Typhoid fever among children, Ghana.

Typhoid fever (TF) remains a problem of concern in many low-income countries. Salmonella enterica serovar Typhi causes ≈22,000,000 symptomatic infections and 220,000 fatalities worldwide annually (1). However, the effect and incidence of TF in many parts of subSaharan Africa are largely unknown because diagnostic laboratories are lacking and fatal TF is frequently attributed to malaria (2,3). In Ghana, TF ranks among the leading 20 causes of outpatient illness, accounting for 0.92% of hospital admissions (4). We conducted our study at the rural Agogo Presbyterian Hospital in the Ashanti Region of Ghana. The percentage of residents of 99 villages and household clusters of buildings (population size 18–13,559 persons, median 277 persons) with access to the study hospital was assessed in a healthcare utilization survey. A proportional-to-size number of children were randomly selected in each village, and a standardized interview was conducted. TF incidences were calculated for September 2007–November 2008 (Table). A bacteriology laboratory with BACTEC 9050 automated blood culture system (Becton Dickinson, Sparks, MD, USA) was established in the study hospital and run to assess the number of admissions with TF, the incidence of TF in the adjoining community and S. enterica ser. Typhi resistance to a panel of antimicrobial drugs

Influenza and Bacterial Coinfections in the 20th Century

To help understand the potential impact of bacterial coinfection during pandemic influenza periods, we undertook a far-reaching review of the existing literature to gain insights into the interaction of influenza and bacterial pathogens. Reports published between 1950 and 2006 were identified from scientific citation databases using standardized search terms. Study outcomes related to coinfection were subjected to a pooled analysis. Coinfection with influenza and bacterial pathogens occurred more frequently in pandemic compared with seasonal influenza periods. The most common bacterial coinfections with influenza virus were due to S. pneumoniae, H. influenzae, Staphylococcus spp., and Streptococcus spp. Of these, S. pneumoniae was the most common cause of bacterial coinfection with influenza and accounted for 40.8% and 16.6% of bacterial coinfections during pandemic and seasonal periods, respectively. These results suggest that bacterial pathogens will play a key role in many countries, as the H1N1(A) influenza pandemic moves forward. Given the role of bacterial coinfections during influenza epidemics and pandemics, the conduct of well-designed field evaluations of public health measures to reduce the burden of these common bacterial pathogens and influenza in at-risk populations is warranted

Influenza and Bacterial Pathogen Coinfections in the 20th Century

To help understand the potential impact of bacterial coinfection during pandemic influenza periods, we undertook a far-reaching review of the existing literature to gain insights into the interaction of influenza and bacterial pathogens. Reports published between 1950 and 2006 were identified from scientific citation databases using standardized search terms. Study outcomes related to coinfection were subjected to a pooled analysis. Coinfection with influenza and bacterial pathogens occurred more frequently in pandemic compared with seasonal influenza periods. The most common bacterial coinfections with influenza virus were due to S. pneumoniae, H. influenzae, Staphylococcus spp., and Streptococcus spp. Of these, S. pneumoniae was the most common cause of bacterial coinfection with influenza and accounted for 40.8% and 16.6% of bacterial coinfections during pandemic and seasonal periods, respectively. These results suggest that bacterial pathogens will play a key role in many countries, as the H1N1(A) influenza pandemic moves forward. Given the role of bacterial coinfections during influenza epidemics and pandemics, the conduct of well-designed field evaluations of public health measures to reduce the burden of these common bacterial pathogens and influenza in at-risk populations is warranted

Acute viral hepatitis morbidity and mortality associated with hepatitis E virus infection: Uzbekistan surveillance data

<p>Abstract</p> <p>Background</p> <p>In Uzbekistan, routine serologic testing has not been available to differentiate etiologies of acute viral hepatitis (AVH). To determine the age groups most affected by hepatitis E virus (HEV) during documented AVH epidemics, trends in AVH-associated mortality rate (MR) per 100,000 over a 15-year period and reported incidence of AVH over a 35-year period were examined.</p> <p>Methods</p> <p>Reported AVH incidence data from 1971 to 2005 and AVH-associated mortality data from 1981 to 1995 were examined. Serologic markers for infection with hepatitis viruses A, B, D, and E were determined from a sample of hospitalized patients with AVH from an epidemic period (1987) and from a sample of pregnant women with AVH from a non-epidemic period (1992).</p> <p>Results</p> <p>Two multi-year AVH outbreaks were identified: one during 1975–1976, and one during 1985–1987. During 1985–1987, AVH-associated MRs were 12.3–17.8 per 100,000 for the general population. Highest AVH-associated MRs occurred among children in the first 3 years of life (40–190 per 100,000) and among women aged 20–29 (15–21 per 100,000). During 1988–1995 when reported AVH morbidity was much lower in the general population, AVH-associated MRs were markedly lower among these same age groups. In 1988, AVH-associated MRs were higher in rural (21 per 100,000) than in urban (8 per 100,000) populations (RR 2.6; 95% CI 1.16–5.93; p < 0.05). Serologic evidence of acute HEV infection was found in 280 of 396 (71%) patients with AVH in 1987 and 12 of 99 (12%) pregnant patients with AVH in 1992.</p> <p>Conclusion</p> <p>In the absence of the availability of confirmatory testing, inferences regarding probable hepatitis epidemic etiologies can sometimes be made using surveillance data, comparing AVH incidence with AVH-associated mortality with an eye to population-based viral hepatitis control measures. Data presented here implicate HEV as the probable etiology of high mortality observed in pregnant women and in children less than 3 years of age in Uzbekistan during 1985–1987. High mortality among pregnant women but not among children less than 3 years has been observed in previous descriptions of epidemic hepatitis E. The high mortality among younger children observed in an AVH outbreak associated with hepatitis E merits corroboration in future outbreaks.</p

Comparative Tuberculosis (TB) Prevention Effectiveness in Children of Bacillus Calmette-Guérin (BCG) Vaccines from Different Sources, Kazakhstan

Except during a 1-year period when BCG vaccine was not routinely administered, annual coverage of infants with Bacillus Calmette-Guérin (BCG) in Kazakhstan since 2002 has exceeded 95%. BCG preparations from different sources (Japan, Serbia, and Russia) or none were used exclusively in comparable 7-month time-frames, September through March, in 4 successive years beginning in 2002. Our objective was to assess relative effectiveness of BCG immunization.Although there were differences in prevention effectiveness observed among the three BCG vaccines, all were protective. The Japanese vaccine (currently used in Kazakhstan), the Serbian vaccine, and the Russian vaccine respectively were 69%, 43%, and 22% effective with respect to clinical TB notifications, and 92%, 82%, and 51% effective with respect to culture confirmed TB. All three vaccines were >70% effective with respect to TB meningitis.Potential limitations included considerations that 1) the methodology used was retrospective, 2) multiple risk factors could have varied between cohorts and affected prevention effectiveness measures, 3) most cases were clinically diagnosed, and TB culture-positive case numbers and TB meningitis case numbers were sparse, and 4) small variations in reported population TB burden could have affected relative risk of exposure for cohorts.All three BCG vaccines evaluated were protective against TB, and prevention effectiveness varied by manufacturer. When setting national immunization policy, consideration should be given to prevention effectiveness of BCG preparations

Three allele combinations associated with Multiple Sclerosis

BACKGROUND: Multiple sclerosis (MS) is an immune-mediated disease of polygenic etiology. Dissection of its genetic background is a complex problem, because of the combinatorial possibilities of gene-gene interactions. As genotyping methods improve throughput, approaches that can explore multigene interactions appropriately should lead to improved understanding of MS. METHODS: 286 unrelated patients with definite MS and 362 unrelated healthy controls of Russian descent were genotyped at polymorphic loci (including SNPs, repeat polymorphisms, and an insertion/deletion) of the DRB1, TNF, LT, TGFβ1, CCR5 and CTLA4 genes and TNFa and TNFb microsatellites. Each allele carriership in patients and controls was compared by Fisher's exact test, and disease-associated combinations of alleles in the data set were sought using a Bayesian Markov chain Monte Carlo-based method recently developed by our group. RESULTS: We identified two previously unknown MS-associated tri-allelic combinations: -509TGFβ1*C, DRB1*18(3), CTLA4*G and -238TNF*B1,-308TNF*A2, CTLA4*G, which perfectly separate MS cases from controls, at least in the present sample. The previously described DRB1*15(2) allele, the microsatellite TNFa9 allele and the biallelic combination CCR5Δ32, DRB1*04 were also reidentified as MS-associated. CONCLUSION: These results represent an independent validation of MS association with DRB1*15(2) and TNFa9 in Russians and are the first to find the interplay of three loci in conferring susceptibility to MS. They demonstrate the efficacy of our approach for the identification of complex-disease-associated combinations of alleles

Inferring causal molecular networks: empirical assessment through a community-based effort.

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution