Distinct fibroblast subsets drive inflammation and damage in arthritis

The identification of lymphocyte subsets with non-overlapping effector functions has been pivotal to the development of targeted therapies in immune-mediated inflammatory diseases (IMIDs)1,2. However, it remains unclear whether fibroblast subclasses with non-overlapping functions also exist and are responsible for the wide variety of tissue-driven processes observed in IMIDs, such as inflammation and damage3-5. Here we identify and describe the biology of distinct subsets of fibroblasts responsible for mediating either inflammation or tissue damage in arthritis. We show that deletion of fibroblast activation protein-α (FAPα)+ fibroblasts suppressed both inflammation and bone erosions in mouse models of resolving and persistent arthritis. Single-cell transcriptional analysis identified two distinct fibroblast subsets within the FAPα+ population: FAPα+THY1+ immune effector fibroblasts located in the synovial sub-lining, and FAPα+THY1- destructive fibroblasts restricted to the synovial lining layer. When adoptively transferred into the joint, FAPα+THY1- fibroblasts selectively mediate bone and cartilage damage with little effect on inflammation, whereas transfer of FAPα+ THY1+ fibroblasts resulted in a more severe and persistent inflammatory arthritis, with minimal effect on bone and cartilage. Our findings describing anatomically discrete, functionally distinct fibroblast subsets with non-overlapping functions have important implications for cell-based therapies aimed at modulating inflammation and tissue damage.

HBEGF+ macrophages in rheumatoid arthritis induce fibroblast invasiveness

Macrophages tailor their function according to the signals found in tissue microenvironments, assuming a wide spectrum of phenotypes. A detailed understanding of macrophage phenotypes in human tissues is limited. Using single-cell RNA sequencing, we defined distinct macrophage subsets in the joints of patients with the autoimmune disease rheumatoid arthritis (RA), which affects ~1% of the population. The subset we refer to as HBEGF+ inflammatory macrophages is enriched in RA tissues and is shaped by resident fibroblasts and the cytokine tumor necrosis factor (TNF). These macrophages promoted fibroblast invasiveness in an epidermal growth factor receptor-dependent manner, indicating that intercellular cross-talk in this inflamed setting reshapes both cell types and contributes to fibroblast-mediated joint destruction. In an ex vivo synovial tissue assay, most medications used to treat RA patients targeted HBEGF+ inflammatory macrophages; however, in some cases, medication redirected them into a state that is not expected to resolve inflammation. These data highlight how advances in our understanding of chronically inflamed human tissues and the effects of medications therein can be achieved by studies on local macrophage phenotypes and intercellular interactions.

Genes with High Network Connectivity Are Enriched for Disease Heritability

Recent studies have highlighted the role of gene networks in disease biology. To formally assess this, we constructed a broad set of pathway, network, and pathway+network annotations and applied stratified LD score regression to 42 diseases and complex traits (average N = 323K) to identify enriched annotations. First, we analyzed 18,119 biological pathways. We identified 156 pathway-trait pairs whose disease enrichment was statistically significant (FDR < 5%) after conditioning on all genes and 75 known functional annotations (from the baseline-LD model), a stringent step that greatly reduced the number of pathways detected; most significant pathway-trait pairs were previously unreported. Next, for each of four published gene networks, we constructed probabilistic annotations based on network connectivity. For each gene network, the network connectivity annotation was strongly significantly enriched. Surprisingly, the enrichments were fully explained by excess overlap between network annotations and regulatory annotations from the baseline-LD model, validating the informativeness of the baseline-LD model and emphasizing the importance of accounting for regulatory annotations in gene network analyses. Finally, for each of the 156 enriched pathway-trait pairs, for each of the four gene networks, we constructed pathway+network annotations by annotating genes with high network connectivity to the input pathway. For each gene network, these pathway+network annotations were strongly significantly enriched for the corresponding traits. Once again, the enrichments were largely explained by the baseline-LD model. In conclusion, gene network connectivity is highly informative for disease architectures, but the information in gene networks may be subsumed by regulatory annotations, emphasizing the importance of accounting for known annotations.

IMPACT: Genomic Annotation of Cell-State-Specific Regulatory Elements Inferred from the Epigenome of Bound Transcription Factors

Despite significant progress in annotating the genome with experimental methods, much of the regulatory noncoding genome remains poorly defined. Here we assert that regulatory elements may be characterized by leveraging local epigenomic signatures where specific transcription factors (TFs) are bound. To link these two features, we introduce IMPACT, a genome annotation strategy that identifies regulatory elements defined by cell-state-specific TF binding profiles, learned from 515 chromatin and sequence annotations. We validate IMPACT using multiple compelling applications. First, IMPACT distinguishes between bound and unbound TF motif sites with high accuracy (average AUPRC 0.81, SE 0.07; across 8 tested TFs) and outperforms state-of-the-art TF binding prediction methods, MocapG, MocapS, and Virtual ChIP-seq. Second, in eight tested cell types, RNA polymerase II IMPACT annotations capture more cis-eQTL variation than sequence-based annotations, such as promoters and TSS windows (25% average increase in enrichment). Third, integration with rheumatoid arthritis (RA) summary statistics from European (N = 38,242) and East Asian (N = 22,515) populations revealed that the top 5% of CD4+ Treg IMPACT regulatory elements capture 85.7% of RA h2, the most comprehensive explanation for RA h2 to date. In comparison, the average RA h2 captured by compared CD4+ T histone marks is 42.3% and by CD4+ T specifically expressed gene sets is 36.4%. Lastly, we find that IMPACT may be used in many different cell types to identify complex trait associated regulatory elements.

Lymphocyte innateness defined by transcriptional states reflects a balance between proliferation and effector functions

How innate T cells (ITC), including invariant natural killer T (iNKT) cells, mucosal-associated invariant T (MAIT) cells, and γδ T cells, maintain a poised effector state has been unclear. Here we address this question using low-input and single-cell RNA-seq of human lymphocyte populations. Unbiased transcriptomic analyses uncover a continuous ‘innateness gradient’, with adaptive T cells at one end, followed by MAIT, iNKT, γδ T and natural killer cells at the other end. Single-cell RNA-seq reveals four broad states of innateness, and heterogeneity within canonical innate and adaptive populations. Transcriptional and functional data show that innateness is characterized by pre-formed mRNA encoding effector functions, but impaired proliferation marked by decreased baseline expression of ribosomal genes. Together, our data shed new light on the poised state of ITC, in which innateness is defined by a transcriptionally-orchestrated trade-off between rapid cell growth and rapid effector function.

Innate T cells (ITC) contain many subsets and are poised to promptly respond to antigens and pathogens, but how this poised state is maintained is still unclear. Here the authors perform single-cell RNA-seq to align the various ITC subsets along an ‘innateness gradient’ that is associated with changes in proliferation and effector functions.

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.

Discovering in vivo cytokine-eQTL interactions from a lupus clinical trial

BACKGROUND

Cytokines are critical to human disease and are attractive therapeutic targets given their widespread influence on gene regulation and transcription. Defining the downstream regulatory mechanisms influenced by cytokines is central to defining drug and disease mechanisms. One promising strategy is to use interactions between expression quantitative trait loci (eQTLs) and cytokine levels to define target genes and mechanisms.

RESULTS

In a clinical trial for anti-IL-6 in patients with systemic lupus erythematosus, we measure interferon (IFN) status, anti-IL-6 drug exposure, and whole blood genome-wide gene expression at three time points. We show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point. We observe a statistically significant enrichment of in vivo eQTL interactions with IFN status and anti-IL-6 drug exposure and find many novel interactions that have not been previously described. Finally, we find transcription factor binding motifs interrupted by eQTL interaction SNPs, which point to key regulatory mediators of these environmental stimuli and therefore potential therapeutic targets for autoimmune diseases. In particular, genes with IFN interactions are enriched for ISRE binding site motifs, while those with anti-IL-6 interactions are enriched for IRF4 motifs.

CONCLUSIONS

This study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.

The eMERGE genotype set of 83,717 subjects imputed to ~40 million variants genome wide and association with the herpes zoster medical record phenotype

The Electronic Medical Records and Genomics (eMERGE) network is a network of medical centers with electronic medical records linked to existing biorepository samples for genomic discovery and genomic medicine research. The network sought to unify the genetic results from 78 Illumina and Affymetrix genotype array batches from 12 contributing medical centers for joint association analysis of 83,717 human participants. In this report, we describe the imputation of eMERGE results and methods to create the unified imputed merged set of genome‐wide variant genotype data. We imputed the data using the Michigan Imputation Server, which provides a missing single‐nucleotide variant genotype imputation service using the minimac3 imputation algorithm with the Haplotype Reference Consortium genotype reference set. We describe the quality control and filtering steps used in the generation of this data set and suggest generalizable quality thresholds for imputation and phenotype association studies. To test the merged imputed genotype set, we replicated a previously reported chromosome 6 HLA‐B herpes zoster (shingles) association and discovered a novel zoster‐associated loci in an epigenetic binding site near the terminus of chromosome 3 (3p29).

High-throughput identification of noncoding functional SNPs via type IIS enzyme restriction

Genome-wide association studies (GWAS) have identified many disease-associated noncoding variants, but cannot distinguish functional single-nucleotide polymorphisms (fSNPs) from others that reside incidentally within risk loci. To address this challenge, we developed an unbiased high-throughput screen that employs type IIS enzymatic restriction to identify fSNPs that allelically modulate the binding of regulatory proteins. We coupled this approach, termed SNP-seq, with flanking restriction enhanced pulldown (FREP) to identify regulation of CD40 by three disease-associated fSNPs via four regulatory proteins, RBPJ, RSRC2 and FUBP-1/TRAP150. Applying this approach across 27 loci associated with juvenile idiopathic arthritis, we identified 148 candidate fSNPs, including two that regulate STAT4 via the regulatory proteins SATB2 and H1.2. Together, these findings establish the utility of tandem SNP-seq/FREP to bridge the gap between GWAS and disease mechanism.

Methods for high-dimensional analysis of cells dissociated from cryopreserved synovial tissue

Background

Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples.

Methods

Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq.

Results

Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4⁺ and CD8⁺ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.

Conclusions

We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1631-y) contains supplementary material, which is available to authorized users.

Single-cell RNA sequencing of skin and kidney cells in lupus nephritis provides insights into pathogenesis and indicates novel potential biomarkers

Classification and treatment decisions in lupus nephritis (LN) are largely based on renal histology. Single-cell RNAseq (scRNAseq) analysis may accurately differentiate types of renal involvement at the transcriptomic level, and better inform treatment decisions and prognosis. scRNAseq was performed on kidney and non-lesional skin tissue collected from clinically indicated renal biopsies, and skin biopsies obtained at the time of renal biopsies, in 20 systemic lupus erythematosus (SLE) patients. Cell-types were determined using principal component analysis and tSNE plotting, resulting in the definitive identification of keratinocytes, tubular cells, mesangial cells, fibroblasts, endothelial cells, and leukocytes. Tubular cells in patients with proliferative nephritis demonstrated upregulated TNF signaling compared with membranous nephritis. Interestingly, keratinocytes of patients with proliferative nephritis also demonstrated upregulated TNF signaling. Furthermore, tubular cells of patients who did not respond to standard immunosuppressive treatment showed upregulation of extracellular matrix proteins and fibrotic markers at the time of biopsy. Using logistic regression analysis, a 4-gene tubular fibrosis score was created which predicted response to treatment, with an area under curve of 0.9. We conclude that scRNAseq using small amounts of renal biopsy tissue in SLE can differentiate between the different classes of LN, and provide important insights into potential pathogenic mechanisms. Further, changes in the skin of LN patients can provide a useful source of biomarkers and may reflect important information concerning concurrent kidney pathological events.

Functionally distinct disease-associated fibroblast subsets in rheumatoid arthritis

Fibroblasts regulate tissue homeostasis, coordinate inflammatory responses, and mediate tissue damage. In rheumatoid arthritis (RA), synovial fibroblasts maintain chronic inflammation which leads to joint destruction. Little is known about fibroblast heterogeneity or if aberrations in fibroblast subsets relate to pathology. Here, we show functional and transcriptional differences between fibroblast subsets from human synovial tissues using bulk transcriptomics of targeted subpopulations and single-cell transcriptomics. We identify seven fibroblast subsets with distinct surface protein phenotypes, and collapse them into three subsets by integrating transcriptomic data. One fibroblast subset, characterized by the expression of proteins podoplanin, THY1 membrane glycoprotein and cadherin-11, but lacking CD34, is threefold expanded in patients with RA relative to patients with osteoarthritis. These fibroblasts localize to the perivascular zone in inflamed synovium, secrete proinflammatory cytokines, are proliferative, and have an in vitro phenotype characteristic of invasive cells. Our strategy may be used as a template to identify pathogenic stromal cellular subsets in other complex diseases.

Synovial fibroblasts are thought to be central mediators of joint destruction in rheumatoid arthritis (RA). Here the authors use single-cell transcriptomics and flow cytometry to identify synovial fibroblast subsets that are expanded and display distinct tissue distribution and function in patients with RA.

Phenome-wide scanning identifies multiple diseases and disease severity phenotypes associated with HLA variants

Although many phenotypes have been associated with variants in human leukocyte antigen (HLA) genes, the full phenotypic impact of HLA variants across all diseases is unknown. We imputed HLA genomic variation from two populations of 28,839 and 8431 European ancestry individuals and tested association of HLA variation with 1368 phenotypes. A total of 104 four-digit and 92 two-digit HLA allele phenotype associations were significant in both discovery and replication cohorts, the strongest being HLA-DQB1*03:02 and type 1 diabetes. Four previously unidentified associations were identified across the spectrum of disease with two- and four-digit HLA alleles and 10 with nonsynonymous variants. Some conditions associated with multiple HLA variants and stronger associations with more severe disease manifestations were identified. A comprehensive, publicly available catalog of clinical phenotypes associated with HLA variation is provided. Examining HLA variant disease associations in this large data set allows comprehensive definition of disease associations to drive further mechanistic insights.

Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis

CD4+ T cells have been long known to play an important role in the pathogenesis of rheumatoid arthritis (RA), but the specific cell populations and states that drive the disease have been challenging to identify with low dimensional single cell data and bulk assays. The advent of high dimensional single cell technologies-like single cell RNA-seq or mass cytometry-has offered promise to defining key populations, but brings new methodological and statistical challenges. Recent single cell profiling studies have revealed a broad diversity of cell types among CD4+ T cells, identifying novel populations that are expanded or altered in RA. Here, we will review recent findings on CD4+ T cell heterogeneity and RA that have come from single cell profiling studies and discuss the best practices for conducting these studies.

Review: Genetics and the Classification of Arthritis in Adults and Children

Current classification of primary inflammatory arthritis begins from the assumption that adults and children are different. No form of juvenile idiopathic arthritis bears the same name as an adult arthritis, a nomenclature gap with implications for both clinical care and research. Recent genetic data have raised questions regarding this adult/pediatric divide, revealing instead broad patterns that span the age spectrum. Combining these genetic patterns with demographic and clinical data, we propose that inflammatory arthritis can be segregated into 4 main clusters, largely irrespective of pediatric or adult onset: seropositive, seronegative (likely including a distinct group that usually begins in early childhood), spondyloarthritis, and systemic. Each of these broad clusters is internally heterogeneous, highlighting the need for further study to resolve etiologically discrete entities. Eliminating divisions based on arbitrary age cutoffs will enhance opportunities for collaboration between adult and pediatric rheumatologists, thereby helping to promote the understanding and treatment of arthritis.

Molecular basis for increased susceptibility of Indigenous North Americans to seropositive rheumatoid arthritis

OBJECTIVE

The pathogenetic mechanisms by which HLA-DRB1 alleles are associated with anticitrullinated peptide antibody (ACPA)-positive rheumatoid arthritis (RA) are incompletely understood. RA high-risk HLA-DRB1 alleles are known to share a common motif, the 'shared susceptibility epitope (SE)'. Here, the electropositive P4 pocket of HLA-DRB1 accommodates self-peptide residues containing citrulline but not arginine. HLA-DRB1 His/Phe13β stratifies with ACPA-positive RA, while His13βSer polymorphisms stratify with ACPA-negative RA and RA protection. Indigenous North American (INA) populations have high risk of early-onset ACPA-positive RA, whereby HLA-DRB1*04:04 and HLA-DRB1*14:02 are implicated as risk factors for RA in INA. However, HLA-DRB1*14:02 has a His13βSer polymorphism. Therefore, we aimed to verify this association and determine its molecular mechanism.

METHODS

HLA genotype was compared in 344 INA patients with RA and 352 controls. Structures of HLA-DRB1*1402-class II loaded with vimentin-64Arg59-71, vimentin-64Cit59-71 and fibrinogen β-74Cit69-81 were solved using X-ray crystallography. Vimentin-64Cit59-71-specific and vimentin59-71-specific CD4+ T cells were characterised by flow cytometry using peptide-histocompatibility leukocyte antigen (pHLA) tetramers. After sorting of antigen-specific T cells, TCRα and β-chains were analysed using multiplex, nested PCR and sequencing.

RESULTS

ACPA+ RA in INA was independently associated with HLA-DRB1*14:02. Consequent to the His13βSer polymorphism and altered P4 pocket of HLA-DRB1*14:02, both citrulline and arginine were accommodated in opposite orientations. Oligoclonal autoreactive CD4+ effector T cells reactive with both citrulline and arginine forms of vimentin59-71 were observed in patients with HLA-DRB1*14:02+ RA and at-risk ACPA- first-degree relatives. HLA-DRB1*14:02-vimentin59-71-specific and HLA-DRB1*14:02-vimentin-64Cit59-71-specific CD4+ memory T cells were phenotypically distinct populations.

CONCLUSION

HLA-DRB1*14:02 broadens the capacity for citrullinated and native self-peptide presentation and T cell expansion, increasing risk of ACPA+ RA.

Genetic landscape of interactive effects of HLA-DRB1 alleles on susceptibility to ACPA(+) rheumatoid arthritis and ACPA levels in Japanese population

BACKGROUND

HLA-DRB1 is the strongest susceptibility gene to rheumatoid arthritis (RA). HLA-DRB1 alleles showed significant non-additive and interactive effects on susceptibility to RA in the European population, but these effects on RA susceptibility should vary between populations due to the difference in allelic distribution. Furthermore, non-additive or interactive effects on the phenotypes of RA are not fully known. We evaluated the non-additive and interactive effects of HLA-DRB1 alleles on RA susceptibility and anticitrullinated protein/peptide antibody (ACPA) levels in Japanese patients.

METHODS

A total of 5581 ACPA(+) RA and 19 170 controls were genotyped or imputed for HLA-DRB1 alleles. Logistic regression analysis was performed for both allelic non-additive effects and interactive effects of allelic combinations. The significant levels were set by Bonferroni's correction. A total of 4371 ACPA(+) RA were analysed for ACPA levels.

RESULTS

We obtained evidence of non-additive and interactive effects of HLA-DRB1 on ACPA(+) RA susceptibility (p=2.5×10^-5 and 1.5×10^-17, respectively). Multiple HLA-DRB1 alleles including HLA-DRB1*04:05, the most common susceptibility allele in the Japanese, showed significant non-additive effects (p≤0.0043). We identified multiple allelic combinations with significant interactive effects including a common combination with the European population as well as novel combinations. Additional variance of ACPA(+) RA susceptibility could be explained substantially by heterozygote dominance or interactive effects. We did not find evidence of non-additive and interactive effects on levels of ACPA.

CONCLUSION

HLA allelic non-additive and interactive effects on ACPA(+) RA susceptibility were observed in the Japanese population. The allelic non-additive and interactive effects depend on allelic distribution in populations.

Investigating methotrexate toxicity within a randomized double-blinded, placebo-controlled trial: Rationale and design of the Cardiovascular Inflammation Reduction Trial-Adverse Events (CIRT-AE) Study

BACKGROUND

The role of low dose methotrexate (LDM) in potential serious toxicities remains unclear despite its common use. Prior observational studies investigating LDM toxicity compared LDM to other active drugs. Prior placebo-controlled clinical trials of LDM in inflammatory conditions were not large enough to investigate toxicity. The Cardiovascular Inflammation Reduction Trial (CIRT) is an ongoing NIH-funded, randomized, double-blind, placebo-controlled trial of LDM in the secondary prevention of cardiovascular disease. We describe here the rationale and design of the CIRT-Adverse Events (CIRT-AE) ancillary study which aims to investigate adverse events within CIRT.

DESIGN

CIRT will randomize up to 7000 participants with cardiovascular disease and no systemic rheumatic disease to either LDM (target dose: 15-20mg/week) or placebo for an average follow-up period of 3-5 years; subjects in both treatment arms receive folic acid 1mg daily for 6 days each week. The primary endpoints of CIRT include recurrent cardio vascular events, incident diabetes, and all-cause mortality, and the ancillary CIRT-AE study has been designed to adjudicate other clinically important adverse events including hepatic, gastrointestinal, respiratory, hematologic, infectious, mucocutaneous, oncologic, renal, neurologic, and musculoskeletal outcomes. Methotrexate polyglutamate levels and genome-wide single nucleotide polymorphisms will be examined for association with adverse events.

SUMMARY

CIRT-AE will comprehensively evaluate potential LDM toxicities among subjects with cardiovascular disease within the context of a large, ongoing, double-blind, placebo-controlled trial. This information may lead to a personalized approach to monitoring LDM in clinical practice.

Brief Report: The Role of Rare Protein-Coding Variants in Anti-Tumor Necrosis Factor Treatment Response in Rheumatoid Arthritis

OBJECTIVE

In many rheumatoid arthritis (RA) patients, disease is controlled with anti-tumor necrosis factor (anti-TNF) biologic therapies. However, in a significant number of patients, the disease fails to respond to anti-TNF therapy. We undertook the present study to examine the hypothesis that rare and low-frequency genetic variants might influence response to anti-TNF treatment.

METHODS

We sequenced the coding region of 750 genes in 1,094 RA patients of European ancestry who were treated with anti-TNF. After quality control, 690 genes were included in the analysis. We applied single-variant association and gene-based association tests to identify variants associated with anti-TNF treatment response. In addition, given the key mechanistic role of TNF, we performed gene set analyses of 27 TNF pathway genes.

RESULTS

We identified 14,420 functional variants, of which 6,934 were predicted as nonsynonymous 2,136 of which were further predicted to be "damaging." Despite the fact that the study was well powered, no single variant or gene showed study-wide significant association with change in the outcome measures disease activity or European League Against Rheumatism response. Intriguingly, we observed 3 genes, of 27 with nominal signals of association (P < 0.05), that were involved in the TNF signaling pathway. However, when we performed a rigorous gene set enrichment analysis based on association P value ranking, we observed no evidence of enrichment of association at genes involved in the TNF pathway (P_enrichment  = 0.15, based on phenotype permutations).

CONCLUSION

Our findings suggest that rare and low-frequency protein-coding variants in TNF signaling pathway genes or other genes do not contribute substantially to anti-TNF treatment response in patients with RA.

Genetic association study of exfoliation syndrome identifies a protective rare variant at LOXL1 and five new susceptibility loci

Exfoliation syndrome (XFS) is the most common known risk factor for secondary glaucoma and a major cause of blindness worldwide. Variants in two genes, LOXL1 and CACNA1A, have previously been associated with XFS. To further elucidate the genetic basis of XFS, we collected a global sample of XFS cases to refine the association at LOXL1, which previously showed inconsistent results across populations, and to identify new variants associated with XFS. We identified a rare protective allele at LOXL1 (p.Phe407, odds ratio (OR) = 25, P = 2.9 × 10^-14) through deep resequencing of XFS cases and controls from nine countries. A genome-wide association study (GWAS) of XFS cases and controls from 24 countries followed by replication in 18 countries identified seven genome-wide significant loci (P < 5 × 10^-8). We identified association signals at 13q12 (POMP), 11q23.3 (TMEM136), 6p21 (AGPAT1), 3p24 (RBMS3) and 5q23 (near SEMA6A). These findings provide biological insights into the pathology of XFS and highlight a potential role for naturally occurring rare LOXL1 variants in disease biology.

A rare coding allele in IFIH1 is protective for psoriatic arthritis

Objectives

Psoriatic arthritis (PsA) is an inflammatory arthritis associated with psoriasis. While many common risk alleles have been reported for association with PsA as well as psoriasis, few rare coding alleles have yet been identified.

Methods

To identify rare coding variation associated with PsA risk or protection, we genotyped 41 267 variants with the exome chip and investigated association within an initial cohort of 1980 PsA cases and 5913 controls. Genotype data for an independent cohort of 2234 PsA cases and 5708 controls was also made available, allowing for a meta-analysis to be performed with the discovery dataset.

Results

We identified an association with the rare variant rs35667974 (p=2.39x10⁻⁶, OR=0.47), encoding an Ile923Val amino acid change in the IFIH1 gene protein product. The association was reproduced in our independent cohort, which reached a high level of significance on meta-analysis with the discovery and replication datasets (p=4.67x10⁻¹⁰). We identified a strong association with IFIH1 when performing multiple-variant analysis (p=6.77x10⁻⁶), and found evidence of independent effects between the rare allele and the common PsA variant at the same locus.

Conclusion

For the first time, we report a rare coding allele in IFIH1 to be protective for PsA. This rare allele has also been identified to have the same direction of effect on type I diabetes and psoriasis. While this association further supports existing evidence for IFIH1 as a causal gene for PsA, mechanistic studies will need to be pursued to confirm that IFIH1 is indeed causal.

Transethnic meta-analysis identifies GSDMA and PRDM1 as susceptibility genes to systemic sclerosis

OBJECTIVES

Systemic sclerosis (SSc) is an autoimmune disease characterised by skin and systemic fibrosis culminating in organ damage. Previous genetic studies including genome-wide association studies (GWAS) have identified 12 susceptibility loci satisfying genome-wide significance. Transethnic meta-analyses have successfully expanded the list of susceptibility genes and deepened biological insights for other autoimmune diseases.

METHODS

We performed transethnic meta-analysis of GWAS in the Japanese and European populations, followed by a two-staged replication study comprising a total of 4436 cases and 14 751 controls. Associations between significant single nuclear polymorphisms (SNPs) and neighbouring genes were evaluated. Enrichment analysis of H3K4Me3, a representative histone mark for active promoter was conducted with an expanded list of SSc susceptibility genes.

RESULTS

We identified two significant SNP in two loci, GSDMA and PRDM1, both of which are related to immune functions and associated with other autoimmune diseases (p=1.4×10^-10 and 6.6×10^-10, respectively). GSDMA also showed a significant association with limited cutaneous SSc. We also replicated the associations of previously reported loci including a non-GWAS locus, TNFAIP3. PRDM1 encodes BLIMP1, a transcription factor regulating T-cell proliferation and plasma cell differentiation. The top SNP in GSDMA was a missense variant and correlated with gene expression of neighbouring genes, and this could explain the association in this locus. We found different human leukocyte antigen (HLA) association patterns between the two populations. Enrichment analysis suggested the importance of CD4-naïve primary T cell.

CONCLUSIONS

GSDMA and PRDM1 are associated with SSc. These findings provide enhanced insight into the genetic and biological basis of SSc.

Fine-mapping the MHC locus in juvenile idiopathic arthritis (JIA) reveals genetic heterogeneity corresponding to distinct adult inflammatory arthritic diseases

Objectives

Juvenile idiopathic arthritis (JIA) is a heterogeneous group of diseases, comprising seven categories. Genetic data could potentially be used to help redefine JIA categories and improve the current classification system. The human leucocyte antigen (HLA) region is strongly associated with JIA. Fine-mapping of the region was performed to look for similarities and differences in HLA associations between the JIA categories and define correspondences with adult inflammatory arthritides.

Methods

Dense genotype data from the HLA region, from the Immunochip array for 5043 JIA cases and 14 390 controls, were used to impute single-nucleotide polymorphisms, HLA classical alleles and amino acids. Bivariate analysis was performed to investigate genetic correlation between the JIA categories. Conditional analysis was used to identify additional effects within the region. Comparison of the findings with those in adult inflammatory arthritic diseases was performed.

Results

We identified category-specific associations and have demonstrated for the first time that rheumatoid factor (RF)-negative polyarticular JIA and oligoarticular JIA are genetically similar in their HLA associations. We also observe that each JIA category potentially has an adult counterpart. The RF-positive polyarthritis association at HLA-DRB1 amino acid at position 13 mirrors the association in adult seropositive rheumatoid arthritis (RA). Interestingly, the combined oligoarthritis and RF-negative polyarthritis dataset shares the same association with adult seronegative RA.

Conclusions

The findings suggest the value of using genetic data in helping to classify the categories of this heterogeneous disease. Mapping JIA categories to adult counterparts could enable shared knowledge of disease pathogenesis and aetiology and facilitate transition from paediatric to adult services.

Protective coding variants in CFH and PELI3 and a variant near CTRB1 are associated with age-related macular degeneration†

Although numerous common age-related macular degeneration (AMD) alleles have been discovered using genome-wide association studies, substantial disease heritability remains unexplained. We sought to identify additional common and rare variants associated with advanced AMD. A total of 4,332 cases and 25,268 controls of European ancestry from three different populations were genotyped using the Illumina Infinium HumanExome BeadChip. We performed meta-analyses to identify associations with common variants, and single variant and gene-based burden tests to identify rare variants. Two protective, low-frequency, non-synonymous variants were significantly associated with a decrease in AMD risk: A307V in PELI3 (odds ratio [OR] = 0.14, P = 4.3 × 10-10) and N1050Y in CFH (OR = 0.76, P = 6.2 × 10-12). The new variants have a large effect size, similar to some rare mutations we reported previously in a targeted sequencing study, which remain significant in this analysis: CFH R1210C (OR = 18.82, P = 3.5 × 10-07), C3 K155Q (OR = 3.27, P = 1.5 × 10-10) and C9 P167S (OR = 2.04, P = 2.8 × 10-07). We also identified a strong protective signal for a common variant (rs8056814) near CTRB1 associated with a decrease in AMD risk (logistic regression: OR = 0.71, P = 1.8 × 10-07). Suggestive protective loci were identified in the COL4A3 and APOH genes. Our results support the involvement of common and low-frequency protective variants in this vision-threatening condition. This study expands the roles of the innate immune pathway as well as the extracellular matrix and high-density lipoprotein pathways in the aetiology of AMD.

New data and an old puzzle: the negative association between schizophrenia and rheumatoid arthritis

BACKGROUND

A long-standing epidemiological puzzle is the reduced rate of rheumatoid arthritis (RA) in those with schizophrenia (SZ) and vice versa. Traditional epidemiological approaches to determine if this negative association is underpinned by genetic factors would test for reduced rates of one disorder in relatives of the other, but sufficiently powered data sets are difficult to achieve. The genomics era presents an alternative paradigm for investigating the genetic relationship between two uncommon disorders.

METHODS

We use genome-wide common single nucleotide polymorphism (SNP) data from independently collected SZ and RA case-control cohorts to estimate the SNP correlation between the disorders. We test a genotype X environment (GxE) hypothesis for SZ with environment defined as winter- vs summer-born.

RESULTS

We estimate a small but significant negative SNP-genetic correlation between SZ and RA (-0.046, s.e. 0.026, P = 0.036). The negative correlation was stronger for the SNP set attributed to coding or regulatory regions (-0.174, s.e. 0.071, P = 0.0075). Our analyses led us to hypothesize a gene-environment interaction for SZ in the form of immune challenge. We used month of birth as a proxy for environmental immune challenge and estimated the genetic correlation between winter-born and non-winter born SZ to be significantly less than 1 for coding/regulatory region SNPs (0.56, s.e. 0.14, P = 0.00090).

CONCLUSIONS

Our results are consistent with epidemiological observations of a negative relationship between SZ and RA reflecting, at least in part, genetic factors. Results of the month of birth analysis are consistent with pleiotropic effects of genetic variants dependent on environmental context.

Genome-Wide Association Studies Suggest Limited Immune Gene Enrichment in Schizophrenia Compared to 5 Autoimmune Diseases

There has been intense debate over the immunological basis of schizophrenia, and the potential utility of adjunct immunotherapies. The major histocompatibility complex is consistently the most powerful region of association in genome-wide association studies (GWASs) of schizophrenia and has been interpreted as strong genetic evidence supporting the immune hypothesis. However, global pathway analyses provide inconsistent evidence of immune involvement in schizophrenia, and it remains unclear whether genetic data support an immune etiology per se. Here we empirically test the hypothesis that variation in immune genes contributes to schizophrenia. We show that there is no enrichment of immune loci outside of the MHC region in the largest genetic study of schizophrenia conducted to date, in contrast to 5 diseases of known immune origin. Among 108 regions of the genome previously associated with schizophrenia, we identify 6 immune candidates (DPP4, HSPD1, EGR1, CLU, ESAM, NFATC3) encoding proteins with alternative, nonimmune roles in the brain. While our findings do not refute evidence that has accumulated in support of the immune hypothesis, they suggest that genetically mediated alterations in immune function may not play a major role in schizophrenia susceptibility. Instead, there may be a role for pleiotropic effects of a small number of immune genes that also regulate brain development and plasticity. Whether immune alterations drive schizophrenia progression is an important question to be addressed by future research, especially in light of the growing interest in applying immunotherapies in schizophrenia.

Mapping rare, deleterious mutations in Factor H: Association with early onset, drusen burden, and lower antigenic levels in familial AMD

The genetic architecture of age-related macular degeneration (AMD) involves numerous genetic variants, both common and rare, in the coding region of complement factor H (CFH). While these variants explain high disease burden in some families, they fail to explain the pathology in all. We selected families whose AMD was unexplained by known variants and performed whole exome sequencing to probe for other rare, highly penetrant variants. We identified four rare loss-of-function variants in CFH associated with AMD. Missense variant CFH 1:196646753 (C192F) segregated perfectly within a family characterized by advanced AMD and drusen temporal to the macula. Two families, each comprising a pair of affected siblings with extensive extramacular drusen, carried essential splice site variant CFH 1:196648924 (IVS6+1G>A) or missense variant rs139360826 (R175P). In a fourth family, missense variant rs121913058 (R127H) was associated with AMD. Most carriers had early onset bilateral advanced AMD and extramacular drusen. Carriers tended to have low serum Factor H levels, especially carriers of the splice variant. One missense variant (R127H) has been previously shown not to be secreted. The two other missense variants were produced recombinantly: compared to wild type, one (R175P) had no functional activity and the other (C192F) had decreased secretion.

Contribution of a Non-classical HLA Gene, HLA-DOA, to the Risk of Rheumatoid Arthritis

Despite the progress in human leukocyte antigen (HLA) causal variant mapping, independent localization of major histocompatibility complex (MHC) risk from classical HLA genes is challenging. Here, we conducted a large-scale MHC fine-mapping analysis of rheumatoid arthritis (RA) in a Japanese population (6,244 RA cases and 23,731 controls) population by using HLA imputation, followed by a multi-ethnic validation study including east Asian and European populations (n = 7,097 and 23,149, respectively). Our study identified an independent risk of a synonymous mutation at HLA-DOA, a non-classical HLA gene, on anti-citrullinated protein autoantibody (ACPA)-positive RA risk (p = 1.4 × 10(-9)), which demonstrated a cis-expression quantitative trait loci (cis-eQTL) effect on HLA-DOA expression. Trans-ethnic comparison revealed different linkage disequilibrium (LD) patterns in HLA-DOA and HLA-DRB1, explaining the observed HLA-DOA variant risk heterogeneity among ethnicities, which was most evident in the Japanese population. Although previous HLA fine-mapping studies have identified amino acid polymorphisms of the classical HLA genes as driving genetic susceptibility to disease, our study additionally identifies the dosage contribution of a non-classical HLA gene to disease etiology. Our study contributes to the understanding of HLA immunology in human diseases and suggests the value of incorporating additional ancestry in MHC fine-mapping.

Genetic risk of extranodal natural killer T-cell lymphoma: a genome-wide association study

BACKGROUND

Extranodal natural killer T-cell lymphoma (NKTCL), nasal type, is a rare and aggressive malignancy that occurs predominantly in Asian and Latin American populations. Although Epstein-Barr virus infection is a known risk factor, other risk factors and the pathogenesis of NKTCL are not well understood. We aimed to identify common genetic variants affecting individual risk of NKTCL.

METHODS

We did a genome-wide association study of 189 patients with extranodal NKTCL, nasal type (WHO classification criteria; cases) and 957 controls from Guangdong province, southern China. We validated our findings in four independent case-control series, including 75 cases from Guangdong province and 296 controls from Hong Kong, 65 cases and 983 controls from Guangdong province, 125 cases and 1110 controls from Beijing (northern China), and 60 cases and 2476 controls from Singapore. We used imputation and conditional logistic regression analyses to fine-map the associations. We also did a meta-analysis of the replication series and of the entire dataset.

FINDINGS

Associations exceeding the genome-wide significance threshold (p<5 × 10(-8)) were seen at 51 single-nucleotide polymorphisms (SNPs) mapping to the class II MHC region on chromosome 6, with rs9277378 (located in HLA-DPB1) having the strongest association with NKTCL susceptibility (p=4·21 × 10(-19), odds ratio [OR] 1·84 [95% CI 1·61-2·11] in meta-analysis of entire dataset). Imputation-based fine-mapping across the class II MHC region suggests that four aminoacid residues (Gly84-Gly85-Pro86-Met87) in near-complete linkage disequilibrium at the edge of the peptide-binding groove of HLA-DPB1 could account for most of the association between the rs9277378*A risk allele and NKTCL susceptibility (OR 2·38, p value for haplotype 2·32 × 10(-14)). This association is distinct from MHC associations with Epstein-Barr virus infection.

INTERPRETATION

To our knowledge, this is the first time that a genetic variant conferring an NKTCL risk is noted at genome-wide significance. This finding underlines the importance of HLA-DP antigen presentation in the pathogenesis of NKTCL.

FUNDING

Top-Notch Young Talents Program of China, Special Support Program of Guangdong, Specialized Research Fund for the Doctoral Program of Higher Education (20110171120099), Program for New Century Excellent Talents in University (NCET-11-0529), National Medical Research Council of Singapore (TCR12DEC005), Tanoto Foundation Professorship in Medical Oncology, New Century Foundation Limited, Ling Foundation, Singapore National Cancer Centre Research Fund, and the US National Institutes of Health (1R01AR062886, 5U01GM092691-04, and 1R01AR063759-01A1).

Investigating the Causal Relationship of C-Reactive Protein with 32 Complex Somatic and Psychiatric Outcomes: A Large-Scale Cross-Consortium Mendelian Randomization Study

BACKGROUND

C-reactive protein (CRP) is associated with immune, cardiometabolic, and psychiatric traits and diseases. Yet it is inconclusive whether these associations are causal.

METHODS AND FINDINGS

We performed Mendelian randomization (MR) analyses using two genetic risk scores (GRSs) as instrumental variables (IVs). The first GRS consisted of four single nucleotide polymorphisms (SNPs) in the CRP gene (GRSCRP), and the second consisted of 18 SNPs that were significantly associated with CRP levels in the largest genome-wide association study (GWAS) to date (GRSGWAS). To optimize power, we used summary statistics from GWAS consortia and tested the association of these two GRSs with 32 complex somatic and psychiatric outcomes, with up to 123,865 participants per outcome from populations of European ancestry. We performed heterogeneity tests to disentangle the pleiotropic effect of IVs. A Bonferroni-corrected significance level of less than 0.0016 was considered statistically significant. An observed p-value equal to or less than 0.05 was considered nominally significant evidence for a potential causal association, yet to be confirmed. The strengths (F-statistics) of the IVs were 31.92-3,761.29 and 82.32-9,403.21 for GRSCRP and GRSGWAS, respectively. CRP GRSGWAS showed a statistically significant protective relationship of a 10% genetically elevated CRP level with the risk of schizophrenia (odds ratio [OR] 0.86 [95% CI 0.79-0.94]; p < 0.001). We validated this finding with individual-level genotype data from the schizophrenia GWAS (OR 0.96 [95% CI 0.94-0.98]; p < 1.72 × 10-6). Further, we found that a standardized CRP polygenic risk score (CRPPRS) at p-value thresholds of 1 × 10-4, 0.001, 0.01, 0.05, and 0.1 using individual-level data also showed a protective effect (OR < 1.00) against schizophrenia; the first CRPPRS (built of SNPs with p < 1 × 10-4) showed a statistically significant (p < 2.45 × 10-4) protective effect with an OR of 0.97 (95% CI 0.95-0.99). The CRP GRSGWAS showed that a 10% increase in genetically determined CRP level was significantly associated with coronary artery disease (OR 0.88 [95% CI 0.84-0.94]; p < 2.4 × 10-5) and was nominally associated with the risk of inflammatory bowel disease (OR 0.85 [95% CI 0.74-0.98]; p < 0.03), Crohn disease (OR 0.81 [95% CI 0.70-0.94]; p < 0.005), psoriatic arthritis (OR 1.36 [95% CI 1.00-1.84]; p < 0.049), knee osteoarthritis (OR 1.17 [95% CI 1.01-1.36]; p < 0.04), and bipolar disorder (OR 1.21 [95% CI 1.05-1.40]; p < 0.007) and with an increase of 0.72 (95% CI 0.11-1.34; p < 0.02) mm Hg in systolic blood pressure, 0.45 (95% CI 0.06-0.84; p < 0.02) mm Hg in diastolic blood pressure, 0.01 ml/min/1.73 m2 (95% CI 0.003-0.02; p < 0.005) in estimated glomerular filtration rate from serum creatinine, 0.01 g/dl (95% CI 0.0004-0.02; p < 0.04) in serum albumin level, and 0.03 g/dl (95% CI 0.008-0.05; p < 0.009) in serum protein level. However, after adjustment for heterogeneity, neither GRS showed a significant effect of CRP level (at p < 0.0016) on any of these outcomes, including coronary artery disease, nor on the other 20 complex outcomes studied. Our study has two potential limitations: the limited variance explained by our genetic instruments modeling CRP levels in blood and the unobserved bias introduced by the use of summary statistics in our MR analyses.

CONCLUSIONS

Genetically elevated CRP levels showed a significant potentially protective causal relationship with risk of schizophrenia. We observed nominal evidence at an observed p < 0.05 using either GRSCRP or GRSGWAS-with persistence after correction for heterogeneity-for a causal relationship of elevated CRP levels with psoriatic osteoarthritis, rheumatoid arthritis, knee osteoarthritis, systolic blood pressure, diastolic blood pressure, serum albumin, and bipolar disorder. These associations remain yet to be confirmed. We cannot verify any causal effect of CRP level on any of the other common somatic and neuropsychiatric outcomes investigated in the present study. This implies that interventions that lower CRP level are unlikely to result in decreased risk for the majority of common complex outcomes.

Recent Advances in Defining the Genetic Basis of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is the most common inflammatory arthritis and exhibits genetic overlap with other autoimmune and inflammatory disorders. Although predominant associations with the HLA-DRB1 locus have been known for decades, recent data have revealed additional insight into the likely causative variants within HLA-DRB1 as well as within other HLA loci that contribute to disease risk. In addition, more than 100 common variants in non-HLA loci have been implicated in disease susceptibility. Genetic factors are involved not only in the development of RA, but also with various disease subphenotypes, including production and circulating levels of autoantibodies and joint destruction. The major current challenge is to integrate these new data into a precise understanding of disease pathogenesis, including the critical cell types and molecular networks involved as well as interactions with environmental factors. We predict that delineating the functional effects of genetic variants is likely to drive new diagnostic and therapeutic approaches to the disease.

A general framework for meta-analyzing dependent studies with overlapping subjects in association mapping

Meta-analysis strategies have become critical to augment power of genome-wide association studies (GWAS). To reduce genotyping or sequencing cost, many studies today utilize shared controls, and these individuals can inadvertently overlap among multiple studies. If these overlapping individuals are not taken into account in meta-analysis, they can induce spurious associations. In this article, we propose a general framework for adjusting association statistics to account for overlapping subjects within a meta-analysis. The key idea of our method is to transform the covariance structure of the data, so it can be used in downstream analyses. As a result, the strategy is very flexible and allows a wide range of meta-analysis methods, such as the random effects model, to account for overlapping subjects. Using simulations and real datasets, we demonstrate that our method has utility in meta-analyses of GWAS, as well as in a multi-tissue mouse expression quantitative trait loci (eQTL) study where our method increases the number of discovered eQTL by up to 19% compared with existing methods.

Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.

Rheumatoid Factor Is Associated With the Distribution of Hand Joint Destruction in Rheumatoid Arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is a chronic disease leading to joint destruction. Although many studies have addressed factors potentially correlated with the speed of joint destruction, less attention has been paid to the distribution of joint destruction in patients with RA. In this study, destruction of the hand bones in patients with RA was classified into 2 anatomic subgroups, the fingers and the non-fingers, with the aim of analyzing which factors are associated with destruction of the finger joints.

METHODS

A total of 1,215 Japanese patients with RA were recruited from 2 different populations. The degree of joint destruction was assessed using the total modified Sharp/van der Heijde score (SHS) of radiographic joint damage. The SHS score of joint damage in the finger joints was used as the dependent variable, and the SHS score in the non-finger joints was used as a covariate. Age, sex, disease duration, smoking, C-reactive protein level, treatment for RA, and positivity for and levels of anti-citrullinated protein antibodies and rheumatoid factor (RF) were evaluated as candidate correlates. Overall effect sizes were assessed in a meta-analysis. In addition, associations observed in the Japanese patients were compared to those in a cohort of 157 Dutch RA patients in the BeSt study (a randomized, controlled trial involving 4 different strictly specified treatment strategies for early RA).

RESULTS

Not surprisingly, disease duration in Japanese patients with RA was associated with the finger SHS score (P ≤ 0.00037). Both positivity for and levels of RF showed significant associations with the finger SHS score after adjustment for covariates (P = 0.0022 and P = 8.1 × 10(-7) , respectively). These associations were also true in relation to the time-averaged finger SHS score. An association between RF positivity and the finger SHS score was also observed in Dutch patients with RA in the BeSt study (P = 0.049).

CONCLUSION

Positivity for and levels of RF are associated with finger joint destruction independent of non-finger joint destruction and other covariates. Our findings suggest that there are different mechanisms of joint destruction operating in the finger joints of patients with RA.

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci

We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn's disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European ancestry, we identified 244 independent multidisease signals, including 27 new genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multidisease signals with expression data sets from human, rat and mouse together with epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases genetically identical to those with another disease, possibly owing to diagnostic misclassification, molecular subtypes or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes.

Autoimmune diseases - connecting risk alleles with molecular traits of the immune system

Genome-wide strategies have driven the discovery of more than 300 susceptibility loci for autoimmune diseases. However, for almost all loci, understanding of the mechanisms leading to autoimmunity remains limited, and most variants that are likely to be causal are in non-coding regions of the genome. A critical next step will be to identify the in vivo and ex vivo immunophenotypes that are affected by risk variants. To do this, key cell types and cell states that are implicated in autoimmune diseases will need to be defined. Functional genomic annotations from these cell types and states can then be used to resolve candidate genes and causal variants. Together with longitudinal studies, this approach may yield pivotal insights into how autoimmunity is triggered.

Interactions between amino acid-defined major histocompatibility complex class II variants and smoking in seropositive rheumatoid arthritis

OBJECTIVE

To define the interaction between cigarette smoking and HLA polymorphisms in seropositive rheumatoid arthritis (RA), in the context of a recently identified amino acid-based HLA model for RA susceptibility.

METHODS

We imputed Immunochip data on HLA amino acids and classical alleles from 3 case-control studies (the Swedish Epidemiological Investigation of Rheumatoid Arthritis [EIRA] study [1,654 cases and 1,934 controls], the Nurses' Health Study [NHS] [229 cases and 360 controls], and the Korean RA Cohort Study [1,390 cases and 735 controls]). We examined the interaction effects of heavy smoking (>10 pack-years) and the genetic risk score (GRS) of multiple RA-associated amino acid positions (positions 11, 13, 71, and 74 in HLA-DRβ1, position 9 in HLA-B, and position 9 in HLA-DPβ1), as well as the interaction effects of heavy smoking and the GRS of HLA-DRβ1 4-amino acid haplotypes (assessed via attributable proportion due to interaction [AP] using the additive interaction model).

RESULTS

Heavy smoking and all investigated HLA amino acid positions and haplotypes were associated with RA susceptibility in the 3 populations. In the interaction analysis, we found a significant deviation from the expected additive joint effect between heavy smoking and the HLA-DRβ1 4-amino acid haplotype (AP 0.416, 0.467, and 0.796, in the EIRA, NHS, and Korean studies, respectively). We further identified the key interacting variants as being located at HLA-DRβ1 amino acid positions 11 and 13 but not at any of the other RA risk-associated amino acid positions. For residues in positions 11 and 13, there were similar patterns between RA risk effects and interaction effects.

CONCLUSION

Our findings of significant gene-environment interaction effects indicate that a physical interaction between citrullinated autoantigens produced by smoking and HLA-DR molecules is characterized by the HLA-DRβ1 4-amino acid haplotype, primarily by positions 11 and 13.

Rare Variants in the Functional Domains of Complement Factor H Are Associated With Age-Related Macular Degeneration

PURPOSE

Age-related macular degeneration (AMD) has a substantial genetic risk component, as evidenced by the risk from common genetic variants uncovered in the first genome-wide association studies. More recently, it has become apparent that rare genetic variants also play an independent role in AMD risk. We sought to determine if rare variants in complement factor H (CFH) played a role in AMD risk.

METHODS

We had previously collected DNA from a large population of patients with advanced age-related macular degeneration (A-AMD) and controls for targeted deep sequencing of candidate AMD risk genes. In this analysis, we tested for an increased burden of rare variants in CFH in 1665 cases and 752 controls from this cohort.

RESULTS

We identified 65 missense, nonsense, or splice-site mutations with a minor allele frequency ≤ 1%. Rare variants with minor allele frequency ≤ 1% (odds ratio [OR] = 1.5, P = 4.4 × 10⁻²), 0.5% (OR = 1.6, P = 2.6 × 10⁻²), and all singletons (OR = 2.3, P = 3.3 × 10⁻²) were enriched in A-AMD cases. Moreover, we observed loss-of-function rare variants (nonsense, splice-site, and loss of a conserved cysteine) in 10 cases and serum levels of FH were decreased in all 5 with an available sample (haploinsufficiency). Further, rare variants in the major functional domains of CFH were increased in cases (OR = 3.2; P = 1.4 × 10⁻³) and the magnitude of the effect correlated with the disruptive nature of the variant, location in an active site, and inversely with minor allele frequency.

CONCLUSIONS

In this large A-AMD cohort, rare variants in the CFH gene were enriched and tended to be located in functional sites or led to low serum levels. These data, combined with those indicating a similar, but even more striking, increase in rare variants found in CFI, strongly implicate complement activation in A-AMD etiopathogenesis as CFH and CFI interact to inhibit the alternative pathway.

Loci associated with N-glycosylation of human IgG are not associated with rheumatoid arthritis: a Mendelian randomisation study

OBJECTIVES

A recent study identified 16 genetic variants associated with N-glycosylation of human IgG. Several of the genomic regions where these single nucleotide polymorphisms (SNPs) reside have also been associated with autoimmune disease (AID) susceptibility, suggesting there may be pleiotropy (genetic sharing) between loci controlling both N-glycosylation and AIDs. We investigated this by testing variants associated with levels of IgG N-glycosylation for association with rheumatoid arthritis (RA) susceptibility using a Mendelian randomisation study, and testing a subset of these variants in a less well-powered study of treatment response and severity.

METHODS

SNPs showing association with IgG N-glycosylation were analysed for association with RA susceptibility in 14 361 RA cases and 43 923 controls. Five SNPs were tested for association with response to anti-tumour necrosis factor (TNF) therapy in 1081 RA patient samples and for association with radiological disease severity in 342 patients.

RESULTS

Only one SNP (rs9296009) associated with N-glycosylation showed an association (p=6.92×10(-266)) with RA susceptibility, although this was due to linkage disequilibrium with causal human leukocyte antigen (HLA) variants. Four regions of the genome harboured SNPs associated with both traits (shared loci); although statistical analysis indicated that the associations observed for the two traits are independent. No SNPs showed association with response to anti-TNF therapy. One SNP rs12342831 was modestly associated with Larsen score (p=0.05).

CONCLUSIONS

In a large, well-powered cohort of RA patients, we show SNPs driving levels of N-glycosylation have no association with RA susceptibility, indicating colocalisation of associated SNPs are not necessarily indicative of a shared genetic background or a role for glycosylation in disease susceptibility.

Functional implications of disease-specific variants in loci jointly associated with coeliac disease and rheumatoid arthritis

Hundreds of genomic loci have been associated with a significant number of immune-mediated diseases, and a large proportion of these associated loci are shared among traits. Both the molecular mechanisms by which these loci confer disease susceptibility and the extent to which shared loci are implicated in a common pathogenesis are unknown. We therefore sought to dissect the functional components at loci shared between two autoimmune diseases: coeliac disease (CeD) and rheumatoid arthritis (RA). We used a cohort of 12 381 CeD cases and 7827 controls, and another cohort of 13 819 RA cases and 12 897 controls, all genotyped with the Immunochip platform. In the joint analysis, we replicated 19 previously identified loci shared by CeD and RA and discovered five new non-HLA loci shared by CeD and RA. Our fine-mapping results indicate that in nine of 24 shared loci the associated variants are distinct in the two diseases. Using cell-type-specific histone markers, we observed that loci which pointed to the same variants in both diseases were enriched for marks of promoters active in CD14+ and CD34+ immune cells (P < 0.001), while loci pointing to distinct variants in one of the two diseases showed enrichment for marks of more specialized cell types, like CD4+ regulatory T cells in CeD (P < 0.0001) compared with Th17 and CD15+ in RA (P = 0.0029).

Partitioning heritability by functional annotation using genome-wide association summary statistics

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many cell type-specific enrichments, including significant enrichment of central nervous system cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior.

Disproportionate Contributions of Select Genomic Compartments and Cell Types to Genetic Risk for Coronary Artery Disease

Large genome-wide association studies (GWAS) have identified many genetic loci associated with risk for myocardial infarction (MI) and coronary artery disease (CAD). Concurrently, efforts such as the National Institutes of Health (NIH) Roadmap Epigenomics Project and the Encyclopedia of DNA Elements (ENCODE) Consortium have provided unprecedented data on functional elements of the human genome. In the present study, we systematically investigate the biological link between genetic variants associated with this complex disease and their impacts on gene function. First, we examined the heritability of MI/CAD according to genomic compartments. We observed that single nucleotide polymorphisms (SNPs) residing within nearby regulatory regions show significant polygenicity and contribute between 59–71% of the heritability for MI/CAD. Second, we showed that the polygenicity and heritability explained by these SNPs are enriched in histone modification marks in specific cell types. Third, we found that a statistically higher number of 45 MI/CAD-associated SNPs that have been identified from large-scale GWAS studies reside within certain functional elements of the genome, particularly in active enhancer and promoter regions. Finally, we observed significant heterogeneity of this signal across cell types, with strong signals observed within adipose nuclei, as well as brain and spleen cell types. These results suggest that the genetic etiology of MI/CAD is largely explained by tissue-specific regulatory perturbation within the human genome.

Coronary artery disease (CAD) and its subcomponent, myocardial infarction (MI), are the leading causes of infirmity and death worldwide. Large-scale genetic association studies have identified many genetic markers associated with CAD and MI. However, it has been difficult to determine the precise functional effects of these markers. Furthermore, it is unknown which cell types are biologically important in the development of MI/CAD. By intersecting findings from large-scale genetic association studies with functional genomic annotations, we show that genetic markers located in genomic regions that regulate expression of genes make up a large proportion of the genetic risk of MI/CAD. Furthermore, we show that this effect is particularly strong in certain tissues, including adipose, brain and spleen tissue. These results highlight the role of tissue-specific regulatory mechanisms in the genetic etiology of MI/CAD.

Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases

Human leukocyte antigen (HLA) genes confer strong risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen binding repertoires between a heterozygote’s two expressed HLA variants may result in additional non-additive risk effects. We tested non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (RA, N_cases=5,337), type 1 diabetes (T1D, N_cases=5,567), psoriasis vulgaris (N_cases=3,089), idiopathic achalasia (N_cases=727), and celiac disease (N_cases=11,115). In four out of five diseases, we observed highly significant non-additive dominance effects (RA: P=2.5×10¹²; T1D: P=2.4×10⁻¹⁰; psoriasis: P=5.9×10⁻⁶; celiac disease: P=1.2×10⁻⁸⁷). In three of these diseases, the dominance effects were explained by interactions between specific classical HLA alleles (RA: P=1.8×10⁻³; T1D: P=8.6×10²⁷; celiac disease: P=6.0×10⁻¹⁰⁰). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (RA: 1.4%, T1D: 4.0%, and celiac disease: 4.1%, beyond a simple additive model).

Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci

Identifying genomic annotations that differentiate causal from trait-associated variants is essential to fine mapping disease loci. Although many studies have identified non-coding functional annotations that overlap disease-associated variants, these annotations often colocalize, complicating the ability to use these annotations for fine mapping causal variation. We developed a statistical approach (Genomic Annotation Shifter [GoShifter]) to assess whether enriched annotations are able to prioritize causal variation. GoShifter defines the null distribution of an annotation overlapping an allele by locally shifting annotations; this approach is less sensitive to biases arising from local genomic structure than commonly used enrichment methods that depend on SNP matching. Local shifting also allows GoShifter to identify independent causal effects from colocalizing annotations. Using GoShifter, we confirmed that variants in expression quantitative trail loci drive gene-expression changes though DNase-I hypersensitive sites (DHSs) near transcription start sites and independently through 3' UTR regulation. We also showed that (1) 15%-36% of trait-associated loci map to DHSs independently of other annotations; (2) loci associated with breast cancer and rheumatoid arthritis harbor potentially causal variants near the summits of histone marks rather than full peak bodies; (3) variants associated with height are highly enriched in embryonic stem cell DHSs; and (4) we can effectively prioritize causal variation at specific loci.

Accurate and fast multiple-testing correction in eQTL studies

In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic variant with the minimum p value among all variants in cis with a gene and corrects for multiple testing to obtain a gene-level p value. For performing multiple-testing correction, a permutation test is widely used. Because of growing sample sizes of eQTL studies, however, the permutation test has become a computational bottleneck in eQTL studies. In this paper, we propose an efficient approach for correcting for multiple testing and assess eGene p values by utilizing a multivariate normal distribution. Our approach properly takes into account the linkage-disequilibrium structure among variants, and its time complexity is independent of sample size. By applying our small-sample correction techniques, our method achieves high accuracy in both small and large studies. We have shown that our method consistently produces extremely accurate p values (accuracy > 98%) for three human eQTL datasets with different sample sizes and SNP densities: the Genotype-Tissue Expression pilot dataset, the multi-region brain dataset, and the HapMap 3 dataset.