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Brain and skin health are becoming global priorities due to the aging population and increased exposure to environmental stressors such as pollution, ultraviolet radiation, and oxidative stress. As lipid-rich organs, the brain and skin are highly susceptible to oxidative damage and serve as sensitive indicators of environmental stress. Lipids play essential roles in maintaining cellular membrane integrity and mediating stress-related signaling pathways. While lipidomics has emerged as a powerful tool to assess biological responses, challenges remain in extracting meaningful biological insights from complex lipid data in relation to cellular systems, molecular pathways, and phenotypic outcomes. This review highlights recent advances in multivariate data analysis, network modeling, and pathway-based tools that enhance the interpretation of lipidomics datasets, and provides an overview of current lipid bioinformatics tools and databases and their limitations. These tools are crucial for biomarker discovery and understanding lipid-mediated mechanisms in skin aging, neurodegeneration, and adaptation to environmental stress. This review also discusses the potential of marine-derived bioactives, such as those from seaweeds and sea cucumbers, alongside plant-derived lipids, in relation to emerging nootropic and cosmeceutical applications. Marine sources such as seaweed and sea cucumber are rich in bioactive lipids, including omega-3 fatty acids, glycolipids, phospholipids, and betaine lipids, which exhibit antioxidant, anti-inflammatory, and regenerative properties, yet remain largely underexplored. Continued innovation in lipid bioinformatics is essential to unlock the full potential of marine bioactives and guide precision strategies for brain and skin health while promoting the sustainable use of marine and plant resources. This review emphasizes the potential of lipid bioinformatics in enabling discovery and functional characterization of bioactive lipids for health-related applications within a systems biology framework.
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Callahan et al. (2026) studied this question.
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