| dc.description.abstract | Introduction: When measuring nutritional biomarkers in blood, recent food intake can greatly impact the concentrations. Hence, it may be important to consider prandial status when interpreting the biomarker concentrations. Current practice involves distinguishing between fasting and non-fasting blood samples. However, metabolite concentrations may change gradually during the postprandial period, meaning the current approach may not be sufficient. The aim of this study was to investigate the dynamic changes in the concentration of nutritional biomarkers during the postprandial and postabsorptive periods. The biomarkers of interest for this thesis include electrolytes, lipids, albumin, folate, and cobalamin. Method: A total of 36 young, healthy study subjects (Age 20-30, BMI 22-27) were recruited. The subjects attended the study centre after a 12-hour overnight fast. After receiving a standardised breakfast meal, the participants consumed only water for the following 24 hours. Blood was drawn at baseline and 13-time points during the intervention at specified times. The blood samples were transported daily to the laboratory for study-specific analyses. Biomarker concentrations were plotted as a function of time since the standardised breakfast, and the geometric mean time course was superimposed on the individual participant data. To evaluate the absolute agreement of measurements at different time points, intraclass correlation coefficients (ICC) were calculated. Results: Data from 34 participants (18 males, 16 females), of which one dropped out at time point 7, were included in the final analyses. On average, the male participants were about two years older than the female participants. As expected, there were some differences in height, body mass, waist circumference, fat mass percentage, and resting metabolic rate (RMR) between males and females, but the average BMI was similar between the genders. We observed considerable fluctuations in biomarker concentrations, particularly in the early postprandial state. The largest fluctuations were observed for potassium, phosphate and triglycerides. A steady increase was observed throughout the postprandial and postabsorptive state for folate and cobalamin. During the intervention period, magnesium, albumin, HDL, and LDL were relatively stable. The calculated ICCs in the total population were 0.37-0.68 for phosphate, potassium, magnesium, LDL, albumin, folate, and cobalamin. Triglycerides had an ICC of 0.76 and HDL of 0.82 in the total population. Overall, the intraindividual fluctuations were larger in females compared to males, as represented by lower ICCs. Conclusion: Large fluctuations were observed in the postprandial period for some of the investigated biomarkers. Other biomarkers demonstrated a steady increase throughout the study period or relatively stable concentrations. This suggests that the prandial status, as reflected by time since the last meal, may be a critical factor in interpreting some, but not all, biomarkers. More considerable variation in biomarker concentrations was observed for females compared to males. The collected data from this study increase our understanding of the postprandial changes in metabolite concentrations, which may have extensive implications both in the clinic and in research. To extend the findings from this study, future studies should aim to examine the postprandial and postabsorptive metabolism in different populations and after meals with different compositions and eaten at other times of the day. | |
