Genomics is a well-established field that investigates an organism’s genome or complete set of DNA, including all of its genes²⁶. In recent decades, the field has substantially evolved largely as a result of the increased access of technologies that allow for sequencing the human genome in its entirety, or more commonly of the exome, i.e., all the expressed genes in the genome. The genome each of us inherits is virtually unchanged across our lifespan; however, variation does exist between individuals including in single nucleotide polymorphisms (SNPs) and insertions/deletions (INDELs). The genetic variation in SNPs and INDELs among individuals can be measured to generate large-scale data that may serve to signal risk to common chronic diseases²⁷ and be used as a marker for risk prediction. Gene-environment (G X E) interactions – the interplay between the environment and the human genome²⁸ – is the concept that the genetic makeup of an individual determines their susceptibility or resistance to adverse effects in the presence of certain environments²⁹. A well-known clinical example of G X E interaction is that of patients with phenylketonuria (PKU) who have a mutation in the gene coding for phenylalanine hydroxylase, the enzyme that metabolizes phenylalanine, an essential amino acid obtained from dietary sources. This genetic mutation leads to an accumulation of high levels of phenylalanine and consequently to neurotoxicity with concomitant mental retardation³⁰. The G X E concept can be similarly applied to the EDC context where genetic differences may make individuals more susceptible to the effects of environmental chemicals. For example, there is evidence to suggest that genetic polymorphisms modify the anti-androgenic effect of dioxin exposure through differential aryl hydrocarbon-receptor activation resulting in male reproductive disturbances²⁹. Recently, Dunaway et al. explored G x E interactions with polychlorinated biphenyl (PCB) exposure and autism risk. Specifically, they performed genome-wide identification of PBC associated methylation changes to investigate genetic interactions. They identified specific genes involved in autism spectrum disorder (ASD) with altered PCB-related methylation. They concluded that gene-specific epigenetic vulnerability to both genetic and environmental hits are important in identifying different ASD etiologies, and further suggest that such knowledge can be used to develop targeted, individual treatment options ³¹. While the application of G x E to EDC research is still new, this salient example demonstrates the utility of omics methods to identify at risk groups based on genetic and EDC profiles and proposes using such data toward precision medicine for an outcome with a large public health burden. However, enthusiasm over G x E studies over the last decade has been replaced with caution and skepticism given the inconsistencies in results and null findings.

As technologies continue to evolve, the strengths of both developed and emerging omics methods will need to be considered in light of their inherent limitations. In Table 1, we present relevant omics methods and outline the strengths and limitation to their application. For a more extensive discussion on genomics and the role of genetics in determining susceptibility to toxicants, including EDCs, we refer to prior works.^32–35

Epigenomics investigates biological mechanisms that change gene expression. If we consider the DNA sequence to be inheritable and fixed, then epigenetic modifications are the markings of this sequence that alter its expression. These marks themselves can be persistent and heritable while they do not change the actual genetic sequence³⁶. In the epigenetics context, ‘persistent’ and ‘heritable’ refer to both the persistence of these marks between parent and daughter cells as well as the inheritance of these marks between parents and offspring. Therefore, one of the underlying properties of epigenetic modifications is that once they are established they do not disappear after the genome is duplicated, but—instead—they can propagate and persist through cell division. DNA methylation and histone modifications are the two epigenetic modifications interrogated in most human studies. DNA methylation is the addition of a methyl group to a cytosine base commonly followed by a guanosine base resulting in a cytosine-phosphate-guanine dinucleotide (CpG)³⁷. Gene-silencing is the best known DNA methylation related mechanism of gene regulation: within the promoter-associated regulatory regions of a gene, the presence of increased methylated CpGs can down-regulate expression of that gene³⁷. However, DNA methylation is not always associated with gene repression. For instance, within the gene body, high levels of methylation are highly correlated with up-regulation of gene expression³⁸.

Today, genome-scale platforms that measure millions of methylation sites are readily available with choices that balance depth of information per sample with sample size and cost (Table 1). DNA methylation has become the more frequently studied epigenetic mark in EDC research because of the availability of robust laboratory methods for analysis³. Large human epidemiologic studies known as epigenome-wide methylation studies often opt for platforms with lower costs per sample, such as the Illumina Infinium Methylation Beadchip, which in its current configuration measures DNA methylation at ~850,000 methylation sites³⁹. Smaller sample sizes in clinical studies have increasingly selected platforms based on deep-sequencing, such as candidate gene pyrosequencing or sequence specific bisulfite sequencing. For instance, Dao et al examined maternal exposure to PBDEs—a class of flame retardants—and promoter methylation in the tumor necrosis factor alpha (TNFa) gene in cord blood⁴⁰. Higher maternal serum concentrations of PBDE47 were associated with lower cord blood methylation in the TNFa promoter region⁴⁰. These results suggest that maternal PBDE47 exposure could alter the CpG methylation in the promoter region, which may lead to altered gene expression of TNFa⁴⁰. Studies such as this could provide a basis from which additional biomarkers could be developed for the purpose of improving EDC exposure characterization and risk assessment. Epigenome-wide methylation methods can measure higher numbers of methylation sites and – at higher cost – can even provide complete coverage of all the 28 million methylation sites in the human genome⁴¹. The main advantage of epigenome-wide methylation profiling lies in its ability to determine absolute DNA methylation levels that cover ~95% of the DNA methylome. This method, however, is subject to high costs, is dependent on technical expertise, and has downstream computational requirements³⁸ (see Table 1 for additional examples of epigenomics methods and their strengths and limitations).

While a biomarker reflecting past EDC exposure has yet to be developed and validated, a well-studied example in the tobacco literature provides a potential model. DNA methylation from exposure to tobacco smoke has led to the development of the first known omics biomarker that reflects detailed personal exposure history. Traditionally, assessment of smoking has primarily relied on self-reported data or urinary cotinine measures; however personal recall of smoking is prone to bias and cotinine is largely a reflection of recent tobacco consumption⁴². A seminal study by Joubert and colleagues identified 26 CpG sites in cord blood that were significantly different among mothers who smoked during pregnancy compared with non-smokers⁴³. Furthermore, a meta-analysis examining 13 cohorts found 6,073 CpG sites differed significantly based on maternal smoking status, and these sites also comprised those identified by Joubert⁴⁴. Both studies identified cg05575921 – a CpG locus that maps to the aryl hydrocarbon receptor repressor (AhRR) gene and known to be activated by tobacco smoking – as the single most significant site. A combination of studies on adult populations have demonstrated that AhRR methylation is associated with not only smoking status (current, former or never), but also with the average number of cigarettes smoked, years of smoking, pack-years of smoking and—among those individuals who quit—years since quitting^43,45,46. While such a biomarker should be evaluated with similar exposures including non-tobacco smoke, DNA methylation of the AhRR receptor may be a potentially useful biomarker to predict past exposure, and has provided motivation for researching DNA methylation biomarkers responsive to EDC exposures. Despite the fact that DNA methylation is a well-developed technology, applying methylation data of specific genes to categorize or predict exposure to EDCs is still new and requires further study and development. Several large human cohorts that assessed EDC exposures have now also generated epigenome-wide methylation data; we expect that a wave of results on the association of EDC exposure and DNA methylation is forthcoming. It is anticipated that results from these new studies will be applied toward gaining understanding on the interrelationship between EDCs and DNA methylation and identifying potential biomarkers.

Transgenerational epigenetic inheritance consists of phenotypic expression transmitted across generations via gametes through epigenetic marks but independently of the genome sequence. Evidence from animal models suggests that environmental stressors, including some EDCs such as pesticides, persistent organic pollutants, and others^47,48_ENREF_43, can lead to adverse health outcomes among descendants not directly exposed^49–51_ENREF_38. Many examples of transgenerational inheritance occur in rodent models^52–54. One study examining di-(2-ethylhexyl) phthalate (DEHP) exposure to F0 pregnant female rats led to the multigenerational inheritance of cryptorchidism (undescended testes). A statistically significant up-regulation of three kinds DNA methyltransferases (Dnmt1, Dnmt3a, and Dnmt3b) was seen in the progeny F1 and F2 male rats’ testes compared to controls⁵². The main effects were shown in the F1 and F2 generations, however no effect was observed in the F3 and F4 generations. This pattern suggests that the observed phthalate effects may be due to direct exposure of the fetus and its gamete cells in utero rather than to genuine transgenerational inheritance. Indeed, the gametes that will generate F2 are already present in the F1 embryo in utero and may be reprogrammed at that stage to produce demonstrable effects in F2. A rodent study on methoxychlor, an insecticide and pesticide, demonstrated true epigenetic transgenerational inheritance of disease through certain sperm epimutations (differential DNA methylation regions). Only the F0 generation of gestating females was exposed to methoxychlor. Exposure in the F0 gestating females was associated with kidney disease, ovarian dysfunction, and obesity among the unexposed F3 generation descendants. This study also compared epigenetic changes in sperm between the control lineage and methoxychlor lineage F3 rats and found 37 epimutations that were significantly different between the two groups. These 37 sperm epimutations were further compared with exposures, such as other pesticides (DDT and DEET) and plastics (BPA and phthalates) and found that only 4 of 37 overlapped with methoxychlor. This suggests that the transgenerational sperm epimutations found in the F3 generation are exposure-specific and induced by methoxychlor⁵³. However, transgenerational epigenetic inheritance in humans is difficult to determine and requires demonstrating adverse effects of EDCs to the 3^rd generation offspring or beyond. Despite evidence in animals, exact mechanisms involved in epigenetic transgenerational inheritance are yet unknown. Designing and conducting human multigenerational studies is particularly challenging, not only because of the time required to follow-up multiple generations but also due to the difficulty of observing exposures and DNA methylation at the appropriate time windows across generations. Therefore, further research is needed to understand the extent to which multigenerational epigenetics inheritance operates in humans.

Investigation of the properties of the mitochondrial DNA (mtDNA) is a relatively new, yet promising field in environmental health and EDC research. Each human cell contains thousands of mitochondria, each carrying 2–10 copies of their own genome, a double-stranded circular mtDNA molecule of approximately 16kb in length. Mitochondria act as the cell’s power plant because they convert energy substrates derived from the breakdown of glucose and fatty acids into adenosine triphosphate (ATP)⁵⁵. The properties of mtDNA differ from nuclear DNA (nDNA), including the lack of histone-wrapping protection and limited repair mechanisms, making mtDNA more vulnerable to accumulating damage when exposed to environmental chemicals⁵⁶.

Mitochondrial damage can result from many sources, and damage can impact mitochondrial structure or function, as well as the mtDNA itself. Endogenous reactive oxygen species are a primary agent of mitochondrial damage and these can be amplified in the presence of an external pollutant source, including many environmental chemicals^57,58. When reactive oxygen species are produced past the point of homeostatic levels, oxidative stress can lead to alterations to mitochondrial structure as well as to its function, including abnormalities to electron transport chain activity, membrane potential, ion transport, and apoptotic signaling, which can ultimately lead to cell death⁵⁹. Several studies on sperm function found that abnormal mitochondria and structural alterations to mitochondria⁶⁰ or its sheath⁶¹ were associated with reduced sperm motility. Studies on the effects of EDCs on mitochondrial DNA are scarce. However, studies that showed effects on mitochondrial membrane potential (MMP), which has been extensively used to document mitochondrial dysfunction², suggest that EDC may affect mitochondria. For instance, one such study found that men with higher phthalate concentrations in semen had lower MMP, and lower MMP was further associated with semen quality⁵⁸. More recently, the US EPA Tox21 program assessed the potential for some environmental chemicals and pharmaceuticals to affect mitochondria dysfunction by measuring MMP. Among the greater than 8000 different chemicals that were tested in vitro, researchers found that 11% of these decreased MMP including certain classes of EDCs². While these studies to not provide information on whether EDCs affect the mitochondrial DNA, they do show that the mitochondria are an EDC target.

Damage to mtDNA has also gained attention in the field of mitochondriomics, with biomarkers being used to quantify mtDNA damage and dysfunction. Damaged mtDNA can co-exists with normal mtDNA copies in cells, and the influence of these mtDNA alterations can range between normal, mild and severe according to the proportion of abnormal mtDNA copies⁶². Biomarkers that measure damage and dysfunction include, among others, mtDNA copy number (a measure of abundance of mtDNA present compared to nDNA) and mtDNA lesions (the amount of damage present on the mtDNA genome)⁶². There are few studies that have examined mtDNA biomarkers in the context of EDCs, however one in vitro study found that cells treated with TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin), the most potent dioxin congener and a known endocrine disruptor, increased mtDNA lesions and reduced mtDNA copy number in the treated cells⁶³. Another study compared mitochondrial function in lymphoblast cells in relation to BPA exposure between children diagnosed with autism and their unaffected siblings. The authors examined several different markers of mitochondrial dysfunction including, MMP, mtDNA copy number in mitochondria genes. The results of this study suggest that among genetically susceptible children, BPA exposure may induce mtDNA dysfunction and act as an important environmental risk factor⁶⁴.

DNA methylation of the mitochondrial genome is growing in popularity as a potential biomarker in the study of EDCs, though controversies surround the existence and functionality of mtDNA methylation⁶⁵. Earlier studies—performed more than 30 years ago—reported no cytosine methylation on the mtDNA⁶⁶. Recently, Shock et al. showed the presence of mtDNA methylation and proposed a possible mechanism of action through DNA methyltrasferases translocating to the mitochondria following a mitochondrial targeting sequence⁶⁷. However, the unsophisticated structure of the mitochondrial genome has led to the belief that the mtDNA may lack the mechanisms that link DNA methylation with gene expression control in the nuclear genome.

While data in human populations are lacking, a recent animal study examined the epigenetic effects of low doses of PBDE47, a flame retardant chemical, demonstrating that prenatally exposed rats exhibited reduced DNA methylation of a specific mitochondrial gene compared to the control group⁶⁸. While mtDNA methylation is still largely understudied—partly due to technical limitations of using standard platforms typically used in nDNA methylation as well as to lingering doubts about its functionality⁶² – other measures of mitochondriomics remain a unique and novel field with potential utility in EDC research. Further development in miochondriomics technology and an expanded awareness of its potential and its limitations will help guide and generate new studies in this area (Table 1).

The central dogma of molecular biology posits that the information contained in genes flows from the DNA sequence to messenger RNA (mRNA) to proteins⁶⁹. Epigenetic regulation helps control the flow from the DNA into mRNA and, indirectly, into proteins. Proteins have many functions in eukaryotic cells varying from serving as structural components to facilitating transport and storage within the cells. Proteins also serve as enzymes that carry out nearly all the chemical reactions that take place in cells, including all those that transform metabolites. In the past two decades, laboratory technologies, including transcriptomics, proteomics and metabolomics methods, have increasingly allowed for characterizing these interconnected layers of cellular functions. In principle, these technologies—individually or in combination—can be used to determine a biological fingerprinting of EDC exposure⁷⁰. However, a major challenge of transcriptomics, proteomics and metabolomics is that given mRNAs, proteins, and metabolites are downstream in the central-dogma flow, they are also much more variable over time. Indeed, cells often need to adapt very rapidly in response to environmental conditions and homeostatic signals and consequently the downstream mechanisms that operate cellular responses are also able to change rapidly. Therefore, while these molecular substrates may reflect current exposures, they are less likely to reflect past exposures. In addition, standardized, easily accessible, high-throughput platforms, while existing for transcriptomics, are not readily available for proteomic and metabolomic applications. As a result, these three technologies have not found as much application in EDC research as per our previously outlined methods (see Table 1). For instance, a PubMed search (conducted on March 27, 2017) on “endocrine disrupting chemicals” yielded 56 papers for “transcriptomics OR mRNA microarray OR mRNA sequencing”, 46 for “proteomics”, and 32 papers for “metabolomics”. As a comparison, the same search retrieved 126 papers for “epigenetics and epigenomics” and 747 for “genetics OR genomics”. These search results suggest a limited application of transcriptomics, proteomics, and metabolomics technologies in EDC research thus far, despite the fact that they are extremely informative in understanding mechanisms of action and biological effects of EDCs.