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ABSTRACT: Bile acids (BA) play a crucial role not only in lipid digestion but also in the regulation of overall energy homeostasis, including glucose and lipid metabolism. The aim of this study was to investigate BA profiles and mRNA expression of BA-related genes in the liver of high versus normal body condition in dairy cows. We hypothesized that body condition and the transition from gestation to lactation affect hepatic BA concentrations as well as the mRNA abundance of BA-related receptors, regulatory enzymes, and transporters. Therefore, we analyzed BA in the liver as well as the mRNA abundance of BA-related synthesizing enzymes, transporters, and receptors in the liver during the transition period in cows with different body conditions around calving. In a previously established animal model, 38 German Holstein cows were divided into groups with high body condition score (HBCS; n = 19) or normal body condition score (NBCS; n = 19) based on BCS and backfat thickness (BFT). Cows were fed diets aimed at achieving the targeted differences in BCS and BFT (NBCS: BCS 3.75, BFT >1.4 cm) until they were dried off at wk 7 before parturition. Both groups were fed identical diets during the dry period and subsequent lactation. Liver biopsies were taken at wk −7, 1, 3, and 12 relative to parturition. For BA measurement, a targeted metabolomics approach with liquid chromatography electrospray ionization MS/MS was used to analyze BA in the liver. The mRNA abundance of targeted genes related to BA synthesizing enzymes, transporters, and receptors in the liver was analyzed using microfluidic quantitative PCR. In total, we could detect 14 BA in the liver: 6 primary and 8 secondary BA, with glycocholic acid (GCA) being the most abundant one. The increase of glycine-conjugated BA after parturition, in parallel to increasing serum glycine concentrations may originate from an enhanced mobilization of muscle protein to meet the high nutritional requirements in early lactating cows. Higher DMI in NBCS cows compared with HBCS cows was associated with higher liver BA concentrations such as GCA, deoxycholic acid, and cholic acid. The mRNA abundance of BA-related enzymes measured herein suggests the dominance of the alternative signaling pathway in the liver of HBCS cows. Overall, BA profiles and BA metabolism in the liver depend on both, the body condition and lactation-induced effects in periparturient dairy cows.

Abstract In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays “The Molecular Human”. We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to “The Molecular Human” ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.

Summary: Metabolism oscillates between catabolic and anabolic states depending on food intake, exercise, or stresses that change a multitude of metabolic pathways simultaneously. We present the HuMet Repository for exploring dynamic metabolic responses to oral glucose/lipid loads, mixed meals, 36-h fasting, exercise, and cold stress in healthy subjects. Metabolomics data from blood, urine, and breath of 15 young, healthy men at up to 56 time points are integrated and embedded within an interactive web application, enabling researchers with and without computational expertise to search, visualize, analyze, and contextualize the dynamic metabolite profiles of 2,656 metabolites acquired on multiple platforms. With examples, we demonstrate the utility of the resource for research into the dynamics of human metabolism, highlighting differences and similarities in systemic metabolic responses across challenges and the complementarity of metabolomics platforms. The repository, providing a reference for healthy metabolite changes to six standardized physiological challenges, is freely accessible through a web portal.

Introduction Circulating omentin levels have been positively associated with insulin sensitivity. Although a role for adiponectin in this relationship has been suggested, underlying mechanisms remain elusive. In order to reveal the relationship between omentin and systemic metabolism, this study aimed to investigate associations of serum concentrations of omentin and metabolites.Research design and methods This study is based on 1124 participants aged 61–82 years from the population-based KORA (Cooperative Health Research in the Region of Augsburg) F4 Study, for whom both serum omentin levels and metabolite concentration profiles were available. Associations were assessed with five multivariable regression models, which were stepwise adjusted for multiple potential confounders, including age, sex, body mass index, waist-to-hip ratio, lifestyle markers (physical activity, smoking behavior and alcohol consumption), serum adiponectin levels, high-density lipoprotein cholesterol, use of lipid-lowering or anti-inflammatory medication, history of myocardial infarction and stroke, homeostasis model assessment 2 of insulin resistance, diabetes status, and use of oral glucose-lowering medication and insulin.Results Omentin levels significantly associated with multiple metabolites including amino acids, acylcarnitines, and lipids (eg, sphingomyelins and phosphatidylcholines (PCs)). Positive associations for several PCs, such as diacyl (PC aa C32:1) and alkyl-alkyl (PC ae C32:2), were significant in models 1–4, whereas those with hydroxytetradecenoylcarnitine (C14:1-OH) were significant in all five models. Omentin concentrations were negatively associated with several metabolite ratios, such as the valine-to-PC ae C32:2 and the serine-to-PC ae C32:2 ratios in most models.Conclusions Our results suggest that omentin may influence insulin sensitivity and diabetes risk by changing systemic lipid metabolism, but further mechanistic studies investigating effects of omentin on metabolism of insulin-sensitive tissues are needed.

Summary: Background: Altered lipid metabolism is a hallmark of cancer development. However, the role of specific lipid metabolites in colorectal cancer development is uncertain. Methods: In a case–control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC), we examined associations between pre-diagnostic circulating concentrations of 97 lipid metabolites (acylcarnitines, glycerophospholipids and sphingolipids) and colorectal cancer risk. Circulating lipids were measured using targeted mass spectrometry in 1591 incident colorectal cancer cases (55% women) and 1591 matched controls. Multivariable conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between concentrations of individual lipid metabolites and metabolite patterns with colorectal cancer risk. Findings: Of the 97 assayed lipids, 24 were inversely associated (nominally p

Abstract Background Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways. Methods We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed. Results We identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism. Conclusion Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.

BackgroundSex hormones and sex hormone-binding globulin (SHBG) may play a role in fatty liver development. We sought to examine the association of various endogenous sex hormones, including testosterone (T), and SHBG with liver fat using complementary observational and Mendelian randomization (MR) analyses.MethodsThe observational analysis included a total of 2,239 participants (mean age 60 years; 35% postmenopausal women) from the population-based KORA study (average follow-up time: 6.5 years). We conducted linear regression analysis to investigate the sex-specific associations of sex hormones and SHBG with liver fat, estimated by fatty liver index (FLI). For MR analyses, we selected genetic variants associated with sex hormones and SHBG and extracted their associations with magnetic resonance imaging measured liver fat from the largest up to date European genome-wide associations studies.ResultsIn the observational analysis, T, dihydrotestosterone (DHT), progesterone and 17α-hydroxyprogesterone (17-OHP) were inversely associated with FLI in men, with beta estimates ranging from -4.23 to -2.30 [p-value

Introduction Low glomerular filtration rate (GFR) is a leading cause of reduced lifespan in type 2 diabetes. Unravelling biomarkers capable to identify high-risk patients can help tackle this burden. We investigated the association between 188 serum metabolites and kidney function in type 2 diabetes and then whether the associated metabolites improve two established clinical models for predicting GFR decline in these patients.Research design and methods Two cohorts comprising 849 individuals with type 2 diabetes (discovery and validation samples) and a follow-up study of 575 patients with estimated GFR (eGFR) decline were analyzed.Results Ten metabolites were independently associated with low eGFR in the discovery sample, with nine of them being confirmed also in the validation sample (ORs range 1.3–2.4 per 1SD, p values range 1.9×10−2–2.5×10−9). Of these, five metabolites were also associated with eGFR decline (ie, tiglylcarnitine, decadienylcarnitine, total dimethylarginine, decenoylcarnitine and kynurenine) (β range −0.11 to −0.19, p values range 4.8×10−2 to 3.0×10−3). Indeed, tiglylcarnitine and kynurenine, which captured all the information of the other three markers, improved discrimination and reclassification (all p

Objective: To gain mechanistic insights into adverse effects of maternal hyperglycemia on the liver of neonates, we performed a multi-omics analysis of liver tissue from piglets developed in genetically diabetic (mutant INS gene induced diabetes of youth; MIDY) or wild-type (WT) pigs. Methods: Proteome, metabolome and lipidome profiles of liver and clinical parameters of serum samples from 3-day-old WT piglets (n = 9) born to MIDY mothers (PHG) were compared with those of WT piglets (n = 10) born to normoglycemic mothers (PNG). Furthermore, protein–protein interaction network analysis was used to reveal highly interacting proteins that participate in the same molecular mechanisms and to relate these mechanisms with human pathology. Results: Hepatocytes of PHG displayed pronounced lipid droplet accumulation, although the abundances of central lipogenic enzymes such as fatty acid-synthase (FASN) were decreased. Additionally, circulating triglyceride (TG) levels were reduced as a trend. Serum levels of non-esterified free fatty acids (NEFA) were elevated in PHG, potentially stimulating hepatic gluconeogenesis. This is supported by elevated hepatic phosphoenolpyruvate carboxykinase (PCK1) and circulating alanine transaminase (ALT) levels. Even though targeted metabolomics showed strongly elevated phosphatidylcholine (PC) levels, the abundances of multiple key enzymes involved in major PC synthesis pathways – most prominently those from the Kennedy pathway – were paradoxically reduced in PHG liver. Conversely, enzymes involved in PC excretion and breakdown such as PC-specific translocase ATP-binding cassette 4 (ABCB4) and phospholipase A2 were increased in abundance. Conclusions: Our study indicates that maternal hyperglycemia without confounding obesity induces profound molecular changes in the liver of neonatal offspring. In particular, we found evidence for stimulated gluconeogenesis and hepatic lipid accumulation independent of de novo lipogenesis. Reduced levels of PC biosynthesis enzymes and increased levels of proteins involved in PC translocation or breakdown may represent counter-regulatory mechanisms to maternally elevated PC levels. Our comprehensive multi-omics dataset provides a valuable resource for future meta-analysis studies focusing on liver metabolism in newborns from diabetic mothers.

Abstract Background Amino acid metabolism is dysregulated in colorectal cancer patients; however, it is not clear whether pre-diagnostic levels of amino acids are associated with subsequent risk of colorectal cancer. We investigated circulating levels of amino acids in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts. Methods Concentrations of 13-21 amino acids were determined in baseline fasting plasma or serum samples in 654 incident colorectal cancer cases and 654 matched controls in EPIC. Amino acids associated with colorectal cancer risk following adjustment for the false discovery rate (FDR) were then tested for associations in the UK Biobank, for which measurements of 9 amino acids were available in 111,323 participants, of which 1221 were incident colorectal cancer cases. Results Histidine levels were inversely associated with colorectal cancer risk in EPIC (odds ratio [OR] 0.80 per standard deviation [SD], 95% confidence interval [CI] 0.69–0.92, FDR P-value=0.03) and in UK Biobank (HR 0.93 per SD, 95% CI 0.87–0.99, P-value=0.03). Glutamine levels were borderline inversely associated with colorectal cancer risk in EPIC (OR 0.85 per SD, 95% CI 0.75–0.97, FDR P-value=0.08) and similarly in UK Biobank (HR 0.95, 95% CI 0.89–1.01, P=0.09) In both cohorts, associations changed only minimally when cases diagnosed within 2 or 5 years of follow-up were excluded. Conclusions Higher circulating levels of histidine were associated with a lower risk of colorectal cancer in two large prospective cohorts. Further research to ascertain the role of histidine metabolism and potentially that of glutamine in colorectal cancer development is warranted.

IntroductionThe role of endogenous androgens in kidney function and disease has not been extensively explored in men and women.Research design and methodsWe analyzed data from the observational KORA F4 study and its follow-up examination KORA FF4 (median follow-up time 6.5 years) including 1293 men and 650 peri- and postmenopausal women, not using exogenous sex hormones. We examined the associations between endogenous androgens (testosterone [T], dihydrotestosterone [DHT], free T [fT], free DHT [fDHT], and T/DHT), with estimated glomerular filtration rate (eGFR) at baseline and follow-up, prevalent, and incident chronic kidney disease (CKD) adjusting for common CKD risk factors.ResultsAt baseline, 73 men (5.7%) and 54 women (8.4%) had prevalent CKD. Cross-sectionally, no significant associations between androgens and kidney function were observed among men. In women, elevated T (β=-1.305, [95% CI -2.290; -0.320]) and fT (β=-1.423, [95% CI -2.449; -0.397]) were associated with lower eGFR. Prospectively, 81 men (8.8%) and 60 women (15.2%) developed incident CKD. In women, a reverse J-shaped associations was observed between DHT and incident CKD (Pnon-linear=0.029), while higher fDHT was associated with lower incident CKD risk (odds ratio per 1 standard deviation=0.613, [95% CI 0.369; 0.971]. Among men, T/DHT (β=-0.819, [95% CI -1.413; -0.226]) and SHBG (Pnon-linear=0.011) were associated with eGFR at follow-up but not with incident CKD. Some associations appeared to be modified by type 2 diabetes (T2D).ConclusionSuggestive associations are observed of androgens and SHBG with kidney impairment among men and women. However, larger well-phenotyped prospective studies are required to further elucidate the potential of androgens, SHBG, and T2D as modifiable risk factors for kidney function and CKD.

Summary: Background: Arterial hypertension is a major cardiovascular risk factor. Identification of secondary hypertension in its various forms is key to preventing and targeting treatment of cardiovascular complications. Simplified diagnostic tests are urgently required to distinguish primary and secondary hypertension to address the current underdiagnosis of the latter. Methods: This study uses Machine Learning (ML) to classify subtypes of endocrine hypertension (EHT) in a large cohort of hypertensive patients using multidimensional omics analysis of plasma and urine samples. We measured 409 multi-omics (MOmics) features including plasma miRNAs (PmiRNA: 173), plasma catechol O-methylated metabolites (PMetas: 4), plasma steroids (PSteroids: 16), urinary steroid metabolites (USteroids: 27), and plasma small metabolites (PSmallMB: 189) in primary hypertension (PHT) patients, EHT patients with either primary aldosteronism (PA), pheochromocytoma/functional paraganglioma (PPGL) or Cushing syndrome (CS) and normotensive volunteers (NV). Biomarker discovery involved selection of disease combination, outlier handling, feature reduction, 8 ML classifiers, class balancing and consideration of different age- and sex-based scenarios. Classifications were evaluated using balanced accuracy, sensitivity, specificity, AUC, F1, and Kappa score. Findings: Complete clinical and biological datasets were generated from 307 subjects (PA=113, PPGL=88, CS=41 and PHT=112). The random forest classifier provided ∼92% balanced accuracy (∼11% improvement on the best mono-omics classifier), with 96% specificity and 0.95 AUC to distinguish one of the four conditions in multi-class ALL-ALL comparisons (PPGL vs PA vs CS vs PHT) on an unseen test set, using 57 MOmics features. For discrimination of EHT (PA + PPGL + CS) vs PHT, the simple logistic classifier achieved 0.96 AUC with 90% sensitivity, and ∼86% specificity, using 37 MOmics features. One PmiRNA (hsa-miR-15a-5p) and two PSmallMB (C9 and PC ae C38:1) features were found to be most discriminating for all disease combinations. Overall, the MOmics-based classifiers were able to provide better classification performance in comparison to mono-omics classifiers. Interpretation: We have developed a ML pipeline to distinguish different EHT subtypes from PHT using multi-omics data. This innovative approach to stratification is an advancement towards the development of a diagnostic tool for EHT patients, significantly increasing testing throughput and accelerating administration of appropriate treatment. Funding: European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 633983, Clinical Research Priority Program of the University of Zurich for the CRPP HYRENE (to Z.E. and F.B.), and Deutsche Forschungsgemeinschaft (CRC/Transregio 205/1).

Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabolic status. To enable the usage of dietary challenges as diagnostic tools, profound knowledge about changes that occur in the postprandial period in healthy individuals is needed. In this study, we characterize the time-resolved changes in plasma levels of 634 metabolites in response to an oral glucose tolerance test (OGTT), an oral lipid tolerance test (OLTT), and a mixed meal (SLD) in healthy young males (n = 15). Metabolite levels for samples taken at different time points (20 per individual) during the challenges were available from targeted (132 metabolites) and non-targeted (502 metabolites) metabolomics. Almost half of the profiled metabolites (n = 308) showed a significant change in at least one challenge, thereof 111 metabolites responded exclusively to one particular challenge. Examples include azelate, which is linked to ω-oxidation and increased only in OLTT, and a fibrinogen cleavage peptide that has been linked to a higher risk of cardiovascular events in diabetes patients and increased only in OGTT, making its postprandial dynamics a potential target for risk management. A pool of 89 metabolites changed their plasma levels during all three challenges and represents the core postprandial response to food intake regardless of macronutrient composition. We used fuzzy c-means clustering to group these metabolites into eight clusters based on commonalities of their dynamic response patterns, with each cluster following one of four primary response patterns: (i) “decrease-increase” (valley-like) with fatty acids and acylcarnitines indicating the suppression of lipolysis, (ii) “increase-decrease” (mountain-like) including a cluster of conjugated bile acids and the glucose/insulin cluster, (iii) “steady decrease” with metabolites reflecting a carryover from meals prior to the study, and (iv) “mixed” decreasing after the glucose challenge and increasing otherwise. Despite the small number of subjects, the diversity of the challenges and the wealth of metabolomic data make this study an important step toward the characterization of postprandial responses and the identification of markers of metabolic processes regulated by food intake.

Abstract Background The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. Methods Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. Results We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. Conclusions Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Objective: Sex hormone-binding globulin (SHBG) and androgens have been associated with mortality in women and men, but controversy still exists. Our objective was to investigate associations of SHBG and androgens with all-cause a nd cause-specific mortality in men and women. Design: 1006 men and 709 peri- and postmenopausal women (age range: 45–82 years) from the German population-based KORA F4 cohort study were followed-up for a median of 8.7 years. Methods: SHBG was measured with an immunoassay, total testosterone (TT) and dihydrotestosterone (DHT) with mass-spectrometry in serum samples and we calculated free testosterone (cFT). To assess associations between SHBG and androgen levels and mortality, we calculated hazard ratios (HRs) with 95% CIs using Cox proportional-hazards models. Results: In the cohort, 128 men (12.7%) and 70 women (9.9%) died. In women, we observed positive associations of SHBG with all-cause (HR: 1.54, 95% CI: 1.16–2.04) and with other disease-related mortality (HR: 1.86, 95% CI: 1.08–3.20) and for DHT with all-cause mortality (HR: 1.32, 95% CI: 1.00–1.73). In men, we found a positive association of SHBG (HR: 1.24 95% CI: 1.00–1.54) and inverse associations of TT (HR: 0.87, 95% CI: 0.77–0.97) and cFT (HR: 0.84, 95% CI: 0.73–0.97) with all-cause mortality. No other associations were found for cause-specific mortality. Conclusions: Higher SHBG levels were associated with increased risk of all-cause mortality in men and women. Lower TT and cFT levels in men and higher DHT levels in women were associated with increased risk of all-cause mortality. Future, well-powered population-based studies should further investigate cause-specific mortality risk.

Abstract Background Hexose-6-Phosphate Dehydrogenase (H6PD) is a generator of NADPH in the Endoplasmic/Sarcoplasmic Reticulum (ER/SR). Interaction of H6PD with 11β-hydroxysteroid dehydrogenase type 1 provides NADPH to support oxo-reduction of inactive to active glucocorticoids, but the wider understanding of H6PD in ER/SR NAD(P)(H) homeostasis is incomplete. Lack of H6PD results in a deteriorating skeletal myopathy, altered glucose homeostasis, ER stress and activation of the unfolded protein response. Here we further assess muscle responses to H6PD deficiency to delineate pathways that may underpin myopathy and link SR redox status to muscle wide metabolic adaptation. Methods We analysed skeletal muscle from H6PD knockout (H6PDKO), H6PD and NRK2 double knockout (DKO) and wild-type (WT) mice. H6PDKO mice were supplemented with the NAD+ precursor nicotinamide riboside. Skeletal muscle samples were subjected to biochemical analysis including NAD(H) measurement, LC-MS based metabolomics, Western blotting, and high resolution mitochondrial respirometry. Genetic and supplement models were assessed for degree of myopathy compared to H6PDKO. Results H6PDKO skeletal muscle showed adaptations in the routes regulating nicotinamide and NAD+ biosynthesis, with significant activation of the Nicotinamide Riboside Kinase 2 (NRK2) pathway. Associated with changes in NAD+ biosynthesis, H6PDKO muscle had impaired mitochondrial respiratory capacity with altered mitochondrial acylcarnitine and acetyl-CoA metabolism. Boosting NAD+ levels through the NRK2 pathway using the precursor nicotinamide riboside elevated NAD+/NADH but had no effect to mitigate ER stress and dysfunctional mitochondrial respiratory capacity or acetyl-CoA metabolism. Similarly, H6PDKO/NRK2 double KO mice did not display an exaggerated timing or severity of myopathy or overt change in mitochondrial metabolism despite depression of NAD+ availability. Conclusions These findings suggest a complex metabolic response to changes in muscle SR NADP(H) redox status that result in impaired mitochondrial energy metabolism and activation of cellular NAD+ salvage pathways. It is possible that SR can sense and signal perturbation in NAD(P)(H) that cannot be rectified in the absence of H6PD. Whether NRK2 pathway activation is a direct response to changes in SR NAD(P)(H) availability or adaptation to deficits in metabolic energy availability remains to be resolved.

Obesity plays an important role in the development of insulin resistance and diabetes, but the molecular mechanism that links obesity and diabetes is still not completely understood. Here, we used 146 targeted metabolomic profiles from the German KORA FF4 cohort consisting of 1715 participants and associated them with obesity and type 2 diabetes. In the basic model, 83 and 51 metabolites were significantly associated with body mass index (BMI) and T2D, respectively. Those metabolites are branched-chain amino acids, acylcarnitines, lysophospholipids, or phosphatidylcholines. In the full model, 42 and 3 metabolites were significantly associated with BMI and T2D, respectively, and replicate findings in the previous studies. Sobel mediation testing suggests that the effect of BMI on T2D might be mediated via lipids such as sphingomyelin (SM) C16:1, SM C18:1 and diacylphosphatidylcholine (PC aa) C38:3. Moreover, mendelian randomization suggests a causal relationship that BMI causes the change of SM C16:1 and PC aa C38:3, and the change of SM C16:1, SM C18:1, and PC aa C38:3 contribute to T2D incident. Biological pathway analysis in combination with genetics and mice experiments indicate that downregulation of sphingolipid or upregulation of phosphatidylcholine metabolism is a causal factor in early-stage T2D pathophysiology. Our findings indicate that metabolites like SM C16:1, SM C18:1, and PC aa C38:3 mediate the effect of BMI on T2D and elucidate their role in obesity related T2D pathologies.

Objective: Technological advances have brought a steady increase in the availability of various types of omics data, from genomics to metabolomics. Integrating these multi-omics data is a chance and challenge for systems biology; yet, tools to fully tap their potential remain scarce. Methods: We present here a fully unsupervised and versatile correlation-based method – termed Correlation guided Network Integration (CoNI) – to integrate multi-omics data into a hypergraph structure that allows for the identification of effective modulators of metabolism. Our approach yields single transcripts of potential relevance that map to specific, densely connected, metabolic subgraphs or pathways. Results: By applying our method on transcriptomics and metabolomics data from murine livers under standard Chow or high-fat diet, we identified eleven genes with potential regulatory effects on hepatic metabolism. Five candidates, including the hepatokine INHBE, were validated in human liver biopsies to correlate with diabetes-related traits such as overweight, hepatic fat content, and insulin resistance (HOMA-IR). Conclusion: Our method's successful application to an independent omics dataset confirmed that the novel CoNI framework is a transferable, entirely data-driven, flexible, and versatile tool for multiple omics data integration and interpretation.

ContextPheochromocytomas and paragangliomas (PPGL) cause catecholamine excess leading to a characteristic clinical phenotype. Intra-individual changes at metabolome level have been described after surgical PPGL removal. The value of metabolomics for the diagnosis of PPGL has not been studied yet.ObjectiveEvaluation of quantitative metabolomics as a diagnostic tool for PPGL.DesignTargeted metabolomics by liquid chromatography-tandem mass spectrometry of plasma specimens and statistical modeling using ML-based feature selection approaches in a clinically well characterized cohort study.PatientsProspectively enrolled patients (n=36, 17 female) from the Prospective Monoamine-producing Tumor Study (PMT) with hormonally active PPGL and 36 matched controls in whom PPGL was rigorously excluded.ResultsAmong 188 measured metabolites, only without considering false discovery rate, 4 exhibited statistically significant differences between patients with PPGL and controls (histidine p=0.004, threonine p=0.008, lyso PC a C28:0 p=0.044, sum of hexoses p=0.018). Weak, but significant correlations for histidine, threonine and lyso PC a C28:0 with total urine catecholamine levels were identified. Only the sum of hexoses (reflecting glucose) showed significant correlations with plasma metanephrines.By using ML-based feature selection approaches, we identified diagnostic signatures which all exhibited low accuracy and sensitivity. The best predictive value (sensitivity 87.5%, accuracy 67.3%) was obtained by using Gradient Boosting Machine Modelling.ConclusionsThe diabetogenic effect of catecholamine excess dominates the plasma metabolome in PPGL patients. While curative surgery for PPGL led to normalization of catecholamine-induced alterations of metabolomics in individual patients, plasma metabolomics are not useful for diagnostic purposes, most likely due to inter-individual variability.

BackgroundExcess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI).Methods and findingsWe assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case-control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10-8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10-5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some-but not all-metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., -0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10-5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10-3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds.ConclusionsThis study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI-the principal modifiable risk factor of kidney cancer.

Introduction Relationships between endogenous female sex hormones and glycemic traits remain understudied, especially in men. We examined whether endogenous 17α-hydroxyprogesterone (17-OHP), progesterone, estradiol (E2), and free estradiol (fE2) were associated with glycemic traits and glycemic deterioration.Research design and methods 921 mainly middle-aged and elderly men and 390 perimenopausal/postmenopausal women from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) F4/FF4 cohort study were followed up for a median of 6.4 years. Sex hormones were measured at baseline using mass spectrometry. We calculated regression coefficients (β) and ORs with 95% CIs using multivariable-adjusted linear and logistic regression models for Z-standardized hormones and glycemic traits or glycemic deterioration (ie, worsening of categorized glucose tolerance status), respectively.Results In the cross-sectional analysis (n=1222 men and n=594 women), in men, 17-OHP was inversely associated with 2h-glucose (2hG) (β=−0.067, 95% CI −0.120 to −0.013) and fasting insulin (β=−0.074, 95% CI −0.118 to −0.030), and positively associated with Quantitative Insulin Sensitivity Check Index (QUICKI) (β=0.061, 95% CI 0.018 to 0.105). Progesterone was inversely associated with fasting insulin (β=−0.047, 95% CI −0.088 to −0.006) and positively associated with QUICKI (β=0.041, 95% CI 0.001 to 0.082). E2 was inversely associated with fasting insulin (β=−0.068, 95% CI −0.116 to −0.020) and positively associated with QUICKI (β=0.059, 95% CI 0.012 to 0.107). fE2 was positively associated with glycated hemoglobin (HbA1c) (β=0.079, 95% CI 0.027 to 0.132). In women, 17-OHP was positively associated with fasting glucose (FG) (β=0.068, 95% CI 0.014 to 0.123). fE2 was positively associated with FG (β=0.080, 95% CI 0.020 to 0.141) and HbA1c (β=0.121, 95% CI 0.062 to 0.180). In the sensitivity analyses restricted to postmenopausal women, we observed a positive association between 17-OHP and glycemic deterioration (OR=1.518, 95% CI 1.033 to 2.264).Conclusions Inter-relations exist between female sex hormones and glucose-related traits among perimenopausal/postmenopausal women and insulin-related traits among men. Endogenous progestogens and estrogens appear to be involved in glucose homeostasis not only in women but in men as well. Further well-powered studies assessing causal associations between endogenous female sex hormones and glycemic traits are warranted.

Objective: The liver regulates the availability of insulin to other tissues and is the first line insulin response organ physiologically exposed to higher insulin concentrations than the periphery. Basal insulin during fasting inhibits hepatic gluconeogenesis and glycogenolysis, whereas postprandial insulin peaks stimulate glycogen synthesis. The molecular consequences of chronic insulin deficiency for the liver have not been studied systematically. Methods: We analyzed liver samples of a genetically diabetic pig model (MIDY) and of wild-type (WT) littermate controls by RNA sequencing, proteomics, and targeted metabolomics/lipidomics. Results: Cross-omics analyses revealed increased activities in amino acid metabolism, oxidation of fatty acids, ketogenesis, and gluconeogenesis in the MIDY samples. In particular, the concentrations of the ketogenic enzyme 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) and of retinol dehydrogenase 16 (RDH16), which catalyzes the first step in retinoic acid biogenesis, were highly increased. Accordingly, elevated levels of retinoic acid, which stimulates the expression of the gluconeogenic enzyme phosphoenolpyruvate carboxykinase (PCK1), were measured in the MIDY samples. In contrast, pathways related to extracellular matrix and inflammation/pathogen defense response were less active than in the WT samples. Conclusions: The first multi-omics study of a clinically relevant diabetic large animal model revealed molecular signatures and key drivers of functional alterations of the liver in insulin-deficient diabetes mellitus. The multi-omics data set provides a valuable resource for comparative analyses with other experimental or clinical data sets. Keywords: Liver, Insulin deficiency, Transcriptome, Proteome, Metabolome, Lipidome

Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing’s syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification.

Glucotoxic metabolites and pathways play a crucial role in diabetic complications, and new treatment options which improve glucotoxicity are highly warranted. In this study, we analyzed bezafibrate (BEZ) treated, streptozotocin (STZ) injected mice, which showed an improved glucose metabolism compared to untreated STZ animals. In order to identify key molecules and pathways which participate in the beneficial effects of BEZ, we studied plasma, skeletal muscle, white adipose tissue (WAT) and liver samples using non-targeted metabolomics (NMR spectroscopy), targeted metabolomics (mass spectrometry), microarrays and mitochondrial enzyme activity measurements, with a particular focus on the liver. The analysis of muscle and WAT demonstrated that STZ treatment elevated inflammatory pathways and reduced insulin signaling and lipid pathways, whereas BEZ decreased inflammatory pathways and increased insulin signaling and lipid pathways, which can partly explain the beneficial effects of BEZ on glucose metabolism. Furthermore, lysophosphatidylcholine levels were lower in the liver and skeletal muscle of STZ mice, which were reverted in BEZ-treated animals. BEZ also improved circulating and hepatic glucose levels as well as lipid profiles. In the liver, BEZ treatment reduced elevated fumarate levels in STZ mice, which was probably due to a decreased expression of urea cycle genes. Since fumarate has been shown to participate in glucotoxic pathways, our data suggests that BEZ treatment attenuates the urea cycle in the liver, decreases fumarate levels and, in turn, ameliorates glucotoxicity and reduces insulin resistance in STZ mice.

Summary: Background: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. Methods: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. Findings: A higher Tpred score was associated with healthier diets high in wholegrain (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=–0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (β=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher Tpred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (β=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (β=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2. Interpretation: Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health. Funding: This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115,317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013) and EFPIA companies.

Summary: The proteasome is the main proteolytic system for targeted protein degradation in the cell and is fine-tuned according to cellular needs. Here, we demonstrate that mitochondrial dysfunction and concomitant metabolic reprogramming of the tricarboxylic acid (TCA) cycle reduce the assembly and activity of the 26S proteasome. Both mitochondrial mutations in respiratory complex I and treatment with the anti-diabetic drug metformin impair 26S proteasome activity. Defective 26S assembly is reversible and can be overcome by supplementation of aspartate or pyruvate. This metabolic regulation of 26S activity involves specific regulation of proteasome assembly factors via the mTORC1 pathway. Of note, reducing 26S activity by metformin confers increased resistance toward the proteasome inhibitor bortezomib, which is reversible upon pyruvate supplementation. Our study uncovers unexpected consequences of defective mitochondrial metabolism for proteasomal protein degradation in the cell, which has important pathophysiological and therapeutic implications.

Objective: The liver is a central target organ of growth hormone (GH), which stimulates the synthesis of insulin-like growth factor 1 (IGF1) and affects multiple biochemical pathways. A systematic multi-omics analysis of GH effects in the liver has not been performed. GH receptor (GHR) deficiency is a unique model for studying the consequences of lacking GH action. In this study, we used molecular profiling techniques to capture a broad spectrum of these effects in the liver of a clinically relevant large animal model for Laron syndrome. Methods: We performed holistic proteome and targeted metabolome analyses of liver samples from 6-month-old GHR-deficient (GHR-KO) pigs and GHR-expressing controls (four males, four females per group). Results: GHR deficiency resulted in an increased abundance of enzymes involved in amino acid degradation, in the urea cycle, and in the tricarboxylic acid cycle. A decreased ratio of long-chain acylcarnitines to free carnitine suggested reduced activity of carnitine palmitoyltransferase 1A and thus reduced mitochondrial import of fatty acids for beta-oxidation. Increased levels of short-chain acylcarnitines in the liver and in the circulation of GHR-KO pigs may result from impaired beta-oxidation of short-chain fatty acids or from increased degradation of specific amino acids. The concentration of mono-unsaturated glycerophosphocholines was significantly increased in the liver of GHR-KO pigs without morphological signs of steatosis, although the abundances of several proteins functionally linked to non-alcoholic fatty liver disease (fetuin B, retinol binding protein 4, several mitochondrial proteins) were increased. Moreover, GHR-deficient liver samples revealed distinct changes in the methionine and glutathione metabolic pathways, in particular, a significantly increased level of glycine N-methyltransferase and increased levels of total and free glutathione. Several proteins revealed a sex-related abundance difference in the control group but not in the GHR-KO group. Conclusions: Our integrated proteomics/targeted metabolomics study of GHR-deficient and control liver samples from a clinically relevant large animal model identified a spectrum of biological pathways that are significantly altered in the absence of GH action. Moreover, new insights into the role of GH in the sex-related specification of liver functions were provided.

Abstract Coenzyme Q (CoQ) deficiency has been associated with primary defects in the CoQ biosynthetic pathway or to secondary events. In some cases, the exogenous CoQ supplementation has limited efficacy. In the Coq9R239X mouse model with fatal mitochondrial encephalopathy due to CoQ deficiency, we have tested the therapeutic potential of β‐resorcylic acid (β‐RA), a structural analog of the CoQ precursor 4‐hydroxybenzoic acid and the anti‐inflammatory salicylic acid. β‐RA noticeably rescued the phenotypic, morphological, and histopathological signs of the encephalopathy, leading to a significant increase in the survival. Those effects were due to the decrease of the levels of demethoxyubiquinone‐9 (DMQ9) and the increase of mitochondrial bioenergetics in peripheral tissues. However, neither CoQ biosynthesis nor mitochondrial function changed in the brain after the therapy, suggesting that some endocrine interactions may induce the reduction of the astrogliosis, spongiosis, and the secondary down‐regulation of astrocytes‐related neuroinflammatory genes. Because the therapeutic outcomes of β‐RA administration were superior to those after CoQ10 supplementation, its use in the clinic should be considered in CoQ deficiencies.

Abstract Background Visceral adipose tissue (VAT) area is a strong predictor of obesity-related cardiometabolic alterations, but its measurement is costly, time consuming and, in some cases, involves radiation exposure. Glutamate, a by-product of branched-chain-amino-acid (BCAA) catabolism, has been shown to be increased in visceral obese individuals. In this follow-up data analysis, we aimed to investigate the ability of plasma glutamate to identify individuals with visceral obesity and concomitant metabolic alterations. Methods Measurements of adiposity, targeted blood metabolomics and cardiometabolic risk factors were performed in 59 healthy middle-aged women. Visceral and subcutaneous adipose tissue areas were measured by computed tomography (CT) whereas body fat and lean mass were assessed by dual-energy x-ray absorptiometry (DEXA). Results The univariate Pearson correlation coefficient between glutamate and VAT area was r = 0.46 (p

Abstract The development of chronic obstructive pulmonary disease (COPD) pathogenesis remains unclear, but emerging evidence supports a crucial role for inducible bronchus‐associated lymphoid tissue (iBALT) in disease progression. Mechanisms underlying iBALT generation, particularly during chronic CS exposure, remain to be defined. Oxysterol metabolism of cholesterol is crucial to immune cell localization in secondary lymphoid tissue. Here, we demonstrate that oxysterols also critically regulate iBALT generation and the immune pathogenesis of COPD. In both COPD patients and cigarette smoke (CS)‐exposed mice, we identified significantly upregulated CH25H and CYP7B1 expression in airway epithelial cells, regulating CS‐induced B‐cell migration and iBALT formation. Mice deficient in CH25H or the oxysterol receptor EBI2 exhibited decreased iBALT and subsequent CS‐induced emphysema. Further, inhibition of the oxysterol pathway using clotrimazole resolved iBALT formation and attenuated CS‐induced emphysema in vivo therapeutically. Collectively, our studies are the first to mechanistically interrogate oxysterol‐dependent iBALT formation in the pathogenesis of COPD, and identify a novel therapeutic target for the treatment of COPD and potentially other diseases driven by the generation of tertiary lymphoid organs.

Background/Aims: Impaired birth outcomes, like low birth weight, have consistently been associated with increased disease susceptibility to hypertension in later life. Alterations in the maternal or fetal metabolism might impact on fetal growth and influence birth outcomes. Discerning associations between the maternal and fetal metabolome and surrogate parameters of fetal growth could give new insight into the complex relationship between intrauterine conditions, birth outcomes, and later life disease susceptibility. Methods: Using flow injection tandem mass spectrometry, targeted metabolomics was performed in serum samples obtained from 226 mother/child pairs at delivery. Associations between neonatal birth weight and concentrations of 163 maternal and fetal metabolites were analyzed. Results: After FDR adjustment using the Benjamini-Hochberg procedure lysophosphatidylcholines (LPC) 14: 0, 16: 1, and 18: 1 were strongly positively correlated with birth weight. In a stepwise linear regression model corrected for established confounding factors of birth weight, LPC 16: 1 showed the strongest independent association with birth weight (CI: 93.63 - 168.94; P = 6.94×10-11 ). The association with birth weight was stronger than classical confounding factors such as offspring sex (CI: -258.81- -61.32; P = 0.002) and maternal smoking during pregnancy (CI: -298.74 - -29.51; P = 0.017). Conclusions: After correction for multiple testing and adjustment for potential confounders, LPC 16: 1 showed a very strong and independent association with birth weight. The underlying molecular mechanisms linking fetal LPCs with birth weight need to be addressed in future studies.

Background/Aims: Gestational diabetes (GDM) might be associated with alterations in the metabolomic profile of affected mothers and their offspring. Until now, there is a paucity of studies that investigated both, the maternal and the fetal serum metabolome in the setting of GDM. Mounting evidence suggests that the fetus is not just passively affected by gestational disease but might play an active role in it. Metabolomic studies performed in maternal blood and fetal cord blood could help to better discern distinct fetal from maternal disease interactions. Methods: At the time of birth, serum samples from mothers and newborns (cord blood samples) were collected and screened for 163 metabolites utilizing tandem mass spectrometry. The cohort consisted of 412 mother/child pairs, including 31 cases of maternal GDM. Results: An initial non-adjusted analysis showed that eight metabolites in the maternal blood and 54 metabolites in the cord blood were associated with GDM. After Benjamini-Hochberg (BH) procedure and adjustment for confounding factors for GDM, fetal phosphatidylcholine acyl-alkyl C 32: 1 and proline still showed an independent association with GDM. Conclusions: This study found metabolites in cord blood which were associated with GDM, even after adjustment for established risk factors of GDM. To the best of our knowledge, this is the first study demonstrating an independent association between fetal serum metabolites and maternal GDM. Our findings might suggest a potential effect of the fetal metabolome on maternal GDM.

Protein imbalance during pregnancy affects women in underdeveloped and developing countries and is associated with compromised offspring growth and an increased risk of metabolic diseases in later life. We studied in a porcine model the glucose and urea metabolism, and circulatory hormone and metabolite profile of offspring exposed during gestation, to maternal isoenergetic low–high (LP-HC), high–low (HP-LC) or adequate (AP) protein–carbohydrate ratio diets. At birth, LP-HC were lighter and the plasma acetylcarnitine to free carnitine ratios at 1 day of life was lower compared to AP offspring. Plasma urea concentrations were lower in 1 day old LP-HC offspring than HP-LC. In the juvenile period, increased insulin concentrations were observed in LP-HC and HP-LC offspring compared to AP, as was body weight from HP-LC compared to LP-HC. Plasma triglyceride concentrations were lower in 80 than 1 day old HP-LC offspring, and glucagon concentrations lower in 80 than 1 day old AP and HP-LC offspring. Plasma urea and the ratio of glucagon to insulin were lower in all 80 than 1 day old offspring. Aminoacyl-tRNA, arginine and phenylalanine, tyrosine and tryptophan metabolism, histidine and beta-alanine metabolism differed between 1 and 80 day old AP and HP-LC offspring. Maternal protein imbalance throughout pregnancy did not result in significant consequences in offspring metabolism compared to AP, indicating enormous plasticity by the placenta and developing offspring.

Objective: The prevalence of diabetes mellitus and associated complications is steadily increasing. As a resource for studying systemic consequences of chronic insulin insufficiency and hyperglycemia, we established a comprehensive biobank of long-term diabetic INSC94Y transgenic pigs, a model of mutant INS gene-induced diabetes of youth (MIDY), and of wild-type (WT) littermates. Methods: Female MIDY pigs (n = 4) were maintained with suboptimal insulin treatment for 2 years, together with female WT littermates (n = 5). Plasma insulin, C-peptide and glucagon levels were regularly determined using specific immunoassays. In addition, clinical chemical, targeted metabolomics, and lipidomics analyses were performed. At age 2 years, all pigs were euthanized, necropsied, and a broad spectrum of tissues was taken by systematic uniform random sampling procedures. Total beta cell volume was determined by stereological methods. A pilot proteome analysis of pancreas, liver, and kidney cortex was performed by label free proteomics. Results: MIDY pigs had elevated fasting plasma glucose and fructosamine concentrations, C-peptide levels that decreased with age and were undetectable at 2 years, and an 82% reduced total beta cell volume compared to WT. Plasma glucagon and beta hydroxybutyrate levels of MIDY pigs were chronically elevated, reflecting hallmarks of poorly controlled diabetes in humans. In total, ∼1900 samples of different body fluids (blood, serum, plasma, urine, cerebrospinal fluid, and synovial fluid) as well as ∼17,000 samples from ∼50 different tissues and organs were preserved to facilitate a plethora of morphological and molecular analyses. Principal component analyses of plasma targeted metabolomics and lipidomics data and of proteome profiles from pancreas, liver, and kidney cortex clearly separated MIDY and WT samples. Conclusions: The broad spectrum of well-defined biosamples in the Munich MIDY Pig Biobank that will be available to the scientific community provides a unique resource for systematic studies of organ crosstalk in diabetes in a multi-organ, multi-omics dimension.

Abstract Diabetes-associated metabolites may aid the identification of new risk variants for type 2 diabetes. Using targeted metabolomics within a subsample of the German EPIC-Potsdam study (n = 2500), we tested previously published SNPs for their association with diabetes-associated metabolites and conducted an additional exploratory analysis using data from the exome chip including replication within 2,692 individuals from the German KORA F4 study. We identified a total of 16 loci associated with diabetes-related metabolite traits, including one novel association between rs499974 (MOGAT2) and a diacyl-phosphatidylcholine ratio (PC aa C40:5/PC aa C38:5). Gene-based tests on all exome chip variants revealed associations between GFRAL and PC aa C42:1/PC aa C42:0, BIN1 and SM (OH) C22:2/SM C18:0 and TFRC and SM (OH) C22:2/SM C16:1). Selecting variants for gene-based tests based on functional annotation identified one additional association between OR51Q1 and hexoses. Among single genetic variants consistently associated with diabetes-related metabolites, two (rs174550 (FADS1), rs3204953 (REV3L)) were significantly associated with type 2 diabetes in large-scale meta-analysis for type 2 diabetes. In conclusion, we identified a novel metabolite locus in single variant analyses and four genes within gene-based tests and confirmed two previously known mGWAS loci which might be relevant for the risk of type 2 diabetes.

The vertebrate Scube (Signal peptide, CUB, and EGF-like domain-containing protein) family consists of three independent members, Scube1–3, which encode secreted cell surface-associated membrane glycoproteins. Limited information about the general function of this gene family is available, and their roles during adulthood. Here, we present the first Scube3 mutant mouse line (Scube3N294K/N294K), which clearly shows phenotypic alterations by carrying a missense mutation in exon 8, and thus contributes to our understanding of SCUBE3 functions. We performed a detailed phenotypic characterization in the German Mouse Clinic (GMC). Scube3N294K/N294K mutants showed morphological abnormalities of the skeleton, alterations of parameters relevant for bone metabolism, changes in renal function, and hearing impairments. These findings correlate with characteristics of the rare metabolic bone disorder Paget disease of bone (PDB), associated with the chromosomal region of human SCUBE3. In addition, alterations in energy metabolism, behavior, and neurological functions were detected in Scube3N294K/N294K mice. The Scube3N294K/N294K mutant mouse line may serve as a new model for further studying the effect of impaired SCUBE3 gene function.

Alongside the obesity epidemic, the prevalence of maternal diabetes is rising worldwide, and adverse effects on fetal development and metabolic disturbances in the offspring's later life have been described. To clarify whether metabolic programming effects are due to mild maternal hyperglycemia without confounding obesity, we investigated wild-type offspring of INSC93S transgenic pigs, which are a novel genetically modified large-animal model expressing mutant insulin (INS) C93S in pancreatic β-cells. This mutation results in impaired glucose tolerance, mild fasting hyperglycemia and insulin resistance during late pregnancy. Compared with offspring from wild-type sows, piglets from hyperglycemic mothers showed impaired glucose tolerance and insulin resistance (homeostatic model assessment of insulin resistance: +3-fold in males; +4.4-fold in females) prior to colostrum uptake. Targeted metabolomics in the fasting and insulin-stimulated state revealed distinct alterations in the plasma metabolic profile of piglets from hyperglycemic mothers. They showed increased levels of acylcarnitines, gluconeogenic precursors such as alanine, phospholipids (in particular lyso-phosphatidylcholines) and α-aminoadipic acid, a potential biomarker for type 2 diabetes. These observations indicate that mild gestational hyperglycemia can cause impaired glucose tolerance, insulin resistance and associated metabolic alterations in neonatal offspring of a large-animal model born at a developmental maturation status comparable to human babies.

Biological exploration of early biomarkers for chronic kidney disease (CKD) in (pre)diabetic individuals is crucial for personalized management of diabetes. Here, we evaluated two candidate biomarkers of incident CKD (sphingomyelin (SM) C18:1 and phosphatidylcholine diacyl (PC aa) C38:0) concerning kidney function in hyperglycemic participants of the Cooperative Health Research in the Region of Augsburg (KORA) cohort, and in two biofluids and six organs of leptin receptor-deficient (db/db) mice and wild type controls. Higher serum concentrations of SM C18:1 and PC aa C38:0 in hyperglycemic individuals were found to be associated with lower estimated glomerular filtration rate (eGFR) and higher odds of CKD. In db/db mice, both metabolites had a significantly lower concentration in urine and adipose tissue, but higher in the lungs. Additionally, db/db mice had significantly higher SM C18:1 levels in plasma and liver, and PC aa C38:0 in adrenal glands. This cross-sectional human study confirms that SM C18:1 and PC aa C38:0 associate with kidney dysfunction in pre(diabetic) individuals, and the animal study suggests a potential implication of liver, lungs, adrenal glands, and visceral fat in their systemic regulation. Our results support further validation of the two phospholipids as early biomarkers of renal disease in patients with (pre)diabetes.

Shared metabolomic patterns at delivery have been suggested to underlie the mother-to-child transmission of adverse metabolic health. This study aimed to investigate whether mothers with gestational diabetes mellitus (GDM) and their offspring show similar metabolomic patterns several years postpartum. Targeted metabolomics (including 137 metabolites) was performed in plasma samples obtained during an oral glucose tolerance test from 48 mothers with GDM and their offspring at a cross-sectional study visit 8 years after delivery. Partial Pearson’s correlations between the area under the curve (AUC) of maternal and offspring metabolites were calculated, yielding so-called Gaussian graphical models. Spearman’s correlations were applied to investigate correlations of body mass index (BMI), Matsuda insulin sensitivity index (ISI-M), dietary intake, and physical activity between generations, and correlations of metabolite AUCs with lifestyle variables. This study revealed that BMI, ISI-M, and the AUC of six metabolites (carnitine, taurine, proline, SM(-OH) C14:1, creatinine, and PC ae C34:3) were significantly correlated between mothers and offspring several years postpartum. Intergenerational metabolite correlations were independent of shared BMI, ISI-M, age, sex, and all other metabolites. Furthermore, creatinine was correlated with physical activity in mothers. This study suggests that there is long-term metabolic programming in the offspring of mothers with GDM and informs us about targets that could be addressed by future intervention studies.

Circulating levels of branched-chain amino acids, glycine, or aromatic amino acids have been associated with risk of type 2 diabetes. However, whether those associations reflect causal relationships or are rather driven by early processes of disease development is unclear. We selected diabetes-related amino acid ratios based on metabolic network structures and investigated causal effects of these ratios and single amino acids on the risk of type 2 diabetes in two-sample Mendelian randomization studies. Selection of genetic instruments for amino acid traits relied on genome-wide association studies in a representative sub-cohort (up to 2265 participants) of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study and public data from genome-wide association studies on single amino acids. For the selected instruments, outcome associations were drawn from the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis, 74,124 cases and 824,006 controls) consortium. Mendelian randomization results indicate an inverse association for a per standard deviation increase in ln-transformed tyrosine/methionine ratio with type 2 diabetes (OR = 0.87 (0.81–0.93)). Multivariable Mendelian randomization revealed inverse association for higher log10-transformed tyrosine levels with type 2 diabetes (OR = 0.19 (0.04–0.88)), independent of other amino acids. Tyrosine might be a causal trait for type 2 diabetes independent of other diabetes-associated amino acids.

Acute anorexia nervosa (AN) constitutes an extreme physiological state. We aimed to detect state related metabolic alterations during inpatient admission and upon short- and long-term weight regain. In addition, we tested the hypothesis that metabolite concentrations adapt to those of healthy controls (HC) after long-term weight regain. Thirty-five female adolescents with AN and 25 female HC were recruited. Based on a targeted approach 187 metabolite concentrations were detected at inpatient admission (T0), after short-term weight recovery (T1; half of target-weight) and close to target weight (T2). Pattern hunter and time course analysis were performed. The highest number of significant differences in metabolite concentrations (N = 32) were observed between HC and T1. According to the detected main pattern, metabolite concentrations at T2 became more similar to those of HC. The course of single metabolite concentrations (e.g., glutamic acid) revealed different metabolic subtypes within the study sample. Patients with AN after short-term weight regain are in a greater “metabolic imbalance” than at starvation. After long-term weight regain, patients reach a metabolite profile similar to HC. Our results might be confounded by different metabolic subtypes of patients with AN.

A large part of metabolomics research relies on experiments involving mouse models, which are usually 6 to 20 weeks of age. However, in this age range mice undergo dramatic developmental changes. Even small age differences may lead to different metabolomes, which in turn could increase inter-sample variability and impair the reproducibility and comparability of metabolomics results. In order to learn more about the variability of the murine plasma metabolome, we analyzed male and female C57BL/6J, C57BL/6NTac, 129S1/SvImJ, and C3HeB/FeJ mice at 6, 10, 14, and 20 weeks of age, using targeted metabolomics (BIOCRATES AbsoluteIDQ™ p150 Kit). Our analysis revealed high variability of the murine plasma metabolome during adolescence and early adulthood. A general age range with minimal variability, and thus a stable metabolome, could not be identified. Age-related metabolomic changes as well as the metabolite profiles at specific ages differed markedly between mouse strains. This observation illustrates the fact that the developmental timing in mice is strain specific. We therefore stress the importance of deliberate strain choice, as well as consistency and precise documentation of animal age, in metabolomics studies.

This study compared metabolite shifts induced by training for, participation in, and recovery from a marathon race competition among athletes divided into three groups based on fitness (relative maximum oxygen uptake (VO2max)) and performance levels (net running time). Plasma samples from 76 male runners participating in the Munich Marathon were analyzed for metabolite shifts using a targeted metabolomics panel. For the entire cohort of runners, pronounced increases were measured immediately after the race for plasma concentrations of acylcarnitines (AC), the ratio (palmitoylcarnitine + stearoylcarnitine)/free carnitine that is used as a proxy for the activity of the mitochondrial enzyme carnitine palmitoyltransferase, and arginine-related metabolites, with decreases in most amino acids (AA) and phospholipids. Plasma levels of AA and phospholipids were strongly increased 24 and 72 h post-race. Post-race plasma concentrations of AC and arginine-related metabolites were higher in the low compared to top performers, indicating an accumulation of fatty acids and a reliance on protein catabolism to provide energy after the marathon event. This study showed that marathon race competition is associated with an extensive and prolonged perturbation in plasma metabolite concentrations with a strong AC signature that is greater in the slower, less aerobically fit runners. Furthermore, changes in the arginine-related metabolites were observed.

Coronary artery disease (CAD) is a common complication of type 2 diabetes mellitus (T2D). This case-control study was done to identify metabolites with different concentrations between T2D patients with and without CAD and to characterise implicated metabolic mechanisms relating to CAD. Fasting serum samples of 57 T2D subjects, 26 with (cases) and 31 without CAD (controls), were targeted for metabolite profiling of 163 metabolites. To assess the association between metabolite levels and CAD, partial least squares (PLS) analysis and multivariate logistic regression analysis with adjustment for CAD risk factors and medications were performed. We observed a separation of cases and controls with two classes of metabolites being significantly associated with CAD, including phosphatidylcholines, and serine. Four metabolites being independent from the common CAD risk factors displaying best separation between cases and controls were further selected. Addition of the metabolite concentrations to risk factor analysis raised the area under the receiver-operating-characteristic curve from 0.72 to 0.88 (p=0.020), providing improved sensitivity and specificity for CAD classification. Serum phospholipid and serine levels independently discriminate T2D patients with and without CAD. Oxidative stress and reduced antioxidative capacity lead to lower metabolite concentrations probably due to changes in membrane composition and accelerated phospholipid degradation.

Ageing, one of the largest risk factors for many complex diseases, is highly interconnected to metabolic processes. Investigating the changes in metabolite concentration during ageing among healthy individuals offers us unique insights to healthy ageing. We aim to identify ageing-associated metabolites that are independent from chronological age to deepen our understanding of the long-term changes in metabolites upon ageing. Sex-stratified longitudinal analyses were performed using fasting serum samples of 590 healthy KORA individuals (317 women and 273 men) who participated in both baseline (KORA S4) and seven-year follow-up (KORA F4) studies. Replication was conducted using serum samples of 386 healthy CARLA participants (195 women and 191 men) in both baseline (CARLA-0) and four-year follow-up (CARLA-1) studies. Generalized estimation equation models were performed on each metabolite to identify ageing-associated metabolites after adjusting for baseline chronological age, body mass index, physical activity, smoking status, alcohol intake and systolic blood pressure. Literature researches were conducted to understand their biochemical relevance. Out of 122 metabolites analysed, we identified and replicated five (C18, arginine, ornithine, serine and tyrosine) and four (arginine, ornithine, PC aa C36:3 and PC ae C40:5) significant metabolites in women and men respectively. Arginine decreased, while ornithine increased in both sexes. These metabolites are involved in several ageing processes: apoptosis, mitochondrial dysfunction, inflammation, lipid metabolism, autophagy and oxidative stress resistance. The study reveals several significant ageing-associated metabolite changes with two-time-point measurements on healthy individuals. Larger studies are required to confirm our findings.

Night shift work can have a serious impact on health. Here, we assess whether and how night shift work influences the metabolite profiles, specifically with respect to different chronotype classes. We have recruited 100 women including 68 nurses working both, day shift and night shifts for up to 5 consecutive days and collected 3640 spontaneous urine samples. About 424 waking-up urine samples were measured using a targeted metabolomics approach. To account for urine dilution, we applied three methods to normalize the metabolite values: creatinine-, osmolality- and regression-based normalization. Based on linear mixed effect models, we found 31 metabolites significantly (false discovery rate

Advances in the "omics" field bring about the need for a high number of good quality samples. Many omics studies take advantage of biobanked samples to meet this need. Most of the laboratory errors occur in the pre-analytical phase. Therefore evidence-based standard operating procedures for the pre-analytical phase as well as markers to distinguish between 'good' and 'bad' quality samples taking into account the desired downstream analysis are urgently needed. We studied concentration changes of metabolites in serum samples due to pre-storage handling conditions as well as due to repeated freeze-thaw cycles. We collected fasting serum samples and subjected aliquots to up to four freeze-thaw cycles and to pre-storage handling delays of 12, 24 and 36 hours at room temperature (RT) and on wet and dry ice. For each treated aliquot, we quantified 127 metabolites through a targeted metabolomics approach. We found a clear signature of degradation in samples kept at RT. Storage on wet ice led to less pronounced concentration changes. 24 metabolites showed significant concentration changes at RT. In 22 of these, changes were already visible after only 12 hours of storage delay. Especially pronounced were increases in lysophosphatidylcholines and decreases in phosphatidylcholines. We showed that the ratio between the concentrations of these molecule classes could serve as a measure to distinguish between 'good' and 'bad' quality samples in our study. In contrast, we found quite stable metabolite concentrations during up to four freeze-thaw cycles. We concluded that pre-analytical RT handling of serum samples should be strictly avoided and serum samples should always be handled on wet ice or in cooling devices after centrifugation. Moreover, serum samples should be frozen at or below -80°C as soon as possible after centrifugation.

BackgroundInformation regarding the variability of metabolite levels over time in an individual is required to estimate the reproducibility of metabolite measurements. In intervention studies, it is critical to appropriately judge changes that are elicited by any kind of intervention. The pre-analytic phase (collection, transport and sample processing) is a particularly important component of data quality in multi-center studies.MethodsReliability of metabolites (within-and between-person variance, intraclass correlation coefficient) and stability (shipment simulation at different temperatures, use of gel-barrier collection tubes, freeze-thaw cycles) were analyzed in fasting serum and plasma samples of 22 healthy human subjects using a targeted LC-MS approach.ResultsReliability of metabolite measurements was higher in serum compared to plasma samples and was good in most saturated short-and medium-chain acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids and hexose. The majority of metabolites were stable for 24 h on cool packs and at room temperature in non-centrifuged tubes. Plasma and serum metabolite stability showed good coherence. Serum metabolite concentrations were mostly unaffected by tube type and one or two freeze-thaw cycles.ConclusionA single time point measurement is assumed to be sufficient for a targeted metabolomics analysis of most metabolites. For shipment, samples should ideally be separated and frozen immediately after collection, as some amino acids and biogenic amines become unstable within 3 h on cool packs. Serum gel-barrier tubes can be used safely for this process as they have no effect on concentration in most metabolites. Shipment of non-centrifuged samples on cool packs is a cost-efficient alternative for most metabolites.

The transcription factor Zscan10 had been attributed a role as a pluripotency factor in embryonic stem cells based on its interaction with Oct4 and Sox2 in in vitro assays. Here we suggest a potential role of Zscan10 in controlling progenitor cell populations in vivo. Mice homozygous for a Zscan10 mutation exhibit reduced weight, mild hypoplasia in the spleen, heart and long bones and phenocopy an eye malformation previously described for Sox2 hypomorphs. Phenotypic abnormalities are supported by the nature of Zscan10 expression in midgestation embryos and adults suggesting a role for Zscan10 in either maintaining progenitor cell subpopulation or impacting on fate choice decisions thereof.

Amebic liver abscess (ALA), a parasitic disease due to infection with the protozoan Entamoeba histolytica, occurs age and gender dependent with strong preferences for adult males. Using a mouse model for ALA with a similar male bias for the disease, we have investigated the role of female and male sexual hormones and provide evidence for a strong contribution of testosterone. Removal of testosterone by orchiectomy significantly reduced sizes of abscesses in male mice, while substitution of testosterone increased development of ALA in female mice. Activation of natural killer T (NKT) cells, which are known to be important for the control of ALA, is influenced by testosterone. Specifically activated NKT cells isolated from female mice produce more IFNγ compared to NKT cells derived from male mice. This high level production of IFNγ in female derived NKT cells was inhibited by testosterone substitution, while the IFNγ production in male derived NKT cells was increased by orchiectomy. Gender dependent differences were not a result of differences in the total number of NKT cells, but a result of a higher activation potential for the CD4(-) NKT cell subpopulation in female mice. Taken together, we conclude that the hormone status of the host, in particular the testosterone level, determines susceptibility to ALA at least in a mouse model of the disease.