform potential future fish testing requirements. The number and size of nuptial tubercles in fathead minnow and papillary processes in medaka can be quantified directly or more practically in preserved specimens. Recommended procedures for the evaluation of secondary sex characteristics in fathead minnow and medaka are available from Appendix 5A and Appendix 5B, respectively.

Vitellogenin (VTG)

• 43.Blood is collected from the caudal artery/vein with a heparinised microhematocrit capillary tubule, or alternatively by cardiac puncture with a syringe. Depending upon the size of the fish, collectable blood volumes generally range from 5 to 60 μl per individual for fathead minnows and 5-15 μl per individual for zebrafish. Plasma is separated from the blood via centrifugation, and stored with protease inhibitors at – 80 °C, until analysed for VTG. Alternatively, in medaka the liver will be used, and in zebrafish the head/tail homogenate can be used as tissue-source for VTG determination (Appendix 6). The measurement of VTG should be based upon a validated homologous ELISA method, using homologous VTG standard and homologous antibodies. It is recommended to use a method capable to detect VTG levels as low as few ng/ml plasma (or ng/mg tissue), which is the background level in unexposed male fish.

• 44.Quality control of VTG analysis will be accomplished through the use of standards, blanks and at least duplicate analyses. For each ELISA method, a test for matrix effect (effect of sample dilution) should be run to determine the minimum sample dilution factor. Each ELISA plate used for VTG assays should include the following quality control samples: at least 6 calibration standards covering the range of expected VTG concentrations, and at least one non-specific binding assay blank (analysed in duplicate). Absorbance of these blanks should be less than 5 % of the maximum calibration standard absorbance. At least two aliquots (well-duplicates) of each sample dilution will be analysed. Well-duplicates that differ by more than 20 % should be re-analysed.

• 45.The correlation coefficient (R²) for calibration curves should be greater than 0,99. However, a high correlation is not sufficient to guarantee adequate prediction of concentration in all ranges. In addition to having a sufficiently high correlation for the calibration curve, the concentration of each standard, as calculated from the calibration curve, should all fall between 70 and 120 % of its nominal concentration. If the nominal concentrations trend away from the calibration regression line (e.g. at lower concentrations), it may be necessary to split the calibration curve into low and high ranges or to use a nonlinear model to adequately fit the absorbance data. If the curve is split, both line segments should have R² > 0,99.

• 46.The limit of detection (LOD) is defined as the concentration of the lowest analytical standard, and limit of quantitation (LOQ) is defined as the concentration of the lowest analytical standard multiplied by the lowest dilution factor.

- 47.On each day that VTG assays are performed, a fortification sample made using an inter-assay reference standard will be analysed (Appendix 7). The ratio of the expected concentration to the measured concentration will be reported along with the results from each set of assays performed on that day.

Evaluation of gonadal histopathology

- 48.Performance of gonadal histopathology may be required by regulatory authorities to study the target organ on the HPG axis following chemical exposure. In this respect, gonads are fixed either whole body or dissected. When histopathology is required, specific endocrine-related responses on the gonads will be looked for in the assessment of the endocrine activity of the test chemical. These diagnostic responses essentially include the presence of testicular oocytes, Leydig cell hyperplasia, decreased yolk formation, increased spermatogonia and perifollicular hyperplasia. Other gonadal lesions like oocyte atresia, testicular degeneration, and stage changes, may have various causes. The Guidance document on fish gonadal histopathology specifies procedures that will be used in the dissection, fixation, sectioning and histopathological evaluation of the gonads (22).

DATA AND REPORTING

Evaluation of Biomarker Responses by Analysis of Variance (ANOVA)

- 49.To identify potential activity of a chemical, responses are compared between treatments and control groups using analysis of variance (ANOVA). Where a solvent control is used, an appropriate statistical test should be performed between the dilution water and solvent controls for each endpoint. Guidance on how to handle dilution water and solvent control data in the subsequent statistical analysis can be found in OECD, 2006c (28). All biological response data should be analysed and reported separately by sex. If the required assumptions for parametric methods are not met — non-normal distribution (e.g. Shapiro-Wilk's test) or heterogeneous variance (Bartlett's test or Levene's test), consideration should be given to transforming the data to homogenise variances prior to performing the ANOVA, or to carrying out a weighted ANOVA. Dunnett's test (parametric) on multiple pair-wise comparisons or a Mann-Whitney with Bonferroni adjustment (non-parametric) may be used for non-monotonous dose-response. Other statistical tests may be used (e.g. Jonckheere-Terpstra test or Williams test) if the dose-response is approximately monotone. A statistical flowchart is provided in Appendix 8 to help in the decision on the most appropriate statistical test to be used. Additional information can also be obtained from the OECD Document on Current Approaches to Statistical Analysis of Ecotoxicity Data (28).

Reporting of test results

• 50.Study data should include:

Testing facility:

• — Responsible personnel and their study responsibilities

• — Each laboratory should have demonstrated proficiency using a range of representative chemicals

Test Chemical:

• — Characterisation of test chemical

• — Physical nature and relevant physicochemical properties

• — Method and frequency of preparation of test concentrations

• — Information on stability and biodegradability

Solvent:

• — Characterisation of solvent (nature, concentration used)

• — Justification of choice of solvent (if other than water)

Test animals:

• — Species and strain

• — Supplier and specific supplier facility

• — Age of the fish at the start of the test and reproductive/spawning status

• — Details of animal acclimation procedure

• — Body weight of the fish at the start of the exposure (from a sub-sample of the fish stock)

Test Conditions:

• — Test procedure used (test-type, loading rate, stocking density, etc.);

• — Method of preparation of stock solutions and flow-rate;

• — The nominal test concentrations, weekly measured concentrations of the test solutions and analytical method used, means of the measured values and standard deviations in the test vessels and evidence that the measurements refer to the concentrations of the test chemical in true solution;

• — Dilution water characteristics (including pH, hardness, alkalinity, temperature, dissolved oxygen concentration, residual chlorine levels, total organic carbon, suspended solids and any other measurements made)

• — Water quality within test vessels: pH, hardness, temperature and dissolved oxygen concentration;

• — Detailed information on feeding (e.g. type of food(s), source, amount given and frequency and analyses for relevant contaminants if available (e.g. PCBs, PAHs and organochlorine pesticides).

Results

• — Evidence that the controls met the acceptance criteria of the test;

• — Data on mortalities occurring in any of the test concentrations and control;

• — Statistical analytical techniques used, treatment of data and justification of techniques used;

• — Data on biological observations of gross morphology, including secondary sex characteristics, egg production and VTG;

• — Results of the data analyses preferably in tabular and graphical form;

- — Incidence of any unusual reactions by the fish and any visible effects produced by the test chemical

GUIDANCE FOR THE INTERPRETATION AND ACCEPTANCE OF THE TEST RESULTS

• 51.This section contains a few considerations to be taken into account in the interpretation of test results for the various endpoints measured. The results should be interpreted with caution where the test chemical appears to cause overt toxicity or to impact on the general condition of the test animal.

• 52.In setting the range of test concentrations, care should be taken not to exceed the maximum tolerated concentration to allow a meaningful interpretation of the data. It is important to have at least one treatment where there are no signs of toxic effects. Signs of disease and signs of toxic effects should be thoroughly assessed and reported. For example, it is possible that production of VTG in females can also be affected by general toxicity and non-endocrine toxic modes of action, e.g. hepatotoxicity. However, interpretation of effects may be strengthened by other treatment levels that are not confounded by systemic toxicity.

• 53.There are a few aspects to consider for the acceptance of test results. As a guide, the VTG levels in control groups of males and females should be distinct and separated by about three orders of magnitude in fathead minnow and zebrafish, and about one order of magnitude for medaka. Examples of the range of values encountered in control and treatment groups are available in the validation reports (1, 2, 3, 4). High VTG values in control males could compromise the responsiveness of the assay and its ability to detect weak oestrogen agonists. Low VTG values in control females could compromise the responsiveness of the assay and its ability to detect aromatase inhibitors and oestrogen antagonists. The validation studies were used to build that guidance.

• 54.Concerning the quantification of egg production, this is subject to important variations [the coefficient of variation (CV) may range from 20 to 60 %] that impinge the ability of the assay to detect a significant decrease in egg production smaller than 70 % as the CV approaches 50 % or more. When the CV is confined to lower values (around 20-30 %), then the assay will have acceptable power (80 %) to detect 40-50 % decrease in egg production. The test design used for the fathead minnow, including four replicates per treatment level, should allow more power to the fecundity endpoint, compared to a test design with 2 replicates only.

• 55.If a laboratory has not performed the assay before or substantial changes (e.g. change of fish strain or supplier) have been made it is advisable that a technical proficiency study is conducted. It is recommended that chemicals covering a range of modes of action or impacts on a number of the test endpoints are used. In practice, each laboratory is encouraged to build its own historical control data for males and females and to perform a positive control chemical for estrogenic activity (e.g. 17β-estradiol at 100 ng/l, or a known weak agonist) resulting in increased VTG in male fish, a positive control chemical for aromatase inhibition (e.g. fadrozole or prochloraz at 300 μg/l) resulting in decreased VTG in female fish, and a positive control chemical for androgenic activity (e.g. 17β-trenbolone at 5 μg/l) resulting in induction of secondary sex characteristics in female fathead minnow and medaka. All these data can be compared to available data from the validation studies (1, 2, 3) to ensure laboratory proficiency.

• 56.In general, VTG measurements should be considered positive if there is a statistically significant increase in VTG in males (p < 0,05), or a statistically significant decrease in females (p < 0,05) at least at the highest dose tested compared to the control group, and in the absence of signs of general toxicity. A positive result is further supported by the demonstration of a biologically plausible relationship between the dose and the response curve. As mentioned earlier, the VTG decrease may not entirely be of endocrine origin; however a positive result should generally be interpreted as evidence of endocrine activity in vivo, and should normally initiate actions for further clarification.

- 57.Gonadal histopathology evaluation may be required by regulatory authorities to determine the reproductive fitness of the test animals and to allow a weight of evidence assessment of the test results. Performance of gonadal histopathology may not be necessary in cases where either, VTG or secondary sex characteristics is positive (i.e. VTG increase or decrease, or induction of secondary sex characteristics).

LITERATURE:

• (1) OECD (2006a). Report of the Initial Work Towards the Validation of the 21-Day Fish Screening Assay for the Detection of Endocrine active Substances (Phase 1A). OECD Environmental Health and Safety Publications Series on Testing and Assessment No.60, Paris.

• (2) OECD (2006b). Report of the Initial Work Towards the Validation of the 21-Day Fish Screening Assay for the Detection of Endocrine active Substances (Phase 1B). OECD Environmental Health and Safety Publications Series on Testing and Assessment No.61, Paris.

• (3) OECD (2007). Final report of the Validation of the 21-day Fish Screening Assay for the Detection of Endocrine Active Substances. Phase 2: Testing Negative Substances. OECD Environmental Health and Safety Publications Series on Testing and Assessment No.78, Paris.

• (4) Owens JW (2007). Phase 3 report of the validation of the OECD Fish Screening Assay. CEFIC LRI Project, Endocrine. http://www.cefic-lri.org/index.php?page=projects (accessed 18/09/08).

• (5) US EPA (2007). Validation of the Fish Short-Term Reproduction Assay: Integrated Summary Report. 15 December 2007. US Environmental Protection Agency, Washington, DC. 104 pp.

• (6) OECD (2008). Report of the Validation Peer Review for the 21-Day Fish Endocrine Screening Assay and Agreement of the Working Group of the National Coordinators of the Test Guidelines Programme on the Follow-up of this Report. OECD Environmental Health and Safety Publications Series on Testing and Assessment No.94, Paris.

• (7) Sumpter J.P. and S. Jobling (1995). Vitellogenesis as a biomarker for estrogenic contamination of the aquatic environment. Environmental Health Perspectives; 103 Suppl 7:173-8 Review.

• (8) Pawlowski S., et al. (2004). Androgenic and estrogenic effects of the synthetic androgen 17alpha-methyltestosterone on sexual development and reproductive performance in the fathead minnow (Pimephales promelas) determined using the gonadal recrudescence assay. Aquatic Toxicology; 68(3):277-91.

• (9) Andersen L., et al (2006). Short-term exposure to low concentrations of the synthetic androgen methyltestosterone affects vitellogenin and steroid levels in adult male zebrafish (Danio rerio). Aquatic Toxicology; 76(3-4):343-52.

• (10) Ankley G.T., et al. (2002). Evaluation of the aromatase inhibitor fadrozole in a short-term reproduction assay with the fathead minnow (Pimephales promelas). Toxicological Sciences; 67(1):121-30.

• (11) Panter G.H., et al. (2004). Successful detection of (anti-)androgenic and aromatase inhibitors in pre-spawning adult fathead minnows (Pimephales promelas) using easily measured endpoints of sexual development. Aquatic Toxicology; 70(1):11-21.

• (12) Parks L.G., et al. (1999). Fathead minnow (Pimephales promelas) vitellogenin: purification, characterization and quantitative immunoassay for the detection of estrogenic compounds. Comparative Biochemistry and Physiology. Part C Pharmacology, toxicology and endocrinology; 123(2):113-25.

• (13) Panter G.H., et al. (1999). Application of an ELISA to quantify vitellogenin concentrations in fathead minnows (Pimephales promelas) exposed to endocrine disrupting chemicals. CEFIC-EMSG research report reference AQ001. CEFIC, Brussels, Belgium.

• (14) Fenske M., et al. (2001). Development and validation of a homologous zebrafish (Danio rerio Hamilton- Buchanan) vitellogenin enzyme-linked immunosorbent assay (ELISA) and its application for studies on estrogenic chemicals. Comp. Biochem. Phys. C 129 (3): 217-232.

• (15) Holbech H., et al. (2001). Development of an ELISA for vitellogenin in whole body homogenate of zebrafish (Danio rerio). Comparative Biochemistry and Physiology. Part C Pharmacology, toxicology and endocrinology; 130: 119-131

• (16) Rose J., et al. (2002). Vitellogenin induction by 17β-estradiol and 17α-ethinylestradiol in male zebrafish (Danio rerio). Comp. Biochem. Physiol. C 131: 531-539.

• (17) Brion F., et al. (2002). Development and validation of an enzyme-linked immunosorbent assay to measure vitellogenin in the zebrafish (Danio rerio). Environmental Toxicology and Chemistry; vol 21: 1699-1708.

• (18) Yokota H., et al. (2001). Development of an ELISA for determination of the hepatic vitellogenin in Medaka (Oryzias latipes). Jpn J Environ Toxicol 4:87–98.

• (19) Tatarazako N., et al. (2004). Validation of an enzyme-linked immunosorbent assay method for vitellogenin in the Medaka. Journal of Health Science 50:301-308.

• (20) Ankley G.T., et al. (2003). Effects of the androgenic growth promoter 17-beta-trenbolone on fecundity and reproductive endocrinology of the fathead minnow. Environmental Toxicology and Chemistry; 22(6): 1350-60.

• (21) Seki M, et al (2004). Fish full life-cycle testing for androgen methyltestosterone on medaka (Oryzias latipes). Environmental Toxicology and Chemistry; 23(3):774-81.

• (22) OECD (2010). Guidance Document on Fish Gonadal Histopathology. OECD Environmental Health and Safety Publications Series on Testing and Assessment No. 123, Paris.

• (23) OECD (2000) Guidance Document on Aquatic Toxicity Testing of Difficult Substances and Mixtures. Environmental Health and Safety Publications. Series on Testing and Assessment. No. 23. Paris

• (24) Hutchinson T.H., et al. (2006a). Acute and chronic effects of carrier solvents in aquatic organisms: A critical review. Review. Aquatic Toxicology, 76; pp.69–92.

• (25) Hutchinson T.H., et al. (2006b). Screening and testing for endocrine disruption in fish-biomarkers as ‘signposts’, not ‘traffic lights,’ in risk assessment. Environmental Health Perspectives; 114 Suppl 1:106-14.

• (26) Miles-Richardson S.R., et al. (1999). Effects of waterborne exposure to 17β-estradiol on secondary sex characteristics and gonads of the fathead minnow (Pimephales promelas). Aquat. Toxicol. 47, 129-145.

• (27) Martinovic D., et al. (2008). Characterization of reproductive toxicity of vinclozolin in the fathead minnow and co-treatment with an androgen to confirm an anti-androgenic mode of action. Environ. Toxicol. Chem. 27, 478-488.

• (28) OECD (2006c), Current Approaches in the Statistical Analysis of Ecotoxicity Data: A Guidance to Application, OECD Environmental Health and Safety Publications, Series on Testing and Assessment No.54, OECD, Paris.

• (29) US EPA (2008), Peer-Review Results for the Fish Short-Term Reproduction Assay, dated 30 January 2008, US Environmental Protection Agency, Washington DC. 110 pp.

- (30) OECD (2012), OECD Conceptual Framework for Testing and Assessment of Endocrine Disrupters, OECD Environmental Health and Safety Publications, Series on Testing and Assessment No. 150, OECD, Paris.

Appendix 1

ABBREVIATIONS & DEFINITIONS:

Chemical : a substance or a mixture

CV : coefficient of variation

ELISA : Enzyme-Linked Immunosorbent Assay

HPG axis : hypothalamic-pituitary-gonadal axis

Loading rate : the wet weight of fish per volume of water.

MTC : Maximum Tolerated Concentration, representing about 10 % of the LC50

Stocking density : is the number of fish per volume of water.

Test chemical : Any substance or mixture tested using this test method.

VTG : vitellogenin is a phospholipoglycoprotein precursor to egg yolk protein that normally occurs in sexually active females of all oviparous species.

Appendix 2

EXPERIMENTAL CONDITIONS FOR THE FISH ENDOCRINE SCREENING ASSAY

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