The effect of rare variants on inflation of the test statistics in case-control analyses.

BACKGROUND: The detection of bias due to cryptic population structure is an important step in the evaluation of findings of genetic association studies. The standard method of measuring this bias in a genetic association study is to compare the observed median association test statistic to the expected median test statistic. This ratio is inflated in the presence of cryptic population structure. However, inflation may also be caused by the properties of the association test itself particularly in the analysis of rare variants. We compared the properties of the three most commonly used association tests: the likelihood ratio test, the Wald test and the score test when testing rare variants for association using simulated data. RESULTS: We found evidence of inflation in the median test statistics of the likelihood ratio and score tests for tests of variants with less than 20 heterozygotes across the sample, regardless of the total sample size. The test statistics for the Wald test were under-inflated at the median for variants below the same minor allele frequency. CONCLUSIONS: In a genetic association study, if a substantial proportion of the genetic variants tested have rare minor allele frequencies, the properties of the association test may mask the presence or absence of bias due to population structure. The use of either the likelihood ratio test or the score test is likely to lead to inflation in the median test statistic in the absence of population structure. In contrast, the use of the Wald test is likely to result in under-inflation of the median test statistic which may mask the presence of population structure.This work was supported by a grant from Cancer Research UK (C490/A16561). AP is funded by a Medical Research Council studentship.This is the final published version. It first appeared at http://dx.doi.org/10.1186%2Fs12859-015-0496-1

The admixture maximum likelihood test to test for association between rare variants and disease phenotypes.

BACKGROUND: The development of genotyping arrays containing hundreds of thousands of rare variants across the genome and advances in high-throughput sequencing technologies have made feasible empirical genetic association studies to search for rare disease susceptibility alleles. As single variant testing is underpowered to detect associations, the development of statistical methods to combine analysis across variants - so-called "burden tests" - is an area of active research interest. We previously developed a method, the admixture maximum likelihood test, to test multiple, common variants for association with a trait of interest. We have extended this method, called the rare admixture maximum likelihood test (RAML), for the analysis of rare variants. In this paper we compare the performance of RAML with six other burden tests designed to test for association of rare variants. RESULTS: We used simulation testing over a range of scenarios to test the power of RAML compared to the other rare variant association testing methods. These scenarios modelled differences in effect variability, the average direction of effect and the proportion of associated variants. We evaluated the power for all the different scenarios. RAML tended to have the greatest power for most scenarios where the proportion of associated variants was small, whereas SKAT-O performed a little better for the scenarios with a higher proportion of associated variants. CONCLUSIONS: The RAML method makes no assumptions about the proportion of variants that are associated with the phenotype of interest or the magnitude and direction of their effect. The method is flexible and can be applied to both dichotomous and quantitative traits and allows for the inclusion of covariates in the underlying regression model. The RAML method performed well compared to the other methods over a wide range of scenarios. Generally power was moderate in most of the scenarios, underlying the need for large sample sizes in any form of association testing.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Genomic risk prediction of coronary artery disease in women with breast cancer: a prospective cohort study.

Funder: Wellcome TrustBackgroundAdvancements in cancer therapeutics have resulted in increases in cancer-related survival; however, there is a growing clinical dilemma. The current balancing of survival benefits and future cardiotoxic harms of oncotherapies has resulted in an increased burden of cardiovascular disease in breast cancer survivors. Risk stratification may help address this clinical dilemma. This study is the first to assess the association between a coronary artery disease-specific polygenic risk score and incident coronary artery events in female breast cancer survivors.MethodsWe utilized the Studies in Epidemiology and Research in Cancer Heredity prospective cohort involving 12,413 women with breast cancer with genotype information and without a baseline history of cardiovascular disease. Cause-specific hazard ratios for association of the polygenic risk score and incident coronary artery disease (CAD) were obtained using left-truncated Cox regression adjusting for age, genotype array, conventional risk factors such as smoking and body mass index, as well as other sociodemographic, lifestyle, and medical variables.ResultsOver a median follow-up of 10.3 years (IQR: 16.8) years, 750 incident fatal or non-fatal coronary artery events were recorded. A 1 standard deviation higher polygenic risk score was associated with an adjusted hazard ratio of 1.33 (95% CI 1.20, 1.47) for incident CAD.ConclusionsThis study provides evidence that a coronary artery disease-specific polygenic risk score can risk-stratify breast cancer survivors independently of other established cardiovascular risk factors

CHAMP: Cognitive behaviour therapy for health anxiety in medical patients, a randomised controlled trial

BACKGROUND: Abnormal health anxiety, also called hypochondriasis, has been successfully treated by cognitive behaviour therapy (CBT) in patients recruited from primary care, but only one pilot trial has been carried out among those attending secondary medical clinics where health anxiety is likely to be more common and have a greater impact on services. The CHAMP study extends this work to examine both the clinical and cost effectiveness of CBT in this population. METHOD/DESIGN: The study is a randomized controlled trial with two parallel arms and equal randomization of 466 eligible patients (assuming a 20% drop-out) to an active treatment group of 5-10 sessions of cognitive behaviour therapy and to a control group. The aim at baseline, after completion of all assessments but before randomization, was to give a standard simple explanation of the nature of health anxiety for all participants. Subsequently the control group was to receive whatever care might usually be available in the clinics, which is normally a combination of clinical assessment, appropriate tests and reassurance. Those allocated to the active treatment group were planned to receive between 5 and 10 sessions of an adapted form of cognitive behaviour therapy based on the Salkovskis/Warwick model, in which a set of treatment strategies are chosen aimed at helping patients understand the factors that drive and maintain health anxiety. The therapy was planned to be given by graduate research workers, nurses or other health professionals trained for this intervention whom would also have their competence assessed independently during the course of treatment. The primary outcome is reduction in health anxiety symptoms after one year and the main secondary outcome is the cost of care after two years. DISCUSSION: This represents the first trial of adapted cognitive behaviour therapy in health anxiety that is large enough to test not only the clinical benefits of treatment but also whether the cost of treatment is offset by savings from reduced use of other health services in comparison to the control group.Cognitive behaviour therapy for Health Anxiety in Medical Patients (CHAMP) TRIAL REGISTRATION: Current Controlled Trials ISRCTN14565822

Exploring professionals' understanding, interpretation and implementation of the 'appropriate medical treatment test' in the 2007 amendment of the Mental Health Act 1983.

BACKGROUND: The appropriate medical treatment test (ATT), included in the Mental Health Act (MHA) (1983, as amended 2007), aims to ensure that detention only occurs when treatment with the purpose of alleviating a mental disorder is available. AIMS: As part of the Assessing the Impact of the Mental Health Act (AMEND) project, this qualitative study aimed to assess professionals' understanding of the ATT, and its impact on clinical practice. METHOD: Forty-one professionals from a variety of mental health subspecialties were interviewed. Interviews were coded related to project aims, and themes were generated in an inductive process. RESULTS: We found that clinicians are often wholly relied upon for the ATT. Considered treatment varied depending on the patient's age rather than diagnosis. The ATT has had little impact on clinical practice. CONCLUSIONS: Our findings suggest the need to review training and support for professionals involved in MHA assessments, with better-defined roles. This may enable professionals to implement the ATT as its designers intended. DECLARATION OF INTEREST: None. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license

Preclinical Development of ADCT-601, a Novel Pyrrolobenzodiazepine Dimer-based Antibody-drug Conjugate Targeting AXL-expressing Cancers

AXL, a tyrosine kinase receptor that is overexpressed in many solid and hematologic malignancies, facilitates cancer progression and is associated with poor clinical outcomes. Importantly, drug-induced expression of AXL results in resistance to conventional chemotherapy and targeted therapies. Together with its presence on multiple cell types in the tumor immune microenvironment, these features make it an attractive therapeutic target for AXL-expressing malignancies. ADCT-601 (mipasetamab uzoptirine) is an AXL-targeted antibody–drug conjugate (ADC) comprising a humanized anti-AXL antibody site specifically conjugated using GlycoConnect technology to PL1601, which contains HydraSpace, a Val-Ala cleavable linker and the potent pyrrolobenzodiazepine (PBD) dimer cytotoxin SG3199. This study aimed to validate the ADCT-601 mode of action and evaluate its efficacy in vitro and in vivo, as well as its tolerability and pharmacokinetics. ADCT-601 bound to both soluble and membranous AXL, and was rapidly internalized by AXL-expressing tumor cells, allowing release of PBD dimer, DNA interstrand cross-linking, and subsequent cell killing. In vivo, ADCT-601 had potent and durable antitumor activity in a wide variety of human cancer xenograft mouse models, including patient-derived xenograft models with heterogeneous AXL expression where ADCT-601 antitumor activity was markedly superior to an auristatin-based comparator ADC. Notably, ADCT-601 had antitumor activity in a monomethyl auristatin E–resistant lung-cancer model and synergized with the PARP inhibitor olaparib in a BRCA1-mutated ovarian cancer model. ADCT-601 was well tolerated at doses of up to 6 mg/kg and showed excellent stability in vivo. These preclinical results warrant further evaluation of ADCT-601 in the clinic

Association between Common Variation in 120 Candidate Genes and Breast Cancer Risk

Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran–Armitage trend test (p-trend) and a two-degrees of freedom χ(2) test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 × 10(−5)) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty