Publications

227 Publications visible to you, out of a total of 227

Abstract (Expand)

In the development of cell-based medicinal products, it is crucial to guarantee that the application of such an advanced therapy medicinal product (ATMP) is safe for the patients. The consensus of the European regulatory authorities is: \textquotedblIn conclusion, on the basis of the state of art, conventional karyotyping can be considered a valuable and useful technique to analyse chromosomal stability during preclinical studies\textquotedbl. 408 chondrocyte samples (84 monolayers and 324 spheroids) from six patients were analysed using trypsin-Giemsa staining, spectral karyotyping and fluorescence in situ hybridisation, to evaluate the genetic stability of chondrocyte samples from non-clinical studies. Single nucleotide polymorphism (SNP) array analysis was performed on chondrocyte spheroids from five of the six donors. Applying this combination of techniques, the genetic analyses performed revealed no significant genetic instability until passage 3 in monolayer cells and interphase cells from spheroid cultures at different time points. Clonal occurrence of polyploid metaphases and endoreduplications were identified associated with prolonged cultivation time. Also, gonosomal losses were observed in chondrocyte spheroids, with increasing passage and duration of the differentiation phase. Interestingly, in one of the donors, chromosomal aberrations that are also described in extraskeletal myxoid chondrosarcoma were identified. The SNP array analysis exhibited chromosomal aberrations in two donors and copy neutral losses of heterozygosity regions in four donors. This study showed the necessity of combined genetic analyses at defined cultivation time points in quality studies within the field of cell therapy.

Authors: M. Wallenborn, O. Petters, D. Rudolf, H. Hantmann, M. Richter, P. Ahnert, L. Rohani, J. J. Smink, G. C. Bulwin, W. Krupp, R. M. Schulz, H. Holland

Date Published: 23rd Mar 2018

Publication Type: Journal article

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An increasing number of genetic variants involved in dyslexia development were discovered during the last years, yet little is known about the molecular functional mechanisms of these SNPs. In this study we investigated whether dyslexia candidate SNPs have a direct, disease-specific effect on local expression levels of the assumed target gene by using a differential allelic expression assay. In total, 12 SNPs previously associated with dyslexia and related phenotypes were suitable for analysis. Transcripts corresponding to four SNPs were sufficiently expressed in 28 cell lines originating from controls and a family affected by dyslexia. We observed a significant effect of rs600753 on expression levels of DYX1C1 in forward and reverse sequencing approaches. The expression level of the rs600753 risk allele was increased in the respective seven cell lines from members of the dyslexia family which might be due to a disturbed transcription factor binding sites. When considering our results in the context of neuroanatomical dyslexia-specific findings, we speculate that this mechanism may be part of the pathomechanisms underlying the dyslexia-specific brain phenotype. Our results suggest that allele-specific DYX1C1 expression levels depend on genetic variants of rs600753 and contribute to dyslexia. However, these results are preliminary and need replication.

Authors: Bent Müller, Johannes Boltze, Ivonne Czepezauer, Volker Hesse, Arndt Wilcke, Holger Kirsten

Date Published: 1st Mar 2018

Publication Type: Journal article

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Objective Adipose tissue-derived signals potentially link obesity and adipose tissue dysfunction with metabolic and cardiovascular diseases. Although some adipocytokines have been closely related too metabolic and cardiovascular traits, it remains open which adipocytokine or adipocytokine cluster serve as meaningful marker of metabolic syndrome (MS) components. Therefore, this study investigates the associations of twelve adipocytokines with components of the MS to identify the most relevant cytokines potentially related to specific metabolic profiles. Research Design/Methods Twelve cytokines (adiponectin, adipocyte fatty acid-binding protein [AFABP], angiopoietin-related growth factor, chemerin, fibroblast growth factor [FGF] 19, FGF21, FGF23, insulin-like growth factor-1, interleukin 10, irisin, progranulin, vaspin) were quantified in a cross-sectional cohort of 1046 subjects. Hypothesis-free cluster analysis, multivariate regression analyses with parameters of the MS, and discriminant analysis were performed to assess associations and the relative importance of each cytokine for reflecting MS and its components. Results Among the studied adipocytokines, adiponectin, AFABP, chemerin, and FGF21 showed the strongest associations with MS and several MS components in discriminant analyses and multiple regression models. For certain metabolic components, these adipocytokines were better discriminators than routine metabolic markers. Other cytokines investigated in the present cohort are less potent to discriminate between metabolically healthy and unhealthy subjects. Conclusions Adiponectin, AFABP, chemerin, and FGF21 show strongest associations with MS components in a general population suggesting that adverse adipose tissue function represents a major contributor to these metabolic abnormalities. Future prospective studies need to address the question whether these adipocytokines are able to predict the development of metabolic disease states.

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

Date Published: 1st Mar 2018

Publication Type: Journal article

Abstract (Expand)

Progranulin is a secreted protein with important functions in processes including immune and inflammatory response, metabolism and embryonic development. The present study aimed at identification of genetic factors determining progranulin concentrations. We conducted a genome-wide association meta-analysis for serum progranulin in three independent cohorts from Europe: Sorbs (N = 848) and KORA (N = 1628) from Germany and PPP-Botnia (N = 335) from Finland (total N = 2811). Single nucleotide polymorphisms (SNPs) associated with progranulin levels were replicated in two additional German cohorts: LIFE-Heart Study (Leipzig; N = 967) and Metabolic Syndrome Berlin Potsdam (Berlin cohort; N = 833). We measured mRNA expression of genes in peripheral blood mononuclear cells (PBMC) by micro-arrays and performed mRNA expression quantitative trait and expression-progranulin association studies to functionally substantiate identified loci. Finally, we conducted siRNA silencing experiments in vitro to validate potential candidate genes within the associated loci. Heritability of circulating progranulin levels was estimated at 31.8% and 26.1% in the Sorbs and LIFE-Heart cohort, respectively. SNPs at three loci reached study-wide significance (rs660240 in CELSR2-PSRC1-MYBPHL-SORT1, rs4747197 in CDH23-PSAP and rs5848 in GRN) explaining 19.4%/15.0% of the variance and 61%/57% of total heritability in the Sorbs/LIFE-Heart Study. The strongest evidence for association was at rs660240 (P = 5.75 x 10-50), which was also associated with mRNA expression of PSRC1 in PBMC (P = 1.51 x 10-21). Psrc1 knockdown in murine preadipocytes led to a consecutive 30% reduction in progranulin secretion. In conclusion, the present meta-GWAS combined with mRNA expression identified three loci associated with progranulin and supports the role of PSRC1 in the regulation of progranulin secretion.

Authors: A. Tonjes, M. Scholz, J. Kruger, K. Krause, D. Schleinitz, H. Kirsten, C. Gebhardt, C. Marzi, H. Grallert, C. Ladenvall, H. Heyne, E. Laurila, J. Kriebel, C. Meisinger, W. Rathmann, C. Gieger, L. Groop, I. Prokopenko, B. Isomaa, F. Beutner, J. Kratzsch, A. Fischer-Rosinsky, A. Pfeiffer, K. Krohn, J. Spranger, J. Thiery, M. Bluher, M. Stumvoll, P. Kovacs

Date Published: 1st Feb 2018

Publication Type: Journal article

Abstract (Expand)

OBJECTIVE To evaluate the perioperative course of urine levels of the renal damage biomarkers tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7)) and to evaluate the predictive value of elevated TIMP-2 \times IGFBP7 concentrations to predict acute kidney injury (AKI) early after cardiac on-pump surgery. DESIGN Prospective, observational cohort study. SETTING University hospital. PARTICIPANTS The study comprised 110 consecutive patients undergoing elective cardiac surgery with cardiopulmonary bypass (CPB) between January and March 2014. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Urinary TIMP-2 \times IGFBP7 levels were quantified using a commercially available kit at the following measurement points: before surgery, 1 hour after starting CPB, 4 hours after weaning from CPB, and 24 hours after weaning from CPB (time points 1-4). Postoperative AKI was defined according to Kidney Disease Improving Global Outcomes criteria. AKI after cardiac surgery was diagnosed in 9 patients (8%). The perioperative course of TIMP-2 \times IGFBP7 was significantly different in patients with and without postoperative AKI (p \textless 0.001). TIMP-2 \times IGFBP7 levels were significantly higher in patients with AKI 1 hour after CPB start and 24 hours after weaning from CPB (p \textless 0.05). TIMP-2 \times IGFBP7 levels \textgreater0.40 (ng/mL)(2)/1,000 measured at 1 hour after starting CPB were found to be the optimal cut-off, with a sensitivity of 0.778 and a specificity of 0.641. The negative predictive value was 0.972. CONCLUSIONS Urine levels of TIMP-2 \times IGFBP7 are predictive for AKI at an early time point (1 hour after starting CPB). Renal damage biomarkers such as TIMP-2 and IGFBP7 might be recommended as a supplement to traditionally used criteria of AKI prediction.

Authors: Tanja Mayer, Daniel Bolliger, Markus Scholz, Oliver Reuthebuch, Michael Gregor, Patrick Meier, Martin Grapow, Manfred D. Seeberger, Jens Fassl

Date Published: 1st Dec 2017

Publication Type: Journal article

Abstract (Expand)

Transcript co-expression is regulated by a combination of shared genetic and environmental factors. Here, we estimate the proportion of co-expression that is due to shared genetic variance. To do so, we estimated the genetic correlations between each pairwise combination of 2469 transcripts that are highly heritable and expressed in whole blood in 1748 unrelated individuals of European ancestry. We identify 556 pairs with a significant genetic correlation of which 77% are located on different chromosomes, and report 934 expression quantitative trait loci, identified in an independent cohort, with significant effects on both transcripts in a genetically correlated pair. We show significant enrichment for transcription factor control and physical proximity through chromatin interactions as possible mechanisms of shared genetic control. Finally, we construct networks of interconnected transcripts and identify their underlying biological functions. Using genetic correlations to investigate transcriptional co-regulation provides valuable insight into the nature of the underlying genetic architecture of gene regulation.Covariance of gene expression pairs is due to a combination of shared genetic and environmental factors. Here the authors estimate the genetic correlation between highly heritable pairs and identify transcription factor control and chromatin interactions as possible mechanisms of correlation.

Authors: Samuel W. Lukowski, Luke R. Lloyd-Jones, Alexander Holloway, Holger Kirsten, Gibran Hemani, Jian Yang, Kerrin Small, Jing Zhao, Andres Metspalu, Emmanouil T. Dermitzakis, Greg Gibson, Timothy D. Spector, Joachim Thiery, Markus Scholz, Grant W. Montgomery, Tonu Esko, Peter M. Visscher, Joseph E. Powell

Date Published: 1st Dec 2017

Publication Type: Journal article

Abstract (Expand)

BACKGROUND When testing for SNP (single nucleotide polymorphism) associations in related individuals, observations are not independent. Simple linear regression assuming independent normally distributedd residuals results in an increased type I error and the power of the test is also affected in a more complicate manner. Inflation of type I error is often successfully corrected by genomic control. However, this reduces the power of the test when relatedness is of concern. In the present paper, we derive explicit formulae to investigate how heritability and strength of relatedness contribute to variance inflation of the effect estimate of the linear model. Further, we study the consequences of variance inflation on hypothesis testing and compare the results with those of genomic control correction. We apply the developed theory to the publicly available HapMap trio data (N=129), the Sorbs (a self-contained population with N=977 characterised by a cryptic relatedness structure) and synthetic family studies with different sample sizes (ranging from N=129 to N=999) and different degrees of relatedness. RESULTS We derive explicit and easily to apply approximation formulae to estimate the impact of relatedness on the variance of the effect estimate of the linear regression model. Variance inflation increases with increasing heritability. Relatedness structure also impacts the degree of variance inflation as shown for example family structures. Variance inflation is smallest for HapMap trios, followed by a synthetic family study corresponding to the trio data but with larger sample size than HapMap. Next strongest inflation is observed for the Sorbs, and finally, for a synthetic family study with a more extreme relatedness structure but with similar sample size as the Sorbs. Type I error increases rapidly with increasing inflation. However, for smaller significance levels, power increases with increasing inflation while the opposite holds for larger significance levels. When genomic control is applied, type I error is preserved while power decreases rapidly with increasing variance inflation. CONCLUSIONS Stronger relatedness as well as higher heritability result in increased variance of the effect estimate of simple linear regression analysis. While type I error rates are generally inflated, the behaviour of power is more complex since power can be increased or reduced in dependence on relatedness and the heritability of the phenotype. Genomic control cannot be recommended to deal with inflation due to relatedness. Although it preserves type I error, the loss in power can be considerable. We provide a simple formula for estimating variance inflation given the relatedness structure and the heritability of a trait of interest. As a rule of thumb, variance inflation below 1.05 does not require correction and simple linear regression analysis is still appropriate.

Authors: Arnd Gross, Anke Tönjes, Markus Scholz

Date Published: 1st Dec 2017

Publication Type: Journal article

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