Follow-up examination of linkage and association to chromosome 1q43 in multiple sclerosis.

Multiple sclerosis (MS) is a debilitating neuroimmunological and neurodegenerative disease affecting >4,00,000 individuals in the United States. Population and family-based studies have suggested that there is a strong genetic component. Numerous genomic linkage screens have identified regions of interest for MS loci. Our own second-generation genome-wide linkage study identified a handful of non-major histocompatibility complex regions with suggestive linkage. Several of these regions were further examined using single-nucleotide polymorphisms (SNPs) with average spacing between SNPs of approximately 1.0 Mb in a dataset of 173 multiplex families. The results of that study provided further evidence for the involvement of the chromosome 1q43 region. This region is of particular interest given linkage evidence in studies of other autoimmune and inflammatory diseases including rheumatoid arthritis and systemic lupus erythematosus. In this follow-up study, we saturated the region with approximately 700 SNPs (average spacing of 10 kb per SNP) in search of disease-associated variation within this region. We found preliminary evidence to suggest that common variation within the RGS7 locus may be involved in disease susceptibility

Evidence of novel finescale structural variation at autism spectrum disorder candidate loci

Background: Autism spectrum disorders (ASD) represent a group of neurodevelopmental disorders characterized by a core set of social-communicative and behavioral impairments. Gamma-aminobutyric acid (GABA) is the major inhibitory neurotransmitter in the brain, acting primarily via the GABA receptors (GABR). Multiple lines of evidence, including altered GABA and GABA receptor expression in autistic patients, indicate that the GABAergic system may be involved in the etiology of autism. Methods: As copy number variations (CNVs), particularly rare and de novo CNVs, have now been implicated in ASD risk, we examined the GABA receptors and genes in related pathways for structural variation that may be associated with autism. We further extended our candidate gene set to include 19 genes and regions that had either been directly implicated in the autism literature or were directly related (via function or ancestry) to these primary candidates. For the high resolution CNV screen we employed custom-designed 244 k comparative genomic hybridization (CGH) arrays. Collectively, our probes spanned a total of 11 Mb of GABA-related and additional candidate regions with a density of approximately one probe every 200 nucleotides, allowing a theoretical resolution for detection of CNVs of approximately 1 kb or greater on average. One hundred and sixty-eight autism cases and 149 control individuals were screened for structural variants. Prioritized CNV events were confirmed using quantitative PCR, and confirmed loci were evaluated on an additional set of 170 cases and 170 control individuals that were not included in the original discovery set. Loci that remained interesting were subsequently screened via quantitative PCR on an additional set of 755 cases and 1,809 unaffected family members. Results: Results include rare deletions in autistic individuals at JAKMIP1, NRXN1, Neuroligin4Y, OXTR, and ABAT. Common insertion/deletion polymorphisms were detected at several loci, including GABBR2 and NRXN3. Overall, statistically significant enrichment in affected vs. unaffected individuals was observed for NRXN1 deletions. Conclusions: These results provide additional support for the role of rare structural variation in ASD

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. © 2014 Erwin et al

High-density mapping of the MHC identifies a shared role for HLA-DRB1*01:03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis.

This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/ng/journal/v47/n2/full/ng.3176.html#acknowledgmentsGenome-wide association studies of the related chronic inflammatory bowel diseases (IBD) known as Crohn's disease and ulcerative colitis have shown strong evidence of association to the major histocompatibility complex (MHC). This region encodes a large number of immunological candidates, including the antigen-presenting classical human leukocyte antigen (HLA) molecules. Studies in IBD have indicated that multiple independent associations exist at HLA and non-HLA genes, but they have lacked the statistical power to define the architecture of association and causal alleles. To address this, we performed high-density SNP typing of the MHC in >32,000 individuals with IBD, implicating multiple HLA alleles, with a primary role for HLA-DRB1*01:03 in both Crohn's disease and ulcerative colitis. Noteworthy differences were observed between these diseases, including a predominant role for class II HLA variants and heterozygous advantage observed in ulcerative colitis, suggesting an important role of the adaptive immune response in the colonic environment in the pathogenesis of IBD.We would like to thank the International PSC study group (http://www.ipscsg.org/) for sharing data. We are grateful to B.A. Lie and K. Holm for helpful discussions. J.D.R. holds a Canada Research Chair, and this work was supported by a US National Institute of Diabetes and Digestive and Kidney Diseases grant (NIDDK; R01 DK064869 and U01 DK062432). The laboratory of A.F. is supported by the German Ministry of Education and Research (BMBF) grant program e:Med (sysINFLAME). A.F. receives infrastructure support from the Deutsche Forschungsgemeinschaft (DFG) Cluster of Excellence 'Inflammation at Interfaces' and holds an endowment professorship (Peter Hans Hofschneider Professorship) of the Foundation for Experimental Biomedicine (Zurich, Switzerland). Grant support for T.H.K. and A.F. was received from the European Union Seventh Framework Programme (FP7/2007-2013, grant number 262055, ESGI). M.N.C. is supported by the Intramural Research Program of the US National Institutes of Health (NIH), Frederick National Laboratory, Center for Cancer Research. This project has been funded in whole or in part with federal funds from the Frederick National Laboratory for Cancer Research, under contract HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the US Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US government. J.C.B. was supported by a Wellcome Trust grant (WT098051). D.M. and V.K. are supported by the NIHR Cambridge Biomedical Research Centre. L.P.S. is supported by an NIDDK grant (U01 DK062429-14). J.A.T. is supported by the UK Medical Research Council. D.P.B.M. is supported by the Leona M. and Harry B. Helmsley Charitable Trust, the European Union (305479) and by grants from the NIDDK (U01 DK062413, P01 DK046763-19, U54 DE023789-01), the National Institute of Allergy and Infectious Diseases (NIAID; U01 AI067068) and the Agency for Healthcare Research and Quality (AHRQ; HS021747). R.H.D. holds the Inflammatory Bowel Disease Genetic Research endowed chair at the University of Pittsburgh and was supported by an NIDDK grant (U01 DK062420) and a US National Cancer Institute grant (CA141743). S.L.H. and J.R.O. would like to also acknowledge the support of the US NIH (R01 NS049477 and 1U19 A1067152) and the National Multiple Sclerosis Society (RG 2899-D11). S.L. wishes to acknowledge support from the Australian National Health and Medical Research Council (R.D. Wright Career Development Fellowship, APP1053756)

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

Transancestral mapping and genetic load in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease with marked gender and ethnic disparities. We report a large transancestral association study of SLE using Immunochip genotype data from 27,574 individuals of European (EA), African (AA) and Hispanic Amerindian (HA) ancestry. We identify 58 distinct non-HLA regions in EA, 9 in AA and 16 in HA (∼50% of these regions have multiple independent associations); these include 24 novel SLE regions (P<5 × 10-8), refined association signals in established regions, extended associations to additional ancestries, and a disentangled complex HLA multigenic effect. The risk allele count (genetic load) exhibits an accelerating pattern of SLE risk, leading us to posit a cumulative hit hypothesis for autoimmune disease. Comparing results across the three ancestries identifies both ancestry-dependent and ancestry-independent contributions to SLE risk. Our results are consistent with the unique and complex histories of the populations sampled, and collectively help clarify the genetic architecture and ethnic disparities in SLE.info:eu-repo/semantics/publishedVersio

DQB1*0602 rather than DRB1*1501 confers susceptibility to multiple sclerosis-like disease induced by proteolipid protein (PLP)

<p>Abstract</p> <p>Background</p> <p>Multiple sclerosis (MS) is associated with pathogenic autoimmunity primarily focused on major CNS-myelin target antigens including myelin basic protein (MBP), proteolipidprotein (PLP), myelin oligodendrocyte protein (MOG). MS is a complex trait whereby the HLA genes, particularly class-II genes of HLA-DR15 haplotype, dominate the genetic contribution to disease-risk. Due to strong linkage disequilibrium in HLA-II region, it has been hard to establish precisely whether the functionally relevant effect derives from the DRB1*1501, DQA1*0102-DQB1*0602, or DRB5*0101 loci of HLA-DR15 haplotype, their combinations, or their epistatic interactions. Nevertheless, most genetic studies have indicated DRB1*1501 as a primary risk factor in MS. Here, we used 'HLA-humanized' mice to discern the potential relative contribution of DRB1*1501 and DQB1*0602 alleles to susceptibility to "humanized" MS-like disease induced by PLP, one of the most prominent and encephalitogenic target-antigens implicated in human MS.</p> <p>Methods</p> <p>The HLA-DRB1*1501- and HLA-DQB1*0602-Tg mice (MHC-II^-/-), and control non-HLA-DR15-relevant-Tg mice were immunized with a set of overlapping PLP peptides or with recombinant soluble PLP for induction of "humanized" MS-like disease, as well as for ex-vivo analysis of immunogenic/immunodominant HLA-restricted T-cell epitopes and associated cytokine secretion profile.</p> <p>Results</p> <p>PLP autoimmunity in both HLA-DR15-Tg mice was focused on 139-151 and 175-194 epitopes. Strikingly, however, the HLA-DRB1*1501-transgenics were refractory to disease induction by any of the overlapping PLP peptides, while HLA-DQB1*0602 transgenics were susceptible to disease induction by PLP139-151 and PLP175-194 peptides. Although both transgenics responded to both peptides, the PLP139-151- and PLP175-194-reactive T-cells were directed to Th1/Th17 phenotype in DQB1*0602-Tg mice and towards Th2 in DRB1*1501-Tg mice.</p> <p>Conclusions</p> <p>While genome studies map a strong MS susceptibility effect to the region of DRB1*1501, our findings offer a rationale for potential involvement of pathogenic DQ6-associated autoimmunity in MS. Moreover, that DQB1*0602, but not DRB1*1501, determines disease-susceptibility to PLP in HLA-transgenics, suggests a potential differential, functional role for DQB1*0602 as a predisposing allele in MS. This, together with previously demonstrated disease-susceptibility to MBP and MOG in DRB1*1501-transgenics, also suggests a differential role for DRB1*1501 and DQB1*0602 depending on target antigen and imply a potential complex 'genotype/target antigen/phenotype' relationship in MS heterogeneity.</p

The genetic basis of multiple sclerosis: a model for MS susceptibility

<p>Abstact</p> <p>Background</p> <p>MS-pathogenesis is known to involve both multiple environmental events, and several independent genetic risk-factors.</p> <p>Methods</p> <p>A model of susceptibility is developed and a mathematical analysis undertaken to elucidate the nature of genetic susceptibility to MS and to understand the constraints that are placed on the genetic basis of MS, both by the known epidemiological facts of this disease and by the known frequency of the HLA DRB1*1501 allele in the general populations of northern Europe and North America.</p> <p>Results</p> <p>For the large majority of cases (possibly all), MS develops, in part, because an individual is genetically susceptible. Nevertheless, 2.2% or less of the general population is genetically susceptible. Moreover, from the model, the number of susceptibility-loci that need to be in a "susceptible allelic state" to produce MS-susceptibility is small (11-18), whereas the total number of such susceptibility-loci is large (50-200), and their "frequency of susceptibility" is low (i.e., ≤ 0.12). The optimal solution to the model equations (which occurs when 80% of the loci are recessive) predicts the epidemiological data quite closely.</p> <p>Conclusions</p> <p>The model suggests that combinations of only a small number of genetic loci in a "susceptible allelic state" produce MS-susceptibility. Nevertheless, genome-wide associations studies with hundreds of thousands of SNPs, are plagued by both false-positive and false-negative identifications and, consequently, emphasis has been rightly placed on the replicability of findings. Nevertheless, because genome-wide screens don't distinguish between true susceptibility-loci and disease-modifying-loci, and because only true susceptibility-loci are constrained by the model, unraveling the two will not be possible using this approach.</p> <p>The model also suggests that HLA DRB1 may not be as uniquely important for MS-susceptibility as currently believed. Thus, this allele is only one among a hundred or more loci involved in MS susceptibility. Even though the "frequency of susceptibility" at the HLA DRB1 locus is four-fold that of other loci, the penetrance of those susceptible genotypes that include this allele is no different from those that don't. Also, almost 50% of genetically-susceptible individuals, lack this allele. Moreover, of those who have it, only a small fraction (≤ 5.2%) are even susceptible to getting MS.</p

Towards Universal Structure-Based Prediction of Class II MHC Epitopes for Diverse Allotypes

The binding of peptide fragments of antigens to class II MHC proteins is a crucial step in initiating a helper T cell immune response. The discovery of these peptide epitopes is important for understanding the normal immune response and its misregulation in autoimmunity and allergies and also for vaccine design. In spite of their biomedical importance, the high diversity of class II MHC proteins combined with the large number of possible peptide sequences make comprehensive experimental determination of epitopes for all MHC allotypes infeasible. Computational methods can address this need by predicting epitopes for a particular MHC allotype. We present a structure-based method for predicting class II epitopes that combines molecular mechanics docking of a fully flexible peptide into the MHC binding cleft followed by binding affinity prediction using a machine learning classifier trained on interaction energy components calculated from the docking solution. Although the primary advantage of structure-based prediction methods over the commonly employed sequence-based methods is their applicability to essentially any MHC allotype, this has not yet been convincingly demonstrated. In order to test the transferability of the prediction method to different MHC proteins, we trained the scoring method on binding data for DRB1*0101 and used it to make predictions for multiple MHC allotypes with distinct peptide binding specificities including representatives from the other human class II MHC loci, HLA-DP and HLA-DQ, as well as for two murine allotypes. The results showed that the prediction method was able to achieve significant discrimination between epitope and non-epitope peptides for all MHC allotypes examined, based on AUC values in the range 0.632–0.821. We also discuss how accounting for peptide binding in multiple registers to class II MHC largely explains the systematically worse performance of prediction methods for class II MHC compared with those for class I MHC based on quantitative prediction performance estimates for peptide binding to class II MHC in a fixed register