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Abstract 1H Nuclear Magnetic Resonance spectroscopy (1H NMR) is increasingly used to measure metabolite concentrations in sets of biological samples for top‐down systems biology and molecular epidemiology. For such purposes, knowledge of the sources of human variation in metabolite concentrations is valuable, but currently sparse. We conducted and analysed a study to create such a resource. In our unique design, identical and non‐identical twin pairs donated plasma and urine samples longitudinally. We acquired 1H NMR spectra on the samples, and statistically decomposed variation in metabolite concentration into familial (genetic and common‐environmental), individual‐environmental, and longitudinally unstable components. We estimate that stable variation, comprising familial and individual‐environmental factors, accounts on average for 60% (plasma) and 47% (urine) of biological variation in 1H NMR‐detectable metabolite concentrations. Clinically predictive metabolic variation is likely nested within this stable component, so our results have implications for the effective design of biomarker‐discovery studies. We provide a power‐calculation method which reveals that sample sizes of a few thousand should offer sufficient statistical precision to detect 1H NMR‐based biomarkers quantifying predisposition to disease.

We have performed a metabolite quantitative trait locus (mQTL) study of the (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) metabolome in humans, building on recent targeted knowledge of genetic drivers of metabolic regulation. Urine and plasma samples were collected from two cohorts of individuals of European descent, with one cohort comprised of female twins donating samples longitudinally. Sample metabolite concentrations were quantified by (1)H NMR and tested for association with genome-wide single-nucleotide polymorphisms (SNPs). Four metabolites' concentrations exhibited significant, replicable association with SNP variation (8.6×10(-11)

NMR is a robust analytical technique that has been employed to investigate the properties of many substances of agricultural relevance. NMR was first used to investigate the properties of milk in the 1950s and has since been employed in a wide range of studies; including properties analysis of specific milk proteins to metabolomics techniques used to monitor the health of dairy cows. In this brief review, we highlight the different uses of NMR in the dairy industry.