JAM: A Scalable Bayesian Framework for Joint Analysis of Marginal SNP Effects.

Recently, large scale genome-wide association study (GWAS) meta-analyses have boosted the number of known signals for some traits into the tens and hundreds. Typically, however, variants are only analysed one-at-a-time. This complicates the ability of fine-mapping to identify a small set of SNPs for further functional follow-up. We describe a new and scalable algorithm, joint analysis of marginal summary statistics (JAM), for the re-analysis of published marginal summary statistics under joint multi-SNP models. The correlation is accounted for according to estimates from a reference dataset, and models and SNPs that best explain the complete joint pattern of marginal effects are highlighted via an integrated Bayesian penalized regression framework. We provide both enumerated and Reversible Jump MCMC implementations of JAM and present some comparisons of performance. In a series of realistic simulation studies, JAM demonstrated identical performance to various alternatives designed for single region settings. In multi-region settings, where the only multivariate alternative involves stepwise selection, JAM offered greater power and specificity. We also present an application to real published results from MAGIC (meta-analysis of glucose and insulin related traits consortium) - a GWAS meta-analysis of more than 15,000 people. We re-analysed several genomic regions that produced multiple significant signals with glucose levels 2 hr after oral stimulation. Through joint multivariate modelling, JAM was able to formally rule out many SNPs, and for one gene, ADCY5, suggests that an additional SNP, which transpired to be more biologically plausible, should be followed up with equal priority to the reported index

Overstating the evidence - double counting in meta-analysis and related problems

Background: The problem of missing studies in meta-analysis has received much attention. Less attention has been paid to the more serious problem of double counting of evidence. Methods: Various problems in overstating the precision of results from meta-analyses are described and illustrated with examples, including papers from leading medical journals. These problems include, but are not limited to, simple double-counting of the same studies, double counting of some aspects of the studies, inappropriate imputation of results, and assigning spurious precision to individual studies. Results: Some suggestions are made as to how the quality and reliability of meta-analysis can be improved. It is proposed that the key to quality in meta-analysis lies in the results being transparent and checkable. Conclusions: Existing quality check lists for meta-analysis do little to encourage an appropriate attitude to combining evidence and to statistical analysis. Journals and other relevant organisations should encourage authors to make data available and make methods explicit. They should also act promptly to withdraw meta-analyses when mistakes are found

Inter subject variability and reproducibility of diffusion tensor imaging within and between different imaging sessions.

The aim of these studies was to provide reference data on intersubject variability and reproducibility of diffusion tensor imaging. Healthy volunteers underwent imaging on two occasions using the same 3T Siemens Verio magnetic resonance scanner. At each session two identical diffusion tensor sequences were obtained along with standard structural imaging. Fractional anisotropy, apparent diffusion coefficient, axial and radial diffusivity maps were created and regions of interest applied in normalised space. The baseline data from all 26 volunteers were used to calculate the intersubject variability, while within session and between session reproducibility were calculated from all the available data. The reproducibility of measurements were used to calculate the overall and within session 95% prediction interval for zero change. The within and between session reproducibility data were lower than the values for intersubject variability, and were different across the brain. The regional mean (range) coefficient of variation figures for within session reproducibility were 2.1 (0.9-5.5%), 1.2 (0.4-3.9%), 1.2 (0.4-3.8%) and 1.8 (0.4-4.3%) for fractional anisotropy, apparent diffusion coefficient, axial and radial diffusivity, and were lower than between session reproducibility measurements (2.4 (1.1-5.9%), 1.9 (0.7-5.7%), 1.7 (0.7-4.7%) and 2.4 (0.9-5.8%); p<0.001). The calculated overall and within session 95% prediction intervals for zero change were similar. This study provides additional reference data concerning intersubject variability and reproducibility of diffusion tensor imaging conducted within the same imaging session and different imaging sessions. These data can be utilised in interventional studies to quantify change within a single imaging session, or to assess the significance of change in longitudinal studies of brain injury and disease.RCUK, Wellcome, OtherThis is the published version. It was originally published by PLoS in PLoS ONE here: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0065941

Normobaric hyperoxia does not improve derangements in diffusion tensor imaging found distant from visible contusions following acute traumatic brain injury

We have previously shown that normobaric hyperoxia may benefit peri-lesional brain and white matter following traumatic brain injury (TBI). This study examined the impact of brief exposure to hyperoxia using diffusion tensor imaging (DTI) to identify axonal injury distant from contusions. Fourteen patients with acute moderate/severe TBI underwent baseline DTI and following one hour of 80% oxygen. Thirty-two controls underwent DTI, with 6 undergoing imaging following graded exposure to oxygen. Visible lesions were excluded and data compared with controls. We used the 99% prediction interval (PI) for zero change from historical control reproducibility measurements to demonstrate significant change following hyperoxia. Following hyperoxia DTI was unchanged in controls. In patients following hyperoxia, mean diffusivity (MD) was unchanged despite baseline values lower than controls (p < 0.05), and fractional anisotropy (FA) was lower within the left uncinate fasciculus, right caudate and occipital regions (p < 0.05). 16% of white and 14% of mixed cortical and grey matter patient regions showed FA decreases greater than the 99% PI for zero change. The mechanistic basis for some findings are unclear, but suggest that a short period of normobaric hyperoxia is not beneficial in this context. Confirmation following a longer period of hyperoxia is required.Dr. Veenith was supported by clinical research training fellowship from National institute of Academic Anaesthesia and Raymond Beverly Sackler studentship. VFJN is supported by a Health Foundation/Academy of Medical Sciences Clinician Scientist Fellowship. JPC was supported by Wellcome trust project grant. DKM is supported by an NIHR Senior Investigator Award. This work was supported by a Wellcome Trust Project Grant (WT093267) and Medical Research Council (UK) Program Grant (Acute brain injury: heterogeneity of mechanisms, therapeutic targets and outcome effects (G9439390 ID 65883)), the UK National Institute of Health Research Biomedical Research Centre at Cambridge, and the Technology Platform funding provided by the UK Department of Health. The funders had no role in study design, data collection and analyses, decision to publish, or preparation of the manuscript

Use of diffusion tensor imaging to assess the impact of normobaric hyperoxia within at-risk pericontusional tissue after traumatic brain injury

Ischemia and metabolic dysfunction remain important causes of neuronal loss after head injury, and we have shown that normobaric hyperoxia may rescue such metabolic compromise. This study examines the impact of hyperoxia within injured brain using diffusion tensor imaging (DTI). Fourteen patients underwent DTI at baseline and after 1 hour of 80% oxygen. Using the apparent diffusion coefficient (ADC) we assessed the impact of hyperoxia within contusions and a 1 cm border zone of normal appearing pericontusion, and within a rim of perilesional reduced ADC consistent with cytotoxic edema and metabolic compromise. Seven healthy volunteers underwent imaging at 21%, 60%, and 100% oxygen. In volunteers there was no ADC change with hyperoxia, and contusion and pericontusion ADC values were higher than volunteers (P < 0.01). There was no ADC change after hyperoxia within contusion, but an increase within pericontusion (P < 0.05). We identified a rim of perilesional cytotoxic edema in 13 patients, and hyperoxia resulted in an ADC increase towards normal (P=0.02). We demonstrate that hyperoxia may result in benefit within the perilesional rim of cytotoxic edema. Future studies should address whether a longer period of hyperoxia has a favorable impact on the evolution of tissue injury

Phenotypic microarrays suggest Escherichia coli ST131 is not a metabolically distinct lineage of extra-intestinal pathogenic E. coli

Extraintestinal pathogenic E. coli (ExPEC) are the major aetiological agent of urinary tract infections (UTIs) in humans. The emergence of the CTX-M producing clone E. coli ST131 represents a major challenge to public health worldwide. A recent study on the metabolic potential of E. coli isolates demonstrated an association between the E. coli ST131 clone and enhanced utilisation of a panel of metabolic substrates. The studies presented here investigated the metabolic potential of ST131 and other major ExPEC ST isolates using 120 API test reagents and found that ST131 isolates demonstrated a lower metabolic activity for 5 of 120 biochemical tests in comparison to non-ST131 ExPEC isolates. Furthermore, comparative phenotypic microarray analysis showed a lack of specific metabolic profile for ST131 isolates countering the suggestion that these bacteria are metabolically fitter and therefore more successful human pathogens

Comparison of inter subject variability and reproducibility of whole brain proton spectroscopy.

The aim of these studies was to provide reference data on intersubject variability and reproducibility of metabolite ratios for Choline/Creatine (Cho/Cr), N-acetyl aspartate/Choline (NAA/Cho) and N-acetyl aspartate/Creatine (NAA/Cr), and individual signal-intensity normalised metabolite concentrations of NAA, Cho and Cr. Healthy volunteers underwent imaging on two occasions using the same 3T Siemens Verio magnetic resonance scanner. At each session two identical Metabolic Imaging and Data Acquisition Software (MIDAS) sequences were obtained along with standard structural imaging. Metabolite maps were created and regions of interest applied in normalised space. The baseline data from all 32 volunteers were used to calculate the intersubject variability, while within session and between session reproducibility were calculated from all the available data. The reproducibility of measurements were used to calculate the overall and within session 95% prediction interval for zero change. The within and between session reproducibility data were lower than the values for intersubject variability, and were variable across the different brain regions. The within and between session reproducibility measurements were similar for Cho/Cr, NAA/Choline, Cho and Cr (11.8%, 11.4%, 14.3 and 10.6% vs. 11.9%, 11.4%, 13.5% and 10.5% respectively), but for NAA/Creatine and NAA between session reproducibility was lower (9.3% and 9.1% vs. 10.1% and 9.9%; p <0.05). This study provides additional reference data that can be utilised in interventional studies to quantify change within a single imaging session, or to assess the significance of change in longitudinal studies of brain injury and disease.TV Veenith was supported by clinical research training fellowship from the National Institute of Academic Anaesthesia and Raymond Beverly Sackler studentship. VFJN is supported by an NIHR academic clinical fellowship. JPC was supported by Wellcome trust project grant. DKM is supported by an NIHR Senior Investigator Award. This work was supported by a Medical Research Council (UK) Program Grant (Acute brain injury: heterogeneity of mechanisms, therapeutic targets and outcome effects (G9439390 ID 65883)), the UK National Institute of Health Research Biomedical Research Centre at Cambridge, and the Technology Platform funding provided by the UK Department of Health.This article was originally published in PLoS ONE (Veenith TV, Mada M, Carter E, Grossac J, Newcombe V, et al. (2014) Comparison of Inter Subject Variability and Reproducibility of Whole Brain Proton Spectroscopy. PLoS ONE 9(12): e115304. doi:10.1371/journal.pone.0115304

Effect of a Successful Intensive Lifestyle Program on Insulin Sensitivity and Glucose Tolerance in Obese Youth

OBJECTIVE—To evaluate the impact on glucose metabolism of a lifestyle program (the Yale Bright Bodies Program) for obese children

The relationship between coronary stenosis morphology and fractional flow reserve: a computational fluid dynamics modelling study

Aims: International guidelines mandate the use of fractional flow reserve (FFR) and/or non-hyperaemic pressure ratios to assess the physiological significance of moderate coronary artery lesions to guide revascularization decisions. However, they remain underused such that visual estimation of lesion severity continues to be the predominant decision-making tool. It would be pragmatic to have an improved understanding of the relationship between lesion morphology and haemodynamics. The aim of this study was to compute virtual FFR (vFFR) in idealized coronary artery geometries with a variety of stenosis and vessel characteristics. Methods and results: Coronary artery geometries were modelled, based upon physiologically realistic branched arteries. Common stenosis characteristics were studied, including % narrowing, length, eccentricity, shape, number, position relative to branch, and distal (myocardial) resistance. Computational fluid dynamics modelling was used to calculate vFFRs using the VIRTUheart™ system. Percentage lesion severity had the greatest effect upon FFR. Any ≥80% diameter stenosis in two views (i.e. concentric) was physiologically significant (FFR ≤ 0.80), irrespective of length, shape, or vessel diameter. Almost all eccentric stenoses and all 50% concentric stenoses were physiologically non-significant, whilst 70% uniform concentric stenoses about 10 mm long straddled the ischaemic threshold (FFR 0.80). A low microvascular resistance (MVR) reduced FFR on average by 0.05, and a high MVR increased it by 0.03. Conclusion: Using computational modelling, we have produced an analysis of vFFR that relates stenosis characteristics to haemodynamic significance. The strongest predictor of a positive vFFR was a concentric, ≥80% diameter stenosis. The importance of MVR was quantified. Other lesion characteristics have a limited impact

TBI lesion segmentation in head CT: impact of preprocessing and data augmentation

Automatic segmentation of lesions in head CT provides keyinformation for patient management, prognosis and disease monitoring.Despite its clinical importance, method development has mostly focusedon multi-parametric MRI. Analysis of the brain in CT is challengingdue to limited soft tissue contrast and its mono-modal nature. We studythe under-explored problem of fine-grained CT segmentation of multiplelesion types (core, blood, oedema) in traumatic brain injury (TBI). Weobserve that preprocessing and data augmentation choices greatly impactthe segmentation accuracy of a neural network, yet these factors arerarely thoroughly assessed in prior work. We design an empirical studythat extensively evaluates the impact of different data preprocessing andaugmentation methods. We show that these choices can have an impactof up to 18% DSC. We conclude that resampling to isotropic resolutionyields improved performance, skull-stripping can be replaced by using theright intensity window, and affine-to-atlas registration is not necessaryif we use sufficient spatial augmentation. Since both skull-stripping andaffine-to-atlas registration are susceptible to failure, we recommend theiralternatives to be used in practice. We believe this is the first work toreport results for fine-grained multi-class segmentation of TBI in CT. Ourfindings may inform further research in this under-explored yet clinicallyimportant task of automatic head CT lesion segmentation