Unique networks: a method to identity disease-specific regulatory networks from microarray data

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The survival of any organismis determined by the mechanisms triggered in response to the inputs received. Underlying mechanisms are described by graphical networks that can be inferred from different types of data such as microarrays. Deriving robust and reliable networks can be complicated due to the microarray structure of the data characterized by a discrepancy between the number of genes and samples of several orders of magnitude, bias and noise. Researchers overcome this problem by integrating independent data together and deriving the common mechanisms through consensus network analysis. Different conditions generate different inputs to the organism which reacts triggering different mechanisms with similarities and differences. A lot of effort has been spent into identifying the commonalities under different conditions. Highlighting similarities may overshadow the differences which often identify the main characteristics of the triggered mechanisms. In this thesis we introduce the concept of study-specific mechanism. We develop a pipeline to semiautomatically identify study-specific networks called unique-networks through a combination of consensus approach, graphical similarities and network analysis. The main pipeline called UNIP (Unique Networks Identification Pipeline) takes a set of independent studies, builds gene regulatory networks for each of them, calculates an adaptation of the sensitivity measure based on the networks graphical similarities, applies clustering to group the studies who generate the most similar networks into study-clusters and derives the consensus networks. Once each study-cluster is associated with a consensus-network, we identify the links that appear only in the consensus network under consideration but not in the others (unique-connections). Considering the genes involved in the unique-connections we build Bayesian networks to derive the unique-networks. Finally, we exploit the inference tool to calculate each gene prediction-accuracy across all studies to further refine the unique-networks. Biological validation through different software and the literature are explored to validate our method. UNIP is first applied to a set of synthetic data perturbed with different levels of noise to study the performance and verify its reliability. Then, wheat under stress conditions and different types of cancer are explored. Finally, we develop a user-friendly interface to combine the set of studies by using AND and NOT logic operators. Based on the findings, UNIP is a robust and reliable method to analyse large sets of transcriptomic data. It easily detects the main complex relationships between transcriptional expression of genes specific for different conditions and also highlights structures and nodes that could be potential targets for further research

GDF15 is elevated in mice following retinal ganglion cell death and in glaucoma patients

Glaucoma is the second leading cause of blindness worldwide. Physicians often use surrogate endpoints to monitor the progression of glaucomatous neurodegeneration. These approaches are limited in their ability to quantify disease severity and progression due to inherent subjectivity, unreliability, and limitations of normative databases. Therefore, there is a critical need to identify specific molecular markers that predict or measure glaucomatous neurodegeneration. Here, we demonstrate that growth differentiation factor 15 (GDF15) is associated with retinal ganglion cell death. Gdf15 expression in the retina is specifically increased after acute injury to retinal ganglion cell axons and in a murine chronic glaucoma model. We also demonstrate that the ganglion cell layer may be one of the sources of secreted GDF15 and that GDF15 diffuses to and can be detected in aqueous humor (AH). In validating these findings in human patients with glaucoma, we find not only that GDF15 is increased in AH of patients with primary open angle glaucoma (POAG), but also that elevated GDF15 levels are significantly associated with worse functional outcomes in glaucoma patients, as measured by visual field testing. Thus, GDF15 maybe a reliable metric of glaucomatous neurodegeneration, although further prospective validation studies will be necessary to determine if GDF15 can be used in clinical practice

Discovering study-specific gene regulatory networks

This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

Action Plan for Stroke in Europe 2018–2030

Two previous pan-European consensus meetings, the 1995 and 2006 Helsingborg meetings, were convened to review the scientific evidence and the state of current services to identify priorities for research and development and to set targets for the development of stroke care for the decade to follow. Adhering to the same format, the European Stroke Organisation (ESO) prepared a European Stroke Action Plan (ESAP) for the years 2018 to 2030, in cooperation with the Stroke Alliance for Europe (SAFE). The ESAP included seven domains: primary prevention, organisation of stroke services, management of acute stroke, secondary prevention, rehabilitation, evaluation of stroke outcome and quality assessment and life after stroke. Research priorities for translational stroke research were also identified. Documents were prepared by a working group and were open to public comments. The final document was prepared after a workshop in Munich on 21–23 March 2018. Four overarching targets for 2030 were identified: (1) to reduce the absolute number of strokes in Europe by 10%, (2) to treat 90% or more of all patients with stroke in Europe in a dedicated stroke unit as the first level of care, (3) to have national plans for stroke encompassing the entire chain of care, (4) to fully implement national strategies for multisector public health interventions. Overall, 30 targets and 72 research priorities were identified for the seven domains. The ESAP provides a basic road map and sets targets for the implementation of evidence-based preventive actions and stroke services to 2030

Dark sectors 2016 Workshop: community report

This report, based on the Dark Sectors workshop at SLAC in April 2016, summarizes the scientific importance of searches for dark sector dark matter and forces at masses beneath the weak-scale, the status of this broad international field, the important milestones motivating future exploration, and promising experimental opportunities to reach these milestones over the next 5-10 years

US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report

This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference

Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology

It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability