Dairy fat and metabolic health - Understanding the role of the food matrix

Cardiovascular disease (CVD) is the leading cause of death worldwide and is commonly associated with modifiable risk factors such as an unhealthy diet. Most studies to date examining the link between food intake and risk of CVD, have focused on modulation of plasma cholesterol concentrations (total cholesterol (TC), LDL-C). However, measurements of LDL-C and HDL-C do not consider the concentrations or complex functions of particles, which can provide further insight into CVD risk. The main objective was to examine the role of the food matrix in the link between saturated fat intake and metabolic health, focusing on sensitive risk markers; LDL particle size and HDL composition. Data from two intervention trials within the Food for Health Ireland (FHI) ‘Healthy Cheese’ work package were used to inform the four experimental chapters in this thesis; the Cheese Matrix intervention trial and the Cheese Melting intervention trial. Data from the Cheese Matrix trial was further analysed and particle size analysis was conducted using NMR, the results suggested that a 6 wk intervention with ~42g of dairy fat per day, in different dairy matrices, resulted in relatively similar effects on the distribution of lipoprotein subclasses, irrespective of the dairy food matrix (cheese or butter). The findings highlighted an overall transition from small LDL particles towards larger LDL particles across all of the groups following dairy fat consumption, potentially indicating beneficial effects on cardiovascular risk profiles. Underlying interindividual variance was further elucidated within this cohort by identifying ‘responders’ and ‘non responders’, determined by change in LDL particle concentrations. The results suggested that the baseline phenotypic characteristics may have influenced the changes observed in biochemical measurements (LDL particle concentrations) postintervention. The main predictors of response based on change (Δ) in total LDL particles and Δ small LDL particles, were the baseline levels of these respective parameters i.e., those identified as responders, had higher levels of the LDL particles at baseline, and this was despite adjustment for baseline. Baseline levels were identified as a predictive characteristic of response, but it was not possible to conclude a causal relationship, and further work is needed to understand the complexities of inter-individual variation. An age and sex-matched sub-group, from groups A (full fat cheddar cheese) and C (deconstructed cheese matrix) of the Cheese Matrix cohort were used to examined changes in the HDL proteome following the 6 week dairy fat intervention. The findings indicated that in a weight-neutral setting, dairy fat consumption did not adversely affect HDL particle composition, nor did it exacerbate the inflammatory phenotype of HDL particles in the metabolically unhealthy state. Finally, data from the Cheese Melting trial was used to investigated whether cheese eaten as melted cheese or solid / unmelted cheese daily for 6 weeks, had a differential effect on markers of CVD, including lipoprotein particles. There was very little change to levels of TRL particles postintervention, the unmelted cheese group (group A) had significantly lower total LDL particles (LDL-P) compared to the deconstructed matrix group (group C) postintervention. Similarly, when comparing the melted cheese group (Group B) to the deconstructed matrix group (group C), group C had a significant increase in total LDL-P compared to group B, where the total LDL-P levels remained unchanged. The findings from this thesis support the need to consider a more holistic approach when assessing the effects of dietary SFA on cardiovascular risk markers, highlighting the importance of the food matrix. Analysis of more sensitive risk markers, such as lipoprotein particle size and composition, should be considered as key biomarkers in the assessment of changes in CVD risk.