Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants

Cell Specific eQTL Analysis without Sorting Cells

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus

Characterization of Structural Features Controlling the Receptiveness of Empty Class II MHC Molecules

MHC class II molecules (MHC II) play a pivotal role in the cell-surface presentation of antigens for surveillance by T cells. Antigen loading takes place inside the cell in endosomal compartments and loss of the peptide ligand rapidly leads to the formation of a non-receptive state of the MHC molecule. Non-receptiveness hinders the efficient loading of new antigens onto the empty MHC II. However, the mechanisms driving the formation of the peptide inaccessible state are not well understood. Here, a combined approach of experimental site-directed mutagenesis and computational modeling is used to reveal structural features underlying “non-receptiveness.” Molecular dynamics simulations of the human MHC II HLA-DR1 suggest a straightening of the α-helix of the β1 domain during the transition from the open to the non-receptive state. The movement is mostly confined to a hinge region conserved in all known MHC molecules. This shift causes a narrowing of the two helices flanking the binding site and results in a closure, which is further stabilized by the formation of a critical hydrogen bond between residues αQ9 and βN82. Mutagenesis experiments confirmed that replacement of either one of the two residues by alanine renders the protein highly susceptible. Notably, loading enhancement was also observed when the mutated MHC II molecules were expressed on the surface of fibroblast cells. Altogether, structural features underlying the non-receptive state of empty HLA-DR1 identified by theoretical means and experiments revealed highly conserved residues critically involved in the receptiveness of MHC II. The atomic details of rearrangements of the peptide-binding groove upon peptide loss provide insight into structure and dynamics of empty MHC II molecules and may foster rational approaches to interfere with non-receptiveness. Manipulation of peptide loading efficiency for improved peptide vaccination strategies could be one of the applications profiting from the structural knowledge provided by this study

Type I Interferon Drives Dendritic Cell Apoptosis via Multiple BH3-Only Proteins following Activation by PolyIC In Vivo

BACKGROUND: DC are activated by pathogen-associated molecular patterns (PAMPs), and this is pivotal for the induction of adaptive immune responses. Thereafter, the clearance of activated DC is crucial to prevent immune pathology. While PAMPs are of major interest for vaccine science due to their adjuvant potential, it is unclear whether and how PAMPs may affect DC viability. We aimed to elucidate the possible apoptotic mechanisms that control activated DC lifespan in response to PAMPs, particularly in vivo. METHODOLOGY/PRINCIPAL FINDINGS: We report that polyinosinic:polycytidylic acid (PolyIC, synthetic analogue of dsRNA) induces dramatic apoptosis of mouse splenic conventional DC (cDC) in vivo, predominantly affecting the CD8α subset, as shown by flow cytometry-based analysis of splenic DC subsets. Importantly, while Bim deficiency conferred only minor protection, cDC depletion was prevented in mice lacking Bim plus one of three other BH3-only proteins, either Puma, Noxa or Bid. Furthermore, we show that Type I Interferon (IFN) is necessary and sufficient for DC death both in vitro and in vivo, and that TLR3 and MAVS co-operate in IFNß production in vivo to induce DC death in response to PolyIC. CONCLUSIONS/SIGNIFICANCE: These results demonstrate for the first time in vivo that apoptosis restricts DC lifespan following activation by PolyIC, particularly affecting the CD8α cDC subset. Such DC apoptosis is mediated by the overlapping action of pro-apoptotic BH3-only proteins, including but not solely involving Bim, and is driven by Type I IFN. While Type I IFNs are important anti-viral factors, CD8α cDC are major cross-presenting cells and critical inducers of CTL. We discuss such paradoxical finding on DC death with PolyIC/Type I IFN. These results could contribute to understand immunosuppression associated with chronic infection, and to the optimization of DC-based therapies and the clinical use of PAMPs and Type I IFNs

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes for brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top-associated cis-expression or -DNA methylation (DNAm) quantitative trait loci (cis-eQTLs or cis-mQTLs) between brain and blood (r b ). Using publicly available data, we find that genetic effects at the top cis-eQTLs or mQTLs are highly correlated between independent brain and blood samples (r b = 0.70 for cis-eQTLs and r ^ b = 0.78 for cis-mQTLs). Using meta-analyzed brain cis-eQTL/mQTL data (n = 526 to 1194), we identify 61 genes and 167 DNAm sites associated with four brain-related phenotypes, most of which are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = 1980 to 14,115). Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL/mQTL data with large sample sizes. © 2018 The Author(s).Peer reviewe

Active Suppression Induced by Repetitive Self-Epitopes Protects against EAE Development

<div><p>Background</p><p>Autoimmune diseases result from a breakdown in self-tolerance to autoantigens. Self-tolerance is induced and sustained by central and peripheral mechanisms intended to deviate harmful immune responses and to maintain homeostasis, where regulatory T cells play a crucial role. The use of self-antigens in the study and treatment of a range of autoimmune diseases has been widely described; however, the mechanisms underlying the induced protection by these means are unclear. This study shows that protection of experimental autoimmune disease induced by T cell self-epitopes in a multimerized form (oligomers) is mediated by the induction of active suppression.</p><p>Principal Findings</p><p>The experimental autoimmune encephalomyelitis (EAE) animal model for multiple sclerosis was used to study the mechanisms of protection induced by the treatment of oligomerized T cell epitope of myelin proteolipid protein (PLP_139–151). Disease protection attained by the administration of oligomers was shown to be antigen specific and effective in both prevention and treatment of ongoing EAE. Oligomer mediated tolerance was actively transferred by cells from treated mice into adoptive hosts. The induction of active suppression was correlated with the recruitment of cells in the periphery associated with increased production of IL-10 and reduction of the pro-inflammatory cytokine TNF-α. The role of suppressive cytokines was demonstrated by the reversion of oligomer-induced protection after <i>in vivo</i> blocking of either IL-10 or TGF-β cytokines.</p><p>Conclusions</p><p>This study strongly supports an immunosuppressive role of repeat auto-antigens to control the development of EAE with potential applications in vaccination and antigen specific treatment of autoimmune diseases.</p></div

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Abstract Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes

Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Abstract Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene–trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits