Options
Brennan, Lorraine
Preferred name
Brennan, Lorraine
Official Name
Brennan, Lorraine
Research Output
Now showing 1 - 10 of 44
- PublicationMetabolomic analysis of bovine pre-implantation embryos(CSIRO Publishing, 2009-12-08)
; ; ; ; 474 - PublicationCombining biomarker and food intake dataRecent developments in biomarker discovery have demonstrated that combining biomarkers with self-reported intake data has the potential to improve estimation of food intake. Here, statistical methods for combining biomarker and self-reported food intake data are discussed. The calibration equations method is a widely applied method that corrects for measurement error in self-reported food intake data through the use of biomarker data. The method is outlined and illustrated through an example where citrus intake is estimated. In order to estimate stable calibration equations, a simulation-based framework is delineated which estimates the percentage of study subjects from whom biomarker data is required. The method of triads is frequently used to assess the validity of self-reported food intake data by combining it with biomarker data. The method is outlined and sensitivity to its underlying assumptions is illustrated through simulation studies.
29 - PublicationEffects of a casein hydrolysate versus intact casein on gastric emptying and amino acid responses(Springer, 2018-01-10)
; ; ; ; Purpose Milk proteins and/or their hydrolysates have been reported to have beneficial effects for improving postprandial glycaemia. Gastric emptying is a major determinant of postprandial glycaemia, yet limited studies have examined the effects of intact milk proteins compared to hydrolysates on gastric emptying. We investigated gastric emptying of a casein hydrolysate compared to intact casein. Methods Nine overweight and obese adults (mean ± SD age: 59.5 ± 6.5 years and BMI 28.4 ± 2.6 kg/m2) were studied in a randomised crossover design. Gastric emptying was assessed by paracetamol absorption test, with HPLC-MS being used for determining paracetamol and its primary metabolites in plasma. Glucose, insulin and amino acid responses were also assessed. Results Linear mixed model analysis showed no effect of treatment [F(1, 55) = 2.1, P = 0.16] or treatment × time interactions [F(6, 54) = 1.5, P = 0.21] for paracetamol concentrations. In addition, there were no significant differences between the intact casein and hydrolysate for any of the gastric emptying outcome measures (Cmax, AUC0–30min, AUC0–60min; AUC0–240min). However, insulin was increased in the early postprandial period (iAUC0–15min, iAUC0–30min; P < 0.05) and there was a treatment effect for glucose [F(1, 53) = 5.3, P = 0.03] following the casein hydrolysate compared to intact casein. No significant differences in amino acids were found between the two conditions. Conclusions Gastric emptying of a casein hydrolysate compared to intact casein does not differ. Mechanisms other than gastric emptying, for example the presence of a bioactive peptide sequence, may contribute to the glycaemic management effects of certain milk protein hydrolysates and warrant further investigation.337Scopus© Citations 6 - PublicationThe Potential of Multi-Biomarker Panels in Nutrition Research: Total Fruit Intake as an Example(Frontiers Media, 2021-01-14)
; ; ; ; ; Dietary and food intake biomarkers offer the potential of improving the accuracy of dietary assessment. An extensive range of putative intake biomarkers of commonly consumed foods have been identified to date. As the field of food intake biomarkers progresses toward solving the complexities of dietary habits, combining biomarkers associated with single foods or food groups may be required. The objective of this work was to examine the ability of a multi-biomarker panel to classify individuals into categories of fruit intake. Biomarker data was measured using H NMR spectroscopy in two studies: (1) An intervention study where varying amounts of fruit was consumed and (2) the National Adult Nutrition Survey (NANS). Using data from an intervention study a biomarker panel (Proline betaine, Hippurate, and Xylose) was constructed from three urinary biomarker concentrations. Biomarker cut-off values for three categories of fruit intake were developed. The biomarker sum cut-offs were ≤ 4.766, 4.766–5.976, >5.976 μM/mOsm/kg for <100, 101–160, and >160 g fruit intake. The ability of the biomarker sum to classify individuals into categories of fruit intake was examined in the cross-sectional study (NANS) (N = 565). Examination of results in the cross-sectional study revealed excellent agreement with self-reported intake: a similar number of participants were ranked into each category of fruit intake. The work illustrates the potential of multi-biomarker panels and paves the way forward for further development in the field. The use of such panels may be key to distinguishing foods and adding specificity to the predictions of food intake. 132Scopus© Citations 5 - 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.567Scopus© Citations 7 - PublicationMetSizeR: selecting the optimal sample size for metabolomic studies using an analysis based approach(BioMed Central, 2013-11-21)
; ; ; ; Background: Determining sample sizes for metabolomic experiments is important but due to the complexity of these experiments, there are currently no standard methods for sample size estimation in metabolomics. Since pilot studies are rarely done in metabolomics, currently existing sample size estimation approaches which rely on pilot data can not be applied. Results: In this article, an analysis based approach called MetSizeR is developed to estimate sample size for metabolomic experiments even when experimental pilot data are not available. The key motivation for MetSizeR is that it considers the type of analysis the researcher intends to use for data analysis when estimating sample size. MetSizeR uses information about the data analysis technique and prior expert knowledge of the metabolomic experiment to simulate pilot data from a statistical model. Permutation based techniques are then applied to the simulated pilot data to estimate the required sample size. Conclusions: The MetSizeR methodology, and a publicly available software package which implements the approach, are illustrated through real metabolomic applications. Sample size estimates, informed by the intended statistical analysis technique, and the associated uncertainty are provided.290Scopus© Citations 76 - PublicationA Metabolomics Approach to the Identification of Urinary Biomarkers of Pea Intake(MDPI, 2018-12-04)
; ; ; ; A significant body of evidence demonstrates that isoflavone metabolites are good markers of soy intake, while research is lacking on specific markers of other leguminous sources such as peas. In this context, the objective of our current study was to identify biomarkers of pea intake using an untargeted metabolomics approach. A randomized cross-over acute intervention study was conducted on eleven participants who consumed peas and couscous (control food) in random order. The urine samples were collected in fasting state and postprandially at regular intervals and were further analysed by ultra-performance liquid chromatography coupled to quadrupole time of flight mass spectrometry (UPLC-QTOF-MS). Multivariate statistical analysis resulted in robust Partial least squares Discriminant Analysis (PLS-DA) models obtained for comparison of fasting against the postprandial time points (0 h vs. 4 h, (R2X = 0.41, Q2 = 0.4); 0 h vs. 6 h, ((R2X = 0.517, Q2 = 0.495)). Variables with variable importance of projection (VIP) scores ≥1.5 obtained from the PLS-DA plot were considered discriminant between the two time points. Repeated measures analysis of variance (ANOVA) was performed to identify features with a significant time effect. Assessment of the time course profile revealed that ten features displayed a differential time course following peas consumption compared to the control food. The interesting features were tentatively identified using accurate mass data and confirmed by tandem mass spectrometry (MS using commercial spectral databases and authentic standards. 2-Isopropylmalic acid, asparaginyl valine and N-carbamoyl-2-amino-2-(4-hydroxyphenyl) acetic acid were identified as markers reflecting pea intake. The three markers also increased in a dose-dependent manner in a randomized intervention study and were further confirmed in an independent intervention study. Overall, key validation criteria were met for the successfully identified pea biomarkers. Future work will examine their use in nutritional epidemiology studies.304Scopus© Citations 12 - PublicationIdentification of a plasma signature of psychotic disorder in children and adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort(Springer Nature, 2017-09-26)
; ; ; ; ; The identification of an early biomarker of psychotic disorder is important as early treatment is associated with improved patient outcome. Metabolomic and lipidomic approaches in combination with multivariate statistical analysis were applied to identify plasma alterations in children (age 11) (38 cases vs 67 controls) and adolescents (age 18) (36 cases vs 117 controls) preceeding or coincident with the development of psychotic disorder (PD) at age 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC). Overall, 179 lipids were identified at age 11, with 32 found to be significantly altered between the control and PD groups. Following correction for multiple comparisons, 8 of these lipids remained significant (lysophosphatidlycholines (LPCs) LPC(18:1), LPC(18:2), LPC(20:3); phosphatidlycholines (PCs) PC(32:2; PC(34:2), PC(36:4), PC(0-34-3) and sphingomyelin (SM) SM(d18:1/24:0)), all of which were elevated in the PD group. At age 18, 23 lipids were significantly different between the control and PD groups, although none remained significant following correction for multiple comparisons. In conclusion, the findings indicate that the lipidome is altered in the blood during childhood, long before the development of psychotic disorder. LPCs in particular are elevated in those who develop PD, indicating inflammatory abnormalities and altered phospholipid metabolism. These findings were not found at age 18, suggesting there may be ongoing alterations in the pathophysiological processes from prodrome to onset of PD.562Scopus© Citations 33 - PublicationThe Relationship between Fish Intake and Urinary Trimethylamine-N-Oxide(Wiley, 2020-02)
; ; ; ; ; ; Scope: Fish intake is reported to be associated with certain health benefits; however, accurate assessment of fish intake is still problematic. The objective of this study is to identify fish intake biomarkers and examine relationships with health parameters in a free‐living population. Methods and results: In the NutriTech study, ten participants randomized into the fish group consume increasing quantities of fish for 3 days per week for 3 weeks. Urine is analyzed by NMR spectroscopy. Trimethylamine‐N‐oxide (TMAO), dimethylamine, and dimethyl sulfone are identified and display significant dose–response with intake (p < 0.05). Fish consumption yields a greater increase in urinary TMAO compared to red meat. Biomarker‐derived fish intake is calculated in the National Adult Nutrition Survey cross‐sectional study. However, the correlation between fish intake and TMAO (r = 0.148, p < 0.01) and that between fish intake and calculated fish intake (r = 0.142, p < 0.01) are poor. In addition, TMAO shows significantly positive correlation with serum insulin and insulin resistance in males and the relationship is more pronounced for males with high dietary fat intake. Conclusion: Urinary TMAO displays a strong dose–response relationship with fish intake; however, use of TMAO alone is insufficient to determine fish intake in a free‐living population.171Scopus© Citations 16 - PublicationImpact of Sample Storage on the NMR Fecal Water Metabolome(ACS, 2018-12-05)
; ; ; ; The study of the fecal metabolome is an important area of research to better understand the human gut microbiome and its impact on human health and diseases. However, there is a lack of work in examining the impact of storage and processing conditions on the metabolite levels of fecal water. Furthermore, there is no universal protocol used for the storage of fecal samples and preparation of fecal water. The objective of the current study was to examine the impact of different storage conditions on fecal samples prior to metabolite extraction. Fecal samples obtained from nine healthy individuals were processed under different conditions: (1) fresh samples prepared immediately after collection, (2) fecal samples stored at 4 °C for 24 h prior to processing, and (3) fecal samples stored at −80 °C for 24 h prior to processing. All samples were analyzed using NMR spectroscopy, multivariate statistical analysis, and repeated measures ANOVA. Samples which were frozen at −80 °C prior to extraction of the metabolites exhibited an increase in the number of metabolites including branched-chain amino acids, aromatic amino acids, and tricarboxylic acid cycle intermediates. Storage of fecal samples at 4 °C ensured higher fidelity to freshly processed samples leading to the recommendation that fecal samples should not be frozen prior to extraction of fecal water. Furthermore, the work highlights the need to standardize sample storage of fecal samples to allow for the accurate study of the fecal metabolome.254Scopus© Citations 11