Per- and poly-fluoroalkyl substances (PFASs) in follicular fluid from women experiencing infertility in Australia

Per- and poly -fluoroalkyl substances (PFASs), Perfluorooctane sulfonate (PFOS), Perfluorooctanoic acid (PFOA), Perfluorohexane sulfonate (PFHxS), Perfluorononanoic acid (PFNA), Australia, infertility 2

1 Per- and poly-fluoroalkyl substances (PFASs) have been widely used and detected in human 2 matrices. Evidence that PFAS exposure may be associated with adverse human reproductive 3 health effects exists, however, data is limited. The use of a human matrix such as follicular 4 fluid to determine chemical exposure, along with reproductive data will be used to investigate 5 if there is a relationship between PFAS exposure and human fertility. 6 7

8 This study aims to: (1) assess if associations exist between PFAS concentrations and/or age 9 and fertilisation rate (as determined in follicular fluid of women in Australia who received 10 assisted reproductive treatment (ART) ); and (2) assess if associations exist between PFAS 11 concentrations and infertility aetiology. 12 13

14 Follicular fluids were originally collected from participants who underwent fully stimulated 15 ART treatment cycles at an in vitro fertilisation (IVF) clinic in the period 2006-2009 and 2010-16 11 in Queensland, Australia. The samples were available for analys is of 32 PFASs including 17 perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonate 18 (PFHxS), and perfluorononanoic acid (PFNA) using high performance liquid chromatography 19 tandem mass spectrometry (HPLC -MS/MS). 9 7 samples were matched with limited 20 demographic data (age and fertilisation rate) and five infertility factors (three known female 21 factors): 1) endometriosis, 2) polycystic ovarian syndrome (PCOS), and 3) genital tract 22 infections - tubal/pelvic inflammation disease; as well as 4) male factor, and 5 ) idiopathic or 23 unknown from either males or females. SPSS was used for linear regression analysis. 24 25

26 PFASs were detected in all follicular fluid samples with the mean concentrations of PFOS and 27 PFOA, 4.9, and 2.4 ng/ml, respectively. A lower fertilisation rate was observed at higher age 28 when age was added as a covariate, but there was no relationship between PFAS concentrations 29 and fertilisation rate. There were few statistically significant associations between PFAS 30 concentrations in follicular fluid and infertility factors. Log-transformed PFHxS concentrations 31 were lower in females with endometriosis (factor 1) than in women who had reported ‘ male 32 3 factors’ as a reason of infertility, while PFHpA was higher in women who had infertile due to 1 female factors (factor 1-3) compared to those who had infertile due to male factor. 2 3

PFASs were detected in follicular fluid of Australian women who had been 4 treated at an IVF clinic. PFAS exposure found in follicular fluids is linked to increased risk of 5 some infertility factors, and increased age was associated with decreased fertilisation rate in 6 our data. But there was no relationship between PFAS and ferlitisation rate. Further large-scale 7 investigations of PFAS and health effects including infertility are warranted.8 4 1. Introduction 9 Per- and poly-fluoroalkyl substances (PFASs), are chemicals that have been used widely as 10 surfactants, lubricants, floor waxes, fire -fighting foams, denture cleane rs, shampoos, 11 pharmaceutical products, and in food packaging since the 1950s (Kantiani et al., 2010). The 12 most common exposure route for PFAS is via ingestion, followed by dermal contact and 13 inhalation (Quaak et al., 2016; D’Hollander et al., 2014; Jian et al., 2017). 14 15 Studies have shown potential associations between PFAS exposure and adverse health effects 16 for metabolism, thyroid function, neurodevelopment, cancers, cardiovascular diseases, 17 reproductive functions, and immunity (as reviewed by Kirk et al., 2018) . Kirk et al. (2018) 18 confirmed that while there are increasing numbers of studies investigating the health effects of 19 exposure to PFASs, the results are limited or inconsistent. When looking specifically in terms 20 of reproductive health outcomes, conflicting results have been observed (Fei et al., 2009; Fei 21 et al., 2012; Whitworth et al., 2012; Jorgensen et al., 2014; Velez et al., 2015; Vestergaard et 22 al., 2012; Buck Louis et al., 2013; Bach et al., 2015; Barrett et al., 2015). For example, lower 23 levels of reproductive hormones, such as estradiol and progesterone, were related to higher 24 concentrations of perfluorooctane sulfonate (PFOS), and perfluorooctane sulfonamide 25 (PFOSA) in nulliparous women (women who have never given birth) (Barrett et al., 2015). 26 However, the results were not consistent for other PFASs, including perfluorooctanoic acid 27 (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), 28 perfluoroundecanoic acid (PFUnDA) and perfluorohexane sulphonate (PFHxS) in parous 29 women (women who have given birth) (Barrett et al., 2015). Fei et al. (2009; 2012) found lower 30 fecundability (ability to achieve pregnancy), when comparing higher PFOS (26.1-43.2 ng/mL) 31 to lower PFOS exposure (<26.1 ng/mL) , when stratified by parity. There was an association 32 between PFOS exposure and increased odds of infertility in three higher quartiles of PFOS 33 concentrations when compared with the lowest quartile (Fei et al., 2009). No association was 34 found between PFOS exposure and subfecundability or infertility (Velez et al., 2015; Bach et 35 al., 2015). 36 37 PFASs are known as possible endocrine disrupting chemicals (EDCs) with adverse health 38 effects on the endocrine system ( Stahl et al., 2011; Caserta et al., 201 3; DeWitt 2015). For 39 example, the pituitary gland produces fertility hormones, including follicle stimulating 40 hormones and luteinizing hormone, which are vital for ovulation and successful conception. 41 5 (Stach et al., 2011). Interference by PFASs or other chemicals on the en docrine system may 42 cause reproductive health issues, such as infertility or hormone imbalance in women (Caserta 43 et al., 2013; DeWitt 2015; Kim et al., 2019). 44 45 PFASs are persistent and bioaccumulate with concentrations detected in human samples 46 worldwide (Cho et al., 2015 (South Korea); Stubleski et al., 2016 (Sweden); Whitworth et al., 47 2012 (Norway); Olsen et al., 2017 (USA); Gao et al., 2019 (China)). In Australia, PFAS were 48 detected in human serum samples dating back to 2002 with levels simila r to or higher than in 49 European and Asian countries (Toms et al., 2014). There is recent interest in Australia and 50 worldwide as to whether or not PFAS exposure may be linked to adverse health effects 51 specifically in communities with PFAS exposure through drinking water and in occupationally 52 exposed groups such as firefighters (Rotander et al., 2015). 53 54 Infertility, defined as the inability to conceive after one year of unprotected intercourse, is a 55 global public health issue affecting about 15% of the population (Datta et al., 2016). Female 56 fertility rate, defined as the average number of children born to a woman during her 57 reproductive years, is likely to decrease with increasing age, and/ or an underlying medical 58 condition that might affect ovulation or hormone imbalance, or cause blocked fallopian tubes 59 (Barbieri 2018; Jaward et al., 2018). The most common medical conditions experienced by 60 infertile women are endometriosis, polycystic ovarian syndrome, or pelvic inflammatory 61 disease while poor semen quality is considered the main male cause (Hruska et al., 2000; Piotr 62 et al., 2016; Skakkebaek et al., 2016; Sifakis et al., 2017; Barbieri 2018). 63 64 Human exposure to PFAS can be measur ed by analysis of food/drinking water, and through 65 analysis of human matrices, such as blood serum, urine or breast milk. In this study, PFASs 66 were examined in follicular fluid. This is a liquid in the ovarian follicle, which can be collected 67 when a woman unde rgoes egg harvest during assisted reproductive technology (ART) 68 treatment. Studies have used follicular fluid to measure PFASs, likely due to ease of collection, 69 which is relatively non-invasive if carried out opportunistically (Governini et al., 2011; McCoy 70 et al., 2017; Petro et al., 2014; Heffernan et al., 2018). Despite the determination of PFASs in 71 follicular fluid, current data is limited to conclude whether associations exist between PFAS 72 concentrations and adverse fertility effects. 73 74 6 Therefore, this study aims to assess if associations exist between : (1) PFAS concentrations 75 and/or age and fertilisation rate (as determined in follicular fluid of women in Australia who 76 received ART); and (2) PFAS concentrations and infertility aetiology. 77 78 79 2. Materials and Methods 80 2.1. Sample collection 81 Follicular fluid samples were collected from female participants who underwent fully 82 stimulated ART treatment cycles at an IVF (in vitro fertilisation) clinic in Queensland in the 83 period 2006-2009 and 2010-2011 (as part of the “Asymptomatic upper genital tract infections 84 in infertile couples and assisted reproductive technology outcomes (ART)” and “Prevalent 85 microorganisms detected in the female upper genital tract: the effect of these microorganisms 86 on oocytes and on assisted reproductive technology outcomes” projects (Pelzer et al., 2013)). 87 The samples were obtained when the participants were undergoing egg harvest for IVF as 88 described previously (Pelzer et al., 2013). The data available included date of birth, infertility 89 aetiology, fertilisation rate, and past clinical history of infertility. Study participants had been 90 classified into groups depending on the aetiology of infertility for the couples including: three 91 female factors with 1= endometriosis, 2= polycystic ovarian syndrome (PCOS), 3= genital tract 92 infections (tubal/pelvic inflammation disease) ; 4= male factor (this is infertility due to only 93 male p artners issues, but detailed health information was not given) ; and 5= idiopathic or 94 unknown. Factor 5, idiopathic, means causes of infertility were not identified from either the 95 female or the male. We considered infertility aetiology 1, 2, and 3 as female case groups, and 96 infertility aetiology factor 4 as a control group. Whilst factor 5 was included in the analysis it 97 was not included as either a case group or a control group due to its unknown causes. ART 98 treatment cycle(s) outcomes were also recorded for each couple. It should be noted that the 99 date of sample collection was not supplied, only that the samples were collected between 2006 100 and 2010. In order to calculate an age at date of collection, we have taken a mid-point of 2008 101 and used participant date of birth to calculate an approximate age. 102 103 2.2 Ethics statement 104 We sought and received a waiver of consent to use follicular samples for analysis of PFAS 105 from the Queensland University of Technology (QUT) ethics committee (approval number: 106 7 1800000016) and The University of Queensland Human Research Ethic Committee (approval 107 number: 2018000550). 108 109 2.3 Chemical Analysis for PFASs 110 Analysis of the follicular fluid samples w as undertaken at the Queensland Alliance for 111 Environmental Health Sciences (QAEHS), The University of Queensland. Samples were 112 analyzed for 32 PFASs; perfluorobutanoic acid (PFBA), perfluoropetanoic acid (PFPeA), 113 perfluorohexanoic acid (PFHxA), perfluorohepatanoic acid (PFHpA), perfluorooctanoic acid 114 (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), 115 perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoDA), 116 perfluorotridecanoic acid (PFTrDA), perfluorotetra decanoic acid (PFTeDA), 117 perfluorohexadecanoic acid (PFHxDA), perfluorooctadecanoic acid (PFODA), 118 perfluorobutane sulphonate (PFBS), perfluoropentane sulphonate (PFPeS), perfluorohexane 119 sulphonate (PFHxS), perfluoroheptane sulphonate (PFHpS), perfluorooctane sulfonate (PFOS), 120 perfluorononane sulfonate (PFNS), perfluordecane sulphonate (PFDS), perfluordodecane 121 sulphonate (PFDoDS) , sodium 1H,1H,2H,2H -perfluorohexane sulfonate (4:2) (8:2 FTS), 122 sodium 1H,1H,2H,2H -perfluorohexane sulfonate (4:2) (4:2 FTS), Sodium 1H,1H,2H,2H -123 perfluorooctane sulfonate (6:2) (6:2 FTS), sodium 1H,1H,2H,2H -perfluorodecane sulfonate 124 (8:2) (8:2 FTS), perfluoroethylcyclohexane sulfonate (PFECHS), perfluoro-1-octane 125 sulfonamide (FOSA), n-ethylperfluoro-1-octane sulfonamidoacetic acid (NEtFOSAA), n-126 methylperfluoro-1-octane sulfonamidoacetic acid (NMeFOSAA), n-methylperfluoro-1-octane 127 sulfonamide (NMeFOSA), n-ethylperfluoro-1-octane sulfonamide (NEtFOSA), 2 -(N-128 methylperfluoro-1-octane sulfonamido)-ethanol (NMe FOSE), 2 -(N-ethylperfluoro-1-octane 129 sulfonamido)-ethanol (NEt FOSE) (Supplementary information Table S1). A 200 μl aliquot of 130 follicular fluid was transferred to a 2 ml Eppendorf tube, followed by addition of the internal 131 standards. Proteins were precipitated with acetonitrile , centrifuged, filtered (2 μm GHP 132 membrane; Pall, East Hills, NY, USA), and concentrated to 200µl under a gentle stream of 133 nitrogen. Samples were reconstitut ed to 500µl with 5 mM ammonium acetate in water and 134 spiked with recovery standards prior to analysis via high performance liquid chromatography 135 tandem mass spectrometry (HPLC -MS/MS) using a Nexera HPLC (Shimadzu Corp., Kyoto, 136 Japan) coupled to a Triple Quad 6500+ mass spectrometer (Sciex, Melbourne, Australia) with 137 electrospray ionizati on (ESI) in terface operating in negative mode. Chromatographic 138 separation of the analyt es was achieved with a Gemini C18 column (50 x 2.0 mm, 4 μm; 139 8 Phenomenex, Torrance, CA), maintained at 45°C, with a flow rate of 0.3 mL/min and injection 140 volume of 5 μL. Mobile phases consisted of methanol water (1:99, v/v) (A), and methanol: 141 water (95:5, v/v) (B), with 5mM ammonium acetate in both phases. An isolator column 142 (Phenomenex) was included inline directly after the mobile phase mixing chamber to delay 143 elution of solvent-derived background PFASs contamination. Data acquisition and processing 144 was carried out using analyst® TF 1.6 and MultiQuantTM software (Sciex). If the PFASs were 145 detected in less than 60% of samples, they were excluded from statistical analysis (eg: PFBA, 146 and PFDoDA, 38.4% and 4% respectively) . Linear PFAS congeners were determined for the 147 current study. 148 149 Quality control 150 Laboratory blanks (MilliQ water) were extracte d and analyzed in parallel with each batch of 151 samples. Batches included inter-batch replicates which generally showed CV < 15%. T he 152

limit of quantification (LOQ) was calculated by multiplying the SD obtained from 153 injecting the lowest calibration standard seven times by 10. Percentage average recovery 154 ranged from 70 to 110%. 155 156 2.4 Data analysis 157 Descriptive statistics were calculated to summarize overall cohort characteristics and PFAS 158 concentrations in follicular fluid samples. Evidence of associations between PFAS 159 concentrations and fertility variables were evaluated using linear modelling. A linear regression 160 model was fitted to examine the inf luence of PFAS concentrations and age on expected 161 fertilisation rates, which was defined as number of oocytes fertilized by ART. This model 162 specified fertilisation rate as the dependent variable, with participant age and individual PFAS 163 concentrations incl uded as continuous independent variables. To assess whether PFAS 164 concentrations varied by aetiology infertility factors, a one-way analysis of variance (ANOVA) 165 was fitted, with log-transformed concentrations as the dependent variable, and aetiology factor 166 as a categorical independent variable. Our decision to apply a log transformation was informed 167 by findings of preliminary analysis to satisfy residual assumptions. Linear modelling outcomes 168 were summarized by parameter estimates and corresponding 95% confidence intervals. 169 Hypothesis testing of estimates was conducted to determine if associations were statistically 170 significant, assuming a significance level of 0.05. All statistical analyses were undertaken i n 171 SPSS version 25. 172 9 173 174 3. Results 175 The mean age of female participants w as 35 years, and the mean fertilisation rate was 63% 176 (Table 1). Most common aetiology factors of females participating in ART treatment in this 177 study was ‘idiopathic (24.7%)’, and male partner’s factors of infertility (22.7%)’ (Table 1). In 178 total, 97 follicular samples matched with demographic information were analysed for 32 179 PFASs. 8 PFASs were detected in most samples (PFOS, PFOA, PFHxS, PFNA, PFDA, PFHpS, 180 PFUnDA, and PFHpA) and were included in further analysis. The concentrations from highest 181 to lowest were: PFOS (Mean = 4.8; Range = 0.7 to 22.4 ng/ml), PFOA (2.4; 0.3 to 14.5 ng/ml), 182 PFHxS (1.7; 0.2 to 21.3 ng/ml), PFNA (0.5; 0.08 to 2.0 ng/ml), PFDA (0.2; 0.05 to 0.9 ng/ml), 183 PFHpS (0.1; 0.05 to 1.1 ng/ml), PFUnDA (0.1; <LOD to 0.4 ng/ml), and PFHpA (0.01; <LOD 184 to 0.6 ng/ml) (Table 2). The remaining 24 PFASs were detected in a small number of samples 185 or at <LOD), thus they were not discussed further, details are available in the SI. 186 187 188 Table 1. Characteristics and fertility outcomes of participating women for ART (N=97) 189 Variable Mean (SD); Range Age (years) 35 (4); 23 to 42 Fertilisation rate (%) 63 (22); 20 to 100 Aetiology of infertility n (%) of 97 participants Endometriosis (factor 1) 18 (18.6) Polycystic ovarian syndrome (factor 2) 18 (18.6) Genital tract infections (factor 3) 15 (15.5) Male factors of infertility (factor 4) 22 (22.7) Idiopathic (factor 5) 24 (24.7) SD: standard deviation 190 191 192 Table 2. Descriptive data of 8 PFASs in follicular fluids (97 demographic information 193 matched samples) 194 10 LOD: Limit of detection 195 196 3.1. PFAS concentrations, and fertilisation rate and age 197 Fertilisation rate is defined as the number of oocytes fertilized by ART divided by the total 198 number of oocytes collected. Information was available for 92 samples (5 missing data points). 199 It was found that age was negatively associated with expected fertilisation rate (Estimate = -200 1.49, 95%CI: -2.64 to -0.35; p = 0.013). Inconsistent results were observed in the relationship 201 between fertilisation rate, age and PFAS concentrations. The concentration of selected PFASs 202 in follicu lar fluid was positively ( eg; PFHpA, PFOA, PFUnDA) or negatively ( eg; PFDA, 203 PFHpS) associated with fertilisation rate, however high levels of uncertainty in parameter 204 estimates meant that none of these associations were statistically significant (Table 3). 205 206 Table 3. Associations between PFAS concentrations and fertilisation rate and age CI 207 (Confidence interval) 208 Variables Estimate 95% CI Test statistic p-value Age -1.49 -2.64 to -0.35 -2.609 0.013 PFOS 2.279 -0.556 to 5.114 1.599 0.114 PFHxS 0.692 -0.855 to 2.239 0.890 0.376 PFHpS -48.371 -111.980 to 15.238 -1.512 0.134 PFOA 0.706 -2.219 to 3.631 0.480 0.633 PFNA 15.647 -18.849 to 50.143 0.902 0.370 ng/ml Detection frequency (%) Minimum Maximum Mean SD PFOS 98 0.7 22.4 4.8 3.1 PFHxS 98 0.2 21.3 1.7 2.7 PFHpS 96 0.05 1.1 0.1 0.1 PFOA 98 0.3 14.5 2.4 1.7 PFNA 97 0.08 2.0 0.5 0.3 PFDA 98 0.05 0.9 0.2 < LOD PFHpA 90 < LOD 0.6 0.01 0.008 PFUnDA 97 < LOD 0.4 0.1 0.007 11 PFDA -60.830 -129.250 to 7.590 -1.768 0.081 PFHpA 17.390 -65.276 to 100.055 0.418 0.677 PFUnDA 73.581 -3.413 to 150.574 1.900 0.061 209 210 3.2. PFAS concentrations and infertility by aetiology factors 211 Analysis of PFAS concentrations by aetiology factor provided mixed results, with statistically 212 significant differences observed for PFHpA (test statistic = 2.4; p -value = 0.04) and PFHxS 213 (test statistic = 4.7; p -value = 0.002) (Table 4). For PFHxS, average log transformed 214 concentrations were seen to be lowest for endometriosis (Mean = -0.3; SE = 0.1) and highest 215 for polycystic ovarian syndrome (Mean = 0.3; SE = 0.1). For PFHpA, average concentrations 216 were observed to be lowest for male-related infertility (Mean =-1.5; SE = 0.1) and highest 217 genital tract infections and idiopathic factors (Mean = -1.2; SE = 0.1) (Table 4). 218 219 Table 4. Association between PFAS concentrations and infertility by 5 aetiology factors. 220 Summary statistics are presented for log -transformed concentrations. SE: Standard 221 error. 222 PFAS (log transformed ng/ml) Mean (SE) Aetiology factor 1 Endometriosis Aetiology factor 2 Polycystic ovarian syndrome Aetiology factor 3 Genital tract infections Aetiology factor 4 Male factors of infertility Aetiology factor 5 Idiopathic Test statistic (p- value) PFOS 0.6 (0.04) 0.7 (0.1) 0.5 (0.04) 0.6 (0.03) 0.5 (0.06) 2.8 (0.26) PFHxS -0.3 (0.1) 0.3 (0.1) 0.02 (0.04) 0.01 (0.03) -0.02 (0.1) 4.7 (0.002) PFHpS -0.8 (0.04) -0.7 (0.06) -0.9 (0.04) -0.8 (0.03) -0.9 (0.05) 3.12 (0.15) PFOA 0.3 (0.1) 0.4 (0.1) 0.2 (0.1) 0.3 (0.03) 0.3 (0.04) 1.7 (0.15) PFNA -0.3 (0.1) -0.3 (0.1) -0.3 (0.1) -0.3 (0.02) -0.3 (0.02) 0.21 (0.93) PFDA -0.7 (0.1) -0.8 (0.1) -0.6 (0.1) -0.7 (0.03) -0.7 (0.04) 0.11 (0.97) 12 PFHpA -1.4 (0.1) -1.3 (0.1) -1.2 (0.1) -1.5 (0.1) -1.2 (0.1) 2.4 (0.04) PFUnDA -1.04 (0.7) -0.9 (0.1) -0.9 (0.1) -0.9 (0.03) -0.9 (0.04) 0.64 (0.63) 223 224 4. Discussion 225 In this study, PFASs were detected in follicular fluid in women experiencing infertility . We 226 observed association between PFAS, such as PFHpA, or PFHxS, and the 5 aetiology factors of 227 infertility. From the limited studies investigating follicular fluid and fertility effects, McCoy et 228 al. (2017 ) found no significant associations between ovarian response measures and PFAS 229 concentrations, and also found decreased blastocyst conversion rate in follicular fluid exposed 230 to perflurononanoic acid (PFNA), and perfluorodecanoic acid (PFDA). Heffernan et al. (2018) 231 conducted a study using serum and follicular fluid of women with and without polycystic 232 ovarian syndrome (PCOS) undergoing fertility treatment and found higher serum PFOS 233 concentrations in PCOS cases than controls , and in women with irregular menstrual cycles 234 compared to women with regular menstrual cycles. Governini et al. (2011) reported that PFASs 235 were present in human follicular fluid and suggested PFAS concentrations had a potentially 236 detrimental effect on oocyte fe rtilisation capacity but the sample size was limited (n=16). 237 Higher levels of PFNA have also been associated with increased risk of infertility in women 238 (Jorgensen et al., 2014). While in another study, the presence of higher PFASs in human 239 follicular fluid (a linear combination of PFOA, PFOS, PFNS and PFHxS) had a higher chance 240 of an oocyte developing into a high-quality embryo (Petro et al., 2014). 241 242 Associations were found between PFHxS, and PFHpA, and 5 aetiology factors of infertility. 243 Epidemiological studies have reported an association between PFASs, and infertility caused by 244 endometriosis (Vagi et al., 2014; Campbell et al., 2016; Wang et al., 2017). In Chinese females 245 seeking ART treatment due to endometriosis, plasma levels of perfluorobutane sulfonic acid 246 (PFBS), which were excluded in this current study due to low detection rate, was related to an 247 increased risk of infertility (Wang et al., 2017). In the United States of America, women with 248 endometriosis had higher levels of PFNA, PFOA and PFOS (Campbell et al., 2016). There was 249 also evidence of a relationship between PCOS and PFASs exposure. Vagi et al. (2014) reported 250 higher serum levels of PFOA and PFOS in females with PCOS compared to females with no 251 PCOS. Although incidence of genital tract infections in both females and males is related to 252 13 risk of infertility, the effects of PFAS exposure on genital tract infections have not been well 253 understood (Pellati et al., 2008). Further epidemiology studies are needed to identify if these 254 disease-causing infertilities are associated with PFAS exposure. 255 256 In the current study, we used individual samples of follicular fluid, and were therefore able to 257 measure the range of PFAS concentrations (minimum to maximum) from individual persons. 258 This is advantageous as the body of exposure data on PFAS in Australia uses pooled blood 259 serum data which has the limitation of not being able to identify extreme concentrations, but 260 rather provides a mean of the concentrations of the individuals in that pool (Toms et al., 2019). 261 Individual’s serum samples have been analysed for PFASs in pregnant women from Western 262 Australia (Callan et al., 2016), community residents ( Bräunig et al., 2017), and workers 263 exposed to PFASs (Rotander et al., 2015) in Australia . In the current study, we were able to 264 calculate the inter quartile range (IQR) for PFASs in Australia which showed little variation in 265 concentrations among the 97 women . This little variation was also observed in 98 pregnant 266 women in the Western Australian study by Callen et al. (2016) (PFOS 0.45 to 8.1 µg/L, PFHxS 267 0.06 to 3.3 µg/L, PFOA 0.21 to 3.1 µg/L). PFOS, PFOA, and PFHxS were detected at the 268 highest concentrations in the follicular fluid as has been seen in human serum in Australia 269 (Toms et al., 2009). This finding is consistent with follicular fluid studies from Belgium (Petro 270 et al., 2014), the United States of America (McCoy et al., 2017), and the United Kingdom 271 (Heffernan et al., 2018). 272 273 In terms of age effects on PFASs, there were no trends in any of the PFAS concentrations by 274 age. As is expected from samples from females of child -bearing age, the age range is 275 reasonably narrow making the assessment of trends difficult. Age trends have been identified 276 in previous studies of Australian serum coveri ng the full lifecycle where different PFAS 277 concentrations varied with age (Toms et al., 2019). We found decreased fertilisation rate in 278 follicular fluids is related to increased age, confirming accepted evidence that fertilisation rate 279 decreases with age (Barbieri 2018). 280 281 282

283 Limited demographic information available on participants and a small sample size limited the 284 interpretation of this dataset. Another limitation arose from simplifying causes of infertility to 285 14 five infertility aetiology factors, as human infertility is influenced by various factors, not only 286 physiologically, or pathogenically, but also environmentally. Thus, considering specific 287 diseases relating to male factors or other causes would be beneficial in future studies. 288 289 290 4. Conclusion 291 292 In conclusion, we identified PFAS in follicular fluid of Australian women who had been treated 293 at an IVF clinic. PFOS, PFOA, and PFHxS were detected in the highest concentrations in the 294 follicular fluids . Increased age was associated with decreased fertilisation rate in our data. 295 There were significant differences in PFAS concentrations between female infertility factors 296 and the control group that showed links between PFAS exposures and increased risk of 297 infertility factors. Further studies are needed to investigate the relationship between PFAS 298 levels and health effects including human infertility. 299 300

301 YR is funded by a Postgraduate research scholarship from Queensland University of 302 Technology. 303 304 Conflict of Interests 305 The authors declare that there is no conflict of interests regarding the publication of this paper. 306 307 308 309 310 311 312 313 314 315 316 317 318 15 319 320

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