High-throughput mass finger printing and Lewis blood group assignment of human milk oligosaccharides.

The structural diversity of human milk oligosaccharides (HMOs) strongly depends on the Lewis (Le) blood group status of the donor which allows a classification of these glycans into three different groups. Starting from 50 µL of human milk, a new high-throughput, standardized, and widely automated mass spectrometric approach has been established which can be used for correlation of HMO structures with the respective Lewis blood groups on the basis of mass profiles of the entire mixture of glycans together with selected fragment ion spectra. For this purpose, the relative abundance of diagnostically relevant compositional species, such as Hex(2)Fuc(2) and Hex(3)HexNAc(1)Fuc(2), as well as the relative intensities of characteristic fragment ions obtained thereof are of key importance. For each Lewis blood group, i.e., Le(a-b+), Le(a+b-), and Le(a-b-), specific mass profile and fragment ion patterns could be thus verified. The described statistically proven classification of the derived glycan patterns may be a valuable tool for analysis and comparison of large sets of milk samples in metabolic studies. Furthermore, the outlined protocol may be used for rapid screening in clinical studies and quality control of milk samples donated to milk banks.

Risk factors of metabolic disorders after liver transplantation: an analysis of data from fasted patients.

BACKGROUND: Metabolic disorders are common complications after orthotopic liver transplantation (OLT) and may lead to increased morbidity and mortality. METHODS: Fasting glucose and lipid metabolism, and body weight of 81 patients undergoing primary OLT were prospectively analyzed. Patients were investigated preoperatively, on postoperative days 1, 3, 5, 10, 14, 28 as well as 6 months and 1 year after OLT. Data of nonfasted patients were excluded from the analysis. Standardized definitions and classifications for diabetes mellitus (DM), body mass index (BMI), and dyslipidemia were used. RESULTS: Prevalence of new-onset diabetes after transplantation was 9.3%, and obesity was its only independent risk factor (odds ratio [OR], 16.5). Preoperative impaired glucose homeostasis (OR, 10.8) and initial poor graft function (OR, 6.89) were independent risk factors for postoperative DM. Maximum prevalence of hypertriglyceridemia and hypercholesterolemia was found on postoperative day 10 and 6 months post-OLT, respectively. Risk factors for hypercholesterolemia at 1 year were patient age (OR, 1.17) and postoperative renal dysfunction (OR, 16.33). Higher preoperative BMI was a risk factor for postoperative hypertriglyceridemia (OR, 1.17). Overall body weight and BMI significantly decreased over 1 year (P < 0.05). Prevalence of obesity was 22.2% before and 20.9% after OLT. CONCLUSION: For the first time, initial poor graft function was identified as a risk factor for post-OLT DM. By ruling out any exogenous factors influencing metabolism, we believe we were able to show the true prevalence of metabolic disorders and therefore provided a valuable contribution to the identification of potential risk factors.