Metabolomics is the study of small-molecule metabolites in biospecimens such as blood or urine. In recent years, new analytical technologies and metabolomics methods have made it possible to measure thousands of metabolites simultaneously—a remarkable advance that could greatly accelerate progress in molecular epidemiology research. The goals of MEB’s research in metabolomics are: 1) to conduct foundational methods research in the field; 2) to identify biomarkers related to diet/nutritional supplements, energy balance, and other exposures of interest to cancer research; and 3) to identify metabolic factors associated with risk in studies of cancer etiology, survival, and overall mortality.
Metabolomics methods continue to evolve rapidly, with new platforms emerging each year. To ensure that these state-of-the-art technologies are scientifically validated, MEB regularly undertakes methodological studies that quantify lab reliability. We also evaluate effects of sample collection method and other handling factors on metabolite levels, and we conduct studies using multiple sample types (e.g., serum, urine, feces) so that we can compare findings by sample type.
In the metabolomics field, there have been many recent intriguing findings, but they stem from studies with small sample sizes. There is thus a need for large studies that can validate findings and demonstrate their generalizability across many populations. Toward that end, MEB has played a key role in developing the Consortium of METabolomics Studies (COMETS), a consortium of 70+ prospective cohorts devoted to the study of human disease. As a COMETS partner, MEB has helped design novel methods for streamlining and standardizing data analyses across dozens of institutions. Among other efforts, we contribute to the development of data analysis software, harmonization of metabolite meta-data, and evaluation of platform comparability through split sample studies.
Biomarkers of Diet/Nutritional Supplements, Energy Balance, and Other Exposures
As MEB and other studies have shown, metabolomic analyses excel at capturing biomarkers of exposures, including biomarkers of diet/nutrition, adiposity, and environmental and chemical hazards. MEB uses metabolomics to examine exposures that may be difficult to measure, such as intake of foods that are not captured well by questionnaires or biomarkers of excess heating of food. To identify such biomarkers, investigators analyze data from randomized trials, feeding studies and other controlled studies, and long-term exposure studies based on, for example, repeat 24-hour recall instruments. MEB also uses metabolomics to characterize the biological effects of common exposures, such as examining plasma and serum metabolic profiles of sodium intake, lipid-soluble vitamins D, E and A, tooth loss, and excess adiposity. Such metabolites can then be carried forward to etiologic studies to examine associations with cancer and other health outcomes. Additionally, MEB also studies interrelationships between metabolites and the microbiome.
For more information, contact Demetrius Albanes or Rachael Stolzenberg-Solomon.
Studies of Cancer Etiology and Survival
Recent cancer cell biology research highlights that malignancies are, in many respects, metabolic diseases, but epidemiologic data on cancer’s metabolic causes have been sparse. MEB conducts several types of metabolomics studies to investigate metabolism’s role in cancer etiology and survival. In prospective nested case-control studies, MEB investigators have been examining associations between 100s to 1000s of metabolites from pre-diagnostic blood and risk of cancers of the prostate, pancreas, breast, liver, colon, and kidney. Investigators have also leveraged specialized assays to optimize measurement of bile acids and lipids (e.g., lipidomics) in further etiologic studies. Many MEB studies particularly examine whether metabolites explain known exposure-cancer relationships, such as the associations of obesity, alcohol, coffee, and vitamin supplement use with cancer risk. In these studies, investigators quantify the degree to which distinct exposure-related metabolites mediate known associations and explore the mechanistic pathways implicated by those metabolites. Going beyond cancer endpoint studies, MEB and other DCEG investigators also use metabolomics to clarify the biology of important cancer precursors such as nonalcoholic fatty liver disease, Li-Fraumeni syndrome, and monoclonal gammopathy of undetermined significance. We also are using metabolomics to evaluate associations of metabolites with overall mortality and cancer survivorship.
- Loftfield E, Vogtmann E, Sampson JN, [...] Sinha R. Comparison of collection methods for fecal samples for discovery metabolomics in epidemiologic studies. Cancer Epidemiol Biomarkers Prev 2016.
- Yu B, [...] Albanes D, [...] Matthews CE, [...] Stolzenberg-Solomon R, [...] Moore SC. The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 prospective cohort studies. Am J Epidemiol 2019.
- Derkach A, Sampson J, Joseph J, Playdon MC, Stolzenberg-Solomon RZ. Effects of dietary sodium on metabolites: The Dietary Approaches to Stop Hypertension (DASH)-Sodium Feeding Study. Am J Clin Nutr 2017.
- Moore SC, Playdon MC, Sampson JN, et al. A metabolomics analysis of body mass index and postmenopausal breast cancer risk. J Natl Cancer Inst 2018.
- Loftfield E, Rothwell JA, Sinha R, [...] Freedman ND. Prospective investigation of serum metabolites, coffee drinking, liver cancer incidence, and liver disease mortality. J Natl Cancer Inst 2020.
- Mondul AM, Moore SC, Weinstein SJ, Karoly ED, Sampson JN, Albanes D. Metabolomic analysis of prostate cancer risk in a prospective cohort: The alpha-tocopherol, beta-carotene cancer prevention (ATBC) study. Int J Cancer 2015.
- Huang J, Mondul AM, Weinstein SJ, Derkach A, Moore SC, Sampson JN, Albanes D. Prospective serum metabolomic profiling of lethal prostate cancer. Int J Cancer 2019.
- Stolzenberg-Solomon R, Derkach A, Moore S, Weinstein SJ, Albanes D, Sampson J. Associations between metabolites and pancreatic cancer risk in a large prospective epidemiological study. Gut 2020.