Mark Beasley

Hyperammonemia following intravenous valproate loading

BACKGROUND Valproic acid (VPA) has been associated with hyperammonemia with and without encephalopathy. We report the frequent but transient nature of hyperammonemia following intravenous (IV) administration of loading doses of VPA. METHODS Forty participants received a VPA loading dose (20 or 30 mg/kg) at 6 or 10mg/kg/min. All participants were monitored for signs of systemic and local intolerance. Serum VPA level, ammonia, complete blood count, bilirubin, transaminases, pancreatic enzymes, and level of consciousness were obtained at baseline, 1 and 24h after administration. Changes in ammonia levels were assessed using repeated-measures ANOVA. RESULTS Asymptomatic hyperammonemia occurred in 30 of 40 participants at 1h post-VPA infusion. Majority of the participants (66%) demonstrated decreasing ammonia concentrations at 24h post-infusion. Multivariable repeated-measures analysis indicates the lack of influence of VPA dose (p=0.8), VPA levels (p>0.24, all time points), infusion rate (p=0.41) and gender (0.68) on ammonia levels across time. Age (p=0.015), time since dosing (p=0.017) and co-therapy with enzyme-inducing antiepileptic drugs (p=0.035) were significant predictors of changes in ammonia levels. CONCLUSIONS Hyperammonemia is a frequent but transient finding following intravenous administration of loading doses of VPA. Hyperammonemia was not associated with alteration in consciousness or hepatic transaminases.

Is funding source related to study reporting quality in obesity or nutrition randomized control trials in top-tier medical journals

Background:Faithful and complete reporting of trial results is essential to the validity of the scientific literature. An earlier systematic study of randomized controlled trials (RCTs) found that industry-funded RCTs appeared to be reported with greater quality than non-industry-funded RCTs. The aim of this study was to examine the association between systematic differences in reporting quality and funding status (that is, industry funding vs non-industry funding) among recent obesity and nutrition RCTs published in top-tier medical journals.Methods:Thirty-eight obesity or nutrition intervention RCT articles were selected from high-profile, general medical journals (The Lancet, Annals of Internal Medicine, JAMA and the British Medical Journal) published between 2000 and 2007. Paired papers were selected from the same journal published in the same year, one with and the other without industry funding. The following identifying information was redacted: journal, title, authors, funding source and institution(s). Then three raters independently and blindly rated each paper according to the Chalmers method, and total reporting quality scores were calculated.Findings:The inter-rater reliability (Cronbachs alpha) was 0.82 (95% confidence interval=0.80–0.84). The total mean (M) and s.d. of Chalmers Index quality score (out of a possible 100) for industry-funded studies were M=84.5, s.d.=7.04 and for non-industry-funded studies they were M=79.4, s.d.=13.00. A Wilcoxon matched-pairs signed-ranks test indicates no significant rank difference in the distributions of total quality scores between funding sources, Z=−0.966, P=0.334 (two tailed).Interpretation:Recently published RCTs on nutrition and obesity that appear in top-tier journals seem to be equivalent in quality of reporting, regardless of funding source. This may be a result of recent reporting of quality statements and efforts of journal editors to raise all papers to a common standard.

Method and computer program for controlling the family‐wise alpha rate in gene association studies involving multiple phenotypes

Multiple significance testing involving multiple phenotypes is not uncommon in the context of gene association studies but has remained largely unaddressed. If no adjustment is made for the multiple tests conducted, the type I error probability will exceed the nominal (per test) alpha level. Nevertheless, many investigators do not implement such adjustments. This may, in part, be because most available methods for adjusting the alpha rate either: 1) do not take the correlation structure among the variables into account and, therefore, tend to be overly stringent; or 2) do not allow statements to be made about specific variables but only about multivariate composites of variables. In this paper we develop a simulation‐based method and computer program that holds the actual alpha rate to the nominal alpha rate but takes the correlation structure into account. We show that this method is more powerful than several common alternative approaches and that this power advantage increases as the number of variables and their intercorrelations increase. The method appears robust to marked non‐normality and variance heterogeneity even with unequal numbers of subjects in each group. The fact that gene association studies with biallelic loci will have (at most) three groups (i.e., AA, Aa, aa) implies by the closure principle that, after detection of a significant result for a specific variable, pairwise comparisons for that variable can be conducted without further adjustment of the alpha level. Genet. Epidemiol. 15:87–101,1998.

The Role of European Genetic Admixture in the Etiology of the Insulin Resistance Syndrome in Children: Are the Effects Mediated by Fat Accumulation?

OBJECTIVES To evaluate the contribution of European genetic admixture (EUADM) to insulin resistance syndrome (IRS) in a multiethnic sample of children age 7-12 years, and to explore whether body fat affects this relationship. STUDY DESIGN Anthropometric measurements and blood pressure were assessed in 243 children. After an overnight fast, an intravenous glucose tolerance test was conducted, and measures of fasting insulin/glucose, lipids, insulin sensitivity (SI), and acute insulin response to glucose (AIRg) were obtained. The proportion of EUADM was determined by maximum likelihood estimation using 140 ancestry informative markers. Subjects were stratified into tertiles according to the proportion of EUADM for analyses. Subjects were categorized as lean or obese using body fat percentage cutpoints (25% in boys, 30% in girls). RESULTS Among lean subjects (72%), the tertile representing the greatest proportion of EUADM was associated with higher SI (P<.001) and serum glucose (P<.05) and lower insulin (P<.05), AIRg (P<.001), high-density lipoprotein cholesterol (P=.05), and blood pressure (P<.05). However, among obese subjects, EUADM was associated only with SI (P<.05). CONCLUSIONS Our results suggest that population differences in IRS likely have a genetic component, but that the influence of genetic background may be masked by obesity.

An adaptive alpha spending algorithm improves the power of statistical inference in microarray data analysis.

The adaptive alpha-spending algorithm incorporates additional contextual evidence (including correlations among genes) about differential expression to adjust the initial p-values to yield the alpha-spending adjusted p-values. The alpha-spending algorithm is named so because of its similarity with the alpha-spending algorithm in interim analysis of clinical trials in which stage-specific significance levels are assigned to each stage of the clinical trial. We show that the Bonferroni correction applied to the alpha-spending adjusted p-values approximately controls the Family Wise Error Rate under the complete null hypothesis. Using simulations we also show that the use of the alpha spending algorithm yields increased power over the unadjusted p-values while controlling FDR. We found the greater benefits of the alpha spending algorithm with increasing sample sizes and correlation among genes. The use of the alpha spending algorithm will result in microarray experiments that make more efficient use of their data and may help conserve resources.

An Empirical Bayes Method for Updating Inferences in Analysis of Quantitative Trait Loci Using Information From Related Genome Scans

Individual genome scans for quantitative trait loci (QTL) mapping often suffer from low statistical power and imprecise estimates of QTL location and effect. This lack of precision yields large confidence intervals for QTL location, which are problematic for subsequent fine mapping and positional cloning. In prioritizing areas for follow-up after an initial genome scan and in evaluating the credibility of apparent linkage signals, investigators typically examine the results of other genome scans of the same phenotype and informally update their beliefs about which linkage signals in their scan most merit confidence and follow-up via a subjective–intuitive integration approach. A method that acknowledges the wisdom of this general paradigm but formally borrows information from other scans to increase confidence in objectivity would be a benefit. We developed an empirical Bayes analytic method to integrate information from multiple genome scans. The linkage statistic obtained from a single genome scan study is updated by incorporating statistics from other genome scans as prior information. This technique does not require that all studies have an identical marker map or a common estimated QTL effect. The updated linkage statistic can then be used for the estimation of QTL location and effect. We evaluate the performance of our method by using extensive simulations based on actual marker spacing and allele frequencies from available data. Results indicate that the empirical Bayes method can account for between-study heterogeneity, estimate the QTL location and effect more precisely, and provide narrower confidence intervals than results from any single individual study. We also compared the empirical Bayes method with a method originally developed for meta-analysis (a closely related but distinct purpose). In the face of marked heterogeneity among studies, the empirical Bayes method outperforms the comparator.