Universitätspublikationen
Refine
Year of publication
- 2014 (270) (remove)
Document Type
- Article (229)
- Doctoral Thesis (15)
- Part of Periodical (12)
- Book (7)
- Conference Proceeding (3)
- Preprint (2)
- Contribution to a Periodical (1)
- Periodical (1)
Language
- English (227)
- German (41)
- Multiple languages (1)
- Romanian (1)
Is part of the Bibliography
- no (270)
Keywords
- Multimorbidity (4)
- Decorin (3)
- Depression (3)
- Primary care (3)
- ATM (2)
- Aortic valve replacement (2)
- Breast cancer (2)
- Cancer (2)
- Chronic disease (2)
- Drug hepatotoxicity (2)
Institute
- Medizin (270) (remove)
Synaptic dysfunction and synapse loss are key features of Alzheimer's pathogenesis. Previously, we showed an essential function of APP and APLP2 for synaptic plasticity, learning and memory. Here, we used organotypic hippocampal cultures to investigate the specific role(s) of APP family members and their fragments for dendritic complexity and spine formation of principal neurons within the hippocampus. Whereas CA1 neurons from APLP1-KO or APLP2-KO mice showed normal neuronal morphology and spine density, APP-KO mice revealed a highly reduced dendritic complexity in mid-apical dendrites. Despite unaltered morphology of APLP2-KO neurons, combined APP/APLP2-DKO mutants showed an additional branching defect in proximal apical dendrites, indicating redundancy and a combined function of APP and APLP2 for dendritic architecture. Remarkably, APP-KO neurons showed a pronounced decrease in spine density and reductions in the number of mushroom spines. No further decrease in spine density, however, was detectable in APP/APLP2-DKO mice. Mechanistically, using APPsalpha-KI mice lacking transmembrane APP and expressing solely the secreted APPsalpha fragment we demonstrate that APPsalpha expression alone is sufficient to prevent the defects in spine density observed in APP-KO mice. Collectively, these studies reveal a combined role of APP and APLP2 for dendritic architecture and a unique function of secreted APPs for spine density.
During cell stress, the transcription and translation of immediate early genes are prioritized, while most other messenger RNAs (mRNAs) are stored away in stress granules or degraded in processing bodies (P-bodies). TIA-1 is an mRNA-binding protein that needs to translocate from the nucleus to seed the formation of stress granules in the cytoplasm. Because other stress granule components such as TDP-43, FUS, ATXN2, SMN, MAPT, HNRNPA2B1, and HNRNPA1 are crucial for the motor neuron diseases amyotrophic lateral sclerosis (ALS)/spinal muscular atrophy (SMA) and for the frontotemporal dementia (FTD), here we studied mouse nervous tissue to identify mRNAs with selective dependence on Tia1 deletion. Transcriptome profiling with oligonucleotide microarrays in comparison of spinal cord and cerebellum, together with independent validation in quantitative reverse transcriptase PCR and immunoblots demonstrated several strong and consistent dysregulations. In agreement with previously reported TIA1 knock down effects, cell cycle and apoptosis regulators were affected markedly with expression changes up to +2-fold, exhibiting increased levels for Cdkn1a, Ccnf, and Tprkb vs. decreased levels for Bid and Inca1 transcripts. Novel and surprisingly strong expression alterations were detected for fat storage and membrane trafficking factors, with prominent +3-fold upregulations of Plin4, Wdfy1, Tbc1d24, and Pnpla2 vs. a −2.4-fold downregulation of Cntn4 transcript, encoding an axonal membrane adhesion factor with established haploinsufficiency. In comparison, subtle effects on the RNA processing machinery included up to 1.2-fold upregulations of Dcp1b and Tial1. The effect on lipid dynamics factors is noteworthy, since also the gene deletion of Tardbp (encoding TDP-43) and Atxn2 led to fat metabolism phenotypes in mouse. In conclusion, genetic ablation of the stress granule nucleator TIA-1 has a novel major effect on mRNAs encoding lipid homeostasis factors in the brain, similar to the fasting effect.
Selection of higher order regression models in the analysis of multi-factorial transcription data
(2014)
Introduction: Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ.
Results: We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes.
Conclusions: We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.
The multifunctional molecule netrin-1 is upregulated in various malignancies and has recently been presented as a major general player in tumorigenesis leading to tumor progression and maintenance in various animal models. However, there is still a lack of clinico-epidemiological data related to netrin-1 expression. Therefore, the aim of our study was to elucidate the association of netrin-1 expression and patient survival in brain metastases since those constitute one of the most limiting factors for patient prognosis. We investigated 104 brain metastases cases for netrin-1 expression using in-situ hybridization and immunohistochemistry with regard to clinical parameters such as patient survival and MRI data. Our data show that netrin-1 is strongly upregulated in most cancer subtypes. Univariate analyses revealed netrin-1 expression as a significant factor associated with poor patient survival in the total cohort of brain metastasis patients and in sub-entities such as non-small cell lung carcinomas. Interestingly, many cancer samples showed a strong nuclear netrin-1 signal which was recently linked to a truncated netrin-1 variant that enhances tumor growth. Nuclear netrin-1 expression was associated with poor patient survival in univariate as well as in multivariate analyses. Our data indicate both total and nuclear netrin-1 expression as prognostic factors in brain metastases patients in contrast to other prognostic markers in oncology such as patient age, number of brain metastases or Ki67 proliferation index. Therefore, nuclear netrin-1 expression constitutes one of the first reported molecular biomarkers for patient survival in brain metastases. Furthermore, netrin-1 may constitute a promising target for future anti-cancer treatment approaches in brain metastases.
Objective: The objective of this study was to describe and analyze the effects of depression on health care utilization and costs in a sample of multimorbid elderly patients.
Method: This cross-sectional analysis used data of a prospective cohort study, consisting of 1,050 randomly selected multimorbid primary care patients aged 65 to 85 years. Depression was defined as a score of six points or more on the Geriatric Depression Scale (GDS-15). Subjects passed a geriatric assessment, including a questionnaire for health care utilization. The impact of depression on health care costs was analyzed using multiple linear regression models. A societal perspective was adopted.
Results: Prevalence of depression was 10.7%. Mean total costs per six-month period were €8,144 (95% CI: €6,199-€10,090) in patients with depression as compared to €3,137 (95% CI: €2,735-€3,538; p<0.001) in patients without depression. The positive association between depression and total costs persisted after controlling for socio-economic variables, functional status and level of multimorbidity. In particular, multiple regression analyses showed a significant positive association between depression and pharmaceutical costs.
Conclusion: Among multimorbid elderly patients, depression was associated with significantly higher health care utilization and costs. The effect of depression on costs was even greater than reported by previous studies conducted in less morbid patients.
Hepatitis C virus (HCV) infection leads to the development of hepatic diseases, as well as extrahepatic disorders such as B-cell non-Hodgkin's lymphoma (B-NHL). To reveal the molecular signalling pathways responsible for HCV-associated B-NHL development, we utilised transgenic (Tg) mice that express the full-length HCV genome specifically in B cells and develop non-Hodgkin type B-cell lymphomas (BCLs). The gene expression profiles in B cells from BCL-developing HCV-Tg mice, from BCL-non-developing HCV-Tg mice, and from BCL-non-developing HCV-negative mice were analysed by genome-wide microarray. In BCLs from HCV-Tg mice, the expression of various genes was modified, and for some genes, expression was influenced by the gender of the animals. Markedly modified genes such as Fos, C3, LTβR, A20, NF-κB and miR-26b in BCLs were further characterised using specific assays. We propose that activation of both canonical and alternative NF-κB signalling pathways and down-regulation of miR-26b contribute to the development of HCV-associated B-NHL.
Association of autoimmune Addison's disease with alleles of STAT4 and GATA3 in European cohorts
(2014)
Background: Gene variants known to contribute to Autoimmune Addison's disease (AAD) susceptibility include those at the MHC, MICA, CIITA, CTLA4, PTPN22, CYP27B1, NLRP-1 and CD274 loci. The majority of the genetic component to disease susceptibility has yet to be accounted for.
Aim: To investigate the role of 19 candidate genes in AAD susceptibility in six European case-control cohorts.
Methods: A sequential association study design was employed with genotyping using Sequenom iPlex technology. In phase one, 85 SNPs in 19 genes were genotyped in UK and Norwegian AAD cohorts (691 AAD, 715 controls). In phase two, 21 SNPs in 11 genes were genotyped in German, Swedish, Italian and Polish cohorts (1264 AAD, 1221 controls). In phase three, to explore association of GATA3 polymorphisms with AAD and to determine if this association extended to other autoimmune conditions, 15 SNPs in GATA3 were studied in UK and Norwegian AAD cohorts, 1195 type 1 diabetes patients from Norway, 650 rheumatoid arthritis patients from New Zealand and in 283 UK Graves' disease patients. Meta-analysis was used to compare genotype frequencies between the participating centres, allowing for heterogeneity.
Results: We report significant association with alleles of two STAT4 markers in AAD cohorts (rs4274624: P = 0.00016; rs10931481: P = 0.0007). In addition, nominal association of AAD with alleles at GATA3 was found in 3 patient cohorts and supported by meta-analysis. Association of AAD with CYP27B1 alleles was also confirmed, which replicates previous published data. Finally, nominal association was found at SNPs in both the NF-κB1 and IL23A genes in the UK and Italian cohorts respectively.
Conclusions: Variants in the STAT4 gene, previously associated with other autoimmune conditions, confer susceptibility to AAD. Additionally, we report association of GATA3 variants with AAD: this adds to the recent report of association of GATA3 variants with rheumatoid arthritis.
Computational analyses of functions of gene sets obtained in microarray analyses or by topical database searches are increasingly important in biology. To understand their functions, the sets are usually mapped to Gene Ontology knowledge bases by means of over-representation analysis (ORA). Its result represents the specific knowledge of the functionality of the gene set. However, the specific ontology typically consists of many terms and relationships, hindering the understanding of the ‘main story’. We developed a methodology to identify a comprehensibly small number of GO terms as “headlines” of the specific ontology allowing to understand all central aspects of the roles of the involved genes. The Functional Abstraction method finds a set of headlines that is specific enough to cover all details of a specific ontology and is abstract enough for human comprehension. This method exceeds the classical approaches at ORA abstraction and by focusing on information rather than decorrelation of GO terms, it directly targets human comprehension. Functional abstraction provides, with a maximum of certainty, information value, coverage and conciseness, a representation of the biological functions in a gene set plays a role. This is the necessary means to interpret complex Gene Ontology results thus strengthening the role of functional genomics in biomarker and drug discovery.
Protein signatures of oxidative stress response in a patient specific cell line model for autism
(2014)
Background: Known genetic variants can account for 10% to 20% of all cases with autism spectrum disorders (ASD). Overlapping cellular pathomechanisms common to neurons of the central nervous system (CNS) and in tissues of peripheral organs, such as immune dysregulation, oxidative stress and dysfunctions in mitochondrial and protein synthesis metabolism, were suggested to support the wide spectrum of ASD on unifying disease phenotype. Here, we studied in patient-derived lymphoblastoid cell lines (LCLs) how an ASD-specific mutation in ribosomal protein RPL10 (RPL10[H213Q]) generates a distinct protein signature. We compared the RPL10[H213Q] expression pattern to expression patterns derived from unrelated ASD patients without RPL10[H213Q] mutation. In addition, a yeast rpl10 deficiency model served in a proof-of-principle study to test for alterations in protein patterns in response to oxidative stress.
Methods: Protein extracts of LCLs from patients, relatives and controls, as well as diploid yeast cells hemizygous for rpl10, were subjected to two-dimensional gel electrophoresis and differentially regulated spots were identified by mass spectrometry. Subsequently, Gene Ontology database (GO)-term enrichment and network analysis was performed to map the identified proteins into cellular pathways.
Results: The protein signature generated by RPL10[H213Q] is a functionally related subset of the ASD-specific protein signature, sharing redox-sensitive elements in energy-, protein- and redox-metabolism. In yeast, rpl10 deficiency generates a specific protein signature, harboring components of pathways identified in both the RPL10[H213Q] subjects' and the ASD patients' set. Importantly, the rpl10 deficiency signature is a subset of the signature resulting from response of wild-type yeast to oxidative stress.
Conclusions: Redox-sensitive protein signatures mapping into cellular pathways with pathophysiology in ASD have been identified in both LCLs carrying the ASD-specific mutation RPL10[H213Q] and LCLs from ASD patients without this mutation. At pathway levels, this redox-sensitive protein signature has also been identified in a yeast rpl10 deficiency and an oxidative stress model. These observations point to a common molecular pathomechanism in ASD, characterized in our study by dysregulation of redox balance. Importantly, this can be triggered by the known ASD-RPL10[H213Q] mutation or by yet unknown mutations of the ASD cohort that act upstream of RPL10 in differential expression of redox-sensitive proteins.