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Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases.

ABSTRACT: Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.

SUBMITTER: Tabassum R

PROVIDER: S-EPMC8004487 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Lipids play an essential role in development, homeostatic functions, immune signaling, reproduction, and growth. Although it is evident that changes in lipid biosynthesis and metabolism can affect organismal physiology, few studies have determined how environmental stressors affect lipid pathways, let alone alter global lipid profiles in fish. This is a significant research gap, as a number of environmental contaminants interact with lipid signaling and metabolic pathways. In this review, we highlight the utility of lipidomics as a tool in environmental toxicology, discussing the current state of knowledge regarding chemical-lipidomic perturbations. As with most oviparous animals, the processing and storage of lipids during oocyte development is also particularly important for embryogenesis in fish. Using largemouth bass (Micropterus salmoides) as an example, transcriptomics data suggest that various chemicals alter lipid metabolism and regulation, highlighting the need for more sophisticated investigations into how toxicants impact lipid responses. We also point out the challenges ahead; these include a lack of understanding about lipid processing and signaling in fish, tissue and species-specific lipid composition, and extraneous factors (e.g., nutrition, temperature) that confound interpretation. For example, toxicant exposure can lead to oxidative stress and lipid peroxidation, resulting in complex lipid byproducts that are challenging to measure. With the emergence of lipidomics in systems toxicology, multi-omics approaches are expected to more clearly define effects on physiology, creating stronger linkages between multiple molecular entities (gene-protein-lipid/metabolite). The development and implementation of novel technologies such as ion mobility-mass spectrometry and ozone-induced dissociation support the complete structural elucidation of lipid molecules. This has implications in the adverse outcome pathway framework, which will enhance the application of lipidomics in toxicology by linking these molecular changes to effects at higher levels of biological organization.

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Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases.

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