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2001 Progress Report: Developmental Exposure to Endocrine Disruptors: Fertility and Gene Expression ProfilesEPA Grant Number: R827402
Title: Developmental Exposure to Endocrine Disruptors: Fertility and Gene Expression Profiles
Investigators: Zacharewski, Timothy
Current Investigators: Zacharewski, Timothy , Chou, Karen , Saama, Peter
Institution: Michigan State University
EPA Project Officer: Fields, Nigel
Project Period: September 1, 1999 through July 31, 2002
Project Period Covered by this Report: September 1, 2000 through July 31, 2001
Project Amount: $738,712
RFA: Endocrine Disruptors (1999) RFA Text | Recipients Lists
Research Category: Economics and Decision Sciences , Endocrine Disruptors , Health , Safer Chemicals
The intent of this project is to determine the effect of gestational and lactational exposure to estrogenic chemicals on sperm counts and quality and to associate these effects to changes in gene expression profiles in the testis, epididymis, and sperm in mice. During the second year, in vivo histological and morphological assessments of gestational and lactational exposure to diethylstilbestrol (DES) and genistein (GEN) were completed, and studies on ethynyl estradiol were initiated. Testicular genome expression was examined, progress was made in in vivo studies, and construction of the microarray and the development of strategies for data analysis were conducted. Further details are provided below.
In Vivo Studies and Results
1st Compound-Diethylstilbestrol: Pregnant C57BL6 mice were gavaged
with 0, 0.1, 1, or 10 µg/kg DES in corn oil from gestational day 12 to postnatal
day (PND) 21. Male neonates were monitored for body weight and anogenital
distance (AGD) and weaned on PND 21. Males were examined at 3, 15, and 45 weeks
of age for testis weight and histopathology. To assess effects on
spermatogenesis, epididymal sperm count, sperm motility, and in vitro
fertilizing ability were measured in 15- and 45-week old mice. Testicular gene
expression was measured by cDNA microarrays at 3, 15, and 45 weeks of age.
Maternal doses of DES were chosen so that adverse effects on spermatogenesis,
fertility, and testicular gene expression were not confounded by gross
reproductive abnormalities or testicular pathologies. Indeed, there was no
increase in the incidence of histological lesions in the testis of DES-exposed
mice. There were no effects on AGD or body weight in F1 males. There was a
modest but significant decrease in testes weight in the highest dose group at 3,
15, and 45 weeks of age. There was a significant decrease in epididymal sperm
count at 45 weeks of age, but not at 15 weeks. No significant decrease in motile
sperm count, or other sperm motion parameters measured by CASA, was assessed.
However, sperm from DES-exposed mice in the high-dose group fertilized
significantly fewer eggs when compared to the control mice at both 15 and 45
weeks of age. There also was a significantly higher number of fertilized eggs in
the high-dose group that did not proceed to the two-cell stage at 15 weeks of
age. To identify alterations at the molecular level that may explain the reduced
fertility in DES-exposed mice, testicular gene expression was examined in 3, 15,
and 45 week-old F-1 male mice using a custom cDNA microarray containing
approximately 2,300 genes. Replicate testicular gene expression profiles from
individual litters in the 10 µg/kg DES group at 3 and 15 weeks of age indicated
variation in gene expression greater than the observed biological or
experimental variation, thus indicating a treatment effect on gene expression.
The variation at 45 weeks of age was similar to biological variation, indicating
little or no effect on gene expression. To determine gene-specific effects,
t-tests and adjusted p values were used to identify log ratios significantly
different from zero, and to identify genes for subsequent experimental
verification. This approach identified 3 genes that were significantly altered
(p < 0.1) by DES at 3 weeks of age, and 80 genes that were altered at 15 weeks of age. There were no significant changes at 45 weeks of age. These microarray observations currently are being verified to identify biomarkers predictive of long-term effects on spermatogenesis. These results indicate that developmental exposure to estrogens may cause long-term and irreversible effects on sperm quality.
As for the F-0 reproductive performance, no statistically significant effects on gestational index (87.5%, 76.9%, 85.7%, and 64.7%, respectively) or 4-day pup survival (98.1%±1.34, 93.4%±3.0, 95.5%±2.6, and 90.9%±9.1, respectively) were observed. Litter size was significantly decreased in the 10 µg/kg treatment group (P < 0.01). Sex ratio (percent male) was significantly higher in the 1 µg/kg treatment group (P < 0.05) and lower in the 10 µg/kg treatment group (P < 0.05).
Among the female offspring, at 3 weeks of age, AGD was longer (4.40±0.11 mm) in the 1 µg/kg treatment group than in the control group (4.13±0.07 mm) (P < 0.05). At 3 and 8 weeks of age, eggs from the F-1 females were collected and examined for fertilizing ability in vitro. At 8 weeks of age, the number of eggs ovulated in responding to PMSG and HCG injections was significantly lower in the 10 µg/kg treatment group (36.1±17.7/mouse) than that in the controls (41.6±20.3/mouse) (P < 0.05). The number of eggs ovulated were not different among 3 weeks of age treatment groups. DES did not have any effect on the fertilizing ability of eggs. At 8 weeks of age, the degeneration rate was lower in the 10µg/kg treatment group (4.7±8.2) than in the control group (15.3±14.0) (P < 0.02). No relationship between body weight and the number of eggs ovulated was observed (P > .1). Results from this study indicated that high-dose treatment of DES could compromise female offspring's ovulatory function in adulthood.
2nd Compound-Genistein: Pregnant C57BL6 mice were gavaged with 0, 0.1, 0.5, 2.5, or 10 mg/kg GEN in corn oil from gestational day 12 to PND 21. Male offspring were assessed as described above in the DES study. Preliminary analysis indicates that testis weight, sperm count, sperm motility, and the number of motile sperm are significantly increased in a dose-dependent manner. Consistent with this observation is an increase in sperm fertilizing ability and a decrease in the number of fragmented eggs in the highest dose group. The data, together with data from male offspring at 45 weeks of age just recently acquired, currently are being analyzed. To identify alterations at the molecular level that may explain the increased fertility in GEN-exposed mice, testicular gene expression will be examined in 3, 15, and 45 week-old F-1 male mice using a custom cDNA microarray containing approximately 2,500 genes. Gene expression analysis currently is in progress.
Female offspring were examined for ovulation and egg fertilizing ability. Unlike DES, no significant differences in the number of eggs ovulated among treatment groups were observed. The fertilizing ability of eggs from the female offspring at 3-5 weeks of age was 82 ± 13, 45 ± 37, 65 ± 30, 71 ± 26, and 85 ± 20 percent, respectively, in the 0, 0.1, 0.5, 2.5, and 10 µg/kg treatment groups. The low fertilizing ability among exposed female offspring was only apparent in the 0.1 µg/kg, the lowest, treatment group (P = .003). In fact, the trend of fertilization rates suggests a reversed dose-response relationship among the four GEN exposed groups. At 8-11 weeks of age, no difference in fertilization rate was observed among treatment groups.
3rd Compound - 17a-Ethynyl estradiol (EE2): The first stage of this study is in progress. In June 12, 2001, 38 C57BL female mice, 11 weeks of age, and 18 proven fertile DBA males were purchased. After 3-day acclamation, each set of two females were paired with one male for breeding. On estimated gestational day 12, pregnant mice, housed individually, were gavaged with 0.1cc corn oil or corn oil containing 0, 0.1, 1, 10, or 100 µg/kg body weight ethynyl estradiol until pups, B6D2-F1, were weaned on day 21 postpartum.
The reproductive function of the female and male offspring will be examined as in DES and GEN studies.
Strategies for Data Analysis
Microarray Data: Mixed models were fitted to determine precisely which genes were most likely driving the patterns observed in the preliminary analyses. The approach centered around two interconnected mixed models, the "normalization" model and the "gene" model. These models were fitted using the original fluorescence measurements, not the log ratio values.1 The normalization model accounted for experiment-wide systematic effects that could bias inferences made on the data from individual genes. The residuals from this model represent "normalized" values, and were the input for the gene model. The gene model was fitted separately to the normalized data for each gene, allowing for inferences to be made using separate estimates of variability. The two models are computationally efficient and provide a conceptual framework for analyzing the data.
The normalization model was:
U represents an overall mean, Ai is the main effect for arrays, Tj is the main effect for treatments, Wk is the main effect for week (k = 1, 2; 1 = Week 3, 2 = Week 15), Dm is the main effect for dye, TW is interaction effect of treatments and weeks, ATW is the random interaction effect of arrays and treatments and weeks, and Eijlkm is stochastic error.
Let rijlkmn denote the residuals from , computed by subtracting the fitted values for the effects from the fluorescence values, yijlkmn. The gene model was:
1 Poor convergence of the models was observed with log-transformed data.
Sin is a random effect for spot nested within patch and array, patch is a subgrid on the array slide and corresponds to a single pin in the array printer, Y ijklm is stochastic error, and all other effects are as defined previously.
Least squares means (LSM) for treatment and week were computed for each gene from . False positives were defined as genes for which the LSM for the treatment was large and positive, but the LSM for the corresponding control was negative. The spot effect in , which is confounded with the array by gene interaction effect, was used to model the spot-to-spot variability. Results from fitting  and  using microarray data from the DES study are shown in Table 1. This analysis confirmed that DES has a remarkable temporal effect on gene expression (P < .05).
Only three genes were induced at both end-points (P < .05). Likewise, only one gene was induced at 3 weeks and 15 weeks (P < .05). One gene was suppressed at 3 weeks but induced at 15 weeks (P < .05). A different gene was induced at 3 weeks but suppressed at 15 weeks (P < .05). These data suggest that the gene expression patterns following DES exposure were not identical at both time periods. These models identified 15 false positives at week 3; 13 false positives were observed at week 15.Future Activities:
Theoretically, fitting variability due to polygenic effects in model  should lead to reduced prediction error variances for rijlkmn. To determine if this is true for our microarray data, a (co)variance structure based on additive genetic relationships will be fitted in .
Journal Articles on this Report : 4 Displayed | Download in RIS Format
|Other project views:||All 66 publications||9 publications in selected types||All 8 journal articles|
||Fielden MR, Zacharewski TR. Challenges and limitations of gene expression profiling in mechanistic and predictive toxicology. Toxicological Sciences 2001;60(1):6-10.||
||Fielden MR, Halgren RG, Dere E, Zacharewski TR. GP3: GenePix post-processing program for automated analysis of raw microarray data. Bioinformatics 2002;18(5):771-773.||
|| Fielden MR, Matthews JB, Fertuck KC, Halgren RG, Zacharewski TR. In silico approaches to mechanistic and predictive toxicology: An introduction to bioinformatics for toxicologists. Critical Reviews in Toxicology 2002;32(2):67-112.
||Halgren RG, Fielden MR, Fong CJ, Zacharewski TR. Assessment of clone identity and sequence fidelity for 1189 IMAGE cDNA clones. Nucleic Acids Research 2001;29(2):582-588||
diethylstilbestrol, genistein, bisphenol A., RFA, Health, Scientific Discipline, Toxics, Ecology, Environmental Chemistry, Chemistry, Epidemiology, pesticides, Endocrine Disruptors - Environmental Exposure & Risk, endocrine disruptors, Risk Assessments, Susceptibility/Sensitive Population/Genetic Susceptibility, Biochemistry, Children's Health, genetic susceptability, Biology, Endocrine Disruptors - Human Health, sensitive populations, estrogenic chemicals, bioavailability, endocrine disrupting chemicals, exposure, statistical analysis, children, fertility, developmental biology, genetic mechanisms, DDT, gene expression, human exposure, growth and development, estrogen response, reproductive processes, reproductive health, sperm count, rodent, developmental toxicants, environmental hazard exposures