HLA and other tales: The different perspectives of Celiac Disease

Auto-immuun ziekten zijn het resultaat van een abnormale reactie van het immuunsysteem op lichaamseigen stoffen die leidt tot aantasting van cellen en weefsels. De kennis over deze ziekten is enorm gegroeid door de ontwikkeling van nieuwe technologieën en analysemethodes vanuit de humane genetica. Dit proefschrift beschrijft verschillende genetische analyses rondom de auto-immuun ziekte coeliakie. We beschrijven een gedetailleerde analyse van het HLA locus, dat een zeer belangrijke genomische regio is voor het immuun systeem. Door het gebruik van nieuwe analytische methodes hebben we nieuwe onafhankelijke associaties van varianten geïdentificeerd in HLA regio’s buiten de regio’s die al eerder met coeliakie geassocieerd waren. Daarnaast schatten we dat de HLA regio een groot deel van de variantie van de erfelijkheid voor coeliakie verklaart (~25%). We analyseren ook de genetische associaties binnen een populatie van Zuid-Aziatische oorsprong. Naast de bevestiging van al bestaande associaties, leverde deze studie ook aanwijzingen op voor nieuwe genetische regio’s die een rol spelen bij coeliakie. Deze analyse demonstreert dus het belang van nieuwe analyses op grote schaal in niet-Europese populaties ten behoeve van het verkrijgen van nieuwe inzichten in de biologie van complexe ziekten. Daarnaast analyseren we de resultaten van genetische studies van coeliakie tezamen met twee andere auto-immuun ziekten (type 1 diabetes en reumatoïde artritis). Deze analyse toont aan dat de genetische factoren voor individuen met dubbele auto-immuniteit (coeliakie en type 1 diabetes) meer lijken op de genetische factoren die type 1 diabetes veroorzaken (in het bijzonder in de HLA regio). De analyse van coeliakie en reumatoïde artritis identificeerde loci met een unieke karakteristiek: ondanks dat varianten in deze loci zijn gelokaliseerd, zijn varianten binnen deze loci onafhankelijk geassocieerd met coeliakie óf reumatoïde artritis en veroorzaken zij verschillende effecten op genexpressie

Зависимость свойств толстопленочных терморезисторов от состава базовой шпинели

Изменением соотношения компонентов шпинели Cu1-x-yCo2yMn2-yO4 получены толстопленочные терморезисторы с удельным объемным электросопротивлением 1,5-33 Омм и тепловой константой В25/85 2980-3690 К

Fine mapping of the celiac disease-associated LPP locus reveals a potential functional variant

Transplantation and immunomodulatio

Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants

Background: The majority of coeliac disease (CD) patients are not being properly diagnosed and therefore remain untreated, leading to a greater risk of developing CD-associated complications. The major genetic risk heterodimer, HLA-DQ2 and DQ8, is already used clinically to help exclude disease. However, approximately 40% of the population carry these alleles and the majority never develop CD. Objective: We explored whether CD risk prediction can be improved by adding non-HLA-susceptible variants to common HLA testing. Design: We developed an average weighted genetic risk score with 10, 26 and 57 single nucleotide polymorphisms (SNP) in 2675 cases and 2815 controls and assessed the improvement in risk prediction provided by the non-HLA SNP. Moreover, we assessed the transferability of the genetic risk model with 26 non-HLA variants to a nested case–control population (n=1709) and a prospective cohort (n=1245) and then tested how well this model predicted CD outcome for 985 independent individuals. Results: Adding 57 non-HLA variants to HLA testing showed a statistically significant improvement compared to scores from models based on HLA only, HLA plus 10 SNP and HLA plus 26 SNP. With 57 non-HLA variants, the area under the receiver operator characteristic curve reached 0.854 compared to 0.823 for HLA only, and 11.1% of individuals were reclassified to a more accurate risk group. We show that the risk model with HLA plus 26 SNP is useful in independent populations. Conclusions: Predicting risk with 57 additional non-HLA variants improved the identification of potential CD patients. This demonstrates a possible role for combined HLA and non-HLA genetic testing in diagnostic work for CD

Refined mapping of autoimmune disease associated genetic variants with gene expression suggests an important role for non-coding RNAs

Genome-wide association and fine-mapping studies in 14 autoimmune diseases (AID) have implicated more than 250 loci in one or more of these diseases. As more than 90% of AID-associated SNPs are intergenic or intronic, pinpointing the causal genes is challenging. We performed a systematic analysis to link 460 SNPs that are associated with 14 AID to causal genes using transcriptomic data from 629 blood samples. We were able to link 71 (39%) of the AID-SNPs to two or more nearby genes, providing evidence that for part of the AID loci multiple causal genes exist. While 54 of the AID loci are shared by one or more AID, 17% of them do not share candidate causal genes. In addition to finding novel genes such as ULK3, we also implicate novel disease mechanisms and pathways like autophagy in celiac disease pathogenesis. Furthermore, 42 of the AID SNPs specifically affected the expression of 53 non-coding RNA genes. To further understand how the non-coding genome contributes to AID, the SNPs were linked to functional regulatory elements, which suggest a model where AID genes are regulated by network of chromatin looping/non-coding RNAs interactions. The looping model also explains how a causal candidate gene is not necessarily the gene closest to the AID SNP, which was the case in nearly 50% of cases

Improved imputation quality of low-frequency and rare variants in European samples using the 'Genome of the Netherlands'

Although genome-wide association studies (GWAS) have identified many common variants associated with complex traits, low-frequency and rare variants have not been interrogated in a comprehensive manner. Imputation from dense reference panels, such as the 1000 Genomes Project (1000G), enables testing of ungenotyped variants for association. Here we present the results of imputation using a large, new population-specific panel: the Genome of The Netherlands (GoNL). We benchmarked the performance of the 1000G and GoNL reference sets by comparing imputation genotypes with 'true' genotypes typed on ImmunoChip in three European populations (Dutch, British, and Italian). GoNL showed significant improvement in the imputation quality for rare variants (MAF 0.05-0.5%) compared with 1000G. In Dutch samples, the mean observed Pearson correlation, r 2, increased from 0.61 to 0.71. W

Meta-analysis of Immunochip data of four autoimmune diseases reveals novel single-disease and cross-phenotype associations.

BACKGROUND: In recent years, research has consistently proven the occurrence of genetic overlap across autoimmune diseases, which supports the existence of common pathogenic mechanisms in autoimmunity. The objective of this study was to further investigate this shared genetic component. METHODS: For this purpose, we performed a cross-disease meta-analysis of Immunochip data from 37,159 patients diagnosed with a seropositive autoimmune disease (11,489 celiac disease (CeD), 15,523 rheumatoid arthritis (RA), 3477 systemic sclerosis (SSc), and 6670 type 1 diabetes (T1D)) and 22,308 healthy controls of European origin using the R package ASSET. RESULTS: We identified 38 risk variants shared by at least two of the conditions analyzed, five of which represent new pleiotropic loci in autoimmunity. We also identified six novel genome-wide associations for the diseases studied. Cell-specific functional annotations and biological pathway enrichment analyses suggested that pleiotropic variants may act by deregulating gene expression in different subsets of T cells, especially Th17 and regulatory T cells. Finally, drug repositioning analysis evidenced several drugs that could represent promising candidates for CeD, RA, SSc, and T1D treatment. CONCLUSIONS: In this study, we have been able to advance in the knowledge of the genetic overlap existing in autoimmunity, thus shedding light on common molecular mechanisms of disease and suggesting novel drug targets that could be explored for the treatment of the autoimmune diseases studied