Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with ...mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.
Access to an electronic medical record is essential for personalized medicine. Currently, only 40% of US physicians have such access, but this is rapidly changing. It is expected that 100,000 ...Americans will have their whole genome sequenced in 2012. The cost of such sequencing is rapidly dropping, and is estimated to be $1000 by 2013. These technological advances will make interpretation of whole genome sequence data a major clinical challenge for the foreseeable future. At present, a relatively small number of genes have been identified to determine drug treatment response phenotypes for asthma. It is anticipated that this will dramatically increase over the next 10 years as personalized medicine becomes more of a reality for asthma patients.
For unclear reasons, obese children with asthma have higher morbidity and reduced response to inhaled corticosteroids.
To assess whether childhood obesity is associated with airway dysanapsis (an ...incongruence between the growth of the lungs and the airways) and whether dysanapsis is associated with asthma morbidity.
We examined the relationship between obesity and dysanapsis in six cohorts of children with and without asthma, as well as the relationship between dysanapsis and clinical outcomes in children with asthma. Adjusted odds ratios (ORs) were calculated for each cohort and in a combined analysis of all cohorts; longitudinal analyses were also performed for cohorts with available data. Hazard ratios (HRs) for clinical outcomes were calculated for children with asthma in the Childhood Asthma Management Program.
Being overweight or obese was associated with dysanapsis in both the cross-sectional (OR, 1.95; 95% confidence interval CI, 1.62-2.35 for overweight/obese compared with normal weight children) and the longitudinal (OR, 4.31; 95% CI, 2.99-6.22 for children who were overweight/obese at all visits compared with normal weight children) analyses. Dysanapsis was associated with greater lung volumes (FVC, vital capacity, and total lung capacity) and lesser flows (FEV
and forced expiratory flow, midexpiratory phase), and with indicators of ventilation inhomogeneity and anisotropic lung and airway growth. Among overweight/obese children with asthma, dysanapsis was associated with severe disease exacerbations (HR, 1.95; 95% CI, 1.38-2.75) and use of systemic steroids (HR, 3.22; 95% CI, 2.02-5.14).
Obesity is associated with airway dysanapsis in children. Dysanapsis is associated with increased morbidity among obese children with asthma and may partly explain their reduced response to inhaled corticosteroids.
Mechanotransduction, the pathway by which mechanical forces are translated to biological signals, plays important but poorly characterized roles in physiology. PIEZOs are recently identified, widely ...expressed, mechanically activated ion channels that are hypothesized to play a role in mechanotransduction in mammals. Here, we describe two distinct PIEZO2 mutations in patients with a subtype of Distal Arthrogryposis Type 5 characterized by generalized autosomal dominant contractures with limited eye movements, restrictive lung disease, and variable absence of cruciate knee ligaments. Electrophysiological studies reveal that the two PIEZO2 mutations affect biophysical properties related to channel inactivation: both E2727del and I802F mutations cause the PIEZO2-dependent, mechanically activated currents to recover faster from inactivation, while E2727del also causes a slowing of inactivation. Both types of changes in kinetics result in increased channel activity in response to a given mechanical stimulus, suggesting that Distal Arthrogryposis Type 5 can be caused by gain-of-function mutations in PIEZO2 . We further show that overexpression of mutated PIEZO2 cDNAs does not cause constitutive activity or toxicity to cells, indicating that the observed phenotype is likely due to a mechanotransduction defect. Our studies identify a type of channelopathy and link the dysfunction of mechanically activated ion channels to developmental malformations and joint contractures.
Intrauterine smoke (IUS) exposure during early childhood has been associated with a number of negative health consequences, including reduced lung function and asthma susceptibility. The biological ...mechanisms underlying these associations have not been established. MicroRNAs regulate the expression of numerous genes involved in lung development. Thus, investigation of the impact of IUS on miRNA expression during human lung development may elucidate the impact of IUS on post-natal respiratory outcomes. We sought to investigate the effect of IUS exposure on miRNA expression during early lung development. We hypothesized that miRNA-mRNA networks are dysregulated by IUS during human lung development and that these miRNAs may be associated with future risk of asthma and allergy. Human fetal lung samples from a prenatal tissue retrieval program were tested for differential miRNA expression with IUS exposure (measured using placental cotinine concentration). RNA was extracted and miRNA-sequencing was performed. We performed differential expression using IUS exposure, with covariate adjustment. We also considered the above model with an additional sex-by-IUS interaction term, allowing IUS effects to differ by male and female samples. Using paired gene expression profiles, we created sex-stratified miRNA-mRNA correlation networks predictive of IUS using DIABLO. We additionally evaluated whether miRNAs were associated with asthma and allergy outcomes in a cohort of childhood asthma. We profiled pseudoglandular lung miRNA in
= 298 samples, 139 (47%) of which had evidence of IUS exposure. Of 515 miRNAs, 25 were significantly associated with intrauterine smoke exposure (q-value < 0.10). The IUS associated miRNAs were correlated with well-known asthma genes (e.g., ORM1-Like Protein 3,
) and enriched in disease-relevant pathways (oxidative stress). Eleven IUS-miRNAs were also correlated with clinical measures (e.g., Immunoglobulin E andlungfunction) in children with asthma, further supporting their likely disease relevance. Lastly, we found substantial differences in IUS effects by sex, finding 95 significant IUS-miRNAs in male samples, but only four miRNAs in female samples. The miRNA-mRNA correlation networks were predictive of IUS (AUC = 0.78 in males and 0.86 in females) and suggested that IUS-miRNAs are involved in regulation of disease-relevant genes (e.g., A disintegrin and metalloproteinase domain 19 (
, LBH regulator of WNT signaling (
) and sex hormone signaling (Coactivator associated methyltransferase 1(
). Our study demonstrated differential expression of miRNAs by IUS during early prenatal human lung development, which may be modified by sex. Based on their gene targets and correlation to clinical asthma and atopy outcomes, these IUS-miRNAs may be relevant for subsequent allergy and asthma risk. Our study provides insight into the impact of IUS in human fetal lung transcriptional networks and on the developmental origins of asthma and allergic disorders.
Background Asthma therapy is typically prescribed and titrated based on patient or parent self-report of symptoms. No longitudinal studies have assessed the relationship between symptoms and severe ...asthma exacerbations in children. The goal of our study was (1) to assess the association of asthma symptoms with severe asthma exacerbations and (2) to compare predictors of persistent asthma symptoms and predictors of severe asthma exacerbations. Methods The Childhood Asthma Management Program was a multicenter clinical trial of 1,041 children randomized to receive budesonide, nedocromil, or placebo (as-needed β-agonist). We conducted a post hoc analysis of diary cards that were completed by subjects on a daily basis to categorize subjects as having persistent vs intermittent symptoms. We defined a severe asthma exacerbation as an episode requiring ≥ 3 days use of oral corticosteroids, hospitalization, or ED visit due to asthma based on self-report at study visits every 4 months. Results While accounting for longitudinal measures, having persistent symptoms from asthma was significantly associated with having severe asthma exacerbations. Predictors of having persistent symptoms compared with intermittent symptoms included not being treated with inhaled corticosteroids, lower FEV1 /FVC ratio, and a lower natural logarithm of provocative concentration of methacholine producing a 20% decline in FEV1 (lnPC20 ). Predictors of having one or more severe asthma exacerbations included younger age, history of hospitalization or ED visit in the prior year, ≥ 3 days use of oral corticosteroids in the prior 3 months, lower FEV1 /FVC ratio, lower lnPC20 , and higher logarithm to the base 10 eosinophil count; treatment with inhaled corticosteroids was predictive of having no severe asthma exacerbations. Conclusions Patients with persistent symptoms from asthma were more likely to experience severe asthma exacerbations. Nevertheless, demographic and laboratory predictors of having persistent symptoms are different from predictors of severe asthma exacerbations. Although symptoms and exacerbations are closely related, their predictors are different. The current focus of the National Asthma Education and Prevention Program guidelines on the two separate domains of asthma control, impairment and risk, are supported by our analysis.
Background Although recent studies have identified the presence of phenotypic clusters in asthmatic patients, the clinical significance and temporal stability of these clusters have not been ...explored. Objective Our aim was to examine the clinical relevance and temporal stability of phenotypic clusters in children with asthma. Methods We applied spectral clustering to clinical data from 1041 children with asthma participating in the Childhood Asthma Management Program. Posttreatment randomization follow-up data collected over 48 months were used to determine the effect of these clusters on pulmonary function and treatment response to inhaled anti-inflammatory medication. Results We found 5 reproducible patient clusters that could be differentiated on the basis of 3 groups of features: atopic burden, degree of airway obstruction, and history of exacerbation. Cluster grouping predicted long-term asthma control, as measured by the need for oral prednisone ( P < .0001) or additional controller medications ( P = .001), as well as longitudinal differences in pulmonary function ( P < .0001). We also found that the 2 clusters with the highest rates of exacerbation had different responses to inhaled corticosteroids when compared with the other clusters. One cluster demonstrated a positive response to both budesonide ( P = .02) and nedocromil ( P = .01) compared with placebo, whereas the other cluster demonstrated minimal responses to both budesonide ( P = .12) and nedocromil ( P = .56) compared with placebo. Conclusion Phenotypic clustering can be used to identify longitudinally consistent and clinically relevant patient subgroups, with implications for targeted therapeutic strategies and clinical trials design.
Recently, long-non-coding RNAs (lncRNAs) have attracted attention because of their emerging role in many important biological mechanisms. The accumulating evidence indicates that the dysregulation of ...lncRNAs is associated with complex diseases. However, only a few lncRNA-disease associations have been experimentally validated and therefore, predicting potential lncRNAs that are associated with diseases become an important task. Current computational approaches often use known lncRNA-disease associations to predict potential lncRNA-disease links. In this work, we exploited the topology of multi-level networks to propose the
ncRNA rank
ng by Netw
rk Diffusio
(LION) approach to identify lncRNA-disease associations. The multi-level complex network consisted of lncRNA-protein, protein-protein interactions, and protein-disease associations. We applied the network diffusion algorithm of LION to predict the lncRNA-disease associations within the multi-level network. LION achieved an AUC value of 96.8% for cardiovascular diseases, 91.9% for cancer, and 90.2% for neurological diseases by using experimentally verified lncRNAs associated with diseases. Furthermore, compared to a similar approach (TPGLDA), LION performed better for cardiovascular diseases and cancer. Given the versatile role played by lncRNAs in different biological mechanisms that are perturbed in diseases, LION's accurate prediction of lncRNA-disease associations helps in ranking lncRNAs that could function as potential biomarkers and potential drug targets.
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