Gibney, Eileen R.
Gibney, Eileen R.
Gibney, Eileen R.
Now showing 1 - 7 of 7
- PublicationExploring the Links between Diet and Health in an Irish Cohort: A Lipidomic Approach(American Chemical Society, 2017-02-01)
; ; ; ; ; ; ;Epidemiology and clinical studies provide clear evidence of the complex links between diet and health. To understand these links, reliable dietary assessment methods are pivotal. Biomarkers have emerged as more objective measures of intake compared with traditional dietary assessment methods. However, there are only a limited number of putative biomarkers of intake successfully identified and validated. The use of biomarkers that reflect food intake to examine diet related diseases represents the next step in biomarker research. Therefore, the aim of this study was to (1) identify and confirm biomarkers associated with dietary fat intake and (2) examine the relationship between those biomarkers with health parameters. Heatmap analysis identified a panel of 22 lipid biomarkers associated with total dietary fat intake in the Metabolic Challenge (MECHE) Study. Confirmation of four of these biomarkers demonstrated responsiveness to different levels of fat intake in a separate intervention study (NutriTech study). Linear regression identified a significant relationship between the panel of dietary fat biomarkers and HOMA-IR, with three lipid biomarkers (C16, PCaaC36:2, and PCae36:4) demonstrating significant associations. Identifying such links allows us to explore the relationship between diet and health to determine whether these biomarkers can be modulated through diet to improve health outcomes. 569Scopus© Citations 7
- PublicationWithin-person reproducibility and sensitivity to dietary change of C15:0 and C17:0 levels in dried blood spots: data from the European Food4Me Study(Wiley, 2017-10)
; ; ; ; ; ; ; ; ; ;ScopePrevious work highlighted the potential of odd-chain length saturated fatty acids as potential markers of dairy intake. The aim of this study was to assess the reproducibility of these biomarkers and their sensitivity to changes in dairy intake.Methods and ResultsFatty acid profiles and dietary intakes from food frequency questionnaires (FFQs) were measured three times over six months in the Food4Me Study. Reproducibility was explored through intra-class correlation coefficients (ICCs) and within-subject coefficients of variation (WCV). Sensitivity to changes in diet was examined using regression analysis. C15:0 blood levels showed high correlation over time (ICC: 0.62, 95% CI: 0.57, 0.68), however, the ICC for C17:0 was much lower (ICC: 0.32, 95% CI: 0.28, 0.46). The WCV for C15:0 was 16.6% and that for C17:0 was 14.6%. There were significant associations between changes in intakes of total dairy, high-fat dairy, cheese and butter and C15:0; and change in intakes of high-fat dairy and cream and C17:0.ConclusionsResults provide evidence of reproducibility of C15:0 levels over time and sensitivity to change in intake of high-fat dairy products with results comparable to the well-established biomarker of fish intake (EPA+DHA). 356Scopus© Citations 10
- PublicationPatterns of dairy food intake, body composition and markers of metabolic health in Ireland: Results from the National Adult Nutrition Survey(Springer, 2017-02-20)
; ; ; ;Background: Studies examining the association between dairy consumption and metabolic health have shown mixed results. This may be due, in part, to the use of different definitions of dairy, and to single types of dairy foods examined in isolation. Objective: The objective of the study was to examine associations between dairy food intake and metabolic health, identify patterns of dairy food consumption and determine whether dairy dietary patterns are associated with outcomes of metabolic health, in a cross-sectional survey. Design:A 4-day food diary was used to assess food and beverage consumption, including dairy (defined as milk, cheese, yogurt, cream and butter) in free-living, healthy Irish adults aged 18-90 years (n=1500). Fasting blood samples (n=897) were collected, and anthropometric measurements taken. Differences in metabolic health markers across patterns and tertiles of dairy consumption were tested via analysis of covariance. Patterns of dairy food consumption, of different fat contents, were identified using cluster analysis. Results: Higher (total) dairy was associated with lower body mass index, %body fat, waist circumference and waist-to-hip ratio (P<0.001), and lower systolic (P=0.02) and diastolic (P<0.001) blood pressure. Similar trends were observed when milk and yogurt intakes were considered separately. Higher cheese consumption was associated with higher C-peptide (P<0.001). Dietary pattern analysis identified three patterns (clusters) of dairy consumption; 'Whole milk', 'Reduced fat milks and yogurt' and 'Butter and cream'. The 'Reduced fat milks and yogurt' cluster had the highest scores on a Healthy Eating Index, and lower-fat and saturated fat intakes, but greater triglyceride levels (P=0.028) and total cholesterol (P=0.015). conclusion: Overall, these results suggest that while milk and yogurt consumption is associated with a favourable body phenotype, the blood lipid profiles are less favourable when eaten as part of a low-fat high-carbohydrate dietary pattern. More research is needed to better understand this association. Conclusion: Overall, these results suggest that although milk and yogurt consumption is associated with a favourable body phenotype, the blood lipid profiles are less favourable when eaten as part of a low-fat high-carbohydrate dietary pattern. More research is needed to better understand this association. 220
- PublicationOptimisation of a metabotype approach to deliver targeted dietary advice(BMC, 2020-09-29)
; ; ; ;Background: Targeted nutrition is defined as dietary advice tailored at a group level. Groups known as metabotypes can be identified based on individual metabolic profiles. Metabotypes have been associated with differential responses to diet, which support their use to deliver dietary advice. We aimed to optimise a metabotype approach to deliver targeted dietary advice by encompassing more specific recommendations on nutrient and food intakes and dietary behaviours. Methods: Participants (n = 207) were classified into three metabotypes based on four biomarkers (triacylglycerol, total cholesterol, HDL-cholesterol and glucose) and using a k-means cluster model. Participants in metabotype-1 had the highest average HDL-cholesterol, in metabotype-2 the lowest triacylglycerol and total cholesterol, and in metabotype-3 the highest triacylglycerol and total cholesterol. For each participant, dietary advice was assigned using decision trees for both metabotype (group level) and personalised (individual level) approaches. Agreement between methods was compared at the message level and the metabotype approach was optimised to incorporate messages exclusively assigned by the personalised approach and current dietary guidelines. The optimised metabotype approach was subsequently compared with individualised advice manually compiled. Results: The metabotype approach comprised advice for improving the intake of saturated fat (69% of participants), fibre (66%) and salt (18%), while the personalised approach assigned advice for improving the intake of folate (63%), fibre (63%), saturated fat (61%), calcium (34%), monounsaturated fat (24%) and salt (14%). Following the optimisation of the metabotype approach, the most frequent messages assigned to address intake of key nutrients were to increase the intake of fruit and vegetables, beans and pulses, dark green vegetables, and oily fish, to limit processed meats and high-fat food products and to choose fibre-rich carbohydrates, low-fat dairy and lean meats (60-69%). An average agreement of 82.8% between metabotype and manual approaches was revealed, with excellent agreements in metabotype-1 (94.4%) and metabotype-3 (92.3%). Conclusions: The optimised metabotype approach proved capable of delivering targeted dietary advice for healthy adults, being highly comparable with individualised advice. The next step is to ascertain whether the optimised metabotype approach is effective in changing diet quality. 18Scopus© Citations 10
- PublicationPhenotypic factors influencing the variation in response of circulating cholesterol level to personalised dietary advice in the Food4me study(Cambridge University Press, 2016-12)
; ; ; ; ; ; ; ; ;Individual response to dietary interventions can be highly variable. The phenotypic characteristics of those who will respond positively to personalised dietary advice are largely unknown. The objective of this study was to compare the phenotypic profiles of differential responders to personalised dietary intervention, with a focus on total circulating cholesterol. Subjects from the Food4Me multi-centre study were classified as responders or non-responders to dietary advice based on the change in cholesterol level from baseline to month 6, with lower and upper quartiles defined as the responder and non-responder groups, respectively. There were no significant differences between the demographic and anthropometric profiles of the groups. Furthermore, with the exception of alcohol, there was no significant difference in reported dietary intake, at baseline. However, there were marked differences in baseline fatty acid profiles. The responder group had significantly higher levels of stearic acid (18:0, p=0.034) and lower levels of palmitic acid (16:0, p=0.009). Total monounsaturated fatty acids (p=0.016) and total polyunsaturated fatty acids (p=0.008) also differed between the groups. In a stepwise logistic regression model, age, baseline total cholesterol, glucose, five fatty acids and alcohol intake were selected as factors that successfully discriminated responders from non-responders, with sensitivity of 82% and specificity of 83%. The successful delivery of personalised dietary advice may depend on our ability to identify phenotypes that are responsive. The results demonstrate the potential use of metabolic profiles in identifying response to an intervention and could play an important role in the development of precision nutrition. 371Scopus© Citations 12
- PublicationUncovering Factors Related to Pancreatic Beta-Cell Function(Public Library of Science, 2016-08-18)
; ; ; ; ; ;Aim: The incidence of type 2 diabetes has increased rapidly on a global scale. Beta-cell dysfunction contributes to the overall pathogenesis of type 2 diabetes. However, factors contributing to beta-cell function are not clear. The aims of this study were (i) to identify factors related to pancreatic beta-cell function and (ii) to perform mechanistic studies in vitro. Methods: Three specific measures of beta-cell function were assessed for 110 participants who completed an oral glucose tolerance test as part of the Metabolic Challenge Study. Anthropometric and biochemical parameters were assessed as potential modulators of beta-cell function. Subsequent in vitro experiments were performed using the BRIN-BD11 pancreatic beta-cell line. Validation of findings were performed in a second human cohort. Results: Waist-to-hip ratio was the strongest anthropometric modulator of beta-cell function, with beta-coefficients of -0.33 (p = 0.001) and -0.30 (p = 0.002) for beta-cell function/homeostatic model assessment of insulin resistance (HOMA-IR), and disposition index respectively. Additionally, the resistin-to-adiponectin ratio (RA index) emerged as being strongly associated with beta-cell function, with beta-coefficients of -0.24 (p = 0.038) and -0.25 (p = 0.028) for beta-cell function/HOMA-IR, and disposition index respectively. Similar results were obtained using a third measure for beta-cell function. In vitro experiments revealed that the RA index was a potent regulator of acute insulin secretion where a high RA index (20ng ml-1 resistin, 5nmol l-1 g-adiponectin) significantly decreased insulin secretion whereas a low RA index (10ng ml-1 resistin, 10nmol l-1 g-adiponectin) significantly increased insulin secretion. The RA index was successfully validated in a second human cohort with beta-coefficients of -0.40 (p = 0.006) and -0.38 (p = 0.008) for beta-cell function/ HOMA-IR, and disposition index respectively. Conclusions: Waist-to-hip ratio and RA index were identified as significant modulators of beta-cell function. The ability of the RA index to modulate insulin secretion was confirmed in mechanistic studies. Future work should identify strategies to alter the RA index. 336Scopus© Citations 4
- PublicationCapturing health and eating status through a Nutritional Perception Screening Questionnaire (NPSQ9) in a randomised internet-based Personalised Nutrition intervention: the Food4Me study(BioMed Central, 2017-12-11)
; ; ; ; ; ; ; ; ; ;Background: National guidelines emphasize healthy eating to promote wellbeing and prevention of non-communicable diseases. The perceived healthiness of food is determined by many factors affecting food intake. A positive perception of healthy eating has been shown to be associated with greater diet quality. Internet-based methodologies allow contact with large populations. Our present study aims to design and evaluate a short nutritional perception questionnaire, to be used as a screening tool for assessing nutritional status, and to predict an optimal level of personalisation in nutritional advice delivered via the Internet. Methods: Data from all participants who were screened and then enrolled into the Food4Me proof-of-principle study (n = 2369) were used to determine the optimal items for inclusion in a novel screening tool, the Nutritional Perception Screening Questionnaire-9 (NPSQ9). Exploratory and confirmatory factor analyses were performed on anthropometric and biochemical data and on dietary indices acquired from participants who had completed the Food4Me dietary intervention (n = 1153). Baseline and intervention data were analysed using linear regression and linear mixed regression, respectively. Results: A final model with 9 NPSQ items was validated against the dietary intervention data. NPSQ9 scores were inversely associated with BMI (β = −0.181, p < 0.001) and waist circumference (Β = −0.155, p < 0.001), and positively associated with total carotenoids (β = 0.198, p < 0.001), omega-3 fatty acid index (β = 0.155, p < 0.001), Healthy Eating Index (HEI) (β = 0.299, p < 0.001) and Mediterranean Diet Score (MDS) (β = 0. 279, p < 0.001). Findings from the longitudinal intervention study showed a greater reduction in BMI and improved dietary indices among participants with lower NPSQ9 scores. Conclusions: Healthy eating perceptions and dietary habits captured by the NPSQ9 score, based on nine questionnaire items, were associated with reduced body weight and improved diet quality. Likewise, participants with a lower score achieved greater health improvements than those with higher scores, in response to personalised advice, suggesting that NPSQ9 may be used for early evaluation of nutritional status and to tailor nutritional advice. 609Scopus© Citations 10