Omentin associates with serum metabolite profiles indicating lower diabetes risk: KORA F4 Study.

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.

Association between pre-diagnostic circulating lipid metabolites and colorectal cancer risk: a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC).

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 < 0.05) with colorectal cancer risk. Hydroxysphingomyelin (SM (OH)) C22:2 (ORper doubling 0.60, 95% CI 0.47-0.77) and acylakyl-phosphatidylcholine (PC ae) C34:3 (ORper doubling 0.71, 95% CI 0.59-0.87) remained associated after multiple comparisons correction. These associations were unaltered after excluding the first 5 years of follow-up after blood collection and were consistent according to sex, age at diagnosis, BMI, and colorectal subsite. Two lipid patterns, one including 26 phosphatidylcholines and all sphingolipids, and another 30 phosphatidylcholines, were weakly inversely associated with colorectal cancer. INTERPRETATION: Elevated pre-diagnostic circulating levels of SM (OH) C22:2 and PC ae C34:3 and lipid patterns including phosphatidylcholines and sphingolipids were associated with lower colorectal cancer risk. This study may provide insight into potential links between specific lipids and colorectal cancer development. Additional prospective studies are needed to validate the observed associations. FUNDING: World Cancer Research Fund (reference: 2013/1002); European Commission (FP7: BBMRI-LPC; reference: 313010).

Circulating amino acid levels and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition and UK Biobank cohorts.

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.

Machine learning for classification of hypertension subtypes using multi-omics: A multi-centre, retrospective, data-driven study.

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).

Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios.

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.

Metabolic Signatures of Healthy Lifestyle Patterns and Colorectal Cancer Risk in a European Cohort.

BACKGROUND & AIMS: Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort. METHODS: Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1-5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer and Nutrition participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression. RESULTS: Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29-0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50-0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86-1.00) overall. Signature associations were stronger in male compared with female participants. CONCLUSIONS: Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer.

Pre- versus post-operative untargeted plasma nuclear magnetic resonance spectroscopy metabolomics of pheochromocytoma and paraganglioma.

PURPOSE: Pheochromocytomas and Paragangliomas (PPGL) result in chronic catecholamine excess and serious health complications. A recent study obtained a metabolic signature in plasma from PPGL patients; however, its targeted nature may have generated an incomplete picture and a broader approach could provide additional insights. We aimed to characterize the plasma metabolome of PPGL patients before and after surgery, using an untargeted approach, and to broaden the scope of the investigated metabolic impact of these tumors. DESIGN: A cohort of 36 PPGL patients was investigated. Blood plasma samples were collected before and after surgical tumor removal, in association with clinical and tumor characteristics. METHODS: Plasma samples were analyzed using untargeted nuclear magnetic resonance (NMR) spectroscopy metabolomics. The data were evaluated using a combination of uni- and multi-variate statistical methods. RESULTS: Before surgery, patients with a nonadrenergic tumor could be distinguished from those with an adrenergic tumor based on their metabolic profiles. Tyrosine levels were significantly higher in patients with high compared to those with low BMI. Comparing subgroups of pre-operative samples with their post-operative counterparts, we found a metabolic signature that included ketone bodies, glucose, organic acids, methanol, dimethyl sulfone and amino acids. Three signals with unclear identities were found to be affected. CONCLUSIONS: Our study suggests that the pathways of glucose and ketone body homeostasis are affected in PPGL patients. BMI-related metabolite levels were also found to be altered, potentially linking muscle atrophy to PPGL. At baseline, patient metabolomes could be discriminated based on their catecholamine phenotype.

Associations of endogenous androgens and sex hormone-binding globulin with kidney function and chronic kidney disease.

Introduction: The role of endogenous androgens in kidney function and disease has not been extensively explored in men and women. Research design and methods: We 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. Results: At 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 (ß=-1.305, [95% CI -2.290; -0.320]) and fT (ß=-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 (ß=-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). Conclusion: Suggestive 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.

The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium.

BACKGROUND: Excess 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 FINDINGS: We 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. CONCLUSIONS: This 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.

Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors.

Context: Pheochromocytomas 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. Objective: Evaluation of quantitative metabolomics as a diagnostic tool for PPGL. Design: Targeted 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. Patients: Prospectively 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. Results: Among 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. Conclusions: The 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.

Cross-sectional and prospective relationships of endogenous progestogens and estrogens with glucose metabolism in men and women: a KORA F4/FF4 Study.

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 (ß) 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) (ß=-0.067, 95% CI -0.120 to -0.013) and fasting insulin (ß=-0.074, 95% CI -0.118 to -0.030), and positively associated with Quantitative Insulin Sensitivity Check Index (QUICKI) (ß=0.061, 95% CI 0.018 to 0.105). Progesterone was inversely associated with fasting insulin (ß=-0.047, 95% CI -0.088 to -0.006) and positively associated with QUICKI (ß=0.041, 95% CI 0.001 to 0.082). E2 was inversely associated with fasting insulin (ß=-0.068, 95% CI -0.116 to -0.020) and positively associated with QUICKI (ß=0.059, 95% CI 0.012 to 0.107). fE2 was positively associated with glycated hemoglobin (HbA1c) (ß=0.079, 95% CI 0.027 to 0.132). In women, 17-OHP was positively associated with fasting glucose (FG) (ß=0.068, 95% CI 0.014 to 0.123). fE2 was positively associated with FG (ß=0.080, 95% CI 0.020 to 0.141) and HbA1c (ß=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.

Posterior subcapsular cataracts are a late effect after acute exposure to 0.5 Gy ionizing radiation in mice.

PURPOSE: The long-term effect of low and moderate doses of ionizing radiation on the lens is still a matter of debate and needs to be evaluated in more detail. MATERIAL AND METHODS: We conducted a detailed histological analysis of eyes from B6C3F1 mice cohorts after acute gamma irradiation (60Co source; 0.063 Gy/min) at young adult age of 10 weeks with doses of 0.063, 0.125, and 0.5 Gy. Sham irradiated (0 Gy) mice were used as controls. To test for genetic susceptibility heterozygous Ercc2 mutant mice were used and compared to wild-type mice of the same strain background. Mice of both sexes were included in all cohorts. Eyes were collected 4 h, 12, 18 and 24 months after irradiation. For a better understanding of the underlying mechanisms, metabolomics analyses were performed in lenses and plasma samples of the same mouse cohorts at 4 and 12 h as well as 12, 18 and 24 months after irradiation. For this purpose, a targeted analysis was chosen. RESULTS: This analysis revealed histological changes particularly in the posterior part of the lens that rarely can be observed by using Scheimpflug imaging, as we reported previously. We detected a significant increase of posterior subcapsular cataracts (PSCs) 18 and 24 months after irradiation with 0.5 Gy (odds ratio 9.3; 95% confidence interval 2.1-41.3) independent of sex and genotype. Doses below 0.5 Gy (i.e. 0.063 and 0.125 Gy) did not significantly increase the frequency of PSCs at any time point. In lenses, we observed a clear effect of sex and aging but not of irradiation or genotype. While metabolomics analyses of plasma from the same mice showed only a sex effect. CONCLUSIONS: This article demonstrates a significant radiation-induced increase in the incidence of PSCs, which could not be identified using Scheimpflug imaging as the only diagnostic tool.

Targeted Metabolomics as a Tool in Discriminating Endocrine From Primary Hypertension.

CONTEXT: Identification of patients with endocrine forms of hypertension (EHT) (primary hyperaldosteronism [PA], pheochromocytoma/paraganglioma [PPGL], and Cushing syndrome [CS]) provides the basis to implement individualized therapeutic strategies. Targeted metabolomics (TM) have revealed promising results in profiling cardiovascular diseases and endocrine conditions associated with hypertension. OBJECTIVE: Use TM to identify distinct metabolic patterns between primary hypertension (PHT) and EHT and test its discriminating ability. METHODS: Retrospective analyses of PHT and EHT patients from a European multicenter study (ENSAT-HT). TM was performed on stored blood samples using liquid chromatography mass spectrometry. To identify discriminating metabolites a "classical approach" (CA) (performing a series of univariate and multivariate analyses) and a "machine learning approach" (MLA) (using random forest) were used.The study included 282 adult patients (52% female; mean age 49 years) with proven PHT (n = 59) and EHT (n = 223 with 40 CS, 107 PA, and 76 PPGL), respectively. RESULTS: From 155 metabolites eligible for statistical analyses, 31 were identified discriminating between PHT and EHT using the CA and 27 using the MLA, of which 16 metabolites (C9, C16, C16:1, C18:1, C18:2, arginine, aspartate, glutamate, ornithine, spermidine, lysoPCaC16:0, lysoPCaC20:4, lysoPCaC24:0, PCaeC42:0, SM C18:1, SM C20:2) were found by both approaches. The receiver operating characteristic curve built on the top 15 metabolites from the CA provided an area under the curve (AUC) of 0.86, which was similar to the performance of the 15 metabolites from MLA (AUC 0.83). CONCLUSION: TM identifies distinct metabolic pattern between PHT and EHT providing promising discriminating performance.

Inflammatory macrophage memory in nonsteroidal anti-inflammatory drug-exacerbated respiratory disease.

BACKGROUND: Nonsteroidal anti-inflammatory drug-exacerbated respiratory disease (N-ERD) is a chronic inflammatory condition, which is driven by an aberrant arachidonic acid metabolism. Macrophages are major producers of arachidonic acid metabolites and subject to metabolic reprogramming, but they have been neglected in N-ERD. OBJECTIVE: This study sought to elucidate a potential metabolic and epigenetic macrophage reprogramming in N-ERD. METHODS: Transcriptional, metabolic, and lipid mediator profiles in macrophages from patients with N-ERD and healthy controls were assessed by RNA sequencing, Seahorse assays, and LC-MS/MS. Metabolites in nasal lining fluid, sputum, and plasma from patients with N-ERD (n = 15) and healthy individuals (n = 10) were quantified by targeted metabolomics analyses. Genome-wide methylomics were deployed to define epigenetic mechanisms of macrophage reprogramming in N-ERD. RESULTS: This study shows that N-ERD monocytes/macrophages exhibit an overall reduction in DNA methylation, aberrant metabolic profiles, and an increased expression of chemokines, indicative of a persistent proinflammatory activation. Differentially methylated regions in N-ERD macrophages included genes involved in chemokine signaling and acylcarnitine metabolism. Acylcarnitines were increased in macrophages, sputum, nasal lining fluid, and plasma of patients with N-ERD. On inflammatory challenge, N-ERD macrophages produced increased levels of acylcarnitines, proinflammatory arachidonic acid metabolites, cytokines, and chemokines as compared to healthy macrophages. CONCLUSIONS: Together, these findings decipher a proinflammatory metabolic and epigenetic reprogramming of macrophages in N-ERD.

Mendelian Randomization Study on Amino Acid Metabolism Suggests Tyrosine as Causal Trait for Type 2 Diabetes.

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.

Physiological relevance of the neuronal isoform of inositol-1,4,5-trisphosphate 3-kinases in mice.

Inositol-1,4,5-trisphosphate 3-kinase-A (ITPKA) is the neuronal isoform of ITPKs and exhibits both actin bundling and InsP3kinase activity. In addition to neurons, ITPKA is ectopically expressed in tumor cells, where its oncogenic activity increases tumor cell malignancy. In order to analyze the physiological relevance of ITPKA, here we performed a broad phenotypic screening of itpka deficient mice. Our data show that among the neurobehavioral tests analyzed, itpka deficient mice reacted faster to a hotplate, prepulse inhibition was impaired and the accelerating rotarod test showed decreased latency of itpka deficient mice to fall. These data indicate that ITPKA is involved in the regulation of nociceptive pathways, sensorimotor gating and motor learning. Analysis of extracerebral functions in control and itpka deficient mice revealed significantly reduced glucose, lactate, and triglyceride plasma concentrations in itpka deficient mice. Based on this finding, expression of ITPKA was analyzed in extracerebral tissues and the highest level was found in the small intestine. However, functional studies on CaCo-2 control and ITPKA depleted cells showed that glucose, as well as triglyceride uptake, were not significantly different between the cell lines. Altogether, these data show that ITPKA exhibits distinct functions in the central nervous system and reveal an involvement of ITPKA in energy metabolism.

Impact of maternal smoking associated lyso-phosphatidylcholine 20:3 on offspring brain development.

Maternal smoking during pregnancy affects fetal neurological development. Metabolomic studies in the general population suggest that smoking is associated with characteristic metabolic alterations. We investigated the association between the maternal smoking status, the fetal metabolome and head circumference at birth, as a surrogate parameter of brain development. 320 mother/newborn pairs of the Berlin Birth Cohort were investigated. Anthropometric parameters, including head circumference, of newborns of smoking mothers, former smoking mothers, and never smoking mothers were compared to assess the impact of maternal smoking behavior. Associations between maternal smoking behavior and 163 cord blood metabolites and associations between newborn head circumference and concentrations of smoking behavior related metabolites were analysed. Male newborns of smoking mothers had a reduced head circumference when compared with newborns from former smoking and never smoking mothers (p < 0.05). Using linear regression models corrected for established confounding factors, maternal smoking during pregnancy showed an independent association with head circumference (95% CI: -0.75～-0.41 cm, p = 2.45×10-11). In a stepwise linear regression model corrected for known confounding factors of brain growth lyso-phosphatidylcholine 20:3 (95% CI: 6.68～39.88 cm, p = 4.62×10-4) was associated with head circumference in male offspring only. None of the metabolites were associated with head circumference of female newborns. In conclusion, maternal smoking during pregnancy impacted on male offspring's development including brain development. The smoking related metabolite lyso-phosphatidylcholine 20:3 was associated with head circumference of male offspring.

Metabolic impact of pheochromocytoma/paraganglioma: targeted metabolomics in patients before and after tumor removal.

OBJECTIVE: Excess catecholamine release by pheochromocytomas and paragangliomas (PPGL) leads to characteristic clinical features and increased morbidity and mortality. The influence of PPGLs on metabolism is ill described but may impact diagnosis and management. The objective of this study was to systematically and quantitatively study PPGL-induced metabolic changes at a systems level. DESIGN: Targeted metabolomics by liquid chromatography-tandem mass spectrometry of plasma specimens in a clinically well-characterized prospective cohort study. METHODS: Analyses of metabolic profiles of plasma specimens from 56 prospectively enrolled and clinically well-characterized patients (23 males, 33 females) with catecholamine-producing PPGL before and after surgery, as well as measurement of 24-h urinary catecholamine using LC-MS/MS. RESULTS: From 127 analyzed metabolites, 15 were identified with significant changes before and after surgery: five amino acids/biogenic amines (creatinine, histidine, ornithine, sarcosine, tyrosine) and one glycerophospholipid (PCaeC34:2) with increased concentrations and six glycerophospholipids (PCaaC38:1, PCaaC42:0, PCaeC40:2, PCaeC42:5, PCaeC44:5, PCaeC44:6), two sphingomyelins (SMC24:1, SMC26:1) and hexose with decreased levels after surgery. Patients with a noradrenergic tumor phenotype had more pronounced alterations compared to those with an adrenergic tumor phenotype. Weak, but significant correlations for 8 of these 15 metabolites with total urine catecholamine levels were identified. CONCLUSIONS: This first large prospective metabolomics analysis of PPGL patients demonstrates broad metabolic consequences of catecholamine excess. Robust impact on lipid and amino acid metabolism may contribute to increased morbidity of PPGL patients.

Ageing Investigation Using Two-Time-Point Metabolomics Data from KORA and CARLA Studies.

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.

Neutral endopeptidase inhibitors blunt kidney fibrosis by reducing myofibroblast formation.

Kidney fibrosis is the common pathophysiological mechanism in end-stage renal disease characterized by excessive accumulation of myofibroblast-derived extracellular matrix. Natriuretic peptides have been demonstrated to have cyclic guanosine monophosphate (cGMP)-dependent anti-fibrotic properties likely due to interference with pro-fibrotic tissue growth factor ß (TGF-ß) signaling. However, in vivo, natriuretic peptides are rapidly degraded by neutral endopeptidases (NEP). In a unilateral ureteral obstruction (UUO) mouse model for kidney fibrosis we assessed the anti-fibrotic effects of SOL1, an orally active compound that inhibits NEP and endothelin-converting enzyme (ECE). Mice (n=10 per group) subjected to UUO were treated for 1 week with either solvent, NEP-/ECE-inhibitor SOL1 (two doses), reference NEP-inhibitor candoxatril or the angiotensin II receptor type 1 (AT1)-antagonist losartan. While NEP-inhibitors had no significant effect on blood pressure, they did increase urinary cGMP levels as well as endothelin-1 (ET-1) levels. Immunohistochemical staining revealed a marked decrease in renal collagen (∼55% reduction, P<0.05) and α-smooth muscle actin (α-SMA; ∼40% reduction, P<0.05). Moreover, the number of α-SMA positive cells in the kidneys of SOL1-treated groups inversely correlated with cGMP levels consistent with a NEP-dependent anti-fibrotic effect. To dissect the molecular mechanisms associated with the anti-fibrotic effects of NEP inhibition, we performed a 'deep serial analysis of gene expression (Deep SAGE)' transcriptome and targeted metabolomics analysis of total kidneys of all treatment groups. Pathway analyses linked increased cGMP and ET-1 levels with decreased nuclear receptor signaling (peroxisome proliferator-activated receptor [PPAR] and liver X receptor/retinoid X receptor [LXR/RXR] signaling) and actin cytoskeleton organization. Taken together, although our transcriptome and metabolome data indicate metabolic dysregulation, our data support the therapeutic potential of NEP inhibition in the treatment of kidney fibrosis via cGMP elevation and reduced myofibroblast formation.