Influenza Aerosols in UK Hospitals during the H1N1 (2009) Pandemic – The Risk of Aerosol Generation during Medical Procedures

Background

Nosocomial infection of health-care workers (HCWs) during outbreaks of respiratory infections (e.g. Influenza A H1N1 (2009)) is a significant concern for public health policy makers. World Health Organization (WHO)-defined ‘aerosol generating procedures’ (AGPs) are thought to increase the risk of aerosol transmission to HCWs, but there are presently insufficient data to quantify risk accurately or establish a hierarchy of risk-prone procedures.

Methodology/Principal Findings

This study measured the amount of H1N1 (2009) RNA in aerosols in the vicinity of H1N1 positive patients undergoing AGPs to help quantify the potential risk of transmission to HCWs. There were 99 sampling occasions (windows) producing a total of 198 May stages for analysis in the size ranges 0.86–7.3 µm. Considering stages 2 (4–7.3 µm) and 3 (0.86–4 µm) as comprising one sample, viral RNA was detected in 14 (14.1%) air samples from 10 (25.6%) patients. Twenty three air samples were collected while potential AGPs were being performed of which 6 (26.1%) contained viral RNA; in contrast, 76 May samples were collected when no WHO 2009 defined AGP was being performed of which 8 (10.5%) contained viral RNA (unadjusted OR = 2.84 (95% CI 1.11–7.24) adjusted OR = 4.31 (0.83–22.5)).

Conclusions/Significance

With our small sample size we found that AGPs do not significantly increase the probability of sampling an H1N1 (2009) positive aerosol (OR (95% CI) = 4.31 (0.83–22.5). Although the probability of detecting positive H1N1 (2009) positive aerosols when performing various AGPs on intensive care patients above the baseline rate (i.e. in the absence of AGPs) did not reach significance, there was a trend towards hierarchy of AGPs, placing bronchoscopy and respiratory and airway suctioning above baseline (background) values. Further, larger studies are required but these preliminary findings may be of benefit to infection control teams.     

Confirmation of a gene for multiple sclerosis (MS) to chromosome region 19q13.3

To identify the chromosomal localizations of the multiple sclerosis (MS) genes, we conducted a genomewide linkage analysis using eighteen affected families. A MS gene is linked to markers located in the 19q13.3 region (multipoint lod-score = 2.1). Apolipoprotein E (ApoE) gene, located in this region, is an excellent candidate gene for MS because the ApoEe4 allele is acting as a severity allele in the disease.     

IL2RA Genetic Heterogeneity in Multiple Sclerosis and Type 1 Diabetes Susceptibility and Soluble Interleukin-2 Receptor Production

Multiple sclerosis (MS) and type 1 diabetes (T1D) are organ-specific autoimmune disorders with significant heritability, part of which is conferred by shared alleles. For decades, the Human Leukocyte Antigen (HLA) complex was the only known susceptibility locus for both T1D and MS, but loci outside the HLA complex harboring risk alleles have been discovered and fully replicated. A genome-wide association scan for MS risk genes and candidate gene association studies have previously described the IL2RA gene region as a shared autoimmune locus. In order to investigate whether autoimmunity risk at IL2RA was due to distinct or shared alleles, we performed a genetic association study of three IL2RA variants in a DNA collection of up to 9,407 healthy controls, 2,420 MS, and 6,425 T1D subjects as well as 1,303 MS parent/child trios. Here, we report “allelic heterogeneity” at the IL2RA region between MS and T1D. We observe an allele associated with susceptibility to one disease and risk to the other, an allele that confers susceptibility to both diseases, and an allele that may only confer susceptibility to T1D. In addition, we tested the levels of soluble interleukin-2 receptor (sIL-2RA) in the serum from up to 69 healthy control subjects, 285 MS, and 1,317 T1D subjects. We demonstrate that multiple variants independently correlate with sIL-2RA levels.     

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.     

Taking the next step: building an Arabidopsis information portal

The Arabidopsis information portal (AIP), a resource expected to provide access to all community data and combine outputs into a single user-friendly interface, has emerged from community discussions over the last 23 months. These discussions began during two closely linked workshops in early 2010 that established the International Arabidopsis Informatics Consortium (IAIC). The design of the AIP will provide core functionality while remaining flexible to encourage multiple contributors and constant innovation. An IAIC-hosted Design Workshop in December 2011 proposed a structure for the AIP to provide a framework for the minimal components of a functional community portal while retaining flexibility to rapidly extend the resource to other species. We now invite broader participation in the AIP development process so that the resource can be implemented in a timely manner.     

Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions

Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn''s disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions—that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit.edu/mpg/grail/).     

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 October 2009-30 November 2009

This article documents the addition of 411 microsatellite marker loci and 15 pairs of Single Nucleotide Polymorphism (SNP) sequencing primers to the Molecular Ecology Resources Database. Loci were developed for the following species: Acanthopagrus schlegeli, Anopheles lesteri, Aspergillus clavatus, Aspergillus flavus, Aspergillus fumigatus, Aspergillus oryzae, Aspergillus terreus, Branchiostoma japonicum, Branchiostoma belcheri, Colias behrii, Coryphopterus personatus, Cynogolssus semilaevis, Cynoglossus semilaevis, Dendrobium officinale, Dendrobium officinale, Dysoxylum malabaricum, Metrioptera roeselii, Myrmeciza exsul, Ochotona thibetana, Neosartorya fischeri, Nothofagus pumilio, Onychodactylus fischeri, Phoenicopterus roseus, Salvia officinalis L., Scylla paramamosain, Silene latifo, Sula sula, and Vulpes vulpes. These loci were cross-tested on the following species: Aspergillus giganteus, Colias pelidne, Colias interior, Colias meadii, Colias eurytheme, Coryphopterus lipernes, Coryphopterus glaucofrenum, Coryphopterus eidolon, Gnatholepis thompsoni, Elacatinus evelynae, Dendrobium loddigesii Dendrobium devonianum, Dysoxylum binectariferum, Nothofagus antarctica, Nothofagus dombeyii, Nothofagus nervosa, Nothofagus obliqua, Sula nebouxii, and Sula variegata. This article also documents the addition of 39 sequencing primer pairs and 15 allele specific primers or probes for Paralithodes camtschaticus.