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Characterizing Blood Metabolomics Profiles Associated with Self-Reported Food Intakes in Female Twins.

ABSTRACT: Using dietary biomarkers in nutritional epidemiological studies may better capture exposure and improve the level at which diet-disease associations can be established and explored. Here, we aimed to identify and evaluate reproducibility of novel biomarkers of reported habitual food intake using targeted and non-targeted metabolomic blood profiling in a large twin cohort. Reported intakes of 71 food groups, determined by FFQ, were assessed against 601 fasting blood metabolites in over 3500 adult female twins from the TwinsUK cohort. For each metabolite, linear regression analysis was undertaken in the discovery group (excluding MZ twin pairs discordant [?1 SD apart] for food group intake) with each food group as a predictor adjusting for age, batch effects, BMI, family relatedness and multiple testing (1.17x10-6 = 0.05/[71 food groups x 601 detected metabolites]). Significant results were then replicated (non-targeted: P<0.05; targeted: same direction) in the MZ discordant twin group and results from both analyses meta-analyzed. We identified and replicated 180 significant associations with 39 food groups (P<1.17x10-6), overall consisting of 106 different metabolites (74 known and 32 unknown), including 73 novel associations. In particular we identified trans-4-hydroxyproline as a potential marker of red meat intake (0.075[0.009]; P = 1.08x10-17), ergothioneine as a marker of mushroom consumption (0.181[0.019]; P = 5.93x10-22), and three potential markers of fruit consumption (top association: apple and pears): including metabolites derived from gut bacterial transformation of phenolic compounds, 3-phenylpropionate (0.024[0.004]; P = 1.24x10-8) and indolepropionate (0.026[0.004]; P = 2.39x10-9), and threitol (0.033[0.003]; P = 1.69x10-21). With the largest nutritional metabolomics dataset to date, we have identified 73 novel candidate biomarkers of food intake for potential use in nutritional epidemiological studies. We compiled our findings into the DietMetab database (http://www.twinsuk.ac.uk/dietmetab-data/), an online tool to investigate our top associations.

SUBMITTER: Pallister T

PROVIDER: S-EPMC4927065 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Characterizing Blood Metabolomics Profiles Associated with Self-Reported Food Intakes in Female Twins.

Pallister Tess T Jennings Amy A Mohney Robert P RP Yarand Darioush D Mangino Massimo M Cassidy Aedin A MacGregor Alexander A Spector Tim D TD Menni Cristina C

PloS one 20160629 6

Using dietary biomarkers in nutritional epidemiological studies may better capture exposure and improve the level at which diet-disease associations can be established and explored. Here, we aimed to identify and evaluate reproducibility of novel biomarkers of reported habitual food intake using targeted and non-targeted metabolomic blood profiling in a large twin cohort. Reported intakes of 71 food groups, determined by FFQ, were assessed against 601 fasting blood metabolites in over 3500 adult ...[more]

PMID: 27355821

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Project description:Background:A limited number of studies have evaluated self-reported dietary intakes against objective recovery biomarkers. Objective:The aim was to compare dietary intakes of multiple Automated Self-Administered 24-h recalls (ASA24s), 4-d food records (4DFRs), and food-frequency questionnaires (FFQs) against recovery biomarkers and to estimate the prevalence of under- and overreporting. Design:Over 12 mo, 530 men and 545 women, aged 50-74 y, were asked to complete 6 ASA24s (2011 version), 2 unweighed 4DFRs, 2 FFQs, two 24-h urine collections (biomarkers for protein, potassium, and sodium intakes), and 1 administration of doubly labeled water (biomarker for energy intake). Absolute and density-based energy-adjusted nutrient intakes were calculated. The prevalence of under- and overreporting of self-report against biomarkers was estimated. Results:Ninety-two percent of men and 87% of women completed ?3 ASA24s (mean ASA24s completed: 5.4 and 5.1 for men and women, respectively). Absolute intakes of energy, protein, potassium, and sodium assessed by all self-reported instruments were systematically lower than those from recovery biomarkers, with underreporting greater for energy than for other nutrients. On average, compared with the energy biomarker, intake was underestimated by 15-17% on ASA24s, 18-21% on 4DFRs, and 29-34% on FFQs. Underreporting was more prevalent on FFQs than on ASA24s and 4DFRs and among obese individuals. Mean protein and sodium densities on ASA24s, 4DFRs, and FFQs were similar to biomarker values, but potassium density on FFQs was 26-40% higher, leading to a substantial increase in the prevalence of overreporting compared with absolute potassium intake. Conclusions:Although misreporting is present in all self-report dietary assessment tools, multiple ASA24s and a 4DFR provided the best estimates of absolute dietary intakes for these few nutrients and outperformed FFQs. Energy adjustment improved estimates from FFQs for protein and sodium but not for potassium. The ASA24, which now can be used to collect both recalls and records, is a feasible means to collect dietary data for nutrition research.

Project description:BackgroundPolycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder accompanied with an increased risk of developing type 2 diabetes mellitus and cardiovascular disease; despite being a common condition, the pathogenesis of PCOS remains unclear. Our aim was to investigate the potential metabolic profiles for different phenotypes of PCOS, as well as for the early prognosis of complications.MethodsA total of 217 women with PCOS and 48 healthy women as normal controls were studied. Plasma samples of subjects were tested using two different analytical platforms of metabolomics: 1H nuclear magnetic resonance (NMR) and gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS).ResultsOur results showed that carbohydrate, lipid and amino acid metabolisms were influenced in PCOS. The levels of lactate, long-chain fatty acids, triglyceride and very low-density lipoprotein were elevated, while glucose, phosphatidylcholine and high-density lipoprotein (HDL) concentrations were reduced in PCOS patients as compared with controls. Additionally, the levels of alanine, valine, serine, threonine, ornithine, phenylalanine, tyrosine and tryptophan were generally increased, whereas the levels of glycine and proline were significantly reduced in PCOS samples compared to controls. Furthermore, the ratio of branched-chain amino acid to aromatic amino acid concentrations (BCAA/AAA) in PCOS plasma was significantly reduced in PCOS patients and was insusceptible to obesity and insulin sensitivity.ConclusionsOur results suggested that the enhanced glycolysis and inhibited tricarboxylic acid cycle (TAC) in women with PCOS. Decrease of BCAA/AAA ratio was directly correlated with the development of PCOS. Ovulatory dysfunction of PCOS patients was associated with raised production of serine, threonine, phenylalanine, tyrosine and ornithine. Elevated levels of valine and leucine, and decreased concentrations of glycine in PCOS plasma could contribute to insulin sensitivity and could be considered as the potential biomarkers for long-term risk assessment of diabetes mellitus.

Project description:ObjectivesTo assess the validity of self-reported weight, height, body mass index (BMI), waist circumference and blood pressure compared with standardized clinical measurements and to determine the classification accuracy in overweight/obesity and central adiposity.MethodsThis pilot study was integrated into a life-course study entitled "Hong Kong Women's Health Study" among 1,253 female nurses in Hong Kong who were aged 35 years to 65 years. Data were collected from self-administered questionnaires that were mailed to the respondents. Of these participants, we obtained the standard body measurements of 144 (11.5%) at our research center. We then compared the self-reported anthropometric variables and blood pressure with the measured data to assess validity based on the level of misreporting, percentage of agreement, consistency, sensitivity and specificity.ResultsThe self-reported and measured values were highly correlated in terms of anthropometry and blood pressure (correlation coefficients ranged from 0.72 to 0.96). Height was overestimated at an average of 0.42 cm, and waist circumference was underestimated at 2.33 cm (both P<0.05), while no significant differences were observed from weight, blood pressure and BMI (all P>0.05). The proportions of overweight, obesity, and central adiposity by self-reported data did not vary greatly from the measured data (all P>0.05). The self-reporting resulted in correct classifications of BMI, waist circumference, and systolic blood pressure in 85%, 78%, and 87% of women, with corresponding Kappa index values of 0.79, 0.55, and 0.82, respectively. Sensitivity and specificity were 84.6% and 95.7%, respectively, with respect to overweight/obesity detection, whereas those for central adiposity detection were 70.6% and 83.8%, respectively.ConclusionIn a sample of female Hong Kong nurses, the self-reported measures of height, weight, BMI, waist circumference and blood pressure were generally valid. Furthermore, the classification accuracies of overweight/obesity and central adiposity were acceptable.

Dataset Information

Characterizing Blood Metabolomics Profiles Associated with Self-Reported Food Intakes in Female Twins.

Publications

Characterizing Blood Metabolomics Profiles Associated with Self-Reported Food Intakes in Female Twins.

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