Risk of Paradoxical Eczema in Patients Receiving Biologics for Psoriasis.

Importance: Biologics used for plaque psoriasis have been reported to be associated with an atopic dermatitis (AD) phenotype, or paradoxical eczema, in some patients. The risk factors for this are unknown. Objective: To explore risk of paradoxical eczema by biologic class and identify factors associated with paradoxical eczema. Design, Setting, and Participants: This prospective cohort study used data from the British Association of Dermatologists Biologics and Immunomodulators Register for adults treated with biologics for plaque psoriasis who were seen at multicenter dermatology clinics in the UK and Ireland. Included participants were registered and had 1 or more follow-up visits between September 2007 and December 2022. Exposures: Duration of exposure to tumor necrosis factor (TNF) inhibitors, interleukin (IL) 17 inhibitors, IL-12/23 inhibitors, or IL-23 inhibitors until paradoxical eczema onset, treatment discontinuation, last follow-up, or death. Main Outcomes and Measures: Incidence rates of paradoxical eczema, paradoxical eczema risk by biologic class, and the association of demographic and clinical variables with risk of paradoxical eczema were assessed using propensity score-weighted Cox proportional hazards regression models. Results: Of 56 553 drug exposures considered, 24 997 from 13 699 participants were included. The 24 997 included exposures (median age, 46 years [IQR, 36-55 years]; 57% male) accrued a total exposure time of 81 441 patient-years. A total of 273 exposures (1%) were associated with paradoxical eczema. The adjusted incidence rates were 1.22 per 100 000 person-years for IL-17 inhibitors, 0.94 per 100 000 person-years for TNF inhibitors, 0.80 per 100 000 person-years for IL-12/23 inhibitors, and 0.56 per 100 000 person-years for IL-23 inhibitors. Compared with TNF inhibitors, IL-23 inhibitors were associated with a lower risk of paradoxical eczema (hazard ratio [HR], 0.39; 95% CI, 0.19-0.81), and there was no association of IL-17 inhibitors (HR, 1.03; 95% CI, 0.74-1.42) or IL-12/23 inhibitors (HR, 0.87; 95% CI, 0.66-1.16) with risk of paradoxical eczema. Increasing age (HR, 1.02 per year; 95% CI, 1.01-1.03) and history of AD (HR, 12.40; 95% CI, 6.97-22.06) or hay fever (HR, 3.78; 95% CI, 1.49-9.53) were associated with higher risk of paradoxical eczema. There was a lower risk in males (HR, 0.60; 95% CI, 0.45-0.78). Conclusions and Relevance: In this study, in biologic-treated patients with psoriasis, paradoxical eczema risk was lowest in patients receiving IL-23 inhibitors. Increasing age, female sex, and history of AD or hay fever were associated with higher risk of paradoxical eczema. The overall incidence of paradoxical eczema was low. Further study is needed to replicate these findings.

Integrated proteomics and genomics analysis of paradoxical eczema in psoriasis patients treated with biologics.

BACKGROUND: Few studies have explored the immunology and genetic risk of paradoxical eczema occurring as an adverse event of biologic therapy in patients with psoriasis. OBJECTIVES: We sought to describe the systemic inflammatory signature of paradoxical eczema using proteomics and explore whether this is genetically mediated. METHODS: This study used the Olink Target 96 Inflammation panel on 256 serum samples from 71 patients with psoriasis and paradoxical eczema, and 75 controls with psoriasis to identify differentially expressed proteins and enriched gene sets. Case samples from 1 or more time points (T1 prebiologic, T2 postbiologic, and T3 postparadoxical eczema) were matched 1:1 with control samples. Genes contributing to enriched gene sets were selected, and functional single nucleotide polymorphisms used to create polygenic risk scores in a genotyped cohort of 88 paradoxical eczema cases and 3124 psoriasis controls. RESULTS: STAMBP expression was lower in cases at T1 than in controls (log-fold change: -0.44; adjusted P = .022); no other proteins reached statistical significance at equivalent time points. Eleven gene sets including cytokine and chemokine pathways were enriched in cases at T2 and 10 at T3. Of the 39 proteins contributing to enriched gene sets, the majority are associated with the atopic dermatitis serum proteome. A polygenic risk score including 38 functional single nucleotide polymorphisms linked to enriched gene sets was associated with paradoxical eczema (adjusted P = .046). CONCLUSIONS: The paradoxical eczema systemic inflammatory proteome trends toward atopic dermatitis at a gene-set level and is detectable before onset of the phenotype. This signature could be genetically determined.

TYK2 as a novel therapeutic target in psoriasis.

INTRODUCTION: Psoriasis is a chronic inflammatory skin disease affecting approximately 60 million people worldwide. Genome-wide association studies (GWAS) have allowed identification of novel therapeutic targets in psoriasis including tyrosine kinase 2 (TYK2) where an exonic variant within the gene increases the risk of developing psoriasis. AREAS COVERED: This review discusses the role of TYK2 in psoriasis pathogenesis, how that relates to genetic variants and recently published ground-breaking clinical trials of novel TYK2 inhibitors. Keyword searches of PubMed were made until January 2023, using the terms: 'TYK2 inhibitor,' 'TYK2 inhibitor AND psoriasis' and 'TYK2 AND GWAS.' Articles and references have been thoroughly reviewed by the authors. EXPERT OPINION: The TYK2 inhibitor deucravacitinib shows promise as an effective oral agent for treating psoriasis. Longer term data are needed to know if thrombotic risk/cancer risk is distinct from other Janus kinase (JAK) inhibitors. Psoriasis is a complex genetic disease for which risk is influenced by genes and environmental factors. GWAS studies have identified several regions of DNA associated with increased risk of disease. We believe that pathway analysis by genetic and genomic means will be key to optimizing TYK2 therapy for the right person at the right time.

Atopic Polygenic Risk Score Is Associated with Paradoxical Eczema Developing in Patients with Psoriasis Treated with Biologics.

Biologic therapies for psoriasis can cause paradoxical eczema. The role of genetic factors in its pathogenesis is unknown. To identify risk variants, we conducted a GWAS of 3,212 patients with psoriasis, of whom 88 developed paradoxical eczema. Two lead SNPs reached genome-wide significance (P ≤ 5 × 10-8) for association with paradoxical eczema: rs192705221 (near UNC5B, P = 9.52 × 10-10) and rs72925168 (within SLC1A2, P = 1.66 × 10-9). Genome-wide significant SNPs from published GWAS were used to generate polygenic risk scores (PRSs) for atopic eczema, general atopic disease, or a combination, which were tested for association with paradoxical eczema. Improvement over a clinical risk model was assessed by the area under the curve. All three atopy polygenic risk scores were associated with paradoxical eczema (P < 0.05); polygenic risk score for a combination of atopic eczema and general atopic disease had the strongest association (OR = 1.83, 95% CI = 1.17-2.84, P = 0.0078). Including atopic polygenic risk scores in the multivariable model, which included age, sex, atopic background, and psoriatic arthritis history, increased the area under the curve from 0.671 to 0.681-0.686. Atopic genetic burden is associated with paradoxical eczema occurring in biologic-treated patients with psoriasis, indicating shared underlying mechanisms. Incorporating genetic risk may improve treatment outcome prediction models for psoriasis.

Genome-wide association analysis identifies a susceptibility locus for sporadic vestibular schwannoma at 9p21.

Vestibular schwannomas are benign nerve sheath tumours that arise on the vestibulocochlear nerves. Vestibular schwannomas are known to occur in the context of tumour predisposition syndromes NF2-related and LZTR1-related schwannomatosis. However, the majority of vestibular schwannomas present sporadically without identification of germline pathogenic variants. To identify novel genetic associations with risk of vestibular schwannoma development, we conducted a genome-wide association study in a cohort of 911 sporadic vestibular schwannoma cases collated from the neurofibromatosis type 2 genetic testing service in the north-west of England, UK and 5500 control samples from the UK Biobank resource. One risk locus reached genome-wide significance in our association analysis (9p21.3, rs1556516, P = 1.47 × 10-13, odds ratio = 0.67, allele frequency = 0.52). 9p21.3 is a genome-wide association study association hotspot, and a number of genes are localized to this region, notably CDKN2B-AS1 and CDKN2A/B, also referred to as the INK4 locus. Dysregulation of gene products within the INK4 locus have been associated with multiple pathologies and the genes in this region have been observed to directly impact the expression of one another. Recurrent associations of the INK4 locus with components of well-described oncogenic pathways provides compelling evidence that the 9p21.3 region is truly associated with risk of vestibular schwannoma tumorigenesis.

Chromatin Looping Links Target Genes with Genetic Risk Loci for Dermatological Traits.

Chromatin looping between regulatory elements and gene promoters presents a potential mechanism whereby disease risk variants affect their target genes. In this study, we use H3K27ac HiChIP, a method for assaying the active chromatin interactome in two cell lines: keratinocytes and skin lymphoma-derived CD8+ T cells. We integrate public datasets for a lymphoblastoid cell line and primary CD4+ T cells and identify gene targets at risk loci for skin-related disorders. Interacting genes enrich for pathways of known importance in each trait, such as cytokine response (psoriatic arthritis and psoriasis) and replicative senescence (melanoma). We show examples of how our analysis can inform changes in the current understanding of multiple psoriasis-associated risk loci. For example, the variant rs10794648, which is generally assigned to IFNLR1, was linked to GRHL3, a gene essential in skin repair and development, in our dataset. Our findings, therefore, indicate a renewed importance of skin-related factors in the risk of disease.

Characterisation of CD4+ T-cell subtypes using single cell RNA sequencing and the impact of cell number and sequencing depth.

CD4+ T-cells represent a heterogeneous collection of specialised sub-types and are a key cell type in the pathogenesis of many diseases due to their role in the adaptive immune system. By investigating CD4+ T-cells at the single cell level, using RNA sequencing (scRNA-seq), there is the potential to identify specific cell states driving disease or treatment response. However, the impact of sequencing depth and cell numbers, two important factors in scRNA-seq, has not been determined for a complex cell population such as CD4+ T-cells. We therefore generated a high depth, high cell number dataset to determine the effect of reduced sequencing depth and cell number on the ability to accurately identify CD4+ T-cell subtypes. Furthermore, we investigated T-cell signatures under resting and stimulated conditions to assess cluster specific effects of stimulation. We found that firstly, cell number has a much more profound effect than sequencing depth on the ability to classify cells; secondly, this effect is greater when cells are unstimulated and finally, resting and stimulated samples can be combined to leverage additional power whilst still allowing differences between samples to be observed. While based on one individual, these results could inform future scRNA-seq studies to ensure the most efficient experimental design.

Mapping DNA interaction landscapes in psoriasis susceptibility loci highlights KLF4 as a target gene in 9q31.

BACKGROUND: Genome-wide association studies (GWAS) have uncovered many genetic risk loci for psoriasis, yet many remain uncharacterised in terms of the causal gene and their biological mechanism in disease. This is largely a result of the findings that over 90% of GWAS variants map outside of protein-coding DNA and instead are enriched in cell type- and stimulation-specific gene regulatory regions. RESULTS: Here, we use a disease-focused Capture Hi-C (CHi-C) experiment to link psoriasis-associated variants with their target genes in psoriasis-relevant cell lines (HaCaT keratinocytes and My-La CD8+ T cells). We confirm previously assigned genes, suggest novel candidates and provide evidence for complexity at psoriasis GWAS loci. For one locus, uniquely, we combine further epigenomic evidence to demonstrate how a psoriasis-associated region forms a functional interaction with the distant (> 500 kb) KLF4 gene. This interaction occurs between the gene and active enhancers in HaCaT cells, but not in My-La cells. We go on to investigate this long-distance interaction further with Cas9 fusion protein-mediated chromatin modification (CRISPR activation) coupled with RNA-seq, demonstrating how activation of the psoriasis-associated enhancer upregulates KLF4 and its downstream targets, relevant to skin cells and apoptosis. CONCLUSIONS: This approach utilises multiple functional genomic techniques to follow up GWAS-associated variants implicating relevant cell types and causal genes in each locus; these are vital next steps for the translation of genetic findings into clinical benefit.

Diversity of peripheral blood human NK cells identified by single-cell RNA sequencing.

Human natural killer (NK) cells in peripheral blood perform many functions, and classification of specific subsets has been a longstanding goal. We report single-cell RNA sequencing of NK cells, comparing gene expression in unstimulated and interleukin (IL)-2-activated cells from healthy cytomegalovirus (CMV)-negative donors. Three NK cell subsets resembled well-described populations; CD56brightCD16-, CD56dimCD16+CD57-, and CD56dimCD16+CD57+. CD56dimCD16+CD57- cells subdivided to include a population with higher chemokine mRNA and increased frequency of killer-cell immunoglobulin-like receptor expression. Three novel human blood NK cell populations were identified: a population of type I interferon-responding NK cells that were CD56neg; a population exhibiting a cytokine-induced memory-like phenotype, including increased granzyme B mRNA in response to IL-2; and finally, a small population, with low ribosomal expression, downregulation of oxidative phosphorylation, and high levels of immediate early response genes indicative of cellular activation. Analysis of CMV+ donors established that CMV altered the proportion of NK cells in each subset, especially an increase in adaptive NK cells, as well as gene regulation within each subset. Together, these data establish an unexpected diversity in blood NK cells and provide a new framework for analyzing NK cell responses in health and disease.

Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes.

To define potentially causal variants for autoimmune disease, we fine-mapped1,2 76 rheumatoid arthritis (11,475 cases, 15,870 controls)3 and type 1 diabetes loci (9,334 cases, 11,111 controls)4. After sequencing 799 1-kilobase regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We defined credible sets of ≤5 causal variants at 5 rheumatoid arthritis and 10 type 1 diabetes loci. We identified potentially causal missense variants at DNASE1L3, PTPN22, SH2B3, and TYK2, and noncoding variants at MEG3, CD28-CTLA4, and IL2RA. We also identified potential candidate causal variants at SIRPG and TNFAIP3. Using functional assays, we confirmed allele-specific protein binding and differential enhancer activity for three variants: the CD28-CTLA4 rs117701653 SNP, MEG3 rs34552516 indel, and TNFAIP3 rs35926684 indel.

Genetic susceptibility to rheumatoid arthritis and its implications for novel drug discovery.

INTRODUCTION: Over 100 susceptibility loci have now been identified for rheumatoid arthritis (RA), several of which are already the targets of approved RA therapies providing proof of concept for the use of genetics in novel drug development for RA. Determining how these loci contribute to disease will be key to elucidating the mechanisms driving disease development, which has the potential for major impact on therapeutic development. AREAS COVERED: Here the authors review the use of genetics in drug discovery, including the use of 'omics' data to prioritise potential drug targets at susceptibility loci using RA as an exemplar. They discuss the current state of RA genetics its impact on stratified medicine, and how the findings from RA genetics studies can be used to inform drug discovery. EXPERT OPINION: It is anticipated that functional characterisation of disease variants will provide biological validation of a gene as a drug target, providing safer targets, with an increased likelihood of efficacy. In the future, techniques such as genome editing may represent a plausible option for RA therapy. Technologies such as genome-wide chromatin conformation capture Hi-C and CRISPR will be crucial to inform our understanding of how diseases develop and in developing new treatments.

A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases.

There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D; P < 1 × 10(-4)) and for 11 autoimmune diseases and rheumatoid arthritis (RA; P < 1 × 10(-3)). This sharing was not explained by subgroup heterogeneity (corrected PBUHMBOX > 0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P < 1 × 10(-9)) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (PBUHMBOX = 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (P < 1 × 10(-4)) that was not explained by subgroup heterogeneity (PBUHMBOX = 0.28; 9,238 MDD cases).

Brief Report: IRF4 Newly Identified as a Common Susceptibility Locus for Systemic Sclerosis and Rheumatoid Arthritis in a Cross-Disease Meta-Analysis of Genome-Wide Association Studies.

OBJECTIVE: Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that have similar clinical and immunologic characteristics. To date, several shared SSc-RA genetic loci have been identified independently. The aim of the current study was to systematically search for new common SSc-RA loci through an interdisease meta-genome-wide association (meta-GWAS) strategy. METHODS: The study was designed as a meta-analysis combining GWAS data sets of patients with SSc and patients with RA, using a strategy that allowed identification of loci with both same-direction and opposite-direction allelic effects. The top single-nucleotide polymorphisms were followed up in independent SSc and RA case-control cohorts. This allowed an increase in the sample size to a total of 8,830 patients with SSc, 16,870 patients with RA, and 43,393 healthy controls. RESULTS: This cross-disease meta-analysis of the GWAS data sets identified several loci with nominal association signals (P < 5 × 10(-6) ) that also showed evidence of association in the disease-specific GWAS scans. These loci included several genomic regions not previously reported as shared loci, as well as several risk factors that were previously found to be associated with both diseases. Follow-up analyses of the putatively new SSc-RA loci identified IRF4 as a shared risk factor for these 2 diseases (Pcombined = 3.29 × 10(-12) ). Analysis of the biologic relevance of the known SSc-RA shared loci identified the type I interferon and interleukin-12 signaling pathways as the main common etiologic factors. CONCLUSION: This study identified a novel shared locus, IRF4, for the risk of SSc and RA, and highlighted the usefulness of a cross-disease GWAS meta-analysis strategy in the identification of common risk loci.

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.

Capture Hi-C reveals novel candidate genes and complex long-range interactions with related autoimmune risk loci.

Genome-wide association studies have been tremendously successful in identifying genetic variants associated with complex diseases. The majority of association signals are intergenic and evidence is accumulating that a high proportion of signals lie in enhancer regions. We use Capture Hi-C to investigate, for the first time, the interactions between associated variants for four autoimmune diseases and their functional targets in B- and T-cell lines. Here we report numerous looping interactions and provide evidence that only a minority of interactions are common to both B- and T-cell lines, suggesting interactions may be highly cell-type specific; some disease-associated SNPs do not interact with the nearest gene but with more compelling candidate genes (for example, FOXO1, AZI2) often situated several megabases away; and finally, regions associated with different autoimmune diseases interact with each other and the same promoter suggesting common autoimmune gene targets (for example, PTPRC, DEXI and ZFP36L1).

Statistical colocalization of genetic risk variants for related autoimmune diseases in the context of common controls.

Determining whether potential causal variants for related diseases are shared can identify overlapping etiologies of multifactorial disorders. Colocalization methods disentangle shared and distinct causal variants. However, existing approaches require independent data sets. Here we extend two colocalization methods to allow for the shared-control design commonly used in comparison of genome-wide association study results across diseases. Our analysis of four autoimmune diseases--type 1 diabetes (T1D), rheumatoid arthritis, celiac disease and multiple sclerosis--identified 90 regions that were associated with at least one disease, 33 (37%) of which were associated with 2 or more disorders. Nevertheless, for 14 of these 33 shared regions, there was evidence that the causal variants differed. We identified new disease associations in 11 regions previously associated with one or more of the other 3 disorders. Four of eight T1D-specific regions contained known type 2 diabetes (T2D) candidate genes (COBL, GLIS3, RNLS and BCAR1), suggesting a shared cellular etiology.

TYK2 protein-coding variants protect against rheumatoid arthritis and autoimmunity, with no evidence of major pleiotropic effects on non-autoimmune complex traits.

Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3 x 10(-21)), A928V (rs35018800, OR = 0.53, P = 1.2 x 10(-9)), and I684S (rs12720356, OR = 0.86, P = 4.6 x 10(-7)). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6 x 10(-18)), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; P(omnibus) = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing >500 phenotypes using electronic medical records (EMR) in >29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases.

High-density genotyping of immune loci in Koreans and Europeans identifies eight new rheumatoid arthritis risk loci.

OBJECTIVE: A highly polygenic aetiology and high degree of allele-sharing between ancestries have been well elucidated in genetic studies of rheumatoid arthritis. Recently, the high-density genotyping array Immunochip for immune disease loci identified 14 new rheumatoid arthritis risk loci among individuals of European ancestry. Here, we aimed to identify new rheumatoid arthritis risk loci using Korean-specific Immunochip data. METHODS: We analysed Korean rheumatoid arthritis case-control samples using the Immunochip and genome-wide association studies (GWAS) array to search for new risk alleles of rheumatoid arthritis with anticitrullinated peptide antibodies. To increase power, we performed a meta-analysis of Korean data with previously published European Immunochip and GWAS data for a total sample size of 9299 Korean and 45,790 European case-control samples. RESULTS: We identified eight new rheumatoid arthritis susceptibility loci (TNFSF4, LBH, EOMES, ETS1-FLI1, COG6, RAD51B, UBASH3A and SYNGR1) that passed a genome-wide significance threshold (p<5×10(-8)), with evidence for three independent risk alleles at 1q25/TNFSF4. The risk alleles from the seven new loci except for the TNFSF4 locus (monomorphic in Koreans), together with risk alleles from previously established RA risk loci, exhibited a high correlation of effect sizes between ancestries. Further, we refined the number of single nucleotide polymorphisms (SNPs) that represent potentially causal variants through a trans-ethnic comparison of densely genotyped SNPs. CONCLUSIONS: This study demonstrates the advantage of dense-mapping and trans-ancestral analysis for identification of potentially causal SNPs. In addition, our findings support the importance of T cells in the pathogenesis and the fact of frequent overlap of risk loci among diverse autoimmune diseases.

A weighted genetic risk score using all known susceptibility variants to estimate rheumatoid arthritis risk.

BACKGROUND: There is currently great interest in the incorporation of genetic susceptibility loci into screening models to identify individuals at high risk of disease. Here, we present the first risk prediction model including all 46 known genetic loci associated with rheumatoid arthritis (RA). METHODS: A weighted genetic risk score (wGRS) was created using 45 RA non-human leucocyte antigen (HLA) susceptibility loci, imputed amino acids at HLA-DRB1 (11, 71 and 74), HLA-DPB1 (position 9) HLA-B (position 9) and gender. The wGRS was tested in 11 366 RA cases and 15 489 healthy controls. The risk of developing RA was estimated using logistic regression by dividing the wGRS into quintiles. The ability of the wGRS to discriminate between cases and controls was assessed by receiver operator characteristic analysis and discrimination improvement tests. RESULTS: Individuals in the highest risk group showed significantly increased odds of developing anti-cyclic citrullinated peptide-positive RA compared to the lowest risk group (OR 27.13, 95% CI 23.70 to 31.05). The wGRS was validated in an independent cohort that showed similar results (area under the curve 0.78, OR 18.00, 95% CI 13.67 to 23.71). Comparison of the full wGRS with a wGRS in which HLA amino acids were replaced by a HLA tag single-nucleotide polymorphism showed a significant loss of sensitivity and specificity. CONCLUSIONS: Our study suggests that in RA, even when using all known genetic susceptibility variants, prediction performance remains modest; while this is insufficiently accurate for general population screening, it may prove of more use in targeted studies. Our study has also highlighted the importance of including HLA variation in risk prediction models.