Spontaneous atopic dermatitis is mediated by innate immunity, with the secondary lung inflammation of the atopic march requiring adaptive immunity.

BACKGROUND: Atopic dermatitis (AD) is an inflammatory skin condition that can occur in early life, predisposing to asthma development in a phenomenon known as the atopic march. Although genetic and environmental factors are known to contribute to AD and asthma, the mechanisms underlying the atopic march remain poorly understood. Filaggrin loss-of-function mutations are a major genetic predisposer for the development of AD and progression to AD-associated asthma. OBJECTIVE: We sought to experimentally address whether filaggrin mutations in mice lead to the development of spontaneous eczematous inflammation and address the aberrant immunologic milieu arising in a mouse model of filaggrin deficiency. METHODS: Filaggrin mutant mice were generated on the proallergic BALB/c background, creating a novel model for the assessment of spontaneous AD-like inflammation. Independently recruited AD case collections were analyzed to define associations between filaggrin mutations and immunologic phenotypes. RESULTS: Filaggrin-deficient mice on a BALB/c background had profound spontaneous AD-like inflammation with progression to compromised pulmonary function with age, reflecting the atopic march in patients with AD. Strikingly, skin inflammation occurs independently of adaptive immunity and is associated with cutaneous expansion of IL-5-producing type 2 innate lymphoid cells. Furthermore, subjects with filaggrin mutations have an increased frequency of type 2 innate lymphoid cells in the skin in comparison with control subjects. CONCLUSION: This study provides new insights into our understanding of the atopic march, with innate immunity initiating dermatitis and the adaptive immunity required for subsequent development of compromised lung function.

Common polygenic variation in coeliac disease and confirmation of ZNF335 and NIFA as disease susceptibility loci.

Coeliac disease (CD) is a chronic immune-mediated disease triggered by the ingestion of gluten. It has an estimated prevalence of approximately 1% in European populations. Specific HLA-DQA1 and HLA-DQB1 alleles are established coeliac susceptibility genes and are required for the presentation of gliadin to the immune system resulting in damage to the intestinal mucosa. In the largest association analysis of CD to date, 39 non-HLA risk loci were identified, 13 of which were new, in a sample of 12,014 individuals with CD and 12 228 controls using the Immunochip genotyping platform. Including the HLA, this brings the total number of known CD loci to 40. We have replicated this study in an independent Irish CD case-control population of 425 CD and 453 controls using the Immunochip platform. Using a binomial sign test, we show that the direction of the effects of previously described risk alleles were highly correlated with those reported in the Irish population, (P=2.2 × 10(-16)). Using the Polygene Risk Score (PRS) approach, we estimated that up to 35% of the genetic variance could be explained by loci present on the Immunochip (P=9 × 10(-75)). When this is limited to non-HLA loci, we explain a maximum of 4.5% of the genetic variance (P=3.6 × 10(-18)). Finally, we performed a meta-analysis of our data with the previous reports, identifying two further loci harbouring the ZNF335 and NIFA genes which now exceed genome-wide significance, taking the total number of CD susceptibility loci to 42.

Detecting Allelic Expression Imbalance at Candidate Genes Using 5' Exonuclease Genotyping Technology.

Genetic variation along the length of a chromosome can influence the transcription of a gene. In a heterozygous individual, this may lead to one chromosome producing different levels of RNA, compared to its paired chromosome, for a given gene. Allelic differences in gene expression can offer insight into the role of variation in transcription, and subsequently infer a route to conferring disease risk. This phenomenon is known as allele expression imbalance or AEI, which may be assayed using a PCR-based method that includes the quantification of the relative dosage of each allele (e.g., 5' exonuclease assays, TaqMan™). Importantly, in heterozygous individuals the resolution of expression imbalance is performed within a controlled system; the comparison of the alternate allele is reported relative to the wild-type, as the experiment can be performed within a single sample, controlled for background genetic information. Alternative methods for the detection of AEI include Primer-extension MALDI-TOF (Sequenom MassARRAY(®)), Next-Generation Sequencing, and SNP genotyping arrays. Here we present the methods used for the TaqMan™ approach and include a description of the SNP identification, allele-specific PCR, and analytic methods to convert allele amplification metrics to relative allele dosage.

Quality Control Procedures for High-Throughput Genetic Association Studies.

Genome-wide association (GWA) studies provide an unbiased approach to discovering the role of genetic determinants of disease across the human genome. The case-control design, the most frequently used GWA study design employed to date, compares allele frequencies in affected patients to those of unaffected controls. Several large-scale GWA studies have identified numerous risk variants for celiac disease (CD). However, due to their low marker density, the early GWA arrays failed to adequately capture much of the genetic variance associated with CD. The Immunochip, a custom Illumina Infinium high-density array containing 196,524 common and rare polymorphisms, was developed to allow deep replication and fine mapping of the previously established GWA significant loci identified in 12 major autoimmune and inflammatory diseases, including CD. It has the advantage of allowing uniform sets of genetic markers to be compared across all diseases. This chapter describes the methods used to perform Immunochip genotyping and the bioinformatics steps necessary for quality control and analysis of the resulting data.

Quality Control and Analysis of NGS RNA Sequencing Data.

Transcriptome sequencing, where RNA is isolated, converted to library of cDNA fragments, and sequenced using next-generation sequencing technology, has become the method of choice for the genome-wide characterization of mRNA levels. It offers a more accurate quantification of transcript levels than array-based methods, but also has the added benefit of allowing the discovery of novel gene/transcripts, alternative splice junctions, and novel RNAs. In addition, RNA sequencing may be used to investigate differential gene expression, allelic imbalance, eQTL mapping, RNA editing, RNA-protein interactions, and alternative splicing. A number of statistical methods and tools are available for differential expression analysis using RNA sequencing data and these are continually being developed and improved to handle more complex experimental designs. This chapter describes an example workflow for the quality control and analysis of raw RNA sequencing reads for the purposes of differential gene expression analysis, followed by pathway/enrichment analysis of significantly different genes. The methods and tools described are just one example of how this analysis can be conducted, but they can be applied to most standard RNA sequencing studies of differential gene expression. The methods covered are based on Illumina HiSeq single-end 50 bp reads. However, all programs used are capable of working with paired-end data, subsequent to minor adaptations.

Transcriptome Analysis of CD4+ T Cells in Coeliac Disease Reveals Imprint of BACH2 and IFNγ Regulation.

Genetic studies have to date identified 43 genome wide significant coeliac disease susceptibility (CD) loci comprising over 70 candidate genes. However, how altered regulation of such disease associated genes contributes to CD pathogenesis remains to be elucidated. Recently there has been considerable emphasis on characterising cell type specific and stimulus dependent genetic variants. Therefore in this study we used RNA sequencing to profile over 70 transcriptomes of CD4+ T cells, a cell type crucial for CD pathogenesis, in both stimulated and resting samples from individuals with CD and unaffected controls. We identified extensive transcriptional changes across all conditions, with the previously established CD gene IFNy the most strongly up-regulated gene (log2 fold change 4.6; P(adjusted) = 2.40x10(-11)) in CD4+ T cells from CD patients compared to controls. We show a significant correlation of differentially expressed genes with genetic studies of the disease to date (P(adjusted) = 0.002), and 21 CD candidate susceptibility genes are differentially expressed under one or more of the conditions used in this study. Pathway analysis revealed significant enrichment of immune related processes. Co-expression network analysis identified several modules of coordinately expressed CD genes. Two modules were particularly highly enriched for differentially expressed genes (P<2.2x10(-16)) and highlighted IFNy and the genetically associated transcription factor BACH2 which showed significantly reduced expression in coeliac samples (log2FC -1.75; P(adjusted) = 3.6x10(-3)) as key regulatory genes in CD. Genes regulated by BACH2 were very significantly over-represented among our differentially expressed genes (P<2.2x10(-16)) indicating that reduced expression of this master regulator of T cell differentiation promotes a pro-inflammatory response and strongly corroborates genetic evidence that BACH2 plays an important role in CD pathogenesis.

Development of strategies for SNP detection in RNA-seq data: application to lymphoblastoid cell lines and evaluation using 1000 Genomes data.

Next-generation RNA sequencing (RNA-seq) maps and analyzes transcriptomes and generates data on sequence variation in expressed genes. There are few reported studies on analysis strategies to maximize the yield of quality RNA-seq SNP data. We evaluated the performance of different SNP-calling methods following alignment to both genome and transcriptome by applying them to RNA-seq data from a HapMap lymphoblastoid cell line sample and comparing results with sequence variation data from 1000 Genomes. We determined that the best method to achieve high specificity and sensitivity, and greatest number of SNP calls, is to remove duplicate sequence reads after alignment to the genome and to call SNPs using SAMtools. The accuracy of SNP calls is dependent on sequence coverage available. In terms of specificity, 89% of RNA-seq SNPs calls were true variants where coverage is >10X. In terms of sensitivity, at >10X coverage 92% of all expected SNPs in expressed exons could be detected. Overall, the results indicate that RNA-seq SNP data are a very useful by-product of sequence-based transcriptome analysis. If RNA-seq is applied to disease tissue samples and assuming that genes carrying mutations relevant to disease biology are being expressed, a very high proportion of these mutations can be detected.

Evidence for cis-acting regulation of ANK3 and CACNA1C gene expression.

OBJECTIVES: Genome-wide association studies (GWAS) have identified Ankyrin-G (ANK3) and the alpha-1C subunit of the L-type voltage-gated calcium channel (CACNA1C) as susceptibility genes for bipolar disorder. Available biological information on these genes suggests a potential molecular mechanism involving ion channel dysfunction. The associated single nucleotide polymorphisms (SNPs) at ANK3 (rs10994336) and CACNA1C (rs1006737) are both intronic with no obvious impact on gene function. We investigated whether, instead of affecting protein function, these risk variants might impact on gene regulation affecting expression. METHODS: We have done this by testing for allelic expression imbalance (AEI) to identify cis-acting regulatory polymorphisms. RESULTS: We identified evidence of cis-acting variation at both loci in HapMap Caucasian Europeans from Utah (CEU) lymphoblastoid cell lines. There was considerable evidence of AEI at ANK3 with more than half of all heterozygous samples (21 out of 34) for marker SNP rs3750800 showing AEI and a small number of samples showing near monoallelic expression. The AEI at either gene could not be attributed to the GWAS-associated SNPs. CONCLUSIONS: These data indicate that there is genetic variation local to both genes affecting their expression, but that this variation is not responsible for increasing risk of bipolar disorder.

Psychosis susceptibility gene ZNF804A and cognitive performance in schizophrenia.

CONTEXT: The Zinc Finger Protein 804A gene (ZNF804A) has been implicated in schizophrenia susceptibility by several genome-wide association studies. ZNF804A is brain expressed but of unknown function. OBJECTIVE: To investigate whether the identified risk allele at the disease-associated single nucleotide polymorphism rs1344706 is associated with variation in neuropsychological performance in patients and controls. DESIGN: Comparison of cases and controls grouped according to ZNF804A genotype (AA vs AC vs CC) on selected measures of cognition in 2 independent samples. SETTING: Unrelated patients from general adult psychiatric inpatient and outpatient services and unrelated healthy participants from the general population were ascertained. PARTICIPANTS: Patients with DSM-IV-diagnosed schizophrenia and healthy participants from independent samples of Irish (297 cases and 165 controls) and German (251 cases and 1472 controls) nationality. MAIN OUTCOME MEASURES: In this 2-stage study, we tested for an association between ZNF804A rs1344706 and cognitive functions known to be impaired in schizophrenia (IQ, episodic memory, working memory, and attention) in an Irish discovery sample. We then tested significant results in a German replication sample. RESULTS: In the Irish samples, the ZNF804A genotype was associated with differences in episodic and working memory in patients but not in controls. These findings replicated in the same direction in the German samples. Furthermore, in both samples, when patients with a lower IQ were excluded, the association between ZNF804A and schizophrenia strengthened. CONCLUSIONS: In a disorder characterized by heterogeneity, a risk variant at ZNF804A seems to delineate a patient subgroup characterized by relatively spared cognitive ability. Further work is required to establish whether this represents a discrete molecular pathogenesis that differs from that of other patient groups and whether this also has consequences for nosologic classification, illness course, or treatment.

Influence of NOS1 on verbal intelligence and working memory in both patients with schizophrenia and healthy control subjects.

CONTEXT: Human and animal studies have implicated the gene NOS1 in both cognition and schizophrenia susceptibility. OBJECTIVE: To investigate whether a potential schizophrenia risk single-nucleotide polymorphism (rs6490121) identified in a recent genome-wide association study negatively influences cognition in patients with schizophrenia and healthy control subjects. DESIGN: A comparison of both cases and controls grouped according to NOS1 genotype (GG vs AG vs AA) on selected measures of cognition in 2 independent samples. We tested for association between NOS1 rs6490121 and cognitive functions known to be impaired in schizophrenia (IQ, episodic memory, working memory, and attentional control) in an Irish sample. We then sought to replicate the significant results in a German sample. SETTING: Unrelated patients from general adult psychiatric inpatient and outpatient services and unrelated healthy volunteers from the general population were ascertained. PARTICIPANTS: Patients with DSM-IV-diagnosed schizophrenia and healthy control subjects from independent samples of Irish (cases, n = 349; controls, n = 230) and German (cases, n = 232; controls, n = 1344) nationality. RESULTS: A main effect of NOS1 genotype on verbal IQ and working memory was observed in the Irish sample where the homozygous carriers of the schizophrenia risk G allele performed poorly compared with the other genotype groups. These findings were replicated in the German sample, again with the GG genotype carriers performing below other genotype groups. Post hoc analysis of additional IQ measures (full-scale and performance IQ) in the German sample revealed that NOS1 GG carriers underperformed on these measures also. CONCLUSIONS: NOS1 is associated with clinically significant variation in cognition. Whether this is a mechanism by which schizophrenia risk is increased (eg, via an influence on cognitive reserve) is yet to be confirmed.

Identification of loci associated with schizophrenia by genome-wide association and follow-up.

We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10(-5) in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 x 10(-4)), and the overall pattern of replication was unlikely to occur by chance (P = 9 x 10(-8)). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 x 10(-7)) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 x 10(-9)).