A CLEC16A variant confers risk for juvenile idiopathic arthritis and anti-cyclic citrullinated peptide antibody negative rheumatoid arthritis

Objective Variants in CLEC16A have conferred susceptibility to autoimmune diseases in genome-wide association studies. The present work aimed to investigate the locus' involvements in juvenile idiopathic arthritis (JIA) and further explore the association with rheumatoid arthritis (RA), type 1 diabetes (T1D) and Addison's disease (AD) in the Norwegian population. Methods Three single nucleotide polymorphisms (SNPs) were genotyped in patients with RA (n=809), JIA (n=509), T1D (n=1211) and AD (n=414) and in healthy controls (n=2149). Results All diseases were associated with CLEC16A, but with different SNPs. The intron 22 SNP, rs6498169, was associated with RA (p=0.006) and JIA (p=0.016) and the intron 19 SNPs, rs12708716/rs12917716, with T1D (p=1×10−5) and AD (p=2×10−4). The RA association was confined to the anti-cyclic citrullinated peptide antibody (anti-CCP) negative subgroup (p=2×10−4). Conclusion This is the first report of a CLEC16A association with JIA and a split of the RA association according to anti-CCP status. Different causative variants underlie the rheumatic versus the organ specific diseases

Construction and analysis of tag single nucleotide polymorphism maps for six human-mouse orthologous candidate genes in type 1 diabetes.

BACKGROUND: One strategy to help identify susceptibility genes for complex, multifactorial diseases is to map disease loci in a representative animal model of the disorder. The nonobese diabetic (NOD) mouse is a model for human type 1 diabetes. Linkage and congenic strain analyses have identified several NOD mouse Idd (insulin dependent diabetes) loci, which have been mapped to small chromosome intervals, for which the orthologous regions in the human genome can be identified. Here, we have conducted re-sequencing and association analysis of six orthologous genes identified in NOD Idd loci: NRAMP1/SLC11A1 (orthologous to Nramp1/Slc11a1 in Idd5.2), FRAP1 (orthologous to Frap1 in Idd9.2), 4-1BB/CD137/TNFRSF9 (orthologous to 4-1bb/Cd137/Tnrfrsf9 in Idd9.3), CD101/IGSF2 (orthologous to Cd101/Igsf2 in Idd10), B2M (orthologous to B2m in Idd13) and VAV3 (orthologous to Vav3 in Idd18). RESULTS: Re-sequencing of a total of 110 kb of DNA from 32 or 96 type 1 diabetes cases yielded 220 single nucleotide polymorphisms (SNPs). Sixty-five SNPs, including 54 informative tag SNPs, and a microsatellite were selected and genotyped in up to 1,632 type 1 diabetes families and 1,709 cases and 1,829 controls. CONCLUSION: None of the candidate regions showed evidence of association with type 1 diabetes (P values > 0.2), indicating that common variation in these key candidate genes does not play a major role in type 1 diabetes susceptibility in the European ancestry populations studied.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

DNA Methylation and Gene Expression Changes in Monozygotic Twins Discordant for Psoriasis: Identification of Epigenetically Dysregulated Genes

Monozygotic (MZ) twins do not show complete concordance for many complex diseases; for example, discordance rates for autoimmune diseases are 20%–80%. MZ discordance indicates a role for epigenetic or environmental factors in disease. We used MZ twins discordant for psoriasis to search for genome-wide differences in DNA methylation and gene expression in CD4+ and CD8+ cells using Illumina's HumanMethylation27 and HT-12 expression assays, respectively. Analysis of these data revealed no differentially methylated or expressed genes between co-twins when analyzed separately, although we observed a substantial amount of small differences. However, combined analysis of DNA methylation and gene expression identified genes where differences in DNA methylation between unaffected and affected twins were correlated with differences in gene expression. Several of the top-ranked genes according to significance of the correlation in CD4+ cells are known to be associated with psoriasis. Further, gene ontology (GO) analysis revealed enrichment of biological processes associated with the immune response and clustering of genes in a biological pathway comprising cytokines and chemokines. These data suggest that DNA methylation is involved in an epigenetic dysregulation of biological pathways involved in the pathogenesis of psoriasis. This is the first study based on data from MZ twins discordant for psoriasis to detect epigenetic alterations that potentially contribute to development of the disease

Limitations and possibilities of low cell number ChIP-seq

Background Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-seq) offers high resolution, genome-wide analysis of DNA-protein interactions. However, current standard methods require abundant starting material in the range of 1–20 million cells per immunoprecipitation, and remain a bottleneck to the acquisition of biologically relevant epigenetic data. Using a ChIP-seq protocol optimised for low cell numbers (down to 100,000 cells / IP), we examined the performance of the ChIP-seq technique on a series of decreasing cell numbers. Results We present an enhanced native ChIP-seq method tailored to low cell numbers that represents a 200-fold reduction in input requirements over existing protocols. The protocol was tested over a range of starting cell numbers covering three orders of magnitude, enabling determination of the lower limit of the technique. At low input cell numbers, increased levels of unmapped and duplicate reads reduce the number of unique reads generated, and can drive up sequencing costs and affect sensitivity if ChIP is attempted from too few cells. Conclusions The optimised method presented here considerably reduces the input requirements for performing native ChIP-seq. It extends the applicability of the technique to isolated primary cells and rare cell populations (e.g. biobank samples, stem cells), and in many cases will alleviate the need for cell culture and any associated alteration of epigenetic marks. However, this study highlights a challenge inherent to ChIP-seq from low cell numbers: as cell input numbers fall, levels of unmapped sequence reads and PCR-generated duplicate reads rise. We discuss a number of solutions to overcome the effects of reducing cell number that may aid further improvements to ChIP performance

Limitations and possibilities of low cell number ChIP-seq

Abstract Background Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-seq) offers high resolution, genome-wide analysis of DNA-protein interactions. However, current standard methods require abundant starting material in the range of 1–20 million cells per immunoprecipitation, and remain a bottleneck to the acquisition of biologically relevant epigenetic data. Using a ChIP-seq protocol optimised for low cell numbers (down to 100,000 cells / IP), we examined the performance of the ChIP-seq technique on a series of decreasing cell numbers. Results We present an enhanced native ChIP-seq method tailored to low cell numbers that represents a 200-fold reduction in input requirements over existing protocols. The protocol was tested over a range of starting cell numbers covering three orders of magnitude, enabling determination of the lower limit of the technique. At low input cell numbers, increased levels of unmapped and duplicate reads reduce the number of unique reads generated, and can drive up sequencing costs and affect sensitivity if ChIP is attempted from too few cells. Conclusions The optimised method presented here considerably reduces the input requirements for performing native ChIP-seq. It extends the applicability of the technique to isolated primary cells and rare cell populations (e.g. biobank samples, stem cells), and in many cases will alleviate the need for cell culture and any associated alteration of epigenetic marks. However, this study highlights a challenge inherent to ChIP-seq from low cell numbers: as cell input numbers fall, levels of unmapped sequence reads and PCR-generated duplicate reads rise. We discuss a number of solutions to overcome the effects of reducing cell number that may aid further improvements to ChIP performance.</p

Extensive variation and low heritability of DNA methylation identified in a twin study

Disturbance of DNA methylation leading to aberrant gene expression has been implicated in the etiology of many diseases. Whereas variation at the genetic level has been studied extensively, less is known about the extent and function of epigenetic variation. To explore variation and heritability of DNA methylation, we performed bisulfite sequencing of 1760 CpG sites in 186 regions in the human major histocompatibility complex (MHC) in CD4+ lymphocytes from 49 monozygotic (MZ) and 40 dizygotic (DZ) twin pairs. Individuals show extensive variation in DNA methylation both between and within regions. In addition, many regions also have a complex pattern of variation. Globally, there appears to be a bimodal distribution of DNA methylation in the regions, but a significant fraction of the CpG sites are also heterogeneously methylated. Classification of regions into CpG islands (intragenic and intergenic), 5′ end of genes not associated with a defined CpG island, conserved noncoding regions, and random CpG sites shows region-type differences in variation and heritability. Analyses revealed slightly lower intra-pair differences among MZ than among DZ pairs, suggesting some genetic influences on DNA methylation variation, with most of the variance attributed to nongenetic factors. Overall, heritability estimates of DNA methylation were low. Our heritability estimates are, however, somewhat deflated due to the presence of batch effects that artificially inflate the estimates of shared environment

Multiple Loci in the HLA Complex Are Associated with Addison's Disease.

Context: A strong association between autoimmune Addison's disease (AAD) and major histocompatibility complex class II-encoded HLA-DRB1-DQA1-DQB1 haplotypes is well known. Recent evidence from other autoimmune diseases has suggested that class I-encoded HLA-A and HLA-B gene variants confer HLA-DRB1-DQA1-DQB1-independent effects on disease. Objective: We aimed to explore AAD predisposing effects of HLA-A and -B and further investigate the role of MICA and HLA-DRB1-DQA1-DQB1 in a much larger material than has previously been studied. Design: HLA-A, -B, -DRB1, and -DQB1 and a microsatellite in MICA were genotyped in 414 AAD patients and 684 controls of Norwegian origin. Results: The strongest association was observed for the DRB1 locus, in which the DRB1*03:01 and DRB1*04:04 conferred increased risk of AAD, particularly in a heterozygous combination [odds ratio 22.13; 95% confidence interval (11.39-43.98); P = 6 × 10(-20)]. After conditioning on DRB1, association with AAD was still present for HLA-B and MICA, suggesting the presence of additional risk factors. Conclusions: The major histocompatibility complex harbors multiple risk loci for AAD, in which DRB1 appears to represent the main risk factor