Acclarogen Ltd

Cambridge, United Kingdom

Acclarogen Ltd

Cambridge, United Kingdom
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Williams F.M.K.,King's College London | Bansal A.T.,Acclarogen Ltd. | Van Meurs J.B.,Erasmus University Rotterdam | Van Meurs J.B.,The Netherlands Genomics Initiative Sponsored Netherlands Consortium for Healthy Aging NGI NCHA | And 17 more authors.
Annals of the Rheumatic Diseases | Year: 2013

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.


PubMed | Karolinska Institutet, BioSci Consulting, University of Nottingham, University of Southampton and 31 more.
Type: Journal Article | Journal: The European respiratory journal | Year: 2015

U-BIOPRED is a European Union consortium of 20 academic institutions, 11 pharmaceutical companies and six patient organisations with the objective of improving the understanding of asthma disease mechanisms using a systems biology approach.This cross-sectional assessment of adults with severe asthma, mild/moderate asthma and healthy controls from 11 European countries consisted of analyses of patient-reported outcomes, lung function, blood and airway inflammatory measurements.Patients with severe asthma (nonsmokers, n=311; smokers/ex-smokers, n=110) had more symptoms and exacerbations compared to patients with mild/moderate disease (n=88) (2.5 exacerbations versus 0.4 in the preceding 12months; p<0.001), with worse quality of life, and higher levels of anxiety and depression. They also had a higher incidence of nasal polyps and gastro-oesophageal reflux with lower lung function. Sputum eosinophil count was higher in severe asthma compared to mild/moderate asthma (median count 2.99% versus 1.05%; p=0.004) despite treatment with higher doses of inhaled and/or oral corticosteroids.Consistent with other severe asthma cohorts, U-BIOPRED is characterised by poor symptom control, increased comorbidity and airway inflammation, despite high levels of treatment. It is well suited to identify asthma phenotypes using the array of omic datasets that are at the core of this systems medicine approach.


PubMed | University of Amsterdam, St. Mary's University, BioSci Consulting, Copenhagen University and 12 more.
Type: Journal Article | Journal: The European respiratory journal | Year: 2015

U-BIOPRED aims to characterise paediatric and adult severe asthma using conventional and innovative systems biology approaches. A total of 99 school-age children with severe asthma and 81 preschoolers with severe wheeze were compared with 49 school-age children with mild/moderate asthma and 53 preschoolers with mild/moderate wheeze in a cross-sectional study. Despite high-dose treatment, the severe cohorts had more severe exacerbations compared with the mild/moderate ones (annual medians: school-aged 3.0 versus 1.1, preschool 3.9 versus 1.8; p<0.001). Exhaled tobacco exposure was common in the severe wheeze cohort. Almost all participants in each cohort were atopic and had a normal body mass index. Asthma-related quality of life, as assessed by the Paediatric Asthma Quality of Life Questionnaire (PAQLQ) and the Paediatric Asthma Caregivers Quality of Life Questionnaire (PACQLQ), was worse in the severe cohorts (meanse school-age PAQLQ: 4.770.15 versus 5.800.19; preschool PACQLQ: 4.270.18 versus 6.040.18; both p0.001); however, mild/moderate cohorts also had significant morbidity. Impaired quality of life was associated with poor control and airway obstruction. Otherwise, the severe and mild/moderate cohorts were clinically very similar. Children with severe preschool wheeze or severe asthma are usually atopic and have impaired quality of life that is associated with poor control and airflow limitation: a very different phenotype from adult severe asthma. In-depth phenotyping of these children, integrating clinical data with high-dimensional biomarkers, may help to improve and tailor their clinical management.


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.
Angiogenesis | Year: 2014

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.


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.
Angiogenesis | Year: 2014

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.


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.
Ophthalmology | Year: 2013

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.


Vignal C.M.,Imperial College London | Vignal C.M.,Glaxosmithkline | Bansal A.T.,Acclarogen Ltd | Balding D.J.,University College London
Annals of Human Genetics | Year: 2011

Rheumatoid arthritis (RA) is strongly associated with the human leukocyte antigen (HLA) genomic region, most notably with a group of HLA-DRB1 alleles termed the shared epitope (SE). There is also substantial evidence of other risk loci in the HLA region, but refinement has been hampered by extensive linkage disequilibrium (LD). Using genotype imputation, we analysed 6575 RA cases and controls with genotypes at 6180 HLA SNPs; about half the subjects had four-digit DRB1 genotypes. Single-SNP tests revealed hundreds of strong associations across the HLA region, even after adjusting for DRB1. We implemented penalised logistic regression in a multi-SNP association analysis using the double-exponential (DE) penalty term on the regression coefficients and the normal-exponential-gamma (NEG). The penalised approaches identified sparse sets of SNPs that could collectively explain most of the association with RA over the whole HLA region. The HLA-DPB1 SNP rs3117225, was consistently identified in our analyses and was confirmed by results from the North American Rheumatoid Arthritis Consortium study (NARAC). We conclude that SNP selection using penalised regression shows a substantial benefit over single-SNP analyses in identifying risk loci in regions of high LD, and the flexibility of the NEG conveys additional advantages. © 2011 The Authors, Annals of Human Genetics © 2011 Blackwell Publishing Ltd/University College London.


Voros S.,Richmond Global | Maurovich-Horvat P.,Semmelweis University | Marvasty I.B.,Richmond Global | Bansal A.T.,Acclarogen Ltd. | And 7 more authors.
Journal of Cardiovascular Computed Tomography | Year: 2014

Background: Complex biological networks of atherosclerosis are largely unknown. Objective: The main objective of the Genetic Loci and the Burden of Atherosclerotic Lesions study is to assemble comprehensive biological networks of atherosclerosis using advanced cardiovascular imaging for phenotyping, a panomic approach to identify underlying genomic, proteomic, metabolomic, and lipidomic underpinnings, analyzed by systems biology-driven bioinformatics. Methods: By design, this is a hypothesis-free unbiased discovery study collecting a large number of biologically related factors to examine biological associations between genomic, proteomic, metabolomic, lipidomic, and phenotypic factors of atherosclerosis. The Genetic Loci and the Burden of Atherosclerotic Lesions study (NCT01738828) is a prospective, multicenter, international observational study of atherosclerotic coronary artery disease. Approximately 7500 patients are enrolled and undergo non-contrast-enhanced coronary calcium scanning by CT for the detection and quantification of coronary artery calcium, as well as coronary artery CT angiography for the detection and quantification of plaque, stenosis, and overall coronary artery disease burden. In addition, patients undergo whole genome sequencing, DNA methylation, whole blood-based transcriptome sequencing, unbiased proteomics based on mass spectrometry, as well as metabolomics and lipidomics on a mass spectrometry platform. The study is analyzed in 3 subsequent phases, and each phase consists of a discovery cohort and an independent validation cohort. For the primary analysis, the primary phenotype will be the presence of any atherosclerotic plaque, as detected by cardiac CT. Additional phenotypic analyses will include per patient maximal luminal stenosis defined as 50% and 70% diameter stenosis. Single-omic and multi-omic associations will be examined for each phenotype; putative biomarkers will be assessed for association, calibration, discrimination, and reclassification. © 2014 The Authors.


McCarthy A.D.,PGXIS Ltd. | Owens I.J.,PGXIS Ltd. | Bansal A.T.,Acclarogen Ltd. | McTighe S.M.,University of Cambridge | And 2 more authors.
Pharmacology Biochemistry and Behavior | Year: 2011

FK962 is a member of a novel class of compounds that promote somatostatin production in the brain, and is being developed as a treatment for patients with Alzheimer's disease. As acetylcholinesterase inhibitors such as Aricept© (donepezil) are widely used to treat these patients, it is important to confirm that potential new medicines in this disease area can be co-administered with drugs such as Aricept. To study the effect of FK962 in combination with donepezil, touchscreen methodology was used to measure the effect on cognition in rats. Doses of FK962 and donepezil were identified that resulted in minimal cognition enhancement when given separately. There was strong evidence (p = 0.002) of a treatment difference between the combination of FK962/donepezil and FK962 alone: the estimated treatment difference is 5.47 (95% CI: 2.19-8.75). There was also evidence (p = 0.017) of a treatment difference between the combination of FK962/donepezil and donepezil alone: the estimated treatment difference is 4.01 (95% CI: 0.77-7.26). Therefore, a combination of low doses of FK962 and donepezil showed a significantly greater effect on cognition than low doses of either compound alone. This is the first time that FK962 has shown activity in a reward-based model of cognition. In addition, these data suggest that this compound could beneficially be given in addition to Aricept to treat Alzheimer's disease patients. © 2010 Elsevier Inc.


Hageman G.S.,University of Utah | Gehrs K.,Center for Macula and Retinal Disease | Lejnine S.,Bioguidance Consultants | Bansal A.T.,Acclarogen Ltd | And 7 more authors.
Human Genomics | Year: 2011

Predictive tests for estimating the risk of developing late-stage neovascular age-related macular degeneration (AMD) are subject to unique challenges. AMD prevalence increases with age, clinical phenotypes are heterogeneous and control collections are prone to high false-negative rates, as many control subjects are likely to develop disease with advancing age. Risk prediction tests have been presented previously, using up to ten genetic markers and a range of self-reported non-genetic variables such as body mass index (BMI) and smoking history. In order to maximise the accuracy of prediction for mainstream genetic testing, we sought to derive a test comparable in performance to earlier testing models but based purely on genetic markers, which are static through life and not subject to misreporting. We report a multicentre assessment of a larger panel of single nucleotide polymorphisms (SNPs) than previously analysed, to improve further the classification performance of a predictive test to estimate the risk of developing choroidal neovascular (CNV) disease. We developed a predictive model based solely on genetic markers and avoided inclusion of self-reported variables (eg smoking history) or non-static factors (BMI, education status) that might otherwise introduce inaccuracies in calculating individual risk estimates. We describe the performance of a test panel comprising 13 SNPs genotyped across a consolidated collection of four patient cohorts obtained from academic centres deemed appropriate for pooling. We report on predictive effect sizes and their classification performance. By incorporating multiple cohorts of homogeneous ethnic origin, we obtained >80 per cent power to detect differences in genetic variants observed between cases and controls. We focused our study on CNV, a subtype of advanced AMD associated with a severe and potentially treatable form of the disease. Lastly, we followed a two-stage strategy involving both test model development and test model validation to present estimates of classification performance anticipated in the larger clinical setting. The model contained nine SNPs tagging variants in the regulators of complement activation (RCA) locus spanning the complement factor H (CFH), complement factor H-related 4 (CFHR4), complement factor H-related 5 (CFHR5) and coagulation factor XIII B subunit (F13B) genes; the four remaining SNPs targeted polymorphisms in the complement component 2 (C2), complement factor B (CFB), complement component 3 (C3) and age-related maculopathy susceptibility protein 2 (ARMS2) genes. The pooled sample size (1,132 CNV cases, 822 controls) allowed for both model development and model validation to confirm the accuracy of risk prediction. At the validation stage, our test model yielded 82 per cent sensitivity and 63 per cent specificity, comparable with metrics reported with earlier testing models that included environmental risk factors. Our test had an area under the curve of 0.80, reflecting a modest improvement compared with tests reported with fewer SNPs. © HENRY STEWART PUBLICATIONS.

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