Information Requirements under the Essential-Use Concept: PFAS Case Studies.

Per- and polyfluoroalkyl substances (PFAS) are a class of substances for which there are widespread concerns about their extreme persistence in combination with toxic effects. It has been argued that PFAS should only be employed in those uses that are necessary for health or safety or are critical for the functioning of society and where no alternatives are available ("essential-use concept"). Implementing the essential-use concept requires a sufficient understanding of the current uses of PFAS and of the availability, suitability, and hazardous properties of alternatives. To illustrate the information requirements under the essential-use concept, we investigate seven different PFAS uses, three in consumer products and four industrial applications. We investigate how much information is available on the types and functions of PFAS in these uses, how much information is available on alternatives, their performance and hazardous properties and, finally, whether this information is sufficient as a basis for deciding on the essentiality of a PFAS use. The results show (i) the uses of PFAS are highly diverse and information on alternatives is often limited or lacking; (ii) PFAS in consumer products often are relatively easy to replace; (iii) PFAS uses in industrial processes can be highly complex and a thorough evaluation of the technical function of each PFAS and of the suitability of alternatives is needed; (iv) more coordination among PFAS manufacturers, manufacturers of alternatives to PFAS, users of these materials, government authorities, and other stakeholders is needed to make the process of phasing out PFAS more transparent and coherent.

Bayesian Refinement of the Permeability-Limited Physiologically Based Pharmacokinetic Model for Perfluorooctanoic Acid in Male Rats.

Physiologically based pharmacokinetic (PBPK) modeling is a powerful technique to inform risk assessment of xenobiotic substances such as perfluorooctanoic acid (PFOA). In our previous study, a permeability-limited PBPK model was developed to simulate the toxicokinetics and tissue distribution of PFOA in male rats. However, due to limited information on some key model parameters (e.g., protein binding and active transport rates), the uncertainty of the permeability-limited PBPK model was quite high. To address this issue, a hierarchical Bayesian analysis with Markov chain Monte Carlo (MCMC) was applied to reduce the uncertainty of parameters and improve the performance of the PBPK model. With the optimized posterior parameters, the PBPK model was evaluated by comparing its prediction with experimental data from three different studies. The results show that the uncertainties of the posterior model parameters were reduced substantially. In addition, most of the PBPK model predictions were improved: with the posterior parameters, most of the predicted plasma toxicokinetics (e.g., half-life) and tissue distribution fell well within a factor of 2.0 of the experimental data. Finally, the Bayesian framework could provide insights into the molecular mechanisms driving PFOA toxicokinetics: PFOA-protein binding, membrane permeability, and active transport.

A Classification Model to Identify Direct-Acting Mutagenic Polycyclic Aromatic Hydrocarbon Transformation Products.

Polycyclic aromatic hydrocarbons (PAHs) are a complex group of environmental contaminants, many having long environmental half-lives. As these compounds degrade, the changes in their structure can result in a substantial increase in mutagenicity compared to the parent compound. Over time, each individual PAH can potentially degrade into several thousand unique transformation products, creating a complex, constantly evolving set of intermediates. Microbial degradation is the primary mechanism of their transformation and ultimate removal from the environment, and this process can result in mutagenic activation similar to the metabolic activation that can occur in multicellular organisms. The diversity of the potential intermediate structures in PAH-contaminated environments renders hazard assessment difficult for both remediation professionals and regulators. A mixture of structural and energetic descriptors has proven effective in existing studies for classifying which PAH transformation products will be mutagenic. However, most existing studies of environmental PAH mutagens primarily focus on nitrogenated derivatives, which are prevalent in the atmosphere and not as relevant in soil. Additionally, PAH products commonly found in the environment can range from as large as five rings to as small as a single ring, requiring a broadly inclusive methodology to comprehensively evaluate mutagenic potential. We developed a combination of supervised and unsupervised machine learning methods to predict environmentally induced PAH mutagenicity with improved performance over currently available tools. K-means clustering with principal component analysis allows us to identify molecular clusters that we hypothesize to have similar mechanisms of action. Recursive feature elimination identifies the most influential descriptors. The cluster-specific regression outperforms available classifiers in predicting direct-acting mutagens resulting from the microbial biodegradation of PAHs and provides direction for future studies evaluating the environmental hazards resulting from PAH biodegradation.

A pathway level analysis of PFAS exposure and risk of gestational diabetes mellitus.

Per- and polyfluoroalkyl substances (PFAS) have been found to be associated with gestational diabetes mellitus (GDM) development, a maternal health disorder in pregnancy with negative effects that can extend beyond pregnancy. Studies that report on this association are difficult to summarize due to weak associations and wide confidence intervals. One way to advance this field is to sharpen the biologic theory on a causal pathway behind this association, and to measure it directly by way of molecular biomarkers. The aim of this review is to summarize the literature that supports a novel pathway between PFAS exposure and GDM development. Epidemiological studies demonstrate a clear association of biomarkers of thyroid hormones and glucose metabolism with GDM development. We report biologic plausibility and epidemiologic evidence that PFAS dysregulation of maternal thyroid hormones and thyrotropin (TSH) may disrupt glucose homeostasis, increasing the risk of GDM. Overall, epidemiological studies demonstrate that PFAS were positively associated with TSH and negatively with triiodothyronine (T3) and thyroxine (T4). PFAS were generally positively associated with glucose and insulin levels in pregnancy. We propose dysregulation of thyroid function and glucose metabolism may be a critical and missing component in the accurate estimation of PFAS on the risk of GDM.

Network Analysis for Prioritizing Biodegradation Metabolites of Polycyclic Aromatic Hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) are a diverse group of environmental contaminants released during the combustion of organic materials and the production and utilization of fossil fuels. Once released, PAHs deposit in soil and water bodies where they are subjected to environmental transport and transformations. As they degrade, intermediate transformation products may play an important role in their environmental impact. However, studying the effects of these degradation products has proven challenging because of the complexity, transience, and low concentration of many intermediates. Herein, a novel integration of a pathway prediction system and network theory was developed and applied to a set of four PAHs to demonstrate a possible solution to this challenge. Network analysis techniques were employed to refine the thousands of potential outputs and elucidate compounds of interest. Using these tools, we determined correlations between PAH degradation network data and intermediate metabolite structures, gaining information about the chemical characteristics of compounds based on their placement within the degradation network. Upon applying our developed filtering algorithm, we are able to predict up to 48% of the most common transformation products identified in a comprehensive empirical literature review. Additionally, our integrated approach uncovers potential metabolites which connect those found by past empirical studies but are currently undetected, thereby filling in the gaps of information in PAH degradation pathways.

Are Fluoropolymers Really of Low Concern for Human and Environmental Health and Separate from Other PFAS?

Fluoropolymers are a group of polymers within the class of per- and polyfluoroalkyl substances (PFAS). The objective of this analysis is to evaluate the evidence regarding the environmental and human health impacts of fluoropolymers throughout their life cycle(s). Production of some fluoropolymers is intimately linked to the use and emissions of legacy and novel PFAS as polymer processing aids. There are serious concerns regarding the toxicity and adverse effects of fluorinated processing aids on humans and the environment. A variety of other PFAS, including monomers and oligomers, are emitted during the production, processing, use, and end-of-life treatment of fluoropolymers. There are further concerns regarding the safe disposal of fluoropolymers and their associated products and articles at the end of their life cycle. While recycling and reuse of fluoropolymers is performed on some industrial waste, there are only limited options for their recycling from consumer articles. The evidence reviewed in this analysis does not find a scientific rationale for concluding that fluoropolymers are of low concern for environmental and human health. Given fluoropolymers' extreme persistence; emissions associated with their production, use, and disposal; and a high likelihood for human exposure to PFAS, their production and uses should be curtailed except in cases of essential uses.

Nontarget Screening of Per- and Polyfluoroalkyl Substances Binding to Human Liver Fatty Acid Binding Protein.

More than 1000 per- and polyfluoroalkyl substances (PFASs) have been discovered by nontarget analysis (NTA), but their prioritization for health concerns is challenging. We developed a method by incorporating size-exclusion column co-elution (SECC) and NTA, to screen PFASs binding to human liver fatty acid binding protein (hL-FABP). Of 74 PFASs assessed, 20 were identified as hL-FABP ligands in which eight of them have high binding affinities. Increased PFAS binding affinities correlate with stronger responses in electrospray ionization (ESI-) and longer retention times on a C18 column. This is well explained by a mechanistic model, which revealed that both polar and hydrophobic interactions are crucial for binding affinities. Encouraged by this, we then developed an SECC method to identify hL-FABP ligands, and all eight high-affinity ligands were selectively captured from 74 PFASs. The method was further applied to an aqueous film-forming foam (AFFF) product in which 31 new hL-FABP ligands were identified. Suspect and nontargeted screening revealed these ligands as analogues of perfluorosulfonic acids and homologues of alkyl ether sulfates (C8- and C10/EOn, C8H17(C2H4O)nSO4-, and C10H21(C2H4O)nSO4-). The SECC method was then applied to AFFF-contaminated surface waters. In addition to perfluorooctanesulfonic acid and perfluorohexanesulfonic acid, eight other AFFF chemicals were discovered as novel ligands, including four C14- and C15/EOn. This study implemented a high-throughput method to prioritize PFASs and revealed the existence of many previously unknown hL-FABP ligands.

Using Machine Learning to Classify Bioactivity for 3486 Per- and Polyfluoroalkyl Substances (PFASs) from the OECD List.

A recent OECD report estimated that more than 4000 per- and polyfluorinated alkyl substances (PFASs) have been produced and used in a broad range of industrial and consumer applications. However, little is known about the potential hazards (e.g., bioactivity, bioaccumulation, and toxicity) of most PFASs. Here, we built machine-learning-based quantitative structure-activity relationship (QSAR) models to predict the bioactivity of those PFASs. By examining a number of available molecular data sets, we constructed the first PFAS-specific database that contains the bioactivity information on 1012 PFASs for 26 bioassays. On the basis of the collected PFAS data set, we trained 5 different machine learning models that cover a variety of conventional models (e.g., random forest and multitask neural network (MNN)) and advanced graph-based models (e.g., graph convolutional network). Those models were evaluated based on the validation data set. Both MNN and graph-based models demonstrated the best performance. The average of the best area-under-the-curve score for each bioassay is 0.916. For predictions on the OECD list, most of the biologically active PFASs have perfluoroalkyl chain lengths less than 12 and are categorized into fluorotelomer-related compounds and perfluoroalkyl acids and their precursors.

Predicting Relative Protein Affinity of Novel Per- and Polyfluoroalkyl Substances (PFASs) by An Efficient Molecular Dynamics Approach.

With the phasing out of long-chain per- and polyfluoroalkyl substances (PFASs), production of a wide variety of alternative PFASs has increased to meet market demand. However, little is known about the bioaccumulation potential of these replacement compounds. Here, we developed a modeling workflow that combines molecular docking and molecular dynamics simulation techniques to estimate the relative binding affinity of a total of 15 legacy and replacement PFASs for human and rat liver-type fatty acid binding protein (hLFABP and rLFABP). The predicted results were compared with experimental data extracted from three different studies. There was good correlation between predicted free energies of binding and measured binding affinities, with correlation coefficients of 0.97, 0.79, and 0.96, respectively. With respect to replacement PFASs, our results suggest that EEA and ADONA are at least as strongly bound to rLFABP as perfluoroheptanoic acid (PFHpA), and as strongly bound to hLFABP as perfluorooctanoic acid (PFOA). For F-53 and F-53B, both have similar or stronger binding affinities than perfluorooctanesulfonate (PFOS). Given that interactions of PFASs with proteins (e.g., LFABPs) are important determinants of bioaccumulation potential in organisms, these alternatives could be as bioaccumulative as legacy PFASs, and are therefore not necessarily safer alternatives to long-chain PFASs.

Polybrominated Diphenyl Ether (PBDE) Accumulation in Farmed Salmon Evaluated Using a Dynamic Sea-Cage Production Model.

Food is an important source of human exposure to hazardous chemicals. Chemical concentration in a food item depends on local environmental contamination, production conditions, and, for animal-derived foods, on feed. Here, we investigate these influences on the accumulation of individual polybrominated diphenyl ether congeners (PBDEs) in farmed Atlantic salmon ( Salmo salar). We develop a dynamic model over a full sea-cage salmon production cycle. To assess the influence of metabolic debromination on PBDE congener profiles, in vitro measurements of debromination rates in fish liver cells were extrapolated to whole-body metabolic rate constants. Model results indicate that the dominant factors governing PBDE concentration in Atlantic salmon fillet are uptake via contaminated feed and fish growth, whereas the influence of metabolic debromination is minor. PBDE concentrations in fish feed depend on several factors, including the geographic origin of fish feed ingredients, which are produced and traded globally. Human exposure to PBDE via salmon consumption is less influenced by environmental concentrations at the location of salmon farming than by environmental concentrations influencing feed components. This dependence of PBDE concentrations in salmon on the origin and composition of feed reveals the complexity of predicting contaminant concentrations in globally traded food.

A Permeability-Limited Physiologically Based Pharmacokinetic (PBPK) Model for Perfluorooctanoic acid (PFOA) in Male Rats.

Physiologically based pharmacokinetic (PBPK) modeling is a powerful in silico tool that can be used to simulate the toxicokinetics and tissue distribution of xenobiotic substances, such as perfluorooctanoic acid (PFOA), in organisms. However, most existing PBPK models have been based on the flow-limited assumption and largely rely on in vivo data for parametrization. In this study, we propose a permeability-limited PBPK model to estimate the toxicokinetics and tissue distribution of PFOA in male rats. Our model considers the cellular uptake and efflux of PFOA via both passive diffusion and transport facilitated by various membrane transporters, association with serum albumin in circulatory and extracellular spaces, and association with intracellular proteins in liver and kidney. Model performance is assessed using seven experimental data sets extracted from three different studies. Comparing model predictions with these experimental data, our model successfully predicts the toxicokinetics and tissue distribution of PFOA in rats following exposure via both IV and oral routes. More importantly, rather than requiring in vivo data fitting, all PFOA-related parameters were obtained from in vitro assays. Our model thus provides an effective framework to test in vitro-in vivo extrapolation and holds great promise for predicting toxicokinetics of per- and polyfluorinated alkyl substances in humans.

Exploring the Use of Molecular Docking to Identify Bioaccumulative Perfluorinated Alkyl Acids (PFAAs).

Methods to predict the bioaccumulation potential of per- and polyfluorinated alkyl substances (PFAS) are sorely needed, given the proliferation of these substances and lack of data on their properties and behavior. Here, we test whether molecular docking, a technique where interactions between proteins and ligands are simulated to predict both bound conformation and interaction affinity, can be used to predict PFAS binding strength and biological half-life. We show that an easy-to-implement docking program, Autodock Vina, can successfully redock perfluorooctanesulfonate (PFOS) to human serum albumin with deviations smaller than 2 Å. Furthermore, predicted binding strengths largely fall within one standard deviation of measured values for perfluorinated alkyl acids (PFAAs). Correlations with half-lives suggest both membrane partitioning and protein interactions are important, and that serum albumin is only one of a number of proteins controlling the fate of these chemicals in organisms. However, few data are available for validation of our approach as a broad screening tool, and available data are highly variable. We therefore call for collection of new data, particularly including proteins other than serum albumin and substances beyond perfluorooctanoic acid (PFOA) and PFOS. The methods we discuss in this work can serve as a framework for guiding such data collection.

Bioaccumulation of perfluorinated alkyl acids: observations and models.

In this review, we consider the two prevailing hypotheses for the mechanisms that control the bioaccumulation of perfluorinated alkyl acids (PFAAs). The first assumes that partitioning to membrane phospholipids, which have a higher affinity for charged species than neutral storage lipids, can explain the high bioaccumulation potential of these compounds. The second assumes that interactions with proteins--including serum albumin, liver fatty acid binding proteins (L-FABP), and organic anion transporters--determine the distribution, accumulation and half-lives of PFAAs. We consider three unique phenomena to evaluate the two models: (1) observed patterns of tissue distribution in the laboratory and field, (2) the relationship between perfluorinated chain length and bioaccumulation, and (3) species- and gender-specific variation in elimination half-lives. Through investigation of these three characteristics of PFAA bioaccumulation, we show the strengths and weaknesses of the two modeling approaches. We conclude that the models need not be mutually exclusive, but that protein interactions are needed to explain some important features of PFAA bioaccumulation. Although open questions remain, further research should include perfluorinated alkyl substances (PFASs) beyond the long-chain PFAAs, as these substances are being phased out and replaced by a wide variety of PFASs with largely unknown properties and bioaccumulation behavior.

Socio-economic analysis for the authorisation of chemicals under REACH: a case of very high concern?

Under the European chemicals' legislation, REACH, substances that are identified to be of "very high concern" will de facto be removed from the market unless the European Commission grants authorisations permitting specific uses. Companies who apply for an authorisation without demonstrating "adequate control" of the risks have to show by means of a socio-economic analysis (SEA) that positive impacts of use outweigh negative impacts for human health and ecosystems. This paper identifies core challenges where further in-depth guidance is urgently required in order to ensure that a SEA can deliver meaningful results and that it can effectively support decision-making on authorisation. In particular, we emphasise the need (i) to better guide the selection of tools for impact assessment, (ii) to explicitly account for stock pollution effects in impact assessments for persistent and very persistent chemicals, (iii) to define suitable impact indicators for PBT/vPvB chemicals given the lack of reliable information about safe concentration levels, (iv) to guide how impacts can be transformed into values for decision-making, and (v) to provide a well-balanced discussion of discounting of long-term impacts of chemicals.

Characterization of per- and polyfluoroalkyl substances (PFAS) concentrations in a community-based sample of infants from Samoa.

Per- and polyfluoroalkyl substances (PFAS) are persistent contaminants with documented harmful health effects. Despite increasing research, little attention has been given to studying PFAS contamination in low- and middle-income countries, including Samoa. Using data and biosamples collected through the Foafoaga o le Ola ("Beginning of Life") Study, which recruited a sample of mothers and infants from Samoa, we conducted an exploratory study to describe concentrations of 40 PFAS analytes in infant cord blood collected at birth (n = 66) and infant dried blood spots (DBS) collected at 4 months post-birth (n = 50). Of the 40 PFAS analytes tested, 19 were detected in cord blood, with 10 detected in >50% of samples (PFBA, PFPeA, PFOA, PFNA, PFDA, PFUnA, PFTrDA, PFHxS, PFOS, and 9Cl-PF3ONS); and 12 analytes were detected in DBS, with 3 detected in >50% of samples (PFBA, PFHxS, and PFOS). PFAS concentrations were generally lower than those reported in existing literature, with the exception of PFHxS, which was detected at higher concentrations. In cord blood, we noted suggestive (p < 0.05) or significant (p < 0.006) associations between higher PFHxS and male sex; higher PFPeA and residence in Northwest 'Upolu (NWU) compared to the Apia Urban Area (AUA); lower PFUnA and 9Cl-PF3ONS and greater socioeconomic resources; lower PFOA and higher parity; higher PFDA and higher maternal age; and lower PFUnA, PFTrDA, and 9Cl-PF3ONS and higher maternal BMI. In DBS, we found suggestive (p < 0.05) or significant (p < 0.025) associations between lower PFBA and residence in NWU versus AUA; lower PFBA and PFHxS and higher maternal age; and higher PFBA and higher maternal BMI. Finally, we observed associations between nutrition source at 4 months and DBS PFBA and PFHxS, with formula- or mixed-fed infants having higher concentrations compared to exclusively breastfed infants. This study represents the first characterization of PFAS contamination in Samoa. Additional work in larger samples is needed to identify potentially modifiable determinants of PFAS concentrations, information that is critical for informing environmental and health policy measures.

Zürich II Statement on Per- and Polyfluoroalkyl Substances (PFASs): Scientific and Regulatory Needs.

Per- and polyfluoroalkyl substances (PFASs) are a class of synthetic organic chemicals of global concern. A group of 36 scientists and regulators from 18 countries held a hybrid workshop in 2022 in Zürich, Switzerland. The workshop, a sequel to a previous Zürich workshop held in 2017, deliberated on progress in the last five years and discussed further needs for cooperative scientific research and regulatory action on PFASs. This review reflects discussion and insights gained during and after this workshop and summarizes key signs of progress in science and policy, ongoing critical issues to be addressed, and possible ways forward. Some key take home messages include: 1) understanding of human health effects continues to develop dramatically, 2) regulatory guidelines continue to drop, 3) better understanding of emissions and contamination levels is needed in more parts of the world, 4) analytical methods, while improving, still only cover around 50 PFASs, and 5) discussions of how to group PFASs for regulation (including subgroupings) have gathered momentum with several jurisdictions proposing restricting a large proportion of PFAS uses. It was concluded that more multi-group exchanges are needed in the future and that there should be a greater diversity of participants at future workshops.

Bioconcentration of perfluorinated alkyl acids: how important is specific binding?

Perfluorinated alkyl acids (PFAAs) are important global pollutants with unique pharmacokinetics. Evidence is accumulating that their behavior within organisms is affected by interaction with a number of proteins. In mammals, serum albumin, fatty acid binding proteins (FABPs) and organic anion transporters (OATs) have been identified as important to the tissue distribution, species-specific accumulation, and species- and gender-specific elimination rates of perfluoroalkyl carboxylates and perfluoroalkane sulfonates. Similar pharmacokinetics has been identified in fish. Yet, no mechanistic model exists for the bioaccumulation of PFAAs in fish that explicitly considers protein interactions. In this work, we present the first mechanistic protein-binding bioconcentration model for PFAAs in fish. Our model considers PFAA uptake via passive diffusion at the gills, association with serum albumin in the circulatory and extracellular spaces, association with FABP in the liver, and renal elimination and reabsorption facilitated by OAT proteins. The model is evaluated using measured bioconcentration and tissue distribution data collected in two previous studies of rainbow trout (Oncorhynchus mykiss) and common carp (Cyprinus carpio). Comparing our model with previous attempts to describe PFAA bioconcentration using a nonspecific (partitioning-type) approach shows that inclusion of protein interactions is key to accurately predicting tissue-specific PFAA distribution and bioconcentration.

Evaluating the Thiessen polygon approach for efficient parameterization of urban stormwater models.

Catchment discretization plays a key role in constructing stormwater models. Traditional methods usually require aerial or topographic data to manually partition the catchment, but this approach is challenging in areas with poor data access. Here, we propose an alternative approach, by drawing Thiessen polygons around sewer nodes to construct a sewershed model. The utility of this approach is evaluated using the EPA's Storm Water Management Model (SWMM) to simulate pipe flow in a sewershed in the City of Pittsburgh. Parameter sensitivities and model uncertainties were explored via Monte Carlo simulations and a simple algorithm applied to calibrate the model. The calibrated model could reliably simulate pipe flow, with a Nash-Sutcliffe efficiency (NSE) of 0.82 when compared to measured flow. The potential influence of sewer data availability on model performance was tested as a function of the number of nodes used to build the model. No statistical differences were observed in model performance when randomly reducing the number of nodes used to build the model (up to 40%). Based on our analyses, the Thiessen polygon approach can be used to construct urban stormwater models and generate good pipe flow simulations even for sewer data limited scenarios.

Understanding impacts of organic contaminants from aquaculture on the marine environment using a chemical fate model.

As demand for sustainable marine aquaculture (mariculture) and marine food supply surges worldwide, there is a growing need for new tools to assess mariculture impacts on local ecosystems, including the cycling of toxic organic contaminants. With this in mind, we developed the Contaminant Fate in Aquaculture-Modified Ecosystems (CFAME) model. The current model was designed to explore the fate of mariculture-derived organic contaminants in the Marlborough Sounds, New Zealand, known for its Chinook salmon farming industry. Model evaluation indicated robust model design, with 80% of modeled concentrations falling within a factor of ten of measured ones for native biota. Model results showed that mariculture was a source of organic contaminants in the sediment even at the Marlborough Sounds regional level and in wild marine fishes with high trophic levels near the farm area. Future research attention should be directed toward measuring chemicals with low log KAW (<0) and high log KOW values (e.g., >3) in sediment, and chemicals with log KOW values of 3-9 in wild fish.

Characterization of Per- and Polyfluoroalkyl Substance (PFAS) concentrations in a community-based sample of infants from Samoa.

Per- and polyfluoroalkyl substances (PFAS) are persistent contaminants with documented harmful health effects. Despite increasing research, little attention has been given to studying PFAS contamination in low- and middle-income countries, including Samoa, where there is more recent modernization and potential window to examine earlier stages of PFAS exposure and consequences. Using data and biosamples collected through the Foafoaga o le Ola ("Beginning of Life") Study, which recruited a sample of mothers and infants from Samoa, we conducted an exploratory study to describe concentrations of 40 PFAS analytes in infant cord blood collected at birth (n=66) and dried blood spots (DBS) collected at 4 months post-birth (n=50). Of the 40 PFAS analytes tested, 19 were detected in cord blood, with 11 detected in >10% of samples (PFBA, PFPeA, PFHpA, PFOA, PFNA, PFDA, PFUnA, PFTrDA, PFHxS, PFOS, and 9Cl-PF3ONS); 12 analytes were detected in DBS, with 3 detected in >10% of samples (PFBA, PFHxS, and PFOS). PFAS concentrations were generally lower than those reported in existing literature, with the exception of PFHxS, which was detected at higher concentrations. In cord blood, we noted associations between higher PFHxS and male sex, higher PFPeA and residence in Northwest 'Upolu (NWU) compared to the Apia Urban Area (AUA), and lower PFUnA and 9Cl-PF3ONS with greater socioeconomic resources. In DBS, we found associations between higher PFBA and greater socioeconomic resources, and between lower PFBA and PFHxS and residence in NWU versus AUA. However, the latter association did not hold when controlling for socioeconomic resources. Finally, we observed associations between nutrition source at 4 months and DBS PFBA and PFHxS, with formula- or mixed-fed infants having higher concentrations compared to exclusively breastfed infants. This study presents the first evidence of PFAS contamination in Samoa. Additional work in larger samples is needed to identify potentially modifiable determinants of PFAS concentrations, information that is critical for informing environmental and health policy measures.