Rationale: Systemic glucocorticoids are used therapeutically to treat a variety of medical conditions. Epigenetic processes such as DNA methylation may reflect exposure to glucocorticoids and may be involved in mediating the responses and side effects associated with these medications.
Objectives: To test the hypothesis that differences in DNA methylation are associated with current systemic steroid use.
Methods: We obtained DNA methylation data at 27,578 CpG sites in 14,475 genes throughout the genome in two large, independent cohorts: the International COPD Genetics Network (ndiscovery = 1,085) and the Boston Early Onset COPD study (nreplication = 369). Sites were tested for association with current systemic steroid use using generalized linear mixed models.
Measurements and Main Results: A total of 511 sites demonstrated significant differential methylation by systemic corticosteroid use in all three of our primary models. Pyrosequencing validation confirmed robust differential methylation at CpG sites annotated to genes such as SLC22A18, LRP3, HIPK3, SCNN1A, FXYD1, IRF7, AZU1, SIT1, GPR97, ABHD16B, and RABGEF1. Functional annotation clustering demonstrated significant enrichment in intrinsic membrane components, hemostasis and coagulation, cellular ion homeostasis, leukocyte and lymphocyte activation and chemotaxis, protein transport, and responses to nutrients.
Conclusions: Our analyses suggest that systemic steroid use is associated with site-specific differential methylation throughout the genome. Differentially methylated CpG sites were found in biologically plausible and previously unsuspected pathways; these genes and pathways may be relevant in the development of novel targeted therapies.
DNA methylation; glucocorticoids; chronic obstructive pulmonary disease
We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.
There are limited data on isoniazid (INH) pharmacokinetics in infants and young children and, therefore, uncertainty on appropriate dosing.
Pharmacokinetic data were obtained from perinatally HIV-exposed South African infants ages 3–24 months receiving INH 10–20 mg/kg/day orally for Mycobacterium tuberculosis (TB) prophylaxis. INH pharmacokinetic parameters were characterized with a population pharmacokinetic approach. Dosing simulations were performed to evaluate weight-based INH doses in children based on N-acetyltransferase 2 enzyme (NAT2) genotype, age, maximum concentrations (Cmax) ≥ 3mg/L, and area under the curve (AUC0-24) ≥ 10.52 mg*hr/L.
In 151 infants (53% female, 48% HIV positive) receiving a mean INH dose of 14.5 mg/kg/day, mean (±SD) Cmax at 3, 6, and 23 months of age were 10.0 (3.5), 8.6 (2.6), and 9.3 (3.8) mg/L, respectively, mean (±SD) AUC0-24 were 53.6 (26.8), 42 (19.9), and 44 (30.7) mg*hr/L, respectively, and mean (±SD) half-life were 2.1 (0.7), 1.9 (0.6), and 1.8 (0.9) hours, respectively. A trimodal apparent oral clearance of INH as a function of NAT2 genotype was apparent as early as 3 months. INH was well tolerated. At an average INH dose of 14.5 mg/kg/day, 99% of infants ages 3–24 months have an INH Cmax ≥ 3 mg/L and 98% have an INH AUC0-24 ≥ 10.52 mg*hr/L.
INH at an average dose of 14.5 mg/kg once daily was well tolerated in infants and achieved INH Cmax values ≥ 3 mg/L and AUC0-24 values ≥ 10.52 mg*hr/L.
isoniazid; pharmacokinetics; dosing; infants; children
The impact of cigarette smoking can persist for extended periods following smoking cessation and may involve epigenetic reprogramming. Changes in DNA methylation associated with smoking may help to identify molecular pathways that contribute to the latency between exposure and disease onset. Cross-sectional cohort data from subjects in the International COPD Genetics Network (n = 1085) and the Boston Early-Onset COPD study (n = 369) were analyzed as the discovery and replication cohorts, respectively. Genome-wide methylation data on 27 578 CpG sites in 14 475 genes were obtained on DNA from peripheral blood leukocytes using the Illumina HumanMethylation27K Beadchip in both cohorts. We identified 15 sites significantly associated with current smoking, 2 sites associated with cumulative smoke exposure, and, within the subset of former smokers, 3 sites associated with time since quitting cigarettes. Two loci, factor II receptor-like 3 (F2RL3) and G-protein-coupled receptor 15 (GPR15), were significantly associated in all three analyses and were validated by pyrosequencing. These findings (i) identify a novel locus (GPR15) associated with cigarette smoking and (ii) suggest the existence of dynamic, site-specific methylation changes in response to smoking which may contribute to the extended risks associated with cigarette smoking that persist after cessation.
Rationale: Chronic obstructive pulmonary disease (COPD) is associated with local (lung) and systemic (blood) inflammation and manifestations. DNA methylation is an important regulator of gene transcription, and global and specific gene methylation marks may vary with cigarette smoke exposure.
Objectives: To perform a comprehensive assessment of methylation marks in DNA from subjects well phenotyped for nonneoplastic lung disease.
Methods: We conducted array-based methylation screens, using a test-replication approach, in two family-based cohorts (n = 1,085 and 369 subjects).
Measurements and Main Results: We observed 349 CpG sites significantly associated with the presence and severity of COPD in both cohorts. Seventy percent of the associated CpG sites were outside of CpG islands, with the majority of CpG sites relatively hypomethylated. Gene ontology analysis based on these 349 CpGs (330 genes) suggested the involvement of a number of genes responsible for immune and inflammatory system pathways, responses to stress and external stimuli, as well as wound healing and coagulation cascades. Interestingly, our observations include significant, replicable associations between SERPINA1 hypomethylation and COPD and lower average lung function phenotypes (combined P values: COPD, 1.5 × 10−23; FEV1/FVC, 1.5 × 10−35; FEV1, 2.2 × 10−40).
Conclusions: Genetic and epigenetic pathways may both contribute to COPD. Many of the top associations between COPD and DNA methylation occur in biologically plausible pathways. This large-scale analysis suggests that DNA methylation may be a biomarker of COPD and may highlight new pathways of COPD pathogenesis.
chronic obstructive pulmonary disease; epigenetics; DNA methylation; smoking
Genome-wide association studies of human gene expression promise to identify functional regulatory genetic variation that contributes to phenotypic diversity. However, it is unclear how useful this approach will be for the identification of disease-susceptibility variants. We generated gene expression profiles for 22 184 mRNA transcripts using RNA derived from peripheral blood CD4+ lymphocytes, and genome-wide genotype data for 516 512 autosomal markers in 200 subjects. We screened for cis-acting variants by testing variants mapping within 50 kb of expressed transcripts for association with transcript abundance using generalized linear models. Significant associations were identified for 1585 genes at a false discovery rate of 0.05 (corresponding to P-values ranging from 1 × 10−91 to 7 × 10−4). Importantly, we identified evidence of regulatory variation for 119 previously mapped disease genes, including 24 examples where the variant with the strongest evidence of disease-association demonstrates strong association with specific transcript abundance. The prevalence of cis-acting variants among disease-associated genes was 63% higher than the genome-wide rate in our data set (P = 6.41 × 10−6), and although many of the implicated loci were associated with immune-related diseases (including asthma, connective tissue disorders and inflammatory bowel disease), associations with genes implicated in non-immune-related diseases including lipid profiles, anthropomorphic measurements, cancer and neurologic disease were also observed. Genetic variants that confer inter-individual differences in gene expression represent an important subset of variants that contribute to disease susceptibility. Population-based integrative genetic approaches can help identify such variation and enhance our understanding of the genetic basis of complex traits.
Little is known about the role of most asthma susceptibility genes during human lung development. Genetic determinants for normal lung development are not only important early in life, but also for later lung function.
To investigate the role of expression patterns of well-defined asthma susceptibility genes during human and murine lung development. We hypothesized that genes influencing normal airways development would be over-represented by genes associated with asthma.
Asthma genes were first identified via comprehensive search of the current literature. Next, we analyzed their expression patterns in the developing human lung during the pseudoglandular (gestational age, 7-16 weeks) and canalicular (17-26 weeks) stages of development, and in the complete developing lung time series of 3 mouse strains: A/J, SW, C57BL6.
In total, 96 genes with association to asthma in at least two human populations were identified in the literature. Overall, there was no significant over-representation of the asthma genes among genes differentially expressed during lung development, although trends were seen in the human (Odds ratio, OR 1.22, confidence interval, CI 0.90-1.62) and C57BL6 mouse (OR 1.41, CI 0.92-2.11) data. However, differential expression of some asthma genes was consistent in both developing human and murine lung, e.g. NOD1, EDN1, CCL5, RORA and HLA-G. Among the asthma genes identified in genome wide association studies, ROBO1, RORA, HLA-DQB1, IL2RB and PDE10A were differentially expressed during human lung development.
Our data provide insight about the role of asthma susceptibility genes during lung development and suggest common mechanisms underlying lung morphogenesis and pathogenesis of respiratory diseases.
Asthma; Development; Expression; Genetics; Lung
Network modeling of whole transcriptome expression data enables characterization of complex epistatic (gene-gene) interactions that underlie cellular functions. Though numerous methods have been proposed and successfully implemented to develop these networks, there are no formal methods for comparing differences in network connectivity patterns as a function of phenotypic trait.
Here we describe a novel approach for quantifying the differences in gene-gene connectivity patterns across disease states based on Graphical Gaussian Models (GGMs). We compare the posterior probabilities of connectivity for each gene pair across two disease states, expressed as a posterior odds-ratio (postOR) for each pair, which can be used to identify network components most relevant to disease status. The method can also be generalized to model differential gene connectivity patterns within previously defined gene sets, gene networks and pathways. We demonstrate that the GGM method reliably detects differences in network connectivity patterns in datasets of varying sample size. Applying this method to two independent breast cancer expression data sets, we identified numerous reproducible differences in network connectivity across histological grades of breast cancer, including several published gene sets and pathways. Most notably, our model identified two gene hubs (MMP12 and CXCL13) that each exhibited differential connectivity to more than 30 transcripts in both datasets. Both genes have been previously implicated in breast cancer pathobiology, but themselves are not differentially expressed by histologic grade in either dataset, and would thus have not been identified using traditional differential gene expression testing approaches. In addition, 16 curated gene sets demonstrated significant differential connectivity in both data sets, including the matrix metalloproteinases, PPAR alpha sequence targets, and the PUFA synthesis pathway.
Our results suggest that GGM can be used to formally evaluate differences in global interactome connectivity across disease states, and can serve as a powerful tool for exploring the molecular events that contribute to disease at a systems level.
Orientations of the seven invertible polysaccharide biosynthesis locus promoters of Bacteroides
fragilis were determined from bacteria grown in vitro, from feces of monoassociated and complex colonized mice, and from B. fragilis-induced murine abscesses. Bacteria grown in vivo have greater variability in orientation of polysaccharide locus promoters than culture-grown organisms.
Rationale: Current understanding of the molecular regulation of lung development is limited and derives mostly from animal studies.
Objectives: To define global patterns of gene expression during human lung development.
Methods: Genome-wide expression profiling was used to measure the developing lung transcriptome in RNA samples derived from 38 normal human lung tissues at 53 to 154 days post conception. Principal component analysis was used to characterize global expression variation and to identify genes and bioontologic attributes contributing to these variations. Individual gene expression patterns were verified by quantitative reverse transcriptase–polymerase chain reaction analysis.
Measurements and Main Results: Gene expression analysis identified attributes not previously associated with lung development, such as chemokine-immunologic processes. Lung characteristics attributes (e.g., surfactant function) were observed at an earlier-than-anticipated age. We defined a 3,223 gene developing lung characteristic subtranscriptome capable of describing a majority of the process. In gene expression space, the samples formed a time-contiguous trajectory with transition points correlating with histological stages and suggesting the existence of novel molecular substages. Induction of surfactant gene expression characterized a pseudoglandular “molecular phase” transition. Individual gene expression patterns were independently validated. We predicted the age of independent human lung transcriptome profiles with a median absolute error of 5 days, supporting the validity of the data and modeling approach.
Conclusions: This study extends our knowledge of key gene expression patterns and bioontologic attributes underlying early human lung developmental processes. The data also suggest the existence of molecular phases of lung development.
microarrays; surfactant; principal component analysis
Cancer cells possess traits reminiscent of those ascribed to normal stem cells. It is unclear, however, whether these phenotypic similarities reflect the activity of common molecular pathways. Here we analyze the enrichment patterns of gene sets associated with embryonic stem (ES) cell identity in the expression profiles of various human tumor types. Strikingly, histologically poorly differentiated tumors display preferential overexpression of genes normally enriched in ES cells, combined with underexpression of Polycomb-regulated genes. Moreover, expression of activation targets of Nanog, Oct4, Sox2 and c-Myc is observed more frequently in poorly differentiated tumors than in well-differentiated tumors. In breast cancers this ES-like signature is associated with high-grade ER-negative tumors, often of the basal-like subtype, and with poor clinical outcome. The ES signature is also present in poorly differentiated glioblastomas and bladder carcinomas. We identify a subset of ES-associated transcription regulators that are preferentially expressed in poorly differentiated tumors. Our results reveal a novel link between genes associated with ES cell identity and the histopathological traits of tumors, and support the possibility that these genes contribute to stem cell-like phenotypes displayed by many tumors.
Summary: Associations between DNA polymorphisms and mRNA abundance are a natural target of genetic investigations, and microarrays facilitate genome-wide and transcriptome-wide surveys of these associations. This work is motivated by emerging requirements for data architectures and algorithm interfaces to allow flexible exploration of public and private archives of genotyping and expression arrays. Using R/Bioconductor facilities, Phase II HapMap genotypes and Illumina 47K expression assay results archived on multiple populations may be interactively explored and analyzed using commodity hardware.
Availability and Implementation: Open Source. Bioconductor 2.3 packages GGtools, GGBase, GGdata, hmyriB36. Freely available on the web at http://www.bioconductor.org
The possible advantage for weight loss of a diet that emphasizes protein, fat, or carbohydrates has not been established, and there are few studies that extend beyond 1 year.
We randomly assigned 811 overweight adults to one of four diets; the targeted percentages of energy derived from fat, protein, and carbohydrates in the four diets were 20, 15, and 65%; 20, 25, and 55%; 40, 15, and 45%; and 40, 25, and 35%. The diets consisted of similar foods and met guidelines for cardiovascular health. The participants were offered group and individual instructional sessions for 2 years. The primary outcome was the change in body weight after 2 years in two-by-two factorial comparisons of low fat versus high fat and average protein versus high protein and in the comparison of highest and lowest carbohydrate content.
At 6 months, participants assigned to each diet had lost an average of 6 kg, which represented 7% of their initial weight; they began to regain weight after 12 months. By 2 years, weight loss remained similar in those who were assigned to a diet with 15% protein and those assigned to a diet with 25% protein (3.0 and 3.6 kg, respectively); in those assigned to a diet with 20% fat and those assigned to a diet with 40% fat (3.3 kg for both groups); and in those assigned to a diet with 65% carbohydrates and those assigned to a diet with 35% carbohydrates (2.9 and 3.4 kg, respectively) (P>0.20 for all comparisons). Among the 80% of participants who completed the trial, the average weight loss was 4 kg; 14 to 15% of the participants had a reduction of at least 10% of their initial body weight. Satiety, hunger, satisfaction with the diet, and attendance at group sessions were similar for all diets; attendance was strongly associated with weight loss (0.2 kg per session attended). The diets improved lipid-related risk factors and fasting insulin levels.
Reduced-calorie diets result in clinically meaningful weight loss regardless of which macronutrients they emphasize.
COPD exacerbations reduce quality of life and increase mortality. Genetic variation may explain the substantial variability seen in exacerbation frequency among COPD subjects with similar lung function. We analyzed whether polymorphisms in five candidate genes previously associated with COPD susceptibility also demonstrate association with COPD exacerbations.
Eighty-eight single nucleotide polymorphisms in microsomal epoxide hydrolase (EPHX1), transforming growth factor beta 1 (TGFB1), SERPINE2, glutathione S-transferase pi (GSTP1), and surfactant protein B (SFTPB) were genotyped in 389 non-Hispanic white participants in the National Emphysema Treatment Trial. Exacerbations were defined as COPD-related emergency room visits or hospitalizations using Centers for Medicare and Medicaid Services claims data.
Measurements and Main Results
216 subjects (56%) experienced one or more exacerbations during the study period. An SFTPB promoter polymorphism, rs3024791, was associated with COPD exacerbations (p=0.008). Logistic regression models confirmed the association with rs3024791 (p = 0.007). Poisson regression models demonstrated association of multiple SFTPB SNPs with exacerbation rates: rs2118177 (p = 0.006), rs2304566 (p = 0.002), rs1130866 (p = 0.04), and rs3024791 (p = 0.002). Polymorphisms in EPHX1, GSTP1, TGFB1, and SERPINE2 did not demonstrate association with COPD exacerbations.
Variants in SFTPB are associated with COPD susceptibility and COPD exacerbation frequency.
association analysis; COPD; exacerbations; genetics; surfactant protein B; single nucleotide polymorphisms
Many pathogens engage host cell surface glycosaminoglycans, but redundancy in pathogen adhesins and host glycosaminoglycan-anchoring proteins (heparan sulfate proteoglycans) has limited the understanding of the importance of glycosaminoglycan binding during infection. The alpha C protein of group B streptococcus, a virulence determinant for this neonatal human pathogen, binds to host glycosaminoglycan and mediates the entry of bacteria into human cells. We studied alpha C protein-glycosaminoglycan binding in Drosophila melanogaster, whose glycosaminoglycan repertoire resembles that of humans but whose genome includes only three characterized membrane heparan sulfate proteoglycan genes. The knockdown of glycosaminoglycan polymerases or of heparan sulfate proteoglycans reduced the cellular binding of alpha C protein. The interruption of alpha C protein-glycosaminoglycan binding was associated with longer host survival and a lower bacterial burden. These data indicate that the glycosaminoglycan-alpha C protein interaction involves multiple heparan sulfate proteoglycans and impairs bacterial killing. Host glycosaminoglycans, anchored by multiple proteoglycans, thereby determine susceptibility to infection. Because there is homology between Drosophila and human glycosaminoglycan/proteoglycan structures and many pathogens express glycosaminoglycan-binding structures, our data suggest that interfering with glycosaminoglycan binding may protect against infections in humans.
Plasma apolipoprotein B (apo B) and VLDL and LDL with apolipoprotein C-III (apo C-III) are independent risk factors for cardiovascular disease (CVD). Dietary intake affects lipoprotein concentration and composition related to those apolipoproteins.
We studied differences in apo B lipoproteins with and without apo C-III after 3 healthy diets based on the Dietary Approaches to Stop Hypertension Trial diet.
Healthy participants (n = 162) were fed each of 3 healthy diets for 6 wk in a crossover design. Diets differed by emphasis of either carbohydrate (Carb), unsaturated fat (Unsat), or protein (Prot). Blood was collected at baseline and after diets for analysis.
Compared with the Carb diet, the Prot diet reduced plasma apo B and triglycerides in VLDL with apo C-III (16%, P = 0.07; 11%, P = 0.05, respectively) and apo B in LDL with apo C-III (16%, P = 0.04). Compared with the Unsat diet, the Prot diet reduced triglycerides in VLDL with apo C-III (16%, P = 0.02). Compared with baseline (subjects' usual diet was higher in saturated fat), the Prot diet reduced apo B in LDL with apo C-III (11%, P = 0.05), and all 3 diets reduced plasma total apo B (6−10%, P < 0.05) and apo B in the major type of LDL, LDL without apo C-III (8 −10%, P < 0.01). All 3 diets reduced the ratio of apo C-III to apo E in VLDL.
Substituting protein for carbohydrate in the context of a healthy dietary pattern reduced atherogenic apo C-III–containing LDL and its precursor, apo C-III–containing VLDL, resulting in the most favorable profile of apo B lipoproteins. In addition, compared with a typical high-saturated fat diet, healthy diets that emphasize carbohydrate, protein, or unsaturated fat reduce plasma total and LDL apo B and produce a lower more metabolically favorable ratio of apo C-III to apo E.
Graphical models (e.g., Bayesian networks) have been used frequently to describe complex interaction patterns and dependent structures among genes and other phenotypes. Estimation of such networks has been a challenging problem when the genes considered greatly outnumber the samples, and the situation is exacerbated when one wishes to consider the impact of polymorphisms (SNPs) in genes.
Here we describe a multistep approach to infer a gene-SNP network from gene expression and genotyped SNP data. Our approach is based on 1) construction of a graphical Gaussian model (GGM) based on small sample estimation of partial correlation and false-discovery rate multiple testing; 2) extraction of a subnetwork of genes directly linked to a target candidate gene of interest; 3) identification of cis-acting regulatory variants for the genes composing the subnetwork; and 4) evaluating the identified cis-acting variants for trans-acting regulatory effects of the target candidate gene. This approach identifies significant gene-gene and gene-SNP associations not solely on the basis of gene co-expression but rather through whole-network modeling. We demonstrate the method by building two complex gene-SNP networks around Interferon Receptor 12B2 (IL12RB2) and Interleukin 1B (IL1B), two biologic candidates in asthma pathogenesis, using 534,290 genotyped variants and gene expression data on 22,177 genes from total RNA derived from peripheral blood CD4+ lymphocytes from 154 asthmatics.
Our results suggest that graphical models based on integrative genomic data are computationally efficient, work well with small samples, and can describe complex interactions among genes and polymorphisms that could not be identified by pair-wise association testing.
Motivation: As the use of microarrays in human studies continues to increase, stringent quality assurance is necessary to ensure accurate experimental interpretation. We present a formal approach for microarray quality assessment that is based on dimension reduction of established measures of signal and noise components of expression followed by parametric multivariate outlier testing.
Results: We applied our approach to several data resources. First, as a negative control, we found that the Affymetrix and Illumina contributions to MAQC data were free from outliers at a nominal outlier flagging rate of α=0.01. Second, we created a tunable framework for artificially corrupting intensity data from the Affymetrix Latin Square spike-in experiment to allow investigation of sensitivity and specificity of quality assurance (QA) criteria. Third, we applied the procedure to 507 Affymetrix microarray GeneChips processed with RNA from human peripheral blood samples. We show that exclusion of arrays by this approach substantially increases inferential power, or the ability to detect differential expression, in large clinical studies.
Availability: http://bioconductor.org/packages/2.3/bioc/html/arrayMvout.html and http://bioconductor.org/packages/2.3/bioc/html/affyContam.html affyContam (credentials: readonly/readonly)
Contact: firstname.lastname@example.org; email@example.com
Analysis of gene expression in the colons of Citrobacter rodentium-infected susceptible and resistant mice suggests that mortality is associated with impaired intestinal ion transport.
Comparative characterization of genome-wide transcriptional changes during infection can help elucidate the mechanisms underlying host susceptibility. In this study, transcriptional profiling of the mouse colon was carried out in two cognate lines of mice that differ in their response to Citrobacter rodentium infection; susceptible inbred FVB/N and resistant outbred Swiss Webster mice. Gene expression in the distal colon was determined prior to infection, and at four and nine days post-inoculation using a whole mouse genome Affymetrix array.
Computational analysis identified 462 probe sets more than 2-fold differentially expressed between uninoculated resistant and susceptible mice. In response to C. rodentium infection, 5,123 probe sets were differentially expressed in one or both lines of mice. Microarray data were validated by quantitative real-time RT-PCR for 35 selected genes and were found to have a 94% concordance rate. Transcripts represented by 1,547 probe sets were differentially expressed between susceptible and resistant mice regardless of infection status, a host effect. Genes associated with transport were over-represented to a greater extent than even immune response-related genes. Electrolyte analysis revealed reduction in serum levels of chloride and sodium in susceptible animals.
The results support the hypothesis that mortality in C. rodentium-infected susceptible mice is associated with impaired intestinal ion transport and development of fatal fluid loss and dehydration. These studies contribute to our understanding of the pathogenesis of C. rodentium and suggest novel strategies for the prevention and treatment of diarrhea associated with intestinal bacterial infections.
To assess the practice-level effects of (1) a physician peer leader intervention and (2) peer leaders in combination with the introduction of asthma education nurses to facilitate care improvement. And, to compare findings with previously reported patient-level outcomes of trial enrollees.
Data were included on children 5–17 years old with asthma in 40 primary care practices, affiliated with managed health care plans enrolled in the Pediatric Asthma Care Patient Outcomes Research Team (PORT) randomized trial.
Primary care practices were randomly assigned to one of two care improvement arms or to usual care. Automated claims data were analyzed for 12-month periods using a repeated cross-sectional design. The primary outcome was evidence of at least one controller medication dispensed among patients with persistent asthma. Secondary outcomes included controller dispensing among all identified asthmatics, evidence of chronic controller use, and the dispensing of oral steroids. Health service utilization outcomes included numbers of ambulatory visits and hospital-based events.
The proportion of children with persistent asthma prescribed controllers increased in all study arms. No effect of the interventions on the proportion receiving controllers was detected (peer leader intervention effect 0.01, 95 percent confidence interval [CI]: −0.07, 0.08; planned care intervention effect −0.03, 95 percent CI: −0.09, 0.02). A statistical trend was seen toward an increased number of oral corticosteroid bursts dispensed in intervention practices. Significant adjusted increases in ambulatory visits of 0.08–0.10 visits per child per year were seen in the first intervention year, but only a statistical trend in these outcomes persisted into the second year of follow-up. No differences in hospital-based events were detected.
This analysis showed a slight increase in ambulatory asthma visits as a result of asthma care improvement interventions, using automated data. The absence of detectable impact on medication use at the practice level differs from the positive intervention effect observed in patient self-reported data from trial enrollees. Analysis of automated data on nonenrollees adds information about practice-level impact of care improvement strategies. Benefits of practice-level interventions may accrue disproportionately to the subgroup of trial enrollees. The effect of such interventions may be less apparent at the level of practices or health plans.
Asthma care; randomized controlled trial; chronic care model; physician behavior change
Graph theoretical concepts are useful for the description and analysis of interactions and relationships in biological systems. We give a brief introduction into some of the concepts and their areas of application in molecular biology. We discuss software that is available through the Bioconductor project and present a simple example application to the integration of a protein-protein interaction and a co-expression network.
Group A streptococci (GAS) produce several exoproteins that are thought to contribute to the pathogenesis of human infection. Two such proteins, streptolysin O (SLO) and NAD+-glycohydrolase (NADase), have been shown to interact functionally as a compound signaling toxin. When GAS are bound to the surface of epithelial cells in vitro, SLO forms pores in the cell membrane and delivers NADase to the epithelial cell cytoplasm. In vitro, intoxication of keratinocytes with NADase is associated with cytotoxic effects and induction of apoptosis; however, the importance of NADase during infection of an animal host has not been established. We employed isogenic GAS mutants to assess the contribution of NADase activity to GAS virulence in vivo using mouse models of invasive soft-tissue infection and septicemia. In both models, mutant GAS that lacked NADase activity were significantly attenuated for virulence compared with the isogenic wild-type parent, confirming an important role for NADase in the infection of a host animal. A double mutant lacking SLO and NADase activity had an intermediate virulence phenotype, consistent with the hypothesis that SLO evokes a protective innate immune response. We conclude that NADase and SLO together enhance GAS virulence in vivo.
Our objective was to develop data-based algorithms for definition of immunologic response to AIDS therapies in pediatric patients, taking account of T-cell subset measurement errors. The study design involved cross-protocol analysis of 2,148 enrollees in six completed Pediatric AIDS Clinical Trials Group trials. We used standard quantitation of T-cell subsets; linear modeling with mean-dependent measurement error variance was used to develop 95% tolerance limits for change in CD4%. For individuals with a CD4% of approximately 25%, the measurement error-based 95% tolerance interval ranges from 15% to 35%, whereas for individuals with a CD4% of approximately 5%, the tolerance interval ranges from 3% to 7%. When pairs of CD4% measures taken within a time interval of less than 30 days are averaged to estimate steady-state CD4%, tolerance interval width decreases by approximately 30%. A simple graphical tool that provides a data-based criterion for immunologic response over and above variation ascribable to T-cell measurement error is provided. Variability in CD4% due to measurement error is substantial, increases with level of CD4%, and complicates assessment of immunologic response to therapy. Replicates of CD4% measures could be used to improve precision of interpretation of CD4% measures.