| 1. |
- Berndt, Sonja I., et al.
(författare)
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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
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Tidskriftsartikel (refereegranskat)abstract
- Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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| 2. |
- Do, Ron, et al.
(författare)
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Common variants associated with plasma triglycerides and risk for coronary artery disease
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:11, s. 1345-
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Tidskriftsartikel (refereegranskat)abstract
- Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 x 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
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| 3. |
- Willer, Cristen J., et al.
(författare)
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Discovery and refinement of loci associated with lipid levels
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:11, s. 1274-1283
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Tidskriftsartikel (refereegranskat)abstract
- Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 x 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.
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| 4. |
- Barrenäs, Fredrik, et al.
(författare)
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Disease-Associated MRNA Expression Differences in Genes with Low DNA Methylation
- 2012
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Although the importance of DNA methylation for mRNA expression has been shown for individualgenes in several complex diseases, such a relation has been difficult to show on a genome-wide scale.Here, we used microarrays to examine the relationship between DNA methylation and mRNAexpression in CD4+ T cells from patients with seasonal allergic rhinitis (SAR) and healthy controls.SAR is an optimal disease model because the disease process can be studied by comparing allergenchallengedCD4+ T cells obtained from patients and controls, and mimicked in Th2 polarised T cellsfrom healthy controls. The cells from patients can be analyzed to study relations between methylationand mRNA expression, while the Th2 cells can be used for functional studies. We found that DNAmethylation, but not mRNA expression clearly separated patients from controls. Similar to studies ofother complex diseases, we found no general relation between DNA methylation and mRNAexpression. However, when we took into account the absence or presence of CpG islands in thepromoters of disease associated genes an association was found: low methylation genes without CpGislands had significantly higher expression levels of disease-associated genes. This association wasconfirmed for genes whose expression levels were regulated by a transcription factor of knownrelevance for allergy, IRF4, using combined ChIP-chip and siRNA mediated silencing of IRF4expression. In summary, disease-associated increases of mRNA expression were found in lowmethylation genes without CpG islands in CD4+ T cells from patients with SAR. Further studies arewarranted to examine if a similar association is found in other complex diseases.
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| 5. |
- Bruhn, Sören, et al.
(författare)
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A Generally Applicable Translational Strategy Identifies S100A4 as a Candidate Gene in Allergy
- 2014
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Ingår i: Science Translational Medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6234 .- 1946-6242. ; 6:218
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Tidskriftsartikel (refereegranskat)abstract
- The identification of diagnostic markers and therapeutic candidate genes in common diseases is complicated by the involvement of thousands of genes. We hypothesized that genes co-regulated with a key gene in allergy, IL13, would form a module that could help to identify candidate genes. We identified a T helper 2 (T(H)2) cell module by small interfering RNA-mediated knockdown of 25 putative IL13-regulating transcription factors followed by expression profiling. The module contained candidate genes whose diagnostic potential was supported by clinical studies. Functional studies of human TH2 cells as well as mouse models of allergy showed that deletion of one of the genes, S100A4, resulted in decreased signs of allergy including TH2 cell activation, humoral immunity, and infiltration of effector cells. Specifically, dendritic cells required S100A4 for activating T cells. Treatment with an anti-S100A4 antibody resulted in decreased signs of allergy in the mouse model as well as in allergen-challenged T cells from allergic patients. This strategy, which may be generally applicable to complex diseases, identified and validated an important diagnostic and therapeutic candidate gene in allergy.
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| 6. |
- Bruhn, Sören, 1976-, et al.
(författare)
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Combining gene expression microarray- and cluster analysis with sequence-based predictions to identify regulators of IL-13 in allergy
- 2012
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Ingår i: Cytokine. - : Elsevier. - 1043-4666 .- 1096-0023. ; 60:3, s. 736-740
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Tidskriftsartikel (refereegranskat)abstract
- The Th2 cytokine IL-13 plays a key role in allergy, by regulating IgE, airway hyper secretion, eosinophils and mast cells. In this study, we aimed to identify novel transcription factors (TFs) that potentially regulated IL-13. We analyzed Th2 polarized naïve T cells from four different blood donors with gene expression microarrays to find clusters of genes that were correlated or anti-correlated with IL13. These clusters were further filtered, by selecting genes that were functionally related. In these clusters, we identified three transcription factors (TFs) that were predicted to regulate the expression of IL13, namely CEBPB, E2F6 and AHR. siRNA mediated knockdowns of these TFs in naïve polarized T cells showed significant increases of IL13, following knockdown of CEBPB and E2F6, but not AHR. This suggested an inhibitory role of CEBPB and E2F6 in the regulation of IL13 and allergy. This was supported by analysis of E2F6, but not CEBPB, in allergen-challenged CD4+ T cells from six allergic patients and six healthy controls, which showed decreased expression of E2F6 in patients. In summary, our findings indicate an inhibitory role of E2F6 in the regulation of IL-13 and allergy. The analytical approach may be generally applicable to elucidate the complex regulatory patterns in Th2 cell polarization and allergy.
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| 7. |
- Edström, Måns, et al.
(författare)
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Regulatory T cells in Multiple Sclerosis – Indications of impaired function of suppressive capacity and a role for chemokines
- 2014
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- BACKGROUND Regulatory T cells (Treg) are critical for immune regulation and homeostasis. In multiple sclerosis (MS), the function of these cells has been shown to be impaired, although the underlying mechanism has yet to be shown. In the current study, we aimed to characterize and assess the phenotypical, functional and transcriptional characteristics of memory and naïve Treg in MS patients and controls.MATERIAL AND METHODS 27 patients with relapsing-remitting disease were included, along with 29 healthy controls. Flow cytometry was used for detailed phenotyping of Treg subpopulations CD4+CD45RA+/- and CD4dimCD25++ and their expression of FOXP3, CD39 and HELIOS. CFSE (proliferation marker) and CD69 (activation marker) were used to investigate the functional capacity of Treg. A microarray was employed for genome-wide transcriptional characterization of isolated Treg.RESULTS CD4+CD45RA–CD25++ activated Treg displayed a higher expression of FOXP3 and CD39 than resting CD4+CD45RA+CD25+ Treg, while no significant phenotypical differences were observed in Treg subpopulations between patients and controls. However, a lower anti-proliferative capacity was observed in activated Treg of MS patients compared with those of controls (p<0.05), while suppression of activation was similar to controls. Gene set enrichment analysis (GSEA) of microarray data revealed enrichment for the GO gene set ‘chemokine receptor binding’ in MS Treg.CONCLUSION Although numerical phenotypical assessment of resting and activated Tregs did not reveal any significant difference between patients and controls, functional co-culturing experiments showed an impaired function in activated Treg of MS patients. Furthermore, GSEA revealed immune-related gene sets overexpressed in Treg of MS patients, possibly containing clues to the functional impairment. In particular over-activity in chemokine signalling in Treg would be of interest for further investigation.
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| 8. |
- Gawel, Danuta, et al.
(författare)
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The Allergic Airway Inflammation Repository - a user-friendly, curated resource of mRNA expression levels in studies of allergic airways
- 2014
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Ingår i: Allergy. European Journal of Allergy and Clinical Immunology. - : Wiley. - 0105-4538 .- 1398-9995. ; 69:8, s. 1115-1117
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Tidskriftsartikel (refereegranskat)abstract
- Public microarray databases allow analysis of expression levels of candidate genes in different contexts. However, finding relevant microarray data is complicated by the large number of available studies. We have compiled a user-friendly, open-access database of mRNA microarray experiments relevant to allergic airway inflammation, the Allergic Airway Inflammation Repository (AAIR, http://aair.cimed.ike.liu.se/). The aim is to allow allergy researchers to determine the expression profile of their genes of interest in multiple clinical data sets and several experimental systems quickly and intuitively. AAIR also provides quick links to other relevant information such as experimental protocols, related literature and raw data files.
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| 9. |
- Gustafsson, Mika, 1977-, et al.
(författare)
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Gene Expression Prediction by Soft Integration and the Elastic Net : Best Performance of the DREAM3 Gene Expression Challenge
- 2010
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 5:2, s. e9134-
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Tidskriftsartikel (refereegranskat)abstract
- Background: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance.Methodology/Principal Findings: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the “elastic net”. Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance.Conclusions/Significance: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.
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| 10. |
- Gustafsson, Mika, 1977-
(författare)
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Gene networks from high-throughput data : Reverse engineering and analysis
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Experimental innovations starting in the 1990’s leading to the advent of high-throughput experiments in cellular biology have made it possible to measure thousands of genes simultaneously at a modest cost. This enables the discovery of new unexpected relationships between genes in addition to the possibility of falsify existing. To benefit as much as possible from these experiments the new inter disciplinary research field of systems biology have materialized. Systems biology goes beyond the conventional reductionist approach and aims at learning the whole system under the assumption that the system is greater than the sum of its parts. One emerging enterprise in systems biology is to use the high-throughput data to reverse engineer the web of gene regulatory interactions governing the cellular dynamics. This relatively new endeavor goes further than clustering genes with similar expression patterns and requires the separation of cause of gene expression from the effect. Despite the rapid data increase we then face the problem of having too few experiments to determine which regulations are active as the number of putative interactions has increased dramatic as the number of units in the system has increased. One possibility to overcome this problem is to impose more biologically motivated constraints. However, what is a biological fact or not is often not obvious and may be condition dependent. Moreover, investigations have suggested several statistical facts about gene regulatory networks, which motivate the development of new reverse engineering algorithms, relying on different model assumptions. As a result numerous new reverse engineering algorithms for gene regulatory networks has been proposed. As a consequent, there has grown an interest in the community to assess the performance of different attempts in fair trials on “real” biological problems. This resulted in the annually held DREAM conference which contains computational challenges that can be solved by the prosing researchers directly, and are evaluated by the chairs of the conference after the submission deadline.This thesis contains the evolution of regularization schemes to reverse engineer gene networks from high-throughput data within the framework of ordinary differential equations. Furthermore, to understand gene networks a substantial part of it also concerns statistical analysis of gene networks. First, we reverse engineer a genome-wide regulatory network based solely on microarray data utilizing an extremely simple strategy assuming sparseness (LASSO). To validate and analyze this network we also develop some statistical tools. Then we present a refinement of the initial strategy which is the algorithm for which we achieved best performer at the DREAM2 conference. This strategy is further refined into a reverse engineering scheme which also can include external high-throughput data, which we confirm to be of relevance as we achieved best performer in the DREAM3 conference as well. Finally, the tools we developed to analyze stability and flexibility in linearized ordinary differential equations representing gene regulatory networks is further discussed.
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