Uta Ceglarek

Novel biomarkers for pre-diabetes identified by metabolomics

Type 2 diabetes (T2D) can be prevented in pre‐diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre‐diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population‐based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre‐diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P‐values ranging from 2.4 × 10−4 to 2.1 × 10−13. Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)‐Potsdam cohort. Using metabolite–protein network analysis, we identified seven T2D‐related genes that are associated with these three IGT‐specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D.

Differences between Human Plasma and Serum Metabolite Profiles

Background Human plasma and serum are widely used matrices in clinical and biological studies. However, different collecting procedures and the coagulation cascade influence concentrations of both proteins and metabolites in these matrices. The effects on metabolite concentration profiles have not been fully characterized. Methodology/Principal Findings We analyzed the concentrations of 163 metabolites in plasma and serum samples collected simultaneously from 377 fasting individuals. To ensure data quality, 41 metabolites with low measurement stability were excluded from further analysis. In addition, plasma and corresponding serum samples from 83 individuals were re-measured in the same plates and mean correlation coefficients (r) of all metabolites between the duplicates were 0.83 and 0.80 in plasma and serum, respectively, indicating significantly better stability of plasma compared to serum (p = 0.01). Metabolite profiles from plasma and serum were clearly distinct with 104 metabolites showing significantly higher concentrations in serum. In particular, 9 metabolites showed relative concentration differences larger than 20%. Despite differences in absolute concentration between the two matrices, for most metabolites the overall correlation was high (mean r = 0.81±0.10), which reflects a proportional change in concentration. Furthermore, when two groups of individuals with different phenotypes were compared with each other using both matrices, more metabolites with significantly different concentrations could be identified in serum than in plasma. For example, when 51 type 2 diabetes (T2D) patients were compared with 326 non-T2D individuals, 15 more significantly different metabolites were found in serum, in addition to the 25 common to both matrices. Conclusions/Significance Our study shows that reproducibility was good in both plasma and serum, and better in plasma. Furthermore, as long as the same blood preparation procedure is used, either matrix should generate similar results in clinical and biological studies. The higher metabolite concentrations in serum, however, make it possible to provide more sensitive results in biomarker detection.

Genetic Regulation of Serum Phytosterol Levels and Risk of Coronary Artery Disease

Background—Phytosterols are plant-derived sterols that are taken up from food and can serve as biomarkers of cholesterol uptake. Serum levels are under tight genetic control. We used a genomic approach to study the molecular regulation of serum phytosterol levels and potential links to coronary artery disease (CAD). Methods and Results—A genome-wide association study for serum phytosterols (campesterol, sitosterol, brassicasterol) was conducted in a population-based sample from KORA (Cooperative Research in the Region of Augsburg) (n=1495) with subsequent replication in 2 additional samples (n=1157 and n=1760). Replicated single-nucleotide polymorphisms (SNPs) were tested for association with premature CAD in a metaanalysis of 11 different samples comprising 13 764 CAD cases and 13 630 healthy controls. Genetic variants in the ATP-binding hemitransporter ABCG8 and at the blood group ABO locus were significantly associated with serum phytosterols. Effects in ABCG8 were independently related to SNPs rs4245791 and rs41360247 (combined P=1.6×10−50 and 6.2×10−25, respectively; n=4412). Serum campesterol was elevated 12% for each rs4245791 T-allele. The same allele was associated with 40% decreased hepatic ABCG8 mRNA expression (P=0.009). Effects at the ABO locus were related to SNP rs657152 (combined P=9.4×10−13). Alleles of ABCG8 and ABO associated with elevated phytosterol levels displayed significant associations with increased CAD risk (rs4245791 odds ratio, 1.10; 95% CI, 1.06 to 1.14; P=2.2×10−6; rs657152 odds ratio, 1.13; 95% CI, 1.07 to 1.19; P=9.4×10−6), whereas alleles at ABCG8 associated with reduced phytosterol levels were associated with reduced CAD risk (rs41360247 odds ratio, 0.84; 95% CI, 0.78 to 0.91; P=1.3×10−5). Conclusion—Common variants in ABCG8 and ABO are strongly associated with serum phytosterol levels and show concordant and previously unknown associations with CAD.

Rapid quantification of steroid patterns in human serum by on-line solid phase extraction combined with liquid chromatography-triple quadrupole linear ion trap mass spectrometry.

BACKGROUND The determination of steroids is important for the diagnosis and monitoring of endocrine diseases and infertility workup. We developed a rapid and reliable mass spectrometric method for the simultaneous quantification of steroid patterns in human serum. METHODS An on-line solid phase extraction (SPE)-liquid chromatography-triple quadrupole linear ion trap (LC-QTrap) method utilizing atmospheric pressure chemical ionization was developed. Following protein precipitation of 100 microL serum, on-line SPE and chromatographic separation was performed for 13 steroids in 1.8 min. Analytes were confirmed by the characteristic fragment patterns. RESULTS The total run time of the method was 4 min. Detection limits ranged between 0.02 microg/L (testosterone) and 9 microg/L (dehydroepiandrosterone sulfate). The method was linear up to 7000 microg/L for dehydroepiandrosterone sulfate, 500 microg/L for cortisol, 125 microg/L for 11-deoxycortisol, and 25 microg/L for aldosterone, 17-hydroxyprogesterone, progesterone, testosterone, androstenedione and beta-estradiol, respectively. Accuracy ranged between 80 and 114%. Between-day variance at three different concentration levels was <15%. Excellent correlations with immunoassays were observed for testosterone, cortisol and beta-estradiol with Pearsons correlation coefficient r=0.967, 0.963, and 0.998, respectively. CONCLUSION The novel on-line SPE-LC-MS/QTrap platform offers a very fast, reliable, and sensitive quantification of steroid patterns and fulfils the quality criteria for routine laboratory application.

LC-MS-based metabolomics in the clinical laboratory.

The analysis of metabolites in human body fluids remains a challenge because of their chemical diversity and dynamic concentration range. Liquid chromatography (LC) in combination with tandem mass spectrometry (MS/MS) offers a robust, reliable, and economical methodology for quantitative single metabolite analysis and profiling of complete metabolite classes of a biological specimen over a broad dynamic concentration range. The application of LC-MS/MS based metabolomic approaches in clinical applications aims at both, the improvement of diagnostic sensitivity and specificity by profiling a metabolite class instead of a single metabolite analysis, and the identification of new disease specific biomarkers. In the present paper we discuss recent advances in method development for LC-MS/MS analysis of lipids, carbohydrates, amino acids and biogenic amines, vitamins and organic acids with focus on human body fluids. In this context an overview on recent LC-MS/MS based metabolome studies for cancer, diabetes and coronary heart disease is presented.

Serum Peptidome Profiling Revealed Platelet Factor 4 as a Potential Discriminating Peptide Associated With Pancreatic Cancer

Purpose: Mass spectrometry–based serum peptidome profiling is a promising tool to identify novel disease-associated biomarkers, but is limited by preanalytic factors and the intricacies of complex data processing. Therefore, we investigated whether standardized sample protocols and new bioinformatic tools combined with external data validation improve the validity of peptidome profiling for the discovery of pancreatic cancer–associated serum markers. Experimental Design: For the discovery study, two sets of sera from patients with pancreatic cancer (n = 40) and healthy controls (n = 40) were obtained from two different clinical centers. For external data validation, we collected an independent set of samples from patients (n = 20) and healthy controls (n = 20). Magnetic beads with different surface functionalities were used for peptidome fractionation followed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). Data evaluation was carried out by comparing two different bioinformatic strategies. Following proteome database search, the matching candidate peptide was verified by MALDI-TOF MS after specific antibody-based immunoaffinity chromatography and independently confirmed by an ELISA assay. Results: Two significant peaks (m/z 3884; 5959) achieved a sensitivity of 86.3% and a specificity of 97.6% for the discrimination of patients and healthy controls in the external validation set. Adding peak m/z 3884 to conventional clinical tumor markers (CA 19-9 and CEA) improved sensitivity and specificity, as shown by receiver operator characteristics curve analysis (AUROCcombined = 1.00). Mass spectrometry–based m/z 3884 peak identification and following immunologic quantitation revealed platelet factor 4 as the corresponding peptide. Conclusions: MALDI-TOF MS-based serum peptidome profiling allowed the discovery and validation of platelet factor 4 as a new discriminating marker in pancreatic cancer.

Phenotypic differences in behavior, physiology and neurochemistry between rats selected for tameness and for defensive aggression towards humans

To better understand the biology of tameness, i.e. tolerance of human presence and handling, we analyzed two lines of wild-derived rats (Rattus norvegicus) artificially selected for tameness and defensive aggression towards humans. In response to a gloved human hand, tame rats tolerated handling, whereas aggressive rats attacked. Cross-fostering showed that these behavioral differences are not caused by postnatal maternal effects. Tame rats were more active and explorative and exhibited fewer anxiety-related behaviors. They also had smaller adrenal glands, larger spleens and lower levels of serum corticosterone. Blood glucose levels were lower in tame rats, whereas the concentrations of nine amino acids were higher. In the brain, tame rats had lower serotonin and higher taurine levels than aggressive rats. Our findings reinforce the notion that tameness is correlated with differences in stress response and will facilitate future efforts to uncover the genetic basis for animal tameness.

Validation of the phenylalanine/tyrosine ratio determined by tandem mass spectrometry: Sensitive newborn screening for phenylketonuria

Abstract The efficacy of the tandem mass spectrometry as a tool for the newborn screening of phenylketonuria, an inherited metabolic disorder, was investigated. Precision, reproducibility, selectivity and sensitivity were validated for phenylalanine and tyrosine measurements from dried blood spots. Bland-Altman plots were used to assess the agreement with conventional methods like fluorometry and ion exchange chromatography. The utility of the phenylalanine/tyrosine ratio for discrimination between mild hyperphenylalaninemia and classical types of phenylketonuria was investigated. Depending on concentration levels of phenylalanine and tyrosine the within-run and between-run assay variability ranged between 4.2% and 12.7%. Higher recoveries and a lower detection limit were found for the mass spectrometric method when compared to the fluorometric method. Pearson correlation coefficients of 0.91 for tandem mass spectrometry vs. fluorometric method, as well as 0.95 for tandem mass spectrometry vs. ion exchange chromatography were calculated. The closest agreement between methods was observed between tandem mass spectrometry and ion exchange chromatography. The results demonstrate a high efficacy of the tandem mass spectrometric method for quantitative determination of phenylalanine and tyrosine from dried blood spots. The phenylalanine/tyrosine ratio is crucial to improve the specificity and positive predictive value for the diagnosis of classical phenylketonuria.

Fast liquid chromatography–quadrupole linear ion trap-mass spectrometry analysis of polyunsaturated fatty acids and eicosanoids in human plasma ☆

Profiling of polyunsaturated fatty acids (PUFAs) and their oxidized metabolites, mainly eicosanoids, in human plasma by fast liquid chromatography-mass spectrometry is described. Sample preparation involved protein precipitation of 200μL plasma followed by on-line solid-phase extraction. 7 PUFAs and 94 oxidized metabolites were separated utilizing a C-18 column packed with 2.6μm core-shell particles in 7min. The analytes and deuterium-labeled standards were detected via scheduled multiple reaction monitoring transitions (123 sMRM). Simultaneously, linear ion trap fragment spectra were acquired for confirmation, if necessary. The lower limit of quantitation ranged between 200 and 1000ng/mL for the PUFAs and 10-1000pg/mL for the metabolites. The method was applied to a study on plasma samples from 50 healthy subjects.

Fast liquid chromatography combined with mass spectrometry for the analysis of metabolites and proteins in human body fluids.

In the last decade various analytical strategies have been established to enhance separation speed and efficiency in high performance liquid chromatography applications. Chromatographic supports based on monolithic material, small porous particles, and porous layer beads have been developed and commercialized to improve throughput and separation efficiency. This paper provides an overview of current developments in fast chromatography combined with mass spectrometry for the analysis of metabolites and proteins in clinical applications. Advances and limitations of fast chromatography for the combination with mass spectrometry are discussed. Practical aspects of, recent developments in, and the present status of high-throughput analysis of human body fluids for therapeutic drug monitoring, toxicology, clinical metabolomics, and proteomics are presented.