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See detailSystems Biology Approaches for Identification of Molecular Mechanisms in Brain Disorders
Androsova, Ganna UL

Doctoral thesis (2018)

One out of four people are affected by a brain disorder at some stage in their life. Depending on the symptoms and the underlying molecular mechanisms, brain disorders can be classified into neurological ... [more ▼]

One out of four people are affected by a brain disorder at some stage in their life. Depending on the symptoms and the underlying molecular mechanisms, brain disorders can be classified into neurological and cognitive disorders. Complex disorders typically have a multifactorial pathogenesis. Epilepsy and postoperative delirium (POD) exemplifying neurological and cognitive disorders are no exception. Research efforts contributed to the understanding of molecular mechanisms of these diseases by discovering associations between clinical and genomic information and disease phenotypes. These findings, although necessary, are not sufficient to reconstruct the complete map of system-level interactions. To achieve a system-level understanding of a biological system, one can integrate diverse data sources by a network-based approach. Network analysis methods characterise interactions within and between molecular systems and can identify candidate biomarkers in various biological contexts. Specifically, correlation networks can reveal condition-dependent molecular patterns whose functional enrichment points to the altered molecular mechanisms of the phenotype. A molecular signature of a phenotype can be determined by machine learning algorithms for supervised classification as a set of molecules accurately discriminating between disease and healthy state. The primary aim of this dissertation is to identify altered biological pathways and functionally relevant molecules of epileptogenesis and postoperative delirium. This cumulative dissertation is composed of six chapters. Chapter 1provides the background information on brain disorders and the systems biology methods to study their molecular mechanisms. Chapter 2 was motivated by the fact that current anti-epilepsy treatments focus on minimisation of the symptoms and epileptic seizures, while no definitive cure exists. The understanding of molecular events triggering the development of epilepsy (also called epileptogenesis) can yield therapies halting the onset of epilepsy. We identified proteomic alterations in the animal model of epileptogenesis by a network-based method and validated our results by external data set and immunohistochemical staining. The functional annotation of molecular expression patterns revealed biological pathways not yet described in the context of epileptogenesis. Next, we identified the gap in a comparative analysis of available antiepileptic drugs for mesial temporal lobe epilepsy due to hippocampal sclerosis. Chapter 3 retrospectively compares retention, efficacy and tolerability of antiepileptic drugs in the large epilepsy pharmacogenomics database. Chapter 4 is focused on the identification of molecular alterations in postoperative delirium. Overlaying postmortem brain expression data with locations of functional networks disturbed in POD, we identified several gene expression patterns with relevant biological enrichment. Moreover, same biological functions were altered in the blood of POD patients. Previously described POD markers such as acetylcholinesterase, alpha-synuclein and protein C appeared in the identified clusters. In Chapter 5, I focused on the identification of a molecular signature discriminating POD patients before they undergo surgery. Having ranked preoperative expression levels of mRNAs and miRNAs by their ability to detect patients with POD, I identified a set of discriminatory features that achieved high accuracy, sensitivity and specificity in the training set. The trained model had a good generalisability on the unseen data set but its performance decreased on the test set not matched by age and gender. The final Chapter 6 summarises the main outcomes of the presented studies and concludes with an outlook. [less ▲]

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See detailPersonalized risk prediction of postoperative cognitive impairment - rationale for the EU-funded BioCog project.
Winterer, G.; Androsova, Ganna UL; Bender, O. et al

in European Psychiatry (2018), 50

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical ... [more ▼]

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation. [less ▲]

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See detailComparative effectiveness of antiepileptic drugs in patients with mesial temporal lobe epilepsy with hippocampal sclerosis
Androsova, Ganna UL; Krause, Roland UL; Borghei, Mojgansadat et al

in Epilepsia (2017)

Objective: Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is a common epilepsy syndrome that is often poorly controlled by antiepileptic drug (AED) treatment. Comparative AED ... [more ▼]

Objective: Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is a common epilepsy syndrome that is often poorly controlled by antiepileptic drug (AED) treatment. Comparative AED effectiveness studies in this condition are lacking. Wereport retention, efficacy, and tolerability in a cohort of patients with MTLE-HS. Methods: Clinical data were collected from a European database of patients with epilepsy. We estimated retention, 12-month seizure freedom, and adverse drug reaction (ADR) rates for the 10 most commonly used AEDs in patients with MTLE-HS. Results: Seven hundred sixty-seven patients with a total of 3,249 AED trials were included. The highest 12-month retention rates were observed with carbamazepine (85.9%), valproate (85%), and clobazam (79%). Twelve-month seizure freedom rates varied from 1.2% for gabapentin and vigabatrin to 11% for carbamazepine. Response rates were highest for AEDs that were prescribed as initial treatment and lowest for AEDs that were used in a third or higher instance. ADRs were reported in 47.6% of patients, with the highest rates observed with oxcarbazepine (35.7%), topiramate (30.9%), and pregabalin (27.4%), and the lowest rates with clobazam (6.5%), gabapentin (8.9%), and lamotrigine (16.6%). The most commonly reported ADRs were lethargy and drowsiness, dizziness, vertigo and ataxia, and blurred vision and diplopia. Significance: Our results did not demonstrate any clear advantage of newer versus older AEDs. Our results provide useful insights into AED retention, efficacy, and ADR rates in patients with MTLE-HS. [less ▲]

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See detailA systems level analysis of epileptogenesis-associated proteome alterations.
Keck, Michael; Androsova, Ganna UL; Gualtieri, Fabio et al

in Neurobiology of Disease (2017), 105

Despite intense research efforts, the knowledge about the mechanisms of epileptogenesis and epilepsy is still considered incomplete and limited. However, an in-depth understanding of molecular ... [more ▼]

Despite intense research efforts, the knowledge about the mechanisms of epileptogenesis and epilepsy is still considered incomplete and limited. However, an in-depth understanding of molecular pathophysiological processes is crucial for the rational selection of innovative biomarkers and target candidates. Here, we subjected proteomic data from different phases of a chronic rat epileptogenesis model to a comprehensive systems level analysis. Weighted Gene Co-expression Network analysis identified several modules of interconnected protein groups reflecting distinct molecular aspects of epileptogenesis in the hippocampus and the parahippocampal cortex. Characterization of these modules did not only further validate the data but also revealed regulation of molecular processes not described previously in the context of epilepsy development. The data sets also provide valuable information about temporal patterns, which should be taken into account for development of preventive strategies in particular when it comes to multi-targeting network pharmacology approaches. In addition, principal component analysis suggests candidate biomarkers, which might inform the design of novel molecular imaging approaches aiming to predict epileptogenesis during different phases or confirm epilepsy manifestation. Further studies are necessary to distinguish between molecular alterations, which correlate with epileptogenesis versus those reflecting a mere consequence of the status epilepticus. [less ▲]

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See detailAnalysis of the dynamic co-expression network of heart regeneration in the zebrafish
Rodius, Sophie; Androsova, Ganna UL; Götz, Lou et al

in Scientific Reports (2016), 6

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact ... [more ▼]

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration. [less ▲]

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See detailDiscrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET
Rodriguez, Ana; Crespo, Isaac UL; Androsova, Ganna UL et al

in PLoS ONE (2015), 10(6), 0127216

High-throughput technologies have led to the generation of an increasing amount of data in different areas of biology. Datasets capturing the cell’s response to its intra- and extra-cellular ... [more ▼]

High-throughput technologies have led to the generation of an increasing amount of data in different areas of biology. Datasets capturing the cell’s response to its intra- and extra-cellular microenvironment allows such data to be incorporated as signed and directed graphs or influence networks. These prior knowledge networks (PKNs) represent our current knowledge of the causality of cellular signal transduction. New signalling data is often examined and interpreted in conjunction with PKNs. However, different biological contexts, such as cell type or disease states, may have distinct variants of signalling pathways, resulting in the misinterpretation of new data. The identification of inconsistencies between measured data and signalling topologies, as well as the training of PKNs using context specific datasets (PKN contextualization), are necessary conditions to construct reliable, predictive models, which are current challenges in the systems biology of cell signalling. Here we present PRUNET, a user-friendly software tool designed to address the contextualization of a PKNs to specific experimental conditions. As the input, the algorithm takes a PKN and the expression profile of two given stable steady states or cellular phenotypes. The PKN is iteratively pruned using an evolutionary algorithm to perform an optimization process. This optimization rests in a match between predicted attractors in a discrete logic model (Boolean) and a Booleanized representation of the phenotypes, within a population of alternative subnetworks that evolves iteratively. We validated the algorithm applying PRUNET to four biological examples and using the resulting contextualized networks to predict missing expression values and to simulate well-characterized perturbations. PRUNET constitutes a tool for the automatic curation of a PKN to make it suitable for describing biological processes under particular experimental conditions. The general applicability of the implemented algorithm makes PRUNET suitable for a variety of biological processes, for instance cellular reprogramming or transitions between healthy and disease states. [less ▲]

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See detailBiomarkers of postoperative delirium and cognitive dysfunction
Androsova, Ganna UL; Krause, Roland UL; Winterer, Georg et al

in Frontiers in Aging Neuroscience (2015), 7(112),

Elderly surgical patients frequently experience postoperative delirium (POD) and the subsequent development of postoperative cognitive dysfunction (POCD). Clinical features include deterioration in ... [more ▼]

Elderly surgical patients frequently experience postoperative delirium (POD) and the subsequent development of postoperative cognitive dysfunction (POCD). Clinical features include deterioration in cognition, disturbance in attention and reduced awareness of the environment and result in higher morbidity, mortality and greater utilization of social financial assistance. The aging Western societies can expect an increase in the incidence of POD and POCD. The underlying pathophysiological mechanisms have been studied on the molecular level albeit with unsatisfying small research efforts given their societal burden. Here, we review the known physiological and immunological changes and genetic risk factors, identify candidates for further studies and integrate the information into a draft network for exploration on a systems level. The pathogenesis of these postoperative cognitive impairments is multifactorial; application of integrated systems biology has the potential to reconstruct the underlying network of molecular mechanisms and help in the identification of prognostic and diagnostic biomarkers. [less ▲]

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See detailA comprehensive integrative analysis of the transcriptional network underlying the zebrafish heart regeneration
Androsova, Ganna UL; Rodius, Sophie; Nazarov, Petr et al

Poster (2014, September 08)

Despite a notable reduction in incidence of acute myocardial infarction (MI), patients who experienced it remain at risk for premature death and cardiac malfunction. The human cardiomyocytes are not able ... [more ▼]

Despite a notable reduction in incidence of acute myocardial infarction (MI), patients who experienced it remain at risk for premature death and cardiac malfunction. The human cardiomyocytes are not able to achieve extensive regeneration upon MI. Remarkably, the adult zebrafish is able to achieve complete heart regeneration following amputation, cryoinjury or genetic ablation. This raises new potential opportunities on how to boost heart healing capacity in humans. The objective of our research is to characterize the transcriptional network of the zebrafish heart regeneration and underlying regulatory mechanisms. To conduct our investigation, we used microarray data from zebrafish at 6 post-cryoinjury time points (4 hours, and 1, 3, 7, 14 and 90 days) and control samples. We thereon looked for the gene co-expression patterns in the data and, based on that, constructed a weighted gene co-expression network. To detect candidate functional sub-networks (modules), we used two different network clustering approaches: a density-based (ClusterONE) and a topological overlap-based (Hybrid Dynamic Branch Cut) algorithms. The visualization of the expression changes of the candidate modules reflected the dynamics of the recovery process. Also we aimed to identify candidate “hub” genes that might regulate the behavior of the biological modules and drive the regeneration process. We identified eighteen distinct modules associated with heart recovery upon cryoinjury. Functional enrichment analysis displayed that the modules are involved in different cellular processes crucial for heart regeneration, including: cell fate specification (p-value < 0.006) and migration (p-value < 0.047), ribosome biogenesis (p-value < 0.004), cardiac cell differentiation (p-value < 3E-04), and various signaling events (p-value < 0.037). The visualization of the modules’ expression profiles confirmed the relevance of these functional enrichments. For instance, the genes of the module involved in regulation of endodermal cell fate specification were up-regulated upon injury until 3 days. Among the candidate hub genes detected in the network, there are genes relevant to atherosclerosis treatment and inflammation during cardiac arrest. These and other findings are currently undergoing deeper computational analyses. The top promising targets will be independently validated using our zebrafish (in vivo) model. In conclusion, our findings provide insights into the complex regulatory mechanisms involved during heart regeneration in the zebrafish. These data will be useful for modelling specific network-based responses to heart injury, and for finding sensitive network points that may trigger or boost heart regeneration. [less ▲]

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See detailNetwork-based Approach Enabling Drug Repositioning for the Treatment of Myocardial Infarction
Androsova, Ganna UL

Bachelor/master dissertation (2014)

Despite a notable reduction in incidence of acute myocardial infarction (MI), patients who experience it remain at risk for premature death and cardiac malfunction. The human cardiomyocytes are not able ... [more ▼]

Despite a notable reduction in incidence of acute myocardial infarction (MI), patients who experience it remain at risk for premature death and cardiac malfunction. The human cardiomyocytes are not able to achieve extensive regeneration upon MI. Remarkably, the adult zebrafish is able to achieve complete heart regeneration following amputation, cryoinjury or genetic ablation. This raises new potential opportunities on how to boost the heart healing capacity in humans. The objective of our research is to characterize the transcriptional network of the zebrafish heart regeneration, to describe underlying regulatory mechanisms, and to identify potential drugs capable to boost heart regeneration capacity. Having identified the gene co-expression patterns in the data from a zebrafish cryoinjury model, we constructed a weighted gene co-expression network. To detect candidate functional sub-networks (modules), we used two different network clustering approaches: a density-based (ClusterONE) and a topological overlap-based (Dynamic Hybrid) algorithms. We identified eighteen distinct modules associated with heart recovery upon cryoinjury. Functional enrichment analysis displayed that the modules are involved in different cellular processes crucial for heart regeneration, including: cell fate specification (p-value < 0.006) and migration (p-value < 0.047), cardiac cell differentiation (p-value < 3E-04), and various signaling events (p-value < 0.037). The visualization of the modules’ expression profiles confirmed the relevance of these functional enrichments. Among the candidate hub genes detected in the network, there are genes relevant to atherosclerosis treatment and inflammation during cardiac arrest. Among the top candidate drugs, there were drugs already reported to play therapeutic roles in heart disease, though the majority of the drugs have not been considered yet for myocardial infarction treatment. In conclusion, our findings provide insights into the complex regulatory mechanisms involved during heart regeneration in the zebrafish. These data will be useful for modeling specific network-based responses to heart injury, and for finding sensitive network points that may trigger or boost heart regeneration in the zebrafish, and possibly in mammals. [less ▲]

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