Erratum: "Diversity Outbred Mice Identify Population-Based Exposure Thresholds and Genetic Factors that Influence Benzene-Induced Genotoxicity"

Exposure to silicates and systemic autoimmune-related outcomes in rodents: a systematic review

BACKGROUND

Autoimmunity can result from the interplay between genetic background and effects of environmental and/or occupational exposure to hazardous materials. Several compounds, including silica dust, have been linked with systemic autoimmunity and systemic autoimmune diseases, based on epidemiological evidence. For asbestos, a strong link with systemic autoimmune diseases does not yet exist, however, several studies have documented features of autoimmunity following asbestos exposure. Even so, human studies are limited in their ability to identify and examine isolated exposures, making it difficult to demonstrate causation or to assess pathogenic mechanisms. Therefore, this systematic review examines the existing animal evidence regarding autoimmunity and exposure to silicates (silica and asbestos).

METHODS

PubMed and EMBASE were systematically searched for peer-reviewed studies examining systemic autoimmune disease-related outcomes after silicate exposure in rodents. Literature databases were searched up to September 2021 for studies written in English and where the full text was available. Search strings were established based on a PECO (Population, Exposure, Comparator, Outcome) format. After title, abstract, and full-text screening, thirty-four studies were identified for further analysis. Quality assessment through ToxR tool and qualitative analysis of the results was performed.

RESULTS

Although there was significant heterogeneity in the included studies in terms of exposure protocol and genetic background of the rodent models used, it was noted that both genetic background and exposure to silicates [(crystalline) silica and asbestos] are highly relevant to the development of (sub-) clinical systemic autoimmune disease.

CONCLUSION

Parallels were observed between the findings from the animal (this review) and human (epidemiological) studies, arguing that experimental animal models are valuable tools for examining exacerbation or development of autoimmune disease after silicate exposure. However, genetic background and synergism between exposures should be considered in future studies.

Utilizing preclinical models of genetic diversity to improve translation of phytochemical activities from rodents to humans and inform personalized nutrition

Mouse models are an essential tool in different areas of research, including nutrition and phytochemical research. Traditional inbred mouse models have allowed the discovery of therapeutical targets and mechanisms of action and expanded our knowledge of health and disease. However, these models lack the genetic variability typically found in human populations, which hinders the translatability of the results found in mice to humans. The development of genetically diverse mouse models, such as the collaborative cross (CC) or the diversity outbred (DO) models, has been a useful tool to overcome this obstacle in many fields, such as cancer, immunology and toxicology. However, these tools have not yet been widely adopted in the field of phytochemical research. As demonstrated in other disciplines, use of CC and DO models has the potential to provide invaluable insights for translation of phytochemicals from rodents to humans, which are desperately needed given the challenges and numerous failed clinical trials in this field. These models may prove informative for personalized use of phytochemicals in humans, including: predicting interindividual variability in phytochemical bioavailability and efficacy, identifying genetic loci or genes governing response to phytochemicals, identifying phytochemical mechanisms of action and therapeutic targets, and understanding the impact of genetic variability on individual response to phytochemicals. Such insights would prove invaluable for personalized implementation of phytochemicals in humans. This review will focus on the current work performed with genetically diverse mouse populations, and the research opportunities and advantages that these models can offer to phytochemical research.

Crosstalk of Genetic Variants, Allele-Specific DNA Methylation, and Environmental Factors for Complex Disease Risk

Over the past decades, genome-wide association studies (GWAS) have identified thousands of phenotype-associated DNA sequence variants for potential explanations of inter-individual phenotypic differences and disease susceptibility. However, it remains a challenge for translating the associations into causative mechanisms for complex diseases, partially due to the involved variants in the noncoding regions and the inconvenience of functional studies in human population samples. So far, accumulating evidence has suggested a complex crosstalk among genetic variants, allele-specific binding of transcription factors (ABTF), and allele-specific DNA methylation patterns (ASM), as well as environmental factors for disease risk. This review aims to summarize the current studies regarding the interactions of the aforementioned factors with a focus on epigenetic insights. We present two scenarios of single nucleotide polymorphisms (SNPs) in coding regions and non-coding regions for disease risk, via potentially impacting epigenetic patterns. While a SNP in a coding region may confer disease risk via altering protein functions, a SNP in non-coding region may cause diseases, via SNP-altering ABTF, ASM, and allele-specific gene expression (ASE). The allelic increases or decreases of gene expression are key for disease risk during development. Such ASE can be achieved via either a "SNP-introduced ABTF to ASM" or a "SNP-introduced ASM to ABTF." Together with our additional in-depth review on insulator CTCF, we are convinced to propose a working model that the small effect of a SNP acts through altered ABTF and/or ASM, for ASE and eventual disease outcome (named as a "SNP intensifier" model). In summary, the significance of complex crosstalk among genetic factors, epigenetic patterns, and environmental factors requires further investigations for disease susceptibility.

FutureTox II: in vitro data and in silico models for predictive toxicology

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology.