Erythroid lineage chromatin accessibility maps facilitate identification and validation of NFIX as a fetal hemoglobin repressor.

Human genetics has validated de-repression of fetal gamma globin (HBG) in adult erythroblasts as a powerful therapeutic paradigm in diseases involving defective adult beta globin (HBB)1. To identify factors involved in the switch from HBG to HBB expression, we performed Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq)2 on sorted erythroid lineage cells derived from bone marrow (BM) or cord blood (CB), representing adult and fetal states, respectively. BM to CB cell ATAC-seq profile comparisons revealed genome-wide enrichment of NFI DNA binding motifs and increased NFIX promoter chromatin accessibility, suggesting that NFIX may repress HBG. NFIX knockdown in BM cells increased HBG mRNA and fetal hemoglobin (HbF) protein levels, coincident with increased chromatin accessibility and decreased DNA methylation at the HBG promoter. Conversely, overexpression of NFIX in CB cells reduced HbF levels. Identification and validation of NFIX as a new target for HbF activation has implications in the development of therapeutics for hemoglobinopathies.

Discovery and Characterization of SY-1365, a Selective, Covalent Inhibitor of CDK7.

Recent studies suggest that targeting transcriptional machinery can lead to potent and selective anticancer effects in cancers dependent on high and constant expression of certain transcription factors for growth and survival. Cyclin-dependent kinase 7 (CDK7) is the catalytic subunit of the CDK-activating kinase complex. Its function is required for both cell-cycle regulation and transcriptional control of gene expression. CDK7 has recently emerged as an attractive cancer target because its inhibition leads to decreased transcript levels of oncogenic transcription factors, especially those associated with super-enhancers. Here, we describe a selective CDK7 inhibitor SY-1365, which is currently in clinical trials in populations of patients with ovarian and breast cancer (NCT03134638). In vitro, SY-1365 inhibited cell growth of many different cancer types at nanomolar concentrations. SY-1365 treatment decreased MCL1 protein levels, and cancer cells with low BCL2L1 (BCL-XL) expression were found to be more sensitive to SY-1365. Transcriptional changes in acute myeloid leukemia (AML) cell lines were distinct from those following treatment with other transcriptional inhibitors. SY-1365 demonstrated substantial antitumor effects in multiple AML xenograft models as a single agent; SY-1365-induced growth inhibition was enhanced in combination with the BCL2 inhibitor venetoclax. Antitumor activity was also observed in xenograft models of ovarian cancer, suggesting the potential for exploring SY-1365 in the clinic in both hematologic and solid tumors. Our findings support targeting CDK7 as a new approach for treating transcriptionally addicted cancers. SIGNIFICANCE: These findings demonstrate the molecular mechanism of action and potent antitumor activity of SY-1365, the first selective CDK7 inhibitor to enter clinical investigation.

A whole-genome sequence study identifies genetic risk factors for neuromyelitis optica.

Neuromyelitis optica (NMO) is a rare autoimmune disease that affects the optic nerve and spinal cord. Most NMO patients ( > 70%) are seropositive for circulating autoantibodies against aquaporin 4 (NMO-IgG+). Here, we meta-analyze whole-genome sequences from 86 NMO cases and 460 controls with genome-wide SNP array from 129 NMO cases and 784 controls to test for association with SNPs and copy number variation (total N = 215 NMO cases, 1244 controls). We identify two independent signals in the major histocompatibility complex (MHC) region associated with NMO-IgG+, one of which may be explained by structural variation in the complement component 4 genes. Mendelian Randomization analysis reveals a significant causal effect of known systemic lupus erythematosus (SLE), but not multiple sclerosis (MS), risk variants in NMO-IgG+. Our results suggest that genetic variants in the MHC region contribute to the etiology of NMO-IgG+ and that NMO-IgG+ is genetically more similar to SLE than MS.

SMN deficiency in severe models of spinal muscular atrophy causes widespread intron retention and DNA damage.

Spinal muscular atrophy (SMA), an autosomal recessive neuromuscular disease, is the leading monogenic cause of infant mortality. Homozygous loss of the gene survival of motor neuron 1 (SMN1) causes the selective degeneration of lower motor neurons and subsequent atrophy of proximal skeletal muscles. The SMN1 protein product, survival of motor neuron (SMN), is ubiquitously expressed and is a key factor in the assembly of the core splicing machinery. The molecular mechanisms by which disruption of the broad functions of SMN leads to neurodegeneration remain unclear. We used an antisense oligonucleotide (ASO)-based inducible mouse model of SMA to investigate the SMN-specific transcriptome changes associated with neurodegeneration. We found evidence of widespread intron retention, particularly of minor U12 introns, in the spinal cord of mice 30 d after SMA induction, which was then rescued by a therapeutic ASO. Intron retention was concomitant with a strong induction of the p53 pathway and DNA damage response, manifesting as γ-H2A.X positivity in neurons of the spinal cord and brain. Widespread intron retention and markers of the DNA damage response were also observed with SMN depletion in human SH-SY5Y neuroblastoma cells and human induced pluripotent stem cell-derived motor neurons. We also found that retained introns, high in GC content, served as substrates for the formation of transcriptional R-loops. We propose that defects in intron removal in SMA promote DNA damage in part through the formation of RNA:DNA hybrid structures, leading to motor neuron death.

JC Polyomavirus Abundance and Distribution in Progressive Multifocal Leukoencephalopathy (PML) Brain Tissue Implicates Myelin Sheath in Intracerebral Dissemination of Infection.

Over half of adults are seropositive for JC polyomavirus (JCV), but rare individuals develop progressive multifocal leukoencephalopathy (PML), a demyelinating JCV infection of the central nervous system. Previously, PML was primarily seen in immunosuppressed patients with AIDS or certain cancers, but it has recently emerged as a drug safety issue through its association with diverse immunomodulatory therapies. To better understand the relationship between the JCV life cycle and PML pathology, we studied autopsy brain tissue from a 70-year-old psoriasis patient on the integrin alpha-L inhibitor efalizumab following a ~2 month clinical course of PML. Sequence analysis of lesional brain tissue identified PML-associated viral mutations in regulatory (non-coding control region) DNA, capsid protein VP1, and the regulatory agnoprotein, as well as 9 novel mutations in capsid protein VP2, indicating rampant viral evolution. Nine samples, including three gross PML lesions and normal-appearing adjacent tissues, were characterized by histopathology and subject to quantitative genomic, proteomic, and molecular localization analyses. We observed a striking correlation between the spatial extent of demyelination, axonal destruction, and dispersion of JCV along white matter myelin sheath. Our observations in this case, as well as in a case of PML-like disease in an immunocompromised rhesus macaque, suggest that long-range spread of polyomavirus and axonal destruction in PML might involve extracellular association between virus and the white matter myelin sheath.

Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways.

Amyotrophic lateral sclerosis (ALS) is a devastating neurological disease with no effective treatment. We report the results of a moderate-scale sequencing study aimed at increasing the number of genes known to contribute to predisposition for ALS. We performed whole-exome sequencing of 2869 ALS patients and 6405 controls. Several known ALS genes were found to be associated, and TBK1 (the gene encoding TANK-binding kinase 1) was identified as an ALS gene. TBK1 is known to bind to and phosphorylate a number of proteins involved in innate immunity and autophagy, including optineurin (OPTN) and p62 (SQSTM1/sequestosome), both of which have also been implicated in ALS. These observations reveal a key role of the autophagic pathway in ALS and suggest specific targets for therapeutic intervention.

Rescue of gene-expression changes in an induced mouse model of spinal muscular atrophy by an antisense oligonucleotide that promotes inclusion of SMN2 exon 7.

Spinal muscular atrophy (SMA) is a neuromuscular disease caused by disruption of the survival motor neuron 1 (SMN1) gene, partly compensated for by the paralogous gene SMN2. Exon 7 inclusion is critical for full-length SMN protein production and occurs at a much lower frequency for SMN2 than for SMN1. Antisense oligonucleotide (ASO)-mediated blockade of an intron 7 splicing silencer was previously shown to promote inclusion of SMN2 exon 7 in SMA mouse models and mediate phenotypic rescue. However, downstream molecular consequences of this ASO therapy have not been defined. Here we characterize the gene-expression changes that occur in an induced model of SMA and show substantial rescue of those changes in central nervous system tissue upon intracerebroventricular administration of an ASO that promotes inclusion of exon 7, with earlier administration promoting greater rescue. This study offers a robust reference set of preclinical pharmacodynamic gene expression effects for comparison of other investigational therapies for SMA.

Whole Genome Sequencing Reveals a Chromosome 9p Deletion Causing DOCK8 Deficiency in an Adult Diagnosed with Hyper IgE Syndrome Who Developed Progressive Multifocal Leukoencephalopathy.

PURPOSE: A 30 year-old man with a history of recurrent skin infections as well as elevated serum IgE and eosinophils developed neurological symptoms and had T2-hyperintense lesions observed in cerebral MRI. The immune symptoms were attributed to Hyper IgE syndrome (HIES) and the neurological symptoms with presence of JC virus in cerebrospinal fluid were diagnosed as Progressive Multifocal Leukoencephalopathy (PML). The patient was negative for STAT3 mutations. To determine if other mutations explain HIES and/or PML in this subject, his DNA was analyzed by whole genome sequencing. METHODS: Whole genome sequencing was completed to 30X coverage, and whole genome SNP typing was used to complement these data. The methods revealed single nucleotide variants, structural variants, and copy number variants across the genome. Genome-wide data were analyzed for homozygous or compound heterozygous null mutations for all protein coding genes. Mutations were confirmed by PCR and/or Sanger sequencing. RESULTS: Whole genome analysis revealed deletions near the telomere of both copies of chromosome 9p. Several genes, including DOCK8, were impacted by the deletions but it was unclear whether each chromosome had identical or distinct deletions. PCR across the impacted region combined with Sanger sequencing of selected fragments confirmed a homozygous deletion from position 10,211 to 586,751. CONCLUSION: While several genes are impacted by the deletion, DOCK8 deficiency is the most probable cause of HIES in this patient. DOCK8 deficiency may have also predisposed the patient to develop PML.

Newborn blood spot screening test using multiplexed real-time PCR to simultaneously screen for spinal muscular atrophy and severe combined immunodeficiency.

BACKGROUND: Spinal muscular atrophy (SMA) is a motor neuron disorder caused by the absence of a functional survival of motor neuron 1, telomeric (SMN1) gene. Type I SMA, a lethal disease of infancy, accounts for the majority of cases. Newborn blood spot screening (NBS) to detect severe combined immunodeficiency (SCID) has been implemented in public health laboratories in the last 5 years. SCID detection is based on real-time PCR assays to measure T-cell receptor excision circles (TREC), a byproduct of T-cell development. We modified a multiplexed real-time PCR TREC assay to simultaneously determine the presence or absence of the SMN1 gene from a dried blood spot (DBS) punch in a single reaction well. METHOD: An SMN1 assay using a locked nucleic acid probe was initially developed with cell culture and umbilical cord blood (UCB) DNA extracts, and then integrated into the TREC assay. DBS punches were placed in 96-well arrays, washed, and amplified directly using reagents specific for TREC, a reference gene [ribonuclease P/MRP 30kDa subunit (RPP30)], and the SMN1 gene. The assay was tested on DBS made from UCB units and from peripheral blood samples of SMA-affected individuals and their family members. RESULTS: DBS made from SMA-affected individuals showed no SMN1-specific amplification, whereas DBS made from all unaffected carriers and UCB showed SMN1 amplification above a well-defined threshold. TREC and RPP30 content in all DBS were within the age-adjusted expected range. CONCLUSIONS: SMA caused by the absence of SMN1 can be detected from the same DBS punch used to screen newborns for SCID.

Development of a multi-biomarker disease activity test for rheumatoid arthritis.

BACKGROUND: Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. OBJECTIVES: To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. METHODS: Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. RESULTS: 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. CONCLUSION: We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.

Progressive multifocal leukoencephalopathy (PML) development is associated with mutations in JC virus capsid protein VP1 that change its receptor specificity.

Progressive multifocal leukoencephalopathy (PML), a fatal demyelinating disease caused by JC virus (JCV) infection of oligodendrocytes, may develop in patients with immune disorders following reactivation of chronic benign infection. Mutations of JCV capsid viral protein 1 (VP1), the capsid protein involved in binding to sialic acid cell receptors, might favor PML onset. Cerebrospinal fluid sequences from 37/40 PML patients contained one of several JCV VP1 amino acid mutations, which were also present in paired plasma but not urine sequences despite the same viral genetic background. VP1-derived virus-like particles (VLPs) carrying these mutations lost hemagglutination ability, showed different ganglioside specificity, and abolished binding to different peripheral cell types compared with wild-type VLPs. However, mutants still bound brain-derived cells, and binding was not affected by sialic acid removal by neuraminidase. JCV VP1 substitutions are acquired intrapatient and might favor JCV brain invasion through abrogation of sialic acid binding with peripheral cells, while maintaining sialic acid-independent binding with brain cells.

Sequencing and analysis of JC virus DNA from natalizumab-treated PML patients.

BACKGROUND: Progressive multifocal leukoencephalopathy (PML) in natalizumab-treated MS patients is linked to JC virus (JCV) infection. JCV sequence variation and rearrangements influence viral pathogenicity and tropism. To better understand PML development, we analyzed viral DNA sequences in blood, CSF and/or urine of natalizumab-treated PML patients. METHODS: Using biofluid samples from 17 natalizumab-treated PML patients, we sequenced multiple isolates of the JCV noncoding control region (NCCR), VP1 capsid coding region, and the entire 5 kb viral genome. RESULTS: Analysis of JCV from multiple biofluids revealed that individuals were infected with a single genotype. Across our patient cohort, multiple PML-associated NCCR rearrangements and VP1 mutations were present in CSF and blood, but absent from urine-derived virus. NCCR rearrangements occurred in CSF of 100% of our cohort. VP1 mutations were observed in blood or CSF in 81% of patients. Sequencing of complete JCV genomes demonstrated that NCCR rearrangements could occur without VP1 mutations, but VP1 mutations were not observed without NCCR rearrangement. CONCLUSIONS: These data confirm that JCV in natalizumab-PML patients is similar to that observed in other PML patient groups, multiple genotypes are associated with PML, individual patients appear to be infected with a single genotype, and PML-associated mutations arise in patients during PML development.

A genome-wide screen of gene-gene interactions for rheumatoid arthritis susceptibility.

The objective of the study was to identify interacting genes contributing to rheumatoid arthritis (RA) susceptibility and identify SNPs that discriminate between RA patients who were anti-cyclic citrullinated protein positive and healthy controls. We analyzed two independent cohorts from the North American Rheumatoid Arthritis Consortium. A cohort of 908 RA cases and 1,260 controls was used to discover pairwise interactions among SNPs and to identify a set of single nucleotide polymorphisms (SNPs) that predict RA status, and a second cohort of 952 cases and 1,760 controls was used to validate the findings. After adjusting for HLA-shared epitope alleles, we identified and replicated seven SNP pairs within the HLA class II locus with significant interaction effects. We failed to replicate significant pairwise interactions among non-HLA SNPs. The machine learning approach "random forest" applied to a set of SNPs selected from single-SNP and pairwise interaction tests identified 93 SNPs that distinguish RA cases from controls with 70% accuracy. HLA SNPs provide the most classification information, and inclusion of non-HLA SNPs improved classification. While specific gene-gene interactions are difficult to validate using genome-wide SNP data, a stepwise approach combining association and classification methods identifies candidate interacting SNPs that distinguish RA cases from healthy controls.

Convergent Random Forest predictor: methodology for predicting drug response from genome-scale data applied to anti-TNF response.

Biomarker development for prediction of patient response to therapy is one of the goals of molecular profiling of human tissues. Due to the large number of transcripts, relatively limited number of samples, and high variability of data, identification of predictive biomarkers is a challenge for data analysis. Furthermore, many genes may be responsible for drug response differences, but often only a few are sufficient for accurate prediction. Here we present an analysis approach, the Convergent Random Forest (CRF) method, for the identification of highly predictive biomarkers. The aim is to select from genome-wide expression data a small number of non-redundant biomarkers that could be developed into a simple and robust diagnostic tool. Our method combines the Random Forest classifier and gene expression clustering to rank and select a small number of predictive genes. We evaluated the CRF approach by analyzing four different data sets. The first set contains transcript profiles of whole blood from rheumatoid arthritis patients, collected before anti-TNF treatment, and their subsequent response to the therapy. In this set, CRF identified 8 transcripts predicting response to therapy with 89% accuracy. We also applied the CRF to the analysis of three previously published expression data sets. For all sets, we have compared the CRF and recursive support vector machines (RSVM) approaches to feature selection and classification. In all cases the CRF selects much smaller number of features, five to eight genes, while achieving similar or better performance on both training and independent testing sets of data. For both methods performance estimates using cross-validation is similar to performance on independent samples. The method has been implemented in R and is available from the authors upon request: Jadwiga.Bienkowska@biogenidec.com.

CRIPTO3, a presumed pseudogene, is expressed in cancer.

Cripto is a cell surface protein highly expressed in certain solid tumors, and overexpression of Cripto protein is oncogenic. Cripto-1 protein is encoded by CRIPTO1 gene. CRIPTO3, a presumed pseudogene, has an open reading frame with six amino acid differences from Cripto-1. We show that CRIPTO3 mRNA is the CRIPTO message expressed in many cancer samples. A CRIPTO3 SAGE tag was found in several cancer SAGE libraries, while the CRIPTO1 tag was found in ES cell libraries. In vitro experiments indicate both Cripto-1 and Cripto-3 proteins are functional in the Nodal-dependent signal pathway. Our data indicate that CRIPTO3 is an expressed gene, particularly in certain cancers, and suggest a potentially novel mechanism of oncogenesis through activation of a retrogene.

Experimental comparison and cross-validation of Affymetrix HT plate and cartridge array gene expression platforms.

The successful use of gene expression microarrays in basic research studies has spawned interest in the use of this technology for clinical trial and population-based studies, but cost, complexity of sample processing and tracking, and limitations of sample throughput have restricted their use for these very large-scale investigations. The Affymetrix GeneChip Plate Array System addresses these concerns and could facilitate larger studies if the data prove to be comparable to industry-standard cartridge arrays. Here we present a comparative evaluation of performance between Affymetrix GeneChip Human 133A cartridge and plate arrays with an emphasis on the assessment of systematic variation and its impact on log ratio data. This study utilized two standardized control RNAs on four independent lots of plate and cartridge arrays. We found that HT plate arrays showed improved specificity and were more reproducible over a wide intensity range, but cartridge arrays exhibit better sensitivity. Not surprisingly, artifactual changes due to positional effects were detectable on plate arrays, but were generally small in number and magnitude and in practice may be removed using standard fold-change and p-value thresholds. Overall, log ratio data between cartridges and plate arrays were remarkably concordant. We conclude that HT arrays offer significant improvements over cartridge arrays for large-scale studies.

Genome-wide association scan identifies candidate polymorphisms associated with differential response to anti-TNF treatment in rheumatoid arthritis.

The prediction of response (or non-response) to anti-TNF treatment for rheumatoid arthritis (RA) is a pressing clinical problem. We conducted a genome-wide association study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning anti-TNF therapy as part of Autoimmune Biomarkers Collaborative Network (ABCoN [Autoimmune Bio-markers Collaborative Network]) patient cohort. Response to therapy was determined by the change in Disease Activity Score (DAS28) observed after 14 wks. We used a two-part analysis that treated the change in DAS28 as a continuous trait and then incorporated it into a dichotomous trait of "good responder" and "nonresponder" by European League Against Rheumatism (EULAR) criteria. We corrected for multiple tests by permutation, and adjusted for potential population stratification using EIGENSTRAT. Multiple single nucleotide polymorphism (SNP) markers showed significant associations near or within loci including: the v-maf musculoaponeurotic fibrosarcoma oncogene homolog B (MAFB) gene on chromosome 20; the type I interferon gene IFNk on chromosome 9; and in a locus on chromosome 7 that includes the paraoxonase I (PON1) gene. An SNP in the IL10 promoter (rs1800896) that was previously reported as associated with anti-TNF response was weakly associated with response in this cohort. Replications of these results in independent and larger data sets clearly are required. We provide a reference list of candidate SNPs (P < 0.01) that can be investigated in future pharmacogenomic studies.

Several regions in the major histocompatibility complex confer risk for anti-CCP-antibody positive rheumatoid arthritis, independent of the DRB1 locus.

Recent evidence suggests that additional risk loci for RA are present in the major histocompatibility complex (MHC), independent of the class II HLA-DRB1 locus. We have now tested a total of 1,769 SNPs across 7.5Mb of the MHC located from 6p22.2 (26.03 Mb) to 6p21.32 (33.59 Mb) derived from the Illumina 550K Beadchip (Illumina, San Diego, CA, USA). For an initial analysis in the whole dataset (869 RA CCP + cases, 1,193 controls), the strongest association signal was observed in markers near the HLA-DRB1 locus, with additional evidence for association extending out into the Class I HLA region. To avoid confounding that may arise due to linkage disequilibrium with DRB1 alleles, we analyzed a subset of the data by matching cases and controls by DRB1 genotype (both alleles matched 1:1), yielding a set of 372 cases with 372 controls. This analysis revealed the presence of at least two regions of association with RA in the Class I region, independent of DRB1 genotype. SNP alleles found on the conserved A1-B8-DR3 (8.1) haplotype show the strongest evidence of positive association (P ~ 0.00005) clustered in the region around the HLA-C locus. In addition, we identified risk alleles that are not present on the 8.1 haplotype, with maximal association signals (P ~ 0.001-0.0027) located near the ZNF311 locus. This latter association is enriched in DRB1*0404 individuals. Finally, several additional association signals were found in the extreme centromeric portion of the MHC, in regions containing the DOB1, TAP2, DPB1, and COL11A2 genes. These data emphasize that further analysis of the MHC is likely to reveal genetic risk factors for rheumatoid arthritis that are independent of the DRB1 shared epitope alleles.

TRAF1-C5 as a risk locus for rheumatoid arthritis--a genomewide study.

BACKGROUND: Rheumatoid arthritis has a complex mode of inheritance. Although HLA-DRB1 and PTPN22 are well-established susceptibility loci, other genes that confer a modest level of risk have been identified recently. We carried out a genomewide association analysis to identify additional genetic loci associated with an increased risk of rheumatoid arthritis. METHODS: We genotyped 317,503 single-nucleotide polymorphisms (SNPs) in a combined case-control study of 1522 case subjects with rheumatoid arthritis and 1850 matched control subjects. The patients were seropositive for autoantibodies against cyclic citrullinated peptide (CCP). We obtained samples from two data sets, the North American Rheumatoid Arthritis Consortium (NARAC) and the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA). Results from NARAC and EIRA for 297,086 SNPs that passed quality-control filters were combined with the use of Cochran-Mantel-Haenszel stratified analysis. SNPs showing a significant association with disease (P<1x10(-8)) were genotyped in an independent set of case subjects with anti-CCP-positive rheumatoid arthritis (485 from NARAC and 512 from EIRA) and in control subjects (1282 from NARAC and 495 from EIRA). RESULTS: We observed associations between disease and variants in the major-histocompatibility-complex locus, in PTPN22, and in a SNP (rs3761847) on chromosome 9 for all samples tested, the latter with an odds ratio of 1.32 (95% confidence interval, 1.23 to 1.42; P=4x10(-14)). The SNP is in linkage disequilibrium with two genes relevant to chronic inflammation: TRAF1 (encoding tumor necrosis factor receptor-associated factor 1) and C5 (encoding complement component 5). CONCLUSIONS: A common genetic variant at the TRAF1-C5 locus on chromosome 9 is associated with an increased risk of anti-CCP-positive rheumatoid arthritis.

STAT4 and the risk of rheumatoid arthritis and systemic lupus erythematosus.

BACKGROUND: Rheumatoid arthritis is a chronic inflammatory disease with a substantial genetic component. Susceptibility to disease has been linked with a region on chromosome 2q. METHODS: We tested single-nucleotide polymorphisms (SNPs) in and around 13 candidate genes within the previously linked chromosome 2q region for association with rheumatoid arthritis. We then performed fine mapping of the STAT1-STAT4 region in a total of 1620 case patients with established rheumatoid arthritis and 2635 controls, all from North America. Implicated SNPs were further tested in an independent case-control series of 1529 patients with early rheumatoid arthritis and 881 controls, all from Sweden, and in a total of 1039 case patients and 1248 controls from three series of patients with systemic lupus erythematosus. RESULTS: A SNP haplotype in the third intron of STAT4 was associated with susceptibility to both rheumatoid arthritis and systemic lupus erythematosus. The minor alleles of the haplotype-defining SNPs were present in 27% of chromosomes of patients with established rheumatoid arthritis, as compared with 22% of those of controls (for the SNP rs7574865, P=2.81x10(-7); odds ratio for having the risk allele in chromosomes of patients vs. those of controls, 1.32). The association was replicated in Swedish patients with recent-onset rheumatoid arthritis (P=0.02) and matched controls. The haplotype marked by rs7574865 was strongly associated with lupus, being present on 31% of chromosomes of case patients and 22% of those of controls (P=1.87x10(-9); odds ratio for having the risk allele in chromosomes of patients vs. those of controls, 1.55). Homozygosity of the risk allele, as compared with absence of the allele, was associated with a more than doubled risk for lupus and a 60% increased risk for rheumatoid arthritis. CONCLUSIONS: A haplotype of STAT4 is associated with increased risk for both rheumatoid arthritis and systemic lupus erythematosus, suggesting a shared pathway for these illnesses.