| 1. |
- Lilja, Sandra, 1989-
(author)
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Digital Twins : High Resolution Disease Models for Optimized Diagnosis and Treatment
- 2022
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Doctoral thesis (other academic/artistic)abstract
- To study immune-mediated diseases, which can affect the expression of thousands of genes among many different cell types and organs, is a daunting challenge. However, for effective diagnosis and therapeutic treatment it is relevant to understand the regulatory functions of disease. In this thesis, we hypothesized that regulatory functions in complex diseases can be effectively prioritized based on so called digital twins, which are based on high-resolution single cell data in combination with network theories. More specifically, we tested if digital twins could be used on a patient-group level to prioritize cell types, genes, and/or organs based on their regulatory function in the disease progression. If this hypothesis is true, potential biomarkers and therapeutic targets can be identified for optimized diagnosis and treatment. The long-term goal is to construct digital twins for personalized medicine, to predict the optimal treatment strategies for the individual patients. Although, this is a very ambitious goal which could not be reached through this thesis, relevant steps towards it have been reached.First, we tested if high-resolution disease models based on single cell RNAsequencing (scRNA-seq) data could be used in combination with network theories, to predict and prevent disease. For this aim, we used a mouse model of antigeninduced arthritis (AIA). Based on the cell type specific genes in AIA joint, we identified a multi-cellular disease model (MCDM), including predicted cell-cell interactions. Analyzing this model, Granulocytes were identified as most central in AIA joint. The results from this centrality analysis correlated with GWAS enrichment among the cell type specific genes, as well as with the centrality analyses based on human RA, supporting our results relevance for human disease. A drug, bezafibrate, was further identified which mainly targeted shared disease modules over the central and GWAS enriched CD4+ T cells in nine of 13 analyzed human diseases. Bezafibrate treatment of our AIA mouse model resulted in a decrease in arthritis severity score as well as a decrease in T cell proliferation into the joint.Since blood is an easily available source of data, it is of interest to know it’s potential usefulness when constructing digital twins. To test if samples taken from blood are representative of the inflamed organ, we performed a meta-analysis of different samples from blood and joint of patients with rheumatoid arthritis, as well as from joint and blood Granulocytes of our AIA mouse model. Based on differentially expressed genes (DEGs) between sick and healthy samples from each dataset, we performed pathway analyses and predicted potential biomarkers and upstream regulators (URs). Comparing the lists of pathways, biomarkers, and URs between the datasets from different subsets of blood samples showed low or no similarities. However, the datasets of human bulk or mouse single cell data collected from synovial fluid or full joint showed high similarities. Furthermore, the top shared enriched pathways, predicted biomarkers, and URs from both human and mouse were to a higher degree connected to known functions of autoimmune diseases or rheumatoid arthritis, compared to the respective results from samples taken from blood. These findings indicate that inflammatory mechanisms in cells in blood and inflamed organs differ greatly, which may have important diagnostic and therapeutic implications.We next analyzed if digital twins could be used to identify the early regulatory mechanisms that are also present at the late time points. For this, we used an in vitro time series model of seasonal allergic rhinitis. Samples were taken before allergen stimulation, as well as at 12 hours, 1 day, 2 days, 3 days, 5 days, and 7 days after allergen stimulation, for scRNA-seq and MCDM construction. Multi-directional interactions including all cell types were found at all time points, even before allergen stimulation, which complicated the identification of one key regulatory cell type or gene. Instead, we found that the regulatory genes could be ranked based on their overall downstream effect over all the time points. Our top-ranked regulatory gene, PDGFB, targeted most of the cell types at all the time points, while a previously known early regulator and drug target in allergy, IL4, targeted only five cell type and time point combinations. Validation studies further showed that neutralization of PDGF-BB on allergen-stimulated PBMC from SAR patients were more effective compared to neutralization of IL-4.Finally, we tested if a digital twin including data from multiple organs could be used to understand the systemic interactional changes due to disease. For this aim, we used a systemic mouse model of arthritis, namely collagen induced arthritis (CIA). We first analyzed ten different organs, based on which we prioritized five organs with the highest number of DEGs between CIA and healthy mice, namely joint, lung, muscle, skin, and spleen. Although only joint showed signs of inflammation, many DEGs were identified in all five organs. Those changes were organized into a multi-organ multi-cellular disease model, which indicated an on/off switch of pro-/anti-inflammatory functions in joint and muscle respectively. Validation studies in human immune-mediated inflammatory diseases supported this on/off switch, where pro-inflammatory functions were mainly found in inflamed organs, while anti-inflammatory functions were found in non-inflamed organs.In conclusion, this thesis supports the potential of using high-resolution disease models for digital twin construction. Such digital twins could then be used to prioritize cell types and genes, for further prediction of diagnostic markers and therapeutic targets. Even though the identification of one key regulatory function was complicated due to multidirectional interactions, the genes could be ranked based on their relative downstream effect. For reproducible results, we found that digital twins should ideally be based on data from locally inflamed organs, while systemic models and models covering different disease stages could be useful to understand the disease progression.
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| 2. |
- Söderholm, Simon, 1986-
(author)
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Exploring the tissue-specific nature of the Wnt cell signaling system : The complex world of cell communication and the search for the Achilles heel of cancer
- 2023
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Doctoral thesis (other academic/artistic)abstract
- The Wnt signaling pathway is a biological mechanism for cell-cell communication found across all species of the animal kingdom. This pathway plays a major role in virtually all stages of embryonic development, and it governs central aspects of stem cell biology, regeneration, and tissue homeostasis. In addition, dysregulation of the pathway is associated with developmental malformations and several forms of sever cancer. However, it is still not fully understood how Wnt signaling can mediate such a variety of processes and outcomes. How is a single pathway, which according to the current models is described as a mostly linear cascade of events, able to induce diverging responses in different biological contexts? Finding an answer to this question would not only satisfy scientific curiosity but could also have clinical significance. Given the importance of Wnt signaling in normal tissue function, therapeutically targeting the pathway has historically proven to be difficult. Thus, a better understanding of the tissue-specific properties of the pathway could help us uncover a way to distinguish disease-related cells from healthy cells and identify new targets whose inhibition could impair disease while avoiding detrimental effects on normal tissue function. This thesis represents four years of research that aims to address the knowledge gaps outlined above. Specifically, the work has been focusing on exploring the time- and tissue-specific properties of Wnt signaling by assessing the genome-wide consequences of perturbing this pathway in different model systems. Through this work, we have revealed further instances of disconnection between classical Wnt components, challenging the current established models of how Wnt signaling operates. Furthermore, we demonstrate that the cellular response to Wnt activation occur in a time-dependent manner, with different responsive patterns in different cell types, and even heterogeneously across cells in an otherwise homogenous cell population, contributing to the emerging notion of context-specific Wnt signaling. Finally, we identify a new tissue-specific player in Wnt-mediated transcriptional regulation, which holds promise as a possible therapeutic target in the continuing battle against cancer. In summary, the scientific results presented in this thesis extend our current knowledge of the Wnt signaling pathway by highlighting context-specific aspects that could help explain how this fundamental process adopts different regulatory avenues. This, in turn, could prove important for our ability to identify and ultimately combat disease-specific traits, including finding the Achilles heel of cancer.
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| 3. |
- Barrenäs, Fredrik, 1981-
(author)
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Bioinformatic identification of disease associated pathways by network based analysis
- 2012
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Doctoral thesis (other academic/artistic)abstract
- Many common diseases are complex, meaning that they are caused by many interacting genes. This makes them difficult to study; to determine disease mechanisms, disease-associated genes must be analyzed in combination. Disease-associated genes can be detected using high-throughput methods, such as mRNA expression microarrays, DNA methylation microarrays and genome-wide association studies (GWAS), but determining how they interact to cause disease is an intricate challenge. One approach is to organize disease-associated genes into networks using protein-protein interactions (PPIs) and dissect them to identify disease causing pathways. Studies of complex disease can also be greatly facilitated by using an appropriate model system. In this dissertation, seasonal allergic rhinitis (SAR) served as a model disease. SAR is a common disease that is relatively easy to study. Also, the key disease cell types, like the CD4+ T cell, are known and can be cultured and activated in vitro by the disease causing pollen.The aim of this dissertation was to determine network properties of disease-associated genes, and develop methods to identify and validate networks of disease-associated genes. First, we showed that disease-associated genes have distinguishing network properties, one being that they co-localize in the human PPI network. This supported the existence of disease modules within the PPI network. We then identified network modules of genes whose mRNA expression was perturbed in human disease, and showed that the most central genes in those network modules were enriched for disease-associated polymorphisms identified by GWAS. As a case study, we identified disease modules using mRNA expression data from allergen-challenged CD4+ cells from patients with SAR. The case study identified and validated a novel disease-associated gene, FGF2 using GWAS data and RNAi mediated knockdown.Lastly, we examined how DNA methylation caused disease-associated mRNA expression changes in SAR. DNA methylation, but not mRNA expression profiles, could accurately distinguish allergic patients from healthy controls. Also, we found that disease-associated mRNA expression changes were associated with a low DNA methylation content and absence of CpG islands. Specifically within this group, we found a correlation between disease-associated mRNA expression changes and DNA methylation changes. Using ChIP-chip analysis, we found that targets of a known disease relevant transcription factor, IRF4, were also enriched among non CpG island genes with low methylation levels.Taken together, in this dissertation the network properties of disease-associated genes were examined, and then used to validate disease networks defined by mRNA expression data. We then examined regulatory mechanisms underlying disease-associated mRNA expression changes in a model disease. These studies support network-based analyses as a method to understand disease mechanisms and identify important disease causing genes, such as treatment targets or markers for personalized medication.
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| 4. |
- Eyer, L., et al.
(author)
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Gaia Data Release 2 Variable stars in the colour-absolute magnitude diagram
- 2019
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 623
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Journal article (peer-reviewed)abstract
- Context. The ESA Gaia mission provides a unique time-domain survey for more than 1.6 billion sources with G less than or similar to 21 mag. Aims. We showcase stellar variability in the Galactic colour-absolute magnitude diagram (CaMD). We focus on pulsating, eruptive, and cataclysmic variables, as well as on stars that exhibit variability that is due to rotation and eclipses. Methods. We describe the locations of variable star classes, variable object fractions, and typical variability amplitudes throughout the CaMD and show how variability-related changes in colour and brightness induce "motions". To do this, we use 22 months of calibrated photometric, spectro-photometric, and astrometric Gaia data of stars with a significant parallax. To ensure that a large variety of variable star classes populate the CaMD, we crossmatched Gaia sources with known variable stars. We also used the statistics and variability detection modules of the Gaia variability pipeline. Corrections for interstellar extinction are not implemented in this article. Results. Gaia enables the first investigation of Galactic variable star populations in the CaMD on a similar, if not larger, scale as was previously done in the Magellanic Clouds. Although the observed colours are not corrected for reddening, distinct regions are visible in which variable stars occur. We determine variable star fractions to within the current detection thresholds of Gaia. Finally, we report the most complete description of variability-induced motion within the CaMD to date. Conclusions. Gaia enables novel insights into variability phenomena for an unprecedented number of stars, which will benefit the understanding of stellar astrophysics. The CaMD of Galactic variable stars provides crucial information on physical origins of variability in a way that has previously only been accessible for Galactic star clusters or external galaxies. Future Gaia data releases will enable significant improvements over this preview by providing longer time series, more accurate astrometry, and additional data types (time series BP and RP spectra, RVS spectra, and radial velocities), all for much larger samples of stars.
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| 5. |
- Franks, P. W., et al.
(author)
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Technological readiness and implementation of genomic-driven precision medicine for complex diseases
- 2021
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In: Journal of Internal Medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 290:3, s. 602-620
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Research review (peer-reviewed)abstract
- The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.
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| 6. |
- Gawel, Danuta R., 1988-
(author)
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Identification of genes and regulators that are shared across T cell associated diseases
- 2018
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Doctoral thesis (other academic/artistic)abstract
- Genome-wide association studies (GWASs) of hundreds of diseases and millions of patients have led to the identification of genes that are associated with more than one disease. The aims of this PhD thesis were to a) identify a group of genes important in multiple diseases (shared disease genes), b) identify shared up-stream disease regulators, and c) determine how the same genes can be involved in the pathogenesis of different diseases. These aims have been tested on CD4+ T cells because they express the T helper cell differentiation pathway, which was the most enriched pathway in analyses of all disease associated genes identified with GWASs.Combining information about known gene-gene interactions from the protein-protein interaction (PPI) network with gene expression changes in multiple T cell associated diseases led to the identification of a group of highly interconnected genes that were miss-expressed in many of those diseases – hereafter called ‘shared disease genes’. Those genes were further enriched for inflammatory, metabolic and proliferative pathways, genetic variants identified by all GWASs, as well as mutations in cancer studies and known diagnostic and therapeutic targets. Taken together, these findings supported the relevance of the shared disease genes.Identification of the shared upstream disease regulators was addressed in the second project of this PhD thesis. The underlying hypothesis assumed that the determination of the shared upstream disease regulators is possible through a network model showing in which order genes activate each other. For that reason a transcription factor–gene regulatory network (TF-GRN) was created. The TF-GRN was based on the time-series gene expression profiling of the T helper cell type 1 (Th1), and T helper cell type 2 (Th2) differentiation from Native T-cells. Transcription factors (TFs) whose expression changed early during polarization and had many downstream predicted targets (hubs) that were enriched for disease associated single nucleotide polymorphisms (SNPs) were prioritised as the putative early disease regulators. These analyses identified three transcription factors: GATA3, MAF and MYB. Their predicted targets were validated by ChIP-Seq and siRNA mediated knockdown in primary human T-cells. CD4+ T cells isolated from seasonal allergic rhinitis (SAR) and multiple sclerosis (MS) patients in their non-symptomatic stages were analysed in order to demonstrate predictive potential of those three TFs. We found that those three TFs were differentially expressed in symptom-free stages of the two diseases, while their TF-GRN{predicted targets were differentially expressed during symptomatic disease stages. Moreover, using RNA-Seq data we identified a disease associated SNP that correlated with differential splicing of GATA3.A limitation of the above study is that it concentrated on TFs as main regulators in cells, excluding other potential regulators such as microRNAs. To this end, a microRNA{gene regulatory network (mGRN) of human CD4+ T cell differentiation was constructed. Within this network, we defined regulatory clusters (groups of microRNAs that are regulating groups of mRNAs). One regulatory cluster was differentially expressed in all of the tested diseases, and was highly enriched for GWAS SNPs. Although the microRNA processing machinery was dynamically upregulated during early T-cell activation, the majority of microRNA modules showed specialisation in later time-points.In summary this PhD thesis shows the relevance of shared genes and up-stream disease regulators. Putative mechanisms of why shared genes can be involved in pathogenesis of different diseases have also been demonstrated: a) differential gene expression in different diseases; b) alternative transcription factor splicing variants may affect different downstream gene target group; and c) SNPs might cause alternative splicing.
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| 7. |
- Helmi, A., et al.
(author)
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Gaia Data Release 2 Kinematics of globular clusters and dwarf galaxies around the Milky Way
- 2018
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 616:A12
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Journal article (peer-reviewed)abstract
- Aims The goal of this paper is to demonstrate the outstanding quality of the second data release of the Gaia mission and its power for constraining many different aspects of the dynamics of the satellites of the Milky Way. We focus here on determining the proper motions of 75 Galactic globular clusters, nine dwarf spheroidal galaxies, one ultra-faint system, and the Large and Small Magellanic Clouds.Methods Using data extracted from the Gaia archive, we derived the proper motions and parallaxes for these systems, as well as their uncertainties. We demonstrate that the errors, statistical and systematic, are relatively well understood. We integrated the orbits of these objects in three different Galactic potentials, and characterised their properties. We present the derived proper motions, space velocities, and characteristic orbital parameters in various tables to facilitate their use by the astronomical community.Results Our limited and straightforward analyses have allowed us for example to (i) determine absolute and very precise proper motions for globular clusters; (ii) detect clear rotation signatures in the proper motions of at least five globular clusters; (iii) show that the satellites of the Milky Way are all on high-inclination orbits, but that they do not share a single plane of motion; (i v) derive a lower limit for the mass of the Milky Way of 9.1(-2.6)(+6.2) x 10(11) M-circle dot based on the assumption that the Leo I dwarf spheroidal is bound; (v) derive a rotation curve for the Large Magellanic Cloud based solely on proper motions that is competitive with line-of-sight velocity curves, now using many orders of magnitude more sources; and (v i) unveil the dynamical effect of the bar on the motions of stars in the Large Magellanic Cloud.Conclusions All these results highlight the incredible power of the Gaia astrometric mission, and in particular of its second data release.
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| 8. |
- Lentini, Antonio, 1990-
(author)
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Dynamic regulation of DNA methylation in human T-cell biology
- 2019
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Doctoral thesis (other academic/artistic)abstract
- T helper cells play a central role in orchestrating immune responses in humans. Upon encountering a foreign antigen, T helper cells are activated followed by a differentiation process where the cells are specialised to help combating the infection. Dysregulation of T helper cell activation, differentiation and function has been implicated in numerous diseases, including autoimmunity and cancer. Whereas gene-regulatory networks help drive T-cell differentiation, acquisition of stable cell states require heritable epigenetic signals, such as DNA methylation. Indeed, the establishment of DNA methylation patterns is a key part of appropriate T-cell differentiation but how this is regulated over time remains unknown. Methylation can be directly attached to cytosine residues in DNA to form 5-methylcytosine (5mC) but the removal of DNA methylation requires multiple enzymatic reactions, commonly initiated by the conversion into 5-hydroxymethylcytosine (5hmC), thus creating a highly complex regulatory system. This thesis aimed to investigate how DNA methylation is dynamically regulated during T-cell differentiation.To this end, we employed large-scale profiling techniques combining gene expression as well as genome-wide 5mC and 5hmC measurements to construct a time-series model of epigenetic regulation of differentiation. This revealed that early T-cell activation was accompanied by extensive genome-wide deposition of 5hmC which resulted in demethylation upon proliferation. Early DNA methylation remodelling through 5hmC was not only indicative of demethylation events during T-cell differentiation but also marked changes persisting longterm in memory T-cell subsets. These results suggest that priming of epigenetic landscapes in T-cells is initiated during early activation events, preceding any establishment of a stable lineage, which are then maintained throughout the cells lifespan. The regions undergoing remodelling were also highly enriched for genetic variants in autoimmune diseases which we show to be functional through disruption of protein binding. These variants could potentially disrupt gene-regulatory networks and the establishment of epigenetic priming, highlighting the complex interplay between genetic and epigenetic layers. In the course of this work, we discovered that a commonly used technique to study genome-wide DNA modifications, DNA immunoprecipitation (DIP)-seq, had a false discovery rate between 50-99% depending on the modification and cell type being assayed. This represented inherent technical errors related to the use of antibodies resulting in off-target binding of repetitive sequences lacking any DNA modifications. These sequences are common in mammalian genomes making robust detection of rare DNA modifications very difficult due to the high background signals. However, offtarget binding could easily be controlled for using a non-specific antibody control which greatly improved data quality and biological insight of the data. Although future studies are advised to use alternative methods where available, error correction is an acceptable alternative which will help fuel new discoveries through the removal of extensive background signals.Taken together, this thesis shows how integrative use of high-resolution epigenomic data can be used to study complex biological systems over time as well as how these techniques can be systematically characterised to identify and correct errors resulting in improved detection.
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| 9. |
- Lindegren, Lennart, et al.
(author)
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Gaia Early Data Release 3 : The Gaia Catalogue of Nearby Stars
- 2021
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 649
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Journal article (peer-reviewed)abstract
- Aims. We produce a clean and well-characterised catalogue of objects within 100 pc of the Sun from the Gaia Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use.Methods. Theselection of objects within 100 pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100 pc is included in the catalogue.Results. We have produced a catalogue of 331 312 objects that we estimate contains at least 92% of stars of stellar type M9 within 100 pc of the Sun. We estimate that 9% of the stars in this catalogue probably lie outside 100 pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of Gaia Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10 pc of the Sun.Conclusions. We provide the community with a large, well-characterised catalogue of objects in the solar neighbourhood. This is a primary benchmark for measuring and understanding fundamental parameters and descriptive functions in astronomy.
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| 10. |
- Samuelsson, Mikael
(author)
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Creating new ventures : A longitudinal investigation of the nascent venturing process
- 2004
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Doctoral thesis (other academic/artistic)abstract
- This study contributes, empirically, theoretically and methodologically, to entrepreneurship research, theory, and practice. I provide answers to three major questions regarding venture opportunity variation, variation in the nascent venturing process, and outcomes from this process. Conclusions and implications are based on theoretically derived hypotheses and empirical information from 622 venture opportunities, which we followed from discovery throughout the nascent venturing process and beyond.New survey design as well as state of the art longitudinal statistical methods made it possible to extend our knowledge into the nascent stages of the entrepreneurial process. This research is an extension and empirical test of recent conceptual discussions in the field and moves the entrepreneurship research toward an opportunity based theory of the creation of new economic activity.
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