| 1. |
- Gustafsson, Mika, et al.
(författare)
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Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions
- 2009
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Ingår i: CHALLENGES OF SYSTEMS BIOLOGY: COMMUNITY EFFORTS TO HARNESS BIOLOGICAL COMPLEXITY. - : Wiley. - 0077-8923 .- 1749-6632. ; 1158, s. 265-275
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Tidskriftsartikel (refereegranskat)abstract
- The quest to determine cause from effect is often referred to as reverse engineering in the context of cellular networks. Here we propose and evaluate an algorithm for reverse engineering a gene regulatory network from time-series kind steady-state data. Our algorithmic pipeline, which is rather standard in its parts but not in its integrative composition, combines ordinary differential equations, parameter estimations by least angle regression, and cross-validation procedures for determining the in-degrees and selection of nonlinear transfer functions. The result of the algorithm is a complete directed net-work, in which each edge has been assigned a score front it bootstrap procedure. To evaluate the performance, we submitted the outcome of the algorithm to the reverse engineering assessment competition DREAM2, where we used the data corresponding to the InSillico1 and InSilico2 networks as input. Our algorithm outperformed all other algorithms when inferring one of the directed gene-to-gene networks.
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| 2. |
- Hägg, Sara, 1977-, et al.
(författare)
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Carbon-14 Dating to Determine Carotid Plaque Age : Carbon-14 Dating of Carotid Plaques
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Rationale: The exact nature of atherosclerotic plaque development and the molecular mechanisms that lead to clinical manifestations of carotid stenosis are unclear. After nuclear bomb tests in the 1950s, atmospheric 14C concentrations rapidly increased. Since then, the concentrations have been declining, and the curve of declination can be used to date biological samples synthesized during the last five to six decades. Objective: To investigate plaque age as a novel characteristic of atherosclerotic plaques in patients with carotid stenosis. Methods and Results: Carotid plaques from 29 well-characterized endarterectomy patients with symptomatic carotid stenosis were analyzed by accelerator mass spectrometry, and global gene expression of 25 plaque samples was profiled with HG-U133 Plus 2.0 arrays. The average plaque age was 9.3 years, and inter- and intrasample standard variations were low (1–3.5 years); thus, most of the plaques were generated 5–15 years before surgery. Plaque age was not associated with patient age or plaque size, determined by intima-media thickness, but was inversely related to plasma insulin levels (P=0.0014). A cluster of functionally related genes enriched with genes involved in immune responses was activated in plaques with low plaque age, as were oxidative phosphorylation genes. Conclusion: Patients with mild insulin resistance have increased immune and inflammatory gene activity in their carotid plaques causing them to become instable, rapidly progressing into clinical manifestations at a relatively young age. These results show that plaque age, determined by 14C dating, is a novel and important characteristic of atherosclerotic plaques that will improve our understanding of the clinical significance and molecular underpinnings of atherosclerosis.
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| 3. |
- Hägg, Sara, et al.
(författare)
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Carotid Plaque Age Is a Feature of Plaque Stability Inversely Related to Levels of Plasma Insulin
- 2011
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:4, s. e18248-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The stability of atherosclerotic plaques determines the risk for rupture, which may lead to thrombus formation and potentially severe clinical complications such as myocardial infarction and stroke. Although the rate of plaque formation may be important for plaque stability, this process is not well understood. We took advantage of the atmospheric C-14-declination curve (a result of the atomic bomb tests in the 1950s and 1960s) to determine the average biological age of carotid plaques. Methodology/Principal Finding: The cores of carotid plaques were dissected from 29 well-characterized, symptomatic patients with carotid stenosis and analyzed for C-14 content by accelerator mass spectrometry. The average plaque age (i.e. formation time) was 9.6+/-3.3 years. All but two plaques had formed within 5-15 years before surgery. Plaque age was not associated with the chronological ages of the patients but was inversely related to plasma insulin levels (p=0.0014). Most plaques were echo-lucent rather than echo-rich (2.2460.97, range 1-5). However, plaques in the lowest tercile of plaque age (most recently formed) were characterized by further instability with a higher content of lipids and macrophages (67.8+/-12.4 vs. 50.4+/-6.2, p=0.00005; 57.6+/-26.1 vs. 39.8+/-25.7, p<0.0005, respectively), less collagen (45.3+/-6.1 vs. 51.1+/-9.8, p<0.05), and fewer smooth muscle cells (130+/-31 vs. 141+/-21, p<0.05) than plaques in the highest tercile. Microarray analysis of plaques in the lowest tercile also showed increased activity of genes involved in immune responses and oxidative phosphorylation. Conclusions/Significance: Our results show, for the first time, that plaque age, as judge by relative incorporation of C-14, can improve our understanding of carotid plaque stability and therefore risk for clinical complications. Our results also suggest that levels of plasma insulin might be involved in determining carotid plaque age.
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| 4. |
- Hägg, Sara, et al.
(författare)
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Molecular Phenotypes of Coronary Artery Disease : The Stockholm Atherosclerosis Gene Expression (STAGE) Study
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- BACKGROUNDBy offering a comprehensive view of the molecular underpinnings of pathology, high-dimensional data have the potential to revolutionize the diagnosis and management of complex disorders such as coronary artery disease (CAD). To identify molecular phenotypes of CAD, we performed multi organ gene expression profiling of subjects enrolled in the Stockholm Atherosclerosis Gene Expression (STAGE) study.METHODSAtherosclerotic and unaffected arterial wall, liver, skeletal muscle, and mediastinal fat biopsies were obtained during coronary artery bypass grafting from 114 well-characterized CAD patients. RNA samples were isolated, and 278 transcription profiles were obtained using Affymetrix HG-U133_Plus_2 GeneChips.RESULTSThe most prominent molecular phenotype of the CAD patients was represented by 733 genes in mediastinal fat, which were involved in extracellular matrix organization, response to stress and regulation of programmed cell death. Other aspects of this phenotype were shared with liver (e.g., oxidoreductase activity), skeletal muscle (insulin-like growth factor binding), and atherosclerotic arterial wall (cell motility and adhesion, fatty acid metabolism). In addition, the activity of 400 genes exclusively in mediastinal fat was associated with the extent of coronary stenosis and atherosclerosis. Immune-cell activation in mediastinal fat defined CAD patients with poor blood glucose control and prolonged hospitalization.CONCLUSIONSThe molecular phenotype of mediastinal fat appears to be central in CAD and should be useful for early identification of CAD risk.
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| 5. |
- Hägg, Sara, 1977-, et al.
(författare)
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Multi-Organ Expression Profiling Uncovers a Gene Module in Coronary Artery Disease Involving Transendothelial Migration of Leukocytes and LIM Domain Binding 2 : The Stockholm Atherosclerosis Gene Expression (STAGE) Study
- 2009
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Ingår i: PLoS Genetics. - : PLoS Genetics. - 1553-7390 .- 1553-7404. ; 5:12, s. e1000754-
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Tidskriftsartikel (refereegranskat)abstract
- Environmental exposures filtered through the genetic make-up of each individual alter the transcriptional repertoire in organs central to metabolic homeostasis, thereby affecting arterial lipid accumulation, inflammation, and the development of coronary artery disease (CAD). The primary aim of the Stockholm Atherosclerosis Gene Expression (STAGE) study was to determine whether there are functionally associated genes (rather than individual genes) important for CAD development. To this end, two-way clustering was used on 278 transcriptional profiles of liver, skeletal muscle, and visceral fat (n=66/tissue) and atherosclerotic and unaffected arterial wall (n=40/tissue) isolated from CAD patients during coronary artery bypass surgery. The first step, across all mRNA signals (n=15,042/12,621 RefSeqs/genes) in each tissue, resulted in a total of 60 tissue clusters (n=3958 genes). In the second step (performed within tissue clusters), one atherosclerotic lesion (n=49/48) and one visceral fat (n=59) cluster segregated the patients into two groups that differed in the extent of coronary stenosis (P=0.008 and P=0.00015). The associations of these clusters with coronary atherosclerosis were validated by analyzing carotid atherosclerosis expression profiles. Remarkably, in one cluster (n=55/54) relating to carotid stenosis (P=0.04), 27 genes in the two clusters relating to coronary stenosis were confirmed (n=16/17, P<10-27and-30). Genes in the transendothelial migration of leukocytes (TEML) pathway were overrepresented in all three clusters, referred to as the atherosclerosis module (A-module). In a second validation step, using three independent cohorts, the A-module was found to be genetically enriched with CAD risk by 1.8-fold (P<0.004). The transcription co-factor LIM domain binding 2 (LDB2) was identified as a potential high-hierarchy regulator of the A-module, a notion supported by subnetwork analysis, cellular and lesion expression of LDB2, and the expression of 13 TEML genes in Ldb2-deficient arterial wall. Thus, the A-module appears to be important for atherosclerosis development and together with LDB2 merits further attention in CAD research.
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| 6. |
- Skogsberg, Josefin, et al.
(författare)
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Whole-genome expression profiling of human plaques to identify genes relevant for atherosclerosis : the Stockholm Atherosclerosis Gene Expression Study, Stockholm Söder Hospital, Sweden (SöS-STAGE)
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- ObjectiveTo reveal relevant genes for atherosclerosis by whole-genome expression analyses of plaques from patients undergoing carotid endorectomy.Methods and ResultsWhole-genome expression measurements (WGEM) using Affymetrix HG-U133_Plus_2 chip of carotid plaques in patients undergoing carotid endorectomy at Stockholm Söder Hospital, Sweden. Patients were screened for conventional risk factors at a three-month follow-up visit and atherosclerosis burden in the common carotid artery (CCA) was measured by intima-media thickness (IMT). An unsupervised coupled two-way clustering approach identified genderspecific genes and 55 genes associated to degree of IMT in these patients.ConclusionsCoupled two-way clustering of carotid lesion expression profiles from a well-characterized clinical cohort is useful for identification of novel genes that may be relevant for atheroscleroris.
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| 7. |
- Cedersund, Gunnar, 1978-, et al.
(författare)
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Optimization in biology parameter estimation and the associated optimization problem
- 2016
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Ingår i: Uncertainty in biology. - Cham : Springer. - 9783319212951 - 9783319212968 ; , s. 177-197
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Bokkapitel (refereegranskat)abstract
- Parameter estimation – the assignment of values to the parameters in a model – is an important and time-consuming task in computational biology. Recent computational and algorithmic developments have provided novel tools to improve this estimation step. One of these improvements concerns the optimization step, where the parameter space is explored to find interesting regions. In this chapter we review the parameter estimation problem, with a special emphasis on the associated optimization methods. In relation to this, we also provide concepts and tools to help you select the appropriate methodology for a specific scenario.
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| 8. |
- Clermont, Gilles, et al.
(författare)
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Bridging the gap between systems biology and medicine
- 2009
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 1:9
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Tidskriftsartikel (refereegranskat)abstract
- ABSTRACT : Systems biology has matured considerably as a discipline over the last decade, yet some of the key challenges separating current research efforts in systems biology and clinically useful results are only now becoming apparent. As these gaps are better defined, the new discipline of systems medicine is emerging as a translational extension of systems biology. How is systems medicine defined? What are relevant ontologies for systems medicine? What are the key theoretic and methodologic challenges facing computational disease modeling? How are inaccurate and incomplete data, and uncertain biologic knowledge best synthesized in useful computational models? Does network analysis provide clinically useful insight? We discuss the outstanding difficulties in translating a rapidly growing body of data into knowledge usable at the bedside. Although core-specific challenges are best met by specialized groups, it appears fundamental that such efforts should be guided by a roadmap for systems medicine drafted by a coalition of scientists from the clinical, experimental, computational, and theoretic domains.
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| 9. |
- Compte, A., et al.
(författare)
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Temporally Irregular Mnemonic Persistent Activity in Prefrontal Neurons of Monkeys during a Delayed Response Task
- 2003
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Ingår i: Journal of Neurophysiology. - : American Physiological Society. - 0022-3077 .- 1522-1598. ; 90:5, s. 3441-3454
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Tidskriftsartikel (refereegranskat)abstract
- An important question in neuroscience is whether and how temporal patterns and fluctuations in neuronal spike trains contribute to information processing in the cortex. We have addressed this issue in the memory-related circuits of the prefrontal cortex by analyzing spike trains from a database of 229 neurons recorded in the dorsolateral prefrontal cortex of 4 macaque monkeys during the performance of an oculomotor delayed-response task. For each task epoch, we have estimated their power spectrum together with interspike interval histograms and autocorrelograms. We find that 1) the properties of most (about 60%) neurons approximated the characteristics of a Poisson process. For about 25% of cells, with characteristics typical of interneurons, the power spectrum showed a trough at low frequencies (<20 Hz) and the autocorrelogram a dip near zero time lag. About 15% of neurons had a peak at <20 Hz in the power spectrum, associated with the burstiness of the spike train, 2) a small but significant task dependency of spike-train temporal structure: delay responses to preferred locations were characterized not only by elevated firing, but also by suppressed power at low (<20 Hz) frequencies, and 3) the variability of interspike intervals is typically higher during the mnemonic delay period than during the fixation period, regardless of the remembered cue. The high irregularity of neural persistent activity during the delay period is likely to be a characteristic signature of recurrent prefrontal network dynamics underlying working memory.
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| 10. |
- Dwivedi, Sanjiv, et al.
(författare)
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Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder
- 2020
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Disease modules in molecular interaction maps have been useful for characterizing diseases. Yet biological networks, that commonly define such modules are incomplete and biased toward some well-studied disease genes. Here we ask whether disease-relevant modules of genes can be discovered without prior knowledge of a biological network, instead training a deep autoencoder from large transcriptional data. We hypothesize that modules could be discovered within the autoencoder representations. We find a statistically significant enrichment of genome-wide association studies (GWAS) relevant genes in the last layer, and to a successively lesser degree in the middle and first layers respectively. In contrast, we find an opposite gradient where a modular protein-protein interaction signal is strongest in the first layer, but then vanishing smoothly deeper in the network. We conclude that a data-driven discovery approach is sufficient to discover groups of disease-related genes. The study of disease modules facilitates insight into complex diseases, but their identification relies on knowledge of molecular networks. Here, the authors show that disease modules and genes can also be discovered in deep autoencoder representations of large human gene expression datasets.
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