Innovative Multi-omic Strategies to Explore Micro- and Nanoplastic Effects

Despite the growing concern about the ecological and health implications of micro- and nanoplastics (MNPs), current studies are often limited to single-level analyses that cannot fully capture the complexity of the biological responses involved. This lack of integrative approaches hampers the ability to identify early markers of exposure and to understand the systemic effects induced by MNPs. Here we propose the application of a multi-omic integration framework, originally validated in metabolomics and other biological contexts, as a promising strategy to address this gap. By combining supervised multiblock approaches such as PLS-DA and DIABLO with the mND metric for feature selection, this method enables the simultaneous analysis of heterogeneous datasets, highlighting coordinated molecular variations across different omic layers. Its demonstrated performance in revealing subtle patterns and improving interpretability makes it highly suitable for studying the complex and often low-dose effects associated with MNP exposure. Applying this approach to MNP research would therefore provide a powerful tool for generating mechanistic hypotheses, discovering candidate biomarkers, and ultimately strengthening risk assessment and regulatory strategies in the context of emerging contaminants.