Carbon and nitrogen isotopic ratios of urine and faeces as novel nutritional biomarkers of meat and fish intake

Purpose Meat and fish consumption are associated with changes in the risk of chronic diseases. Intake is mainly assessed using self-reporting, as no true quantitative nutritional biomarker is available. The measurement of plasma fatty acids, often used as an alternative, is expensive and time-consuming. As meat and fish differ in their stable isotope ratios, δ13C and δ15N have been proposed as biomarkers. However, they have never been investigated in controlled human dietary intervention studies. Objective In a short-term feeding study, we investigated the suitability of δ13C and δ15N in blood, urine and faeces as biomarkers of meat and fish intake. Methods The dietary intervention study (n = 14) followed a randomised cross-over design with three eight-day dietary periods (meat, fish and half-meat–half-fish). In addition, 4 participants completed a vegetarian control period. At the end of each period, 24-h urine, fasting venous blood and faeces were collected and their δ13C and δ15N analysed. Results There was a significant difference between diets in isotope ratios in faeces and urine samples, but not in blood samples (Kruskal–Wallis test, p < 0.0001). In pairwise comparisons, δ13C and δ15N were significantly higher in urine and faecal samples following a fish diet when compared with all other diets, and significantly lower following a vegetarian diet. There was no significant difference in isotope ratio between meat and half-meat–half-fish diets for blood, urine or faecal samples. Conclusions The results of this study show that urinary and faecal δ13C and δ15N are suitable candidate biomarkers for short-term meat and fish intake

Sea, sickness and cautionary tales: a multi-isotope study from a post-mediaeval hospital at the city-port of Gibraltar (AD 1462–1704)

Abstract: During the sixteenth to eighteenth centuries, Spanish ships sailed around the globe connecting Spain to its colonies. While documentary records offer rich details concerning life on board ship, archaeological information is essential to generating a full picture of the past. The cemetery at Old St Bernard’s Hospital, Gibraltar, provides an opportunity to study the skeletal remains of sailors. Following previous osteological research, carbon, nitrogen, oxygen and strontium isotope analyses were undertaken on thirty-three of these individuals. The results show that the, largely male, individuals had various different diets during life and came from several different places. Diets were largely based on C3 food chains; some individuals consumed C3 foods with low δ13C values; others consumed some marine foods, and a few individuals had a high trophic level diet, through the consumption of either freshwater resources or a high proportion of animal protein. The individuals spent their childhoods in several different places, although these homelands do not correlate simply with dietary variation. This variety in diets and homelands is consistent with our expectations for this hospital site given its location in a post-mediaeval entrepôt. The interpretation of these results are greatly helped by the available historical information and this has broader implications for the interpretation of isotope data elsewhere where the historical context of the site and the mobility patterns of the individuals are less well known

Serum carbon and nitrogen stable isotopes as potential biomarkers of dietary intake and their relation with incident type 2 diabetes: the EPIC-Norfolk study.

BACKGROUND: Stable-isotope ratios of carbon (¹³C/¹²C, expressed as δ¹³C) and nitrogen (¹⁵N/¹⁴N, or δ¹⁵N) have been proposed as potential nutritional biomarkers to distinguish between meat, fish, and plant-based foods. OBJECTIVE: The objective was to investigate dietary correlates of δ¹³C and δ¹⁵N and examine the association of these biomarkers with incident type 2 diabetes in a prospective study. DESIGN: Serum δ¹³C and δ¹⁵N (‰) were measured by using isotope ratio mass spectrometry in a case-cohort study (n = 476 diabetes cases; n = 718 subcohort) nested within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk population-based cohort. We examined dietary (food-frequency questionnaire) correlates of δ¹³C and δ¹⁵N in the subcohort. HRs and 95% CIs were estimated by using Prentice-weighted Cox regression. RESULTS: Mean (±SD) δ¹³C and δ¹⁵N were -22.8 ± 0.4‰ and 10.2 ± 0.4‰, respectively, and δ¹³C (r = 0.22) and δ¹⁵N (r = 0.20) were positively correlated (P < 0.001) with fish protein intake. Animal protein was not correlated with δ¹³C but was significantly correlated with δ¹⁵N (dairy protein: r = 0.11; meat protein: r = 0.09; terrestrial animal protein: r = 0.12, P ≤ 0.013). δ¹³C was inversely associated with diabetes in adjusted analyses (HR per tertile: 0.74; 95% CI: 0.65, 0.83; P-trend < 0.001], whereas δ¹⁵N was positively associated (HR: 1.23; 95% CI: 1.09, 1.38; P-trend = 0.001). CONCLUSIONS: The isotope ratios δ¹³C and δ¹⁵N may both serve as potential biomarkers of fish protein intake, whereas only δ¹⁵N may reflect broader animal-source protein intake in a European population. The inverse association of δ¹³C but a positive association of δ¹⁵N with incident diabetes should be interpreted in the light of knowledge of dietary intake and may assist in identifying dietary components that are associated with health risks and benefits.The EPIC-Norfolk study is supported by program grants from the Medical Research Council UK and Cancer Research UK. MRC Epidemiology Unit core support is acknowledged (MC_UU_12015/1 and MC_UU_12015/5). TCO and CKK were supported by the Wellcome Trust (grant no. 074229/Z/04/Z).This version is the published accepted manuscript, distributed under a Creative Commons Attribution License 2.0. It can also be found on the publisher's website at: http://ajcn.nutrition.org/content/early/2014/07/02/ajcn.113.068577.abstrac

On the Use of Biomineral Oxygen Isotope Data to Identify Human Migrants in the Archaeological Record: Intra-Sample Variation, Statistical Methods and Geographical Considerations

<div><p>Oxygen isotope analysis of archaeological skeletal remains is an increasingly popular tool to study past human migrations. It is based on the assumption that human body chemistry preserves the δ¹⁸O of precipitation in such a way as to be a useful technique for identifying migrants and, potentially, their homelands. In this study, the first such global survey, we draw on published human tooth enamel and bone bioapatite data to explore the validity of using oxygen isotope analyses to identify migrants in the archaeological record. We use human δ¹⁸O results to show that there are large variations in human oxygen isotope values within a population sample. This may relate to physiological factors influencing the preservation of the primary isotope signal, or due to human activities (such as brewing, boiling, stewing, differential access to water sources and so on) causing variation in ingested water and food isotope values. We compare the number of outliers identified using various statistical methods. We determine that the most appropriate method for identifying migrants is dependent on the data but is likely to be the IQR or median absolute deviation from the median under most archaeological circumstances. Finally, through a spatial assessment of the dataset, we show that the degree of overlap in human isotope values from different locations across Europe is such that identifying individuals’ homelands on the basis of oxygen isotope analysis alone is not possible for the regions analysed to date. Oxygen isotope analysis is a valid method for identifying first-generation migrants from an archaeological site when used appropriately, however it is difficult to identify migrants using statistical methods for a sample size of less than <i>c</i>. 25 individuals. In the absence of local previous analyses, each sample should be treated as an individual dataset and statistical techniques can be used to identify migrants, but in most cases pinpointing a specific homeland should not be attempted.</p></div

Histogram of oxygen isotope values for all European individuals in the Post-Infant Dentition data-subset.

<p>Histogram of oxygen isotope values for all European individuals in the Post-Infant Dentition data-subset.</p

The proportion of outliers found at each site using the five different outlier identification methods, plotted by site sample size, for all sites where N>4 in the Post-Infant Dentition data-subset.

<p>For some of methods, there are multiple apparent curves for sample sizes between 5 and 25. This is an artefact of producing estimates of either one, two or three outliers within the sample, producing “curves” of 1/x where x is the number of outliers (i.e. 1, 2 or 3).</p

Histogram of the difference between each individual’s oxygen isotope value and (a) the site mean oxygen isotopic value or (b) the site median oxygen isotopic value, for all specimens from sites where N>4 in the Post-Infant Dentition data-subset.

<p>Histogram of the difference between each individual’s oxygen isotope value and (a) the site mean oxygen isotopic value or (b) the site median oxygen isotopic value, for all specimens from sites where N>4 in the Post-Infant Dentition data-subset.</p

The limits of the ‘local’ signal of the different outlier identification methods for European sites, calculated: (a) by country, (b) by lat/long grid square, (c) by altitude, (d) by site-specific modern precipitation oxygen isotopic values (δ¹⁸O_MAP).

<p>Plotted for groupings with N>4. Criteria of each method (2SD, 1.5IQR, 3MAD_norm, 3MAD_Q3) as defined in the text. (a) Full data in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0153850#pone.0153850.s014" target="_blank">S4 Table</a>, the countries are statistically different: H(8) = 297.67, P<0.001. (b) Full data including alphanumeric codes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0153850#pone.0153850.s015" target="_blank">S5 Table</a>, the grid squares are statistically different: H(12) = 312.50, P<0.001. (c) Full data in S6, data binned in 150m intervals, the altitudinal groups are statistically different: H(4) = 155.94, P<0.001. (d) Full data in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0153850#pone.0153850.s017" target="_blank">S7 Table</a>, δ¹⁸O_MAP data binned in 1‰ intervals, the precipitation oxygen isotope groups are statistically different: H(3) = 93.78, P<0.001.</p

Descriptive statistics for data in the Post-Infant Dentition data-subset from the sites of Velim-Velištak, Kaminaljuyu and Ban Non Wat, in comparison to the numbers of outliers found using the five different outlier identification methods.

<p>Descriptive statistics for data in the Post-Infant Dentition data-subset from the sites of Velim-Velištak, Kaminaljuyu and Ban Non Wat, in comparison to the numbers of outliers found using the five different outlier identification methods.</p