In this review article, we compiled peer-reviewed literature describing PFAS exposure and reproductive effects in animals and humans. The aim was to compare environmental occurrence and effects of the most prominent long-chain PFAS compounds and their short-chain replacements. Long-chain PFAS compounds are known to persist in the environment due to their chemical stability, and also known to bioaccumulate; hence, these compounds are being replaced globally. Indeed, PFOA and PFOS are considered long-chain “forever pollutants,” and thus the potential reproductive risk may continue for decades. Much less is known about their short-chain replacements despite the fact that they becoming more widespread in the environment. Short-chain PFAS are generally less bioaccumulative than long-chain, but they are more mobile and persistent in aquatic ecosystems. The three most prominent of these are commonly referred to as GenX, ADONA and F53B. The short-chain PFAS have similar physical and chemical properties as their predecessors; however, because they are relatively new, much less is known about the potential to disrupt reproduction. Indeed, high-quality epidemiological studies are needed to determine associations between short-chain PFAS exposure and effects on reproductive health. However, epidemiological evidence is mounting that long-chain PFAS exposure is associated with reproductive effects (i.e., decrease in fertility, reduced fetal growth and birth weight, pregnancy-induced hypertension and preeclampsia, thyroid hormone disruption during pregnancy, and preterm birth). Evidence from animal models and human cell lines indicates that short-chain PFAS similarly affect reproductive endpoints; however, epidemiological studies are scarce and inconsistent. Although short-chain PFAS have been quantified in drinking water and sediment worldwide, most of these studies did not focus on quantitation of GenX, ADONA, and F53B. There are also many other short-chain PFAS byproducts of manufacturing that have yet to be identified and studied. When sum total concentration of long- and short-chain PFAS are considered, the concentration rises by an order or magnitude or greater, as will the risk of exposure and subsequent reproductive effects.

Anthropogenic endocrine-disrupting chemicals (EDCs) can contaminate air, soil, and water. Human exposures to EDCs occur through inhalation, absorption, and ingestion. EDCs act by disrupting various pathways in the endocrine system. When the hypothalamic–pituitary–gonadal (HPG) axis is disrupted by EDCs, there can be effects on fertility in both men and women. Not only can fertility be indirectly affected by EDC disruptions of the HPG axis, but EDCs can also directly affect the menstrual cycle and sperm morphology. In this review, we will discuss the current findings on EDCs that can be inhaled. This review examines effects of exposure to prominent EDCs: brominated and organophosphate flame retardants, diesel exhaust, polycyclic aromatic hydrocarbons, cadmium and lead, TCDD, and polychlorinated biphenyls on fertility through alterations that disrupt the HPG axis and fertility through inhalation. Although the studies included herein include multiple exposure routes, all the studies indicate receptor interactions that can occur from inhalation and the associated effects of all compounds on the HPG axis and subsequent fertility.

Pharmaceuticals have a wide range of biological properties and are released into the environment in relatively large amounts, yet little information is available regarding their effects or potential ecological risks. We exposed outdoor aquatic microcosms to combinations of ibuprofen (a nonsteroidal anti‐inflammatory drug), fluoxetine (a selective serotonin reuptake inhibitor), and ciprofloxacin (a DNA gyrase—inhibiting antibiotic) at concentrations of 6, 10, and 10 μg/L, respectively (low treatment [LT]); 60, 100, and 100 μg/L, respectively (medium treatment [MT]); and 600, 1,000, and 1,000 μg/L, respectively (high treatment [HT]). We maintained these concentrations for 35 d. Few responses were observed in the LT; however, effects were observed in the MT and HT. Fish mortality occurred in the MT (<35 d) and in the HT (<4 d). Phytoplankton increased in abundance and decreased in diversity (number of taxa) in the HT, with consistent trends being observed in the MT and LT. Zooplankton also showed increased abundance and decreases in diversity in the HT, with consistent trends being observed in the MT. Multivariate analyses for zooplankton and phytoplankton suggested interactions between these communities. Lemna gibba and Myriophyllum spp. showed mortality in the HT; growth of L. gibba was also reduced in the MT. Bacterial abundance did not change in the HT. All responses were observed at concentrations well below the equivalent pharmacologically active concentrations in mammals. Although the present data do not suggest that ibuprofen, fluoxetine, and ciprofloxacin are individually causing adverse effects in surface‐water environments, questions remain about additive responses from mixtures.

Endometrial cancer (EC) is the most common gynecological neoplasm in high-income countries. Five-year survival rates are related to stage at diagnosis, but currently, no validated screening tests are available in clinical practice. The metabolome offers an unprecedented overview of the molecules underlying EC. In this study, we aimed to validate a metabolomics signature as a screening test for EC on a large study population of symptomatic women. Serum samples collected from women scheduled for gynecological surgery (n = 691) were separated into training (n = 90), test (n = 38), and validation (n = 563) sets. The training set was used to train seven classification models. The best classification performance during the training phase was the PLS-DA model (96% accuracy). The subsequent screening test was based on an ensemble machine learning algorithm that summed all the voting results of the seven classification models, statistically weighted by each models’ classification accuracy and confidence. The efficiency and accuracy of these models were evaluated using serum samples taken from 871 women who underwent endometrial biopsies. The EC serum metabolomes were characterized by lower levels of serine, glutamic acid, phenylalanine, and glyceraldehyde 3-phosphate. Our results illustrate that the serum metabolome can be an inexpensive, non-invasive, and accurate EC screening test.

Colorectal cancer (CRC) is a high incidence disease, characterized by high morbidity and mortality rates. Early diagnosis remains challenging because fecal occult blood screening tests have performed sub-optimally, especially due to hemorrhoidal, inflammatory, and vascular diseases, while colonoscopy is invasive and requires a medical setting to be performed. The objective of the present study was to determine if serum metabolomic profiles could be used to develop a novel screening approach for colorectal cancer. Furthermore, the study evaluated the metabolic alterations associated with the disease. Untargeted serum metabolomic profiles were collected from 100 CRC subjects, 50 healthy controls, and 50 individuals with benign colorectal disease. Different machine learning models, as well as an ensemble model based on a voting scheme, were built to discern CRC patients from CTRLs. The ensemble model correctly classified all CRC and CTRL subjects (accuracy = 100%) using a random subset of the cohort as a test set. Relevant metabolites were examined in a metabolite-set enrichment analysis, revealing differences in patients and controls primarily associated with cell glucose metabolism. These results support a potential use of the metabolomic signature as a non-invasive screening tool for CRC. Moreover, metabolic pathway analysis can provide valuable information to enhance understanding of the pathophysiological mechanisms underlying cancer. Further studies with larger cohorts, including blind trials, could potentially validate the reported results.