Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach

Towards AI-driven longevity research: An overview

While in the past technology has mostly been utilized to store information about the structural configuration of proteins and molecules for research and medical purposes, Artificial Intelligence is nowadays able to learn from the existing data how to predict and model properties and interactions, revealing important knowledge about complex biological processes, such as aging. Modern technologies, moreover, can rely on a broader set of information, including those derived from the next-generation sequencing (e.g., proteomics, lipidomics, and other omics), to understand the interactions between human body and the external environment. This is especially relevant as external factors have been shown to have a key role in aging. As the field of computational systems biology keeps improving and new biomarkers of aging are being developed, artificial intelligence promises to become a major ally of aging research.

Differential susceptibility to endocrine disruptor-induced epimutagenesis

There is now considerable evidence indicating the potential for endocrine disrupting chemicals to alter the epigenome and for subsets of these epigenomic changes or "epimutations" to be heritably transmitted to offspring in subsequent generations. While there have been many studies indicating how exposure to endocrine disrupting chemicals can disrupt various organs associated with the body's endocrine systems, there is relatively limited information regarding the relative susceptibility of different specific organs, tissues, or cell types to endocrine disrupting chemical-induced epimutagenesis. Here we review available information about different organs, tissues, cell types, and/or cell lines which have been shown to be susceptible to specific endocrine disrupting chemical-induced epimutations. In addition, we discuss possible mechanisms that may be involved, or impacted by this tissue- or cell type-specific, differential susceptibility to different endocrine disrupting chemicals. Finally, we summarize available information indicating that certain periods of development display elevated susceptibility to endocrine disrupting chemical exposure and we describe how this may affect the extent to which germline epimutations can be transmitted inter- or transgenerationally. We conclude that cell type-specific differential susceptibility to endocrine disrupting chemical-induced epimutagenesis is likely to directly impact the extent to, or manner in, which endocrine disrupting chemical exposure initially induces epigenetic changes to DNA methylation and/or histone modifications, and how these endocrine disrupting chemical-induced epimutations can then subsequently impact gene expression, potentially leading to the development of heritable disease states.

Environmentally induced epigenetic transgenerational inheritance of disease

Ancestral environmental exposures such as toxicants, abnormal nutrition or stress can promote the epigenetic transgenerational inheritance of disease and phenotypic variation. These environmental factors induce the epigenetic reprogramming of the germline (sperm and egg). The germline epimutations can in turn increase disease susceptibility of subsequent generations of the exposed ancestors. A variety of environmental factors, species and exposure specificity of this induced epigenetic transgenerational inheritance of disease is discussed with a consideration of generational toxicology. The molecular mechanisms and processes involved in the ability of these inherited epimutations to increase disease susceptibility are discussed. In addition to altered disease susceptibility, the potential impact of the epigenetic inheritance on phenotypic variation and evolution is considered. Observations suggest environmentally induced epigenetic transgenerational inheritance of disease is a critical aspect of disease etiology, toxicology and evolution that needs to be considered.

Ancestral perinatal obesogen exposure results in a transgenerational thrifty phenotype in mice

Ancestral environmental exposures to non-mutagenic agents can exert effects in unexposed descendants. This transgenerational inheritance has significant implications for understanding disease etiology. Here we show that exposure of F0 mice to the obesogen tributyltin (TBT) throughout pregnancy and lactation predisposes unexposed F4 male descendants to obesity when dietary fat is increased. Analyses of body fat, plasma hormone levels, and visceral white adipose tissue DNA methylome and transcriptome collectively indicate that the F4 obesity is consistent with a leptin resistant, thrifty phenotype. Ancestral TBT exposure induces global changes in DNA methylation and altered expression of metabolism-relevant genes. Analysis of chromatin accessibility in F3 and F4 sperm reveals significant differences between control and TBT groups and significant similarities between F3 and F4 TBT groups that overlap with areas of differential methylation in F4 adipose tissue. Our data suggest that ancestral TBT exposure induces changes in chromatin organization transmissible through meiosis and mitosis.

Early life exposure to endocrine disrupting chemicals has been linked to increased adiposity during adulthood. Here Chamorro-García et al. show that ancestral exposure to the obesogen tributyltin causes obesity in untreated F4 generation male descendants by inducing heritable changes in genome architecture that promote a thrifty phenotype.

Machine learning for epigenetics and future medical applications

Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems with ML to develop a more efficient feature selection process and address the imbalance problem in all genomic data sets. The power of this novel ML approach and our ability to predict epigenetic phenomena and associated disease is suggested. The current approach requires extensive computation of features over the genome. A promising new approach is to introduce Deep Learning (DL) for the generation and simultaneous computation of novel genomic features tuned to the classification task. This approach can be used with any genomic or biological data set applied to medicine. The application of molecular epigenetic data in advanced machine learning analysis to medicine is the focus of this review.

Mercury-induced epigenetic transgenerational inheritance of abnormal neurobehavior is correlated with sperm epimutations in zebrafish

Methylmercury (MeHg) is a ubiquitous environmental neurotoxicant, with human exposures predominantly resulting from fish consumption. Developmental exposure of zebrafish to MeHg is known to alter their neurobehavior. The current study investigated the direct exposure and transgenerational effects of MeHg, at tissue doses similar to those detected in exposed human populations, on sperm epimutations (i.e., differential DNA methylation regions [DMRs]) and neurobehavior (i.e., visual startle and spontaneous locomotion) in zebrafish, an established human health model. F0 generation embryos were exposed to MeHg (0, 1, 3, 10, 30, and 100 nM) for 24 hours ex vivo. F0 generation control and MeHg-exposed lineages were reared to adults and bred to yield the F1 generation, which was subsequently bred to the F2 generation. Direct exposure (F0 generation) and transgenerational actions (F2 generation) were then evaluated. Hyperactivity and visual deficit were observed in the unexposed descendants (F2 generation) of the MeHg-exposed lineage compared to control. An increase in F2 generation sperm epimutations was observed relative to the F0 generation. Investigation of the DMRs in the F2 generation MeHg-exposed lineage sperm revealed associated genes in the neuroactive ligand-receptor interaction and actin-cytoskeleton pathways being effected, which correlate to the observed neurobehavioral phenotypes. Developmental MeHg-induced epigenetic transgenerational inheritance of abnormal neurobehavior is correlated with sperm epimutations in F2 generation adult zebrafish. Therefore, mercury can promote the epigenetic transgenerational inheritance of disease in zebrafish, which significantly impacts its environmental health considerations in all species including humans.

Tertiary Epimutations - A Novel Aspect of Epigenetic Transgenerational Inheritance Promoting Genome Instability

Exposure to environmental factors can induce the epigenetic transgenerational inheritance of disease. Alterations to the epigenome termed “epimutations” include “primary epimutations” which are epigenetic alterations in the absence of genetic change and “secondary epimutations” which form following an initial genetic change. To determine if secondary epimutations contribute to transgenerational transmission of disease following in utero exposure to the endocrine disruptor vinclozolin, we exposed pregnant female rats carrying the lacI mutation-reporter transgene to vinclozolin and assessed the frequency of mutations in kidney tissue and sperm recovered from F1 and F3 generation progeny. Our results confirm that vinclozolin induces primary epimutations rather than secondary epimutations, but also suggest that some primary epimutations can predispose a subsequent accelerated accumulation of genetic mutations in F3 generation descendants that have the potential to contribute to transgenerational phenotypes. We therefore propose the existence of “tertiary epimutations” which are initial primary epimutations that promote genome instability leading to an accelerated accumulation of genetic mutations.