Few well-controlled trials have evaluated the effects that macronutrient composition has on changes in food cravings during weight loss treatment. The present study, which was part of the POUNDS LOST trial, investigated whether the fat and protein content of four different diets affected changes in specific food cravings in overweight and obese adults. A sample of 811 adults were recruited across two clinical sites, and each participant was randomly assigned to one of four macronutrient prescriptions: (1) Low fat (20% of energy), average protein (15% of energy); (2) Moderate fat (40%), average protein (15%); (3) Low fat (20%), high protein (25%); (4) Moderate fat (40%), high protein (25%). With few exceptions, the type of diet that participants were assigned did not differentially affect changes in specific food cravings. Participants assigned to the high fat diets, however, had reduced cravings for carbohydrates at Month12 (p< .05) and fruits and vegetables at Month 24. Also, participants assigned to high protein diets had increased cravings for sweets at Month 6 (p< .05). Participants in all four dietary conditions reported significant reductions in food cravings for specific types of foods (i.e., high fat foods, fast food fats, sweets, and carbohydrates/starches; all ps< .05). Cravings for fruits and vegetables, however, were increased at Month 24 (p< .05). Calorically restricted diets (regardless of their macronutrient composition) yielded significant reductions in cravings for fats, sweets, and starches whereas cravings for fruits and vegetables were increased.
Macronutrient composition; Caloric restriction; Food type; Fat; Carbohydrate; Protein
To determine the relative contributions of triglycerides (TGs) and high-density lipoprotein (HDL) cholesterol in the residual risk of coronary heart disease (CHD) after the reduction of low-density lipoprotein (LDL) cholesterol to guideline-recommended levels, we conducted a hospital-based, case-control study with optimal matching in the strata of LDL cholesterol, gender, ethnicity, and age. The 170 cases and 175 controls were patients at Brigham and Women's Hospital (Boston, Massachusetts) from 2005 to 2008 who had an LDL cholesterol level <130 mg/dl. The cases had incident CHD, and the controls had diagnoses unrelated to CHD. The 170 cases and 175 controls had a mean LDL cholesterol level of 73 and 87 mg/dl, respectively. The association between TG and HDL cholesterol levels and CHD risk was assessed using conditional and unconditional logistic regression analysis. The models investigated accommodated the possibility of an interaction between lipid factors. The odds of CHD increased by approximately 20% per 23-mg/dl increase in TGs and decreased by approximately 40% per 7.5-mg/dl decrease in HDL cholesterol. High TGs and low HDL cholesterol interacted synergistically to increase the odds ratio to 10 for the combined greatest TG (≥190 mg/dl) and lowest HDL cholesterol quintiles (<30 mg/dl). High TG levels were more strongly associated with CHD when the HDL cholesterol was low than average or high; and low HDL cholesterol levels were more strongly associated with CHD when the TGs were high. TGs and HDL cholesterol were associated with CHD in patients with a LDL cholesterol level of ≤70 mg/dl, with a risk similar to, or greater than, those in the total group. In conclusion, high TG and low HDL cholesterol levels contribute strongly and synergistically to CHD when LDL cholesterol is well controlled. Thus, high TGs might have greater importance in patients with optimal rather than greater LDL cholesterol concentrations.
Smoking while pregnant is associated with a myriad of negative health outcomes in the child. Some of the detrimental effects may be due to epigenetic modifications, although few studies have investigated this hypothesis in detail.
To characterize site-specific epigenetic modifications conferred by prenatal smoking exposure within asthmatic children.
Using Illumina HumanMethylation27 microarrays, we estimated the degree of methylation at 27,578 distinct DNA sequences located primarily in gene promoters using whole blood DNA samples from the Childhood Asthma Management Program (CAMP) subset of Asthma BRIDGE childhood asthmatics (n = 527) ages 5–12 with prenatal smoking exposure data available. Using beta-regression, we screened loci for differential methylation related to prenatal smoke exposure, adjusting for gender, age and clinical site, and accounting for multiple comparisons by FDR.
Of 27,578 loci evaluated, 22,131 (80%) passed quality control assessment and were analyzed. Sixty-five children (12%) had a history of prenatal smoke exposure. At an FDR of 0.05, we identified 19 CpG loci significantly associated with prenatal smoke, of which two replicated in two independent populations. Exposure was associated with a 2% increase in mean CpG methylation in FRMD4A (p = 0.01) and Cllorf52 (p = 0.001) compared to no exposure. Four additional genes, XPNPEP1, PPEF2, SMPD3 and CRYGN, were nominally associated in at least one replication group.
These data suggest that prenatal exposure to tobacco smoke is associated with reproducible epigenetic changes that persist well into childhood. However, the biological significance of these altered loci remains unknown.
Kaposi's sarcoma-associated herpesvirus (KSHV) latency-associated nuclear antigen (LANA) is a 1,162-amino-acid protein that mediates the maintenance of episomal viral genomes in latently infected cells. The two central components of episome persistence are DNA replication with each cell division and the segregation of DNA to progeny nuclei. LANA self-associates to bind KSHV terminal-repeat (TR) DNA and to mediate its replication. LANA also simultaneously binds to TR DNA and mitotic chromosomes to mediate the segregation of episomes to daughter nuclei. The N-terminal region of LANA binds histones H2A and H2B to attach to mitotic chromosomes, while the C-terminal region binds TR DNA and also associates with chromosomes. Both the N- and C-terminal regions of LANA are essential for episome persistence. We recently showed that deletion of all internal LANA sequences results in highly deficient episome maintenance. Here we assess independent internal LANA regions for effects on episome persistence. We generated a panel of LANA mutants that included deletions in the large internal repeat region and in the unique internal sequence. All mutants contained the essential N- and C-terminal regions, and as expected, all maintained the ability to associate with mitotic chromosomes in a wild-type fashion and to bind TR DNA, as assessed by electrophoretic mobility shift assays (EMSA). Deletion of the internal regions did not reduce the half-life of LANA. Notably, deletions within either the repeat elements or the unique sequence resulted in deficiencies in DNA replication. However, only the unique internal sequence exerted effects on the ability of LANA to retain green fluorescent protein (GFP) expression from TR-containing episomes deficient in DNA replication, consistent with a role in episome segregation; this region did not independently associate with mitotic chromosomes. All mutants were deficient in episome persistence, and the deficiencies ranged from minor to severe. Mutants deficient in DNA replication that contained deletions within the unique internal sequence had the most-severe deficits. These data suggest that internal LANA regions exert critical roles in LANA-mediated DNA replication, segregation, and episome persistence, likely through interactions with key host cell factors.
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
Although population differences in gene expression have been established, the impact on differential gene expression studies in large populations is not well understood. We describe the effect of self-reported race on a gene expression study of lung function in asthma. We generated gene expression profiles for 254 young adults (205 non-Hispanic whites and 49 African Americans) with asthma on whom concurrent total RNA derived from peripheral blood CD4+ lymphocytes and lung function measurements were obtained. We identified four principal components that explained 62% of the variance in gene expression. The dominant principal component, which explained 29% of the total variance in gene expression, was strongly associated with self-identified race (P<10−16). The impact of these racial differences was observed when we performed differential gene expression analysis of lung function. Using multivariate linear models, we tested whether gene expression was associated with a quantitative measure of lung function: pre-bronchodilator forced expiratory volume in one second (FEV1). Though unadjusted linear models of FEV1 identified several genes strongly correlated with lung function, these correlations were due to racial differences in the distribution of both FEV1 and gene expression, and were no longer statistically significant following adjustment for self-identified race. These results suggest that self-identified race is a critical confounding covariate in epidemiologic studies of gene expression and that, similar to genetic studies, careful consideration of self-identified race in gene expression profiling studies is needed to avoid spurious association.
ancestry; gene expression; population stratification; self-identified race
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
Weight loss reduces energy expenditure, but the contribution of different macronutrients to this change is unclear.
We tested the hypothesis that macronutrient composition of the diet might affect the partitioning of energy expenditure during weight loss.
A sub-study of 99 participants from the POUNDS LOST trial had total energy expenditure (TEE) measured by doubly labeled water and resting energy expenditure (REE) measured by indirect calorimetry at baseline and repeated at 6 months in 89 participants. Participants were randomly assigned to one of 4 diets with either 15% or 25% protein and 20% or 40% fat.
TEE and REE were positively correlated with each other and with fat free mass and body fat, at baseline and 6 months. The average weight loss of 8.1±0.65 kg (LSmean±SE) reduced TEE by 120±56 kcal/d and REE by 136±18 kcal/d. A greater weight loss at 6 months was associated with a greater decrease in TEE and REE. Participants eating the high fat diet lost significantly more fat free mass (1.52±0.55 kg) than the low fat diet group (p<0.05). Participants eating the low fat diet had significantly higher measures of physical activity than the high fat group.
A greater weight loss was associated with a larger decrease in both TEE and REE. The low fat diet was associated with significant changes in fat free body mass and energy expenditure from physical activity compared to the high fat diet.
Bronchodilator response (BDR) is an important asthma phenotype that measures reversibility of airway obstruction by comparing lung function (i.e. FEV1) before and after the administration of a short-acting β2-agonist, the most common rescue medications used for the treatment of asthma. BDR also serves as a test of β2-agonist efficacy. BDR is a complex trait that is partly under genetic control. A genome-wide association study (GWAS) of BDR, quantified as percent change in baseline FEV1 after administration of a β2-agonist, was performed with 1,644 non-Hispanic white asthmatic subjects from six drug clinical trials: CAMP, LOCCS, LODO, a medication trial conducted by Sepracor, CARE, and ACRN. Data for 469,884 single-nucleotide polymorphisms (SNPs) were used to measure the association of SNPs with BDR using a linear regression model, while adjusting for age, sex, and height. Replication of primary P-values was attempted in 501 white subjects from SARP and 550 white subjects from DAG. Experimental evidence supporting the top gene was obtained via siRNA knockdown and Western blotting analyses. The lowest overall combined P-value was 9.7E-07 for SNP rs295137, near the SPATS2L gene. Among subjects in the primary analysis, those with rs295137 TT genotype had a median BDR of 16.0 (IQR = [6.2, 32.4]), while those with CC or TC genotypes had a median BDR of 10.9 (IQR = [5.0, 22.2]). SPATS2L mRNA knockdown resulted in increased β2-adrenergic receptor levels. Our results suggest that SPATS2L may be an important regulator of β2-adrenergic receptor down-regulation and that there is promise in gaining a better understanding of the biological mechanisms of differential response to β2-agonists through GWAS.
Bronchodilator response (BDR) is an important asthma phenotype that measures reversibility of airway obstruction by comparing lung function before and after the administration of short-acting β2-agonists, common medications used for asthma treatment. We performed a genome-wide association study of BDR with 1,644 white asthmatic subjects from six drug clinical trials and attempted to replicate these findings in 1,051 white subjects from two independent cohorts. The most significant associated variant was near the SPATS2L gene. We knocked down SPATS2L mRNA in human airway smooth muscle cells and found that β2-adrenergic receptor levels increased, suggesting that SPATS2L may be a regulator of BDR. Our results highlight the promise of pursuing GWAS results that do not necessarily reach genome-wide significance and are an example of how results from pharmacogenetic GWAS can be studied functionally.
HIV-infected children are treated with tenofovir in combination with other, potentially interacting, antiretroviral agents. We report the pharmacokinetic parameters of tenofovir in combination with efavirenz, darunavir-ritonavir, or atazanavir-ritonavir in HIV-infected children. HIV-infected patients 8 to 18 years of age receiving a tenofovir (300 mg)-based regimen containing efavirenz (300 or 600 mg) once daily (group 1), darunavir (300 or 600 mg)-ritonavir (100 mg) twice daily (group 2), or atazanavir (150 to 400 mg)-ritonavir (100 mg) once daily (group 3) were enrolled. Plasma samples were collected over a 24-h time interval. The 90% confidence intervals (90% CI) of the geometric means for the area under the plasma concentration-time curve (AUC) and the minimum concentration of drug in serum (Cmin) of each antiretroviral were computed and checked for overlap with intervals bracketing published values obtained in adult or pediatric studies demonstrating safety and/or efficacy. Group 1 efavirenz plasma concentrations were observed to be higher in patients receiving fixed-dose combination tablets compared with subjects receiving the individual formulation. In group 2, tenofovir and darunavir exposure was observed to be lower than expected. In group 3, tenofovir and atazanavir administered concomitantly produced exposures similar to those published for adult patients. The 90% CI of AUC and Cmin for tenofovir overlapped the target range for all combinations. Informal comparisons of treatment groups did not indicate any advantage to any combination with respect to tenofovir exposure. Further study of exposures achieved with antiretrovirals administered in combination is warranted.
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.
Recent breakthroughs in next-generation sequencing technologies allow cost-effective methods for measuring a growing list of cellular properties, including DNA sequence and structural variation. Next-generation sequencing has the potential to revolutionize complex trait genetics by directly measuring common and rare genetic variants within a genome-wide context. Because for a given gene both rare and common causal variants can coexist and have independent effects on a trait, strategies that model the effects of both common and rare variants could enhance the power of identifying disease-associated genes. To date, little work has been done on integrating signals from common and rare variants into powerful statistics for finding disease genes in genome-wide association studies. In this analysis of the Genetic Analysis Workshop 17 data, we evaluate various strategies for association of rare, common, or a combination of both rare and common variants on quantitative phenotypes in unrelated individuals. We show that the analysis of common variants only using classical approaches can achieve higher power to detect causal genes than recently proposed rare variant methods and that strategies that combine association signals derived independently in rare and common variants can slightly increase the power compared to strategies that focus on the effect of either the rare variants or the common variants.
Research on the conceptualization of adherence to treatment has not addressed a key question: Is adherence best defined as being a uni-dimensional or multi-dimensional behavioral construct? The primary aim of this study was to test which of these conceptual models best described adherence to a weight management program. This ancillary study was conducted as a part of the POUNDS LOST trial that tested the efficacy of four dietary macro-nutrient compositions for promoting weight loss. A sample of 811 overweight/obese adults was recruited across two clinical sites, and each participant was randomly assigned to one of four macronutrient prescriptions: (1) Low fat (20% of energy), average protein (15% of energy); (2) High fat (40%), average protein (15%); (3) Low fat (20%), high protein (25%); (4) High fat (40%), high protein (25%). Throughout the first 6 months of the study, a computer tracking system collected data on eight indicators of adherence. Computer tracking data from the initial 6 months of the intervention were analyzed using exploratory and confirmatory analyses. Two factors (accounting for 66% of the variance) were identified and confirmed: (1) behavioral adherence and (2) dietary adherence. Behavioral adherence did not differ across the four interventions, but prescription of a high fat diet (vs. a low fat diet) was found to be associated with higher levels of dietary adherence. The findings of this study indicated that adherence to a weight management program was best conceptualized as being multi-dimensional, with two dimensions: behavioral and dietary adherence.
Adherence; Overweight; Obesity; Randomized controlled trial; Lifestyle behavior modification
The primary aim of this study was to test the association of early (first 6 months) adherence related to diet, self-monitoring, and attendance with changes in adiposity and cardiovascular risk factors. This study used data from the 24-month POUNDS LOST trial that tested the efficacy of four dietary macronutrient compositions for short-and long-term weight loss. A computer tracking system was used to record data on eight indicator variables related to adherence. Using canonical correlations at the 6 and 24 month measurement periods, early behavioral adherence was associated with changes in percent weight loss and waist circumference at 6 months (R = 0.52) and 24 months (R = 0.37), but was not associated with cardiovascular disease risk factor levels. Early dietary adherence was associated with changes in insulin at 6 months (R = 0.19), but not at 24 months (R = 0.08, ns). Early dietary adherence was not associated with changes in adiposity.
Obesity; Weight management; Adherence; Computer tracking; Waist circumference; Insulin
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.
The relationships between total serum IgE levels and gene expression patterns in peripheral blood CD4+ T cells (in all subjects and within each sex specifically) are not known.
Peripheral blood CD4+ T cells from 223 participants from the Childhood Asthma Management Program (CAMP) with simultaneous measurement of IgE. Total RNA was isolated, and expression profiles were generated with Illumina HumanRef8 v2 BeadChip arrays. Modeling of the relationship between genome-wide gene transcript levels and IgE levels was performed in all subjects, and stratified by sex.
Among all subjects, significant evidence for association between gene transcript abundance and IgE was identified for a single gene, the interleukin 17 receptor B (IL17RB), explaining 12% of the variance (r2) in IgE measurement (p value = 7 × 10-7, 9 × 10-3 after adjustment for multiple testing). Sex stratified analyses revealed that the correlation between IL17RB and IgE was restricted to males only (r2 = 0.19, p value = 8 × 10-8; test for sex-interaction p < 0.05). Significant correlation between gene transcript abundance and IgE level was not found in females. Additionally we demonstrated substantial sex-specific differences in IgE when considering multi-gene models, and in canonical pathway analyses of IgE level.
Our results indicate that IL17RB may be the only gene expressed in CD4+ T cells whose transcript measurement is correlated with the variation in IgE level in asthmatics. These results provide further evidence sex may play a role in the genomic regulation of IgE.
Rationale: Animal models demonstrate that aberrant gene expression in utero can result in abnormal pulmonary phenotypes.
Objectives: We sought to identify genes that are differentially expressed during in utero airway development and test the hypothesis that variants in these genes influence lung function in patients with asthma.
Methods: Stage 1 (Gene Expression): Differential gene expression analysis across the pseudoglandular (n = 27) and canalicular (n = 9) stages of human lung development was performed using regularized t tests with multiple comparison adjustments. Stage 2 (Genetic Association): Genetic association analyses of lung function (FEV1, FVC, and FEV1/FVC) for variants in five differentially expressed genes were conducted in 403 parent-child trios from the Childhood Asthma Management Program (CAMP). Associations were replicated in 583 parent-child trios from the Genetics of Asthma in Costa Rica study.
Measurements and Main Results: Of the 1,776 differentially expressed genes between the pseudoglandular (gestational age: 7–16 wk) and the canalicular (gestational age: 17–26 wk) stages, we selected 5 genes in the Wnt pathway for association testing. Thirteen single nucleotide polymorphisms in three genes demonstrated association with lung function in CAMP (P < 0.05), and associations for two of these genes were replicated in the Costa Ricans: Wnt1-inducible signaling pathway protein 1 with FEV1 (combined P = 0.0005) and FVC (combined P = 0.0004), and Wnt inhibitory factor 1 with FVC (combined P = 0.003) and FEV1/FVC (combined P = 0.003).
Conclusions: Wnt signaling genes are associated with impaired lung function in two childhood asthma cohorts. Furthermore, gene expression profiling of human fetal lung development can be used to identify genes implicated in the pathogenesis of lung function impairment in individuals with asthma.
asthma; lung development; lung function; genetic variation; gene expression
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.