Randomised trial of glutamine, selenium, or both, to supplement parenteral nutrition for critically ill patients

Peer reviewedPublisher PD

Old lessons learned anew: family-based methods for detecting genes responsible for quantitative and qualitative traits in the Genetic Analysis Workshop 17 mini-exome sequence data

Family-based study designs are again becoming popular as new next-generation sequencing technologies make whole-exome and whole-genome sequencing projects economically and temporally feasible. Here we evaluate the statistical properties of linkage analyses and family-based tests of association for the Genetic Analysis Workshop 17 mini-exome sequence data. Based on our results, the linkage methods using relative pairs or nuclear families had low power, with the best results coming from variance components linkage analysis in nuclear families and Elston-Stewart model-based linkage analysis in extended pedigrees. For family-based tests of association, both ASSOC and ROMP performed well for genes with large effects, but ROMP had the advantage of not requiring parental genotypes in the analysis. For the linkage analyses we conclude that genome-wide significance levels appear to control type I error well but that “suggestive” significance levels do not. Methods that make use of the extended pedigrees are well powered to detect major loci segregating in the families even when there is substantial genetic heterogeneity and the trait is mainly polygenic. However, large numbers of such pedigrees will be necessary to detect all major loci. The family-based tests of association found the same major loci as the linkage analyses and detected low-frequency loci with moderate effect sizes, but control of type I error was not as stringent

A central resource for accurate allele frequency estimation from pooled DNA genotyped on DNA microarrays

Analysing pooled DNA on microarrays is an efficient way to genotype hundreds of individuals for thousands of markers for genome-wide association. Although direct comparison of case and control fluorescence scores is possible, correction for differential hybridization of alleles is important, particularly for rare single nucleotide polymorphisms. Such correction relies on heterozygous fluorescence scores and requires the genotyping of hundreds of individuals to obtain sufficient estimates of the correction factor, completely negating any benefit gained by pooling samples. We explore the effect of differential hybridization on test statistics and provide a solution to this problem in the form of a central resource for the accumulation of heterozygous fluorescence scores, allowing accurate allele frequency estimation at no extra cost

Performance of random forests and logic regression methods using mini-exome sequence data

Machine learning approaches are an attractive option for analyzing large-scale data to detect genetic variants that contribute to variation of a quantitative trait, without requiring specific distributional assumptions. We evaluate two machine learning methods, random forests and logic regression, and compare them to standard simple univariate linear regression, using the Genetic Analysis Workshop 17 mini-exome data. We also apply these methods after collapsing multiple rare variants within genes and within gene pathways. Linear regression and the random forest method performed better when rare variants were collapsed based on genes or gene pathways than when each variant was analyzed separately. Logic regression performed better when rare variants were collapsed based on genes rather than on pathways

The screening and management of pituitary dysfunction following traumatic brain injury in adults: British Neurotrauma Group guidance.

Pituitary dysfunction is a recognised, but potentially underdiagnosed complication of traumatic brain injury (TBI). Post-traumatic hypopituitarism (PTHP) can have major consequences for patients physically, psychologically, emotionally and socially, leading to reduced quality of life, depression and poor rehabilitation outcome. However, studies on the incidence of PTHP have yielded highly variable findings. The risk factors and pathophysiology of this condition are also not yet fully understood. There is currently no national consensus for the screening and detection of PTHP in patients with TBI, with practice likely varying significantly between centres. In view of this, a guidance development group consisting of expert clinicians involved in the care of patients with TBI, including neurosurgeons, neurologists, neurointensivists and endocrinologists, was convened to formulate national guidance with the aim of facilitating consistency and uniformity in the care of patients with TBI, and ensuring timely detection or exclusion of PTHP where appropriate. This article summarises the current literature on PTHP, and sets out guidance for the screening and management of pituitary dysfunction in adult patients with TBI. It is hoped that future research will lead to more definitive recommendations in the form of guidelines

Multiple locus VNTR analysis highlights that geographical clustering and distribution of Dichelobacter nodosus, the causal agent of footrot in sheep, correlates with inter-country movements

Dichelobacter nodosus is a Gram-negative, anaerobic bacterium and the causal agent of footrot in sheep. Multiple locus variable number tandem repeat (VNTR) analysis (MLVA) is a portable technique that involves the identification and enumeration of polymorphic tandem repeats across the genome. The aims of this study were to develop an MLVA scheme for D. nodosus suitable for use as a molecular typing tool, and to apply it to a global collection of isolates. Seventy-seven isolates selected from regions with a long history of footrot (GB, Australia) and regions where footrot has recently been reported (India, Scandinavia), were characterised. From an initial 61 potential VNTR regions, four loci were identified as usable and in combination had the attributes required of a typing method for use in bacterial epidemiology: high discriminatory power (D > 0.95), typeability and reproducibility. Results from the analysis indicate that D. nodosus appears to have evolved via recombinational exchanges and clonal diversification. This has resulted in some clonal complexes that contain isolates from multiple countries and continents; and others that contain isolates from a single geographic location (country or region). The distribution of alleles between countries matches historical accounts of sheep movements, suggesting that the MLVA technique is sufficiently specific and sensitive for an epidemiological investigation of the global distribution of D. nodosus

Randomised trial of glutamine and selenium supplemented parenteral nutrition for critically ill patients

Background: Mortality rates in the Intensive Care Unit and subsequent hospital mortality rates in the UK remain high. Infections in Intensive Care are associated with a 2–3 times increased risk of death. It is thought that under conditions of severe metabolic stress glutamine becomes "conditionally essential". Selenium is an essential trace element that has antioxidant and anti-inflammatory properties. Approximately 23% of patients in Intensive Care require parenteral nutrition and glutamine and selenium are either absent or present in low amounts. Both glutamine and selenium have the potential to influence the immune system through independent biochemical pathways. Systematic reviews suggest that supplementing parenteral nutrition in critical illness with glutamine or selenium may reduce infections and mortality. Pilot data has shown that more than 50% of participants developed infections, typically resistant organisms. We are powered to show definitively whether supplementation of PN with either glutamine or selenium is effective at reducing new infections in critically ill patients. Methods/design: 2 × 2 factorial, pragmatic, multicentre, double-blind, randomised controlled trial. The trial has an enrolment target of 500 patients. Inclusion criteria include: expected to be in critical care for at least 48 hours, aged 16 years or over, patients who require parenteral nutrition and are expected to have at least half their daily nutritional requirements given by that route. Allocation is to one of four iso-caloric, iso-nitrogenous groups: glutamine, selenium, both glutamine & selenium or no additional glutamine or selenium. Trial supplementation is given for up to seven days on the Intensive Care Unit and subsequent wards if practicable. The primary outcomes are episodes of infection in the 14 days after starting trial nutrition and mortality. Secondary outcomes include antibiotic usage, length of hospital stay, quality of life and cost-effectiveness. Discussion: To date more than 285 patients have been recruited to the trial from 10 sites in Scotland. Recruitment is due to finish in August 2008 with a further six months follow up. We expect to report the results of the trial in summer 2009. Trial registration: This trial is registered with the International Standard Randomised Controlled Trial Number system. ISRCTN87144826Not peer reviewedPublisher PD

Comparison of results from tests of association in unrelated individuals with uncollapsed and collapsed sequence variants using tiled regression

Tiled regression is an approach designed to determine the set of independent genetic variants that contribute to the variation of a quantitative trait in the presence of many highly correlated variants. In this study, we evaluate the statistical properties of the tiled regression method using the Genetic Analysis Workshop 17 data in unrelated individuals for traits Q1, Q2, and Q4. To increase the power to detect rare variants, we use two methods to collapse rare variants and compare the results with those from the uncollapsed data. In addition, we compare the tiled regression method to traditional tests of association with and without collapsed rare variants. The results show that collapsing rare variants generally improves the power to detect associations regardless of method, although only variants with the largest allelic effects could be detected. However, for traditional simple linear regression, the average estimated type I error is dependent on the trait and varies by about three orders of magnitude. The estimated type I error rate is stable for tiled regression across traits