Time filter

Source Type

Cambridge, United Kingdom

Lambrechts D.,Vesalius Research Center | Lambrechts D.,Catholic University of Leuven | Moisse M.,Vesalius Research Center | Moisse M.,Catholic University of Leuven | And 10 more authors.

Purpose: There are currently no validated biomarkers predicting bevacizumab treatment outcome or toxicity. We combined biomarker data from six phase III trials of bevacizumab to assess whether genetic variation in vascular endothelial growth factor-A (VEGF-A) pathway or hypertension-related genes are associated with bevacizumab-induced hypertension. Experimental design: Germline DNA was available from 1,631 patients receiving bevacizumab-containing therapy for advanced solid tumors. Overall, 194 white patients had grade 1-4 bevacizumab-induced hypertension. In total, 236 single nucleotide polymorphisms (SNPs) located in VEGF-A, VEGF-A receptors (FLT1 and KDR), and other genes were selected using a SNP tagging approach and genotyped. A logistic regression on individual patient data was performed after adjustment for cancer type and five other covariates. Results: Ten SNPs were associated with bevacizumab-induced hypertension (P ≤ 0.05), but none surpassed the threshold adjusted for multiple testing (P < 0.0002). The most significant VEGF-A pathway SNP was rs1680695 in EGLN3 [allelic odds ratio (OR) 1.50 [95 % confidence interval (Cl) 1.09-2.07], P = 0.012]. Two additional SNPs, rs4444903 in EGF and rs2305949 in KDR, were associated with hypertension (allelic OR 1.57 [95 % CI 1.17-2.11], P = 0.0025; allelic OR 0.62 [95 % CI 0.42-0.93], P = 0.020, respectively) and closely linked to nearby functional variants. Consistent with previous reports, rs11064560 in WNK1 was also associated with bevacizumab-induced hypertension (OR 1.41 [95 % CI 1.04-1.92], P = 0.028). Conclusions: The genes described in this large genetic analysis using pooled datasets warrant further functional investigation regarding their role in mediating bevacizumab-induced hypertension. © 2014 Springer Science+Business Media Dordrecht. Source

Williams F.M.K.,Kings College London | Bansal A.T.,Acclarogen Ltd | Van Meurs J.B.,Erasmus University Rotterdam | Bell J.T.,Kings College London | And 15 more authors.
Annals of the Rheumatic Diseases

Objective: Lumbar disc degeneration (LDD) is an important cause of low back pain, which is a common and costly problem. LDD is characterised by disc space narrowing and osteophyte growth at the circumference of the disc. To date, the agnostic search of the genome by genome-wide association (GWA) to identify common variants associated with LDD has not been fruitful. This study is the first GWA meta-analysis of LDD. Methods: We have developed a continuous trait based on disc space narrowing and osteophytes growth which is measurable on all forms of imaging ( plain radiograph, CT scan and MRI) and performed a meta-analysis of five cohorts of Northern European extraction each having GWA data imputed to HapMap V.2. Results: This study of 4600 individuals identified four single nucleotide polymorphisms with p<5×10-8, the threshold set for genome-wide significance. We identified a variant in the PARK2 gene (p=2.8×10-8) associated with LDD. Differential methylation at one CpG island of the PARK2 promoter was observed in a small subset of subjects (β=8.74×10-4, p=0.006). Conclusions LDD accounts for a considerable proportion of low back pain and the pathogenesis of LDD is poorly understood. This work provides evidence of association of the PARK2 gene and suggests that methylation of the PARK2 promoter may influence degeneration of the intervertebral disc. This gene has not previously been considered a candidate in LDD and further functional work is needed on this hitherto unsuspected pathway. Source

De Haas S.,Hoffmann-La Roche | Delmar P.,Hoffmann-La Roche | Bansal A.T.,Acclarogen Ltd | Moisse M.,Vesalius Research Center | And 10 more authors.

Background: Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified. Methods: We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome. Results: The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene. Conclusions: This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy. © 2014 Springer Science+Business Media Dordrecht. Source

Wang J.,Roche Holding AG | Bansal A.T.,Acclarogen Ltd | Martin M.,Roche Holding AG | Germer S.,Roche Holding AG | And 13 more authors.
Pharmacogenomics Journal

Rheumatoid arthritis (RA) is an immune-mediated inflammatory disease affecting the joints. A heterogeneous response to available therapies demonstrates the need to identify those patients likely to benefit from a particular therapy. Our objective was to identify genetic factors associated with response to tocilizumab, a humanized monoclonal antibody targeting the interleukin (IL)-6 receptor, recently approved for treating RA. We report the first genome-wide association study on the response to tocilizumab in 1683 subjects with RA from six clinical studies. Putative associations were identified with eight loci, previously unrecognized as linked to the IL-6 pathway or associated with RA risk. This study suggests that it is unlikely that a major genetic determinant of response exists, and it illustrates the complexity of performing genome-wide association scans in clinical trials. © 2013 Macmillan Publishers Limited. All rights reserved 1470-269X/13. Source

Perlee L.T.,Sequenom | Bansal A.T.,Acclarogen Ltd | Gehrs K.,University of Iowa | Heier J.S.,Ophthalmic Consultants of Boston | And 7 more authors.

Purpose: The accuracy of predicting conversion from early-stage age-related macular degeneration (AMD) to the advanced stages of choroidal neovascularization (CNV) or geographic atrophy (GA) was evaluated to determine whether inclusion of clinically relevant genetic markers improved accuracy beyond prediction using phenotypic risk factors alone. Design: Cohort study. Participants: White, non-Hispanic subjects participating in the Age-Related Eye Disease Study (AREDS) sponsored by the National Eye Institute consented to provide a genetic specimen. Of 2415 DNA specimens available, 940 were from disease-free subjects and 1475 were from subjects with early or intermediate AMD. Methods: DNA specimens from study subjects were genotyped for 14 single nucleotide polymorphisms (SNPs) in genes shown previously to associate with CNV: ARMS2, CFH, C3, C2, FB, CFHR4, CFHR5, and F13B. Clinical demographics and established disease associations, including age, sex, smoking status, body mass index (BMI), AREDS treatment category, and educational level, were evaluated. Four multivariate logistic models (phenotype; genotype; phenotype + genotype; and phenotype + genotype + demographic + environmental factors) were tested using 2 end points (CNV, GA). Models were fitted using Cox proportional hazards regression to use time-to-disease onset data. Main Outcome Measures: Brier score (measure of accuracy) was used to identify the model with the lowest prediction error in the training set. The most accurate model was subjected to independent statistical validation, and final model performance was described using area under the receiver operator curve (AUC) or C-statistic. Results: The CNV prediction models that combined genotype with phenotype with or without age and smoking revealed superior performance (C-statistic = 0.96) compared with the phenotype model based on the simplified severity scale and the presence of CNV in the nonstudy eye (C-statistic = 0.89; P<0.01). For GA, the model that combined genotype with phenotype demonstrated the highest performance (AUC = 0.94). Smoking status and ARMS2 genotype had less of an impact on the prediction of GA compared with CNV. Conclusions: Inclusion of genotype assessment improves CNV prediction beyond that achievable with phenotype alone and may improve patient management. Separate assessments should be used to predict progression to CNV and GA because genetic markers and smoking status do not equally predict both end points. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references. © 2013 American Academy of Ophthalmology. Source

Discover hidden collaborations