Now showing 1 - 4 of 4
  • Publication
    Sexual dimorphism, age, and fat mass are key phenotypic drivers of proteomic signatures
    Validated protein biomarkers are needed for assessing health trajectories, predicting and subclassifying disease, and optimizing diagnostic and therapeutic clinical decision-making. The sensitivity, specificity, accuracy, and precision of single or combinations of protein biomarkers may be altered by differences in physiological states limiting the ability to translate research results to clinically useful diagnostic tests. Aptamer based affinity assays were used to test whether low abundant serum proteins differed based on age, sex, and fat mass in a healthy population of 94 males and 102 females from the MECHE cohort. The findings were replicated in 217 healthy male and 377 healthy female participants in the DiOGenes consortium. Of the 1129 proteins in the panel, 141, 51, and 112 proteins (adjusted p < 0.1) were identified in the MECHE cohort and significantly replicated in DiOGenes for sexual dimorphism, age, and fat mass, respectively. Pathway analysis classified a subset of proteins from the 3 phenotypes to the complement and coagulation cascades pathways and to immune and coagulation processes. These results demonstrated that specific proteins were statistically associated with dichotomous (male vs female) and continuous phenotypes (age, fat mass), which may influence the identification and use of biomarkers of clinical utility for health diagnosis and therapeutic strategies.
      407Scopus© Citations 13
  • Publication
    Optimisation of a metabotype approach to deliver targeted dietary advice
    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.
      93Scopus© Citations 18
  • Publication
    Uncovering Factors Related to Pancreatic Beta-Cell Function
    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.
      408Scopus© Citations 4
  • Publication
    Exploring the Links between Diet and Health in an Irish Cohort: A Lipidomic Approach
    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.
      783Scopus© Citations 7