Utah Pandemic Influenza Response Plan

An influenza pandemic has the potential to cause widespread illness and death. Planning and preparedness before the next pandemic strikes are critical for an effective response. Utah’s Pandemic Influenza Response Plan describes a coordinated strategy to prepare for and respond to an influenza pandemic. Influenza causes seasonal worldwide epidemics of disease that result in an average of 36,000 deaths each year in the United States. A pandemic – or global epidemic – occurs when there is a major change in the influenza virus so that most or all people in the world’s population have no immunity against the virus. Three pandemics occurred during the 20th century; the most severe pandemic (1918) caused over 500,000 deaths in the U.S. and 20-100 million deaths worldwide. Recent outbreaks of human disease caused by avian influenza strains in Asia and Europe have highlighted the potential of new strains to be introduced into the population. An avian influenza (H5N1) virus capable of directly infecting humans was first detected in Hong Kong in 1997. That virus strain has been circulating widely in several Asian countries since 2003. Avian influenza H5N1 has caused 122 human cases and 62 deaths (WHO as of October 24, 2005) and has become enzootic in wild migratory birds. If these strains acquire the ability to be transmitted effectively from person to person a pandemic may occur. Regardless of whether the currently circulating avian influenza (H5N1) strains evolve so as to cause a pandemic or not, history indicates that we will experience another pandemic of influenza sooner or later. Characteristics of an influenza pandemic that must be considered in preparedness and response planning include: 1) simultaneous impacts in communities across the state and the U.S., limiting the ability of any jurisdiction to provide support and assistance to other areas; 2) an overwhelming burden of ill persons requiring hospitalization or outpatient medical care; 3) shortages and delays in the availability of vaccines and antiviral medications; 4) disruption of national and community infrastructures including health care, transportation, commerce, utilities and public safety; and 5) global spread of infection with outbreaks throughout the world. The Utah Department of Health is preparing to effectively respond to the issues mentioned above. This progress has been accomplished through programs specific for influenza as well as programs focused on increasing preparedness for bioterrorism and emerging infectious disease threats. In addition, resources have been allocated to improve statewide influenza surveillance, increase influenza testing capacity at the Utah Public Health Laboratory, assess the need for and potential uses of an antiviral drug stockpile, develop means to deliver vaccine against the pandemic influenza strain once it becomes available, and improve health care system readiness at the community level

Spinach-associated Escherichia coli O157:H7 Outbreak, Utah and New Mexico, 2006

In 2006, Utah and New Mexico health departments investigated a multistate cluster of Escherichia coli O157:H7. A case–control study of 22 case-patients found that consuming bagged spinach was significantly associated with illness (p<0.01). The outbreak strain was isolated from 3 bags of 1 brand of spinach. Nationally, 205 persons were ill with the outbreak strain

HFE Gene Variants Modify the Association between Maternal Lead Burden and Infant Birthweight: A Prospective Birth Cohort Study in Mexico City, Mexico

<p>Abstract</p> <p>Background</p> <p>Neonatal growth is a complex process involving genetic and environmental factors. Polymorphisms in the hemochromatosis (<it>HFE</it>) iron regulatory genes have been shown to modify transport and toxicity of lead which is known to affect birth weight.</p> <p>Methods</p> <p>We investigated the role of <it>HFE C282Y</it>, <it>HFE H63 D</it>, and transferrin <it>(TF) P570 S </it>gene variants in modifying the association of lead and infant birthweight in a cohort of Mexican mother-infant pairs. Subjects were initially recruited between 1994-1995 from three maternity hospitals in Mexico City and 411 infants/565 mothers had archived blood available for genotyping. Multiple linear regression models, stratified by either maternal/infant <it>HFE </it>or <it>TF </it>genotype and then combined with interaction terms, were constructed examining the association of lead and birthweight after controlling for covariates.</p> <p>Results</p> <p>3.1%, 16.8% and 17.5% of infants (N = 390) and 1.9%, 14.5% and 18.9% of mothers (N = 533) carried the <it>HFE C282Y</it>, <it>HFE H63D</it>, and <it>TF P570 S </it>variants, respectively. The presence of infant <it>HFE H63 D </it>variants predicted 110.3 g (95% CI -216.1, -4.6) decreases in birthweight while maternal <it>HFE H63 D </it>variants predicted reductions of 52.0 g (95% CI -147.3 to 43.2). Interaction models suggest that both maternal and infant <it>HFE H63 D </it>genotype may modify tibia lead's effect on infant birthweight in opposing ways. In our interaction models, maternal <it>HFE H63 D </it>variant carriers had a negative association between tibia lead and birthweight.</p> <p>Conclusions</p> <p>These results suggest that the <it>HFE H63 D </it>genotype modifies lead's effects on infant birthweight in a complex fashion that may reflect maternal-fetal interactions with respect to the metabolism and transport of metals.</p

SREBP Coordinates Iron and Ergosterol Homeostasis to Mediate Triazole Drug and Hypoxia Responses in the Human Fungal Pathogen Aspergillus fumigatus

Sterol regulatory element binding proteins (SREBPs) are a class of basic helix-loop-helix transcription factors that regulate diverse cellular responses in eukaryotes. Adding to the recognized importance of SREBPs in human health, SREBPs in the human fungal pathogens Cryptococcus neoformans and Aspergillus fumigatus are required for fungal virulence and susceptibility to triazole antifungal drugs. To date, the exact mechanism(s) behind the role of SREBP in these observed phenotypes is not clear. Here, we report that A. fumigatus SREBP, SrbA, mediates regulation of iron acquisition in response to hypoxia and low iron conditions. To further define SrbA's role in iron acquisition in relation to previously studied fungal regulators of iron metabolism, SreA and HapX, a series of mutants were generated in the ΔsrbA background. These data suggest that SrbA is activated independently of SreA and HapX in response to iron limitation, but that HapX mRNA induction is partially dependent on SrbA. Intriguingly, exogenous addition of high iron or genetic deletion of sreA in the ΔsrbA background was able to partially rescue the hypoxia growth, triazole drug susceptibility, and decrease in ergosterol content phenotypes of ΔsrbA. Thus, we conclude that the fungal SREBP, SrbA, is critical for coordinating genes involved in iron acquisition and ergosterol biosynthesis under hypoxia and low iron conditions found at sites of human fungal infections. These results support a role for SREBP–mediated iron regulation in fungal virulence, and they lay a foundation for further exploration of SREBP's role in iron homeostasis in other eukaryotes

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Modeling the variations in pediatric respiratory syncytial virus seasonal epidemics

Abstract Background Seasonal respiratory syncytial virus (RSV) epidemics occur annually in temperate climates and result in significant pediatric morbidity and increased health care costs. Although RSV epidemics generally occur between October and April, the size and timing vary across epidemic seasons and are difficult to predict accurately. Prediction of epidemic characteristics would support management of resources and treatment. Methods The goals of this research were to examine the empirical relationships among early exponential growth rate, total epidemic size, and timing, and the utility of specific parameters in compartmental models of transmission in accounting for variation among seasonal RSV epidemic curves. RSV testing data from Primary Children's Medical Center were collected on children under two years of age (July 2001-June 2008). Simple linear regression was used explore the relationship between three epidemic characteristics (final epidemic size, days to peak, and epidemic length) and exponential growth calculated from four weeks of daily case data. A compartmental model of transmission was fit to the data and parameter estimated used to help describe the variation among seasonal RSV epidemic curves. Results The regression results indicated that exponential growth was correlated to epidemic characteristics. The transmission modeling results indicated that start time for the epidemic and the transmission parameter co-varied with the epidemic season. Conclusions The conclusions were that exponential growth was somewhat empirically related to seasonal epidemic characteristics and that variation in epidemic start date as well as the transmission parameter over epidemic years could explain variation in seasonal epidemic size. These relationships are useful for public health, health care providers, and infectious disease researchers.</p

A Hybrid Spectral Library and Protein Sequence Database Search Strategy for Bottom-Up and Top-Down Proteomic Data Analysis

Tandem mass spectrometry (MS/MS) is widely employed for the analysis of complex proteomic samples. While protein sequence database searching and spectral library searching are both well-established peptide identification methods, each has shortcomings. Protein sequence databases lack fragment peak intensity information, which can result in poor discrimination between correct and incorrect spectrum assignments. Spectral libraries usually contain fewer peptides than protein sequence databases, which limits the number of peptides that can be identified. Notably, few post-translationally modified peptides are represented in spectral libraries. This is because few search engines can both identify a broad spectrum of PTMs and create corresponding spectral libraries. Also, programs that generate spectral libraries using deep learning approaches are not yet able to accurately predict spectra for the vast majority of PTMs. Here, we address these limitations through use of a hybrid search strategy that combines protein sequence database and spectral library searches to improve identification success rates and sensitivity. This software uses Global PTM Discovery (G-PTM-D) to produce spectral libraries for a wide variety of different PTMs. These features, along with a new spectrum annotation and visualization tool, have been integrated into the freely available and open-source search engine MetaMorpheus