Publications

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

Abstract (Expand)

We systematically studied the expression of more than fifty histone and DNA (de)methylating enzymes in lymphoma and healthy controls. As a main result, we found that the expression levels of nearly all enzymes become markedly disturbed in lymphoma, suggesting deregulation of large parts of the epigenetic machinery. We discuss the effect of DNA promoter methylation and of transcriptional activity in the context of mutated epigenetic modifiers such as EZH2 and MLL2. As another mechanism, we studied the coupling between the energy metabolism and epigenetics via metabolites that act as cofactors of JmjC-type demethylases. Our study results suggest that Burkitt's lymphoma and diffuse large B-cell Lymphoma differ by an imbalance of repressive and poised promoters, which is governed predominantly by the activity of methyltransferases and the underrepresentation of demethylases in this regulation. The data further suggest that coupling of epigenetics with the energy metabolism can also be an important factor in lymphomagenesis in the absence of direct mutations of genes in metabolic pathways. Understanding of epigenetic deregulation in lymphoma and possibly in cancers in general must go beyond simple schemes using only a few modes of regulation.

Authors: L. Hopp, L. Nersisyan, H. Loffler-Wirth, A. Arakelyan, H. Binder

Date Published: 21st Oct 2015

Publication Type: Not specified

Human Diseases: non-Hodgkin lymphoma

Abstract (Expand)

MOTIVATION: Comprehensive analysis of genome-wide molecular data challenges bioinformatics methodology in terms of intuitive visualization with single-sample resolution, biomarker selection, functional information mining and highly granular stratification of sample classes. oposSOM combines those functionalities making use of a comprehensive analysis and visualization strategy based on self-organizing maps (SOM) machine learning which we call 'high-dimensional data portraying'. The method was successfully applied in a series of studies using mostly transcriptome data but also data of other OMICs realms. AVAILABILITY AND IMPLEMENTATION: oposSOM is now publicly available as Bioconductor R package. CONTACT: wirth@izbi.uni-leipzig.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors: H. Loffler-Wirth, M. Kalcher, H. Binder

Date Published: 1st Oct 2015

Publication Type: Not specified

Abstract (Expand)

Developmental dyslexia, a severe impairment of literacy acquisition, is known to have a neurological basis and a strong genetic background. However, effects of individual genetic variations on dyslexia-associated deficits are only moderate and call for the assessment of the genotype’s impact on mediating neuro-endophenotypes by the imaging genetics approach. Using voxel-based morphometry (VBM) in German participants with and without dyslexia, we investigated gray matter changes and their association with impaired phonological processing, such as reduced verbal working memory. These endophenotypical alterations were, together with dyslexia-associated genetic variations, examined on their suitability as potential predictors of dyslexia. We identified two gray matter clusters in the left posterior temporal cortex related to verbal working memory capacity. Regional cluster differences correlated with genetic risk variants in TNFRSF1B. High-genetic-risk participants exhibit a structural predominance of auditory-association areas relative to auditory-sensory areas, which may partly compensate for deficient early auditory-sensory processing stages of verbal working memory. The reverse regional predominance observed in low-genetic-risk participants may in turn reflect reliance on these early auditory-sensory processing stages. Logistic regression analysis further supported that regional gray matter differences and genetic risk interact in the prediction of individuals’ diagnostic status: With increasing genetic risk, the working-memory related structural predominance of auditory-association areas relative to auditory-sensory areas classifies participants with dyslexia versus control participants. Focusing on phonological deficits in dyslexia, our findings suggest endophenotypical changes in the left posterior temporal cortex could comprise novel pathomechanisms for verbal working memory-related processes translating TNFRSF1B genotype into the dyslexia phenotype. Developmental dyslexia, a severe impairment of literacy acquisition, is known to have a neurological basis and a strong genetic background. However, effects of individual genetic variations on dyslexia-associated deficits are only moderate and call for the assessment of the genotype’s impact on mediating neuro-endophenotypes by the imaging genetics approach. Using voxel-based morphometry (VBM) in German participants with and without dyslexia, we investigated gray matter changes and their association with impaired phonological processing, such as reduced verbal working memory. These endophenotypical alterations were, together with dyslexia-associated genetic variations, examined on their suitability as potential predictors of dyslexia. We identified two gray matter clusters in the left posterior temporal cortex related to verbal working memory capacity. Regional cluster differences correlated with genetic risk variants in TNFRSF1B. High-genetic-risk participants exhibit a structural predominance of auditory-association areas relative to auditory-sensory areas, which may partly compensate for deficient early auditory-sensory processing stages of verbal working memory. The reverse regional predominance observed in low-genetic-risk participants may in turn reflect reliance on these early auditory-sensory processing stages. Logistic regression analysis further supported that regional gray matter differences and genetic risk interact in the prediction of individuals’ diagnostic status: With increasing genetic risk, the working-memory related structural predominance of auditory-association areas relative to auditory-sensory areas classifies participants with dyslexia versus control participants. Focusing on phonological deficits in dyslexia, our findings suggest endophenotypical changes in the left posterior temporal cortex could comprise novel pathomechanisms for verbal working memory-related processes translating TNFRSF1B genotype into the dyslexia phenotype.

Authors: Claudia Männel, Lars Meyer, Arndt Wilcke, Johannes Boltze, Holger Kirsten, Angela D. Friederici

Date Published: 1st Oct 2015

Publication Type: Journal article

Abstract (Expand)

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of \sim185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) \textgreater 0.05) and 2.7 million low-frequency (0.005 \textless MAF \textless 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.   Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of \sim185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) \textgreater 0.05) and 2.7 million low-frequency (0.005 \textless MAF \textless 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.   Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of \sim185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) \textgreater 0.05) and 2.7 million low-frequency (0.005 \textless MAF \textless 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.   Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of \sim185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) \textgreater 0.05) and 2.7 million low-frequency (0.005 \textless MAF \textless 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size. //  Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of \sim185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) \textgreater 0.05) and 2.7 million low-frequency (0.005 \textless MAF \textless 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.

Author: CARDIoGRAMplusC4D Consortium

Date Published: 1st Oct 2015

Publication Type: Journal article

Abstract (Expand)

Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2,107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6; rs12210538, rs17657775), propionylcarnitine (chromosome 10; rs12779637), 2-hydroxyisovalerylcarnitine (chromosome 21; rs1571700), stearoylcarnitine (chromosome 1; rs3811444), and aspartic acid traits (chromosome 8; rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies.

Authors: R. Burkhardt, H. Kirsten, F. Beutner, L. M. Holdt, A. Gross, A. Teren, A. Tonjes, S. Becker, K. Krohn, P. Kovacs, M. Stumvoll, D. Teupser, J. Thiery, U. Ceglarek, M. Scholz

Date Published: 25th Sep 2015

Publication Type: Not specified

Human Diseases: kidney disease

Abstract (Expand)

The revised NIA-AA diagnostic criteria for Alzheimer's disease (AD) and mild cognitive impairment (MCI) due to AD make use of amyloid pathology and neurodegeneration biomarkers which increase the diagnostic confidence in the majority of patients. However, in daily praxis, cases with conflicting biomarker constellations occur. A MCI subject underwent neuropsychological testing supplemented by FDG and amyloid PET/MRI as well as CSF sampling. In this subject, the biomarkers of Abeta deposition were negative. [18F]FDG PET, however, showed an AD-typical hypometabolism. Further studies are required to determine frequency and relevance of cases with neurodegeneration-first biomarker constellations to improve our understanding on pathogenesis and diagnosis of AD.

Authors: S. Tiepolt, M. Patt, K. T. Hoffmann, M. L. Schroeter, O. Sabri, H. Barthel

Date Published: 25th Sep 2015

Publication Type: Not specified

Human Diseases: cognitive disorder, Alzheimer's disease

Abstract (Expand)

BACKGROUND: Studies have shown that dementia and cognitive impairment can increase mortality, but less is known about the association between subjectively perceived cognitive deficits (subjective cognitive decline, SCD) and mortality risk. OBJECTIVE: In this study, we analyzed mortality in non-demented individuals with SCD in a general population sample aged 75+ years. METHOD: Data were derived from the Leipzig Longitudinal Study of the Aged (LEILA75+). We used the Kaplan-Meier survival method to estimate survival times of individuals with and without SCD and multivariable Cox proportional hazards regression to assess the association between SCD and mortality risk, controlled for covariates. RESULTS: Out of 953 non-demented individuals at baseline, 117 (12.3% ) expressed SCD. Participants with SCD showed a significantly higher case-fatality rate per 1,000 person-years (114.8, 95% CI = 90.5-145.7 versus 71.7, 95% CI = 64.6-79.5) and a significantly shorter mean survival time than those without (5.4 versus 6.9 years, p < 0.001). The association between SCD and mortality remained significant in the Cox analysis; SCD increased mortality risk by about 50% (adjusted Hazard Ratio = 1.51) during the study period. Besides SCD, older age, male gender, diabetes mellitus, stroke, and lower global cognitive functioning were also significantly associated with increased mortality. CONCLUSION: Our findings suggest an increased mortality risk in non-demented older individuals with SCD. Even though further studies are required to analyze potential underlying mechanisms, subjective reports on cognitive deficits may be taken seriously in clinical practice not only for an increased risk of developing dementia and AD but also for a broader range of possible adverse health outcomes.

Authors: T. Luck, S. Roehr, F. Jessen, A. Villringer, M. C. Angermeyer, S. G. Riedel-Heller

Date Published: 24th Sep 2015

Publication Type: Not specified

Human Diseases: dementia

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