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An efficient and robust approach to Mendelian randomization with measured pleiotropic effects in a high-dimensional setting.
Valid estimation of a causal effect using instrumental variables requires that all of the instruments are independent of the outcome conditional on the risk factor of interest and any confounders. In Mendelian randomization studies with large numbers of genetic variants used as instruments, it is unlikely that this condition will be met. Any given genetic variant could be associated with a large number of traits, all of which represent potential pathways to the outcome which bypass the risk factor of interest. Such pleiotropy can be accounted for using standard multivariable Mendelian randomization with all possible pleiotropic traits included as covariates. However, the estimator obtained in this way will be inefficient if some of the covariates do not truly sit on pleiotropic pathways to the outcome. We present a method that uses regularization to identify which out of a set of potential covariates need to be accounted for in a Mendelian randomization analysis in order to produce an efficient and robust estimator of a causal effect. The method can be used in the case where individual-level data are not available and the analysis must rely on summary-level data only. It can be used where there are any number of potential pleiotropic covariates up to the number of genetic variants less one. We show the results of simulation studies that demonstrate the performance of the proposed regularization method in realistic settings. We also illustrate the method in an applied example which looks at the causal effect of urate plasma concentration on coronary heart disease
Acute Hepatic Necrosis Caused by Salmonella enterica Serotype I 4,5,12:-:1,2 in a Dog.
Acute hepatic necrosis was diagnosed in a dog. Gram staining and fluorescence in situ hybridization identified Salmonella enterica in the liver, subsequently confirmed as S. enterica serotype I 4,5,12:-:1,2. This is the first report of acute hepatic necrosis with liver failure caused by Salmonella in a dog.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1128/JCM.01256-1
Integration of innovative statistical methods using genetic data provides pharmacological insight and facilitates drug development
The use of genetic data can be of great benefit in drug development. When analysed with appropriate statistical methods, such resources can be leveraged to identify potential drug targets and inform experimental trials [1]. It has been shown that drug development done with the backing of genetic data is more likely to be successful [2]. Increasingly, pharmacological studies are able to harness the results of genome-wide association studies (GWAS), which test for associations between a phenotype and genetic variation across the entire genome. Such studies are rapidly expanding in terms of both size of samples and range of phenotypes [3]. Although GWAS are able to identify many genetic variants that are associated with a phenotypic trait of interest, they are not able to provide, on their own, evidence as to which of these associations are causal, or by which mechanisms these associations come about. New statistical methodology is being developed which uses genetic data to help to answer these questions
Campylobacter jejuni PflB is required for motility and colonisation of the chicken gastrointestinal tract.
Campylobacter jejuni is the leading cause of foodborne bacterial gastroenteritis worldwide. Although the mechanisms by which C. jejuni causes disease are not completely understood, the presence of functional flagella appears to be required for colonisation of the gastrointestinal tract of humans and animals. Therefore much attention has been given to understanding the synthesis and role of flagella in C. jejuni. In this study we report insights into the function of PflB that is essential for Campylobacter motility. We have explored the function of this gene by constructing deletion mutants in C. jejuni strains NCTC11168 and M1, in the genes cj0390 and CJM1_0368, respectively. The mutants were non-motile yet assembled flagella that appeared structurally identical to the wild type. Furthermore the protein is required for C. jejuni colonisation of caeca in a two-week old chicken colonisation model.This work was supported by the Department for Environment, Food and Rural Affairs (Defra) Senior Fellowship awarded to D.J.M.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.micpath.2015.09.01
Gout in a 15-year-old boy with juvenile idiopathic arthritis: A case study
Joint pain is a common complaint in pediatrics and is most often attributed to overuse or injury. In the face of persistent, severe, or recurrent symptoms, the differential typically expands to include bony or structural causes versus rheumatologic conditions. Rarely, a child has two distinct causes for joint pain. In this case, an obese 15-year-old male was diagnosed with gout, a disease common in adults but virtually ignored in the field of pediatrics. The presence of juvenile idiopathic arthritis (JIA) complicated and delayed the consideration of this second diagnosis. Indeed, the absence of gout from this patientโs differential diagnosis resulted in a greater than two-year delay in receiving treatment. The patientsโ BMI was 47.4, and he was also mis-diagnosed with osteochondritis dissecans and underwent medical treatment for JIA, assorted imaging studies, and multiple surgical procedures before the key history of increased pain with red meat ingestion, noticed by the patient, and a subsequent elevated uric acid confirmed his ultimate diagnosis. With the increased prevalence of obesity in the adolescent population, the diagnosis of gout should be an important consideration in the differential diagnosis for an arthritic joint in an overweight patient, regardless of age
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Noise-augmented directional clustering of genetic association data identifies distinct mechanisms underlying obesity.
Funder: NIHR Cambridge Biomedical Research CentreClustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease
Exploring students' perceptions on the use of significant event analysis, as part of a portfolio assessment process in general practice, as a tool for learning how to use reflection in learning
BACKGROUND: Portfolio learning enables students to collect evidence of their learning. Component tasks making up a portfolio can be devised that relate directly to intended learning outcomes. Reflective tasks can stimulate students to recognise their own learning needs. Assessment of portfolios using a rating scale relating to intended learning outcomes offers high content validity. This study evaluated a reflective portfolio used during a final-year attachment in general practice (family medicine). Students were asked to evaluate the portfolio (which used significant event analysis as a basis for reflection) as a learning tool. The validity and reliability of the portfolio as an assessment tool were also measured. METHODS: 81 final-year medical students completed reflective significant event analyses as part of a portfolio created during a three-week attachment (clerkship) in general practice (family medicine). As well as two reflective significant event analyses each portfolio contained an audit and a health needs assessment. Portfolios were marked three times; by the student's GP teacher, the course organiser and by another teacher in the university department of general practice. Inter-rater reliability between pairs of markers was calculated. A questionnaire enabled the students' experience of portfolio learning to be determined. RESULTS: Benefits to learning from reflective learning were limited. Students said that they thought more about the patients they wrote up in significant event analyses but information as to the nature and effect of this was not forthcoming. Moderate inter-rater reliability (Spearman's Rho .65) was found between pairs of departmental raters dealing with larger numbers (20 โ 60) of portfolios. Inter-rater reliability of marking involving GP tutors who only marked 1 โ 3 portfolios was very low. Students rated highly their mentoring relationship with their GP teacher but found the portfolio tasks time-consuming. CONCLUSION: The inter-rater reliability observed in this study should be viewed alongside the high validity afforded by the authenticity of the learning tasks (compared with a sample of a student's learning taken by an exam question). Validity is enhanced by the rating scale which directly connects the grade given with intended learning outcomes. The moderate inter-rater reliability may be increased if a portfolio is completed over a longer period of time and contains more component pieces of work. The questionnaire used in this study only accessed limited information about the effect of reflection on students' learning. Qualitative methods of evaluation would determine the students experience in greater depth. It would be useful to evaluate the effects of reflective learning after students have had more time to get used to this unfamiliar method of learning and to overcome any problems in understanding the task
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