Network biology approach to human tissue-specific chemical exposome

Identification of endocrine-disrupting chemicals targeting key OP-associated genes via bioinformatics and machine learning

Osteoporosis (OP), a metabolic disorder predominantly impacting postmenopausal women, has seen considerable progress in diagnosis and treatment over the past few decades. However, the intricate interplay between genetic factors and endocrine disruptors (EDCs) in the pathogenesis of OP remains inadequately elucidated. The objective of this research is to examine the environmental pollutants and their regulatory mechanisms that could potentially influence the pathogenesis of OP, in order to establish a theoretical foundation for the targeted prevention and medical management of individuals with OP. Utilizing CTD and GEO datasets, network toxicology and bioinformatics analyses were conducted to identify target genes from a pool of 98 co-associated genes. Subsequently, a novel prediction model was developed employing a multiple machine learning algorithm. The efficacy of the model was validated based on the area under the receiver operating characteristic curve. Finally, real-time quantitative polymerase chain reaction (qRT-PCR) was used to confirm the expression levels of key genes in clinical samples. We have identified significant genes (FOXO3 and LUM) associated with OP and conducted Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, immune infiltration analysis, and molecular docking analysis. Through the analysis of these key genes, we have identified 13 EDCs that have the potential to impact OP. Several endocrine disruptors, such as Dexamethasone, Perfluorononanoic acid, genistein, cadmium, and bisphenol A, have been identified as notable environmental pollutants that impact the OP. Molecular docking analysis revealed significant binding affinity of major EDCs to the post-translational protein structures of key genes. This study demonstrates that EDCs, including dexamethasone, perfluorononanoic acid, genistein, cadmium, and bisphenol A, can be identified as important environmental pollutants affecting OP, and that FOXO3 and LUM have the potential to be diagnostic markers for OP. These results elucidate a novel association between EDCs regulated by key genes and the onset of OP.

Leveraging integrative toxicogenomic approach towards development of stressor-centric adverse outcome pathway networks for plastic additives

Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage and environmental persistence. Plastic additives, that are intentionally added to achieve specific functionality in plastics, leach into the environment upon plastic degradation and pose considerable risk to ecological and human health. Limited knowledge concerning the presence of plastic additives throughout plastic life cycle has hindered their effective regulation, thereby posing risks to product safety. In this study, we leveraged the adverse outcome pathway (AOP) framework to understand the mechanisms underlying plastic additives-induced toxicities. We first identified an exhaustive list of 6470 plastic additives from chemicals documented in plastics. Next, we leveraged heterogenous toxicogenomics and biological endpoints data from five exposome-relevant resources, and identified associations between 1287 plastic additives and 322 complete and high quality AOPs within AOP-Wiki. Based on these plastic additive-AOP associations, we constructed a stressor-centric AOP network, wherein the stressors are categorized into ten priority use sectors and AOPs are linked to 27 disease categories. We visualized the plastic additives-AOP network for each of the 1287 plastic additives and made them available in a dedicated website: https://cb.imsc.res.in/saopadditives/ . Finally, we showed the utility of the constructed plastic additives-AOP network by identifying highly relevant AOPs associated with benzo[a]pyrene (B[a]P), bisphenol A (BPA), and bis(2-ethylhexyl) phthalate (DEHP) and thereafter, explored the associated toxicity pathways in humans and aquatic species. Overall, the constructed plastic additives-AOP network will assist regulatory risk assessment of plastic additives, thereby contributing towards a toxic-free circular economy for plastics.

Analysis of Gene-Environment Interactions Related to Developmental Disorders

Various genetic and environmental factors are associated with developmental disorders (DDs). It has been suggested that interaction between genetic and environmental factors (G × E) is involved in the etiology of DDs. There are two major approaches to analyze the interaction: genome-wide and candidate gene-based approaches. In this mini-review, we demonstrate how these approaches can be applied to reveal the G × E related to DDs focusing on zebrafish and mouse models. We also discuss novel approaches to analyze the G × E associated with DDs.