Exposure to Long- and Short-Chain Per- and Polyfluoroalkyl Substances in Mice and Ovarian-Related Outcomes: An in Vivo and in Vitro Study

Abstract

Background: The extensive use of per- and polyfluoroalkyl substances (PFAS) has led to environmental contamination and bioaccumulation of these substances. Previous research linked PFAS exposure to female reproductive disorders, but the mechanism remains elusive. Further, most studies focused on legacy long-chain PFOA and PFOS, yet the reproductive impacts of other long-chain PFAS and short-chain alternatives are rarely explored.

Objectives: We investigated the effects of long- and short-chain PFAS on the mouse ovary and further evaluated the toxic mechanisms of long-chain perfluorononanoic acid (PFNA).

Methods: A 3D in vitro mouse ovarian follicle culture system and an in vivo mouse model were used, together with approaches of reverse transcription-quantitative polymerase chain reaction (RT-qPCR), enzyme-linked immunosorbent assay (ELISA), RNA sequencing (RNA-seq), pharmacological treatments, in situ zymography, histology, in situ hybridization, analytical chemistry, and benchmark dose modeling (BMD). Using these approaches, a wide range of exposure levels ($1-250\mu M$) of long-chain PFAS (PFOA, PFOS, PFNA) and short-chain PFAS (PFHpA, PFBS, GenX) were first tested in cultured follicles to examine their effects on follicle growth, hormone secretion, and ovulation. We identified $250\mu M$ as the most effective concentration for further investigation into the toxic mechanisms of PFNA, followed by an in vivo mouse exposure model to verify the accumulation of PFNA in the ovary and its ovarian-disrupting effects.

Results: In vitro cultured ovarian follicles exposed to long- but not short-chain PFAS showed poorer gonadotropin-dependent follicle growth, ovulation, and hormone secretion in comparison with control follicles. RT-qPCR and RNA-seq analyses revealed significant alterations in the expression of genes involved in follicle-stimulating hormone (FSH)-dependent follicle growth, luteinizing hormone (LH)-stimulated ovulation, and associated regulatory pathways in the PFNA-exposed group in comparison with the control group. The PPAR agonist experiment demonstrated that a peroxisome proliferator-activated receptor gamma ($\text{PPAR}\gamma$) antagonist could reverse both the phenotypic and genotypic effects of PFNA exposure, restoring them to levels comparable to the control group. Furthermore, in vivo experiments confirmed that PFNA could accumulate in ovarian tissues and validated the in vitro findings. The BMD, in vitro, and in vivo extrapolation analyses estimated follicular rupture as the most sensitive end point and that observed effects occurred in the range of human exposure to long-chain PFAS.

Discussion: Our study demonstrates that long-chain PFAS, particularly PFNA, act as a $\text{PPAR}\gamma$ agonist in granulosa cells to interfere with gonadotropin-dependent follicle growth, hormone secretion, and ovulation; and exposure to high levels of PFAS may cause adverse ovarian outcomes. https://doi.org/10.1289/EHP14876.

Figure 1.

A tiered ovarian toxicity testing and the effects of per- and polyfluoroalkyl substances (PFAS) on follicle growth. (A) The schematic of tiered ovarian toxicity testing starting from a 3D eIVFG system. (B) Effects of PFAS on follicle growth. Follicles were treated with either 0.1% DMSO as vehicle control, long-chain (PFOA, PFOS, and PFNA), or short-chain (PFHpA, PFBS, and GenX) at concentrations indicated from day 2. Average follicle diameter on day 6. $n=10–12$ follicles in each treatment group. Data were analyzed using one-way ANOVA followed by a Tukey’s multiple comparisons test. (B) Shown on the line charts are $\text{mean}\pm \text{SD}$; whiskers above and below box plots indicate the lowest and highest values of data; asterisk indicates the significant difference between different PFAS concentration groups to the control group (vehicle); *$p<0.05$ and **$p<0.01$. (C) Representative follicle images on day 0 and day 6 of eIVFG treated with either vehicle or PFAS at $250\mathrm{\mu }\mathrm{M}$, as indicated. Data represented in Figure 1B are included in Excel Table S9. Note: ANOVA, analysis of variance; DMSO, dimethylsulfoxide; eIVFG, encapsulated in vitro follicle growth; GenX, ammonium salt of HFPO-DA; hCG, human chorionic gonadotropin; HFPO-DA, hexafluoropropylene oxide dimer acid; PFAS, per- and polyfluoroalkyl substances; PFBA, perfluorobutane sulfonic acid; PFHpA, perfluoroheptanoic acid; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; SD, standard deviation.

Figure 2.

Effects of exposure to long-chain and short-chain PFAS during the entire gonadotropin-dependent follicle maturation and ovulation window on follicle ovulation. (A) Representative images of follicles before and after hCG treatment, oocyte with polar body extrusion, and unruptured follicle after PFAS exposure. In vitro ovulation was induced by treating follicles with $1.5\text{\hspace{0.17em}IU}/\mathrm{mL}$ of hCG on day 6 of eIVFG for 14 h. (B,C) Percentages of ruptured and unruptured follicles (B) and ovulated MII oocytes (C) treated with various concentrations of long- and short-chain PFAS; $n=10$ follicles in each treatment group. Statistical analysis was done using Fisher’s exact test. Asterisk indicates the significant difference between different PFAS concentration groups to the control group ($0\mathrm{\mu }\mathrm{M}$); *$p<0.05$, **$p<0.01$, and ***$p<0.001$. Data represented in Figure 2A,B are included in Excel Table S10. Note: hCG, human chorionic gonadotropin; eIVFG, encapsulated in vitro follicle growth; MII, metaphase II; MII oocytes, oocytes with the first polar body extrusion; PFAS, per- and polyfluoroalkyl substances.

Figure 3.

Effects of PFAS exposure during the entire gonadotropin-dependent follicle maturation and ovulation window on ovarian steroidogenesis. (A,B) Bars represent the average ${\log }_{10}$ concentration ($\text{pg}/\mathrm{mL}$) of estradiol (A) and testosterone (B) in the conditioned follicle culture media collected on day 6 of eIVFG. (C) Average ${\log }_{10}$ concentration ($\text{pg}/\mathrm{mL}$) of progesterone in the conditioned follicle culture media collected on day 9 after hCG-stimulated follicles were cultured for 48 h. Data were analyzed with one-way ANOVA followed by a Tukey’s multiple comparisons test; $n=5–10$ follicles in each group. Bars represent $\text{mean}\pm \text{SD}$; asterisk indicates the significant difference between different PFAS concentration groups to the control group ($0\mathrm{\mu }\mathrm{M}$); *$p<0.05$ and **$p<0.01$. Data represented in Figure 3A,C are included in Excel Table S11. Note: ANOVA, analysis of variance; eIVFG, encapsulated in vitro follicle growth; hCG, human chorionic gonadotropin; PFAS, per- and polyfluoroalkyl substances; SD, standard deviation.

Figure 4.

Effects of PFNA and GenX on follicle ovulation, resumption of oocyte meiosis, hormone secretion, and expression of follicle maturation genes. Follicles were exposed to various concentrations of PFNA or GenX from day 2 to 6 of eIVFG. (A,B) Percentages of ruptured and unruptured follicles (A) and ovulated MII oocytes (B) treated with various concentrations of PFNA or GenX. (C) Average ${\log }_{10}$ concentration (picograms per milliliter) of progesterone in the conditioned follicle culture media on day 9 after hCG-stimulated follicles were cultured for 48 h. (D) Relative mRNA expression of follicle maturation genes examined by RT-qPCR in single follicles treated with $250\mathrm{\mu }\mathrm{M}$ PFNA from day 2 to 6 of eIVFG. The mRNA expression levels were normalized by the expression of Gapdh. Data were analyzed with Student’s $t$-test. $n=8–10$ follicles in each group. Shown are $\text{mean}\pm \text{SD}$; asterisk indicates the significant difference between different PFAS concentration groups in comparison with the control group ($0\mathrm{\mu }\mathrm{M}$); *$p<0.05$ and **$p<0.01$. Data represented in Figure 4A,D are included in Excel Table S12. Note: eIVFG, encapsulated in vitro follicle growth; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; GenX, ammonium salt of HFPO-DA; hCG, human chorionic gonadotropin; HFPO-DA, hexafluoropropylene oxide dimer acid; MII, metaphase II; MII oocytes, oocytes with the first polar body extrusion; PFAS, per- and polyfluoroalkyl substances; PFNA, perfluorononanoic acid; RT-qPCR, reverse transcription–quantitative polymerase chain reaction; SD, standard deviation.

Figure 5.

Single-follicle RNA-seq analysis of follicles exposed to PFNA during the FSH-stimulated follicle maturation window. (A) PCA of the first two PCs for follicles treated with PFNA at $250\mathrm{\mu }\mathrm{M}$ ($n=9$) or vehicle ($n=10$). (B) Volcano plot of DEGs; FDR $<0.05$; (absolute fold change $\ge 2$ or $\le 0.5$) in PFNA-treated follicles in comparison with the control. Pink, red: up-regulated genes; black: insignificantly altered genes; light blue: down-regulated genes. (C) Heat map of the same set of follicle maturation-related genes examined by both single-follicle RNA-seq (here) and RT-qPCR. Each column in the heat map represents the relative difference of expression level in the genes for each sample. GO and KEGG pathway analysis of DEGs identified by single-follicle RNA-seq between follicles treated with PFNA at $250\mathrm{\mu }\mathrm{M}$ ($n=9$) or vehicle ($n=10$) during the follicle maturation window. (D–G) GO analyses of DEGs, including the top 10 enriched biological processes (D), the top 10 enriched cellular components (E), and the top 10 enriched molecular functions (F). (G) Top 10 enriched KEGG pathways. Data represent in Figure 5D–G are also presented in Excel Table S1. (H) Single-follicle RNA-seq data analysis comparing DEGs regulated by PFNA to PPAR target genes during follicle maturation window exposure. Heat map of DEGs in enriched process of “cell cycle” and their comparisons with predicted PPAR target genes from the PPAR gene database. Data represented in Figure 5C are included in Excel Table S13. Note: DEGs, differentially expressed gene; FDR, false discovery rate; FSH, follicle-stimulating hormone; GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; PCA, principal component analysis; PFNA, perfluorononanoic acid; PPAR, peroxisome proliferator–activated receptor; RNA-seq, RNA sequencing; RT-qPCR, reverse transcription–quantitative polymerase chain reaction.

Figure 5.

Single-follicle RNA-seq analysis of follicles exposed to PFNA during the FSH-stimulated follicle maturation window. (A) PCA of the first two PCs for follicles treated with PFNA at $250\mathrm{\mu }\mathrm{M}$ ($n=9$) or vehicle ($n=10$). (B) Volcano plot of DEGs; FDR $<0.05$; (absolute fold change $\ge 2$ or $\le 0.5$) in PFNA-treated follicles in comparison with the control. Pink, red: up-regulated genes; black: insignificantly altered genes; light blue: down-regulated genes. (C) Heat map of the same set of follicle maturation-related genes examined by both single-follicle RNA-seq (here) and RT-qPCR. Each column in the heat map represents the relative difference of expression level in the genes for each sample. GO and KEGG pathway analysis of DEGs identified by single-follicle RNA-seq between follicles treated with PFNA at $250\mathrm{\mu }\mathrm{M}$ ($n=9$) or vehicle ($n=10$) during the follicle maturation window. (D–G) GO analyses of DEGs, including the top 10 enriched biological processes (D), the top 10 enriched cellular components (E), and the top 10 enriched molecular functions (F). (G) Top 10 enriched KEGG pathways. Data represent in Figure 5D–G are also presented in Excel Table S1. (H) Single-follicle RNA-seq data analysis comparing DEGs regulated by PFNA to PPAR target genes during follicle maturation window exposure. Heat map of DEGs in enriched process of “cell cycle” and their comparisons with predicted PPAR target genes from the PPAR gene database. Data represented in Figure 5C are included in Excel Table S13. Note: DEGs, differentially expressed gene; FDR, false discovery rate; FSH, follicle-stimulating hormone; GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; PCA, principal component analysis; PFNA, perfluorononanoic acid; PPAR, peroxisome proliferator–activated receptor; RNA-seq, RNA sequencing; RT-qPCR, reverse transcription–quantitative polymerase chain reaction.

Figure 6.

The role of PPAR in the effect of PFNA on follicle maturation. (A,B) Follicles were treated with 0, 0.1, $10\mathrm{\mu }\mathrm{M}$ $\text{PPAR}\mathrm{\alpha }$ antagonist (MK886), $\text{PPAR}\mathrm{\beta }$ antagonist (GWK3787), or $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662) as indicated, or $250\mathrm{\mu }\mathrm{M}$ PFNA, or both $0.1–10\mathrm{\mu }\mathrm{M}$ PPAR antagonists and $250\mathrm{\mu }\mathrm{M}$ PFNA, or vehicle from day 4 to day 6 of eIVFG. (A) Average diameters of follicles from day 0 to day 6. Insets: Average follicle diameter on day 6. Asterisk indicates the significant difference from different treatment groups to the control group ($0\mathrm{\mu }\mathrm{M}$); (B) Percentage of ruptured and unruptured follicles; asterisk indicates the significant difference between the cotreatment of PFNA and PPAR antagonist groups to the corresponding PPAR antagonist concentration groups; (C,D) Follicles were treated with $10\mathrm{\mu }\mathrm{M}$ PPAR antagonists or $250\mathrm{\mu }\mathrm{M}$ PFNA alone or in combination of both, or vehicle control from day 4–6 of eIVFG. (C) Average ${\log }_{10}$ concentration of estradiol and testosterone in the conditioned follicle culture media collected on day 6; asterisk indicates the significant difference between two connected groups. (D) Relative mRNA expression of follicle maturation genes examined by RT-qPCR ($n=8$) in follicles treated with vehicle, $10\mathrm{\mu }\mathrm{M}$ $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662), $250\mathrm{\mu }\mathrm{M}$ PFNA, or both $10\mathrm{\mu }\mathrm{M}$ $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662) and $250\mathrm{\mu }\mathrm{M}$ PFNA; asterisk indicates the indicate significant difference between two connected groups. Expression levels were normalized by the expression of Gapdh. Data were analyzed with Student’s $t$-test (A), Fisher’s exact test (B), and one-way ANOVA followed by a Tukey’s multiple comparisons test (C,D), $n=8–10$ follicles in each treatment group. Shown are $\text{mean}\pm \text{SD}$. Data represented in Figure 6 are included in Excel Table S14. Note: ANOVA, analysis of variance; eIVFG, encapsulated in vitro follicle growth; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; PFNA, perfluorononanoic acid; PPAR, peroxisome proliferator–activated receptor; $\text{PPAR}\mathrm{\alpha }$, peroxisome proliferator–activated receptor alpha; $\text{PPAR}\mathrm{\beta }$, peroxisome proliferator–activated receptor lowercase beta; $\text{PPAR}\mathrm{\gamma }$, peroxisome proliferator–activated receptor lowercase gamma; RT-qPCR, reverse transcription–quantitative polymerase chain reaction; SD, standard deviation. *$p<0.05$; **$p<0.01$; and ***$p<0.001$.

Figure 6.

The role of PPAR in the effect of PFNA on follicle maturation. (A,B) Follicles were treated with 0, 0.1, $10\mathrm{\mu }\mathrm{M}$ $\text{PPAR}\mathrm{\alpha }$ antagonist (MK886), $\text{PPAR}\mathrm{\beta }$ antagonist (GWK3787), or $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662) as indicated, or $250\mathrm{\mu }\mathrm{M}$ PFNA, or both $0.1–10\mathrm{\mu }\mathrm{M}$ PPAR antagonists and $250\mathrm{\mu }\mathrm{M}$ PFNA, or vehicle from day 4 to day 6 of eIVFG. (A) Average diameters of follicles from day 0 to day 6. Insets: Average follicle diameter on day 6. Asterisk indicates the significant difference from different treatment groups to the control group ($0\mathrm{\mu }\mathrm{M}$); (B) Percentage of ruptured and unruptured follicles; asterisk indicates the significant difference between the cotreatment of PFNA and PPAR antagonist groups to the corresponding PPAR antagonist concentration groups; (C,D) Follicles were treated with $10\mathrm{\mu }\mathrm{M}$ PPAR antagonists or $250\mathrm{\mu }\mathrm{M}$ PFNA alone or in combination of both, or vehicle control from day 4–6 of eIVFG. (C) Average ${\log }_{10}$ concentration of estradiol and testosterone in the conditioned follicle culture media collected on day 6; asterisk indicates the significant difference between two connected groups. (D) Relative mRNA expression of follicle maturation genes examined by RT-qPCR ($n=8$) in follicles treated with vehicle, $10\mathrm{\mu }\mathrm{M}$ $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662), $250\mathrm{\mu }\mathrm{M}$ PFNA, or both $10\mathrm{\mu }\mathrm{M}$ $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662) and $250\mathrm{\mu }\mathrm{M}$ PFNA; asterisk indicates the indicate significant difference between two connected groups. Expression levels were normalized by the expression of Gapdh. Data were analyzed with Student’s $t$-test (A), Fisher’s exact test (B), and one-way ANOVA followed by a Tukey’s multiple comparisons test (C,D), $n=8–10$ follicles in each treatment group. Shown are $\text{mean}\pm \text{SD}$. Data represented in Figure 6 are included in Excel Table S14. Note: ANOVA, analysis of variance; eIVFG, encapsulated in vitro follicle growth; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; PFNA, perfluorononanoic acid; PPAR, peroxisome proliferator–activated receptor; $\text{PPAR}\mathrm{\alpha }$, peroxisome proliferator–activated receptor alpha; $\text{PPAR}\mathrm{\beta }$, peroxisome proliferator–activated receptor lowercase beta; $\text{PPAR}\mathrm{\gamma }$, peroxisome proliferator–activated receptor lowercase gamma; RT-qPCR, reverse transcription–quantitative polymerase chain reaction; SD, standard deviation. *$p<0.05$; **$p<0.01$; and ***$p<0.001$.

Figure 7.

Effects of PFNA and GenX on follicle ovulation, expression of ovulatory genes, and gelatinase activity. Follicles were exposed to various concentrations of vehicle, PFNA, or GenX as well as $1.5\text{\hspace{0.17em}IU}/\mathrm{mL}$ hCG on day 6 of eIVFG for in vitro ovulation induction. (A) Percentages of ruptured and unruptured follicles treated with various concentrations of PFNA and GenX. (B) Percentage of ovulated MII oocytes. (C) Average ${\log }_{10}$ concentration ($\text{pg}/\mathrm{mL}$) of progesterone in the conditioned follicle culture media after hCG-stimulated follicles were cultured for 48 h ($n=8$). (D) Relative mRNA expression of ovulation-related genes at 4 h of post-hCG treatment was examined by RT-qPCR. Expression data were normalized with the expression of Gapdh. (E) Representative images and quantification of in situ zymography of follicles treated with vehicle or PFNA at 14 h post hCG. Data were analyzed with Fisher’s exact test (A,B), and Student’s $t$-test (C–E). Shown bars represent $\text{mean}\pm \text{SD}$; $n=8–10$ follicles in each treatment group; asterisk indicates the significant difference from different treatment groups to the control group ($0\mathrm{\mu }\mathrm{M}$); *$p<0.05$; **$p<0.01$. Data represented in Figure 7 are included in Excel Table S15. Note: eIVFG, encapsulated in vitro follicle growth; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; GenX, ammonium salt of HFPO-DA; hCG, human chorionic gonadotropin; HFPO-DA, hexafluoropropylene oxide dimer acid; MFI, mean fluorescent intensity; MII, metaphase II; MII oocytes, oocytes with the first polar body extrusion; PFNA, perfluorononanoic acid; RT-qPCR, reverse transcription–quantitative polymerase chain reaction; SD, standard deviation.

Figure 8.

Single-follicle RNA-seq analysis of follicles exposed to PFNA during the ovulation window only. (A–H) Follicles were treated with vehicle control or $250\mathrm{\mu }\mathrm{M}$ PFNA and $1.5\text{\hspace{0.17em}UI}/\mathrm{mL}$ hCG for 4 h on day 8 of eIVFG. (A) PCA of the first two principal components for follicles treated with PFNA ($n=10$) or vehicle control ($n=11$). (B) Volcano plot of differentially expressed genes (DEGs; FDR $<0.05$; absolute fold change $>2$ or $<-2$) in PFNA-treated follicles in comparison with the control group. Pink, red: up-regulated genes; black: nonsignificantly altered genes; light blue: down-regulated genes. (C) Heat map indicating relative change of ovulatory genes in PFNA-treated follicles (column 12–21) and control (column 1–11). (D,F) GO analyses of DEGs, including the top 10 biological process enrichment results (D), the top 10 cellular component enrichment results (E), and the top 10 molecular function enrichment results (F). (G) Top 10 KEGG pathway enrichment results. (H) Heat map indicating relative change of inflammatory genes in PFNA-treated follicles (column 12–21) and control (column 1–11). Data presented in Figure 8C,H are included in Excel Table S16; Figure 8D,G data are included in Excel Table S2. Note: DEG, differentially expressed gene; eIVFG, encapsulated in vitro follicle growth; FDR, false discovery rate; GO, gene ontology; hCG, human chorionic gonadotrophin; KEGG, Kyoto Encyclopedia of Genes and Genomes; PCA, principal component analysis; PFNA, perfluorononanoic acid; RNA-seq, RNA sequencing.

Figure 8.

Single-follicle RNA-seq analysis of follicles exposed to PFNA during the ovulation window only. (A–H) Follicles were treated with vehicle control or $250\mathrm{\mu }\mathrm{M}$ PFNA and $1.5\text{\hspace{0.17em}UI}/\mathrm{mL}$ hCG for 4 h on day 8 of eIVFG. (A) PCA of the first two principal components for follicles treated with PFNA ($n=10$) or vehicle control ($n=11$). (B) Volcano plot of differentially expressed genes (DEGs; FDR $<0.05$; absolute fold change $>2$ or $<-2$) in PFNA-treated follicles in comparison with the control group. Pink, red: up-regulated genes; black: nonsignificantly altered genes; light blue: down-regulated genes. (C) Heat map indicating relative change of ovulatory genes in PFNA-treated follicles (column 12–21) and control (column 1–11). (D,F) GO analyses of DEGs, including the top 10 biological process enrichment results (D), the top 10 cellular component enrichment results (E), and the top 10 molecular function enrichment results (F). (G) Top 10 KEGG pathway enrichment results. (H) Heat map indicating relative change of inflammatory genes in PFNA-treated follicles (column 12–21) and control (column 1–11). Data presented in Figure 8C,H are included in Excel Table S16; Figure 8D,G data are included in Excel Table S2. Note: DEG, differentially expressed gene; eIVFG, encapsulated in vitro follicle growth; FDR, false discovery rate; GO, gene ontology; hCG, human chorionic gonadotrophin; KEGG, Kyoto Encyclopedia of Genes and Genomes; PCA, principal component analysis; PFNA, perfluorononanoic acid; RNA-seq, RNA sequencing.

Figure 9.

The role of PPAR in the effect of PFNA on follicle ovulation. (A) GSEA of DEGs, including KEGG PPAR signaling pathway gene sets and predicted PPAR target genes. (B) Heat map of genes in the KEGG PPAR signaling pathway and predicted PPAR target genes. Columns represent the relative difference of expression level of genes in each sample. (C) Follicles were treated with 0, 0.1, 1, $10\mathrm{\mu }\mathrm{M}$ PPAR antagonists, or $250\mathrm{\mu }\mathrm{M}$ PFNA, or combination of PPAR antagonists and PFNA, or vehicle control. Follicle rupture was then examined at 14 h post hCG and ($n=10$); asterisk indicates the significant difference between the cotreatment of PFNA and PPAR antagonist groups to the corresponding PPAR antagonist concentration groups. (D) Relative mRNA expression of ovulatory genes examined by RT-qPCR; follicles were treated with $10\mathrm{\mu }\mathrm{M}$ $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662), $250\mathrm{\mu }\mathrm{M}$ PFNA, or a combination of both, or vehicle control with hCG for 4 h ($n=8$). The expression level of each gene was normalized by the expression of Gapdh. Asterisk indicates the significant difference between two connected groups. (E) Average ${\log }_{10}$ concentration of progesterone in conditioned ovulation-induction media collected 48 h post hCG ($n=8–10$); asterisk indicates the significant difference between two connected groups. Statistical analyses were done with Fisher’s exact test (B) and one-way ANOVA followed by a Tukey’s multiple comparisons test (C,D). Bars represent $\text{mean}\pm \text{SD}$. Data presented in Figure 9 are presented in Excel Table S17–S18. Note: ANOVA, analysis of variance; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; GSEA, gene set enrichment analysis; hCG, human chorionic gonadotrophin; KEGG, Kyoto Encyclopedia of Genes and Genomes; PFNA, perfluorononanoic acid; PPAR, peroxisome proliferator–activated receptor; RT-qPCR, reverse transcription–quantitative polymerase chain reaction; SD, standard deviation. *$p<0.05$; **$p<0.01$; and ***$p<0.001$.

Figure 9.

The role of PPAR in the effect of PFNA on follicle ovulation. (A) GSEA of DEGs, including KEGG PPAR signaling pathway gene sets and predicted PPAR target genes. (B) Heat map of genes in the KEGG PPAR signaling pathway and predicted PPAR target genes. Columns represent the relative difference of expression level of genes in each sample. (C) Follicles were treated with 0, 0.1, 1, $10\mathrm{\mu }\mathrm{M}$ PPAR antagonists, or $250\mathrm{\mu }\mathrm{M}$ PFNA, or combination of PPAR antagonists and PFNA, or vehicle control. Follicle rupture was then examined at 14 h post hCG and ($n=10$); asterisk indicates the significant difference between the cotreatment of PFNA and PPAR antagonist groups to the corresponding PPAR antagonist concentration groups. (D) Relative mRNA expression of ovulatory genes examined by RT-qPCR; follicles were treated with $10\mathrm{\mu }\mathrm{M}$ $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662), $250\mathrm{\mu }\mathrm{M}$ PFNA, or a combination of both, or vehicle control with hCG for 4 h ($n=8$). The expression level of each gene was normalized by the expression of Gapdh. Asterisk indicates the significant difference between two connected groups. (E) Average ${\log }_{10}$ concentration of progesterone in conditioned ovulation-induction media collected 48 h post hCG ($n=8–10$); asterisk indicates the significant difference between two connected groups. Statistical analyses were done with Fisher’s exact test (B) and one-way ANOVA followed by a Tukey’s multiple comparisons test (C,D). Bars represent $\text{mean}\pm \text{SD}$. Data presented in Figure 9 are presented in Excel Table S17–S18. Note: ANOVA, analysis of variance; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; GSEA, gene set enrichment analysis; hCG, human chorionic gonadotrophin; KEGG, Kyoto Encyclopedia of Genes and Genomes; PFNA, perfluorononanoic acid; PPAR, peroxisome proliferator–activated receptor; RT-qPCR, reverse transcription–quantitative polymerase chain reaction; SD, standard deviation. *$p<0.05$; **$p<0.01$; and ***$p<0.001$.

Figure 10.

Effects of PFNA on ovulation in a mouse superovulation model. (A) Schematic of the superovulation model and PFNA exposure in vivo. (B) Average numbers of ovulated oocytes collected from prepubertal mice treated with vehicle ($n=18$), 1 ($n=9$), 5 ($n=13$), and 25 ($n=9$) mg/kg of PFNA; asterisk indicates the significant difference from different PFNA dose groups to the control group ($0\mathrm{mg}/\mathrm{kg}$ PFNA). (C) Representative images of ovary histology from mice treated with PBS and $25\mathrm{mg}/\mathrm{kg}$ PFNA. Red arrows indicate unovulated late-stage antral follicles. (D) Average number of antral follicles in mice treated with PBS ($n=5$) or $25\mathrm{mg}/\mathrm{kg}$ PFNA ($n=5$). (E) Analytical measurement of PFNA in the serum, whole ovary, or FF of large antral follicles ($n=3–4$). The amount of PFNA in the whole ovary and ovary FF is referred to the left y-axis (PFNA ng per ovary). The concentration of PFNA in serum is referred to the right y-axis (PFNA $\mathrm{\mu }\mathrm{g}/\mathrm{mL}$ serum). (F) Relative mRNA expression of ovulation-related genes at 4 h post hCG injection examined by RT-qPCR ($n=5$ in the control and $n=5$ in the PFNA treatment group). Expression data were normalized with Gapdh. Asterisk indicates the significant difference from different PFNA dose groups to the control 4 h post-hCG group ($0\mathrm{\mu }\mathrm{M}$). (G) Representative images of in situ hybridization of large antral follicles treated with vehicle or PFNA at 4 h post hCG injection. (H) Average numbers of ovulated oocytes collected from mice treated with PBS ($n=8$), $1\mathrm{mg}/\mathrm{kg}$ $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662) ($n=5$), $25\mathrm{mg}/\mathrm{kg}$ PFNA ($n=8$), or cotreatment of $\text{PPAR}\mathrm{\gamma }$ antagonist (GW9662) and PFNA ($n=9$); asterisk indicates the significant difference between two connected groups. Data were analyzed with Student’s $t$-test (B,D). Error bars: $\text{mean}\pm \text{SD}$. Data in Figure 10 are presented in Excel Table S19. Note: FF, follicular fluid; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; hCG, human chorionic gonadotrophin; ND, nondetectable; PBS, phosphate-buffered saline; PFNA, perfluorononanoic acid; $\text{PPAR}\mathrm{\gamma }$, peroxisome proliferator–activated receptor gamma; RT-qPCR, reverse transcription–quantitative polymerase chain reaction; SD, standard deviation. *$p<0.05$; **$p<0.01$.

Figure 11.

BMCL₁₀ of PFNA for dual-, maturation-, and ovulation-window exposures as indicated for in vitro follicle rupture (A) and meiotic resumption (B). Data presented in this figure are also included in Excel Table S5–S7. Note: BMCL, benchmark concentration lower confidence limit; BMD, benchmark dose modeling; PFNA, perfluorononanoic acid.