Applications | Epidemiology
Epidemiology
Explore the intersection of metabolomics and epidemiology to decode the body’s molecular blueprint and transform population health.
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Metabolomics in Epidemiology Research
Epidemiology studies largely rely on human genomics data from large cohorts to predict genetic associations of a given disease. However, genomics alone often presents more questions than answers, particularly when multiple genes contribute to a disease phenotype (polygenic diseases) and clear genetic signatures are difficult to establish. Additionally, genomics does not capture the environmental contributions (e.g., diet, lifestyle, microbiome, etc.) of individuals or populations, which contribute greatly to disease risk, presentation of symptoms, and healthcare outcomes. Moreover, a challenge faced by population health researchers is the ability to consistently and reliably collect patient samples, often slowing or even preventing completion of population health studies.
Metabolomics data is a readout of the functional phenotype. Thus, the combination of metabolomics and genomics captures the result of both the genetic root(s) and environmental contributors leading to disease in a study population. Metabolomics can support epidemiology research by measuring changes in metabolite levels from a range of biological samples, including blood, urine, feces, and tissues, which can then be mapped to the appropriate biochemical pathways. They can then guide re-analysis of genomics data to identify additional genes that contribute to the phenotype, as well as support a mechanistic and functional understanding of disease biology. In this way, metabolomics can provide researchers and clinicians with a more comprehensive understanding of how genes, microbiome, diet, lifestyle, and treatments influence health and disease in both individuals and populations.
Uncover Functional, Actionable Insights with Metabolomics
To fully understand health and disease in individuals and populations, we need to understand how genes and the environment interact to influence disease and health outcomes. Metabolon can help researchers fill in crucial knowledge gaps by providing the functional phenotype readout, which can then be combined with genetic and other data to fully understand disease risk, presentation, and outcome.
Reliable Sampling Methods
Metabolon has validated the use of alternative sampling methods for metabolomics analysis to support large-scale metabolomics research needs. For example, although 150 µl of blood product (whole, plasma, serum) is ideal to run untargeted metabolomics on our Global Discovery Panel, Metabolon-validated dried blood spot (DBS) cards and Neoteryx microsampling devices not only allow for easier sample collection, but also require far less volume to be tested for consistent and reliable metabolic changes. Additionally, through our collaboration with DNA Genotek, we validated metabolomic stability of temporary ambient temperature collection and storage using the OMNImet®•GUT device for clinic or at-home stool sample collection. This dramatically expands the accessibility of metabolomics for gut microbiome studies. These novel sampling methods for metabolomics research provide a low-cost and effective solution to tackle the challenge of sample collection in large-scale population health studies.
De Bruin OM, Freinkman E, Breton H, et al. OMNImet®•GUT enables at-home collection and ambient temperature transport of fecal samples for metabolomics. 2020. PD-WP-00066.pdf (dnagenotek.com)
Diener C, Dai CL, Wilmanski T. et al. Genome–microbiome interplay provides insight into the determinants of the human blood metabolome. Nat Metab. 2022; 4: 560–1572 (2022). doi:10.1038/s42255-022-00670-1
Comprehensive Biomarker Discovery
Metabolomics allows for the identification of a wide range of small molecules (metabolites) in biological samples. This comprehensive approach can uncover novel biomarkers associated with various health conditions. These biomarkers can be used for early disease detection, risk assessment, and monitoring health outcomes in populations. Identifying specific metabolites linked to diseases or health trends can inform targeted interventions and personalized medicine approaches. For example, researchers performed an in-depth analysis of circulating lipids in patients suffering critical illness as a result of trauma, observing delayed and selective lipogenesis in patients that remained critically ill. Phosphatidylethanolamines, specifically, remained elevated in patients with persistent critical illness, suggesting that an increase in systemic PE levels could serve as a prognostic biomarker for critical illness.
Wu J, Cyr A, Gruen DS, et al. Lipidomic signatures align with inflammatory patterns and outcomes in critical illness. Nat Commun. 2022;13(1):6789. doi: 10.1038/s41467-022-34420-4
Personalized and Precision Medicine
Metabolomics can contribute to the advancement of personalized and precision medicine. By analyzing an individual’s metabolomic profile, healthcare providers can tailor treatments and interventions to their unique metabolic characteristics. In population health research, this approach can be scaled to identify subpopulations with specific metabolic signatures, allowing for targeted interventions and healthcare strategies. This personalized approach can lead to more effective healthcare delivery and improved outcomes for individuals within a population. For example, the NHLBI Trans-Omics for Precision Medicine (TOPMed) study associated metabolites with genes in multi-ethnic populations to understand human disease.
Feofanova EV, Brown MR, Alkis T, et al. Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations. Nat Commun. 2023;14(1):3111. doi:10.1038/s41467-023-38800-2
Metabolomics Applications for Epidemiology Research
- EValidation of sampling methods
- EBiomarker discovery
- EDisease risk assessment
- EEarly disease detection
- EHealth outcome monitoring
- EPersonalized medicine research
- EIdentification of gene-metabolite associations
- EPopulation health strategies
- EPrecision medicine research
“We found that genetic variants that regulate metabolite levels were more likely to influence gene expression and disease risk compared to the ones that do not.”
Yin X, Bose D, Kown A et al.
Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk. Am J Hum Genet. 2022;109(10):1727-1741. doi: 10.1016/j.ajhg.2022.08.007
Metabolomics Insights into Epidemiology
The IMPACC cohort study, involving over 1,000 hospitalized COVID-19 patients, employs a comprehensive multiomics approach to investigate acute infection dynamics. This extensive analysis, encompassing more than 15,000 longitudinal samples from 540 participants, utilizes 14 distinct assays across various omics disciplines. Notably, metabolomics plays a pivotal role within this multiomics framework, focusing on the analysis of metabolites and lipids in blood samples. The study categorizes patients into five disease trajectory groups based on severity, and within 72 hours of hospital admission, unbiased analyses identify distinct cellular and molecular signatures that differentiate between moderate and severe/fatal COVID-19 cases. Metabolomics, integrated with other omics, provides a holistic understanding of the host’s immune responses and molecular alterations associated with different disease trajectories, offering valuable insights for clinical prognosis and potential therapeutic interventions.
Figure 1. Association of plasma metabolomics modules with clinical trajectory groups. For each boxplot, the vertical line indicates the median, the box indicates the interquartile range, and the whiskers indicate 1.5 times the interquartile range.
The metabolomics contribution in this study enriches the multiomics approach by delving into the host’s metabolic response to SARS-CoV-2 infection. Through the analysis of metabolites and lipids in blood samples, researchers identified specific metabolic changes associated with disease severity. This emphasis on metabolomics enhances the overall depth and comprehensiveness of the investigation, allowing for a nuanced exploration of the intricate interplay between metabolic processes and the immune response during acute COVID-19 infection. By integrating metabolomics with other omics techniques, the study not only highlights the significance of metabolic alterations in shaping clinical outcomes but also provides a more comprehensive view of the molecular dynamics underpinning the heterogeneity observed in COVID-19 cases.
Diray-Arce J, Fourati S, Doni Jayavelu N, et al. Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients. Cell Rep Med. 2023;4(6):101079. doi:10.1016/j.xcrm.2023.101079
Epidemiology Publications and Citations
Metabolon has contributed extensively to publications ranging from basic research to clinical trials.
Epidemiology Knowledge Base
Dive deeper by viewing our case studies and webinars. Learn more about how Metabolon furthers epidemiology research and check back for more to stay up to date on the latest developments in metabolomics in epidemiology.
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