No abstract

Protein profiling of human serum by matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) is potentially a new diagnostic tool for early detection of human diseases, including cancer. Sample preparation is a key issue in MALDI MS and the analysis of complex samples such as serum requires optimized, reproducible methods for handling and deposition of protein samples. Data acquisition in MALDI MS is also a critical issue, since heterogeneity of sample deposits leads to attenuation of ion signals in MALDI MS. In order to improve the robustness and reproducibility of MALDI MS for serum protein profiling we investigated a range of sample preparation techniques and developed a statistical method based on repeated analyses for evaluation of protein-profiling performance of MALDI MS. Two different solid-phase extraction (SPE) methods were investigated, namely custom-made microcolumns and commercially available magnetic beads. Using these two methods, nineteen different sample preparation methods for serum profiling by MALDI MS were systematically tested with regard to matrix selection, stationary phase, selectivity, and reproducibility. Microcolumns were tested with regard to chromatographic properties; reversed phase (C8, C18, SDB-XC), ion-exchange (anion, weak cation, mixed-phase (SDB-RPS)) and magnetic beads were tested with regard to chromatographic properties; reversed phase (C8) or affinity chromatography (Cu-IMAC). The reproducibility of each sample preparation method was determined by enumeration and analysis of protein signals that were detected in at least six out of nine spectra obtained by three triplicate analyses of one serum sample.A candidate for best overall performance as evaluated by the number of peaks generated and the reproducibility of mass spectra was found among the tested methods. Up to 418 reproducible peaks were detected in one cancer serum sample. These protein peaks can be part of a possible diagnostic profile, suggesting that this sample preparation method and data acquisition approach is suitable for large-scale analysis of serum samples for protein profiling.

OBJECTIVE -To compare non-HDL cholesterol (HDLc) and apolipoprotein B (apoB) in the identification of nonconventional high-risk dyslipidemic phenotypes in type 2 diabetic patients.RESEARCH DESIGN AND METHODS -Total cholesterol and triglycerides, HDLc, LDL cholesterol, non-HDLc, apolipoprotein B (apoB), and LDL size were determined in 122 type 2 diabetic patients (68% male, aged 59.6 Ϯ 9.7 years, and HbA 1c 7.5% [range 5.2-16.0]). They were then classified as normo-and hypertriglyceridemic if their triglyceride concentrations were below/above 2.25 mmol/l, as normo/hyper-non-HDLc if non-HDLc concentrations were below/ above 4.13 mmol/l, and as normo-and hyperapoB if apoB concentrations were below/above 0.97 g/l. Both classifications were compared (concordance assessed with the index), and low HDLc and LDL phenotype B were identified in each category.RESULTS -A total of 26 patients were hypertriglyceridemic and 96 were normotriglyceridemic. All hypertriglyceridemic subjects had increased non-HDLc, whereas 24 had increased apoB (ϭ 0.95). In the normotriglyceridemic group, 44 had increased non-HDLc, 68 had increased apoB, and 25 of the 52 patients with normal non-HDLc had increased apoB (ϭ 0.587). Low HDLc and LDL phenotype B were similarly distributed into the equivalent categories.CONCLUSIONS -Non-HDLc and apoB are equivalent risk markers in hypertriglyceridemic patients, but apoB identifies additional patients with high-risk dyslipidemic phenotypes in normotriglyceridemic type 2 diabetic patients. Diabetes Care 26:2048 -2051, 2003L DL cholesterol (LDLc) is the main therapeutic target in the treatment of dyslipidemia (1,2). Nevertheless, several epidemiologic studies have shown that both non-HDL cholesterol (HDLc) and apolipoprotein B (apoB) are better predictors of cardiovascular events than LDLc (3-5). The former has, in fact, been included as a therapeutic target for hypertriglyceridemic patients in the most recent National Cholesterol Education Program (NCEP) recommendations (1) and is easy and cheap to calculate. On the other hand, apoB identifies high-risk dyslipidemic phenotypes that are not detected by the standard lipid profile in type 2 diabetic patients, who may present with hyperapoB-dependent dyslipidemic phenotypes (6,7). Because of the high correlation between non-HDLc and apoB in nondiabetic subjects (8), non-HDLc is considered a good surrogate marker for apoB. To our knowledge, however, no comparison has been made between nonHDLc and apoB in the classification of patients into dyslipidemic phenotypes.The aim of this study was to compare the classification into nonconventional dyslipidemic phenotypes of a group of type 2 diabetic subjects using apoB and non-HDLc. RESEARCH DESIGN AND METHODS PatientsA total of 122 type 2 diabetic patients from a university hospital were consecutively included in the study. Those receiving treatments or who were in situations (unrelated to their diabetes) that are known to affect lipid metabolism were excluded. Patients with hypertension were not treated with nonselec...

In patients with repeatedly high B12 levels, ICs were detected in approximately 25% of samples. Precipitation with PEG is an easy method to confirm the presence of ICs and to evaluate serum vitamin B12 levels in these patients.

Plasma holotranscobalamin (holoTC) transports active cobalamin. Decreased levels of holoTC have been considered to be the earliest marker of cobalamin (Cbl) deficiency. In this work, holoTC was evaluated in low or borderline serum Cbl (LB12) and a concordance analysis was carried out with methylmalonic acid (MMA) and homocysteine (Hcy). Levels of Cbl, holoTC, MMA, and Hcy were investigated in a reference group in 106 patients with LB12 (≤200 pmol/l) and in 27 with folate deficiency (FOL). HoloTC levels were evaluated by an automated immunoassay (Active B12, Abbott Lab, Abbott Park, IL, USA). Lower levels of holoTC were observed in both LB12 and FOL groups (reference group vs LB12; p < 0.0001. Reference group vs FOL; p = 0.002). HoloTC levels were lower in LB12 than in FOL (p = 0.001). In LB12, concordance between Hcy and MMA was 82.1 % (chi-square test, p < 0.001; Kappa Index, 0.64, p < 0.0001). Concordance between Hcy and holoTC was 62 % (chi-square test, p = 0.006; Kappa index, 0.245, p = 0.006). Concordance between holoTC and MMA was 55.6 % (p = 0.233). Some cases with LB12 and elevated MMA did not show decreased holoTC. By contrast, MMA and Hcy were not increased in some patients with low holoTC and LB12. In conclusion, levels of holoTC were decreased in LB12 and FOL. In LB12 patients, holoTC concordance with MMA was poor. MMA/Hcy levels were not increased in a significant number of subjects with LB12 and low holoTC. This profile was found in iron deficiency. The significance of these changes remains to be clarified.