Exposome-Informed Multi-Omics and Epigenetic Regulation for Predictive Toxicology and Precision Risk Assessment in Human Health

Human health trajectories are shaped by the totality of exposures across the lifespan, including environmental, occupational, lifestyle, dietary, microbiome-derived, and endogenous factors, acting in concert with genetic and epigenetic variability. Epigenetic mechanisms (e.g., DNA methylation, chromatin regulation, non-coding RNAs) and multi-layer molecular phenotypes (transcriptomic, proteomic, metabolomic, and other omics) provide a mechanistic bridge between exposures and downstream biological responses. Advances in exposomics and integrative multi-omics now enable time-resolved profiling of exposure-linked molecular changes, creating opportunities to uncover gene–environment interactions, explain inter-individual susceptibility, and identify early indicators of adverse outcomes.This Research Topic will bring together interdisciplinary studies that integrate exposure measurement (including longitudinal or life-course designs) with multi-omics and functional genomics to generate actionable, testable predictions of toxicity and disease risk. We particularly welcome work combining computational modeling and machine learning with experimental validation (e.g., CRISPR-based perturbation, single-cell/spatial omics, organoid or other human-relevant models) to establish causal pathways linking exposures to molecular mechanisms and phenotypes. Submissions should move beyond descriptive associations to deliver predictive signatures, mechanistic insight, and translational relevance for precision toxicology, including consideration of ethical, regulatory, and societal implications such as genetic privacy and equity in exposure-informed risk prediction.Topics of interest include (but are not limited to):o Gene–environment interactions and multi-omics mechanisms underlying differential susceptibility to toxicants and complex exposure mixtureso Longitudinal/life-course exposomics (prenatal, developmental, aging) linked to molecular trajectories and adverse outcomeso Integration of exposome data (e.g., metabolomics/adductomics, diet/microbiome-derived metabolites, wearable/digital measures, real-world exposure proxies) with genomics and epigenomicso Construction and validation of predictive multi-omics signatures (genetic/epigenetic markers) for toxicity prediction and precision risk assessmento Computational and ML models that incorporate genetic/epigenetic variability to forecast toxicological events and health risko Functional genomics and mechanistic validation (CRISPR screening/editing, perturb-seq, single-cell/spatial approaches) to map exposure-responsive pathwayso Human-relevant experimental systems (e.g., iPSC-derived models, organoids, microphysiological systems) for exposure-to-phenotype inferenceo Translational studies linking exposome-informed signatures to risk stratification, personalized prevention, or tailored intervention strategieso New methodologies enabling time-resolved, high-resolution, and scalable exposome and multi-omics characterizationo Ethical, regulatory, and societal issues in exposure + genetic risk prediction (privacy, fairness, equity, interpretability) Topic editors: Shabana Anjum, DIA ADVANI, Aijaz Malik Source: https://www.frontiersin.org/research-topics/79097/exposome-informed-multi-omics-and-epigenetic-regulation-for-predictive-toxicology-and-precision-risk-assessment-in-human-health