Fritz Huber

The dynamic range of the human metabolome revealed by challenges

Metabolic challenge protocols, such as the oral glucose tolerance test, can uncover early alterations in metabolism preceding chronic diseases. Nevertheless, most metabolomics data accessible today reflect the fasting state. To analyze the dynamics of the human metabolome in response to environmental stimuli, we submitted 15 young healthy male volunteers to a highly controlled 4 d challenge protocol, including 36 h fasting, oral glucose and lipid tests, liquid test meals, physical exercise, and cold stress. Blood, urine, exhaled air, and breath condensate samples were analyzed on up to 56 time points by MS‐and NMR‐based methods, yielding 275 metabolic traits with a focus on lipids and amino acids. Here, we show that physiological challenges increased interindividual variation even in phenotypically similar volunteers, revealing metabotypes not observable in baseline metabolite profiles; volunteer‐specific metabolite concentrations were consistently reflected in various biofluids; and readouts from a systematic model of β‐oxidation (e.g., acetylcarnitine/palmitylcarnitine ratio) showed significant and stronger associations with physiological parameters (e.g., fat mass) than absolute metabolite concentrations, indicating that systematic models may aid in understanding individual challenge responses. Due to the multitude of analytical methods, challenges and sample types, our freely available metabolomics data set provides a unique reference for future metabolomics studies and for verification of systems biology models.—Krug, S., Kastenmüller, G., Stückler, F., Rist, M. J., Skurk, T., Sailer, M., Raffler, J., Römisch‐Margl, W., Adamski, J., Prehn, C., Frank, T., Engel, K‐H., Hofmann, T., Luy, B., Zimmermann, R., Moritz, F., Schmitt‐Kopplin, P., Krumsiek, J., Kremer, W., Huber, F., Oeh, U., Theis, F. J., Szymczak, W., Hauner, H., Suhre, K., Daniel, H. The dynamic range of the human metabolome revealed by challenges. FASEB J. 26, 2607‐2619 (2012). www.fasebj.org

Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits

Previously, we reported strong influences of genetic variants on metabolic phenotypes, some of them with clinical relevance. Here, we hypothesize that DNA methylation may have an important and potentially independent effect on human metabolism. To test this hypothesis, we conducted what is to the best of our knowledge the first epigenome-wide association study (EWAS) between DNA methylation and metabolic traits (metabotypes) in human blood. We assess 649 blood metabolic traits from 1814 participants of the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) population study for association with methylation of 457 004 CpG sites, determined on the Infinium HumanMethylation450 BeadChip platform. Using the EWAS approach, we identified two types of methylome–metabotype associations. One type is driven by an underlying genetic effect; the other type is independent of genetic variation and potentially driven by common environmental and life-style-dependent factors. We report eight CpG loci at genome-wide significance that have a genetic variant as confounder (P = 3.9 × 10−20 to 2.0 × 10−108, r2 = 0.036 to 0.221). Seven loci display CpG site-specific associations to metabotypes, but do not exhibit any underlying genetic signals (P = 9.2 × 10−14 to 2.7 × 10−27, r2 = 0.008 to 0.107). We further identify several groups of CpG loci that associate with a same metabotype, such as 4-vinylphenol sulfate and 4-androsten-3-beta,17-beta-diol disulfate. In these cases, the association between CpG-methylation and metabotype is likely the result of a common external environmental factor, including smoking. Our study shows that analysis of EWAS with large numbers of metabolic traits in large population cohorts are, in principle, feasible. Taken together, our data suggest that DNA methylation plays an important role in regulating human metabolism.

Solution Structure of the Ras Binding Domain of the Protein Kinase Byr2 from Schizosaccharomyces pombe

BACKGROUND After activation, small GTPases such as Ras transfer the incoming signal to effectors by specifically interacting with the binding domain of these proteins. Structural details of the binding domain of different effectors determine which pathway is predominantly activated. Byr2 from fission yeast is a functional homolog of Raf, which is the direct downstream target of Ras in mammalians that initiates a protein kinase cascade. The amino acid sequence of Byr2s Ras binding domain is only weakly related to that of Raf, and Byr2s three-dimensional structure is unknown. RESULTS We have solved the 3D structure of the Ras binding domain of Byr2 (Byr2RBD) from Schizosaccharomyces pombe in solution. The structure consists of three alpha helices and a mixed five-stranded beta pleated sheet arranged in the topology betabetaalphabetabetaalphabetaalpha with the first seven canonic secondary structure elements forming a ubiquitin superfold. 15N-(1)H-TROSY-HSQC spectroscopy of the complex of Byr2RBD with Ras*Mg(2+)*GppNHp reveals that the first and second beta strands and the first alpha helix of Byr2 are mainly involved in the protein-protein interaction as observed in other Ras binding domains. Although the putative interaction site of H-Ras from human and Ras1 from S. pombe are identical in sequence, binding to Byr2 leads to small but significant differences in the NMR spectra, indicating a slightly different binding mode. CONCLUSIONS The ubiquitin superfold appears to be the general structural motif for Ras binding domains even in cases with vanishing sequence identity. However, details of the 3D structure and the interacting interface are different, thereby determining the specifity of the recognition of Ras and Ras-related proteins.

Macrophage cholesterol efflux correlates with lipoprotein subclass distribution and risk of obstructive coronary artery disease in patients undergoing coronary angiography

BackgroundStudies in patients with low HDL have suggested that impaired cellular cholesterol efflux is a heritable phenotype increasing atherosclerosis risk. Less is known about the association of macrophage cholesterol efflux with lipid profiles and CAD risk in normolipidemic subjects. We have therefore measured macrophage cholesterol efflux in142 normolipidemic subjects undergoing coronary angiography.MethodsMonocytes isolated from blood samples of patients scheduled for cardiac catheterization were differentiated into macrophages over seven days. Isotopic cholesterol efflux to exogenously added apolipoprotein A-I and HDL2 was measured. Quantitative cholesterol efflux from macrophages was correlated with lipoprotein subclass distribution in plasma from the same individuals measured by NMR-spectroscopy of lipids and with the extent of coronary artery disease seen on coronary angiography.ResultsMacrophage cholesterol efflux was positively correlated with particle concentration of smaller HDL and LDL particles but not with total plasma concentrations of HDL or LDL-cholesterol. We observed an inverse relationship between macrophage cholesterol efflux and the concntration of larger and triglyceride rich particles (VLDL, chylomicrons). Subjects with significant stenosis on coronary angiography had lower cholesterol efflux from macrophages compared to individuals without significant stenosis (adjusted p = 0.02).ConclusionMacrophage cholesterol efflux is inversely correlated with lipoprotein particle size and risk of CAD.

Large-Scale Candidate Gene Analysis of HDL Particle Features

Background HDL cholesterol (HDL-C) is an established marker of cardiovascular risk with significant genetic determination. However, HDL particles are not homogenous, and refined HDL phenotyping may improve insight into regulation of HDL metabolism. We therefore assessed HDL particles by NMR spectroscopy and conducted a large-scale candidate gene association analysis. Methodology/Principal Findings We measured plasma HDL-C and determined mean HDL particle size and particle number by NMR spectroscopy in 2024 individuals from 512 British Caucasian families. Genotypes were 49,094 SNPs in >2,100 cardiometabolic candidate genes/loci as represented on the HumanCVD BeadChip version 2. False discovery rates (FDR) were calculated to account for multiple testing. Analyses on classical HDL-C revealed significant associations (FDR<0.05) only for CETP (cholesteryl ester transfer protein; lead SNP rs3764261: p = 5.6*10−15) and SGCD (sarcoglycan delta; rs6877118: p = 8.6*10−6). In contrast, analysis with HDL mean particle size yielded additional associations in LIPC (hepatic lipase; rs261332: p = 6.1*10−9), PLTP (phospholipid transfer protein, rs4810479: p = 1.7*10−8) and FBLN5 (fibulin-5; rs2246416: p = 6.2*10−6). The associations of SGCD and Fibulin-5 with HDL particle size could not be replicated in PROCARDIS (n = 3,078) and/or the Womens Genome Health Study (n = 23,170). Conclusions We show that refined HDL phenotyping by NMR spectroscopy can detect known genes of HDL metabolism better than analyses on HDL-C.

The lipoprotein subfraction profile: heritability and identification of quantitative trait loci.

The HDL and LDL subclass profile is an emerging cardiovascular risk factor. Yet, the biological and genetic mechanisms controlling the lipoprotein subclass distribution are unclear. Therefore, we aimed 1) to determine the heritability of the entire spectrum of LDL and HDL subclass features and 2) to identify gene loci influencing the lipoprotein subfraction pattern. Using NMR spectroscopy, we analyzed the lipoprotein subclass distribution in 1,275 coronary artery disease patients derived from the Regensburg Myocardial Infarction Family Study. We calculated heritabilities, performed a microsatellite genome scan, and calculated linkage. HDL and LDL subclass profiles showed heritabilities ranging from 23% to 67% (all P < 10−3) of traits using univariate calculation. After multivariate adjustment, we found heritabilities of 27–48% (all P < 0.05) for HDL and 21–44% for LDL traits. The linkage analysis revealed a significant logarithm of the odds (LOD) score (3.3) for HDL particle concentration on chromosome 18 and a highly suggestive signal for HDL particle size on chromosome 12 (2.9). After multivariate adjustment, we found a significant maximum LOD score of 3.7 for HDL size. Our study is the first to analyze heritability and linkage for the entire spectrum of LDL and HDL subclass features. Our findings may lead to the identification of genes controlling the lipoprotein subclass distribution.

Structure of the leech protein saratin and characterization of its binding to collagen

The leech protein Saratin from Hirudo medicinalis prevents thrombocyte aggregation by interfering with the first binding step of the thrombocytes to collagen by binding to collagen. We solved the three-dimensional structure of the leech protein Saratin in solution and identified its collagen binding site by NMR titration experiments. The NMR structure of Saratin consists of one alpha-helix and a five-stranded beta-sheet arranged in the topology betabetaalphabetabetabeta. The C-terminal region, of about 20 amino acids in length, adopts no regular structure. NMR titration experiments with collagen peptides show that the collagen interaction of Saratin takes place in a kind of notch that is formed by the end of the alpha-helix and the beta-sheet. NMR data-driven docking experiments to collagen model peptides were used to elucidate the putative binding mode of Saratin and collagen. Mainly, parts of the first and the end of the fifth beta-strand, the loop connecting the alpha-helix and the third beta-strand, and a short part of the loop connecting the fourth and fifth beta-strand participate in binding.

Genetic associations with lipoprotein subfractions provide information on their biological nature

Adverse levels of lipoproteins are highly heritable and constitute risk factors for cardiovascular outcomes. Hitherto, genome-wide association studies revealed 95 lipid-associated loci. However, due to the small effect sizes of these associations large sample numbers (>100 000 samples) were needed. Here we show that analyzing more refined lipid phenotypes, namely lipoprotein subfractions, can increase the number of significantly associated loci compared with bulk high-density lipoprotein and low-density lipoprotein analysis in a study with identical sample numbers. Moreover, lipoprotein subfractions provide novel insight into the human lipid metabolism. We measured 15 lipoprotein subfractions (L1-L15) in 1791 samples using (1)H-NMR (nuclear magnetic resonance) spectroscopy. Using cluster analyses, we quantified inter-relationships among lipoprotein subfractions. Additionally, we analyzed associations with subfractions at known lipid loci. We identified five distinct groups of subfractions: one (L1) was only marginally captured by serum lipids and therefore extends our knowledge of lipoprotein biochemistry. During a lipid-tolerance test, L1 lost its special position. In the association analysis, we found that eight loci (LIPC, CETP, PLTP, FADS1-2-3, SORT1, GCKR, APOB, APOA1) were associated with the subfractions, whereas only four loci (CETP, SORT1, GCKR, APOA1) were associated with serum lipids. For LIPC, we observed a 10-fold increase in the variance explained by our regression models. In conclusion, NMR-based fine mapping of lipoprotein subfractions provides novel information on their biological nature and strengthens the associations with genetic loci. Future clinical studies are now needed to investigate their biomedical relevance.

Reproducibility of NMR Analysis of Urine Samples: Impact of Sample Preparation, Storage Conditions, and Animal Health Status

Introduction. Spectroscopic analysis of urine samples from laboratory animals can be used to predict the efficacy and side effects of drugs. This employs methods combining 1H NMR spectroscopy with quantification of biomarkers or with multivariate data analysis. The most critical steps in data evaluation are analytical reproducibility of NMR data (collection, storage, and processing) and the health status of the animals, which may influence urine pH and osmolarity. Methods. We treated rats with a solvent, a diuretic, or a nephrotoxicant and collected urine samples. Samples were titrated to pH 3 to 9, or salt concentrations increased up to 20-fold. The effects of storage conditions and freeze-thaw cycles were monitored. Selected metabolites and multivariate data analysis were evaluated after 1H NMR spectroscopy. Results. We showed that variation of pH from 3 to 9 and increases in osmolarity up to 6-fold had no effect on the quantification of the metabolites or on multivariate data analysis. Storage led to changes after 14 days at 4°C or after 12 months at −20°C, independent of sample composition. Multiple freeze-thaw cycles did not affect data analysis. Conclusion. Reproducibility of NMR measurements is not dependent on sample composition under physiological or pathological conditions.

NMR-Spektroskopie – ein modernes Werkzeug zur Serum-Analytik von Lipoproteinen und Metaboliten

Zusammenfassung Die NMR-Spektroskopie ist eine moderne analytische Methode, die sich gut zur Analyse unterschiedlichster Körperflüssigkeiten eignet. Im Serum können neben kleinen Metaboliten auch differenziert Lipoprotein-Fraktionen bestimmt werden. Die Technik ist gut standardisierbar und erlaubt im Vergleich zur Lipoproteinfraktionierung mittels Ultrazentrifugation eine umfassende Automatisierung und guten Probendurchsatz. Da in einer Messung alle auszuwertenden Parameter gleichzeitig gemessen werden, eignet sich die Methode besonders gut für Metabolomics-Ansätze, in denen auch subtile Verschiebungen in den Metabolitenverhältnissen von Bedeutung sein können. Dieser Review gibt eine Übersicht über aktuelle Ansätze der NMR-spektroskopischen Messtechnik, Auswertestrategien und praktischen Anwendungen in verschiedenen Studien, sowohl auf der Seite der Lipidanalyse, also auch hinsichtlich des Metabolitenprofils. Die NMR-Spektroskopie hat sich in den letzten Jahren von einer reinen Forschungsmethode mit großen Schritten weiterentwickelt und dürfte in Zukunft einen Platz in der Routinediagnostik einnehmen.