178 research outputs found

    Allele-specific expression changes dynamically during T cell activation in HLA and other autoimmune loci

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    © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc. Genetic studies have revealed that autoimmune susceptibility variants are over-represented in memory CD4+ T cell regulatory elements1–3. Understanding how genetic variation affects gene expression in different T cell physiological states is essential for deciphering genetic mechanisms of autoimmunity4,5. Here, we characterized the dynamics of genetic regulatory effects at eight time points during memory CD4+ T cell activation with high-depth RNA-seq in healthy individuals. We discovered widespread, dynamic allele-specific expression across the genome, where the balance of alleles changes over time. These genes were enriched fourfold within autoimmune loci. We found pervasive dynamic regulatory effects within six HLA genes. HLA-DQB1 alleles had one of three distinct transcriptional regulatory programs. Using CRISPR–Cas9 genomic editing we demonstrated that a promoter variant is causal for T cell–specific control of HLA-DQB1 expression. Our study shows that genetic variation in cis-regulatory elements affects gene expression in a manner dependent on lymphocyte activation status, contributing to the interindividual complexity of immune responses

    Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies

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    Summary: Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols

    Disordered T cell-B cell interactions in autoantibody-positive inflammatory arthritis

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    T peripheral helper (Tph) cells, identified in the synovium of adults with seropositive rheumatoid arthritis, drive B cell maturation and antibody production in non-lymphoid tissues. We sought to determine if similarly dysregulated T cell-B cell interactions underlie another form of inflammatory arthritis, juvenile oligoarthritis (oligo JIA). Clonally expanded Tph cells able to promote B cell antibody production preferentially accumulated in the synovial fluid (SF) of oligo JIA patients with antinuclear antibodies (ANA) compared to autoantibody-negative patients. Single-cell transcriptomics enabled further definition of the Tph gene signature in inflamed tissues and showed that Tph cells from ANA-positive patients upregulated genes associated with B cell help to a greater extent than patients without autoantibodies. T cells that co-expressed regulatory T and B cell-help factors were identified. The phenotype of these Tph-like Treg cells suggests an ability to restrain T cell-B cell interactions in tissues. Our findings support the central role of disordered T cell-help to B cells in autoantibody-positive arthritides

    Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription.

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    DNA sequence variation has been associated with quantitative changes in molecular phenotypes such as gene expression, but its impact on chromatin states is poorly characterized. To understand the interplay between chromatin and genetic control of gene regulation, we quantified allelic variability in transcription factor binding, histone modifications, and gene expression within humans. We found abundant allelic specificity in chromatin and extensive local, short-range, and long-range allelic coordination among the studied molecular phenotypes. We observed genetic influence on most of these phenotypes, with histone modifications exhibiting strong context-dependent behavior. Our results implicate transcription factors as primary mediators of sequence-specific regulation of gene expression programs, with histone modifications frequently reflecting the primary regulatory event

    Methylation QTLs in the developing brain and their enrichment in schizophrenia risk loci

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    We characterized DNA methylation quantitative trait loci (mQTLs) in a large collection (n = 166) of human fetal brain samples spanning 56-166 d post-conception, identifying >16,000 fetal brain mQTLs. Fetal brain mQTLs were primarily cis-acting, enriched in regulatory chromatin domains and transcription factor binding sites, and showed substantial overlap with genetic variants that were also associated with gene expression in the brain. Using tissue from three distinct regions of the adult brain (prefrontal cortex, striatum and cerebellum), we found that most fetal brain mQTLs were developmentally stable, although a subset was characterized by fetal-specific effects. Fetal brain mQTLs were enriched amongst risk loci identified in a recent large-scale genome-wide association study (GWAS) of schizophrenia, a severe psychiatric disorder with a hypothesized neurodevelopmental component. Finally, we found that mQTLs can be used to refine GWAS loci through the identification of discrete sites of variable fetal brain methylation associated with schizophrenia risk variants

    Comparative analysis of distinct phenotypes in gambling disorder based on gambling preferences

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    Background: Studies examining gambling preferences have identified the importance of the type of gambling practiced on distinct individual profiles. The objectives were to compare clinical, psychopathological and personality variables between two different groups of individuals with a gambling disorder (strategic and non-strategic gamblers) and to evaluate the statistical prediction capacity of these preferences with respect to the severity of the disorder. Method: A total sample of 2010 treatment-seeking patients with a gambling disorder participated in this stand-alone study. All were recruited from a single Pathological Gambling Unit in Spain (1709 strategic and 301 non-strategic gamblers). The design of the study was cross-sectional and data were collected at the start of treatment. Data was analysed using logistic regression for binary outcomes and analysis of variance (ANOVA) for quantitative responses. Results: There were significant differences in several socio-demographic and clinical variables, as well as in personality traits (novelty seeking and cooperativeness). Multiple regression analysis showed harm avoidance and self-directedness were the main predictors of gambling severity and psychopathology, while age at assessment and age of onset of gambling behaviour were predictive of gambling severity. Strategic gambling (as opposed to non-strategic) was significantly associated with clinical outcomes, but the effect size of the relationships was small. Conclusions: It is possible to identify distinct phenotypes depending on the preference of gambling. While these phenotypes differ in relation to the severity of the gambling disorder, psychopathology and personality traits, they can be useful from a clinical and therapeutic perspective in enabling risk factors to be identified and prevention programs targeting specific individual profiles to be developed
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