Publications by authors named "Jerzy Adamski"

338 Publications

Non-targeted metabolomics identify polyamine metabolite acisoga as novel biomarker for reduced left ventricular function.

ESC Heart Fail 2021 Nov 22. Epub 2021 Nov 22.

Department of Internal Medicine 1, University Hospital Aachen, RWTH Aachen University, Aachen, Germany.

Aims: Chronic heart failure with reduced ejection fraction remains a major health issue. To date, no reliable biomarker is available to predict reduced left ventricular ejection fraction (LV-EF). We aimed to identify novel circulating biomarkers for reduced left ventricular function using untargeted serum metabolomics in two independent patient cohorts.

Methods And Results: Echocardiography and non-targeted serum metabolomics were conducted in two patient cohorts with varying left ventricular function: (1) 25 patients with type 2 diabetes with established cardiovascular disease or high cardiovascular risk (LV-EF range 20-66%) (discovery cohort) and (2) 37 patients hospitalized for myocardial infarction (LV-EF range 25-60%) (validation cohort). In the discovery cohort, untargeted metabolomics revealed seven metabolites performing better than N-terminal pro-B-type natriuretic peptide in the prediction of impaired left ventricular function shown by LV-EF. For only one of the metabolites, acisoga, the predictive value for LV-EF could be confirmed in the validation cohort (r = -0.37, P = 0.02). In the discovery cohort, acisoga did not only correlate with LV-EF (r = -60, P = 0.0016), but also with global circumferential strain (r = 0.67, P = 0.0003) and global longitudinal strain (r = 0.68, P = 0.0002). Similar results could be detected in the discovery cohort in a 6 month follow-up proofing stability of these results over time. With an area under the curve of 0.86 in the receiver operating characteristic analysis, acisoga discriminated between patients with normal EF and LV-EF < 40%. Multivariate analysis exposed acisoga as independent marker for impairment of LV-EF (Beta = -0.71, P = 0.004).

Conclusions: We found the polyamine metabolite acisoga to be elevated in patients with impaired LV-EF in two independent cohorts. Our analyses suggest that acisoga may be a valuable biomarker to detect patients with heart failure with reduced ejection fraction.
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http://dx.doi.org/10.1002/ehf2.13713DOI Listing
November 2021

The Effect of Dietary Protein Imbalance during Pregnancy on the Growth, Metabolism and Circulatory Metabolome of Neonatal and Weaned Juvenile Porcine Offspring.

Nutrients 2021 Sep 20;13(9). Epub 2021 Sep 20.

Institute of Nutritional Physiology 'Oskar Kellner', Research Institute for Farm Animal Biology (FBN), 18196 Dummerstorf, Germany.

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.
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http://dx.doi.org/10.3390/nu13093286DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8471113PMC
September 2021

Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors.

Front Endocrinol (Lausanne) 2021 7;12:722656. Epub 2021 Sep 7.

Department of Internal Medicine I, Division of Endocrinology and Diabetes, University Hospital, University of Würzburg, Würzburg, Germany.

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.
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http://dx.doi.org/10.3389/fendo.2021.722656DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453166PMC
September 2021

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

PLoS Med 2021 09 20;18(9):e1003786. Epub 2021 Sep 20.

Nutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France.

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.
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http://dx.doi.org/10.1371/journal.pmed.1003786DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496779PMC
September 2021

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

Endocrine 2021 Sep 18. Epub 2021 Sep 18.

Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.

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.
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http://dx.doi.org/10.1007/s12020-021-02858-zDOI Listing
September 2021

Common Muscle Metabolic Signatures Highlight Arginine and Lysine Metabolism as Potential Therapeutic Targets to Combat Unhealthy Aging.

Int J Mol Sci 2021 Jul 26;22(15). Epub 2021 Jul 26.

Institute for Diabetes and Cancer, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany.

Biological aging research is expected to reveal modifiable molecular mechanisms that can be harnessed to slow or possibly reverse unhealthy trajectories. However, there is first an urgent need to define consensus molecular markers of healthy and unhealthy aging. Established aging hallmarks are all linked to metabolism, and a 'rewired' metabolic circuitry has been shown to accelerate or delay biological aging. To identify metabolic signatures distinguishing healthy from unhealthy aging trajectories, we performed nontargeted metabolomics on skeletal muscles from 2-month-old and 21-month-old mice, and after dietary and lifestyle interventions known to impact biological aging. We hypothesized that common metabolic signatures would highlight specific pathways and processes promoting healthy aging, while revealing the molecular underpinnings of unhealthy aging. Here, we report 50 metabolites that commonly distinguished aging trajectories in all cohorts, including 18 commonly reduced under unhealthy aging and 32 increased. We stratified these metabolites according to known relationships with various aging hallmarks and found the greatest associations with oxidative stress and nutrient sensing. Collectively, our data suggest interventions aimed at maintaining skeletal muscle arginine and lysine may be useful therapeutic strategies to minimize biological aging and maintain skeletal muscle health, function, and regenerative capacity in old age.
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http://dx.doi.org/10.3390/ijms22157958DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8348621PMC
July 2021

Correlation guided Network Integration (CoNI) reveals novel genes affecting hepatic metabolism.

Mol Metab 2021 Nov 13;53:101295. Epub 2021 Jul 13.

Computational Discovery Research Unit, Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany; Institute for Diabetes and Obesity, Helmholtz Diabetes Center at Helmholtz Zentrum München, Germany. Electronic address:

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.
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http://dx.doi.org/10.1016/j.molmet.2021.101295DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8361260PMC
November 2021

Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study.

Diabetes 2021 09 7;70(9):2092-2106. Epub 2021 Jul 7.

Department of Epidemiology and Data Science, Amsterdam Medical Centre, location VUMC, Amsterdam, the Netherlands.

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants ( = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISR), and insulin secretion potentiation ( < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISR ( < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.
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http://dx.doi.org/10.2337/db21-0227DOI Listing
September 2021

Physiological extremes of the human blood metabolome: A metabolomics analysis of highly glycolytic, oxidative, and anabolic athletes.

Physiol Rep 2021 06;9(12):e14885

Exercise Biology, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.

Human metabolism is highly variable. At one end of the spectrum, defects of enzymes, transporters, and metabolic regulation result in metabolic diseases such as diabetes mellitus or inborn errors of metabolism. At the other end of the spectrum, favorable genetics and years of training combine to result in physiologically extreme forms of metabolism in athletes. Here, we investigated how the highly glycolytic metabolism of sprinters, highly oxidative metabolism of endurance athletes, and highly anabolic metabolism of natural bodybuilders affect their serum metabolome at rest and after a bout of exercise to exhaustion. We used targeted mass spectrometry-based metabolomics to measure the serum concentrations of 151 metabolites and 43 metabolite ratios or sums in 15 competitive male athletes (6 endurance athletes, 5 sprinters, and 4 natural bodybuilders) and 4 untrained control subjects at fasted rest and 5 minutes after a maximum graded bicycle test to exhaustion. The analysis of all 194 metabolite concentrations, ratios and sums revealed that natural bodybuilders and endurance athletes had overall different metabolite profiles, whereas sprinters and untrained controls were more similar. Specifically, natural bodybuilders had 1.5 to 1.8-fold higher concentrations of specific phosphatidylcholines and lower levels of branched chain amino acids than all other subjects. Endurance athletes had 1.4-fold higher levels of a metabolite ratio showing the activity of carnitine-palmitoyl-transferase I and 1.4-fold lower levels of various alkyl-acyl-phosphatidylcholines. When we compared the effect of exercise between groups, endurance athletes showed 1.3-fold higher increases of hexose and of tetradecenoylcarnitine (C14:1). In summary, physiologically extreme metabolic capacities of endurance athletes and natural bodybuilders are associated with unique blood metabolite concentrations, ratios, and sums at rest and after exercise. Our results suggest that long-term specific training, along with genetics and other athlete-specific factors systematically change metabolite concentrations at rest and after exercise.
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http://dx.doi.org/10.14814/phy2.14885DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8215680PMC
June 2021

DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function.

Clin Epigenetics 2021 06 2;13(1):121. Epub 2021 Jun 2.

Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.

Background: The difference between an individual's chronological and DNA methylation predicted age (DNAmAge), termed DNAmAge acceleration (DNAmAA), can capture life-long environmental exposures and age-related physiological changes reflected in methylation status. Several studies have linked DNAmAA to morbidity and mortality, yet its relationship with kidney function has not been assessed. We evaluated the associations between seven DNAm aging and lifespan predictors (as well as GrimAge components) and five kidney traits (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [uACR], serum urate, microalbuminuria and chronic kidney disease [CKD]) in up to 9688 European, African American and Hispanic/Latino individuals from seven population-based studies.

Results: We identified 23 significant associations in our large trans-ethnic meta-analysis (p < 1.43E-03 and consistent direction of effect across studies). Age acceleration measured by the Extrinsic and PhenoAge estimators, as well as Zhang's 10-CpG epigenetic mortality risk score (MRS), were associated with all parameters of poor kidney health (lower eGFR, prevalent CKD, higher uACR, microalbuminuria and higher serum urate). Six of these associations were independently observed in European and African American populations. MRS in particular was consistently associated with eGFR (β =  - 0.12, 95% CI = [- 0.16, - 0.08] change in log-transformed eGFR per unit increase in MRS, p = 4.39E-08), prevalent CKD (odds ratio (OR) = 1.78 [1.47, 2.16], p = 2.71E-09) and higher serum urate levels (β = 0.12 [0.07, 0.16], p = 2.08E-06). The "first-generation" clocks (Hannum, Horvath) and GrimAge showed different patterns of association with the kidney traits. Three of the DNAm-estimated components of GrimAge, namely adrenomedullin, plasminogen-activation inhibition 1 and pack years, were positively associated with higher uACR, serum urate and microalbuminuria.

Conclusion: DNAmAge acceleration and DNAm mortality predictors estimated in whole blood were associated with multiple kidney traits, including eGFR and CKD, in this multi-ethnic study. Epigenetic biomarkers which reflect the systemic effects of age-related mechanisms such as immunosenescence, inflammaging and oxidative stress may have important mechanistic or prognostic roles in kidney disease. Our study highlights new findings linking kidney disease to biological aging, and opportunities warranting future investigation into DNA methylation biomarkers for prognostic or risk stratification in kidney disease.
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http://dx.doi.org/10.1186/s13148-021-01082-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170969PMC
June 2021

Fibroblast growth factor induced Ucp1 expression in preadipocytes requires PGE2 biosynthesis and glycolytic flux.

FASEB J 2021 05;35(5):e21572

Department of Molecular Nutritional Medicine, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.

High uncoupling protein 1 (Ucp1) expression is a characteristic of differentiated brown adipocytes and is linked to adipogenic differentiation. Paracrine fibroblast growth factor 8b (FGF8b) strongly induces Ucp1 transcription in white adipocytes independent of adipogenesis. Here, we report that FGF8b and other paracrine FGFs act on brown and white preadipocytes to upregulate Ucp1 expression via a FGFR1-MEK1/2-ERK1/2 axis, independent of adipogenesis. Transcriptomic analysis revealed an upregulation of prostaglandin biosynthesis and glycolysis upon Fgf8b treatment of preadipocytes. Oxylipin measurement by LC-MS/MS in FGF8b conditioned media identified prostaglandin E as a putative mediator of FGF8b induced Ucp1 transcription. RNA interference and pharmacological inhibition of the prostaglandin E biosynthetic pathway confirmed that PGE2 is causally involved in the control over Ucp1 transcription. Importantly, impairment of or failure to induce glycolytic flux blunted the induction of Ucp1, even in the presence of PGE . Lastly, a screening of transcription factors identified Nrf1 and Hes1 as required regulators of FGF8b induced Ucp1 expression. Thus, we conclude that paracrine FGFs co-regulate prostaglandin and glucose metabolism to induce Ucp1 expression in a Nrf1/Hes1-dependent manner in preadipocytes, revealing a novel regulatory network in control of Ucp1 expression in a formerly unrecognized cell type.
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http://dx.doi.org/10.1096/fj.202002795RDOI Listing
May 2021

Cancer-associated cells release citrate to support tumour metastatic progression.

Life Sci Alliance 2021 06 23;4(6). Epub 2021 Mar 23.

Institute of Pathology, Kaufbeuren-Ravensburg, Kaufbeuren, Germany.

Citrate is important for lipid synthesis and epigenetic regulation in addition to ATP production. We have previously reported that cancer cells import extracellular citrate via the pmCiC transporter to support their metabolism. Here, we show for the first time that citrate is supplied to cancer by cancer-associated stroma (CAS) and also that citrate synthesis and release is one of the latter's major metabolic tasks. Citrate release from CAS is controlled by cancer cells through cross-cellular communication. The availability of citrate from CAS regulated the cytokine profile, metabolism and features of cellular invasion. Moreover, citrate released by CAS is involved in inducing cancer progression especially enhancing invasiveness and organ colonisation. In line with the in vitro observations, we show that depriving cancer cells of citrate using gluconate, a specific inhibitor of pmCiC, significantly reduced the growth and metastatic spread of human pancreatic cancer cells in vivo and muted stromal activation and angiogenesis. We conclude that citrate is supplied to tumour cells by CAS and citrate uptake plays a significant role in cancer metastatic progression.
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http://dx.doi.org/10.26508/lsa.202000903DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994318PMC
June 2021

Functional characterization of two 20β-hydroxysteroid dehydrogenase type 2 homeologs from Xenopus laevis reveals multispecificity.

J Steroid Biochem Mol Biol 2021 06 17;210:105874. Epub 2021 Mar 17.

Helmholtz Zentrum München, German Research Center for Environmental Health, Research Unit Molecular Endocrinology and Metabolism, Neuherberg, Germany; German Center for Diabetes Research, Neuherberg, Germany; Lehrstuhl für Experimentelle Genetik, Technische Universität München, Freising-Weihenstephan, Germany; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.

The African clawed frog, Xenopus laevis, is a versatile model for biomedical research and is largely similar to mammals in terms of organ development, anatomy, physiology, and hormonal signaling mechanisms. Steroid hormones control a variety of processes and their levels are regulated by hydroxysteroid dehydrogenases (HSDs). The subfamily of 20β-HSD type 2 enzymes currently comprises eight members from teleost fish and mammals. Here, we report the identification of three 20β-HSD type 2 genes in X. tropicalis and X. laevis and the functional characterization of the two homeologs from X. laevis. X. laevis Hsd20b2.L and Hsd20b2.S showed high sequence identity with known 20β-HSD type 2 enzymes and mapped to the two subgenomes of the allotetraploid frog genome. Both homeologs are expressed during embryonic development and in adult tissues, with strongest signals in liver, kidney, intestine, and skin. After recombinant expression in human cell lines, both enzymes co-localized with the endoplasmic reticulum and catalyzed the conversion of cortisone to 20β-dihydrocortisone. Both Hsd20b2.L and Hsd20b2.S catalyzed the 20β-reduction of further C steroids (17α-hydroxyprogesterone, progesterone, 11-deoxycortisol, 11-deoxycorticosterone), while only Hsd20b2.S was able to convert corticosterone and cortisol to their 20β-reduced metabolites. Estrone was only a poor and androstenedione no substrate for both enzymes. Our results demonstrate multispecificity of 20β-HSD type 2 enzymes from X. laevis similar to other teleost 20β-HSD type 2 enzymes. X. laevis 20β-HSD type 2 enzymes are probably involved in steroid catabolism and in the generation of pheromones for intraspecies communication. A role in oocyte maturation is unlikely.
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http://dx.doi.org/10.1016/j.jsbmb.2021.105874DOI Listing
June 2021

Potential involvement of extracellular citrate in brain tumor progression.

Curr Mol Med 2021 Mar 2. Epub 2021 Mar 2.

Department of Surgery, University Medical Center Regensburg. Germany.

Brain tissue is known to have elevated citrate levels necessary to regulate ion chelation, neuron excitability, and the supply of necessary energy substrates to neurons. Importantly, citrate also acts as a central substrate in cancer metabolism. Recent studies have shown that extracellular citrate levels in the brain undergo significant changes during tumor development, and may play a dual role in tumor progression, as well as cancer cell aggressiveness. In the present article, we review available literature describing changes of citrate levels in brain tissue, blood, and cerebrospinal fluid, as well as intracellular alterations during tumor development before and after metastatic progression. Based on the available literature and our recent findings, we hypothesize that changes in extracellular citrate levels may be related to the increased consumption of this metabolite by cancer cells; interestingly, cancer-associated cells, including reactive astrocytes, might be a source of citrate. Extracellular citrate uptake mechanisms, as well as potential citrate synthesis and releasing by surrounding stroma, could provide novel targets for anti-cancer treatments of primary brain tumors and brain metastases.
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http://dx.doi.org/10.2174/1566524021666210302143802DOI Listing
March 2021

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

BMJ Open Diabetes Res Care 2021 02;9(1)

Institute of of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, München-Neuherberg, Germany

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 (HbA) (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 HbA (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.
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http://dx.doi.org/10.1136/bmjdrc-2020-001951DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880095PMC
February 2021

Validation of Candidate Phospholipid Biomarkers of Chronic Kidney Disease in Hyperglycemic Individuals and Their Organ-Specific Exploration in Leptin Receptor-Deficient db/db Mouse.

Metabolites 2021 Feb 3;11(2). Epub 2021 Feb 3.

Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.

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.
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http://dx.doi.org/10.3390/metabo11020089DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913334PMC
February 2021

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

Int J Radiat Biol 2021 1;97(4):529-540. Epub 2021 Mar 1.

Institute of Developmental Genetics, Helmholtz Zentrum München GmbH, German Research Center for Environmental Health, Neuherberg, Germany.

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 (Co 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 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.
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http://dx.doi.org/10.1080/09553002.2021.1876951DOI Listing
September 2021

Extracellular Citrate Fuels Cancer Cell Metabolism and Growth.

Front Cell Dev Biol 2020 4;8:602476. Epub 2020 Dec 4.

Department of Surgery, University Medical Center Regensburg, Regensburg, Germany.

Cancer cells need excess energy and essential nutrients/metabolites not only to divide and proliferate but also to migrate and invade distant organs for metastasis. Fatty acid and cholesterol synthesis, considered a hallmark of cancer for anabolism and membrane biogenesis, requires citrate. We review here potential pathways in which citrate is synthesized and/or supplied to cancer cells and the impact of extracellular citrate on cancer cell metabolism and growth. Cancer cells employ different mechanisms to support mitochondrial activity and citrate synthesis when some of the necessary substrates are missing in the extracellular space. We also discuss the different transport mechanisms available for the entry of extracellular citrate into cancer cells and how citrate as a master metabolite enhances ATP production and fuels anabolic pathways. The available literature suggests that cancer cells show an increased metabolic flexibility with which they tackle changing environmental conditions, a phenomenon crucial for cancer cell proliferation and metastasis.
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http://dx.doi.org/10.3389/fcell.2020.602476DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793864PMC
December 2020

Systemic Regulation of Host Energy and Oogenesis by Microbiome-Derived Mitochondrial Coenzymes.

Cell Rep 2021 01;34(1):108583

Department of Biomolecular Sciences, Weizmann Institute of Science, 7670001 Rehovot, Israel.

Gut microbiota have been shown to promote oogenesis and fecundity, but the mechanistic basis of remote influence on oogenesis remained unknown. Here, we report a systemic mechanism of influence mediated by bacterial-derived supply of mitochondrial coenzymes. Removal of microbiota decreased mitochondrial activity and ATP levels in the whole-body and ovary, resulting in repressed oogenesis. Similar repression was caused by RNA-based knockdown of mitochondrial function in ovarian follicle cells. Reduced mitochondrial function in germ-free (GF) females was reversed by bacterial recolonization or supplementation of riboflavin, a precursor of FAD and FMN. Metabolomics analysis of GF females revealed a decrease in oxidative phosphorylation and FAD levels and an increase in metabolites that are degraded by FAD-dependent enzymes (e.g., amino and fatty acids). Riboflavin supplementation opposed this effect, elevating mitochondrial function, ATP, and oogenesis. These findings uncover a bacterial-mitochondrial axis of influence, linking gut bacteria with systemic regulation of host energy and reproduction.
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http://dx.doi.org/10.1016/j.celrep.2020.108583DOI Listing
January 2021

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

J Clin Endocrinol Metab 2021 03;106(4):1111-1128

Klinik für Endokrinologie, Diabetologie und Klinische Ernährung, UniversitätsSpital Zürich, Zurich, Switzerland.

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.
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http://dx.doi.org/10.1210/clinem/dgaa954DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993566PMC
March 2021

Evaluation of Metabolic Profiles of Patients with Anorexia Nervosa at Inpatient Admission, Short- and Long-Term Weight Regain-Descriptive and Pattern Analysis.

Metabolites 2020 Dec 24;11(1). Epub 2020 Dec 24.

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Wickenburgstr. 21, 45147 Essen, Germany.

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 (T), after short-term weight recovery (T; half of target-weight) and close to target weight (T). Pattern hunter and time course analysis were performed. The highest number of significant differences in metabolite concentrations (N = 32) were observed between HC and T. According to the detected main pattern, metabolite concentrations at T 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.
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http://dx.doi.org/10.3390/metabo11010007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7823299PMC
December 2020

Metabolomics for Diagnosis and Prognosis of Uterine Diseases? A Systematic Review.

J Pers Med 2020 Dec 21;10(4). Epub 2020 Dec 21.

Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia.

This systematic review analyses the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases. These diseases are diagnosed invasively, which entails delayed treatment and a worse clinical outcome. New options for diagnosis and prognosis are needed. PubMed, OVID, and Scopus were searched for research papers on metabolomics in physiological fluids and tissues from patients with uterine diseases. The search identified 484 records. Based on inclusion and exclusion criteria, 44 studies were included into the review. Relevant data were extracted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist and quality was assessed using the QUADOMICS tool. The selected metabolomics studies analysed plasma, serum, urine, peritoneal, endometrial, and cervico-vaginal fluid, ectopic/eutopic endometrium, and cervical tissue. In endometriosis, diagnostic models discriminated patients from healthy and infertile controls. In cervical cancer, diagnostic algorithms discriminated patients from controls, patients with good/bad prognosis, and with/without response to chemotherapy. In endometrial cancer, several models stratified patients from controls and recurrent from non-recurrent patients. Metabolomics is valuable for constructing diagnostic models. However, the majority of studies were in the discovery phase and require additional research to select reliable biomarkers for validation and translation into clinical practice. This review identifies bottlenecks that currently prevent the translation of these findings into clinical practice.
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http://dx.doi.org/10.3390/jpm10040294DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7767462PMC
December 2020

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

Nutrients 2020 Dec 19;12(12). Epub 2020 Dec 19.

Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, 14558 Nuthetal, Germany.

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 log-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.
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http://dx.doi.org/10.3390/nu12123890DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766372PMC
December 2020

Intergenerational Metabolomic Analysis of Mothers with a History of Gestational Diabetes Mellitus and Their Offspring.

Int J Mol Sci 2020 Dec 17;21(24). Epub 2020 Dec 17.

Institute of Diabetes Research, Helmholtz Zentrum München, and Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universität München, 85764 Neuherberg, Germany.

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.
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http://dx.doi.org/10.3390/ijms21249647DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766614PMC
December 2020

Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study.

Diabetes Care 2021 02 15;44(2):511-518. Epub 2020 Dec 15.

Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.

Objective: We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D).

Research Design And Methods: A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), β-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression.

Results: Faster HbA progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles ( = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role.

Conclusions: Deteriorating insulin sensitivity and β-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, β-cell function, and insulin clearance may be relevant to prevent progression.
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http://dx.doi.org/10.2337/dc20-1567DOI Listing
February 2021

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

Clin Gastroenterol Hepatol 2020 Dec 29. Epub 2020 Dec 29.

CIBER Epidemiología y Salud Pública, Spain; Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain; Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain.

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.
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http://dx.doi.org/10.1016/j.cgh.2020.11.045DOI Listing
December 2020

The liver-alpha cell axis associates with liver fat and insulin resistance: a validation study in women with non-steatotic liver fat levels.

Diabetologia 2021 03 4;64(3):512-520. Epub 2020 Dec 4.

Diabetes Research Group, Department of Medicine IV, University Hospital, LMU Munich, Munich, Germany.

Aims/hypothesis: Many individuals who develop type 2 diabetes also display increased glucagon levels (hyperglucagonaemia), which we have previously found to be associated with the metabolic syndrome. The concept of a liver-alpha cell axis provides a possible link between hyperglucagonaemia and elevated liver fat content, a typical finding in the metabolic syndrome. However, this association has only been studied in individuals with non-alcoholic fatty liver disease. Hence, we searched for a link between the liver and the alpha cells in individuals with non-steatotic levels of liver fat content. We hypothesised that the glucagon-alanine index, an indicator of the functional integrity of the liver-alpha cell axis, would associate with liver fat and insulin resistance in our cohort of women with low levels of liver fat.

Methods: We analysed data from 79 individuals participating in the Prediction, Prevention and Subclassification of Type 2 Diabetes (PPSDiab) study, a prospective observational study of young women at low to high risk for the development of type 2 diabetes. Liver fat content was determined by MRI. Insulin resistance was calculated as HOMA-IR. We conducted Spearman correlation analyses of liver fat content and HOMA-IR with the glucagon-alanine index (the product of fasting plasma levels of glucagon and alanine). The prediction of the glucagon-alanine index by liver fat or HOMA-IR was tested in multivariate linear regression analyses in the whole cohort as well as after stratification for liver fat content ≤0.5% (n = 39) or >0.5% (n = 40).

Results: The glucagon-alanine index significantly correlated with liver fat and HOMA-IR in the entire cohort (ρ = 0.484, p < 0.001 and ρ = 0.417, p < 0.001, respectively). These associations resulted from significant correlations in participants with a liver fat content >0.5% (liver fat, ρ = 0.550, p < 0.001; HOMA-IR, ρ = 0.429, p = 0.006). In linear regression analyses, the association of the glucagon-alanine index with liver fat remained significant after adjustment for age and HOMA-IR in all participants and in those with liver fat >0.5% (β = 0.246, p = 0.0.23 and β = 0.430, p = 0.007, respectively) but not in participants with liver fat ≤0.5% (β = -0.184, p = 0.286).

Conclusions/interpretation: We reproduced the previously reported association of liver fat content and HOMA-IR with the glucagon-alanine index in an independent study cohort of young women with low to high risk for type 2 diabetes. Furthermore, our data indicates an insulin-resistance-independent association of liver fat content with the glucagon-alanine index. In summary, our study supports the concept that even lower levels of liver fat (from 0.5%) are connected to relative hyperglucagonaemia, reflecting an imminent impairment of the liver-alpha cell axis.
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http://dx.doi.org/10.1007/s00125-020-05334-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864806PMC
March 2021

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

Genome Med 2020 12 1;12(1):109. Epub 2020 Dec 1.

NIHR Exeter Clinical Research Facility, University of Exeter Medical School, Exeter, UK.

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.
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http://dx.doi.org/10.1186/s13073-020-00806-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708171PMC
December 2020

Homology modeling meets site-directed mutagenesis: An ideal combination to elucidate the topology of 17β-HSD2.

J Steroid Biochem Mol Biol 2021 02 24;206:105790. Epub 2020 Nov 24.

Pharmaceutical Chemistry, Philipps University Marburg, Marbacher Weg 6, 35037 Marburg, Germany; Pharmaceutical and Medicinal Chemistry, Saarland University, Campus C2.3, 66123 Saarbrücken, Germany. Electronic address:

17β-Hydroxysteroid dehydrogenase type 2 (17β-HSD2) catalyzes the conversion of highly active estrogens and androgens into their less active forms using NAD as cofactor. Substrate and cofactor specificities of 17β-HSD2 have been reported and potent 17β-HSD2 inhibitors have been discovered in a ligand-based approach. However, the molecular basis and the amino acids involved in the enzymatic functionality are poorly understood, as no crystal structure of the membrane-associated 17β-HSD2 exists. The functional properties of only few amino acids are known. The lack of topological information impedes structure-based drug design studies and limits the design of biochemical experiments. The aim of this work was the determination of the 17β-HSD2 topology. For this, the first homology model of 17β-HSD2 in complex with NAD and 17β-estradiol was built, using a multi-fragment "patchwork" approach. To confirm the quality of the model, fifteen selected amino acids were exchanged one by one using site directed mutagenesis. The mutants' functional behavior demonstrated that the generated model was of very good quality and allowed the identification of several key amino acids involved in either ligand or internal structure stabilization. The final model is an optimal basis for further experiments like, for example, lead optimization.
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http://dx.doi.org/10.1016/j.jsbmb.2020.105790DOI Listing
February 2021
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