Bi-allelic variants in DNAH3 cause male infertility with asthenoteratozoospermia in humans and mice.

STUDY QUESTION: Are there other pathogenic genes for asthenoteratozoospermia (AT)? SUMMARY ANSWER: DNAH3 is a novel candidate gene for AT in humans and mice. WHAT IS KNOWN ALREADY: AT is a major cause of male infertility. Several genes underlying AT have been reported; however, the genetic aetiology remains unknown in a majority of affected men. STUDY DESIGN SIZE DURATION: A total of 432 patients with AT were recruited in this study. DNAH3 mutations were identified by whole-exome sequencing (WES). Dnah3 knockout mice were generated using the genome editing tool. The morphology and motility of sperm from Dnah3 knockout mice were investigated. The entire study was conducted over 3 years. PARTICIPANTS/MATERIALS SETTING METHODS: WES was performed on 432 infertile patients with AT. In addition, two lines of Dnah3 knockout mice were generated. Haematoxylin and eosin (H&E) staining, transmission electron microscopy (TEM), immunostaining, and computer-aided sperm analysis (CASA) were performed to investigate the morphology and motility of the spermatozoa. ICSI was used to overcome the infertility of one patient and of the Dnah3 knockout mice. MAIN RESULTS AND THE ROLE OF CHANCE: DNAH3 biallelic variants were identified in three patients from three unrelated families. H&E staining revealed various morphological abnormalities in the flagella of sperm from the patients, and TEM and immunostaining further showed the loss of the central pair of microtubules, a dislocated mitochondrial sheath and fibrous sheath, as well as a partial absence of the inner dynein arms. In addition, the two Dnah3 knockout mouse lines demonstrated AT. One patient and the Dnah3 knockout mice showed good treatment outcomes after ICSI. LARGE SCALE DATA: N/A. LIMITATIONS REASONS FOR CAUTION: This is a preliminary report suggesting that defects in DNAH3 can lead to asthenoteratozoospermia in humans and mice. The pathogenic mechanism needs to be further examined in a future study. WIDER IMPLICATIONS OF THE FINDINGS: Our findings show that DNAH3 is a novel candidate gene for AT in humans and mice and provide crucial insights into the biological underpinnings of this disorder. The findings may also be beneficial for counselling affected individuals. STUDY FUNDING/COMPETING INTERESTS: This work was supported by grants from National Natural Science Foundation of China (82201773, 82101961, 82171608, 32322017, 82071697, and 81971447), National Key Research and Development Program of China (2022YFC2702604), Scientific Research Foundation of the Health Committee of Hunan Province (B202301039323, B202301039518), Hunan Provincial Natural Science Foundation (2023JJ30716), the Medical Innovation Project of Fujian Province (2020-CXB-051), the Science and Technology Project of Fujian Province (2023D017), China Postdoctoral Science Foundation (2022M711119), and Guilin technology project for people's benefit (20180106-4-7). The authors declare no competing interests.

Challenges and opportunities for overcoming dog use in agrochemical evaluation and registration.

Progress in developing new tools, assays, and approaches to assess human hazard and health risk provides an opportunity to re-evaluate the necessity of dog studies for the safety evaluation of agrochemicals. A workshop was held where partic­ipants discussed the strengths and limitations of past use of dogs for pesticide evaluations and registrations. Opportunities were identified to support alternative approaches to answer human safety questions without performing the required 90-day dog study. Development of a decision tree for determining when the dog study might not be necessary to inform pesticide safety and risk assessment was proposed. Such a process will require global regulatory authority participation to lead to its acceptance. The identification of unique effects in dogs that are not identified in rodents will need further evaluation and determination of their relevance to humans. The establishment of in vitro and in silico approaches that can provide critical data on relative species sensitivity and human relevance will be an important tool to advance the decision process. Promising novel tools including in vitro comparative metabolism studies, in silico models, and high-throughput assays able to identify metabolites and mechanisms of action leading to development of adverse outcome pathways will need further development. To replace or eliminate the 90-day dog study, a collaborative, multidisciplinary, international effort that transcends organi­zations and regulatory agencies will be needed in order to develop guidance on when the study would not be necessary for human safety and risk assessment.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making.

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

Predicting nonlinear relationships between external and internal concentrations with physiologically based pharmacokinetic modeling.

Although external concentrations are more readily quantified and often used as the metric for regulating and mitigating exposures to environmental chemicals, the toxicological response to an environmental chemical is more directly related to its internal concentrations than the external concentration. The processes of absorption, distribution, metabolism, and excretion (ADME) determine the quantitative relationship between the external and internal concentrations, and these processes are often susceptible to saturation at high concentrations, which can lead to nonlinear changes in internal concentrations that deviate from proportionality. Using generic physiologically-based pharmacokinetic (PBPK) models, we explored how saturable absorption or clearance influence the shape of the internal to external concentration (IEC) relationship. We used the models for hypothetical chemicals to show how differences in kinetic parameters can impact the shape of an IEC relationship; and models for styrene and caffeine to explore how exposure route, frequency, and duration impact the IEC relationships in rat and human exposures. We also analyzed available plasma concentration data for 2,4-dichlorophenoxyacetic acid to demonstrate how a PBPK modeling approach can be an alternative to common statistical methods for analyzing dose proportionality. A PBPK modeling approach can be a valuable tool used in the early stages of a chemical safety assessment program to optimize the design of longer-term animal toxicity studies or to interpret study results.

A Systematic Review of Published Physiologically-based Kinetic Models and an Assessment of their Chemical Space Coverage.

Across multiple sectors, including food, cosmetics and pharmaceutical industries, there is a need to predict the potential effects of xenobiotics. These effects are determined by the intrinsic ability of the substance, or its derivatives, to interact with the biological system, and its concentration-time profile at the target site. Physiologically-based kinetic (PBK) models can predict organ-level concentration-time profiles, however, the models are time and resource intensive to generate de novo. Read-across is an approach used to reduce or replace animal testing, wherein information from a data-rich chemical is used to make predictions for a data-poor chemical. The recent increase in published PBK models presents the opportunity to use a read-across approach for PBK modelling, that is, to use PBK model information from one chemical to inform the development or evaluation of a PBK model for a similar chemical. Essential to this process, is identifying the chemicals for which a PBK model already exists. Herein, the results of a systematic review of existing PBK models, compliant with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format, are presented. Model information, including species, sex, life-stage, route of administration, software platform used and the availability of model equations, was captured for 7541 PBK models. Chemical information (identifiers and physico-chemical properties) has also been recorded for 1150 unique chemicals associated with these models. This PBK model data set has been made readily accessible, as a Microsoft Excel® spreadsheet, providing a valuable resource for those developing, using or evaluating PBK models in industry, academia and the regulatory sectors.

Incorporating human exposure information in a weight of evidence approach to inform design of repeated dose animal studies.

Human health risks from chronic exposures to environmental chemicals are typically estimated from potential human exposure estimates and dose-response data obtained from repeated-dose animal toxicity studies. Various criteria are available for selecting the top (highest) dose used in these animal studies. For example, toxicokinetic (TK) and toxicological data provided by shorter-term or dose range finding studies can be evaluated in a weight of evidence approach to provide insight into the dose range that would provide dose-response data that are relevant to human exposures. However, there are concerns that a top dose resulting from the consideration of TK data may be too low compared to other criteria, such as the limit dose or the maximum tolerated dose. In this paper, we address several concerns related to human exposures by discussing 1) the resources and methods available to predict human exposure levels and the associated uncertainty and variability, and 2) the margin between predicted human exposure levels and the dose levels used in repeated-dose animal studies. A series of case studies, ranging from data-rich to data-poor chemicals, are presented to demonstrate that expected human exposures to environmental chemicals are typically orders of magnitude lower than no-observed-adverse-effect levels/lowest-observed-adverse-effect levels (NOAELs/LOAELs) when available (used as conservative surrogates for top doses). The results of these case studies support that a top dose based, in part, on TK data is typically orders of magnitude higher than expected human exposure levels.

Opportunities and challenges related to saturation of toxicokinetic processes: Implications for risk assessment.

Top dose selection for repeated dose animal studies has generally focused on identification of apical endpoints, use of the limit dose, or determination of a maximum tolerated dose (MTD). The intent is to optimize the ability of toxicity tests performed in a small number of animals to detect effects for hazard identification. An alternative approach, the kinetically derived maximum dose (KMD), has been proposed as a mechanism to integrate toxicokinetic (TK) data into the dose selection process. The approach refers to the dose above which the systemic exposures depart from being proportional to external doses. This non-linear external-internal dose relationship arises from saturation or limitation of TK process(es), such as absorption or metabolism. The importance of TK information is widely acknowledged when assessing human health risks arising from exposures to environmental chemicals, as TK determines the amount of chemical at potential sites of toxicological responses. However, there have been differing opinions and interpretations within the scientific and regulatory communities related to the validity and application of the KMD concept. A multi-stakeholder working group, led by the Health and Environmental Sciences Institute (HESI), was formed to provide an opportunity for impacted stakeholders to address commonly raised scientific and technical issues related to this topic and, more specifically, a weight of evidence approach is recommended to inform design and dose selection for repeated dose animal studies. Commonly raised challenges related to the use of TK data for dose selection are discussed, recommendations are provided, and illustrative case examples are provided to address these challenges or refute misconceptions.

Gaining acceptance in next generation PBK modelling approaches for regulatory assessments - An OECD international effort.

Physiologically Based Kinetic (PBK) models are valuable tools to help define safe external levels of chemicals based on internal doses at target organs in experimental animals, humans and organisms used in environmental risk assessment. As the toxicity testing paradigm shifts to alternative testing approaches, PBK model development has started to rely (mostly or entirely) on model parameters quantified using in vitro or in silico methods. Recently, the Organisation for Economic Cooperation and Development (OECD) published a guidance document (GD) describing a scientific workflow for characterising and validating PBK models developed using in vitro and in silico data. The GD provides an assessment framework for evaluating these models, with emphasis on the major uncertainties underlying model inputs and outputs. To help end-users submit or evaluate a PBK model for regulatory purposes, the GD also includes a template for documenting the model characteristics, and a checklist for evaluating the quality of a model. This commentary highlights the principles, criteria and tools laid out in the OECD PBK model GD, with the aim of facilitating the dialogue between model developers and risk assessors.

PBPK model reporting template for chemical risk assessment applications.

Physiologically-based pharmacokinetic (PBPK) modeling analysis does not stand on its own for regulatory purposes but is a robust tool to support drug/chemical safety assessment. While the development of PBPK models have grown steadily since their emergence, only a handful of models have been accepted to support regulatory purposes due to obstacles such as the lack of a standardized template for reporting PBPK analysis. Here, we expand the existing guidances designed for pharmaceutical applications by recommending additional elements that are relevant to environmental chemicals. This harmonized reporting template can be adopted and customized by public health agencies receiving PBPK model submission, and it can also serve as general guidance for submitting PBPK-related studies for publication in journals or other modeling sharing purposes. The current effort represents one of several ongoing collaborations among the PBPK modeling and risk assessment communities to promote, when appropriate, incorporating PBPK modeling to characterize the influence of pharmacokinetics on safety decisions made by regulatory agencies.

Application of a combined aggregate exposure pathway and adverse outcome pathway (AEP-AOP) approach to inform a cumulative risk assessment: A case study with phthalates.

Advancements in measurement and modeling capabilities are providing unprecedented access to estimates of chemical exposure and bioactivity. With this influx of new data, there is a need for frameworks that help organize and disseminate information on chemical hazard and exposure in a manner that is accessible and transparent. A case study approach was used to demonstrate integration of the Adverse Outcome Pathway (AOP) and Aggregate Exposure Pathway (AEP) frameworks to support cumulative risk assessment of co-exposure to two phthalate esters that are ubiquitous in the environment and that are associated with disruption of male sexual development in the rat: di(2-ethylhexyl) phthalate (DEHP) and di-n-butyl phthalate (DnBP). A putative AOP was developed to guide selection of an in vitro assay for derivation of bioactivity values for DEHP and DnBP and their metabolites. AEPs for DEHP and DnBP were used to extract key exposure data as inputs for a physiologically based pharmacokinetic (PBPK) model to predict internal metabolite concentrations. These metabolite concentrations were then combined using in vitro-based relative potency factors for comparison with an internal dose metric, resulting in an estimated margin of safety of ~13,000. This case study provides an adaptable workflow for integrating exposure and toxicity data by coupling AEP and AOP frameworks and using in vitro and in silico methodologies for cumulative risk assessment.

A weight of evidence approach to investigate potential common mechanisms in pesticide groups to support cumulative risk assessment: A case study with dinitroaniline pesticides.

In 2016, the United States Environmental Protection Agency's (EPA) Office of Pesticide Programs published guidelines for establishing candidate common mechanism groups (CMGs) for cumulative risk assessment (CRA) weight-of-evidence-based screenings. A candidate CMG is a group of chemicals that may share similar structure, apical endpoints, and/or mechanistic data that suggest the potential for a common mechanism of toxicity among them. Here, a weight-of-evidence approach is presented to establish candidacy of a CMG for a group of nine dinitroaniline pesticides. This approach involves review of available in vivo toxicity information and literature to determine mode of action, along with analyses of in vitro toxicity data and chemical structure. Despite structural similarity among some dinitroanilines and some shared target organs identified through toxicity observed in in vivo studies, there were no consistencies among groups, suggesting lack of a common mechanism when all analyses are considered together. For example, two structurally similar compounds with thyroid/liver in vivo effects were not found active in any Toxicity Forecaster (ToxCast) in vitro assays. The weight-of-evidence is insufficient to support the testable hypothesis that dinitroanilines could form a CMG, and highlights the importance of establishing a consensus among multiple lines of evidence prior to CRA.

A Workflow for Identifying Metabolically Active Chemicals to Complement in vitro Toxicity Screening.

The new paradigm of toxicity testing approaches involves rapid screening of thousands of chemicals across hundreds of biological targets through use of in vitro assays. Such assays may lead to false negatives when the complex metabolic processes that render a chemical bioactive in a living system are unable to be replicated in an in vitro environment. In the current study, a workflow is presented for complementing in vitro testing results with in silico and in vitro techniques to identify inactive parents that may produce active metabolites. A case study applying this workflow involved investigating the influence of metabolism for over 1,400 chemicals considered inactive across18 in vitro assays related to the estrogen receptor (ER) pathway. Over 7,500 first-generation and second-generation metabolites were generated for these in vitro inactive chemicals using an in silico software program. Next, a consensus model comprised of four individual quantitative structure activity relationship (QSAR) models was used to predict ER-binding activity for each of the metabolites. Binding activity was predicted for ~8-10% of metabolites in each generation, with these metabolites linked to 259 in vitro inactive parent chemicals. Metabolites were enriched in substructures consisting of alcohol, aromatic, and phenol bonds relative to their inactive parent chemicals, suggesting these features are potentially favorable for ER-binding. The workflow presented here can be used to identify parent chemicals that can be potentially bioactive, to aid confidence in high throughput risk screening.

Aggregate Exposure Pathways in Support of Risk Assessment.

Over time, risk assessment has shifted from establishing relationships between exposure to a single chemical and a resulting adverse health outcome, to evaluation of multiple chemicals and disease outcomes simultaneously. As a result, there is an increasing need to better understand the complex mechanisms that influence risk of chemical and non-chemical stressors, beginning at their source and ending at a biological endpoint relevant to human or ecosystem health risk assessment. Just as the Adverse Outcome Pathway (AOP) framework has emerged as a means of providing insight into mechanism-based toxicity, the exposure science community has seen the recent introduction of the Aggregate Exposure Pathway (AEP) framework. AEPs aid in making exposure data applicable to the FAIR (i.e., findable, accessible, interoperable, and reusable) principle, especially by (1) organizing continuous flow of disjointed exposure information;(2) identifying data gaps, to focus resources on acquiring the most relevant data; (3) optimizing use and repurposing of existing exposure data; and (4) facilitating interoperability among predictive models. Herein, we discuss integration of the AOP and AEP frameworks and how such integration can improve confidence in both traditional and cumulative risk assessment approaches.

Physiological Concentration of Prostaglandin E2 Exerts Anti-inflammatory Effects by Inhibiting Microglial Production of Superoxide Through a Novel Pathway.

This study investigated the physiological regulation of brain immune homeostasis in rat primary neuron-glial cultures by sub-nanomolar concentrations of prostaglandin E2 (PGE2). We demonstrated that 0.01 to 10 nM PGE2 protected dopaminergic neurons against LPS-induced neurotoxicity through a reduction of microglial release of pro-inflammatory factors in a dose-dependent manner. Mechanistically, neuroprotective effects elicited by PGE2 were mediated by the inhibition of microglial NOX2, a major superoxide-producing enzyme. This conclusion was supported by (1) the close relationship between inhibition of superoxide and PGE2-induced neuroprotective effects; (2) the mediation of PGE2-induced reduction of superoxide and neuroprotection via direct inhibition of the catalytic subunit of NOX2, gp91phox, rather than through the inhibition of conventional prostaglandin E2 receptors; and (3) abolishment of the neuroprotective effect of PGE2 in NOX2-deficient cultures. In summary, this study revealed a potential physiological role of PGE2 in maintaining brain immune homeostasis and protecting neurons via an EP receptor-independent mechanism.

Refining the aggregate exposure pathway.

Advancements in measurement technologies and modeling capabilities continue to result in an abundance of exposure information, adding to that currently in existence. However, fragmentation within the exposure science community acts as an obstacle for realizing the vision set forth in the National Research Council's report on Exposure Science in the 21st century to consider exposures from source to dose, on multiple levels of integration, and to multiple stressors. The concept of an Aggregate Exposure Pathway (AEP) was proposed as a framework for organizing and integrating diverse exposure information that exists across numerous repositories and among multiple scientific fields. A workshop held in May 2016 followed introduction of the AEP concept, allowing members of the exposure science community to provide extensive evaluation and feedback regarding the framework's structure, key components, and applications. The current work briefly introduces topics discussed at the workshop and attempts to address key challenges involved in refining this framework. The resulting evolution in the AEP framework's features allows for facilitating acquisition, integration, organization, and transparent application and communication of exposure knowledge in a manner that is independent of its ultimate use, thereby enabling reuse of such information in many applications.

Challenges Associated With Applying Physiologically Based Pharmacokinetic Modeling for Public Health Decision-Making.

The development and application of physiologically based pharmacokinetic (PBPK) models in chemical toxicology have grown steadily since their emergence in the 1980s. However, critical evaluation of PBPK models to support public health decision-making across federal agencies has thus far occurred for only a few environmental chemicals. In order to encourage decision-makers to embrace the critical role of PBPK modeling in risk assessment, several important challenges require immediate attention from the modeling community. The objective of this contemporary review is to highlight 3 of these challenges, including: (1) difficulties in recruiting peer reviewers with appropriate modeling expertise and experience; (2) lack of confidence in PBPK models for which no tissue/plasma concentration data exist for model evaluation; and (3) lack of transferability across modeling platforms. Several recommendations for addressing these 3 issues are provided to initiate dialog among members of the PBPK modeling community, as these issues must be overcome for the field of PBPK modeling to advance and for PBPK models to be more routinely applied in support of public health decision-making.

Sperm DNA damage has a negative effect on early embryonic development following in vitro fertilization.

Sperm DNA damage is recognized as an important biomarker of male infertility. To investigate this, sperm DNA damage was assessed by the sperm chromatin dispersion (SCD) test in semen and motile spermatozoa harvested by combined density gradient centrifugation (DGC) and swim-up in 161 couples undergoing in vitro fertilization (IVF). Semen analysis and sperm DNA damage results were compared between couples who did or did not achieve pregnancy. The sperm DNA damage level was significantly different between the two groups (P < 0.05) and was negatively correlated with IVF outcomes. Logistic regression analysis confirmed that it was an independent predictor for achieving clinical pregnancy. The effects of different levels of sperm DNA damage on IVF outcomes were also compared. There were significant differences in day 3 embryo quality, blastocyst formation rate, and implantation and pregnancy rates (P < 0.05), but not in the basic fertilization rate between the two groups. Thus, sperm DNA damage as measured by the SCD appears useful for predicting the clinical pregnancy rate following IVF.

Investigating the state of physiologically based kinetic modelling practices and challenges associated with gaining regulatory acceptance of model applications.

Physiologically based kinetic (PBK) models are used widely throughout a number of working sectors, including academia and industry, to provide insight into the dosimetry related to observed adverse health effects in humans and other species. Use of these models has increased over the last several decades, especially in conjunction with emerging alternative methods to animal testing, such as in vitro studies and data-driven in silico quantitative-structure-activity-relationship (QSAR) predictions. Experimental information derived from these new approach methods can be used as input for model parameters and allows for increased confidence in models for chemicals that did not have in vivo data for model calibration. Despite significant advancements in good modelling practice (GMP) for model development and evaluation, there remains some reluctance among regulatory agencies to use such models during the risk assessment process. Here, the results of a survey disseminated to the modelling community are presented in order to inform the frequency of use and applications of PBK models in science and regulatory submission. Additionally, the survey was designed to identify a network of investigators involved in PBK modelling and knowledgeable of GMP so that they might be contacted in the future for peer review of PBK models, especially in regards to vetting the models to such a degree as to gain a greater acceptance for regulatory purposes.

Estimating Methylmercury Intake for the General Population of South Korea Using Physiologically Based Pharmacokinetic Modeling.

The Korean National Environmental Health Survey (KoNEHS 2009-2011) tracks levels of environmental pollutants in biological samples from the adult Korean population (age 19-88). Recent survey results for blood mercury (Hg) suggest some exceedance above existing blood Hg reference levels. Because total blood Hg represents both organic and inorganic forms, and methylmercury (MeHg) has been specifically linked to several adverse health outcomes, a need exists to quantify MeHg intake for this population. Gender, age, and frequency of fish consumption were first identified as important predictors of KoNEHS blood Hg levels using generalized linear models. Stratified distributions of total blood Hg were then used to estimate distributions of blood MeHg using fractions of MeHg to total Hg from the literature. Next, a published physiologically based pharmacokinetic (PBPK) model was used to predict distributions of blood MeHg as a function of MeHg intake; ratios of MeHg intake to model-predicted blood MeHg were then combined with KoNEHS-based blood MeHg values to produce MeHg intake estimates. These intake estimates were ultimately compared with the Reference Dose (RfD) for MeHg (0.1 µg/kg/day) and reported as margin of exposure (MOE) estimates for specific KoNEHS subgroups. The derived MOEs across all subgroups, based on estimated geometric mean intake, ranged from 1.6 to 4.1. These results suggest MeHg exposures approaching the RfD for several subgroups of the Korean population, and not just for specific subgroups (eg, those who eat fish very frequently).