# Per- and Polyfluoroalkyl Substances as Potentiators of Hepatotoxicity in an Exposome Framework: Current Challenges of Environmental Toxicology

Minna Choi, Sophie Rose, Sophie Langouët

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Minna Choi, Sophie Rose, Sophie Langouët. Per- and Polyfluoroalkyl Substances as Potentiators of Hepatotoxicity in an Exposome Framework: Current Challenges of Environmental Toxicology. Toxicology, 2025, 515, pp.154167. 10.1016/j.tox.2025.154167. hal-05064327

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# Per- and polyfluoroalkyl substances as potentiators of hepatotoxicity in an exposome framework: Current challenges of environmental toxicology

Minna A Choi, Sophie Rose, Sophie Langouët*

Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes 35000, France

## ARTICLE INFO

**Keywords:**

Exposome

EDCs

Heterocyclic aromatic amines

MASLD

Hepatotoxicity

Organoids

Predictive toxicology

## ABSTRACT

Chronic liver diseases, including metabolic dysfunction-associated steatosic liver disease (MASLD) and hepatocellular carcinoma (HCC), are on the rise, potentially due to daily exposure to complex mixtures of chemical compounds forming part of the exposome. Understanding the mechanisms involved in hepatotoxicity of these mixtures is essential to identify common molecular targets that may highlight potential interactions at the molecular level. We illustrated this issue with two families of environmental contaminants, per- and polyfluoroalkyl substances (PFAS) and heterocyclic aromatic amines (HAAs), both of which could be involved in the progression of chronic liver diseases, and whose toxicity may be potentiated by interactions at the level of xenobiotic metabolism. In the study of exposome effects on chronic liver disease, New Approach Methodologies (NAMs) including omics analyses and data from various *in vitro*, *in vivo* and *in silico* approaches, are crucial for improving predictivity of toxicological studies in humans while reducing animal experimentation. Additionally, the development of complex *in vitro* human liver cell models, such as organoids, is essential to avoid interspecies differences that minimize the risk for humans. All together, these approaches will contribute to construct Adverse Outcome Pathways (AOPs) and could be applied not only to PFAS mixtures but also to other chemical families, providing valuable insights into mixture hepatotoxicity prediction in the study of the exposome. A better understanding of toxicological mechanisms will clarify the role of environmental contaminant mixtures in the development of MASLD and HCC, supporting risk assessment for better treatment, monitoring and prevention strategies.

## 1. Exposome

### 1.1. Definition and evolution of the exposome concept

The concept of exposome emerged in 2005, aiming to study the role of environmental factors in the development of multifactorial pathologies in addition to the genome. It was initially defined as all external environmental exposures throughout an individual's life also called external exposome. This includes chemical, physical and biological agents, as well as psychological, social and lifestyle factors (Wild, 2005). Subsequently, the scope of the exposome covered all biological responses induced by environmental exposures (Miller et Jones, 2014). Finally, the notion of internal exposome was integrated, encompassing both exogenous and endogenous metabolites in the bloodstream. Exogenous metabolites originate from external exposures such as food or environmental contaminants, while endogenous metabolites come from the disruption of metabolic pathways induced by external exposures

(Rappaport, 2018). Altogether, the French National Agency for Food, Environmental and Occupational Health Safety (Agence Nationale de Sécurité Sanitaire de l'Alimentation, de l'Environnement et du Travail or ANSES) defines the exposome as "all harmful and beneficial exposures to chemical, biological and physical agents interacting with the physiological state, the living environment and the psychosocial context experienced by an individual from its conception to death in order to better understand its state of health" (ANSES, 2023).

### 1.2. The chemical exposome and chronic liver diseases

With the rise of industrial activities, numerous contaminants that form part of the external chemical exposome find their way into the air, soil and water, ultimately contaminating the food chain. Some of these contaminants, classified as persistent organic pollutants (POPs), are highly lipophilic and non-biodegradable. As a result, they accumulate in the body's fatty tissues (Jones et De Voogt, 1999), in high-fat foods

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: sophie.langouet@univ-rennes.fr, sophie.langouet@inserm.fr (S. Langouët).</footnote>
(Stiefel et Stintzing, 2023) and persist in the environment despite their restriction of use (United Nation Environment Programme, 2023). POPs include organochlorine pesticides, flame retardants, per- and polyfluoroalkyl substances (PFAS), organotins and dioxins (Diamanti-Kandarakis et al. 2009; Stiefel et Stintzing, 2023; Metcalfe et al. 2022). In contrast, other contaminants such as bisphenol A (BPA) (Völkel et al. 2002) and phthalates (Genuis et al. 2012) have shorter half-lives and are eliminated from the body more rapidly. Commonly used in plastic packaging, these compounds can be released into food (Stiefel et Stintzing, 2023). Pharmaceuticals residues, including both hormonal and non-hormonal drugs, are another source of environmental contamination (Sabir, Akhtar, et Saleem, 2019). Additionally, air pollutants such as 2.5- and 10-micron nanoparticles, sulfur dioxide, nitrogen oxide, volatile organic compounds, polycyclic aromatic hydrocarbons (PAHs) contribute to the widespread environmental exposure (Shetty et al. 2023). Furthermore, carcinogenic compounds like furan, acrylamide and heterocyclic aromatic amines (HAA) can form during cooking and food processing (Stiefel et Stintzing, 2023). Overall, long-term exposure to these chemical contaminants has been linked to the onset of cancers and chronic diseases. They disrupt multiple physiological systems, including the neural, cardiovascular, respiratory, digestive, reproductive, endocrine and immune systems, while also contributing to metabolic disorders (Shetty et al. 2023; Manisalidis et al. 2020; Petrakis et al. 2017). The main chemical contaminants, their sources and their target organs are illustrated in Fig. 1.

The liver is a vital organ as it plays an essential role in lipid, glucose and amino-acid metabolism, but also detoxifies xenobiotics, including chemical environmental contaminants. As a result, it continuously interacts with the exposome and is exposed to a multitude of exogenous compounds capable of generating reactive metabolites. Numerous studies have demonstrated that environmental contaminants are a risk

factor for chronic liver disease, highlighting its connection to the exposome (Barouki et al. 2023). Metabolism-associated Steatosic Liver Disease (MASLD) is the most common chronic liver disease in industrialized Western countries, and its prevalence increased by 50 % over two decades (Younossi et al. 2023). Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer, the latter being the 6th most commonly diagnosed cancer worldwide and the 3rd cause of cancer-related deaths (Sung et al., 2021). Although the incidence of HCC is higher in developing countries, accounting for 782,000 new cases in 2012 (Ferlay et al. 2015), MASLD-induced HCC continues to rise, especially in industrialized countries (Llovet et al. 2023).

The study of the exposome, also known as exposomics, aims to investigate all external and internal exposures and their consequences on the organism including biological and health effects (Barouki et al. 2023). Using toxicological approaches, exposomics will notably provide a better understanding of the role of environmental factors in the development of liver diseases. Toxicology provides insights on the mechanisms underlying the biological effects of mixtures, using both conventional and innovative approaches. In this review, we will discuss challenges and prospects for the study of the exposome, focusing on the contributions of toxicology.

1) The challenge of assessing the hepatotoxicity of chemical mixtures lies in understanding their interactions and their cumulative effects. Since toxicological risk assessments primarily focus on individual compounds, mixture effects are generally considered when co-exposure is likely. However, given the impracticality of testing all potential combinations, one promising approach is to categorize chemicals with similar toxicokinetic properties, allowing for the prioritization of mixtures most likely to exhibit significant toxicological interactions (Braeuning et al. 2022).

2) Given the diversity of environmental contaminants to which we

<figure><img src="image_2.png" /><figcaption>Fig. 1. Main environmental contaminants, their sources and their target organs.</figcaption></figure>
are exposed at low doses, relevant and sensitive models are required to evaluate the toxicity of complex chemical mixtures at low doses. Thus, the second challenge lies in the need to develop cellular models that are as close as possible to human models, in order to overcome interspecies differences that limit the predictive capacity of toxicological studies. In this context, complex human liver cell culture represents a promising tool.

3) Finally, the study of chemical mixtures in the exposome framework could benefit from New Approach Methodologies (NAMs) which provide more efficient and human-relevant tools for assessing the potential toxic effects of various chemicals.

## 2. Studies of chemical contaminant mixtures

### 2.1. Hepatotoxicity of chemical environmental contaminant mixtures

The impact of various mixtures of chemical environmental contaminants on the liver has been investigated using *in vitro* and *in vivo* models, and through epidemiological studies. In the liver, these compounds were found to alter lipid, glucose and xenobiotic metabolism, to interact with the antioxidant system or to be genotoxic, all of which are involved in the pathogenesis from MASLD to HCC (Table S1).

### 2.2. Environmental contaminants are major risk factors for MASLD and HCC

To understand the impact of environmental contaminants on the onset of chronic liver diseases, it is important to first understand the pathogenesis from MASLD to HCC. MASLD includes different stages of liver diseases linked to lipid accumulation, ranging from hepatic steatosis to more severe forms such as non-alcoholic steatohepatitis, fibrosis and cirrhosis, which can progress to HCC (Chalasani et al. 2012). Hepatic steatosis is defined by an accumulation of triglycerides in more than 5 % of hepatocytes in the form of lipid droplets (Cobbina et Akhlaghi, 2017; Pouwels et al. 2022). 90 % of HCC cases develop on pre-existing cirrhosis (Dhanasekaran, Bandoh, et Roberts, 2016).

In order to better characterize the involvement of environmental contaminant mixtures on the development of MASLD and HCC, more mechanistic studies are required. To illustrate such challenge, we focus here on endocrine disrupting chemicals (EDC), specifically PFAS and chemical carcinogens like HAAs, two families of contaminants that currently raise significant concerns for human health and for which there is mechanistic evidence linking them to liver disease progression.

#### 2.2.1. EDCs like PFAS may induce metabolic disruption in the liver

Based on *in vitro*, *in silico*, *in vivo* and epidemiological studies, there is a wealth of data on the mechanisms by which EDCs exert adverse effects on health. EDCs are associated not only with developmental and reproductive abnormalities, but also chronic diseases such as cancer, obesity, diabetes, neurodegenerative, cardiovascular and autoimmune diseases (Ahn et Jeung, 2023). Despite growing evidence on these effects, a consensus on assessing the risks of EDCs to human health and thus harmonizing their identification and classification criteria remains challenging. This difficulty arises from the complex characteristics of EDCs, such as:

- the presence of low-dose effects

- mixture interactions

- the delay between exposure and the onset of biological effects.

Conventional risk assessment frameworks often struggle to integrate these factors, making it difficult to establish a causal link between exposure and adverse effects (Stiefel et Stintzing, 2023). Among EDCs, PFAS seem to deregulate lipid and glucose metabolism at transcriptomic and functional levels in *in vitro* and *in vivo* studies (Bjork, Butenhoff, et Wallace, 2011; Attema et al. 2022; Rosen, Abbott et al., 2008), possibly

contributing to the progression of liver disease from steatosis to fibrosis and cirrhosis, the latter being a key step in the development of HCC (Chalasani et al. 2012).

#### 2.2.1.1. Exposure levels, bioaccumulation and metabolism of PFAS in the liver.
PFAS are synthetic chemicals that are widely used in industrial and household products such as surfactants in cleaning products, cosmetics, paints, coatings and textiles for their water and dirt-repelling properties. They act as grease-proofing agents in food packaging and are also found in nonstick cookware as well as firefighting foams (Stiefel et Stintzing, 2023; Metcalfe et al. 2022).

The Organization of Economic Cooperation and Development or OECD defines PFAS as “fluorinated substances that contain at least one fully fluorinated methyl or methylene carbon atom” (OECD, 2018). To date, over 14,000 different PFAS have been identified (Park et al. 2024), which are mainly categorized into non-polymers, including perfluoroalkyl acids, perfluoroalkylether acids and their precursors, as well as polymers such as fluoropolymers or perfluoropolyethers (Buck et al. 2011; Kwiatkowski et al. 2020). The strong carbon-fluorine bond within the perfluorinated structure gives PFAS chemical stability and resistance to breakdown (Kwiatkowski et al. 2020). PFOA, the first widely used PFAS, was later followed by the development of PFOS and PFHxS, whose structures are illustrated in Fig. 2 A.

Unlike many xenobiotics, PFAS undergo minimal metabolism (Ylinen et al. 1989) and are reabsorbed through enterohepatic circulation (Cao et al. 2022). However, certain precursors, such as fluoro-telomer alcohols and perfluoroalkane sulfonamides, can undergo atmospheric metabolization and hepatic biotransformation, forming persistent PFAS like PFOA and PFNA (Butt, Muir, et Mabury, 2013). Moreover, PFAS are poorly eliminated from the body. Due to their long half-lives ranging from 1.48 to 8.5 years for PFOA, PFOS and PFHxS in human serum (Rosato et al. 2024), PFAS can be measured in human serum and tissues.

The cross-sectional ESTEBAN study, conducted by ANSES on 17 PFAS, revealed that 7 of them, including PFOS, PFOA, PFHxS, PFNA, PFDA, PFHpS and PFUnA are detected in the French adult population, with the highest serum concentrations ranging from 1.37 to 4.03 µg/L for the first 3 compounds (Amivi Oleko, 2019). Postmortem analysis of human brain, liver, lung, bone and kidney tissues revealed that PFOS and PFOA were detected in 90 % and 45 % of liver tissue samples respectively, with hepatic concentrations corresponding to 41.9 ng/g and 4 ng/g (Pérez et al. 2013). Computational and experimental studies further show that medium and long-chain PFAS, such as PFOS and its alternatives are detected in rat blood and liver while short-chain PFAS exhibit lower accumulation. A key factor contributing to liver retention is the high binding affinity of PFAS for liver fatty acid binding protein (L-FABP), facilitating their uptake into hepatocytes. A strong correlation has been observed between PFAS binding to L-FABP and their measured liver concentrations in rats (Cao et al. 2019). This binding mechanism, along with their chemical stability, may further contribute to PFAS bioaccumulation and environmental persistence.

Recognizing their persistence and toxicity, PFOA, PFOS and PFHxS are classified as POPs and listed under the Stockholm Convention, restricting or banning their production and use (United Nation Environment Programme, 2023). Although environmental levels of these specific PFAS have declined since the implementation of these regulations, their ubiquitous presence in the environment remain a concern (Brase, Mullin, et Spink, 2021).

With these regulations, various replacement PFAS or replacement chemicals have been introduced. To enhance clarity, we define “replacement PFAS” as fluorinated substances introduced to substitute legacy PFAS. In contrast, we define “replacement chemicals” more broadly as non-fluorinated compounds intended to be used in PFAS-free products. Historically, regulated PFAS have been replaced with other structurally similar unregulated PFAS. However, this practice is
<figure><img src="image_3.png" /><figcaption>**Fig. 2.** A. Chemical structures of PFAS of interest. Among perfluoroalkyl acids, we find perfluoroalkyl sulfonic acids such as PFOS or PFHxS and perfluoroalkyl carboxylic acids such as PFOA. B. Chemical structures of HAAs and their occurrence in the environment. HAA include (A) 3-amino-1,4-dimethyl-5H-pyrido[4,3- b] indole (Trp-P-1), 3-amino-1-methyl-5H-pyrido[4,3- b]indole (Trp-P-2), 2-amino-9H-pyrido[2,3- b]indole (AαC) and 2-amino-3-methyl-9H-pyrido[2,3- b]indole (MeAαC) in diesel exhaust. (B) Additionally, 2-amino-6- methyldipyrido[1,2-a:3',2'-d]imidazole (Glu-P-1), 2-aminodipyrido[1,2-a: 3',2'-d]imidazole (Glu-P-2), 2- amino-3-methylimidazo[4,5-f]quinoline (IQ) and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) are present in cigarette smoke. Other HAAs such as 2- amino-3,4- dimethylimidazo[4, 5-f]quinoline (MeIQ) or 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) are found in cooked meat and fish (adapted from (Bellamri, Walmsley, et Turesky, 2021)).</figcaption></figure>

discouraged in the European Union because their metabolism and
toxicity mechanisms remain less understood. Although initial findings
suggest shorter half-lives, some new replacement PFAS, such as
perfluorodecalin-2-sulfonic acid (PFDecS) and *N*-diperfluorobutanoic
acid (N-diPFBS), display strong binding affinity to L-FABP, thus pro-
moting liver accumulation. This strong interaction is thought to be
driven by their molecular structures, which promote stable hydrophobic
interactions within the protein's binding cavity (Cao et al. 2019).
Additionally, recent findings indicate that certain replacement PFAS
such as ammonium 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)-propa-
noic acid (GenX), perfluorohexanoic acid (PFHxA) and

perfluorobutanoic acid (PFBA) may have similar toxicity profiles to
legacy compounds in animal models (Gomis et al. 2018). These findings,
among others, raise concerns about the potential of emerging PFAS for
bioaccumulation and long-term toxicity. Therefore, rigorous toxicolog-
ical assessments are necessary to determine whether these replacements
truly offer a safer alternative or if they pose comparable risks to liver
health.

2.2.1.2. Alteration of lipid and glucose metabolism by PFAS in the liver through nuclear receptors. Nuclear receptors are transcriptional regulators that play a fundamental role in maintaining lipid and glucose

<figure><img src="image_4.png" /><figcaption>**Fig. 3.** Transcriptional regulation of lipid and carbohydrate metabolism by PPAR, CAR and PXR (adapted from Grygiel-Górniak, 2014; Cai, Young, et Xie, 2021; Swanson et al. 2013).</figcaption></figure>
homeostasis, as well as adipogenesis. Their activity is regulated by the organism's nutritional status, ensuring energy balance (Fig. 3) (Grygiel-Górniak, 2014; Cai, Young, et Xie, 2021; Swanson et al. 2013). However, exposure to EDCs such as PFAS can interact with these nuclear receptors, possibly disrupting normal metabolic regulation and leading to adverse health effects, including hepatic steatosis and obesity (Heindel et al. 2022; Grün et Blumberg, 2009; Bernal et al. 2022). This section focuses on key nuclear hormone receptors involved in liver metabolism, including Peroxisome Proliferator-Activated Receptors (PPARs) and xenobiotic receptors such as Constitutive Androstane Receptor (CAR) and Pregnane X Receptor (PXR). Given the interspecies differences that can be observed for such receptors, it is important to note that the expression levels, ligand recognition and downstream responses of these nuclear receptors can vary between rodents and humans, potentially impacting the translatability of experimental data to human health risk assessment (Moore et al. 2000; Keller et al. 1997; Garoche et al. 2021).

Among the PPAR family, PPARα is highly expressed in metabolically active tissues such as the liver (Braissant et al. 1996), where it promotes β-oxidation and lipolysis, thereby preventing hepatic lipid accumulation. Studies using hepatocyte PPARα knockout mice supports its protective role (Montagner et al. 2016). In contrast, PPARγ, mainly expressed in the white adipose tissue (Braissant et al. 1996), serves as a key regulator of adipogenesis in the 3T3-L1 murine preadipocyte cell line (Chawla et al. 1994). Although normally expressed at low levels in a healthy liver, PPARγ expression increases in obese diabetic mice, possibly contributing to hepatic steatosis (Memon et al. 2000).

It has been shown that PFOA activate PPARα at doses of 0.05 and 0.3 mg/kg body weight/day (Attema et al. 2022), while another study reported a dose of 0.7 mg/kg body weight/day to achieve serum PFOA concentrations comparable to those seen in highly exposed workers (Schlezinger et al. 2020). Although these levels are lower than doses used in other studies (Rosen, Abbott et al., 2008; Bjork, Butenhoff, et Wallace, 2011), they still remain higher than plasmatic PFOA concentrations measured in the ESTEBAN study, underscoring the challenge of translating experimental exposures to environmentally relevant human conditions. Nevertheless, at these tested doses, by PFOA-mediated PPARα activation resulted in decreased plasma cholesterol and triglycerides, as well as anti-adipogenic effects with reduced body weight in PPARα knockout mice models. Despite these apparent lipid-lowering effects, PFOA exposure paradoxically increases liver weight, triglyceride levels and hepatic lipid accumulation, suggesting that PPARα may contribute to PFAS-induced steatosis (Attema et al. 2022; Schlezinger et al. 2020; Rosen, Abbott et al., 2008). Additionally, PFOA can activate PPARγ (Schlezinger et al. 2020) which promotes adipocyte differentiation as mentioned earlier (Chawla et al. 1994). It was hypothesized that while chronic activation of PPARα is required for its anti-adipogenic effects, acute activation is enough to induce and maintain adipocyte differentiation by PPARγ, reinforcing their classification as obesogenic EDCs (Grün and Blumberg, 2009).

Beyond PPARs, xenobiotic receptors such as PXR and CAR play critical roles in liver metabolism. These receptors are expressed in the liver and intestine and regulate endogenous processes such as the metabolism of bilirubin, bile acids, thyroid hormones, steroids, and energy metabolism, including lipid and glucose homeostasis (Cai, Young, et Xie, 2021). In primary rat hepatocytes and primary human hepatocytes (PHH), gene expression analysis reveals that both PPARα and xenobiotic receptors CAR and PXR seem to contribute to the transcriptional response following PFOA and PFOS treatment. Interestingly, species-specificity were observed, with human PPARα being less responsive than in rat, suggesting interspecies variability in PFAS-mediated receptor activation. In the same study, metabolic pathway analysis demonstrates that PFOA might favor fatty acid oxidation over carbohydrate metabolism in rat hepatocytes, but this effect was more pronounced in rat hepatocytes compared to human hepatocytes due to metabolic interspecies differences. Interestingly, it

was hypothesized that after PPARα activation by PFOS and PFOA, the resulting metabolites from fatty acid oxidation might lead to secondary activation of other nuclear receptors including CAR, PXR and LXR (Bjork, Butenhoff, et Wallace, 2011). Studies using nuclear receptor knockout mouse models further demonstrate that PPARα and CAR play central roles in cytochrome induction following acute or chronic PFAS exposure (Cheng et Klaassen, 2008; Rosen, Lee, et al. 2008; Schlezinger et al. 2020). While these studies provide valuable mechanistic insights on pathways affected by PFAS, it is important to note that they often use high doses, which may not accurately reflect real-life human exposure levels. At such elevated concentrations, off-target effects become more likely, potentially complicating data interpretation.

Finally, there is growing evidence that exposure to certain PFAS leads to sex-dependent alterations in lipid homeostasis. Studies have demonstrated that females may be more susceptible to PFAS-induced metabolic dysregulation. For instance, it was reported that in a human MASLD cohort, circulating PFAS, specifically PFOA, PFNA and PFOS concentrations are positively associated with elevated serum bile acids. Additionally, PFOA and PFOS concentrations were also positively associated with hepatic lipids like ceramides, phospholipids and triglycerides, with a more pronounced effect observed in females. The same tendency was also found in PPARα mouse models (Sen et al. 2022). Similarly, PFOA exposure at real-world relevant concentrations significantly increased liver triglyceride levels in both male and female but serum triglyceride levels were particularly elevated in female human PPARα-null mice. Moreover, notable gender differences were observed in the expression of transcriptional regulators involved in lipid metabolism. In female mice, genes that upregulating lipid degradation and decreasing lipid synthesis were significantly downregulated (Schlezinger et al. 2021). Finally, sex-specific gene expression changes were reported in rats exposed to higher doses of 6:1 FTOH, 10:2 FTOH and PFHxSAm. Fatty acid oxidation and gluconeogenesis genes were increased in male rats, while females showed upregulated genes involved in lipid synthesis (Hari et al. 2024). These findings suggest a heightened susceptibility of females to PFAS-induced metabolic disruption, emphasizing the importance to elucidate sex-specific mechanistic pathways involved in PFAS toxicity and consider gender differences in future PFAS risk assessment.

### 2.2.1.3. Association between PFAS and liver diseases.
Hepatic lipid accumulation is promoted by an imbalance between lipid synthesis and degradation, notably by: 1) excessive fatty acid synthesis by de novo lipogenesis, 2) reduced fatty acid degradation by β-oxidation, 3) increased fatty acid internalization by hepatocytes, 4) decreased fatty acid export in the form of Very Low Density Lipoprotein (VLDL) (Bernal et al. 2022). As discussed in the previous section, studies on specific legacy PFAS, particularly PFOS and PFOA, suggest that these compounds can disrupt lipid metabolism in certain conditions by influencing these pathways. This can potentially contribute to hepatic lipid accumulation and lead to steatosis, the first stage of MASLD. However, such findings cannot be generalized to all PFAS, given the structural diversity and varying biological effects across this large chemical class. Additionally, experimental studies strongly suggest that obesogenic EDCs contribute to MASLD development (Heindel et al. 2022; Cano et al. 2021; Chen et al. 2023; Heindel et al. 2017). Compared to experimental data, epidemiological evidence regarding the association between PFAS exposure and hepatic steatosis remains more limited and sometimes inconsistent. For example, according to a study including data from 2017 to 2018 NHANES, high levels of PFAS, especially PFHxS, are associated with elevated biomarkers of liver injury and increased risk of fatty liver disease among individuals with risk factors like high alcohol consumption, obesity or high-fat diet (X. Zhang et al. 2023). Similarly, a study including a human MASLD cohort demonstrated a positive association between serum PFAS concentrations (PFOS, PFHxS, PFNA and PFOA) and liver fat content, insulin resistance, non-alcoholic
steatohepatitis and hepatic fibrosis (Sen et al. 2022). Conversely, another study reported inconsistent associations between PFAS and biomarkers of liver disease (Samala et al. 2024), highlighting the need for further epidemiological research to clarify the potential hepatotoxic effects of PFAS.

Obesogenic EDCs including some PFAS are also involved in the progression of MASLD, from steatosis to cirrhosis, by promoting inflammation, oxidative stress, apoptosis and fibrosis (Cano et al. 2021). Most cases of HCC develop on MASLD-induced cirrhosis (Llovet et al. 2023), the progression of which may be promoted by environmental contaminants. Indeed, sequencing of liver tumors has uncovered recurrent mutations that are not linked to classic HCC etiologies, but to other unidentified environmental factors (Guichard et al. 2012).

### 2.2.2. HAAs induce DNA damage through metabolic activation in the liver

HAAs, a family of chemical carcinogens present in air and food, are suspected to cause mutations observed in HCC. HAAs are divided into 2 types. On one hand, thermal HAAs are formed at temperatures between 100 and 300°C by the Maillard reaction between hexoses, amino acids and creatinine in meat. Their structure is of the imidazo-quinoxaline and amino-imidazo-azarene type. On the other hand, pyrolytic HAAs are formed above 300°C by a reaction between meat proteins and amino acids and have an amino-carboline structure (Sugimura et al. 2004; Skog et al. 1997; J.S. Felton et al. 1986). Several factors, such as meat type, temperature and cooking time, influence the nature and quantity of HAAs formed. The main source of HAAs is the cooking of meat and fish, which generates HAAs in the nanogram per gram (ng/g) range (Nadeem et al. 2021). AαC is the most abundant HAA in cigarette smoke, with concentrations up to 260 ng per cigarette (Yoshida et al. Matsumoto, 1980; L. Zhang et al. 2020). Its concentrations is 25–100 times higher than molecules proven to be carcinogenic in humans, such as 4-amino-biphenyl and B[a]P (Ohgaki, Takayama, et Sugimura, 1991; Yoshida et al. Matsumoto, 1980; Bellamri et al. 2017). Finally, diesel particulates contain carcinogenic molecules such as PAHs, but also amino-carboline-type HAAs such as Trp-P-1, Trp-P-2, AαC and MeAαC (Manabe et al. 1991) (Fig. 2B).

Studies on genotoxicity, mutagenesis and carcinogenesis studies demonstrate that HAAs target the liver and may therefore contribute to HCC development. Experimental studies have shown that HAAs are potent mutagens in bacterial assays, such as the Ames test, where they induce frame-shift and base-pair mutations in Salmonella typhimuryum in the presence of a metabolic activator, S9 fraction of liver microsomes (James S. Felton et Knize, 1991; Sugimura, 1986; Sugimura, 1997; Table S2). Moreover, the mutagenic potential of HAAs in bacteria has been shown to correlate with their carcinogenic potential in rodents (Hatch et al. 1992). In rodent models, the oral administration of HAAs leads to tumor formation in multiple organs, with the liver being a primary target for HAAs like IQ and MeIQx (Sugimura, 1997). In primates, oral administration of IQ has shown to induce hepatocellular carcinoma, further supporting the carcinogenic potential of HAAs in the liver (Adamson et al. 1995). Finally, mutations in oncogenes (Ha-Ras, Ki-Ras, β-catenin) and tumor suppressor genes (p53, APC) have been reported in various HAA-induced tumors in rodents. The liver appears to be a major target for IQ- and MeIQx-induced mutations, while PhIP induces extrahepatic tumors, notably in the colon and mammary gland (Archer et al. 2000; Sinha et al. 2001; Table S2).

Metabolic activation plays a crucial role in the genotoxicity of HAAs. As pro-carcinogens, HAAs induce DNA damage following their activation by CYP1A2. The metabolism of MeIQx (Langouët et al. 2001) and PhIP (Langouët et al. 2002) is well-characterized in human and rat hepatocytes, revealing interspecies differences that leads to the underestimation of HAAs' genotoxicity in humans (Langouët et al. 2001). Specifically, reactive metabolites are produced in greater quantities in human hepatocytes than in rat hepatocytes due to the higher catalytic activity of human CYP1A2 in the N-hydroxylation of MeIQx and PhIP. Furthermore, CYP1A2 exhibits regioselectivity, primarily catalyzing

N-oxidation which leads to bioactivation in humans, whereas in rats, the same enzyme predominantly oxidizes heterocycles, resulting in detoxification products.

There is compelling experimental evidence demonstrating the mutagenic and carcinogenic effects of HAAs in animal models. However, the available human epidemiological data remain insufficient to prove causality. Consequently, the International Agency for Research on Cancer (IARC) has classified IQ as a probable human carcinogen (Group 2 A) and other HAAs as possible carcinogens (Group 2B) (International Agency for Research on Cancer 1993). Addressing these knowledge gaps requires further research to better understand the metabolic activation of HAAs in humans generating reactive metabolites and DNA adducts. Identifying these adducts could provide crucial biomarkers for assessing HAA exposure and genetic polymorphisms, as it remains challenging to track individual exposure through retrospective and prospective studies.

### 2.3. Common targets of EDCs and HAAs: xenobiotic receptors and potential combined effects of EDCs and HAAs on liver disease

Xenobiotic receptors appear to be a point of convergence in the complex mechanisms underlying the actions of EDCs and HAAs. Notably, EDCs have been shown to exert obesogenic effects, at least in part, through mechanisms involving nuclear receptors. This disruption may contribute to alterations in lipid and glucose metabolism, thereby potentially promoting weight gain. Exposure to a high-fat diet, in conjunction with EDC exposure, can amplify weight gain and steatosis in animal models and these interactions have been well documented (Heindel et al. 2022). Certain EDCs also seem to modulate the expression of xenobiotic metabolizing enzymes (XME) via a nuclear xenobiotic receptor-dependent mechanism. For example, dioxins such as TCDD and PCB are well-established AhR ligands and are particularly known to induce the expression of CYP1A (Stevens, Mezrich, et Bradfield, 2009). Similarly, BPA and its analogues have also been reported to upregulate CYP1A1 and UGT1A1 via an AhR-dependent mechanism in the HepG2 liver cell line (Hercog et al. 2019). Additionally, certain peroxisome proliferators such as phthalates induce CYP1A1 through PPARα activation in various human cell models, including the HepG2 cell line (Rusyn, Peters, et Cunningham, 2006). Although HepG2 are less metabolically active than human hepatocytes, it was shown that CYP1A1 and CYP1A2 levels are significantly induced by 5 different AhR agonists (Westerink et Schoonen, 2007). As for PFAS, a proteomic analysis of mice offspring livers suggests that PFOA, PFOS and PFHxS up-regulate the expression of proteins involved in xenobiotic metabolism (Kaye et al. 2024). Furthermore, PFOA and PFOS were also found to increase CYP1A1 and CYP1A2-like enzymatic activity in the rainbow trout (Solan, Franco, et Lavado, 2022). Conversely, HAAs like PhIP and MeIQx are genotoxic and carcinogenic following metabolic activation by XME (Langouët et al. 2001; Langouët et al. 2002). By an AhR-dependent mechanism, some HAAs have been found to induce CYP1A1 and CYP1A2, which are responsible for their bioactivation in the HepaRG cell line (Sekimoto et al. 2016) and in rodents (Dumont et al. 2010). Thus, both PFAS and HAAs could be linked to alterations at the level of xenobiotic metabolism.

These interactions may collectively result in modifications of XME expression, ultimately influencing the bioactivation of pro-carcinogenic molecules. Studies have demonstrated that when co-treated with different EDCs and benzo[a]pyrene (B[a]P) - a well-documented pro-carcinogen bioactivated by CYP1A - DNA damage is exacerbated compared to treatment with B[a]P alone. For example, in rats exposed to DEHP and the pesticide silvex for 14 days, B[a]P treatment led to an increased CYP1A1 activity while simultaneously reducing glutathione-S-transferase (GST) activity compared to untreated rat hepatocytes, and more B[a]P-diol-epoxide-derived DNA adducts were formed in the presence of DEHP or silvex. This effect may be explained by greater CYP1A1-catalyzed metabolic activation of B[a]P, coupled with reduced ability of GST to detoxify electrophilic metabolites (Voskoboinik et al.
1997). Similarly, in HepG2 cells, co-treatment with PCB 180 and B[a]P increases DNA strand breaks compared to cells treated with B[a]P alone (Al-Anati et al. 2015). Like B[a]P, HAAs are recognized as pro-carcinogens requiring metabolic activation mediated by CYP1A mainly. However, whether the co-administration of HAAs and EDCs results in additive, synergistic potentiation of their genotoxic or carcinogenic effects remains unclear. Given the observed interactions between EDCs and HAAs at both the nuclear receptor and XME levels, we can hypothesize that simultaneous exposure to these compounds may increase the hepatocarcinogenic potential of HAAs, tipping the balance towards metabolic activation and reducing detoxification capacities.

It is legitimate to wonder about additive, synergistic and antagonistic effects in the development of MASLD and HCC upon co-exposure to compounds like PFAS and HAAs that seem to share common targets, as their presence is ubiquitous. In the context of studying hepatotoxicity of mixtures, it is crucial to characterize the combined effects of metabolic disruption induced by EDCs and genotoxic damages caused by HAAs. Toxicological approaches will provide a better understanding of the mechanisms involved in the biological effects induced by mixtures. When assessing the effects of the exposome on human health, another challenge is to improve the predictivity of toxicological studies in humans.

### 3. New approach methodologies to improve the predictivity of toxicological studies

Predictive toxicology is a discipline aimed at forecasting the potential toxic effects of chemical substances on living organisms and the environment. It forms the foundation of the next generation risk assessment, enabling a more efficient risk assessment associated with exposure to chemicals, environmental pollutants, and pharmaceuticals while reducing reliance on animal models. This field integrates various *in chemico*, *in silico*, and *in vitro* approaches also known as NAMs. These methods primarily include high-throughput screening, omics approaches, cell culture techniques, microphysiological systems, machine learning with artificial intelligence and QSAR predictions as described by Najjar et al. Among these, microphysiological systems associated with complex cell models, large-scale "omics" analyses such as transcriptomics, proteomics, metabolomics, and adductomics, and physiologically-based pharmacokinetics (PBPK) modeling are currently being developed in numerous laboratories (Najjar et al. 2023). According to the FDA's predictive toxicology roadmap, these NAMs contribute to the study of risks associated with chronic low-dose exposure and chemical mixtures (*Food and Drug Administration, 2017*). Innovative *in vitro* models are particularly valuable for assessing the impact of exposome on liver diseases and will be discussed in the following section.

#### 3.1. *Experimental models for the study of the exposome and liver diseases*

To this day, *in vivo* animal studies remain widely used for preclinical assessment of chronic toxicity and carcinogenesis. However, there is growing recognition within the scientific and regulatory communities of the limitations of animal models in accurately predicting human health outcomes. Interspecies differences in physiology and metabolism raise questions about the accuracy of animal studies in human risk assessment. For instance, while Drug-Induced Liver Injury (DILI) is a major cause of drug withdrawal in clinical trials (Regev, 2014), animal models only predict 43–63 % of DILI cases in humans (Olson et al. 2000). Differences in xenobiotic metabolizing enzyme expression can underestimate the risk of pro-carcinogenic molecules in humans that requires metabolic activation. Moreover, animal studies are costly and time-consuming but also raise ethical issues. Recognizing these issues, and in line with the 3Rs principle (Replacement, Reduction, Refinement), many regulatory frameworks in the European Union now consider animal testing a method of last resort (European Commission,

2006). Given the chemical complexity and the need for more human-relevant data, it is essential to shift toward experimental models that better replicate human physiology. In this regard, complex human liver cell culture systems offers significant advantages and are increasingly favored for assessing hepatotoxicity.

#### 3.1.1. *In vitro models*

##### 3.1.1.1. *Human liver cell types.*
The liver is made up of two main cell types: parenchymal cells, essentially hepatocytes, and non-parenchymal cells. Each cell type controls a set of physiological responses and influences the behavior of neighboring cells (Taylor, Alarcon, et Billiar, 1998). Hepatocytes account for 80–90 % of the liver mass, and perform the main metabolic functions in the liver (Blouin, Bolender, et Weibel, 1977). PHHs are undeniably the gold standard for establishing relevant *in vitro* culture models. Extracted directly from the liver, they reflect the organ's functionality as closely as possible *in vivo*, enabling highly predictive *in vitro* pharmacological and toxicological data. As each preparation is derived from a specific donor, they offer the opportunity to study inter-individual variations associated with genetic or expression polymorphisms. Thus, the primary culture of human hepatocytes is of major interest for pharmacokinetic and toxicological studies, as well as for biotechnological applications. However, the low availability of PHHs due to a shortage of donors are major obstacles to the use of these cells and explain the development of alternative cell models.

Numerous cell lines obtained from human hepatocarcinoma are widely used for *in vitro* studies. These cells have a high proliferative capacity which, combined with a relatively stable phenotype over time, makes them well-suited to high-throughput screening under standardized, reproducible conditions. Among these, the HepG2 line has been very well characterized, and an exhaustive literature is available regarding the effects of a large number of exogenous compounds on these cells (O'Brien, 2011; Schoonen et al. 2005; Van Summeren et al. 2011) but their use is restricted by their very limited differentiated liver functions. The HepaRG line, generated from tumor cells of a hepatitis C-infected woman with hepatocarcinoma (Gripon et al. 2002), is the most highly differentiated human hepatocarcinoma cell line. HepaRG hepatocyte-like cells express many of the morphological and functional characteristics of mature hepatocytes upon treatment with DMSO (Aninat et al. 2006), including nuclear receptors (CAR, PXR, AhR, RXR) and hepatic-specific transcription factors (HNF1, HNF4α) (Kanebratt et Andersson, 2008) as well as the main transporters involved in drug elimination (Le Vee et al. 2013).

Intensive research is also being carried out to generate hepatocytes from induced pluripotent stem cells (iPSCs). The main advantage of the latter lies in the fact that they can self-renew indefinitely. Although the differentiated cells resemble more the fetal than the adult stage (Doss et Sachinidis, 2019), iPSC-derived hepatocytes have been successfully used to study various liver diseases (Ramli et al. 2020; Graffmann et al. 2016; Ouchi et al. 2019; Ramli et al. 2020).

Apart from hepatocytes, non-parenchymal cells account for around 6.3 % of liver cells (Ishibashi et al. 2009), including hepatic stellar cells (1,4 %), Kupffer cells (2,1 %), and sinusoidal endothelial cells (2.8 %). They play a crucial role in regulating liver functions such as immunity, liver regeneration and maintenance of homeostasis. Thus, heterotypic co-culture of PHHs with primary stellate cells and human umbilical vein endothelial cells (HUVECs) not only enables maintenance of hepatocyte morphology and enhancement of their specific functions (albumin production, urea synthesis, xenobiotic metabolism) but also the formation of capillary-like structures (Salerno et al. 2011). Approaches based on micropatterning techniques, in which hepatocytes are seeded onto collagen spots surrounded by support cells, such as fibroblasts, also help stabilize liver functions (March et al. 2015; Trask, Moore, et LeCluyse, 2014). Hepatocytes cultured in this way show better differentiation and increased sensitivity for predicting xenobiotic toxicity than when
conventionally cultured (Khetani et al. 2013).

### 3.1.1.2. Conventional two-dimensional (2D) culture models and limitations.
Traditionally, hepatocytes are cultured on plastic substrates coated or not with collagen and covered with a culture medium (Andria et al. 2010). The 2D culture of PHHs offers many advantages and has long been considered the "gold standard" in preclinical studies for detecting drug hepatotoxicity, metabolism, and genetic polymorphism (Soldatow et al. 2013). It is easy to use and cost-effective; it can be used under standardized conditions, making it useful for high-throughput screening (Tutty, Movia, et Prina-Mello, 2022). However, one of its major limitations is that PHHs cultured in 2D rapidly lose their hepatocyte-specific functions and phenotype, including metabolic activity and gene expression (Hewitt et al. 2007). Moreover, 2D models fail to replicate the complex microenvironment encountered in vivo. To bridge the gap between 2D models and animal studies, 3D culture models have been developed to study the effect of xenobiotics in a more complex environment, and to achieve maximum differentiation of human liver cells.

### 3.1.1.3. Three-dimensional (3D) cell culture models.
To replicate the liver's 3D architecture and improve hepatocyte differentiation and survival, 3D cell culture models including spheroids and organoids have been developed. Spheroids are defined as aggregates formed by a single cell type, while organoids are aggregates formed by several parenchymal and non-parenchymal cell types (Kammerer, 2021). In 3D cultures, cells adhere and regain a natural morphology and polarity, improving differentiation and viability (Ishida-Ishihara et al. 2022; Jensen et Teng, 2020).

Spheroids and organoids can be cultured in scaffold-free or scaffold-based systems (Fig. 4). Scaffold-free models are based on the self-

aggregation capability of liver cells into spheroids or organoids without any material mimicking the ECM. Systems such as ultra-low attachment plates, gravity forces, magnetic action enables the establishment of intercellular contacts and leads cells to secrete their own matrix components (Godoy et al. 2013). *In vivo*, the ECM plays an essential role in maintaining tissue structure, hepatocyte polarization, cell signaling, and differentiation (Ye et al. 2019). *In vitro*, scaffold-based models rely on the use of a physical support in which cells are embedded. The support aims to mimic certain essential features of the ECM, and their physicochemical properties have an impact on cell morphology and functionality (Xu, 2021; Guilak et al. 2009). Compared with conventional 2D cell culture, cells grown in hydrogels regain morphological characteristics and functional capacities close to those in their natural microenvironment. A large number of natural and synthetic hydrogels have been optimized for cell culture. Their composition and physical properties make them the most suitable option for mimicking the mechanical and diffusion properties of ECM (Tibbitt et Anseth, 2009).

Natural hydrogels used for culture are extracted directly from animal or plant tissues (Ravi et al. 2015; Worthington, Pochan, et Langhans, 2015). They can be classified into 3 main categories according to their chemical nature: hydrogels based on proteins present in quantity in the ECM, polysaccharide-based hydrogels and decellularized ECM (Fig. 4). Most protein- or peptide-based hydrogels used in culture are structural proteins of the ECM, responsible for the matrix's tensile strength and elasticity. They are biocompatible, low in toxicity and induce low inflammatory and immunogenic responses in vivo (Dawson et al. 2008), while also being bioactive, containing growth factors and arginine-glycine-aspartic acid peptide motifs that bind integrin receptors, and promote numerous cellular functions such as viability and proliferation (Liu et al. 2014; Ruedinger et al. 2015). The most widely

<figure><img src="image_5.png" /><figcaption>**Fig. 4.** The principle of scaffold-free and scaffold-based 3D cell culture techniques. For scaffold-free 3D cell culture, commonly used techniques include static suspension cultures, agitation or rotation cultures, hanging drops, low-adhesion plates, and magnetic levitation. For scaffold-based 3D cell culture, natural hydrogels are derived from living organisms and can be peptide- or protein-based, such as collagen, gelatin, and elastin. Others are polysaccharide-based, like glycosaminoglycans, hyaluronic acid, alginate, or cellulose. The most commonly used synthetic hydrogels are polyethylene glycol (PEG) and polyvinyl alcohol (PVA) and, to a lesser extent, polyurethane (PU), polycaprolactone (PCL), polyglycolic Acid (PGA), polytetrahydrofuran (PTHF) and polyethylene perephthalate (PET).</figcaption></figure>
used hydrogels for 3D liver cell culture are Matrigel and type I collagen (Glowacki et al. Mizuno, 2008; Orgel et al., 2014; Pathak et al. Kumar, 2011). It has been shown that modifying collagen concentration modulates matrix stiffness and porosity and influences cell differentiation and proliferation in normal and transformed human liver cells (Bomo et al. 2016; Rose et al. 2021). However, as with any natural product, the complex composition of these matrices is often ill-defined and variable, making it difficult to accurately determine the factors likely to influence cell phenotype (Cushing et al. Anseth, 2007). These factors have encouraged the development of synthetic hydrogels (Peppas et al. 2006; Thiele et al. 2014) whose composition is perfectly controlled (Andria et al. 2010) (Fig. 4).

One example of a 3D cell culture model is HEPOID®, a 3D human hepatocyte culture model developed by S. Langouët's team. Various cell types including PHHs (Rose et al. 2021) or transformed hepatocytes such as HepaRG (Rose et al. 2022) and HuH7 (Bomo et al. 2016) cell lines are cultured in a collagen matrix and organize into a monolayer to form small hollow spheroids that measure approximately 50 µm after 28 days of culture. Under these conditions, it was discovered that PHHs are able to undergo several proliferation cycles. Both PHHs and cell lines maintain this organization while proliferating (Rose et al. 2021). These characteristics distinguish them from traditional larger spheroids measuring up to 200 µm, where oxygen diffusion to the spheroid's center is limited, causing necrosis (Xu, 2021). HEPOID® with the HepaRG cell line can quickly differentiate within a week without DMSO treatment, with gene expression, enzyme activity, albumin, and urea secretion functions, as well as polarity, comparable to DMSO-differentiated 2D HepaRG. They can proliferate while maintaining their phenotype for at least 28 days of culture. The hepatocytes are sensitive to both low and high doses of hepatotoxic and steatosis-inducing molecules, as well as genotoxic agents (Rose et al. 2021). This demonstrates that 3D human hepatocyte culture models are suitable for long-term treatments at doses close to real-life exposure levels, making them valuable for studying the toxicity of environmental contaminants in mixtures. For example, the effects of PFAS have been studied recently individually (Bernal et al. 2024) and in mixtures (Addicks et al. 2023) on human liver spheroids.

Some of these natural and synthetic hydrogels can also be used for 3D bioprinting, which involves assembling biomaterials in complex structures layer by layer (Fig. 4). This technique allows for precise control over the spatial organization of different cell types in the matrix, thus closely mimicking the structure of tissues and organs in vivo with a high repeatability (Grix et al. 2018; Taymour et al. 2021). It has been shown that co-culturing hepatocyte-like cells derived from iPSCs with endothelial and mesenchymal cells, bioprinted within a hexagonal matrix with dimensions resembling hepatic lobules, improves hepatocyte organization, and significantly increases hepatospecific gene expression levels (albumin, HNF4α), metabolic secretions (albumin, urea) and induction of CYP3A4, CYP2C9 and CYP2C19 (Ma et al. 2016).

#### 3.1.1.4. 3D culture in dynamic conditions.
Compared to static 3D culture models, it is now established that in dynamic perfusable models, flow rate and shear forces significantly impact hepatocyte differentiation and the establishment of physiological gradients in oxygen, nutrients, growth factors and waste products (Dash et al. 2013; Rashidi et al. 2016; P. Roy et al. 2001). Culture in perfusion systems enables mass transfer and environmental control of hepatocytes. Cells undergo much smaller variations in pH, oxygen and medium composition than in static culture systems. Continuous addition of nutrients and removal of metabolic by-products are ensured by an automated perfusion system (Tostões et al. 2012). Several devices can be adapted to dynamic conditions, including bioreactors (Beckwitt et al. 2018; Zeilinger et al. 2004) or microfluidic chips (Rennert et al. 2015; Kimura, Sakai, et Fujii, 2018), each enabling mono or co-culture of liver cells (Fig. 4). The use of bioreactors efficiently produce large quantities of uniform spheroids, under

controlled supply conditions, with rotating wall vessels preferred over spinner flasks as they create a microgravity environment by rotating along the x-axis and reduce shear stress (Phelan et al. 2019). Finally, microfluidic devices are sophisticated systems that use microchannels to deliver continuous perfusion to cells grown in 3D. This perfusion generates a dynamic microenvironment by applying physiological shear forces on the cells, enhancing intercellular interactions to promote differentiation and proliferation. A common limitation of some 3D cell cultures is poor oxygenation; perfusion enhances oxygen delivery, reducing central necrosis within spheroids (Ahmed et al. 2019). The flow delivers oxygen and nutrients while removing carbon dioxide, metabolites and waste products, mimicking the dynamics of a hepatic sinusoidal capillary. However, the high technicity and the specific equipment required for perfused microchips restrict their use to specific applications.

#### 3.1.1.5. Challenges and prospects of 3D models and their applications in the study of exposome and chronic liver diseases.
The three main applications of 3D liver cell models include studying hepatotoxicity as well as drug and contaminant metabolism, developing disease models, and hepatocyte transplantation for regenerative medicine (Xu, 2021). For hepatotoxicity studies, a major challenge in 3D human liver cell culture is creating more complex models that closely imitate the human liver microenvironment. An ideal model should be robust, reproducible, user-friendly, automatable, high-throughput, and cost-effective (Gupta et al. 2016). Numerous laboratories are advancing towards this goal.

Combining the aforementioned culture methods brings together the benefits of different techniques to create complex human liver cell models. For example, liver spheroids or organoids cultured in microfluidic devices enhance hepatocyte differentiation and functionality, increasing their sensitivity to tested molecules (Cong et al. 2020). Furthermore, 3D bioprinting can improve liver models by organizing hepatocytes into lobules. Integrating vascularization with blood vessels and bile ducts remains a key challenge in bioprinting (Taymour et al. 2021). One notable study demonstrated that bioprinting techniques using hepatocytes and stellate cells can recreate the hexagonal hepatic lobule structure with perfusable channels in a microfluidic system. Researchers are now looking to incorporate endothelial cells into the channels to mimic hepatic sinusoids (Grix et al. 2018).

In evaluating the effects of the exposome on human health, 3D liver cell models are critical for assessing the impact of mixtures under conditions resembling real-life exposure. These models enable repeated administrations for long-term studies, are sensitive to low-dose treatments and accurately mimic the human liver microenvironment. Furthermore, 3D culture techniques enable the modeling of complex liver diseases, such as MASLD, by partially replicating the inflammatory and fibrotic components. Animal models are predominantly used to study liver fibrosis due to the complexity of its pathogenesis, which involves multiple cell types and inflammatory mediators that influence the activation of stellate cells. Moreover, 3D human liver cell models can also contribute to the development of *in vitro* fibrosis models. Examples include the co-culture of hepatocytes and non-parenchymal cells in microfluidic systems and organoids derived from induced human pluripotent stem cells cultured in Matrigel®. In these models, a sequence of steatosis, inflammation, and fibrosis can be observed in response to fatty acid treatment (Lee et Seki, 2023). To recapitulate *in vivo* physiology, a key challenge in developing *in vitro* pathological models is to better represent the complexity of the inflammatory process (Macedo et al. 2023), by modeling the different compartments of the liver including the space of Disse or sinusoidal capillaries, and the migration of immune cells between compartments during inflammation and fibrosis (Koyama et Brenner, 2017). Overall, 3D models offer promising tools to study the effects of environmental contaminants on liver disease.
### 3.1.2. *In silico* modelisation for toxicological research and risk assessment

In the field of toxicology and risk assessment, *in silico* modeling aims to predict the toxicity of various chemicals using computational tools without the necessity of performing tests using *in vitro* or *in vivo* models. *In silico* approaches are based on structural similarity by grouping structurally close molecules, but also on chemical reactivity (Hemmerich et Ecker, 2020; Raunio, 2011). Quantitative Structure-Activity Relationship (QSAR) models relate the chemical structure of a compound to its biological activity. By analyzing known data on similar compounds, QSAR models can predict the toxicity of new chemicals. The Read-Across method uses data from similar chemicals or analogues to predict the properties and toxicological profiles of a new compound that lacks toxicological data. It assumes that similar chemicals have similar biological effects (Raunio, 2011).

Therefore, *in silico* modelling is particularly useful to predict the toxicity for structurally close molecules such as PFAS or HAAs that occur in mixtures. For example, a recent screening study investigated the binding interactions between 9000 different PFAS and the nuclear receptors VDR, PPARγ, PXR, and ERα, suggesting that PFAS have high binding affinities to these receptors, displacing endogenous or native ligands. Mixtures of PFAS could engage in competitive interactions and eventually saturate the system, resulting in either additive, synergistic or antagonistic outcomes (S. Roy et al. 2024). Regarding HAAs, given the diversity of metabolites, *in silico* modeling approaches using bioinformatic tools and predictive models have been developed to predict MeIQx metabolic pathways in the liver (Delannée et al. 2017). Another study developed a modeling approach to predict which HAAs' metabolites can bind to DNA by using different enzyme profiles. These tools

have potential applications to predict the genotoxicity of other contaminants (Conan et al. 2021).

### 3.2. Contribution of predictive toxicology on chemical mixture studies

Although the effects of individual PFAS has been extensively studied, there remains a significant gap in understanding the toxicity of their mixtures and their molecular interactions, constituting a challenge in risk assessment (Ojo et al. 2021). Recent research has combined NAMs with traditional *in vitro* models to predict the toxicity of PFAS mixtures as shown in Table 1. We focused on studies on PFAS mixture toxicity with an emphasis on liver-related effects. Additionally, we prioritized *in vitro* mechanistic studies to better understand the molecular pathways involved. It can be noted that mixture studies show inconsistencies in interactions and unpredictable responses, with either synergistic, antagonistic or additive outcomes. These inconsistencies can be attributed to numerous factors, including concentrations, mixture composition and ratios, biological models and endpoints (Ojo et al. 2021; Addicks et al. 2023). The diversity of biological endpoints such as mRNA expression levels, protein expression, or activity, cytotoxicity or genotoxicity can exhibit incoherent results. Mechanisms involved in mixtures are complex as they may involve multiple steps of drug metabolism or non-monotonic dose-responses (Goedtke et al. 2021).

A major challenge in studying chemical contaminant mixtures is defining and replicating environmentally relevant compositions, as combinations of chemicals are complex and often remain unidentified in real life. Differences in regional exposures, individual metabolic variations, and co-exposures further complicate mixture studies. Based on the

<table><caption>**Table 1**

In vitro studies on the hepatotoxic effects of PFAS mixtures.</caption><thead><tr><th>Chemical mixture and doses</th><th>Duration</th><th>Model/Tool used for mixture prediction</th><th>Endpoint/Outcome</th><th>Nature of interaction</th><th>References</th></tr></thead><tbody><tr><td>PFOA, PFOS, PFBA, PFHxA, PFHpA, PFNA, PFDA, PFUnA, PFBS, PFHxS, PFAS, 6:2 fluorotelomer sulfonate, 8:2 fluorotelomer sulfonate, PFOSA<br>Up to 100 µM</td><td>Short-term exposure: 24 h<br>Long-term exposure: 10 days</td><td>Human hepatocytes spheroids<br>Principle of concentration addition</td><td>- Gene expression perturbations<br>- Oxidative stress<br>GSH depletion<br>No significant ROS production<br>- Dose-dependent cytotoxicity</td><td>Additive</td><td>(Addicks et al. 2023)</td></tr><tr><td>Binary mixtures<br>PFOS, PFOA, PFDA, PFNA, PFHxS<br>0.2, 2, 20 µM</td><td>24 h</td><td>HepG2 cells</td><td>- Genotoxicity of PFAS mixtures<br>Slight increase in DNA damage without dose-response relationship<br>- Dose-dependent cytotoxicity</td><td>Not significant</td><td>(Ojo et al. 2021)</td></tr><tr><td>Binary mixtures<br>PFNA<br>PFOS<br>PFDA<br>PFOA<br>PFHxS<br>0-400 µM<br>PFOS<br>PFOA<br>PFHxA<br>2.5-300 µM</td><td>24 h</td><td>HepG2 cells<br>Additive index approach</td><td>- Altered miRNA signatures: miRNA involved in hepatic fibrosis and hepatocellular carcinoma<br>- Prediction of PFAS mixture toxicity and chemical interactions<br>- Measurement of developmental toxicity on zebrafish embryos</td><td>Synergistic or additive</td><td>(Ojo, Peng, et al. 2022)</td></tr><tr><td>Binary mixtures<br>11 chemicals including PFOS (0-40 µM) and PFOA (22, 38, 68 µM)</td><td>1-4 days post-fertilization</td><td>NAM combining machine learning method (hybrid neural network AI-HNN) and pathophysiology method (Chemo-Phenotypic Based Toxicity Measurement CPTM)<br>Experimental dose-response zebrafish-embryo assays</td><td>- Cytotoxicity assessment<br>- Phospholipidosis assessment</td><td>Not determined</td><td>(Carberry et al. 2024)</td></tr><tr><td>Binary / ternary mixtures<br>Cytotoxicity:<br>PFECHS 1-1935mg/L<br>PFOS 0.5-685 mg/L<br>FBSA 1.3-2550 mg/L<br>Lipid quantification: PFOS 0.8-1665 mg/L<br>PFECHS 0.97-1935mg/L</td><td>24 h</td><td>Immortalized rainbow trout gill cell line (RTgill-W1)<br>Mixture predictions following the Loewes Additivity and Steel and Peckham methods</td><td>- Acute toxicity test for each species following OECD guidelines</td><td>Synergistic in both experimental and prediction models<br>Cytotoxicity: additive or synergistic depending on concentration and mixture composition<br>Phospholipidosis: additive</td><td>(Limbu et al. 2024)<br>(Mahoney et al. 2024)</td></tr><tr><td>Binary mixtures<br>PFOS, PFNA, PFBS, PFBA<br>31.25-1000 mg/L</td><td>96 h<br>24 h, 48 h</td><td>Raphidocelis subcapitata<br>Daphnia magna</td><td>- Acute toxicity test for each species following OECD guidelines</td><td>Additive or antagonistic</td><td>(Pietropoli et al. 2024)</td></tr></tbody></table>
studies presented in Table 1 and Table S1, many research select mixture components based on their presence in the environment or in human biomonitoring studies. However, to enhance the relevance of mixture studies, it is essential to also consider the mechanisms of action and shared biological targets of the selected compounds. The liver, as a central hub for metabolic processes, is particularly susceptible to chemical interactions, with nuclear receptors serving as key molecular targets. Understanding how multiple contaminants interact at these converging sites could help elucidating the mechanisms underlying synergistic, additive and antagonistic effects. Future exposome research should integrate exposure data with mechanistic toxicology to refine mixture selection and improve relevance of human health risk assessment.

Additionally, the concentrations and the duration of studies vary, making the interpretation and the comparison of outcomes difficult (Table 1). A critical aspect in exposome research, more specifically in the interpretation of PFAS mixture toxicity, is the relevance of experimental exposure concentrations to real-world human exposure. As presented in Table 1 and Table S1, many *in vitro* and *in vivo* studies are conducted over a short period of time, often utilizing concentrations in the micromolar range or doses higher than those detected in human biological samples, which typically fall within the nanomolar range. While such studies provide mechanistic data, these results must be carefully interpreted when assessing human health risks as they may not accurately reflect the reality of environmental exposures. To ensure human relevance, experiments should be conducted based on biomonitoring data using environmentally realistic concentrations. This is particularly important for EDCs since they are known for non-monotonic dose-response. Still, the challenge remains in determining dose extrapolation methods that takes into account toxicokinetics data, exposure and mixture interactions all together.

In this context, *in vitro-to-in vivo* extrapolation (IVIVE) could help linking experimentally observed effects to real-world exposure levels. Based on PBPK models that include pharmacokinetic data of the target chemical, IVIVE aims to predict *in vivo* doses and health effects using *in vitro* experimental data. This approach enables a more accurate comparison between experimental concentrations and human exposure levels and therefore ensures that toxicity assessments remain relevant to real-world human exposure (Bell et al. 2018). IVIVE research is currently emerging and for the past 5 years, studies have been conducted to predict various toxicities, including hepatotoxicity as well as classic endocrine-disrupting effects (Han et al. 2024). Given the gaps in mechanistic knowledge of PFAS hepatotoxicity and the challenges in comparing and integrating various results, IVIVE could help improve the interpretation of toxicological findings and strengthen risk assessment of PFAS and their mixtures.

The Integrated Approaches to Testing and Assessment (IATA) involves combining new data from NAMs or from traditional methods with data from existing literature data to assess risks while minimizing animal testing (OECD, 2017). For instance, integrating data from multiple "omics" methods helps visualizing disruptions at the molecular level in response to chemicals, and omics approaches can also be combined with *in vitro* or *in vivo* methods. All of these elements contribute to the enrichment of Adverse Outcome Pathways (AOPs) (Schmeisser et al. 2023), which integrate and organize data at multiple biological levels in order to understand the mechanisms leading to adverse events. AOPs describe the sequence of events, from molecular interaction to key events and adverse effects at the organism level (Caloni, De Angelis, et Hartung, 2022). These are particularly useful for addressing mixture effects, as they enable molecules to be linked to specific stages of the AOPs and identify converging points to detect potential interactions, which could result in additive, synergistic or antagonistic effects (Barouki et al. 2022). AOPs can also help in constructing IATAs. For example, links between exposure to PFAS and metabolic outcomes have been identified from an automatic screening of the literature including *in vitro*, *in vivo* and human studies by using a computational tool called

AOP-helpFinder. This will help building AOPs related to PFAS and liver diseases in the future (Kaiser et al. 2022).

## 4. Prevention

Currently, there are few effective and targeted treatments for chronic liver diseases. The most effective treatment for early-stage HCC is liver resection. At advanced stages, systemic treatments are promising, but none specifically target a gene mutated in HCC. Moreover, obesity is a major cause of MASLD and HCC. Since MASLD is reversible, the preferred treatment is weight loss through calorie restriction and increased physical activity. However, losing weight and maintaining a stable weight is challenging, and other factors than excess calorie intake may contribute to weight gain. Given the growing evidence of the role of environmental contaminants in the development of chronic liver diseases, preventing these diseases requires reducing exposure to environmental contaminants, which are risk factors for these conditions.

To implement preventive measures, it is first necessary to identify and classify these compounds. Regarding EDCs, the challenge lies in harmonizing the criteria to identify and classify new substances as EDCs. The European Commission has included new hazard classes for EDCs within the classification, labeling, and packaging (CLP) regulation. Starting from April 2023, the new regulation requires manufacturers, importers and distributors to classify their chemical substances based on these new hazard classes. This enables to communicate the risks associated with EDCs to consumers and to manage the associated dangers. This advancement could help reduce exposure to substances labeled as EDCs (European Chemicals Agency, 2023). With the aim of reducing exposure to PFAS and the adverse health effects associated with these compounds, the United States Environmental Protection Agency or US EPA has announced the National Primary Drinking Water Regulation on April 2024. This new regulation imposes "maximum contaminant levels" for 6 PFAS in drinking water, making monitoring of PFAS levels mandatory for public water systems, which will have to inform the public of PFAS levels by 2027 and find solutions to reduce them by 2029 if maximum contaminant levels are exceeded.

Since we are inevitably exposed to complex mixtures of environmental contaminants on a daily basis, some of which are persistent and bioaccumulative, reducing exposure is not sufficient to prevent the onset of chronic liver diseases. Another approach is chemoprevention, which involves using natural, synthetic or biological molecules to prevent, reverse, or slow down carcinogenesis (Steward et Brown, 2013). As HAAs exert their genotoxic effects through metabolic activation, it is possible to modulate XME expression to favor detoxification over bioactivation pathways. Certain dietary compounds alter the expression of XME. For example, caffeine mitigates the genotoxic effects of some HAAs by inhibiting CYP1A2, the enzyme primarily responsible for HAAs bioactivation (Woziwodzka, Goluński, et Piosik, 2013). Various dietary molecules induce GST, which increases the elimination of substances as glutathione conjugates, making them useful in chemoprevention (Higgins et Hayes, 2011). Phenethyl isothiocyanate found in cruciferous vegetables can reduce PhIP's genotoxicity by inducing GST expression (Dingley et al. 2003). Lastly, flavonoids and phenolic compounds in plants and fruits have antioxidant properties that act as scavengers of free radical produced during the formation of HAAs and inhibit their formation (Teng et al. 2023).

Identifying hazard is a crucial step in prevention. The introduction of regulations makes it possible to communicate these hazards to consumers and take preventive measures to reduce human exposure to environmental contaminants on a global scale. On an individual level, this awareness could encourage people to change certain lifestyle habits, such as opting for foods that help eliminate contaminants and reduce their harmful effects on health.
## 5. Conclusion and future directions

Understanding the impact of the exposome on human health requires an integrative, multidisciplinary approach. Toxicology at the cellular and molecular level play a key role in uncovering the mechanisms underlying biological effects. This must be complemented by analytical approaches to detect and quantify both external and internal contaminant exposure, as well as to identify biomarkers of exposure and effect. Additionally, epidemiological studies remain essential for establishing associations between human exposure and health outcomes. Finally, computational methods are increasingly necessary to manage large amounts of data generated from omics studies and to develop predictive mathematical models.

Our review highlights the potential for certain well-studied PFAS, notably PFOA and PFOS, to enhance hepatotoxic effects, particularly in the context of chemical mixtures. We also emphasize the growing relevance of predictive toxicology tools such as NAMS, AOPs, and IVIVE. These tools contribute to refine risk assessment and bridge gaps between *in vivo*, *in vitro* and *in silico* data obtained experimentally and real-world human exposures, moving toward more human-relevant and ethical approaches to toxicity testing.

The goal is to assess the toxicity and risks of a wide range of chemical substances in a more efficient, cost-effective and human-relevant way, while reducing animal testing. Ultimately, by improving the accuracy of toxicity assessments, we can implement preventive measures to protect public health in a continuously evolving environmental landscape.

### Funding sources

Studies were funded in part by Inserm and University of Rennes, as well as from the French National Research Program for Environmental and Occupational Health of Anses with financial support from ITMO Cancer of Aviesan (National Alliance for Life Sciences & Health) within the framework of the 2021–2030 Cancer Control Strategy, on funds administered by Inserm (ANSES-23-EST-117). MC benefits for the University of Rennes doctoral fellowship.

### CRediT authorship contribution statement

**Langouet Sophie:** Writing – review & editing, Supervision, Resources, Project administration, Funding acquisition, Conceptualization.
**Rose Sophie:** Writing – review & editing. **Choi Minna:** Writing – original draft, Investigation, Formal analysis.

### Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgements

We greatly appreciate the support for this study provided by the National Institute of Health and Medical Research (Inserm), University of Rennes and Anses. The authors would also like to thank Catherine Lavau for her careful reading of the manuscript.

### Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.tox.2025.154167.

### Data availability

No data was used for the research described in the article.

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