Molecular Epidemiology
The approaches developed in Biomolecular Medicine have major application in epidemiological research. In collaboration with those from the School of Public Health at Imperial College we have pioneered the new field of ‘metabolome-wide association’ (MWAS) studies.
This opens up the possibility of testing epidemiologically generated hypotheses at the cellular and physiological level, with discovery of novel metabolic biomarkers that link to environmental exposures and phenotypic traits.
Integrating individual-level molecular profiles within small-area and large-scale population epidemiological studies promises to provide new insight into the environmental and lifestyle factors that influences high-priority diseases such as hypertension, diabetes and cancer. Metabolic profiling provides the opportunity to identify biomarkers of exposure, early effect, early onset and disease progression, and to generate hypotheses about how physiological measurements routinely collected in epidemiological studies are mechanistically related to metabolic phenotype.
Recently, we have used large-scale epidemiological sample sets to clearly demonstrate the metabolic phenotypic clustering by geographical location, and that variation within populations can be meaningfully related to physiological measurements (Holmes et al. 2008). This work has helped derive novel associations between urinary metabolites and blood pressure (see INTERMAP project page) that has provided additional evidence for public health decision making and hypotheses to test relating to the underlying mechanisms of the observed relationships.
Such approaches are also potentially useful in verifying epidemiological questionnaire data (i.e. does reported usage relate well to observed excretion profile) and for investigating the underlying causes of idiosyncratic drug efficacy and toxicity. The analysis of these data have greatly been helped by the continued development and application of novel statistical correlation approaches that can facilitate rapid structure elucidation using spectroscopic profile data (Holmes et al. 2007).
Furthermore, these resources present the opportunity to begin relating xenobiotic and endogenous metabolites in a way that can report on common biochemical mechanisms and highlight populations that may have a heightened risk of adverse consequences to exposure due to lifestyle or other factors.
Key Project
Key Recent Publications
Holmes E, Loo RL, Stamler J, Bictash M, Yap IK, Chan Q, Ebbels T, De Iorio M, Brown IJ, Veselkov KA and others. 2008. Human metabolic phenotype diversity and its association with diet and blood pressure. Nature 453(7193):396-400.
Loo RL, Coen M, Ebbels T, Cloarec O, Maibaum E, Bictash M, Yap I, Elliott P, Stamler J, Nicholson JK and others. 2009. Metabolic profiling and population screening of analgesic usage in nuclear magnetic resonance spectroscopy-based large-scale epidemiologic studies. Anal Chem 81(13):5119-29.
Bictash M, Ebbels TM, Chan Q, Loo RL, Yap IK, Brown IJ, de Iorio M, Daviglus ML, Holmes E, Stamler J and others. Opening up the "Black Box": Metabolic phenotyping and metabolome-wide association studies in epidemiology. J Clin Epidemiol.
Li M, Wang B, Zhang M, Rantalainen M, Wang S, Zhou H, Zhang Y, Shen J, Pang X, Wei H and others. 2008. Symbiotic gut microbes modulate human metabolic phenotypes. Proc Natl Acad Sci U S A 105(6):2117-22.
Dumas ME, Maibaum EC, Teague C, Ueshima H, Zhou B, Lindon JC, Nicholson JK, Stamler J, Elliott P, Chan Q and others. 2006. Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP Study. Anal Chem 78(7):2199-208.
