Joint Statement on Pediatric Education at Schools of Pharmacy

Providing health care for children is a unique specialty, and pediatric patients represent approximately 25% of the population. Education of pharmacy students on patients across the lifespan is required by current Accreditation Council for Pharmacy Education standards and outcomes; thus, it is essential that pharmacy students gain a proficiency in caring for children. A collaborative panel of pediatric faculty members from schools and colleges of pharmacy was established to review the current literature regarding pediatric education in Doctor of Pharmacy curricula and establish updated recommendations for the provision of pediatric pharmacy education. This statement outlines five recommendations supporting inclusion of pediatric content and skills in Doctor of Pharmacy curricula

Analysis of human mini-exome sequencing data from Genetic Analysis Workshop 17 using a Bayesian hierarchical mixture model

Next-generation sequencing technologies are rapidly changing the field of genetic epidemiology and enabling exploration of the full allele frequency spectrum underlying complex diseases. Although sequencing technologies have shifted our focus toward rare genetic variants, statistical methods traditionally used in genetic association studies are inadequate for estimating effects of low minor allele frequency variants. Four our study we use the Genetic Analysis Workshop 17 data from 697 unrelated individuals (genotypes for 24,487 autosomal variants from 3,205 genes). We apply a Bayesian hierarchical mixture model to identify genes associated with a simulated binary phenotype using a transformed genotype design matrix weighted by allele frequencies. A Metropolis Hasting algorithm is used to jointly sample each indicator variable and additive genetic effect pair from its conditional posterior distribution, and remaining parameters are sampled by Gibbs sampling. This method identified 58 genes with a posterior probability greater than 0.8 for being associated with the phenotype. One of these 58 genes, PIK3C2B was correctly identified as being associated with affected status based on the simulation process. This project demonstrates the utility of Bayesian hierarchical mixture models using a transformed genotype matrix to detect genes containing rare and common variants associated with a binary phenotype

Detrimental Effects of Environmental Tobacco Smoke in Relation to Asthma Severity

Background: Environmental tobacco smoke (ETS) has adverse effects on the health of asthmatics, however the harmful consequences of ETS in relation to asthma severity are unknown. Methods: In a multicenter study of severe asthma, we assessed the impact of ETS exposure on morbidity, health care utilization and lung functions; and activity of systemic superoxide dismutase (SOD), a potential oxidative target of ETS that is negatively associated with asthma severity. Findings: From 2002-2006, 654 asthmatics (non-severe 366, severe 288) were enrolled, among whom 109 non-severe and 67 severe asthmatics were routinely exposed to ETS as ascertained by history and validated by urine cotinine levels. ETS-exposure was associated with lower quality of life scores; greater rescue inhaler use; lower lung function; greater bronchodilator responsiveness; and greater risk for emergency room visits, hospitalization and intensive care unit admission. ETS-exposure was associated with lower levels of serum SOD activity, particularly in asthmatic women of African heritage. Interpretation: ETS-exposure of asthmatic individuals is associated with worse lung function, higher acuity of exacerbations, more health care utilization, and greater bronchial hyperreactivity. The association of diminished systemic SOD activity to ETS exposure provides for the first time a specific oxidant mechanism by which ETS may adversely affect patients with asthma. © 2011 Comhair et al

Enterovirus D68 outbreak detection through a syndromic disease epidemiology network

BACKGROUND: In 2014, enterovirus D68 (EV-D68) was responsible for an outbreak of severe respiratory illness in children, with 1,153 EV-D68 cases reported across 49 states. Despite this, there is no commercial assay for its detection in routine clinical care. BioFire® Syndromic Trends (Trend) is an epidemiological network that collects, in near real-time, deidentified. BioFire test results worldwide, including data from the BioFire® Respiratory Panel (RP). OBJECTIVES: Using the RP version 1.7 (which was not explicitly designed to differentiate EV-D68 from other picornaviruses), we formulate a model, Pathogen Extended Resolution (PER), to distinguish EV-D68 from other human rhinoviruses/enteroviruses (RV/EV) tested for in the panel. Using PER in conjunction with Trend, we survey for historical evidence of EVD68 positivity and demonstrate a method for prospective real-time outbreak monitoring within the network. STUDY DESIGN: PER incorporates real-time polymerase chain reaction metrics from the RPRV/EV assays. Six institutions in the United States and Europe contributed to the model creation, providing data from 1,619 samples spanning two years, confirmed by EV-D68 gold-standard molecular methods. We estimate outbreak periods by applying PER to over 600,000 historical Trend RP tests since 2014. Additionally, we used PER as a prospective monitoring tool during the 2018 outbreak. RESULTS: The final PER algorithm demonstrated an overall sensitivity and specificity of 87.1% and 86.1%, respectively, among the gold-standard dataset. During the 2018 outbreak monitoring period, PER alerted the research network of EV-D68 emergence in July. One of the first sites to experience a significant increase, Nationwide Children's Hospital, confirmed the outbreak and implemented EV-D68 testing at the institution in response. Applying PER to the historical Trend dataset to determine rates among RP tests, we find three potential outbreaks with predicted regional EV-D68 rates as high as 37% in 2014, 16% in 2016, and 29% in 2018. CONCLUSIONS: Using PER within the Trend network was shown to both accurately predict outbreaks of EV-D68 and to provide timely notifications of its circulation to participating clinical laboratories

Genome-wide joint SNP and CNV analysis of aortic root diameter in African Americans: the HyperGEN study

<p>Abstract</p> <p>Background</p> <p>Aortic root diameter is a clinically relevant trait due to its known relationship with the pathogenesis of aortic regurgitation and risk for aortic dissection. African Americans are an understudied population despite a particularly high burden of cardiovascular diseases. We report a genome-wide association study on aortic root diameter among African Americans enrolled in the HyperGEN study. We invoked a two-stage, mixed model procedure to jointly identify SNP allele and copy number variation effects.</p> <p>Results</p> <p>Results suggest novel genetic contributors along a large region between the <it>CRCP </it>and <it>KCTD7 </it>genes on chromosome 7 (p = 4.26 × 10^<b>-7</b>); and the <it>SIRPA </it>and <it>PDYN </it>genes on chromosome 20 (p = 3.28 × 10^<b>-8</b>).</p> <p>Conclusions</p> <p>The regions we discovered are candidates for future studies on cardiovascular outcomes, particularly in African Americans. The methods we employed can also provide an outline for genetic researchers interested in jointly testing SNP and CNV effects and/or applying mixed model procedures on a genome-wide scale.</p

Genome-Wide Association Study of Cardiac Structure and Systolic Function in African Americans: The Candidate Gene Association Resource (CARe) Study

Using data from four community-based cohorts of African Americans (AA), we tested the association between genome-wide markers (SNPs) and cardiac phenotypes in the Candidate-gene Association REsource (CARe) study

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury(1-4). These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries(5). Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.Peer reviewe