Exposure to Legacy and Novel Per- and Polyfluoroalkyl Substances and Diminished Ovarian Reserve: Evidence from Blood-Follicle Transfer and Mixture Risk Assessment in Reproductive-Aged Women

A total of 361 plasma and 261 follicular fluid samples were collected from enrolled participants. Following sample matching, 222 paired plasma-follicular fluid sets were retained for BFTE analysis. From the follicular fluid cohort, a case-control study was established, comprising 92 individuals diagnosed with DOR and 92 age- and BMI-matched controls. Baseline demographic and exposure characteristics of the matched cohort are summarized in Table . The DOR group had a median age of 33.0 years and a median BMI of 22.6 kg/m 2 , while the control group had corresponding values of 34.0 years and 22.5 kg/m 2 . Median infertility duration was 3.0 years in both groups. Statistically significant differences were observed between groups for educational attainment, physical activity frequency, exposure to rubber or plastic products, exposure to disinfectant, and egg consumption frequency ( p < 0.05). In contrast, no significant differences were detected in menstrual cycle characteristics (duration, cycle length, or flow), household income, smoking status, alcohol consumption, fish intake, history of spontaneous abortion, or parity ( p ≥ 0.05). Abbreviations: BMI, body mass index; n = sample size. Among the PFAS detected in matched plasma and follicular fluid samples, 15 compounds with detection rates exceeding 50% in both matrices were retained for BFTE analysis ( Tables S4, S5 ). This subset consisted of eight PFCA (PFBA, PFHpA, PFOA, PFNA, PFDA, PFUnDA, PFDoDA, and PFTriDA), two PFECA (PFMOAA and PFO5DoDA), three PFSA (PFHxS, PFHpS, and PFOS), and two PFESA (6:2 Cl-PFESA and 8:2 Cl-PFESA) ( Table S6 ). PFOA exhibited the highest median concentration across all PFAS analytes, measuring 3.50 ng/mL in follicular fluid and 4.55 ng/mL in plasma, followed by PFOS at 2.78 ng/mL and 3.73 ng/mL, respectively. The alternative compound 6:2 Cl-PFESA also showed relatively high levels, with median concentrations of 0.88 ng/mL in follicular fluid and 1.20 ng/mL in plasma ( Table S6 ; Figure A,B). Concentrations of PFAS detected in human follicular fluid samples and in the paired plasma samples. (A) Concentrations of PFAS in human follicular fluid samples. (B) Concentrations of PFAS in the paired plasma samples. (C) Distribution levels of main PFAS in follicular fluid of case and control participants. Corresponding raw data are presented in Tables S6 and S7 . Within the case-control cohort, 13 PFCA/PFECA (PFBA, PFPeA, PFHxA, PFHpA, PFMOAA, PFOA, PFNA, PFDA, PFUnDA, PFDoDA, PFTriDA, PFTeDA, and PFO5DoDA) and six PFSA/PFESA (PFBS, PFHxS, PFHpS, PFOS, 6:2 Cl-PFESA, and 8:2 Cl-PFESA) were detected in more than 50% of follicular fluid samples ( Table S7 ). PFOA and PFOS remained the dominant species, with median concentrations of 3.75 ng/mL (cases: 3.44 ng/mL; controls: 3.92 ng/mL) and 2.84 ng/mL (cases: 2.82 ng/mL; controls: 2.84 ng/mL), respectively. Several emerging compounds, including PFMOAA (0.96 ng/mL) and 6:2 Cl-PFESA (0.88 ng/mL), were present at appreciable concentrations. Comparative analysis revealed significant group differences for PFBA, PFPeA, PFTeDA, PFBS, and PFHxS ( p < 0.05, Table S7 ), with the DOR group exhibiting elevated levels of PFBA and PFPeA relative to controls ( Figure C). Transfer efficiency of PFAS from blood to follicle and its association with chain length. (A) Blood-follicle transfer efficiencies of PFAS. (B) Simple linear regression model examining the association of chain length with transfer efficiencies for PFAS with detection rates more than 50%. Corresponding raw data are presented in Table S6 . Pearson correlation analysis stratified by carboxylic and sulfonic acid classes revealed distinct clustering patterns. Strong positive correlations were observed among short-chain PFCA/PFECA (PFBA, PFPeA, PFHxA, and PFMOAA), with coefficients ranging from 0.60 to 0.88. Long-chain PFCA/PFECA exhibited even stronger correlations, with the strongest correlation observed between PFDoDA and PFUnDA ( r = 0.94). A similar trend was observed among sulfonic acids, with long-chain PFSA/PFESA compounds exhibiting moderate to strong correlations ( r = 0.57–0.84) and short-chain compounds such as PFBS and PFHxS exhibiting weaker associations ( r = 0.29). These correlation structures suggest that PFAS with similar chemical properties may share common exposure pathways or exhibit analogous transport dynamics. Median BFTEs across the 15 PFAS compounds ranged from 62.43% to 470.93% ( Figure A; Table S6 ), revealing a distinct chain-length-dependent pattern. Among PFCA, a pronounced inverse relationship was observed between carbon chain length and BFTE, with transfer efficiencies exceeding 100% restricted to short-chain PFCA and all PFECA, descending in the order PFBA (470.93%), PFMOAA (418.08%), PFO5DoDA (146.52%), and PFHpA (135.44%). In contrast, PFSA and PFESA displayed substantially lower transfer efficiencies, with PFHxS reaching 84.61% and 8:2 Cl-PFESA showing the lowest value at 62.43%. Simple linear regression analysis substantiated a significant inverse relationship between carbon chain length and BFTE [β = −0.31 (95% CI: −0.52, −0.11)], indicating that molecular size exerts a constraining effect on PFAS passage across the blood-follicle barrier ( Figure B). Associations between specific PFAS and DOR are shown in Table S8 and Figure . Fully adjusted logistic regression models identified strong positive associations between short-chain PFCA and PFECA, notably PFBA and PFPeA, and the likelihood of DOR, with ORs of 1.58 (95% CI: 1.22, 2.05) and 1.36 (95% CI: 1.12, 1.65) per unit increase in ln-transformed concentration, respectively. In contrast, inverse associations were observed for several long-chain compounds, including PFTriDA (OR: 0.57, 95% CI: 0.33, 0.99), PFTeDA (OR: 0.36, 95% CI: 0.18, 0.73), and PFHxS (OR: 0.56, 95% CI: 0.32, 0.98). Analysis of AMH concentrations revealed divergent trends across PFAS compounds. Significant negative associations with AMH were observed for PFBA, PFPeA, and PFMOAA, whereas positive associations emerged for PFOA, PFUnDA, PFDoDA, PFTriDA, PFTeDA, PFHxS, 6:2 Cl-PFESA, and 8:2 Cl-PFESA ( Table S9 ; Figure ). Poisson regression models assessing AFC demonstrated significant reductions associated with short-chain PFAS exposure: each ln-unit increase in PFBA, PFPeA, PFHxA, and PFMOAA corresponded to significant declines in AFC to 91%, 94%, 95%, and 93% of baseline values, respectively ( Table S10 ; Figure ). Associations of individual PFAS exposure in follicular fluid with DOR and ovarian reserve parameters (AMH, AFC). Odds ratios (ORs) for DOR were derived from conditional logistic regression; β coefficients for AMH from multiple linear regression; and incidence rate ratio (IRR) for AFC from Poisson regression. The numbers in the figure represent the effect sizes from the regression analyses. Note: All models were adjusted for educational level, physical exercise frequency, exposure to rubber and plastic products, exposure to disinfectants, and egg consumption, abortion, and parturition. Linear and Poisson regression were additionally adjusted for age and BMI. *: p < 0.05, **: p < 0.01, ***: p < 0.001. The numerical values are presented in Tables S9–S11 . Quartile-based analyses further substantiated the associations identified in continuous exposure models ( Table S11 ). Elevated DOR risk was observed in the third and fourth quartiles of PFBA concentrations and across all quartiles of PFPeA, with significant dose–response trends ( p < 0.05). In contrast, PFBS exhibited an inverse relationship with DOR risk relative to the lowest quartile. AMH concentrations declined markedly with increasing exposure to short-chain compounds, including PFBA, PFPeA, PFHxA, and PFMOAA. Conversely, progressive elevations in AMH were observed across higher quartiles of several long-chain PFAS, including PFOA, PFUnDA, PFDoDA, PFTriDA, PFO5DoDA, PFBS, PFHxS, PFHpS, and PFOS. In quartile-based analyses of AFC, significant inverse dose–response trends were identified for short-chain PFCA/PFECA and PFDA. To investigate potential nonlinear exposure-response relationships, RCS models were constructed using knots at the fifth, 35th, 65th, and 95th percentiles ( Figures S4, S5 ). PFHpA was excluded due to insufficient effective knots compromising spline structure stability. Analysis revealed a significant inverted U-shaped association between PFUnDA and DOR risk ( Figure S4 ), while PFOA, PFNA, PFDA, and PFUnDA all demonstrated significant U-shaped relationships with AMH concentrations ( Figure S5 ). As shown in Figure A, increasing PFAS mixture concentrations were positively associated with the risk of DOR. Each quartile increment in the mixture index corresponded to an OR of 2.00 (95% CI: 1.24, 3.22) for DOR ( Figure A; Table S12 ). WQS regression identified PFBA as the dominant contributor (58.40%), followed by PFNA, PFO5DoDA, and PFOA ( Figure A; Table S13 ). BKMR analysis supported these findings, revealing a monotonic increase in DOR risk with rising mixture exposure levels ( Figure B). Posterior inclusion probability analysis further highlighted short-chain PFCA/PFECA as the most influential group (groupPIP = 1.000), with PFBA exhibiting the highest conditional probability (condPIP = 0.7558) ( Table S14 ). In single-exposure modeling, an increase in PFBA from the 25th to 75th percentile was most strongly associated with DOR ( Figure S6 ). Univariate exposure-response functions confirmed a pronounced positive relationship between PFBA and DOR, with a steep dose–response curve ( Figure S7 ). No meaningful interaction effects were detected among PFAS compounds, as the concentration–response slopes remained stable across coexposure levels ( Figure S8 ). Although inverse trends were noted between total PFAS mixture exposure and both AMH and AFC, these associations did not reach statistical significance ( Figure C, D). Associations of PFAS mixture with DOR, AMH, and AFC ( n = 184). (A) WQS analysis of the associations between the follicular fluid PFAS mixture and DOR. (B) Associations between the follicular fluid PFAS mixture and DOR calculated by BKMR. (C) WQS analysis of the associations between the follicular fluid PFAS mixture and AMH. (D) WQS analysis of the associations between the follicular fluid PFAS mixture and AFC. Note: WQS and BKMR models for DOR were adjusted for educational level, physical exercise frequency, exposure to rubber and plastic products, exposure to disinfectants, and egg consumption, abortion, and parturition. Models for AMH and AFC were further adjusted for age and BMI. Targeted analysis of the short-chain PFCA/PFECA subgrouppreviously identified as key contributorswas applied to isolate their effects on ovarian reserve. In the WQS model constrained for positive direction, a one-unit increase in the short-chain PFCA/PFECA mixture index was associated with a significantly elevated DOR risk (OR = 1.88), with PFBA again emerging as the primary driver ( Figure A; Tables S12, S15 ). The mixture index was also negatively associated with AMH concentrations (β = −1.28), with PFHpA and PFBA contributing the highest weights ( Figure B; Tables S12, S15 ). For AFC, increasing mixture concentrations corresponded to a reduction to 92% of baseline values, again predominantly attributable to PFBA ( Figure C; Tables S12, S15 ). All WQS models focused on the short-chain PFCA/PFECA subset yielded statistically significant results, and detailed weights and estimates are provided in Tables S12 and S15 . These key contributorsparticularly PFBAwere consistently identified across both the full mixture and the short-chain-specific WQS models. For comparative analysis, WQS models were also constructed for long-chain PFCA/PFECA and PFSA/PFESA. These showed divergent directions of association with DOR and AMH, while AFC tended to decrease in all models except for the negatively constrained long-chain PFCA/PFECA model, in which AFC showed a modest increase with greater mixture exposure ( Tables S12, S16, S17 ). Associations of short-chain PFCA/PFECA mixture with DOR, AMH, and AFC ( n = 184). (A) WQS analysis of the associations between the follicular fluid short-chain PFCA/PFECA mixture and DOR. (B) WQS analysis of the associations between the follicular fluid short-chain PFCA/PFECA mixture and AMH. (C) WQS analysis of the associations between the follicular fluid short-chain PFCA/PFECA mixture and AFC. Note: WQS models for DOR were adjusted for educational level, physical exercise frequency, exposure to rubber and plastic products, exposure to disinfectants, and egg consumption, abortion, and parturition Models for AMH and AFC were further adjusted age and BMI. To address multicollinearity among PFAS concentrations in follicular fluid, PCA was conducted ( Table S18 ). Components with eigenvalues exceeding 1 were retained, yielding four principal components that individually explained 48.70%, 16.98%, 5.99%, and 5.73% of total variance, respectively. The cumulative variance explained by these four components was 77.40% (PC1:48.70%, PC1+PC2:65.68%, PC1+PC2+PC3:71.67%, PC1+PC2+PC3+PC4:77.40%) ( Table S19 ). PC1 primarily captured variation in long-chain PFCA/PFECA and PFSA/PFESA, excluding PFBS. PC2 was largely driven by short-chain PFCA/PFECA, with the exception of PFHpA. PC3 and PC4 were predominantly defined by PFBS and PFHpA respectively. PCR identified significant associations between specific PCs and ovarian reserve indicators ( Table S20 ). Both PC2 and PC4 were positively associated with the likelihood of DOR. For AMH, a positive association was observed with PC1, while PC2 showed a negative relationship. In the analysis of AFC, only PC2 demonstrated a statistically significant inverse association.

Reproductive-aged women (≤40 years) receiving clinical care at Shengjing Hospital in Shenyang, China, between 2017 and 2020 were enrolled in this study. Matched plasma and follicular fluid samples were collected from each participant whenever possible. All participants were fully informed of the study procedures and provided written informed consent. The Ethics Review Committee of Shengjing Hospital of China Medical University approved this study (Approval No.: 2019PS024F). Sample collection occurred on the day of oocyte retrieval, and participants voluntarily provided the paired biological samples. After exclusion of follicular fluid samples with insufficient volume or blood contamination, a total of 361 plasma and 261 follicular fluid samples were available for analysis. Details of the participant pairing protocol are presented in Figure S1 . Clinical data were extracted from electronic medical records by uniformly trained personnel following completion of IVF cycles. In accordance with clinical requirements and to eliminate the potential confounding due to differences in bilateral follicle development, follicular fluid samples were aspirated during oocyte retrieval by puncturing the dominant follicle in the left ovary. To avoid contamination or dilution by flushing media during double-lumen needle aspiration, only the initial aspirate was collected. Approximately 1–2 mL of follicular fluid was obtained and centrifuged at 3 000 r/min for 5 min. The supernatant was transferred into 500 μL microcentrifuge tubes and stored at – 80 °C for subsequent analysis. A total of 32 PFAS were quantified, including C4–C12 perfluorocarboxylic acids (PFCA) [PFBA, perfluoropentanoic acid (PFPeA), perfluorohexanoic acid (PFHxA), PFHpA, PFOA, perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoDA), perfluorotridecanoic acid (PFTriDA), and perfluorotetradecanoic acid (PFTeDA)]; perfluorosulfonic acids (PFSA) with carbon chain lengths of 4, 5, 6, 7, 8, and 10 [PFBS, perfluoropentanesulfonic acid (PFPeS), perfluorohexanesulfonic acid (PFHxS), perfluoroheptanesulfonic acid (PFHpS), PFOS, and perfluorodecanesulfonic acid (PFDS)]; 13 PFECA [hexafluoropropylene oxide dimer acid (HFPO–DA), perfluoro-2,5-dimethyl-3,6-dioxo-heptanoic acid (HFPO-TrA (C7)), perfluoro-2,5-dimethyl-3,6-dioxo-octanoic acid (HFPO-TrA (C8)), hexafluoropropylene oxide trimer acid (HFPO-TrA (C9)), hexafluoropropylene oxide tetramer acid (HFPO-TeA), perfluoro-2-methoxyacetic acid (PFMOAA), perfluoro-(3,5,7,9-tetraoxadecanoic) acid (PFO4PeA), perfluoro-5-oxahexanoic acid (PF5OHxA), perfluoro-(3,5-dioxahexanoic) acid (PFO2HxA), perfluoro-3,6-dioxaheptanoic acid (3,6-OPFHpA), perfluoro-(3,5,7-trioxaoctanoic) acid (PFO3OA), perfluoro-(3,5,7,9-tetraoxadecanoic) acid (PFO4DA), and perfluoro-3,5,7,9,11-pentaoxadodecanoic acid (PFO5DoDA)]; and 3 PFESA [4:2 chlorinated polyfluoroalkyl ether sulfonic acid (4:2 Cl-PFESA), 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA), and potassium 11-chloroheicosafluoro-3-oxanonane-1-sulfonate (8:2 Cl-PFESA)]. Analytical protocols followed a previously published method. After thawing at 4 °C, plasma and follicular fluid samples were vortexed and centrifuged to eliminate fibrin precipitates generated during the freeze–thaw process. We added 5 μL (0.5 ng) of a mixed internal standard working solution and 1 mL of acetonitrile into 200 μL of plasma or 400 μL of follicular fluid samples, respectively. After ultrasonic treatment, vortex mixing, and centrifugation, the supernatant was collected. The extraction procedure was repeated, and combined supernatants were evaporated to dryness under a gentle nitrogen stream. Redissolve the residue in 200 μL of methanol–water, vortex (2 000 r/min, 2 min), and then centrifuge (4 400 r/min, 15 min). Transfer 100 μL of the supernatant into a vial for instrumental analysis. Target PFAS were measured using ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS, AB SCIEX 6500, Framingham, MA, USA). Details on the chromatographic columns and instrument parameters are provided in Tables S1, S2 . Comprehensive quality assurance and control (QA/QC) procedures were implemented to ensure accurate PFAS quantification. One procedural blank was included in each batch of 20 samples to monitor potential background contamination. Quality control materials (SRM1957 for plasma and pooled control samples for follicular fluid) were analyzed with each batch to evaluate data reliability. Calibration standards (0.1, 1, and 10 ng/mL) were analyzed every 40 samples to monitor chromatographic system performance. Limits of quantification (LOQs) ranged from 0.01–0.02 ng/mL for plasma and 0.005–0.01 ng/mL for follicular fluid. Matrix spike recovery rates ranged from 82.29%–115.21% for plasma and 80.42%–118.76% for follicular fluid. Plasma and follicular fluid samples were paired to generate matched sets for evaluating PFAS partitioning between the two biological matrices. The BFTEs were calculated as the ratio of PFAS concentrations in follicular fluid to those in plasma. To enhance estimation accuracy, only analytes with detection frequencies exceeding 50% in paired samples were included in BFTE calculations. Compounds with a detection rate lower than 50% in any matrix were excluded, including PFPeA, PFHxA, PFTeDA, PFBS, PFPeS, PFO4PeA and 4:2 Cl-PFESA. Avoid potential bias due to low exposure levels where most of the data rely on imputation. Associations between PFAS carbon chain length and BFTE values were examined using simple linear regression models. DOR currently lacks universally standardized diagnostic criteria, although it is commonly defined by reduced AMH, low AFC, and elevated FSH. For this study, DOR was diagnosed when at least one of the following conditions was met: AFC < 6 or AMH 12 U/L is recognized as an auxiliary diagnostic marker, it was not used for classification due to the requirement for repeated measurements to ensure reliability. Case exclusion criteria were: (a) Age ≥ 40 years or BMI > 30 kg/m 2 ; (b) clinical diagnosis of polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI), endometriosis, adenomyosis, thyroid disorders, hyperprolactinemia, or hyperglycemia; (c) prior ovarian surgery, tuberculosis, or bilateral salpingectomy; and (d) missing baseline serum sex hormone data. Control inclusion criteria were: (a) age ≤ 40 years and BMI < 30 kg/m 2 ; (b) no history of recurrent miscarriage; (c) absence of exclusion conditions (b–d); and (d) undergoing assisted reproduction for male-factor infertility. Cases and controls were matched 1:1 using SPSS software based on age (±1 year) and BMI (±1 kg/m 2 ). Detailed matching results are presented in Table S3 . Covariates were identified using both directed acyclic graphs and statistical comparisons ( Figure S2 ). Independent samples t -tests (for continuous variables) and chi-square tests (for categorical variables) were applied to compare potential confounders between groups, excluding samples with missing data and omitting categorical variable groups with incidence below 5%. Variables showing significant between-group differences ( p < 0.05) were retained as covariates and included educational attainment, physical activity frequency, exposure to disinfectants, exposure to rubber and plastic products, and egg consumption. Furthermore, given established evidence linking abortion history and prior parturition to PFAS accumulation and ovarian function, these two continuous variables were also incorporated as control factors in subsequent analyses. Descriptive statistics were employed to characterize the demographic profiles and PFAS concentrations in both case and control groups. Categorical variables were presented as frequencies and percentages, while continuous variables were reported as medians with interquartile ranges (25th–75th percentiles). All continuous variables underwent normality assessment prior to statistical analysis. PFAS and AMH concentrations exhibited skewed distributions. Therefore, group differences in PFAS concentrations were assessed using the Wilcoxon rank-sum test. Only compounds detected in more than 50% of follicular fluid samples were retained for further statistical analysis. Values below the LOQ were imputed as LOQ divided by √ 2 . For multivariate models requiring the assumption of normality, all follicular fluid PFAS concentrations and AMH values were natural log (ln)-transformed. The skewness of the transformed data decreased, and Shapiro-Wilk tests indicated that most variables followed a normal distribution ( p > 0.05), supporting the use of parametric methods. Pearson correlation coefficients were calculated to examine intercorrelations among ln-transformed PFAS analytes. To assess the association between individual PFAS and ovarian reserve outcomes, multivariable regression models were used and provided effect estimates. Logistic regression was used to estimate the odds ratios (ORs) of DOR, multiple linear regression was applied to model AMH levels, and Poisson regression to calculate the incidence rate ratios of AFC. Covariate adjustment followed a three-tiered strategy: unadjusted crude model; Model 1 adjusted for educational attainment, physical activity, exposure to rubber and plastic products, exposure to disinfectants, and egg consumption; and Model 2, which additionally adjusted for obstetric history, including prior childbirth and abortion. For linear and Poisson regression analyses, all models additionally controlled for age and BMI. In addition, to evaluate the trend of ovarian reserve outcomes with PFAS quartile, we treated the median value of each PFAS quartile as a continuous variable and calculated the p -trend. Restricted cubic spline (RCS) regression was also employed to examine nonlinear dose–response relationships between ln-transformed PFAS levels and DOR. To evaluate the joint effects of PFAS exposure, weighted quantitative sum (WQS) regression and Bayesian kernel machine regression (BKMR) models were employed. WQS regression was set as primary method to constructs a weighted index representing combined exposure to multiple PFAS, allowing estimation of the joint association with outcomes and quantification of the relative contribution of each compound. In the WQS model, exposure data were randomly partitioned into a 40% training set for weight derivation and a 60% validation set for association testing, with 500 bootstrap iterations to enhance parameter stability. However, this model requires the assumption that the effects of all compounds are in the same direction. Using BKMR as a supplement allows for flexible modeling of potentially nonlinear relationships and interactions among mixture components, without requiring the effect directions in advance. Given the high collinearity among PFAS, stratified BKMR analyses were performed by chemical class: short-chain PFCA/PFECA, long-chain PFCA/PFECA, and PFSA/PFESA. All BKMR models were implemented using a Markov chain Monte Carlo (MCMC) algorithm with 10 000 iterations to ensure posterior convergence. To address multicollinearity, we conducted principal component regression (PCR) by integrating principal component analysis (PCA) with multiple regression. Data were Z-score normalized, and components with eigenvalues greater than 1 (per Kaiser criterion) were retained for inclusion in the regression models. This method can identify potential exposure patterns of PFAS and assess the association between these patterns and outcomes. WQS, BKMR, and RCS analyses were conducted in R v4.4.1 (R Development Core Team) using the packages “gWQS”, “bkmr”, and “plotRCS”, respectively. All other statistical analyses were performed using SPSS v27.0 (SPSS Inc., Chicago, IL, USA). A two-sided p -value <0.05 was considered statistically significant.

This study provides the first evidence that PFECA (PFMOAA and PFO5DoDA) are present in human follicular fluid, demonstrating that short-chain and alternative perfluoroalkyl ether carboxylic acids can cross the blood-follicle barrier. Analyses identified a significant positive correlation between PFAS exposure and DOR risk, with short-chain PFCA/PFECA serving as the principal contributors and PFBA exerting the strongest influence. These findings advance current understanding of the reproductive hazards associated with short-chain and alternative PFAS and highlight the importance of incorporating these compounds into future risk-assessment frameworks.

Widespread detection of both legacy and emerging PFAS in human follicular fluid provides direct evidence for their translocation across the blood-follicle barrier, implying potential risk of exposure to oocytes. A statistically robust association was observed between PFAS mixture burden and elevated risk of DOR. Notably, compound-specific exposure-response patterns were detected, with short-chain PFCA/PFECA species showing preferential accumulation in follicular fluid and exerting a marked influence on DOR risk, predominantly by PFBA. Despite global restrictions on PFOA and PFOS under the Stockholm Convention, these substances remained the predominant PFAS detected in follicular fluid. However, concentrations in this cohort were lower than those reported in multiple Chinese populations, including 6.54 ng/mL and 3.13 ng/mL in infertile women in Shanghai, 5.56 ng/mL and 4.28 ng/mL in IVF-ET patients in Yantai and Beijing, and 4.35 ng/mL and 5.22 ng/mL in PCOS patients in Xiamen. Compared with European data sets, PFOA levels were lower, while PFOS concentrations were comparable with values reported in Sweden and Estonia. In addition to legacy compounds, this study is the first to have identified PFMOAA and PFO5DoDA in human follicular fluid, with detection frequencies exceeding 90% of samples. These high detection frequencies, combined with strong BFTEs, highlight the substantial biological accessibility of novel ether-based PFAS. Furthermore, 6:2 Cl-PFESA, a widely used PFOS replacement in the electroplating sector, was detected at concentrations similar to or exceeding those of several long-chain PFCA. Median levels exceeded those reported in Guangxi (0.452 ng/mL) but were slightly lower than those measured in Beijing (1.09 ng/mL) and Yantai (2.16 ng/mL), reflecting a distinct exposure profile among Chinese populations. PFAS distribution between plasma and follicular fluid exhibited clear chain length-dependent partitioning, consistent with prior findings in IVF cohorts from Guangxi and Beijing. BFTEs decreased with increasing chain length, with short-chain PFCA and all PFECA species demonstrating markedly higher transfer efficiencies. These patterns suggest preferential accumulation in follicular fluid compared to plasma, potentially due to the binding characteristics of serum albumin. , Compounds with lower binding affinity and smaller molecular dimensionscharacteristic of short-chain PFASmore readily accumulate in follicular fluid. In contrast, long-chain compounds exhibit strong albumin binding that reduces the freely dissolved fraction available for transfer. A previous study has shown that the logKow of PFAS is significantly negatively associated with its BFTEs, suggesting that the higher lipophilicity of long-chain PFAS further restricts their transfer efficiencies. The lower BFTEs of sulfonic acids relative to carboxylic acids of comparable carbon chain length are likely attributable to the stronger binding affinity of PFOS for serum albumin compared to PFOA. , Although direct measurements of albumin binding for ether-based PFAS are limited, the reduced albumin-water partition coefficient reported for HFPO–DA compared to PFHxA indicates that ether oxygen substitution may attenuate protein-binding affinity, providing a plausible mechanism for the elevated BFTEs observed for PFMOAA and PFO5DoDA. In relation to health outcomes, this study identified significant positive associations between elevated concentrations of short-chain PFCA and PFECA, particularly PFBA and PFPeA, and the likelihood of DOR in reproductive-aged women. These associations corresponded with declines in AMH levels and AFC. AMH, a glycoprotein hormone secreted by granulosa cells of early stage follicles, regulates the recruitment of primordial follicles and correlates with the number of growing follicles. In AMH-knockout mouse models, younger mice show accelerated recruitment of primordial follicles, while older mice exhibit near-complete depletion of the follicle pool. This hormonal disruption leads to premature follicular exhaustion and causes reduced AFC, eventually manifesting as DOR. These mechanistic insights align with retrospective data showing negative correlations between serum PFBA and PFPeA levels and circulating AMH. Additional support comes from follicular fluid analyses in women undergoing assisted reproduction, where higher PFAS mixtures are reported to be inversely associated with AMH levels. Interestingly, positive correlations were observed between long-chain PFCA/PFECA (PFOA) and PFSA/PFESA (PFHxS). This may reflect enhanced primordial follicle recruitment, followed by accelerated follicular depletion. In contrast, inverse associations between DOR and PFTriDA, PFTeDA, and PFHxS were also observed. It is necessary to emphasize that these associations do not represent protective actions and may instead reflect residual confounding or feedback mechanisms by which ovarian dysfunction alters PFAS metabolism, tissue distribution, or excretion. One study observed that estradiol could regulate the expression of transport proteins, facilitating the entry of PFAS into urine and reducing the serum concentration in ovariectomized female mice. This suggests that hormonal fluctuations in DOR patients may influence the systemic distribution and clearance of PFAS. Meanwhile, the median concentration of PFHxS, PFTeDA and PFTriDA in this study was higher in the control group than in the case group, which may explain the negative association with DOR. Nonetheless, further studies are warranted to elucidate these processes and clarify causality. Given that human exposure typically involves complex mixtures rather than isolated PFAS compounds, this study applied both WQS and BKMR to characterize mixed effects. WQS identified a significant positive association between combined PFAS burden and DOR risk, with BKMR demonstrating a consistent monotonic increase in DOR likelihood across the exposure gradient. A study showed a positive association between PFAS mixtures (PFOA, PFOS, PFHxA, PFDA, PFNA, PFUdA, PFTrDA, LPFHpS, and LPFHxS) and DOR risk. Although the association did not reach statistically significant, the short-chain compound PFHxA exhibited a relatively high cPIP in BKMR model. Accumulating mechanistic evidence indicates that PFAS mixtures may compromise ovarian reserve through multiple interconnected pathways. Activation of peroxisome proliferator-activated receptor signaling disrupts lipid homeostasis, drives abnormal lipid accumulation, and suppresses genes essential for oocyte maturation, collectively diminishing developmental competence. Disruption of gap-junction intercellular communication between oocytes and granulosa cells further interferes with cytoplasmic and metabolic coordination essential for oocyte maturation. Additional studies implicate mitochondrial dysfunction, including inhibition of electron transport chain activity, impaired ovarian oxidative phosphorylation, increased ROS generation, and induction of granulosa cell necroptosis via intrinsic pathways, culminating in follicular atresia and tissue injury. , These potential pathways likely operate synergistically to disrupt oocyte development and maturation, deplete follicular reserves, and ultimately elevate the risk of DOR in reproductive-aged women. In response to increasing regulatory constraints on the production and use of traditional long-chain PFAS, short-chain alternativescharacterized by relatively short half-lives and low bioaccumulation have been rapidly adopted. However, a growing body of toxicological evidence indicates that these replacements pose considerable reproductive risks. For example, PFBS exposure in Caenorhabditis elegans has been shown to induce germ cell apoptosis via ROS elevation, with prenatal exposure leading to reduction of ovarian follicles and corpus luteum in adult offspring. In humans, gestational exposure to PFHxS and PFPeA is associated with higher incidence of small-for-gestational-age (SGA) neonates and accelerated placental senescence. Consistent with these findings, the present study identified PFBA as a principal driver of increased DOR risk. Subchronic exposure of PFBA in zebrafish induces oocyte deformation and follicular atresia and disrupts estrogen homeostasis through direct and indirect targeting of estrogen-related receptor γ at nanomolar concentrations. Simultaneously, high serum PFBA concentrations also correlate with adverse reproductive outcomes, including unexplained recurrent spontaneous abortion (URSA) and increased preterm birth risk. These multidisciplinary data reinforce concerns that short-chain PFCA/PFECA, particularly PFBA, may adversely impact female reproductive health. PCR further delineated heterogeneous exposure-response relationships across individual PFAS. After accounting for multicollinearity, two distinct exposure patterns emerged. PC1 was characterized predominantly by long-chain PFCA/PFECA and PFSA/PFESA (excluding PFBS), whereas PC2 reflected short-chain PFCA/PFECA exposures (excluding PFHpA). Notably, PC2 exhibited strong positive associations with DOR risk and inverse correlations with both AMH and AFC, reinforcing the contribution of short-chain PFCA/PFECA to diminished ovarian reserve after dimensionality reduction analysis. Pearson correlation analysis indicates that PFBS and PFHpA exhibit lower correlations with other PFAS (r = 0.06–0.29 and 0.09–0.20 respectively), suggesting that these compounds have limited correlation between exposure sources and distribution behavior. This finding also explains why PCA identifies them as distinct drivers of PC3 and PC4. To the best of our knowledge, this study represents the first matched case-control investigation to assess associations between DOR and a comprehensive panel of legacy and emerging PFAS, analyzed both as individual compounds and as mixtures. DOR was defined as a binary clinical diagnosis rather than inferred from surrogate biomarkers, enabling improved specificity in outcome classification. Follicular fluid served as the biological matrix, offering a more direct representation of ovarian exposure than serum or plasma. Furthermore, the robustness of the mixed-effects results was confirmed through multiple models. Importantly, both single-compound and mixture analyses identified short-chain PFCA/PFECA as predominant contributors to PFAS accumulation in follicular fluid and principal drivers of mixture effects, providing novel human evidence of their potential reproductive toxicity. However, several study limitations must be acknowledged. The cross-sectional case-control design precludes causal inference, necessitating confirmation through longitudinal and mechanistic studies. Sampling of follicular fluid at a single time point also limits the ability to capture cumulative or cyclical exposure variation. Notably, samples collected on one side cannot represent the exposure on the other side. Although there is no evidence indicating significant distribution differences of PFAS between left and right ovaries, we cannot rule out variations arising from disparities in the degree of local vascularization. Furthermore, the study sample was recruited exclusively from a single reproductive medical center in Shenyang, China, which may limit the generalizability of the research results to other geographical regions, ethnic backgrounds, or populations with different exposure characteristics. Shenyang, as an industrial city in Northeast China, has a different PFAS exposure profile from other regions. Meanwhile, the participants recruited from the reproductive medicine center may differ from the general population in seeking healthy behaviors, lifestyles, or potential causes of infertility, which may introduce selection bias. Although rigorous matching and multivariable adjustment were implemented to control for key confounders, residual confounding cannot be fully excluded. Finally, we need to acknowledge the limitation of sample size. Therefore, future research should combine larger prospective cohorts with toxicological studies to reveal the impact of short-chain and alternative PFCA/PFECA on ovarian function.

Per- and polyfluoroalkyl substances (PFAS) constitute a diverse group of synthetic chemicals extensively deployed across industrial applications and consumer products since the mid-20th century, including firefighting foams, food packaging, textiles, and leather treatment. Among them, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are long-chain representatives that have been persistently detected across environmental compartments. Their widespread occurrence reflects high chemical stability and pronounced bioaccumulation potential, and their toxicological profiles include hepatotoxicity and immunotoxicity, , leading to international regulatory actions. In response to phase-out policies targeting legacy PFAS, the chemical industry has increasingly adopted short-chain analogs and developed structurally modified substitutes, including perfluoroalkyl ether carboxylic acids (PFECA) and perfluoroalkyl ether sulfonic acids (PFESA), which feature ether linkages or hydrogen/chlorine atom substitutions within their backbones. Despite these structural modifications, most alternatives retain environmental persistence and toxicity comparable to those of phased-out legacy compounds and are now frequently detected in various environmental matrices, including soils and surface waters, as well as human biological fluids such as serum and breast milk. Recent mechanistic studies have revealed that exposure to short-chain compounds, such as perfluorobutanoic acid (PFBA), can elicit more pronounced oxidative stress responses than those triggered by PFOA, characterized by increased mitochondrial reactive oxygen species (ROS) generation and robust suppression of antioxidant enzyme activities in neuronal cells. Epidemiological findings have also connected prenatal exposure to perfluorobutanesulfonic acid (PFBS) and perfluoroheptanoic acid (PFHpA) with endocrine disruption, including changes in fetal gonadotropin levels and aberrant free androgen regulation. Collectively, these findings underscore rising concerns over the toxicological equivalency of PFAS alternatives and their potential to exert adverse reproductive and developmental effects. Infertility has emerged as a significant global public health issue, with prevalence estimates ranging from 12.6% to 17.5% and showing a persistent upward trajectory. , Among the principal contributors to female infertility is diminished ovarian reserve (DOR), a condition marked by a progressive loss in both the quantity and developmental competence of oocytes. DOR is broadly categorized into physiological age-related decline and premature pathological depletion, with the latter drawing increasingly clinical focus due to its rising incidence among young reproductive-aged women. Beyond its role in reducing natural fecundity and increasing the risk of recurrent pregnancy loss, , DOR is frequently linked to adverse outcomes in in vitro fertilization (IVF) cycles, including poor ovarian response and elevated risks of obstetric and perinatal complications such as preeclampsia and fetal vascular abnormalities. This trend underscores the need to identify and characterize modifiable risk factors contributing to early ovarian dysfunction. In parallel with established determinants such as chronological age and genetic predisposition, environmental exposure to pollutants has gained increasing recognition as a critical influence on ovarian aging. , Among these, PFAS are a prominent class of endocrine-disrupting chemicals associated with female reproductive toxicity, specifically ovarian dysfunction and folliculogenesis. , Experimental models in mice have demonstrated that chronic PFOS exposure leads to the reduction of histone H3K14 acetylation at the promoter region of the steroidogenic acute regulatory (STAR) promoter, thereby impairing estrogen biosynthesis and disrupting follicular development and ovulation. Similarly, PFOA has been shown to disrupt hormone levels and accelerate follicle growth in a nonmonotonic manner through decreasing steroidogenic gene expression. Epidemiological data further support these mechanistic findings, indicating that elevated PFAS body burdens correlate with altered ovarian reserve markers, including reductions in anti-Müllerian hormone (AMH), lower antral follicle counts (AFC), and altered follicle stimulating hormone (FSH) levels. Together, these findings implicate PFAS exposure as a potential contributor to both the onset and progression of DOR. Nevertheless, current investigations into the relationship between PFAS exposure and DOR remain constrained by several methodological and conceptual gaps. First, most existing studies have focused predominantly on legacy PFAS, while the potential reproductive effects of emerging alternatives have received limited attention. Second, reliance on peripheral blood as the primary biological samples may not adequately capture internal PFAS distributions relevant to ovarian physiology. In contrast, follicular fluidenriched in plasma-derived constituents selectively transported across the follicular barrierrepresents a more proximate and biologically relevant matrix for assessing chemical exposures that may influence oocyte maturation and folliculogenesis. PFAS have been detected in follicular fluid, , suggesting that these substances can cross the barrier and act locally on developing gametes, thereby disturbing ovarian function. Given the reproductive consequences associated with DOR, identifying modifiable environmental determinants has become an urgent public health objective. The present study was designed to address critical gaps by (1) quantifying the transfer efficiencies of legacy and emerging PFAS from plasma to follicular fluid based on paired concentration measurements; (2) evaluating association between individual compounds and PFAS mixtures in follicular fluid and the probability of DOR in a case-control framework matched for age and body mass index (BMI); and (3) investigating correlations between follicular PFAS levels and key clinical indicators of ovarian reserve. By characterizing chemical burdens within the local ovarian microenvironment, this study provides mechanistic and epidemiological evidence linking PFAS exposure to female reproductive dysfunction.