Publications

959 Publications visible to you, out of a total of 959

Abstract (Expand)

AIMS Adipose tissue-secreted proteins, i.e. adipocytokines, have been identified as potential mediators linking fat mass and adipose tissue dysfunction with impaired glucose homeostasis, alterationss in the inflammatory status, and risk of diabetes. The aim of this study was to determine whether seven circulating adipocytokines are associated with gestational diabetes mellitus (GDM) or are altered by metabolic and weight changes during pregnancy itself. METHODS A panel of seven adipocytokines (i.e. adiponectin, adipocyte fatty acid-binding protein, chemerin, leptin, Pro-Enkephalin, progranulin, and Pro-Neurotensin) was quantified in serum in a cross-sectional cohort of 222 women with the following three groups matched for age and body mass index: (i) 74 pregnant women with GDM; (ii) 74 pregnant women without GDM; and (iii) 74 non-pregnant and healthy women. A stepwise statistical approach was used by performing pairwise comparisons, principal component analysis (PCA), and partial least square discriminant analysis (PLS-DA). RESULTS Five out of seven adipocytokines were dysregulated between pregnant and non-pregnant women, i.e. adiponectin, chemerin, leptin, Pro-Enkephalin, and progranulin. None of the adipocytokines significantly differed between GDM and non-GDM status during pregnancy. The same five adipocytokines clustered in a principal component representing pregnancy-induced effects. Fasting insulin was the most relevant parameter in the discrimination of GDM as compared to pregnant women without GDM, whereas chemerin and adiponectin were most relevant factors to discriminate pregnancy status. CONCLUSIONS Pregnancy status but not presence of GDM can be distinguished by the seven investigated adipocytokines in discrimination analyses.

Authors: Thomas Ebert, Claudia Gebhardt, Markus Scholz, Dorit Schleinitz, Matthias Blüher, Michael Stumvoll, Peter Kovacs, Mathias Fasshauer, Anke Tönjes

Date Published: 10th Apr 2020

Publication Type: Journal article

Abstract (Expand)

BACKGROUND Changes in the metabolic fingerprint of blood during child growth and development are a largely under-investigated area of research. The examination of such aspects requires a cohort off healthy children and adolescents who have been subjected to deep phenotyping, including collection of biospecimens for metabolomic analysis. The present study considered whether amino acid (AA) and acylcarnitine (AC) concentrations are associated with age, sex, body mass index (BMI), and puberty during childhood and adolescence. It also investigated whether there are associations between amino acids (AAs) and acylcarnitines (ACs) and laboratory parameters of glucose and lipid metabolism, as well as liver, kidney, and thyroid parameters. METHODS A total of 3989 dried whole blood samples collected from 2191 healthy participants, aged 3 months to 18 years, from the LIFE Child cohort (Leipzig, Germany) were analyzed using liquid chromatography tandem mass spectrometry to detect levels of 23 AAs, 6 ACs, and free carnitine (C0). Age- and sex-related percentiles were estimated for each metabolite. In addition, correlations between laboratory parameters and levels of the selected AAs and ACs were calculated using hierarchical models. RESULTS Four different age-dependent profile types were identified for AAs and ACs. Investigating the association with puberty, we mainly identified peak metabolite levels at Tanner stages 2 to 3 in girls and stages 3 to 5 in boys. Significant correlations were observed between BMI standard deviation score (BMI-SDS) and certain metabolites, among them, branched-chain (leucine/isoleucine, valine) and aromatic (phenylalanine, tyrosine) amino acids. Most of the metabolites correlated significantly with absolute concentrations of glucose, glycated hemoglobin (HbA1c), triglycerides, cystatin C (CysC), and creatinine. After age adjustment, significant correlations were observed between most metabolites and CysC, as well as HbA1c. CONCLUSIONS During childhood, several AA and AC levels are related to age, sex, BMI, and puberty. Moreover, our data verified known associations but also revealed new correlations between AAs/ACs and specific key markers of metabolic function.

Authors: Josephin Hirschel, Mandy Vogel, Ronny Baber, Antje Garten, Carl Beuchel, Yvonne Dietz, Julia Dittrich, Antje Körner, Wieland Kiess, Uta Ceglarek

Date Published: 1st Apr 2020

Publication Type: Journal article

Abstract (Expand)

Body shape and composition are heterogeneous among humans with possible impact for health. Anthropometric methods and data are needed to better describe the diversity of the human body in human populations, its age dependence, and associations with health risk. We applied whole-body laser scanning to a cohort of 8499 women and men of age 40-80 years within the frame of the LIFE (Leipzig Research Center for Civilization Diseases) study aimed at discovering health risk in a middle European urban population. Body scanning delivers multidimensional anthropometric data, which were further processed by machine learning to stratify the participants into body types. We here applied this body typing concept to describe the diversity of body shapes in an aging population and its association with physical activity and selected health and lifestyle factors. We find that aging results in similar reshaping of female and male bodies despite the large diversity of body types observed in the study. Slim body shapes remain slim and partly tend to become even more lean and fragile, while obese body shapes remain obese. Female body shapes change more strongly than male ones. The incidence of the different body types changes with characteristic Life Course trajectories. Physical activity is inversely related to the body mass index and decreases with age, while self-reported incidence for myocardial infarction shows overall the inverse trend. We discuss health risks factors in the context of body shape and its relation to obesity. Body typing opens options for personalized anthropometry to better estimate health risk in epidemiological research and future clinical applications.

Authors: A. Frenzel, H. Binder, N. Walter, K. Wirkner, M. Loeffler, H. Loeffler-Wirth

Date Published: 29th Mar 2020

Publication Type: Not specified

Abstract (Expand)

A large set of IHC stained DLBCL specimens is provided together with segmentation masks for different cell populations generated by a reference method for automated image analysis, thus featuring considerable reuse potential. Provided image data comprise a) fluorescence microscopy images of 44 multiple immunohistostained DLBCL tumor subregions, captured at four channels corresponding to CD14, CD163, Pax5 and DAPI; b) cartoon-filtered versions of these images, generated by Rudin-Osher-Fatemi (ROF) denoising; c) an automatically generated mask of the evaluation subregion, based on information from the DAPI channel, and d) automatically generated segmentation masks for macrophages, B-cells and the total of cell nuclei, using information from CD14, CD163, Pax5 and DAPI channels, respectively.

Authors: Marcus Wagner, Sarah Reinke, René Hänsel, Wolfram Klapper, Ulf-Dietrich Braumann

Date Published: 12th Mar 2020

Publication Type: Journal article

Human Diseases: diffuse large B-cell lymphoma

Abstract (Expand)

PURPOSE To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germlinee PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 \times 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 \times 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 \times 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 \times 10-2). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 \times 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer risk management of PALB2 PV carriers.

Authors: Xin Yang, Goska Leslie, Alicja Doroszuk, Sandra Schneider, Jamie Allen, Brennan Decker, Alison M. Dunning, James Redman, James Scarth, Inga Plaskocinska, Craig Luccarini, Mitul Shah, Karen Pooley, Leila Dorling, Andrew Lee, Muriel A. Adank, Julian Adlard, Kristiina Aittomäki, Irene L. Andrulis, Peter Ang, Julian Barwell, Jonine L. Bernstein, Kristie Bobolis, Åke Borg, Carl Blomqvist, Kathleen B. M. Claes, Patrick Concannon, Adeline Cuggia, Julie O. Culver, Francesca Damiola, Antoine de Pauw, Orland Diez, Jill S. Dolinsky, Susan M. Domchek, Christoph Engel, D. Gareth Evans, Florentia Fostira, Judy Garber, Lisa Golmard, Ellen L. Goode, Stephen B. Gruber, Eric Hahnen, Christopher Hake, Tuomas Heikkinen, Judith E. Hurley, Ramunas Janavicius, Zdenek Kleibl, Petra Kleiblova, Irene Konstantopoulou, Anders Kvist, Holly Laduca, Ann S. G. Lee, Fabienne Lesueur, Eamonn R. Maher, Arto Mannermaa, Siranoush Manoukian, Rachel McFarland, Wendy McKinnon, Alfons Meindl, Kelly Metcalfe, Nur Aishah Mohd Taib, Jukka Moilanen, Katherine L. Nathanson, Susan Neuhausen, Pei Sze Ng, Tu Nguyen-Dumont, Sarah M. Nielsen, Florian Obermair, Kenneth Offit, Olufunmilayo I. Olopade, Laura Ottini, Judith Penkert, Katri Pylkäs, Paolo Radice, Susan J. Ramus, Vilius Rudaitis, Lucy Side, Rachel Silva-Smith, Valentina Silvestri, Anne-Bine Skytte, Thomas Slavin, Jana Soukupova, Carlo Tondini, Alison H. Trainer, Gary Unzeitig, Lydia Usha, Thomas van Overeem Hansen, James Whitworth, Marie Wood, Cheng Har Yip, Sook-Yee Yoon, Amal Yussuf, George Zogopoulos, David Goldgar, John L. Hopper, Georgia Chenevix-Trench, Paul Pharoah, Sophia H. L. George, Judith Balmaña, Claude Houdayer, Paul James, Zaki El-Haffaf, Hans Ehrencrona, Marketa Janatova, Paolo Peterlongo, Heli Nevanlinna, Rita Schmutzler, Soo-Hwang Teo, Mark Robson, Tuya Pal, Fergus Couch, Jeffrey N. Weitzel, Aaron Elliott, Melissa Southey, Robert Winqvist, Douglas F. Easton, William D. Foulkes, Antonis C. Antoniou, Marc Tischkowitz

Date Published: 1st Mar 2020

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Abstract (Expand)

Background: Patients with cardiac complaints but without confirmed diagnosis of coronary heart disease by angiography frequently develop cardiac events in the following years. This follow-up study investigated the frequency of cardiac symptoms and cardiovascular events (CVE) 5 years after initial angiography of patients with nonobstructive coronary artery disease (NobCAD, LIFE Heart study), with the aim to identify gender-specific indicators for CVE. Methods: In 2014/2015, 1462 women and men with NobCAD, defined as no or non-relevant obstructive coronary artery disease were identified among 2660 subjects participating in the observational angiographic LIFE Heart study. Questionnaires of 820 responding patients were analyzed. Results: The median observation time was 55 months. Cardiac symptoms were found in 53.6% of all patients, significantly more often in women than in men (59.4% vs. 48.8%; p = 0.002). CVE occurred in 46.1% of all participants (n = 378/820). Patients with cardiac symptoms had a 2.94 time higher risk for CVE than those without cardiac symptoms (p \textless 0.001). Men with no cardiac symptoms had significantly more CVE (p = 0.042) than women. Common risk factors for CVE comprised cardiac symptoms, atrial fibrillation, and age. Sex-specific risk factors comprised body mass index (BMI) \geq25 kg/m2 for women and anxiety for men. Conclusions: Patients with cardiac symptoms have about three times higher risk for CVE within 5 years than patients without cardiac symptoms. Sex differences exist in patients without symptoms where men were at higher risk for CVE. Atrial fibrillation was the strongest indicator for CVE, whereas anxiety was an indicator only in men and BMI \geq25 kg/m2 only in women, suggesting sex- and gender-specific phenotypic profiles.

Authors: Ahmad T. Nauman, Andrej Teren, Samira Zeynalova, Joachim Thiery, Vera Regitz-Zagrosek, Markus Scholz, Ute Seeland

Date Published: 1st Mar 2020

Publication Type: Journal article

Abstract (Expand)

A combined OMICS screening approach of human plasma and serum was used to characterize protein and metabolome signatures displaying association to severity of Community-acquired pneumonia (CAP). 240 serum and BD P100 EDTA plasma samples from patients diagnosed with CAP, collected during the day of enrolment to the hospital, were analyzed by a metabolomic and proteomic approach, respectively. Disease severity of CAP patients was stratified using the Sequential Organ Failure Assessment (SOFA) score. Quantitative proteome and metabolome data, derived by LC-MS/MS, were associated to SOFA and specific parameters of SOFA using linear regression models adjusted for age, BMI, sex, smoking and technical variables. Both proteome and metabolome profiling revealed remarkable strong changes in plasma and serum composition in relation to severity of CAP. Proteins and metabolites displaying SOFA associated levels are involved in immune response, particularly in processes of lipid metabolism. Proteins, which show an association to SOFA score, are involved in acute phase response, coagulation, complement activation and inflammation. Many of these metabolites and proteins displayed not only associations to SOFA, but also to parameters of SOFA score, which likely reflect the strong influence of lung-, liver-, kidney- and heart-dysfunction on the metabolome and proteome patterns. SIGNIFICANCE: Community-acquired pneumonia is the most frequent infection disease with high morbidity and mortality. So far, only few studies focused on the identification of proteins or metabolites associated to severity of CAP, often based on smaller sample sets. A screening for new diagnostic markers requires extensive sample collections in combination with high quality clinical data. To characterize the proteomic and metabolomics pattern associated to severity of CAP we performed a combined metabolomics and proteomic approach of serum and plasma sample from a multi-center clinical study focused on patients with CAP, requiring hospitalization. The results of this association study of omics data to the SOFA score enable not only an interpretation of changes in molecular patterns with severity of CAP but also an assignment of altered molecules to dysfunctions of respiratory, renal, coagulation, cardiovascular systems as well as liver.

Authors: Manuela Gesell Salazar, Sophie Neugebauer, Tim Kacprowski, Stephan Michalik, Peter Ahnert, Petra Creutz, Maciej Rosolowski, Markus Löffler, Michael Bauer, Norbert Suttorp, Michael Kiehntopf, Uwe Völker

Date Published: 1st Mar 2020

Publication Type: Journal article

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