Metabolic profiling strategy for discovery of nutritional biomarkers: proline betaine as a marker of citrus consumption

Abstract

Background: New food biomarkers are needed to objectively evaluate the effect of diet on health and to check adherence to dietary recommendations and healthy eating patterns.

Objective: We developed a strategy for food biomarker discovery, which combined nutritional intervention with metabolic phenotyping and biomarker validation in a large-scale epidemiologic study.

Design: We administered a standardized diet to 8 individuals and established a putative urinary biomarker of fruit consumption by using (1)H nuclear magnetic resonance (NMR) spectroscopic profiling. The origin of the biomarker was confirmed by using targeted NMR spectroscopy of various fruit. Excretion kinetics of the biomarker were measured. The biomarker was validated by using urinary NMR spectra from UK participants of the INTERMAP (International Collaborative Study of Macronutrients, Micronutrients, and Blood Pressure) (n = 499) in which citrus consumption was ascertained from four 24-h dietary recalls per person. Finally, dietary patterns of citrus consumers (n = 787) and nonconsumers (n = 1211) were compared.

Results: We identified proline betaine as a putative biomarker of citrus consumption. High concentrations were observed only in citrus fruit. Most proline betaine was excreted < or =14 h after a first-order excretion profile. Biomarker validation in the epidemiologic data showed a sensitivity of 86.3% for elevated proline betaine excretion in participants who reported citrus consumption and a specificity of 90.6% (P < 0.0001). In comparison with noncitrus consumers, citrus consumers had lower intakes of fats, lower urinary sodium-potassium ratios, and higher intakes of vegetable protein, fiber, and most micronutrients.

Conclusion: The biomarker identification and validation strategy has the potential to identify biomarkers for healthier eating patterns associated with a reduced risk of major chronic diseases. The trials were registered at clinicaltrials.gov as NCT01102049 and NCT01102062.

Figures

FIGURE 1

Identification of putative biomarkers by using metabolite profiling and multivariate analysis. A: Study design for the dietary intervention study (n = 8). B: Representative 1H nuclear magnetic resonance (NMR) spectra of urine specimens in response to fruit consumption (red) compared with the standard (STD) meal (black). Apparent differences are highlighted (dashed rectangles). C: Partial least-squares discriminant analysis (PLS-DA) scores plot of urine specimens 0–24 h after fruit challenge, which shows a clear separation of the fruit and STD meals. All urine specimens from the morning of day 1 to the evening of day 2 were allocated to the STD diet, and all urine specimens collected after consumption of the fruit meal (bed time of day 2 until evening of day 3) were allocated to the fruit class. D: Loading plots of the fruit challenge compared with the STD meal indicated the following putative biomarkers for fruit consumption: hippuric acid (δ 2.97d, 7.55t, 7.64t, and 7.84d), proline betaine (δ 2.18m, δ 2.30m, δ 2.50m, δ 3.11, δ 3.31, and δ 3.54), tartaric acid (δ 4.34s), and unknown (δ 7.74d and δ 6.98d). The P value of proline betaine before fruit consumption compared with after fruit consumption was <0.0001. ppm, parts per million; a.u., arbitrary units; Y, response variable (classification identifier); R2Y, variation of Y modeled; Q2Y, cross-validated variation of Y predicted; T[1], first predictive PLS scores vector; Tyosc [1], first orthogonal PLS score vector.

FIGURE 2

Urinary excretion kinetics of proline betaine after orange juice consumption (n = 6). A: Proline betaine singlet at δ 3.11 was integrated over the spectral region δ 3.106–3.116 as shown where the peak overlap is minimal. B: Mean and SD proline betaine integral (solid bold line) and the proline betaine integral for each of the 6 volunteers plotted over time. The red arrow indicates the time of orange juice consumption. ppm, parts per million.

FIGURE 3

Box plots of urinary proline betaine excretion of volunteers recording no citrus fruit consumption (no citrus), citrus fruit consumption (citrus), and citrus fruit consumption only on day 1 (only D 1). A: Proline betaine in the Belfast (UK) sample (no citrus: n = 96; citrus: n = 96; only D 1: n = 28). B: Proline betaine in the West Bromwich (UK) sample (no citrus: n = 181; citrus: n = 71; only D 1: n = 27). C: Receiver operating characteristic curves to assess the predictive ability of excretion of proline betaine for discrimination of citrus fruit intake and no citrus fruit intake as reported in the dietary recall data for the training set [International Collaborative Study of Macronutrients, Micronutrients, and Blood Pressure (INTERMAP) UK Belfast sample] and test set (INTERMAP UK West Bromwich sample). The optimal operating point (▪) for the training set was a peak integral value of 39.4 for proline betaine. This represented a specificity and sensitivity of 90.6% and 86.3%, respectively, for the training set and 92.3% and 80.6%, respectively, for the validation set.