@article{ElHajjDittrichBoecketal.2016,
  author    = {El Hajj, Nady and Dittrich, Marcus and B{\"o}ck, Julia and Kraus, Theo F. J. and Nanda, Indrajit and M{\"u}ller, Tobias and Seidmann, Larissa and Tralau, Tim and Galetzka, Danuta and Schneider, Eberhard and Haaf, Thomas},
  title     = {Epigenetic dysregulation in the developing Down syndrome cortex},
  series = {Epigenetics},
  volume    = {11},
  journal   = {Epigenetics},
  number    = {8},
  doi       = {10.1080/15592294.2016.1192736},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-191239},
  pages     = {563-578},
  year      = {2016},
  abstract  = {Using Illumina 450K arrays, 1.85\% of all analyzed CpG sites were significantly hypermethylated and 0.31\% hypomethylated in fetal Down syndrome (DS) cortex throughout the genome. The methylation changes on chromosome 21 appeared to be balanced between hypo- and hyper-methylation, whereas, consistent with prior reports, all other chromosomes showed 3-11times more hyper- than hypo-methylated sites. Reduced NRSF/REST expression due to upregulation of DYRK1A (on chromosome 21q22.13) and methylation of REST binding sites during early developmental stages may contribute to this genome-wide excess of hypermethylated sites. Upregulation of DNMT3L (on chromosome 21q22.4) could lead to de novo methylation in neuroprogenitors, which then persists in the fetal DS brain where DNMT3A and DNMT3B become downregulated. The vast majority of differentially methylated promoters and genes was hypermethylated in DS and located outside chromosome 21, including the protocadherin gamma (PCDHG) cluster on chromosome 5q31, which is crucial for neural circuit formation in the developing brain. Bisulfite pyrosequencing and targeted RNA sequencing showed that several genes of PCDHG subfamilies A and B are hypermethylated and transcriptionally downregulated in fetal DS cortex. Decreased PCDHG expression is expected to reduce dendrite arborization and growth in cortical neurons. Since constitutive hypermethylation of PCDHG and other genes affects multiple tissues, including blood, it may provide useful biomarkers for DS brain development and pharmacologic targets for therapeutic interventions.},
  language  = {en}
}
@article{HassounaOttWuestefeldetal.2016,
  author    = {Hassouna, I. and Ott, C. and W{\"u}stefeld, L. and Offen, N. and Neher, R. A. and Mitkovski, M. and Winkler, D. and Sperling, S. and Fries, L. and Goebbels, S. and Vreja, I. C. and Hagemeyer, N. and Dittrich, M. and Rossetti, M. F. and Kr{\"o}hnert, K. and Hannke, K. and Boretius, S. and Zeug, A. and H{\"o}schen, C. and Dandekar, T. and Dere, E. and Neher, E. and Rizzoli, S. O. and Nave, K.-A. and Sir{\´e}n, A.-L. and Ehrenreich, H.},
  title     = {Revisiting adult neurogenesis and the role of erythropoietin for neuronal and oligodendroglial differentiation in the hippocampus},
  series = {Molecular Psychiatry},
  volume    = {21},
  journal   = {Molecular Psychiatry},
  number    = {12},
  doi       = {10.1038/mp.2015.212},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-186669},
  pages     = {1752-1767},
  year      = {2016},
  abstract  = {Recombinant human erythropoietin (EPO) improves cognitive performance in neuropsychiatric diseases ranging from schizophrenia and multiple sclerosis to major depression and bipolar disease. This consistent EPO effect on cognition is independent of its role in hematopoiesis. The cellular mechanisms of action in brain, however, have remained unclear. Here we studied healthy young mice and observed that 3-week EPO administration was associated with an increased number of pyramidal neurons and oligodendrocytes in the hippocampus of similar to 20\%. Under constant cognitive challenge, neuron numbers remained elevated until >6 months of age. Surprisingly, this increase occurred in absence of altered cell proliferation or apoptosis. After feeding a \(^{15}\)N-leucine diet, we used nanoscopic secondary ion mass spectrometry, and found that in EPO-treated mice, an equivalent number of neurons was defined by elevated \(^{15}\)N-leucine incorporation. In EPO-treated NG2-Cre-ERT2 mice, we confirmed enhanced differentiation of preexisting oligodendrocyte precursors in the absence of elevated DNA synthesis. A corresponding analysis of the neuronal lineage awaits the identification of suitable neuronal markers. In cultured neurospheres, EPO reduced Sox9 and stimulated miR124, associated with advanced neuronal differentiation. We are discussing a resulting working model in which EPO drives the differentiation of non-dividing precursors in both (NG2+) oligodendroglial and neuronal lineages. As endogenous EPO expression is induced by brain injury, such a mechanism of adult neurogenesis may be relevant for central nervous system regeneration.},
  language  = {en}
}
@article{SendtnerDittrichHughesetal.1994,
  author    = {Sendtner, Michael and Dittrich, F. and Hughes, R. A. and Thoenen, H.},
  title     = {Actions of CNTF and neurotrophins on degenerating motoneurons : preclinical studies and clinical implications},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-62939},
  year      = {1994},
  abstract  = {Spinal motoneurons innervating skeletal muscle were amongst the first neurons shown to require the presence of their target cells to develop appropriately. Isolated embryonie chick and rat motoneurons have been used to identify neurotrophic factors and cytokines capable of supporting the survival of developing motoneurons. Such factors include ciliary neurotrophic factor (CNTF), which is present physiologically in high amounts in myelinating Schwann cells of peripheral nerves, and brain-derived neurotrophic factor (BDNF) which is synthesized in skeletal muscle and, after peripheral nerve lesion. in Schwann cells. These factors have been further analyzed for their physiological significance in maintaining motoneuron function in vivo, and for their potential therapeutic usefulness in degenerative motoneuron disease. Both CNTF and BDNF are capable of rescuing injured facial motoneurons in newbom rats. Furthermore, CNTF prolongs survival and improves motor function of pmn mice, an animal model for degenerative motoneuron disease, by preventing degeneration of motoneuron axons and somata. Thus treatment of human motoneuron disease with neurotrophic factors should be possible, provided that rational means for application of these factors can be established considering also the appearance of potential side effects.},
  subject      = {Neurobiologie},
  language  = {en}
}
@article{StaigerCadotKooteretal.2012,
  author    = {Staiger, Christine and Cadot, Sidney and Kooter, Raul and Dittrich, Marcus and M{\"u}ller, Tobias and Klau, Gunnar W. and Wessels, Lodewyk F. A.},
  title     = {A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer},
  series = {PLoS One},
  volume    = {7},
  journal   = {PLoS One},
  number    = {4},
  doi       = {10.1371/journal.pone.0034796},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-131323},
  pages     = {e34796},
  year      = {2012},
  abstract  = {Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.},
  language  = {en}
}
@article{UrbanRemmeleDittrichetal.2020,
  author    = {Urban, Lara and Remmele, Christian W. and Dittrich, Marcus and Schwarz, Roland F. and M{\"u}ller, Tobias},
  title     = {covRNA: discovering covariate associations in large-scale gene expression data},
  series = {BMC Reserach Notes},
  volume    = {13},
  journal   = {BMC Reserach Notes},
  doi       = {10.1186/s13104-020-04946-1},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229258},
  year      = {2020},
  abstract  = {Objective The biological interpretation of gene expression measurements is a challenging task. While ordination methods are routinely used to identify clusters of samples or co-expressed genes, these methods do not take sample or gene annotations into account. We aim to provide a tool that allows users of all backgrounds to assess and visualize the intrinsic correlation structure of complex annotated gene expression data and discover the covariates that jointly affect expression patterns. Results The Bioconductor package covRNA provides a convenient and fast interface for testing and visualizing complex relationships between sample and gene covariates mediated by gene expression data in an entirely unsupervised setting. The relationships between sample and gene covariates are tested by statistical permutation tests and visualized by ordination. The methods are inspired by the fourthcorner and RLQ analyses used in ecological research for the analysis of species abundance data, that we modified to make them suitable for the distributional characteristics of both, RNA-Seq read counts and microarray intensities, and to provide a high-performance parallelized implementation for the analysis of large-scale gene expression data on multi-core computational systems. CovRNA provides additional modules for unsupervised gene filtering and plotting functions to ensure a smooth and coherent analysis workflow.},
  language  = {en}
}