Showing papers by "Bengt Sennblad published in 2014"
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TL;DR: In this paper, the authors aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry.
Abstract: To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
954 citations
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TL;DR: A Bayesian Markov-chain Monte Carlo-based method is presented that integrates GD, gene loss, LGT, and sequence evolution, and is applied in a genome-wide analysis of two groups of bacteria: Mollicutes and Cyanobacteria.
Abstract: Lateral gene transfer (LGT)—which transfers DNA between two non-vertically related individuals belonging to the same or different species—is recognized as a major force in prokaryotic evolution, and evidence of its impact on eukaryotic evolution is ever increasing. LGT has attracted much public attention for its potential to transfer pathogenic elements and antibiotic resistance in bacteria, and to transfer pesticide resistance from genetically modified crops to other plants. In a wider perspective, there is a growing body of studies highlighting the role of LGT in enabling organisms to occupy new niches or adapt to environmental changes. The challenge LGT poses to the standard tree-based conception of evolution is also being debated. Studies of LGT have, however, been severely limited by a lack of computational tools. The best currently available LGT algorithms are parsimony-based phylogenetic methods, which require a pre-computed gene tree and cannot choose between sometimes wildly differing most parsimonious solutions. Moreover, in many studies, simple heuristics are applied that can only handle putative orthologs and completely disregard gene duplications (GDs). Consequently, proposed LGT among specific gene families, and the rate of LGT in general, remain debated. We present a Bayesian Markov-chain Monte Carlo-based method that integrates GD, gene loss, LGT, and sequence evolution, and apply the method in a genome-wide analysis of two groups of bacteria: Mollicutes and Cyanobacteria. Our analyses show that although the LGT rate between distant species is high, the net combined rate of duplication and close-species LGT is on average higher. We also show that the common practice of disregarding reconcilability in gene tree inference overestimates the number of LGT and duplication events. (Bayesian; gene duplication; gene loss; horizontal gene transfer; lateral gene transfer; MCMC; phylogenetics.)
89 citations
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TL;DR: Further evidence of involvement of autoantibodies against native and MDA-modified apoB-100 peptide 210 in cardiovascular disease in humans is provided and it is demonstrated that these associations are present already at a subclinical stage of the disease.
29 citations
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TL;DR: Low anti-PC levels increase the risk of CVE in men, and this effect may be partly mediated by a fast C-IMT progression, as well as conventional cardiovascular risk factors.
29 citations
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Wellcome Trust Sanger Institute1, University of Washington2, Karolinska Institutet3, Harvard University4, Leiden University5, University of Edinburgh6, University of Texas Health Science Center at Houston7, University of Greifswald8, University of Minnesota9, St George's, University of London10, VU University Amsterdam11, National Institutes of Health12, Aix-Marseille University13, University of Glasgow14, University College Cork15, Greifswald University Hospital16, University of Oxford17, Ludwig Maximilian University of Munich18, University of Augsburg19, Cedars-Sinai Medical Center20, Boston University21, Erasmus University Rotterdam22, University of Helsinki23, University of Split24, University of Bristol25, Mario Negri Institute for Pharmacological Research26, Hannover Medical School27, University of Auckland28, University of Sydney29, University of Münster30, University of Ulm31, Northwestern University32, University of Paris33, Veterans Health Administration34
TL;DR: This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations.
Abstract: Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2×10−8. This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.
11 citations