There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined approximately 2,000 individuals for each of 7 major diseases and a shared set of approximately 3,000 controls. Case-control comparisons identified 24 independent association signals at
Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5m genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N≤71,225 European ancestry, N=12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N=29,136). We identified association between systolic or diastolic blood pressure and common variants in 8 regions near the CYP17A1 (P=7×10−24), CYP1A2 (P=1×10−23), FGF5 (P=1×10−21), SH2B3 (P=3×10−18), MTHFR (P=2×10−13), c10orf107 (P=1×10−9), ZNF652 (P=5×10−9) and PLCD3 (P=1×10−8) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.
We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.
Objective: To determine whether rheumatoid factor (RF), anti-cyclic citrullinated peptide (CCP) antibodies, or carriage of shared epitope (SE) and PTPN22 genetic susceptibility variants predict response to therapy in patients with rheumatoid arthritis (RA) treated with antitumour necrosis factor (TNF) agents. Methods: UK-wide multicentre collaborations were established to recruit a large cohort of patients treated with anti-TNF drugs for RA. Serum RF, anti-CCP antibody and SE status were determined using commercially available kits. PTPN22 R620W genotyping was performed by Sequenom MassArray. Linear regression analyses were performed to investigate the role of these four factors in predicting response to treatment by 6 months, defined as the absolute change in 28-joint Disease Activity Score (DAS28). Results: Of the 642 patients analysed, 46% received infliximab, 43% etanercept and 11% adalimumab. In all, 89% and 82% of patients were RF and anti-CCP positive, respectively. Patients that were RF negative had a 0.48 (95% CI 0.08 to 0.87) greater mean improvement in DAS28 compared to patients that were RF positive. A better response was also seen among patients that were anti-CCP negative. No association was demonstrated between drug response and SE or PTPN22 620W carriage. Conclusion: The presence of RF or anti-CCP antibodies was associated with a reduced response to anti-TNF drugs. However, these antibodies only account for a small proportion of the variance in treatment response. It is likely that genetic factors will contribute to treatment response, but these do not include the well established RA susceptibility loci, SE and PTPN22.
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