Metabolomics as the missing piece in epigenetics research

The study of epigenetics has revolutionized our understanding of how environment, diet, and lifestyle influence health [1, 2]. Experience-dependent and potentially heritable epigenetic mechanisms, such as DNA methylation [3], histone modifications [4], and the activity of non-coding RNA [5], regulate the expression of genes involved in cell function, development, aging, and disease [6, 7]. These mechanisms, explored through genomic and transcriptomic approaches, have traditionally been the primary focus of epigenetic research [8]. However, metabolomics, the study of small molecules (metabolites) involved in cellular processes, represents a promising yet underexplored component of the epigenetic landscape [9]. Metabolites act as potential biomarkers of health and disease due to their critical role at the downstream end of the gene–RNA–protein–cell function cascade, making them highly sensitive indicators of gene–environment interactions [10]. For example, the metabolome changes in response to external influences such as physical activity, diet [11, 12], pollutants [13–15], and stress [16–19]. Thus, integrating metabolomics into epigenetic research may help bridge existing knowledge gaps by illuminating how metabolism influences epigenetic regulation—and vice versa—thereby paving the way for therapeutic innovation [20]. Cellular metabolism plays a critical role in epigenetic regulation by producing key metabolites that support epigenetic modifications [21]. Metabolites such as S-adenosyl-l-methionine (SAM) [22], acetyl-coenzyme A (Acetyl-CoA) [23], nicotinamide adenine dinucleotide (NAD⁺) [24], and α-ketoglutarate [25] act as substrates or cofactors for enzymes that modify DNA and histones. SAM serves as a methyl donor for DNA and histone methylation [26], while acetyl-CoA is essential for histone acetylation, influencing chromatin accessibility and transcriptional activity [27]. The interplay between metabolism and epigenetics is particularly relevant in the context of disease. Metabolic perturbations, such as the Warburg effect in cancer, alter the availability of key metabolites such as NAD⁺, pyruvate, and α-ketoglutarate, which can drive maladaptive epigenetic modifications associated with tumour progression [28]. Similarly, dietary influences on metabolite levels are linked to metabolic disorders such as obesity and diabetes. For example, Acetyl-CoA, influenced by carbohydrate and fat intake, and SAM, affected by dietary methyl donors such as folate, choline, and methionine, are both implicated in heightened susceptibility to and progression of these diseases [29]. A study of metabolic dysfunction in pregnancy showed that both carbohydrate and methionine levels were altered in mothers with obesity and gestational diabetes [30]. Altogether, these findings highlight the need for deeper investigation into how metabolites regulate gene expression in both health and disease. Practical applications of metabolomics in clinical research are promising for risk prediction and diagnostic purposes, particularly when metabolomic biomarkers reflect upstream epigenetic changes. Profiling metabolites may help identify epigenetic modifications by detecting changes in specific metabolic pathways, including those related to inflammation [31], DNA methylation [32], and histone acetylation [33]. Moreover, metabolic signatures may reflect experience-dependent epigenetic changes that influence cellular or organ function and the risk of non-communicable diseases. These include epigenetic mechanisms and pathways associated with stress and trauma [34–40], radiation exposure [41], space flight [42], sedentary lifestyle [43], social isolation [44], smoking [45], and malnutrition [46]. Metabolomics, as a source of sensitive and robust biomarkers of pathological changes, holds significant potential for the development of non-invasive diagnostics using blood, saliva, urine, or stool. These approaches may provide insights into epigenetic changes associated with disease predisposition, symptom expression, or recovery, with important implications for clinical management and precision medicine in non-communicable diseases [47]. For instance, in oncology, alterations in specific metabolite profiles, such as 2-hydroxyglutarate and lactate, have been linked to tumour metabolism and epigenetic dysregulation, offering valuable information for the development of targeted therapies [48]. Thus, by characterizing the metabolic and epigenetic landscape of cancer, clinicians may be better equipped to deliver improved and personalized treatment options. Despite its potential for epigenetics research, metabolomics remains underutilized in the field. This is due in large part to the unique challenges metabolomics faces compared to more established approaches such as genomics and transcriptomics. The complexity of connecting single metabolites or metabolic profiles to specific epigenetic modifications requires the use of systems biology methodologies and advanced pathway identification tools. Paired with a demand for interdisciplinary expertise in data science, these obstacles have raised the bar of entry [12]. Nevertheless, recent advances in integrative multi-omics approaches are making it easier to perform comprehensive metabolic and epigenetic analyses [49]​. By improving methods for the creation, analysis, and integration of metabolomics data with other ‘omics’ approaches, the intricate relationships between metabolism and epigenetics will become more clear [50]. Thus, future research will benefit from focusing on the causal pathways by which metabolites regulate epigenetic modifications, and how epigenetic modifications may result in cellular metabolic programming and pathological states [51]. While the integration of metabolomics into epigenetic research is still in its early stages, it represents a rapidly growing frontier in our understanding of genomic regulation. By exploring the links between cellular metabolism and epigenetic mechanisms, metabolomics has the potential to provide novel mechanistic insights into disease processes and to uncover new biomarkers and therapeutic targets for personalized medicine. As technological advancements continue to enhance the precision and accessibility of metabolomic tools, their contribution to epigenetic research is expected to grow, thus offering promising opportunities for future discovery and innovation. Unravelling the complex metabolic pathways underlying disease states will benefit from interdisciplinary collaboration across all ‘omics’ approaches and will help advance clinical solutions for the effective prevention and treatment of non-communicable diseases. Thomas Kenney (Methodology [equal], Writing – original draft [lead], Writing – review & editing [lead]), Tony Montina (Conceptualization [equal], Methodology [equal], Writing – original draft [equal], Writing – review & editing [equal]), and Gerlinde A. S. Metz (Conceptualization [equal], Writing – original draft [equal], Writing – review & editing [equal]) None declared.

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