OBJECTIVE: Tofacitinib is an oral JAK inhibitor for the treatment of rheumatoid arthritis (RA), psoriatic arthritis, and ulcerative colitis, and has been previously investigated for psoriasis (PsO). This meta-analysis of genome-wide association studies (GWAS) was performed to identify genetic factors associated with increased risk/faster onset of herpes zoster (HZ) in subjects with RA or PsO receiving tofacitinib treatment, and to determine potential mechanisms that could be attributed to the varying rates of HZ across ethnicities. METHODS: In an ethnicity/indication-specific, trans-ethnic, trans-population meta-analysis of GWAS in subjects with RA or PsO from phase II, phase III, and long-term extension studies of tofacitinib, 8 million genetic variants were evaluated for their potential association with time to an HZ event and incidence of an HZ event (case versus control) with tofacitinib treatment, using Cox proportional hazard and logistic regression analyses, respectively. RESULTS: In total, 5,246 subjects were included (3,168 with RA and 2,078 with PsO). After adjustment for age, baseline absolute lymphocyte count, genetically defined ethnicity, and concomitant methotrexate use (in RA subjects only), 4 loci were significantly associated with faster onset of HZ in European subjects (P < 5 × 10-8 ), including a single-nucleotide polymorphism (SNP) near CD83 (frequency of risk allele ~2% in European subjects versus ~0.1% in East Asian subjects). In the trans-ethnic, trans-population meta-analysis, the CD83 SNP remained significant. Four additional significant loci were identified in the meta-analysis, among which a SNP near IL17RB was associated with faster onset of HZ (meta-analysis hazard ratio 3.6 [95% confidence interval 2.40-5.44], P = 7.6 × 10-10 ; frequency of risk allele ~12% in East Asian subjects versus <0.2% in European subjects). CONCLUSION: Genetic analysis of tofacitinib-treated subjects with RA or PsO identified multiple loci associated with increased HZ risk. Prevalent variants near the immune-relevant genes CD83 and IL17RB in European and East Asian populations, respectively, may contribute to risk of HZ in tofacitinib-treated subjects.
Response to tofacitinib treatment (herpes zoster)(time to event)
Response to tofacitinib treatment in psoriasis (herpes zoster)
Response to tofacitinib treatment in rheumatoid arthritis (herpes zoster)(time to event)
Response to tofacitinib treatment in rheumatoid arthritis (herpes zoster)
Response to tofacitinib treatment in psoriasis (herpes zoster)(time to event)
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.
Psychiatric disorders are highly genetically correlated, but little research has been conducted on the genetic differences between disorders. We developed a new method (case-case genome-wide association study; CC-GWAS) to test for differences in allele frequency between cases of two disorders using summary statistics from the respective case-control GWAS, transcending current methods that require individual-level data. Simulations and analytical computations confirm that CC-GWAS is well powered with effective control of type I error. We applied CC-GWAS to publicly available summary statistics for schizophrenia, bipolar disorder, major depressive disorder and five other psychiatric disorders. CC-GWAS identified 196 independent case-case loci, including 72 CC-GWAS-specific loci that were not significant at the genome-wide level in the input case-control summary statistics; two of the CC-GWAS-specific loci implicate the genes KLF6 and KLF16 (from the Krüppel-like family of transcription factors), which have been linked to neurite outgrowth and axon regeneration. CC-GWAS loci replicated convincingly in applications to datasets with independent replication data.
Bipolar disorder vs anorexia nervosa (ordinary least squares (OLS))
Anorexia nervosa vs Tourette's syndrome and other tic disorders (ordinary least squares (OLS))
Schizophrenia vs anorexia nervosa (ordinary least squares (OLS))
Autism spectrum disorder vs Tourette's syndrome and other tic disorders (ordinary least squares (OLS))
Autism spectrum disorder vs obsessive compulsive disorder (ordinary least squares (OLS))
Ulcerative colitis vs rheumatoid arthritis (ordinary least squares (OLS))
Bipolar disorder vs ADHD (ordinary least squares (OLS))
Major depressive disorder vs ADHD (ordinary least squares (OLS))
Bipolar disorder vs major depressive disorder (ordinary least squares (OLS))
Major depressive disorder vs anorexia nervosa (ordinary least squares (OLS))
Schizophrenia vs autism spectrum disorder (ordinary least squares (OLS))
Bipolar disorder vs autism spectrum disorder (ordinary least squares (OLS))
Schizophrenia vs major depressive disorder (ordinary least squares (OLS))
ADHD vs anorexia nervosa (ordinary least squares (OLS))
Schizophrenia vs bipolar disorder (ordinary least squares (OLS))
Bipolar disorder vs obsessive compulsive disorder (ordinary least squares (OLS))
Obsessive compulsive disorder vs Tourette's syndrome and other tic disorders (ordinary least squares (OLS))
Schizophrenia vs Tourette's syndrome and other tic disorders (ordinary least squares (OLS))
Schizophrenia vs ADHD (ordinary least squares (OLS))
ADHD vs autism spectrum disorder (ordinary least squares (OLS))
Bipolar disorder vs Tourette's syndrome and other tic disorders (ordinary least squares (OLS))
Anorexia nervosa vs autism spectrum disorder (ordinary least squares (OLS))
Crohn's disease vs rheumatoid arthritis (ordinary least squares (OLS))
Major depressive disorder vs autism spectrum disorder (ordinary least squares (OLS))
Crohn's disease vs ulcerative colitis (ordinary least squares (OLS))
ADHD vs Tourette's syndrome and other tic disorders (ordinary least squares (OLS))
ADHD vs obsessive compulsive disorder (ordinary least squares (OLS))
OBJECTIVES: Nearly 110 susceptibility loci for rheumatoid arthritis (RA) with modest effect sizes have been identified by population-based genetic association studies, suggesting a large number of undiscovered variants behind a highly polygenic genetic architecture of RA. Here, we performed the largest-ever trans-ancestral meta-analysis with the aim to identify new RA loci and to better understand RA biology underlying genetic associations. METHODS: Genome-wide RA association summary statistics in three large case-control collections consisting of 311 292 individuals of Korean, Japanese and European populations were used in an inverse-variance-weighted fixed-effects meta-analysis. Several computational analyses using public omics resources were conducted to prioritise causal variants and genes, RA variant-implicating features (tissues, pathways and transcription factors) and potentially repurposable drugs for RA treatment. RESULTS: We identified 11 new RA susceptibility loci that explained 6.9% and 1.8% of the single-nucleotide polymorphism-based heritability in East Asians and Europeans, respectively, and confirmed 71 known non-human leukocyte antigens (HLA) susceptibility loci, identifying 90 independent association signals. The RA variants were preferentially located in binding sites of various transcription factors and in cell type-specific transcription-activation histone marks that simultaneously highlighted the importance of CD4+ T-cell activation and the potential role of non-immune organs in RA pathogenesis. A total of 615 plausible effector genes, based on gene-based associations, expression-associated variants and chromatin interaction, included targets of drugs approved for RA treatments and potentially repurposable drugs approved for other indications. CONCLUSION: Our findings provide useful insights regarding RA genetic aetiology and variant-driven RA pathogenesis.
Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (ntotal = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified latent genetic components, which pinpointed responsible variants and biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (for example, allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human diseases through genetics.
Chronic hepatitis B infection
Meniere's disease
Brain tumor
Cirrhosis
Endometrial cancer
Epilepsy
Hyperthyroidism
Asthma
HDL cholesterol
Systemic lupus erythematosus
Medication use (adrenergics, inhalants)
Medication use (diuretics)
Chronic sinusitis
Mean arterial pressure
Prostate cancer
Medication use (drugs used in diabetes)
Medication use (opioids)
Contact dermatitis
Triglycerides
Cardiac valvular disease
Insomnia
LDL cholesterol
Medication use (antithrombotic agents)
Medication use (antidepressants)
Schizophrenia
Chronic bronchitis
Glucose levels
Mean corpuscular hemoglobin
Ulcerative colitis
Iron deficiency anemia
Atrial fibrillation/atrial flutter
Hemoglobin A1c levels
Ovarian cyst
Myocardial infarction
Aplastic anemia
Urticaria
Type 1 diabetes
Dysentery
Weight
Skin cancer
Cervical cancer
Glaucoma
Medication use (glucocorticoids)
Serum alkaline phosphatase levels
Stevens-Johnson syndrome
Aortic aneurysm
Lymphocyte counts
Psoriasis vulgaris
Neutrophil count
Mean corpuscular hemoglobin concentration
Retinitis pigmentosa
Peripheral artery disease
Gastric cancer
Serum uric acid levels
Typhoid fever
Polymyositis
Parkinson's disease
Medication use (drugs affecting bone structure and mineralization)
Keloid
Acute glomerulonephritis
Medication use (antiglaucoma preparations and miotics)
Zoster infection
Medication use (agents acting on the renin-angiotensin system)
Ringworm
Interstitial lung disease
Serum total protein level
Acute pancreatitis
Allergic rhinitis
Medication use (anti-inflammatory and antirheumatic products, non-steroids)
Lung cancer
Ischemic stroke
Sleep apnea syndrome
Esophageal cancer
Medication use (antihistamines for systemic use)
Medication use (calcium channel blockers)
Cystitis
Atopic dermatitis
Thyroid cancer
Sarcoidosis
Pneumothorax
Ventricular arrhythmia
Blood urea nitrogen levels
Nephrotic syndrome
Goiter
Chronic renal failure
C-reactive protein
White blood cell count
Medication use (HMG CoA reductase inhibitors)
Monocyte count
Pyelonephritis
Unstable angina pectoris
Hepatic cancer
Varicose veins
Intracerebral hemorrhage
Spinal canal stenosis
Medication use (thyroid preparations)
Aspartate aminotransferase levels
Gastroesophageal reflux disease
Hematocrit
Medication use (immunosuppressants)
Chronic obstructive pulmonary disease
Eosinophil counts
Serum albumin levels
Subarachnoid hemorrhage
Chronic heart failure
Bronchitis
Angina pectoris
Type 2 diabetes
Bronchiectasis
Cholelithiasis
Mastopathy
Uterine fibroids
Alanine aminotransferase levels
Pulse pressure
Juvenile rheumatoid arthritis
Autoimmune hepatitis
Constipation
Medication use (antimigraine preparations)
Diastolic blood pressure
Hypertrophic cardiomyopathy
Rheumatoid arthritis
Medication use (anilides)
Graves' disease
Gastric ulcer
Gastric polyp
Platelet count
Uterine prolapse
Inguinal hernia
Medication use (beta blocking agents)
Chronic glomerulonephritis
Chronic pancreatitis
Depression
Hypothyroidism
Substance dependence
Iritis
Pediatric asthma
Colorectal cancer
Back pain
Medication use (antihypertensives)
Esophageal varix
Hashimoto thyroiditis
Carpal tunnel syndrome
Uveitis
Hemoglobin
Retinal detachment
Pulmonary fibrosis
Neuropathic bladder
Malignant lymphoma
Height
Medication use (drugs for peptic ulcer and gastro-oesophageal reflux disease)
Hepatic bile duct cancer
Pancreatic cancer
Pulmonary tuberculosis
Hearing loss, difficulty in hearing
Systolic blood pressure
Sjögren's syndrome
Gamma glutamyl transpeptidase
Nasal polyps
Medication use (vasodilators used in cardiac diseases)
OBJECTIVE: Genome-wide association studies (GWAS) in rheumatoid arthritis (RA) have discovered over 100 RA loci, explaining patient-relevant RA pathogenesis but showing a large fraction of missing heritability. As a continuous effort, we conducted GWAS in a large Korean RA case-control population. METHODS: We newly generated genome-wide variant data in two independent Korean cohorts comprising 4068 RA cases and 36 487 controls, followed by a whole-genome imputation and a meta-analysis of the disease association results in the two cohorts. By integrating publicly available omics data with the GWAS results, a series of bioinformatic analyses were conducted to prioritise the RA-risk genes in RA loci and to dissect biological mechanisms underlying disease associations. RESULTS: We identified six new RA-risk loci (SLAMF6, CXCL13, SWAP70, NFKBIA, ZFP36L1 and LINC00158) with pmeta<5×10-8 and consistent disease effect sizes in the two cohorts. A total of 122 genes were prioritised from the 6 novel and 13 replicated RA loci based on physical distance, regulatory variants and chromatin interaction. Bioinformatics analyses highlighted potentially RA-relevant tissues (including immune tissues, lung and small intestine) with tissue-specific expression of RA-associated genes and suggested the immune-related gene sets (such as CD40 pathway, IL-21-mediated pathway and citrullination) and the risk-allele sharing with other diseases. CONCLUSION: This study identified six new RA-associated loci that contributed to better understanding of the genetic aetiology and biology in RA.
Rheumatoid arthritis (RA) is a common chronic autoimmune disease leading to joint destruction. The aim of the present study was to identify the genomic factors predictive of susceptibility to joint destruction in patients with RA by performing a genome-wide association study of genetic variants, including single nucleotide polymorphisms (SNPs). The study sample included 228 patients with a diagnosis of RA in the past 5 years. Patients were classified into rapid (total Sharp score/years of RA, ≥50) and slow (total Sharp score/years of RA, <50) joint destruction groups for analysis. The association between the genome-wide SNP analysis and joint destruction was evaluated. The following SNPs were strongly associated with rapid radiographic joint destruction: rs2295926 (P<1x10-7), belonging to the N-acetylgalactosaminyltransferase 12 (GALNT12) gene and rs11958855 (P<1x10-6), belonging to the KCNN2 gene (associated with the potassium calcium-activated channel subfamily). The identification of genetic predictors of rapid joint destruction in RA (GALNT12 and KCNN2) may provide information regarding potential therapeutic targets, and this information may be used to assist in the management RA disease progression, thereby improving the functional outcomes for patients.
joint destruction in rheumatoid arthritis (rapid vs slow)
Aim: To identify novel genetic variants predisposing to elevation of Alanine aminotransferase (ALT) in rheumatoid arthritis (RA) patients after initiation of methotrexate (MTX) treatment. Patients & methods: We performed genome-wide association studies in 198 RA patients starting MTX. Outcomes were maximum level of ALT and ALT >1.5-times the upper level of normal within the first 6 months of treatment. Results: RAVER2 (rs72675408) was significantly associated with maximum level of ALT (p = 4.36 × 10-8). This variant is in linkage disequilibrium with rs72675451, which is associated with differential expression of JAK1 and RAVER2. Conclusion: We found an association between ALT elevation and genetic variants that may regulate the expression of JAK1 and RAVER2. JAK1 encodes a janus kinase involved in the pathogenesis of RA.
Alanine aminotransferase level after methotrexate initiation in rheumatoid arthritis
OBJECTIVES: The present study aimed to discover novel susceptibility loci associated with risk of rheumatoid arthritis (RA). METHODS: We performed a new genome-wide association study (GWAS) in Chinese subjects (1027 RA cases and 2879 controls) and further conducted an expanded meta-analysis with previous GWAS summary data and replication studies. The functional roles of the associated loci were interrogated using publicly available databases. Dual-luciferase reporter and cytokine assay were also used for exploring variant function. RESULTS: We identified five new susceptibility loci (IL12RB2, BOLL-PLCL1, CCR2, TCF7 and IQGAP1; pmeta <5.00E-08) with same effect direction in each study cohort. The sensitivity analyses showed that the genetic association of at least three loci was reliable and robust. All these lead variants are expression quantitative trait loci and overlapped with epigenetic marks in immune cells. Furthermore, genes within the five loci are genetically associated with risk of other autoimmune diseases, and genes within four loci are known functional players in autoimmunity, which supports the validity of our findings. The reporter assay showed that the risk allele of rs8030390 in IQGAP1 have significantly increased reporter activity in HEK293T cells. In addition, the cytokine assay found that the risk allele of rs244672 in TCF7 was most significantly associated with increased plasma IL-17A levels in healthy controls. Finally, identified likely causal genes in these loci significantly interacted with RA drug targets. CONCLUSION: This study identified novel RA risk loci and highlighted that comprehensive genetic study can provide important information for RA pathogenesis and drug therapy.
The overwhelming majority of participants in current genetic studies are of European ancestry. To elucidate disease biology in the East Asian population, we conducted a genome-wide association study (GWAS) with 212,453 Japanese individuals across 42 diseases. We detected 320 independent signals in 276 loci for 27 diseases, with 25 novel loci (P < 9.58 × 10-9). East Asian-specific missense variants were identified as candidate causal variants for three novel loci, and we successfully replicated two of them by analyzing independent Japanese cohorts; p.R220W of ATG16L2 (associated with coronary artery disease) and p.V326A of POT1 (associated with lung cancer). We further investigated enrichment of heritability within 2,868 annotations of genome-wide transcription factor occupancy, and identified 378 significant enrichments across nine diseases (false discovery rate < 0.05) (for example, NKX3-1 for prostate cancer). This large-scale GWAS in a Japanese population provides insights into the etiology of complex diseases and highlights the importance of performing GWAS in non-European populations.
Autoimmune thyroid disease is the most common autoimmune disease and is highly heritable1. Here, by using a genome-wide association study of 30,234 cases and 725,172 controls from Iceland and the UK Biobank, we find 99 sequence variants at 93 loci, of which 84 variants are previously unreported2-7. A low-frequency (1.36%) intronic variant in FLT3 (rs76428106-C) has the largest effect on risk of autoimmune thyroid disease (odds ratio (OR) = 1.46, P = 2.37 × 10-24). rs76428106-C is also associated with systemic lupus erythematosus (OR = 1.90, P = 6.46 × 10-4), rheumatoid factor and/or anti-CCP-positive rheumatoid arthritis (OR = 1.41, P = 4.31 × 10-4) and coeliac disease (OR = 1.62, P = 1.20 × 10-4). FLT3 encodes fms-related tyrosine kinase 3, a receptor that regulates haematopoietic progenitor and dendritic cells. RNA sequencing revealed that rs76428106-C generates a cryptic splice site, which introduces a stop codon in 30% of transcripts that are predicted to encode a truncated protein, which lacks its tyrosine kinase domains. Each copy of rs76428106-C doubles the plasma levels of the FTL3 ligand. Activating somatic mutations in FLT3 are associated with acute myeloid leukaemia8 with a poor prognosis and rs76428106-C also predisposes individuals to acute myeloid leukaemia (OR = 1.90, P = 5.40 × 10-3). Thus, a predicted loss-of-function germline mutation in FLT3 causes a reduction in full-length FLT3, with a compensatory increase in the levels of its ligand and an increased disease risk, similar to that of a gain-of-function mutation.
BACKGROUND: Biopharmaceutical products (BPs) are widely used to treat autoimmune diseases, but immunogenicity limits their efficacy for an important proportion of patients. Our knowledge of patient-related factors influencing the occurrence of antidrug antibodies (ADAs) is still limited. METHODS AND FINDINGS: The European consortium ABIRISK (Anti-Biopharmaceutical Immunization: prediction and analysis of clinical relevance to minimize the RISK) conducted a clinical and genomic multicohort prospective study of 560 patients with multiple sclerosis (MS, n = 147), rheumatoid arthritis (RA, n = 229), Crohn's disease (n = 148), or ulcerative colitis (n = 36) treated with 8 different biopharmaceuticals (etanercept, n = 84; infliximab, n = 101; adalimumab, n = 153; interferon [IFN]-beta-1a intramuscularly [IM], n = 38; IFN-beta-1a subcutaneously [SC], n = 68; IFN-beta-1b SC, n = 41; rituximab, n = 31; tocilizumab, n = 44) and followed during the first 12 months of therapy for time to ADA development. From the bioclinical data collected, we explored the relationships between patient-related factors and the occurrence of ADAs. Both baseline and time-dependent factors such as concomitant medications were analyzed using Cox proportional hazard regression models. Mean age and disease duration were 35.1 and 0.85 years, respectively, for MS; 54.2 and 3.17 years for RA; and 36.9 and 3.69 years for inflammatory bowel diseases (IBDs). In a multivariate Cox regression model including each of the clinical and genetic factors mentioned hereafter, among the clinical factors, immunosuppressants (adjusted hazard ratio [aHR] = 0.408 [95% confidence interval (CI) 0.253-0.657], p < 0.001) and antibiotics (aHR = 0.121 [0.0437-0.333], p < 0.0001) were independently negatively associated with time to ADA development, whereas infections during the study (aHR = 2.757 [1.616-4.704], p < 0.001) and tobacco smoking (aHR = 2.150 [1.319-3.503], p < 0.01) were positively associated. 351,824 Single-Nucleotide Polymorphisms (SNPs) and 38 imputed Human Leukocyte Antigen (HLA) alleles were analyzed through a genome-wide association study. We found that the HLA-DQA1*05 allele significantly increased the rate of immunogenicity (aHR = 3.9 [1.923-5.976], p < 0.0001 for the homozygotes). Among the 6 genetic variants selected at a 20% false discovery rate (FDR) threshold, the minor allele of rs10508884, which is situated in an intron of the CXCL12 gene, increased the rate of immunogenicity (aHR = 3.804 [2.139-6.764], p < 1 × 10-5 for patients homozygous for the minor allele) and was chosen for validation through a CXCL12 protein enzyme-linked immunosorbent assay (ELISA) on patient serum at baseline before therapy start. CXCL12 protein levels were higher for patients homozygous for the minor allele carrying higher ADA risk (mean: 2,693 pg/ml) than for the other genotypes (mean: 2,317 pg/ml; p = 0.014), and patients with CXCL12 levels above the median in serum were more prone to develop ADAs (aHR = 2.329 [1.106-4.90], p = 0.026). A limitation of the study is the lack of replication; therefore, other studies are required to confirm our findings. CONCLUSION: In our study, we found that immunosuppressants and antibiotics were associated with decreased risk of ADA development, whereas tobacco smoking and infections during the study were associated with increased risk. We found that the HLA-DQA1*05 allele was associated with an increased rate of immunogenicity. Moreover, our results suggest a relationship between CXCL12 production and ADA development independent of the disease, which is consistent with its known function in affinity maturation of antibodies and plasma cell survival. Our findings may help physicians in the management of patients receiving biotherapies.
Anti-drug antibodies in autoimmune disease (time to event)
OBJECTIVES: The genetic background of rheumatoid arthritis-interstitial lung disease (RA-ILD) has been evaluated in Europeans, but little knowledge has been obtained in non-Europeans. This study aimed to elucidate genome-wide risk of RA-ILD in non-Europeans. METHODS: We performed an initial genome-wide association study (GWAS) of RA-ILD in the Japanese population. By conducting the meta-analysis of the three GWAS datasets of the RA cohorts and biobank of Japanese, our study included 358 RA-ILD cases and 4550 RA subjects without ILD. We then conducted the stratified analysis of the effect of the GWAS risk allele in each CT image pattern. RESULTS: We identified one novel RA-ILD risk locus at 7p21 that satisfied the genome-wide significance threshold (rs12702634 at RPA3-UMAD1, OR=2.04, 95% CI 1.59 to 2.60, p=1.5×10-8). Subsequent stratified analysis based on the CT image patterns demonstrated that the effect size of the RA-ILD risk allele (rs12702634-C) was large with the UIP pattern (OR=1.86, 95% CI 0.97 to 3.58, p=0.062) and the probable UIP pattern (OR=2.26, 95% CI 1.36 to 3.73, p=0.0015). CONCLUSION: We revealed one novel genetic association with RA-ILD in Japanese. The RA-ILD risk of the identified variant at RPA3-UMAD1 was relatively high in the CT image patterns related to fibrosis. Our study should contribute to elucidation of the complicated aetiology of RA-ILD.
Interstitial lung diseases in rheumatoid arthritis
Certolizumab pegol (CZP) is a PEGylated Fc-free tumor necrosis factor (TNF) inhibitor antibody approved for use in the treatment of rheumatoid arthritis (RA), Crohns disease, psoriatic arthritis, axial spondyloarthritis and psoriasis. In a clinical trial of patients with severe RA, CZP improved disease symptoms in approximately half of patients. However, variability in CZP efficacy remains a problem for clinicians, thus, the aim of this study was to identify genetic variants predictive of CZP response. We performed a genome-wide association study (GWAS) of 302 RA patients treated with CZP in the REALISTIC trial to identify common single nucleotide polymorphisms (SNPs) associated with treatment response. Whole-exome sequencing was also performed for 74 CZP extreme responders and non-responders within the same population, as well as 1546 population controls. No common SNPs or rare functional variants were significantly associated with CZP response, though a non-significant enrichment in the RA-implicated KCNK5 gene was observed. Two SNPs near spondin-1 and semaphorin-4G approached genome-wide significance. The results of the current study did not provide an unambiguous predictor of CZP response.
BACKGROUND: Previous studies of radiological damage in rheumatoid arthritis (RA) have used candidate-gene approaches, or evaluated single genome-wide association studies (GWAS). We undertook the first meta-analysis of GWAS of RA radiological damage to: (1) identify novel genetic loci for this trait; and (2) test previously validated variants. METHODS: Seven GWAS (2,775 RA cases, of a range of ancestries) were combined in a meta-analysis. Radiological damage was assessed using modified Larsen scores, Sharp van Der Heijde scores, and erosive status. Single nucleotide polymophsim (SNP) associations with radiological damage were tested at a single time-point using regression models. Primary analyses included age and disease duration as covariates. Secondary analyses also included rheumatoid factor (RF). Meta-analyses were undertaken in trans-ethnic and European-only cases. RESULTS: In the trans-ethnic primary meta-analysis, one SNP (rs112112734) in close proximity to HLA-DRB1, and strong linkage disequilibrium with the shared-epitope, attained genome-wide significance (P = 4.2x10-8). In the secondary analysis (adjusting for RF) the association was less significant (P = 1.7x10-6). In both trans-ethnic primary and secondary meta-analyses 14 regions contained SNPs with associations reaching P<5x10-6; in the European primary and secondary analyses 13 and 10 regions contained SNPs reaching P<5x10-6, respectively. Of the previously validated SNPs for radiological progression, only rs660895 (tagging HLA-DRB1*04:01) attained significance (P = 1.6x10-5) and had a consistent direction of effect across GWAS. CONCLUSIONS: Our meta-analysis confirms the known association between the HLA-DRB1 shared epitope and RA radiological damage. The lack of replication of previously validated non-HLA markers highlights a requirement for further research to deliver clinically-useful prognostic genetic markers.
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.
Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.
Diffuse large B-cell lymphoma or multiple sclerosis
Follicular lymphoma or multiple sclerosis
Chronic lymphocytic leukemia or multiple sclerosis
Chronic lymphocytic leukemia or systemic lupus erythematosus
Marginal zone lymphoma or rheumatoid arthritis
Marginal zone lymphoma or systemic lupus erythematosus
Follicular lymphoma or rheumatoid arthritis
Diffuse large B-cell lymphoma or systemic lupus erythematosus
Marginal zone lymphoma or multiple sclerosis
Chronic lymphocytic leukemia or rheumatoid arthritis
Diffuse large B-cell lymphoma or 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).
Joint destruction in rheumatoid arthritis (RA) is heritable, but knowledge on specific genetic determinants of joint damage in RA is limited. We have used the Immunochip array to examine whether genetic variants influence variation in joint damage in a cohort of Mexican Americans (MA) and European Americans (EA) with RA. We studied 720 MA and 424 EA patients with RA. Joint damage was quantified using a radiograph of both hands and wrists, scored using Sharp's technique. We conducted association analyses with the transformed Sharp score and the Immunochip single nucleotide polymorphism (SNP) data using PLINK. In MAs, 15 SNPs from chromosomes 1, 5, 9, 17 and 22 associated with joint damage yielded strong p-values (p < 1 × 10(-4) ). The strongest association with joint damage was observed with rs7216796, an intronic SNP located in the MAP3K14 gene, on chromosome 17 (β ± SE = -0.25 ± 0.05, p = 6.23 × 10(-6) ). In EAs, 28 SNPs from chromosomes 1, 4, 6, 9, and 21 showed associations with joint damage (p-value < 1 × 10(-4) ). The best association was observed on chromosome 9 with rs59902911 (β ± SE = 0.86 ± 0.17, p = 1.01 × 10(-6) ), a synonymous SNP within the CARD9 gene. We also observed suggestive evidence for some loci influencing joint damage in MAs and EAs. We identified two novel independent loci (MAP3K14 and CARD9) strongly associated with joint damage in MAs and EAs and a few shared loci showing suggestive evidence for association.
Rheumatoid arthritis (RA) is characterised by chronic synovial joint inflammation. Treatment has been revolutionised by tumour necrosis factor alpha inhibitors (TNFi) but each available drug shows a significant non-response rate. We conducted a genome-wide association study of 1752 UK RA TNFi-treated patients to identify predictors of change in the Disease Activity Score 28 (DAS28) and subcomponents over 3-6 months. The rs7195994 variant at the FTO gene locus was associated with infliximab response when looking at a change in the swollen joint count (SJC28) subcomponent (p = 9.74 × 10-9). Capture Hi-C data show chromatin interactions in GM12878 cells between rs2540767, in high linkage disequilibrium with rs7195994 (R2 = 0.9) and IRX3, a neighbouring gene of FTO. IRX3 encodes a transcription factor involved in adipocyte remodelling and is regarded as the obesity gene at the FTO locus. Importantly, the rs7195994 association remained significantly associated following adjustment for BMI. In addition, using capture Hi-C data we showed interactions between TNFi-response associated variants and 16 RA susceptibility variants.
Response to TNF inhibitor in rheumatoid arthritis (erythrocyte sedimentation rate)
Response to TNF inhibitor in rheumatoid arthritis (change in swollen 28-joint count)
Response to TNF inhibitor in rheumatoid arthritis (change in disease activity score)
Response to TNF inhibitor in rheumatoid arthritis (change in tender 28-joint count)
Response to TNF inhibitor in rheumatoid arthritis (change in patient global heath assessment score)
OBJECTIVE: Immune-mediated inflammatory diseases (IMIDs) are heterogeneous and complex conditions with overlapping clinical symptoms and elevated familial aggregation, which suggests the existence of a shared genetic component. In order to identify this genetic background in a systematic fashion, we performed the first cross-disease genome-wide meta-analysis in systemic seropositive rheumatic diseases, namely, systemic sclerosis, systemic lupus erythematosus, rheumatoid arthritis and idiopathic inflammatory myopathies. METHODS: We meta-analysed ~6.5 million single nucleotide polymorphisms in 11 678 cases and 19 704 non-affected controls of European descent populations. The functional roles of the associated variants were interrogated using publicly available databases. RESULTS: Our analysis revealed five shared genome-wide significant independent loci that had not been previously associated with these diseases: NAB1, KPNA4-ARL14, DGQK, LIMK1 and PRR12. All of these loci are related with immune processes such as interferon and epidermal growth factor signalling, response to methotrexate, cytoskeleton dynamics and coagulation cascade. Remarkably, several of the associated loci are known key players in autoimmunity, which supports the validity of our results. All the associated variants showed significant functional enrichment in DNase hypersensitivity sites, chromatin states and histone marks in relevant immune cells, including shared expression quantitative trait loci. Additionally, our results were significantly enriched in drugs that are being tested for the treatment of the diseases under study. CONCLUSIONS: We have identified shared new risk loci with functional value across diseases and pinpoint new potential candidate loci that could be further investigated. Our results highlight the potential of drug repositioning among related systemic seropositive rheumatic IMIDs.
Systemic seropositive rheumatic diseases (Systemic sclerosis or systemic lupus erythematosus or rheumatoid arthritis or idiopathic inflammatory myopathies)
OBJECTIVE: To investigate the gene-environment interaction between smoking and single nucleotide polymorphisms (SNPs), using Immunochip material, on the risk of developing either of two serologically defined subsets of RA. METHODS: Interaction between smoking and 133,648 genetic markers from the Immunochip was examined for two RA subsets, defined by the presence or absence of ACPA. A total of 1590 ACPA-positive and 891 ACPA-negative cases were compared with 1856 controls in the Swedish Epidemiological Investigation of RA (EIRA) case-control study. Logistic regression models were used to determine the presence of interaction. The proportion attributable to interaction was calculated for each smoking-SNP pair. Replication was carried out in an independent dataset from northern Sweden. To further validate and extend the results, interaction analysis was also performed using genome-wide association studies data on EIRA individuals. RESULTS: In ACPA-positive RA, 102 SNPs interacted significantly with smoking, after Bonferroni correction. All 102 SNPs were located in the HLA region, mainly within the HLA class II region, 51 of which were replicated. No additional loci outside chromosome 6 were identified in the genome-wide association studies validation. After adjusting for HLA-DRB1 shared epitope, 15 smoking-SNP pairs remained significant for ACPA-positive RA, with 8 of these replicated (loci: BTNL2, HLA-DRA, HLA-DRB5, HLA-DQA1, HLA-DOB and TAP2). For ACPA-negative RA, no smoking-SNP pairs passed the threshold for significance. CONCLUSION: Our study presents extended gene variation patterns involved in gene-smoking interaction in ACPA-positive, but not ACPA-negative, RA. Notably, variants in HLA-DRB1 and those in additional genes within the MHC class II region, but not in any other gene regions, showed interaction with smoking.
OBJECTIVE: Psoriatic arthritis (PsA) is a chronic inflammatory arthritis affecting up to 30% of patients with psoriasis (Ps). To date, most of the known risk loci for PsA are shared with Ps, and identifying disease-specific variation has proven very challenging. The objective of the present study was to identify genetic variation specific for PsA. METHODS: We performed a genome-wide association study in a cohort of 835 patients with PsA and 1558 controls from Spain. Genetic association was tested at the single marker level and at the pathway level. Meta-analysis was performed with a case-control cohort of 2847 individuals from North America. To confirm the specificity of the genetic associations with PsA, we tested the associated variation using a purely cutaneous psoriasis cohort (PsC, n=614) and a rheumatoid arthritis cohort (RA, n=1191). Using network and drug-repurposing analyses, we further investigated the potential of the PsA-specific associations to guide the development of new drugs in PsA. RESULTS: We identified a new PsA risk single-nucleotide polymorphism at B3GNT2 locus (p=1.10e-08). At the pathway level, we found 14 genetic pathways significantly associated with PsA (pFDR<0.05). From these, the glycosaminoglycan (GAG) metabolism pathway was confirmed to be disease-specific after comparing the PsA cohort with the cohorts of patients with PsC and RA. Finally, we identified candidate drug targets in the GAG metabolism pathway as well as new PsA indications for approved drugs. CONCLUSION: These findings provide insights into the biological mechanisms that are specific for PsA and could contribute to develop more effective therapies.
The human genome, which includes thousands of genes, represents a big data challenge. Rheumatoid arthritis (RA) is a complex autoimmune disease with a genetic basis. Many single-nucleotide polymorphism (SNP) association methods partition a genome into haplotype blocks. The aim of this genome wide association study (GWAS) was to select the most appropriate haplotype block partitioning method for the North American Rheumatoid Arthritis Consortium (NARAC) dataset. The methods used for the NARAC dataset were the individual SNP approach and the following haplotype block methods: the four-gamete test (FGT), confidence interval test (CIT), and solid spine of linkage disequilibrium (SSLD). The measured parameters that reflect the strength of the association between the biomarker and RA were the P-value after Bonferroni correction and other parameters used to compare the output of each haplotype block method. This work presents a comparison among the individual SNP approach and the three haplotype block methods to select the method that can detect all the significant SNPs when applied alone. The GWAS results from the NARAC dataset obtained with the different methods are presented. The individual SNP, CIT, FGT, and SSLD methods detected 541, 1516, 1551, and 1831 RA-associated SNPs respectively, and the individual SNP, FGT, CIT, and SSLD methods detected 65, 156, 159, and 450 significant SNPs respectively, that were not detected by the other methods. Three hundred eighty-three SNPs were discovered by the haplotype block methods and the individual SNP approach, while 1021 SNPs were discovered by all three haplotype block methods. The 383 SNPs detected by all the methods are promising candidates for studying RA susceptibility. A hybrid technique involving all four methods should be applied to detect the significant SNPs associated with RA in the NARAC dataset, but the SSLD method may be preferred because of its advantages when only one method was used.
Large meta-analyses of rheumatoid arthritis (RA) susceptibility in European (EUR) and East Asian (EAS) populations have identified >100 RA risk loci, but genome-wide studies of RA in African-Americans (AAs) are absent. To address this disparity, we performed an analysis of 916 AA RA patients and 1392 controls and aggregated our data with genotyping data from >100 000 EUR and Asian RA patients and controls. We identified two novel risk loci that appear to be specific to AAs: GPC5 and RBFOX1 (PAA < 5 × 10-9). Most RA risk loci are shared across different ethnicities, but among discordant loci, we observed strong enrichment of variants having large effect sizes. We found strong evidence of effect concordance for only 3 of the 21 largest effect index variants in EURs. We used the trans-ethnic fine-mapping algorithm PAINTOR3 to prioritize risk variants in >90 RA risk loci. Addition of AA data to those of EUR and EAS descent enabled identification of seven novel high-confidence candidate pathogenic variants (defined by posterior probability > 0.8). In summary, our trans-ethnic analyses are the first to include AAs, identified several new RA risk loci and point to candidate pathogenic variants that may underlie this common autoimmune disease. These findings may lead to better ways to diagnose or stratify treatment approaches in RA.
OBJECTIVE: To investigate the genetic background influencing the development of cardiovascular (CV) disease in patients with rheumatoid arthritis (RA). METHODS: We performed a genome-wide association study (GWAS) in which, after quality control and imputation, a total of 6,308,944 polymorphisms across the whole genome were analyzed in 2,989 RA patients of European origin. Data on subclinical atherosclerosis, obtained through assessment of carotid intima-media thickness (CIMT) and presence/absence of carotid plaques by carotid ultrasonography, were available for 1,355 individuals. RESULTS: A genetic variant of the RARB gene (rs116199914) was associated with CIMT values at the genome-wide level of significance (minor allele [G] β coefficient 0.142, P = 1.86 × 10-8 ). Interestingly, rs116199914 overlapped with regulatory elements in tissues related to CV pathophysiology and immune cells. In addition, biologic pathway enrichment and predictive protein-protein relationship analyses, including suggestive GWAS signals of potential relevance, revealed a functional enrichment of the collagen biosynthesis network related to the presence/absence of carotid plaques (Gene Ontology no. 0032964; false discovery rate-adjusted P = 4.01 × 10-3 ). Furthermore, our data suggest potential influences of the previously described candidate CV risk loci NFKB1, MSRA, and ZC3HC1 (P = 8.12 × 10-4 , P = 5.94 × 10-4 , and P = 2.46 × 10-4 , respectively). CONCLUSION: The present findings strongly suggest that genetic variation within RARB contributes to the development of subclinical atherosclerosis in patients with RA.
Ischemic heart disease in rheumatoid arthritis
Carotid plaques in rheumatoid arthritis
Cardiovascular event in rheumatoid arthritis
Carotid intima media thickness in rheumatoid arthritis
INTRODUCTION: Rheumatoid arthritis (RA) patients can be classified based on presence or absence of anticitrullinated peptide antibodies (ACPA) in their serum. This heterogeneity among patients may reflect important biological differences underlying the disease process. To date, the majority of genetic studies have focused on the ACPA-positive group. Therefore, our goal was to analyse the genetic risk factors that contribute to ACPA-negative RA. METHODS: We performed a large-scale genome-wide association study (GWAS) in three Caucasian European cohorts comprising 1148 ACPA-negative RA patients and 6008 controls. All patients were screened using the Illumina Human Cyto-12 chip, and controls were genotyped using different genome-wide platforms. Population-independent analyses were carried out by means of logistic regression. Meta-analysis with previously published data was performed as follow-up for selected signals (reaching a total of 1922 ACPA-negative RA patients and 7087 controls). Imputation of classical HLA alleles, amino acid residues and single nucleotide polymorphisms was undertaken. RESULTS: The combined analysis of the studied cohorts resulted in identification of a peak of association in the HLA-region and several suggestive non-HLA associations. Meta-analysis with previous reports confirmed the association of the HLA region with this subset and an observed association in the CLYBL locus remained suggestive. The imputation and deep interrogation of the HLA region led to identification of a two amino acid model (HLA-B at position 9 and HLA-DRB1 at position 11) that accounted for the observed genome-wide associations in this region. CONCLUSIONS: Our study shed light on the influence of the HLA region in ACPA-negative RA and identified a suggestive risk locus for this condition.
Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.
Sero-negative rheumatoid arthritis (RA) is a highly heterogeneous disorder with only a few additive loci identified to date. We report a genotypic variability-based genome-wide association study (vGWAS) of six cohorts of sero-negative RA recruited in Europe and the US that were genotyped with the Immunochip. A two-stage approach was used: (1) a mixed model to partition dichotomous phenotypes into an additive component and non-additive residuals on the liability scale and (2) the Levene's test to assess equality of the residual variances across genotype groups. The vGWAS identified rs2852853 (P = 1.3e-08, DHCR7) and rs62389423 (P = 1.8e-05, near IRF4) in addition to two previously identified loci (HLA-DQB1 and ANKRD55), which were all statistically validated using cross validation. DHCR7 encodes an enzyme important in cutaneous synthesis of vitamin D and DHCR7 mutations are believed to be important for early humans to adapt to Northern Europe where residents have reduced ultraviolet-B exposure and tend to have light skin color. IRF4 is a key locus responsible for skin color, with a vitamin D receptor-binding interval. These vGWAS results together suggest that vitamin D deficiency is potentially causal of sero-negative RA and provide new insights into the pathogenesis of the disorder.
IMPORTANCE: Posttraumatic stress disorder (PTSD) is a prevalent, serious public health concern, particularly in the military. The identification of genetic risk factors for PTSD may provide important insights into the biological foundation of vulnerability and comorbidity. OBJECTIVE: To discover genetic loci associated with the lifetime risk for PTSD in 2 cohorts from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). DESIGN, SETTING, AND PARTICIPANTS: Two coordinated genome-wide association studies of mental health in the US military contributed participants. The New Soldier Study (NSS) included 3167 unique participants with PTSD and 4607 trauma-exposed control individuals; the Pre/Post Deployment Study (PPDS) included 947 unique participants with PTSD and 4969 trauma-exposed controls. The NSS data were collected from February 1, 2011, to November 30, 2012; the PDDS data, from January 9 to April 30, 2012. The primary analysis compared lifetime DSM-IV PTSD cases with trauma-exposed controls without lifetime PTSD. Data were analyzed from March 18 to December 27, 2015. MAIN OUTCOMES AND MEASURES: Association analyses for PTSD used logistic regression models within each of 3 ancestral groups (European, African, and Latino American) by study, followed by meta-analysis. Heritability and genetic correlation and pleiotropy with other psychiatric and immune-related disorders were estimated. RESULTS: The NSS population was 80.7% male (6277 of 7774 participants; mean [SD] age, 20.9 [3.3] years); the PPDS population, 94.4% male (5583 of 5916 participants; mean [SD] age, 26.5 [6.0] years). A genome-wide significant locus was found in ANKRD55 on chromosome 5 (rs159572; odds ratio [OR], 1.62; 95% CI, 1.37-1.92; P = 2.34 × 10-8) and persisted after adjustment for cumulative trauma exposure (adjusted OR, 1.64; 95% CI, 1.39-1.95; P = 1.18 × 10-8) in the African American samples from the NSS. A genome-wide significant locus was also found in or near ZNF626 on chromosome 19 (rs11085374; OR, 0.77; 95% CI, 0.70-0.85; P = 4.59 × 10-8) in the European American samples from the NSS. Similar results were not found for either single-nucleotide polymorphism in the corresponding ancestry group from the PPDS sample, in other ancestral groups, or in transancestral meta-analyses. Single-nucleotide polymorphism-based heritability was nonsignificant, and no significant genetic correlations were observed between PTSD and 6 mental disorders or 9 immune-related disorders. Significant evidence of pleiotropy was observed between PTSD and rheumatoid arthritis and, to a lesser extent, psoriasis. CONCLUSIONS AND RELEVANCE: In the largest genome-wide association study of PTSD to date, involving a US military sample, limited evidence of association for specific loci was found. Further efforts are needed to replicate the genome-wide significant association with ANKRD55-associated in prior research with several autoimmune and inflammatory disorders-and to clarify the nature of the genetic overlap observed between PTSD and rheumatoid arthritis and psoriasis.
BACKGROUND: Studies of Caucasian patients with rheumatoid arthritis (RA) to identify genetic biomarkers of anti-tumor necrosis factor (TNF) response have used response at a single time point as the phenotype with which single nucleotide polymorphism (SNP) associations have been tested. The findings have been inconsistent across studies. Among Japanese patients, only a few SNPs have been investigated. We report here the first genome-wide association study (GWAS) to identify genetic biomarkers of anti-TNF response among Japanese RA patients, using response at 2 time-points for a more reliable clinical phenotype over time. METHODS: Disease Activity Scores based on 28 joint counts (DAS28) were assessed at baseline (before initial therapy), and after 3 and 6 months in 487 Japanese RA patients starting anti-TNF therapy for the first time or switching to a new anti-TNF agent. A genome-wide panel of SNPs was genotyped and additional SNPs were imputed. Using change in DAS28 scores from baseline at both 3 (ΔDAS-3) and 6 months (ΔDAS-6) as the response phenotype, a longitudinal genome-wide association analysis was conducted using generalized estimating equations (GEE) models, adjusting for baseline DAS28, treatment duration, type of anti-TNF agent and concomitant methotrexate. Cross-sectional analyses were performed using multivariate linear regression models, with response from a single time point (ΔDAS-3 or ΔDAS-6) as phenotype; all other variables were the same as in the GEE models. RESULTS: In the GEE models, borderline significant association was observed at 3 chromosomal regions (6q15: rs284515, p = 6.6x10(-7); 6q27: rs75908454, p = 6.3x10(-7) and 10q25.3: rs1679568, p = 8.1x10(-7)), extending to numerous SNPs in linkage disequilibrium (LD) across each region. Potential candidate genes in these regions include MAP3K7, BACH2 (6q15), GFRA1 (10q25.3), and WDR27 (6q27). The association at GFRA1 replicates a previous finding from a Caucasian dataset. In the cross-sectional analyses, ΔDAS-6 was significantly associated with the 6q15 locus (rs284511, p = 2.5x10(-8)). No other significant or borderline significant associations were identified. CONCLUSION: Three genomic regions demonstrated significant or borderline significant associations with anti-TNF response in our dataset of Japanese RA patients, including a locus previously associated among Caucasians. Using repeated measures of response as phenotype enhanced the power to detect these associations.
Response to anti-TNF therapy in rheumatoid arthritis
AIM: Bone erosion is a major problem worsening quality of rheumatoid arthritis (RA) patients' lives. However, causal factors responsible for bone erosion in RA have remained unclear. We aimed to examine genetic variants conferring bone erosion in RA using a Korean genome-wide association study (GWAS) and to search for possible biological mechanisms underlying the development of bone erosion. METHOD: We obtained genome-wide single nucleotide polymorphism (SNP) data for 711 Korean RA patients using Illumina HapMap 550v3/660W arrays. Associations between SNPs and bone erosion status based on the Steinbrocker staging system were examined using multivariate logistic regression. Cell-type-specific enrichment of the epigenomic chromatin annotation H3K4me3 at the bone erosion associated variants was further investigated using National Institute of Health Roadmap Epigenomics data. RESULTS: As we tested the associations between 439 289 SNPs and bone erosion in 385 patients with erosive RA and 326 with non-erosive RA, none of the tested SNPs reached the genome-wide significance threshold, although many loci showed modest genetic effect on bone erosion status with suggestive association (e.g., rs2741200 [P = 3.75 × 10-6 ] in the SLA-TG locus and rs12422918 [P = 4.13 × 10-6 ] in SRGAP1). However, the top-ranked SNPs and their linked proxies, which were mostly located in non-coding variants, were significantly co-localized with the highly tissue-specific regulatory marker H3K4me3 in CD8+ memory T-cells (P = 0.014). CONCLUSION: Although, there was no large-effect variants associated with bone erosion in our GWAS, we have shown that CD8+ memory T-cells may have relevance with bone erosion in patients with RA through the analysis of ChiP-seq data.
BACKGROUND: Rheumatoid arthritis (RA) can be divided into two major subsets based on the presence or absence of antibodies to citrullinated peptide antigens (ACPA). Until now, data from genome-wide association studies (GWAS) have only been published from ACPA-positive subsets of RA or from studies that have not separated the two subsets. The aim of the current study is to provide and compare GWAS data for both subsets. METHODS AND RESULTS: GWAS using the Illumina 300K chip was performed for 774 ACPA-negative patients with RA, 1147 ACPA-positive patients with RA and 1079 controls from the Swedish population-based case-control study EIRA. Imputation was performed which allowed comparisons using 1,723,056 single nucleotide polymorphisms (SNPs). No SNP achieved genome-wide significance (2.9 × 10⁻⁸) in the comparison between ACPA-negative RA and controls. A case-case association study was then performed between ACPA-negative and ACPA-positive RA groups. The major difference in this analysis was in the HLA region where 768 HLA SNPs passed the threshold for genome-wide significance whereas additional contrasting SNPs did not reach genome-wide significance. However, one SNP close to the RPS12P4 locus in chromosome 2 reached a p value of 2 × 10⁶ and this locus can thus be considered as a tentative candidate locus for ACPA-negative RA. CONCLUSIONS: ACPA-positive and ACPA-negative RA display significant risk allele frequency differences which are mainly confined to the HLA region. The data provide further support for distinct genetic aetiologies of RA subsets and emphasise the need to consider them separately in genetic as well as functional studies of this disease.
OBJECTIVE: Genetic factors underlying susceptibility to rheumatoid arthritis (RA) in Arab populations are largely unknown. This genome-wide association study (GWAS) was undertaken to explore the generalizability of previously reported RA loci to Arab subjects and to discover new Arab-specific genetic loci. METHODS: The Genetics of Rheumatoid Arthritis in Some Arab States Study was designed to examine the genetics and clinical features of RA patients from Jordan, the Kingdom of Saudi Arabia, Lebanon, Qatar, and the United Arab Emirates. In total, >7 million single-nucleotide polymorphisms (SNPs) were tested for association with RA overall and with seropositive or seronegative RA in 511 RA cases and 352 healthy controls. In addition, replication of 15 signals was attempted in 283 RA cases and 221 healthy controls. A genetic risk score of 68 known RA SNPs was also examined in this study population. RESULTS: Three loci (HLA region, intergenic 5q13, and 17p13 at SMTNL2/GGT6) reached genome-wide significance in the analyses of association with RA and with seropositive RA, and for all 3 loci, evidence of independent replication was demonstrated. Consistent with the findings in European and East Asian populations, the association of RA with HLA-DRB1 amino acid position 11 conferred the strongest effect (P = 4.8 × 10-16 ), and a weighted genetic risk score of previously associated RA loci was found to be associated with RA (P = 3.41 × 10-5 ) and with seropositive RA (P = 1.48 × 10-6 ) in this population. In addition, 2 novel associations specific to Arab populations were found at the 5q13 and 17p13 loci. CONCLUSION: This first RA GWAS in Arab populations confirms that established HLA-region and known RA risk alleles contribute strongly to the risk and severity of disease in some Arab groups, suggesting that the genetic architecture of RA is similar across ethnic groups. Moreover, this study identified 2 novel RA risk loci in Arabs, offering further population-specific insights into the pathophysiology of RA.
OBJECTIVE: Rheumatoid factor (RF) is a well-established diagnostic and prognostic biomarker in rheumatoid arthritis (RA). However, ∼20% of RA patients are negative for this anti-IgG antibody. To date, only variation at the HLA-DRB1 gene has been associated with the presence of RF. This study was undertaken to identify additional genetic variants associated with RF positivity. METHODS: A genome-wide association study (GWAS) for RF positivity was performed using an Illumina Quad610 genotyping platform. A total of 937 RF-positive and 323 RF-negative RA patients were genotyped for >550,000 single-nucleotide polymorphisms (SNPs). Association testing was performed using an allelic chi-square test implemented in Plink software. An independent cohort of 472 RF-positive and 190 RF-negative RA patients was used to validate the most significant findings. RESULTS: In the discovery stage, a SNP in the IRX1 locus on chromosome 5p15.3 (SNP rs1502644) showed a genome-wide significant association with RF positivity (P = 4.13 × 10(-8) , odds ratio [OR] 0.37 [95% confidence interval (95% CI) 0.26-0.53]). In the validation stage, the association of IRX1 with RF was replicated in an independent group of RA patients (P = 0.034, OR 0.58 [95% CI 0.35-0.97] and combined P = 1.14 × 10(-8) , OR 0.43 [95% CI 0.32-0.58]). CONCLUSION: To our knowledge, this is the first GWAS of RF positivity in RA. Variation at the IRX1 locus on chromosome 5p15.3 is associated with the presence of RF. Our findings indicate that IRX1 and HLA-DRB1 are the strongest genetic factors for RF production in RA.
Rheumatoid factor seropositivity in rheumatoid arthritis
OBJECTIVES: During the last years, genome-wide association studies (GWASs) have identified a number of common genetic risk factors for rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). However, the genetic overlap between these two immune-mediated diseases has not been thoroughly examined so far. The aim of the present study was to identify additional risk loci shared between RA and SLE. METHODS: We performed a large-scale meta-analysis of GWAS data from RA (3911 cases and 4083 controls) and SLE (2237 cases and 6315 controls). The top-associated polymorphisms in the discovery phase were selected for replication in additional datasets comprising 13 641 RA cases and 31 921 controls and 1957 patients with SLE and 4588 controls. RESULTS: The rs9603612 genetic variant, located nearby the COG6 gene, an established susceptibility locus for RA, reached genome-wide significance in the combined analysis including both discovery and replication sets (p value=2.95E-13). In silico expression quantitative trait locus analysis revealed that the associated polymorphism acts as a regulatory variant influencing COG6 expression. Moreover, protein-protein interaction and gene ontology enrichment analyses suggested the existence of overlap with specific biological processes, specially the type I interferon signalling pathway. Finally, genetic correlation and polygenic risk score analyses showed cross-phenotype associations between RA and SLE. CONCLUSIONS: In conclusion, we have identified a new risk locus shared between RA and SLE through a meta-analysis including GWAS datasets of both diseases. This study represents the first comprehensive large-scale analysis on the genetic overlap between these two complex disorders.
Systemic lupus erythematosus or rheumatoid arthritis
The aim of this study was to identify genetic variants associated with rheumatoid arthritis (RA) risk in black South Africans. Black South African RA patients (n = 263) were compared with healthy controls (n = 374). Genotyping was performed using the Immunochip, and four-digit high-resolution human leukocyte antigen (HLA) typing was performed by DNA sequencing of exon 2. Standard quality control measures were implemented on the data. The strongest associations were in the intergenic region between the HLA-DRB1 and HLA-DQA1 loci. After conditioning on HLA-DRB1 alleles, the effect in the rest of the extended major histocompatibility (MHC) diminished. Non-HLA single nucleotide polymorphisms (SNPs) in the intergenic regions LOC389203|RBPJ, LOC100131131|IL1R1, KIAA1919|REV3L, LOC643749|TRAF3IP2, and SNPs in the intron and untranslated regions (UTR) of IRF1 and the intronic region of ICOS and KIAA1542 showed association with RA (p < 5 × 10(-5)). Of the SNPs previously associated with RA in Caucasians, one SNP, rs874040, locating to the intergenic region LOC389203|RBPJ was replicated in this study. None of the variants in the PTPN22 gene was significantly associated. The seropositive subgroups showed similar results to the overall cohort. The effects observed across the HLA region are most likely due to HLA-DRB1, and secondary effects in the extended MHC cannot be detected. Seven non-HLA loci are associated with RA in black South Africans. Similar to Caucasians, the intergenic region between LOC38920 and RBPJ is associated with RA in this population. The strong association of the R620W variant of the PTPN22 gene with RA in Caucasians was not replicated since this variant was monomorphic in our study, but other SNP variants of the PTPN22 gene were also not associated with RA in black South Africans, suggesting that this locus does not play a major role in RA in this population.
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.
OBJECTIVE: Methotrexate (MTX) is the drug of first choice for the treatment of rheumatoid arthritis (RA), but is effective only in around 60% of the patients. Identification of genetic markers to predict response is essential for effective treatment within a critical window period of 6 months after diagnosis, but have been hitherto elusive. In this study, we used genome-wide genotype data to identify the potential risk variants associated with MTX (poor)response in a north Indian RA cohort. MATERIALS AND METHODS: Genome-wide genotyping data for a total of 457 RA patients [297 good (DAS28-3≤3.2) and 160 poor (DAS28-3≥5.1) responders] on MTX monotherapy were tested for association using an additive model. Support vector machine and genome-wide pathway analysis were used to identify additional risk variants and pathways. All risk loci were imputed to fine-map the association signals and identify causal variant(s) of therapeutic/diagnostic relevance. RESULTS: Seven novel suggestive loci from genome-wide (P≤5×10(-5)) and three from support vector machine analysis were associated with MTX (poor)response. The associations of published candidate genes namely DHFR (P=0.014), FPGS (P=0.035), and TYMS (P=0.005) and purine and nucleotide metabolism pathways were reconfirmed. Imputation, followed by bioinformatic analysis indicated possible interaction between two reversely oriented overlapping genes namely ENOSF1 and TYMS at the post-transcriptional level. CONCLUSION: In this first ever genome-wide analysis on MTX treatment response in RA patients, 10 new risk loci were identified. These preliminary findings warrant replication in independent studies. Further, TYMS expression at the post-transcriptional level seems to be probably regulated through an antisense-RNA involving the 6-bp ins/del marker in the overlapping segment at 3'UTR of TYMS-ENOSF1, a finding with impending pharmacogenetic applications.
We used the Immunochip array to analyze 2,816 individuals with juvenile idiopathic arthritis (JIA), comprising the most common subtypes (oligoarticular and rheumatoid factor-negative polyarticular JIA), and 13,056 controls. We confirmed association of 3 known JIA risk loci (the human leukocyte antigen (HLA) region, PTPN22 and PTPN2) and identified 14 loci reaching genome-wide significance (P < 5 × 10(-8)) for the first time. Eleven additional new regions showed suggestive evidence of association with JIA (P < 1 × 10(-6)). Dense mapping of loci along with bioinformatics analysis refined the associations to one gene in each of eight regions, highlighting crucial pathways, including the interleukin (IL)-2 pathway, in JIA disease pathogenesis. The entire Immunochip content, the HLA region and the top 27 loci (P < 1 × 10(-6)) explain an estimated 18, 13 and 6% of the risk of JIA, respectively. In summary, this is the largest collection of JIA cases investigated so far and provides new insight into the genetic basis of this childhood autoimmune disease.
Juvenile idiopathic arthritis (oligoarticular or rheumatoid factor-negative polyarticular)
A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
OBJECTIVE: Rheumatoid arthritis (RA) that is negative for anticitrullinated protein antibodies (ACPA) is a subentity of RA, characterized by less severe disease. At the individual level, however, considerable differences in the severity of joint destruction occur. We performed a study on genetic factors underlying the differences in joint destruction in ACPA-negative patients. METHODS: A genome-wide association study was done with 262 ACPA-negative patients with early RA included in the Leiden Early Arthritis Clinic and related to radiographic joint destruction over 7 years. Significant single-nucleotide polymorphisms (SNP) were evaluated for association with progression of radiographic joint destruction in 253 ACPA-negative patients with early RA included in the Better Anti-Rheumatic Farmaco Therapy (BARFOT) study. According to the Bonferroni correction of the number of tested SNP, the threshold for significance was p < 2 × 10(-7) in phase 1 and 0.0045 in phase 2. In both cohorts, joint destruction was measured by Sharp/van der Heijde method with good reproducibility. RESULTS: Thirty-three SNP associated with severity of joint destruction (p < 2 × 10(-7)) in phase 1. In phase 2, rs2833522 (p = 0.0049) showed borderline significance. A combined analysis of both the Leiden and BARFOT datasets of rs2833522 confirmed this association with joint destruction (p = 3.57 × 10(-9)); the minor allele (A) associated with more severe damage (for instance, after 7 yrs followup, patients carrying AA had 1.22 times more joint damage compared to patients carrying AG and 1.50 times more joint damage than patients carrying GG). In silico analysis using the ENCODE and Ensembl databases showed presence of H3K4me3 histone mark, transcription factors, and long noncoding RNA in the region of rs2833522, an intergenic SNP located between HUNK and SCAF4. CONCLUSION: Rs2833522 might be associated with the severity of joint destruction in ACPA-negative RA.
Joint damage progression in ACPA-negative rheumatoid arthritis
OBJECTIVE: To investigate differences in genetic risk factors for rheumatoid arthritis (RA) in Han Chinese as compared with Europeans. METHODS: A genome-wide association study was conducted in China with 952 patients and 943 controls, and 32 variants were followed up in 2,132 patients and 2,553 controls. A transpopulation meta-analysis with results from a large European RA study was also performed to compare the genetic architecture across the 2 ethnic remote populations. RESULTS: Three non-major histocompatibility complex (non-MHC) loci were identified at the genome-wide significance level, the effect sizes of which were larger in anti-citrullinated protein antibody (ACPA)-positive patients than in ACPA-negative patients. These included 2 novel variants, rs12617656, located in an intron of DPP4 (odds ratio [OR] 1.56, P = 1.6 × 10(-21) ), and rs12379034, located in the coding region of CDK5RAP2 (OR 1.49, P = 1.1 × 10(-16) ), as well as a variant at the known CCR6 locus, rs1854853 (OR 0.71, P = 6.5 × 10(-15) ). The analysis of ACPA-positive patients versus ACPA-negative patients revealed that rs12617656 at the DPP4 locus showed a strong interaction effect with ACPAs (P = 5.3 × 10(-18) ), and such an interaction was also observed for rs7748270 at the MHC locus (P = 5.9 × 10(-8) ). The transpopulation meta-analysis showed genome-wide overlap and enrichment in association signals across the 2 populations, as confirmed by prediction analysis. CONCLUSION: This study has expanded the list of alleles that confer risk of RA, provided new insight into the pathogenesis of RA, and added empirical evidence to the emerging polygenic nature of complex trait variation driven by common genetic variants.
BACKGROUND: Radiographic progression is reported to be highly heritable in rheumatoid arthritis (RA). However, previous study using genetic loci showed an insufficient accuracy of prediction for radiographic progression. The aim of this study is to identify a biologically relevant prediction model of radiographic progression in patients with RA using a genome-wide association study (GWAS) combined with bioinformatics analysis. METHODS: We obtained genome-wide single nucleotide polymorphism (SNP) data for 374 Korean patients with RA using Illumina HumanOmni2.5Exome-8 arrays. Radiographic progression was measured using the yearly Sharp/van der Heijde modified score rate, and categorized in no or severe progression. Significant SNPs for severe radiographic progression from GWAS were mapped on the functional genes and reprioritized by post-GWAS analysis. For robust prediction of radiographic progression, tenfold cross-validation using a support vector machine (SVM) classifier was conducted. Accuracy was used for selection of optimal SNPs set in the Hanyang Bae RA cohort. The performance of our final model was compared with that of other models based on GWAS results and SPOT (one of the post-GWAS analyses) using receiver operating characteristic (ROC) curves. The reliability of our model was confirmed using GWAS data of Caucasian patients with RA. RESULTS: A total of 36,091 significant SNPs with a p value <0.05 from GWAS were reprioritized using post-GWAS analysis and approximately 2700 were identified as SNPs related to RA biological features. The best average accuracy of ten groups was 0.6015 with 85 SNPs, and this increased to 0.7481 when combined with clinical information. In comparisons of the performance of the model, the 0.7872 area under the curve (AUC) in our model was superior to that obtained with GWAS (AUC 0.6586, p value 8.97 × 10-5) or SPOT (AUC 0.7449, p value 0.0423). Our model strategy also showed superior prediction accuracy in Caucasian patients with RA compared with GWAS (p value 0.0049) and SPOT (p value 0.0151). CONCLUSIONS: Using various biological functions of SNPs and repeated machine learning, our model could predict severe radiographic progression relevantly and robustly in patients with RA compared with models using only GWAS results or other post-GWAS tools.
Celiac disease is a common autoimmune disorder characterized by an intestinal inflammation triggered by gluten, a storage protein found in wheat, rye and barley. Similar to other autoimmune diseases such as type 1 diabetes, psoriasis and rheumatoid arthritis, celiac disease is the result of an immune response to self-antigens leading to tissue destruction and production of autoantibodies. Common diseases like celiac disease have a complex pattern of inheritance with inputs from both environmental as well as additive and non-additive genetic factors. In the past few years, Genome Wide Association Studies (GWAS) have been successful in finding genetic risk variants behind many common diseases and traits. To complement and add to the previous findings, we performed a GWAS including 206 trios from 97 nuclear Swedish and Norwegian families affected with celiac disease. By stratifying for HLA-DQ, we identified a new genome-wide significant risk locus covering the DUSP10 gene. To further investigate the associations from the GWAS we performed pathway analyses and two-locus interaction analyses. These analyses showed an over-representation of genes involved in type 2 diabetes and identified a set of candidate mechanisms and genes of which some were selected for mRNA expression analysis using small intestinal biopsies from 98 patients. Several genes were expressed differently in the small intestinal mucosa from patients with celiac autoimmunity compared to intestinal mucosa from control patients. From top-scoring regions we identified susceptibility genes in several categories: 1) polarity and epithelial cell functionality; 2) intestinal smooth muscle; 3) growth and energy homeostasis, including proline and glutamine metabolism; and finally 4) innate and adaptive immune system. These genes and pathways, including specific functions of DUSP10, together reveal a new potential biological mechanism that could influence the genesis of celiac disease, and possibly also other chronic disorders with an inflammatory component.
OBJECTIVE: Genome-wide association studies (GWAS) and their subsequent meta-analyses have changed the landscape of genetics in rheumatoid arthritis (RA) by uncovering several novel genes. Such studies are heavily weighted by samples from Caucasian populations, but they explain only a small proportion of total heritability. Our previous studies in genetically distinct North Indian RA cohorts have demonstrated apparent allelic/genetic heterogeneity between North Indian and Western populations, warranting GWAS in non-European populations. We undertook this study to detect additional disease-associated loci that may be collectively important in the presence or absence of genes with a major effect. METHODS: High-quality genotypes for >600,000 single-nucleotide polymorphisms (SNPs) in 706 RA patients and 761 controls from North India were generated in the discovery stage. Twelve SNPs showing suggestive association (P < 5 × 10(-5)) were then tested in an independent cohort of 927 RA patients and 1,148 controls. Additional disease-associated loci were determined using support vector machine (SVM) analyses. Fine-mapping of novel loci was performed by using imputation. RESULTS: In addition to the expected association of the HLA locus with RA, we identified association with a novel intronic SNP of ARL15 (rs255758) on chromosome 5 (Pcombined = 6.57 × 10(-6); odds ratio 1.42). Genotype-phenotype correlation by assaying adiponectin levels demonstrated the functional significance of this novel gene in disease pathogenesis. SVM analysis confirmed this association along with that of a few more replication stage genes. CONCLUSION: In this first GWAS of RA among North Indians, ARL15 emerged as a novel genetic risk factor in addition to the classic HLA locus, which suggests that population-specific genetic loci as well as those shared between Asian and European populations contribute to RA etiology. Furthermore, our study reveals the potential of machine learning methods in unraveling gene-gene interactions using GWAS data.
OBJECTIVE: The number of confirmed rheumatoid arthritis (RA) loci currently stands at 32, but many lines of evidence indicate that expansion of existing genome-wide association studies (GWAS) enhances the power to detect additional loci. This study was undertaken to extend our previous RA GWAS in a UK cohort, adding more independent RA cases and healthy controls, with the aim of detecting novel association signals for susceptibility to RA in a homogeneous UK cohort. METHODS: A total of 3,223 UK RA cases and 5,272 UK controls were available for association analyses, with the extension adding 1,361 cases and 2,334 controls to the original GWAS data set. The genotype data for all RA cases were imputed using the Impute program version 2. After stringent quality control thresholds were applied, 3,034 cases and 5,271 controls (1,831,729 single-nucleotide polymorphisms [SNPs]) were available for analysis. Association testing was performed using Plink software. RESULTS: The analyses indicated a suggestive association with susceptibility to RA (P < 0.0001) for 6 novel RA loci that have been previously found to be associated with other autoimmune diseases; these 6 SNPs were genotyped in independent samples. Two of the associated loci were validated, one of which was associated with RA at genome-wide levels of significance in the combined analysis, identifying a novel RA locus at 22q12 (P = 6.9 × 10(-9) ). In addition, most of the previously known RA susceptibility loci were confirmed to be associated with RA, and for 16 of the loci, the strength of the association was increased. CONCLUSION: This study identified a new RA locus mapping to 22q12. These results support the notion that increasing the power of GWAS enhances novel gene discovery.
Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8 × 10(-8)), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3' UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1 × 10(-11) in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry.
Response to anti-TNF treatment in rheumatoid arthritis (infliximab, EULAR response analysis)
Response to anti-TNF treatment in rheumatoid arthritis (infliximab, delta-DAS analysis)
Response to anti-TNF treatment in rheumatoid arthritis (Etanercept, EA)
Response to anti-TNF treatment in rheumatoid arthritis (all patients, EULAR response analysis)
Rheumatoid arthritis (RA) is a chronic inflammatory disorder with a polygenic mode of inheritance. This study examined the hypothesis that runs of homozygosity (ROHs) play a recessive-acting role in the underlying RA genetic mechanism and identified RA-associated ROHs. Ours is the first genome-wide homozygosity association study for RA and characterized the ROH patterns associated with RA in the genomes of 2,000 RA patients and 3,000 normal controls of the Wellcome Trust Case Control Consortium. Genome scans consistently pinpointed two regions within the human major histocompatibility complex region containing RA-associated ROHs. The first region is from 32,451,664 bp to 32,846,093 bp (-log10(p)>22.6591). RA-susceptibility genes, such as HLA-DRB1, are contained in this region. The second region ranges from 32,933,485 bp to 33,585,118 bp (-log10(p)>8.3644) and contains other HLA-DPA1 and HLA-DPB1 genes. These two regions are physically close but are located in different blocks of linkage disequilibrium, and ∼40% of the RA patients' genomes carry these ROHs in the two regions. By analyzing homozygote intensities, an ROH that is anchored by the single nucleotide polymorphism rs2027852 and flanked by HLA-DRB6 and HLA-DRB1 was found associated with increased risk for RA. The presence of this risky ROH provides a 62% accuracy to predict RA disease status. An independent genomic dataset from 868 RA patients and 1,194 control subjects of the North American Rheumatoid Arthritis Consortium successfully validated the results obtained using the Wellcome Trust Case Control Consortium data. In conclusion, this genome-wide homozygosity association study provides an alternative to allelic association mapping for the identification of recessive variants responsible for RA. The identified RA-associated ROHs uncover recessive components and missing heritability associated with RA and other autoimmune diseases.