Identification of rare coding variants in TYK2 protective for rheumatoid arthritis in the Japanese population and their effects on cytokine signalling

ObjectiveAlthough genome-wide association studies (GWAS) have identified approximately 100 loci for rheumatoid arthritis (RA), the disease mechanisms are not completely understood. We evaluated the pathogenesis of RA by focusing on rare coding variants.MethodsThe coding regions of 98 candidate genes identified by GWAS were sequenced in 2294 patients with RA and 4461 controls in Japan. An association analysis was performed using cases and controls for variants, genes and domains of TYK2. Cytokine responses for two associated variants (R231W, rs201917359; and R703W, rs55882956) in TYK2 as well as a previously reported risk variant (P1004A, rs34536443) for multiple autoimmune diseases were evaluated by reporter assays.ResultsA variant in TYK2 (R703W) showed a suggestive association (p=5.47×10−8, OR=0.48). We observed more accumulation of rare coding variants in controls in TYK2 (p=3.94×10−12, OR=0.56). The four-point-one, ezrin, radixin, moesin (FERM; 2.14×10−3, OR=0.66) and pseudokinase domains (1.63×10−8, OR=0.52) of TYK2 also showed enrichment of variants in controls. R231W in FERM domain especially reduced interleukin (IL)-6 and interferon (IFN)-γ signalling, whereas P1104A in kinase domain reduced IL-12, IL-23 and IFN-α signalling. R703W in pseudokinase domain reduced cytokine signals similarly to P1104A, but the effects were weaker than those of P1104A.ConclusionsThe FERM and pseudokinase domains in TYK2 were associated with the risk of RA in the Japanese population. Variants in TYK2 had different effects on cytokine signalling, suggesting that the regulation of selective cytokine signalling is a target for RA treatment.

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The open targets post-GWAS analysis pipeline

Bioinformatics ◽

10.1093/bioinformatics/btaa020 ◽

2020 ◽

Vol 36 (9) ◽

pp. 2936-2937 ◽

Cited By ~ 4

Author(s):

Gareth Peat ◽

William Jones ◽

Michael Nuhn ◽

José Carlos Marugán ◽

William Newell ◽

...

Keyword(s):

Drug Targets ◽

Gene Expression Regulation ◽

Association Studies ◽

Genome Wide Association Studies ◽

Protein Coding ◽

Data Resource ◽

Coding Regions ◽

Genome Wide ◽

Causal Genes ◽

Interactive Data

Abstract Motivation Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. Results We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. Availability and implementation The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io.

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Association analysis of juvenile idiopathic arthritis genetic susceptibility factors in Estonian patients

Clinical Rheumatology ◽

10.1007/s10067-021-05756-x ◽

2021 ◽

Author(s):

Tiit Nikopensius ◽

Priit Niibo ◽

Toomas Haller ◽

Triin Jagomägi ◽

Ülle Voog-Oras ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Juvenile Idiopathic Arthritis ◽

Autoimmune Diseases ◽

Genetic Risk ◽

Association Studies ◽

Control Sample ◽

Case Control ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract Background Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic condition of childhood. Genetic association studies have revealed several JIA susceptibility loci with the strongest effect size observed in the human leukocyte antigen (HLA) region. Genome-wide association studies have augmented the number of JIA-associated loci, particularly for non-HLA genes. The aim of this study was to identify new associations at non-HLA loci predisposing to the risk of JIA development in Estonian patients. Methods We performed genome-wide association analyses in an entire JIA case–control sample (All-JIA) and in a case–control sample for oligoarticular JIA, the most prevalent JIA subtype. The entire cohort was genotyped using the Illumina HumanOmniExpress BeadChip arrays. After imputation, 16,583,468 variants were analyzed in 263 cases and 6956 controls. Results We demonstrated nominal evidence of association for 12 novel non-HLA loci not previously implicated in JIA predisposition. We replicated known JIA associations in CLEC16A and VCTN1 regions in the oligoarticular JIA sample. The strongest associations in the All-JIA analysis were identified at PRKG1 (P = 2,54 × 10−6), LTBP1 (P = 9,45 × 10−6), and ELMO1 (P = 1,05 × 10−5). In the oligoarticular JIA analysis, the strongest associations were identified at NFIA (P = 5,05 × 10−6), LTBP1 (P = 9,95 × 10−6), MX1 (P = 1,65 × 10−5), and CD200R1 (P = 2,59 × 10−5). Conclusion This study increases the number of known JIA risk loci and provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis. The reported loci are involved in molecular pathways of immunological relevance and likely represent genomic regions that confer susceptibility to JIA in Estonian patients. Key Points• Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease with heterogeneous presentation and genetic predisposition.• Present genome-wide association study for Estonian JIA patients is first of its kind in Northern and Northeastern Europe.• The results of the present study increase the knowledge about JIA risk loci replicating some previously described associations, so adding weight to their relevance and describing novel loci.• The study provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis.

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