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1.  The impact of genetic variation and cigarette smoke on DNA methylation in current and former smokers from the COPDGene study 
Epigenetics  2015;10(11):1064-1073.
DNA methylation can be affected by systemic exposures, such as cigarette smoking and genetic sequence variation; however, the relative impact of each on the epigenome is unknown. We aimed to assess if cigarette smoking and genetic variation are associated with overlapping or distinct sets of DNA methylation marks and pathways. We selected 85 Caucasian current and former smokers with genome-wide single nucleotide polymorphism (SNP) genotyping available from the COPDGene study.  Genome-wide methylation was obtained on DNA from whole blood using the Illumina HumanMethylation27 platform. To determine the impact of local sequence variation on DNA methylation (mQTL), we examined the association between methylation and SNPs within 50 kb of each CpG site.  To examine the impact of cigarette smoking on DNA methylation, we examined the differences in methylation by current cigarette smoking status. We detected 770 CpG sites annotated to 708 genes associated at an FDR < 0.05 in the cis-mQTL analysis and 1,287 CpG sites annotated to 1,242 genes, which were nominally associated in the smoking-CpG association analysis (Punadjusted < 0.05). Forty-three CpG sites annotated to 40 genes were associated with both SNP variation and current smoking; this overlap was not greater than that expected by chance. Our results suggest that cigarette smoking and genetic variants impact distinct sets of DNA methylation marks, the further elucidation of which may partially explain the variable susceptibility to the health effects of cigarette smoking. Ascertaining how genetic variation and systemic exposures differentially impact the human epigenome has relevance for both biomarker identification and therapeutic target development for smoking-related diseases.
doi:10.1080/15592294.2015.1106672
PMCID: PMC4844199  PMID: 26646902
cis-mQTL; CpG site; epigenetics; environmental factor; genetic variant
2.  Differential DNA methylation marks and gene comethylation of COPD in African-Americans with COPD exacerbations 
Respiratory Research  2016;17:143.
Background
Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide. Identifying COPD-associated DNA methylation marks in African-Americans may contribute to our understanding of racial disparities in COPD susceptibility. We determined differentially methylated genes and co-methylation network modules associated with COPD in African-Americans recruited during exacerbations of COPD and smoking controls from the Pennsylvania Study of Chronic Obstructive Pulmonary Exacerbations (PA-SCOPE) cohort.
Methods
We assessed DNA methylation from whole blood samples in 362 African-American smokers in the PA-SCOPE cohort using the Illumina Infinium HumanMethylation27 BeadChip Array. Final analysis included 19302 CpG probes annotated to the nearest gene transcript after quality control. We tested methylation associations with COPD case-control status using mixed linear models. Weighted gene comethylation networks were constructed using weighted gene coexpression network analysis (WGCNA) and network modules were analyzed for association with COPD.
Results
There were five differentially methylated CpG probes significantly associated with COPD among African-Americans at an FDR less than 5 %, and seven additional probes that approached significance at an FDR less than 10 %. The top ranked gene association was MAML1, which has been shown to affect NOTCH-dependent angiogenesis in murine lung. Network modeling yielded the “yellow” and “blue” comethylation modules which were significantly associated with COPD (p-value 4 × 10-10 and 4 × 10-9, respectively). The yellow module was enriched for gene sets related to inflammatory pathways known to be relevant to COPD. The blue module contained the top ranked genes in the concurrent differential methylation analysis (FXYD1/LGI4, gene significance p-value 1.2 × 10-26; MAML1, p-value 2.0 × 10-26; CD72, p-value 2.1 × 10-25; and LPO, p-value 7.2 × 10-25), and was significantly associated with lung development processes in Gene Ontology gene-set enrichment analysis.
Conclusion
We identified 12 differentially methylated CpG sites associated with COPD that mapped to biologically plausible genes. Network module comethylation patterns have identified candidate genes that may be contributing to racial differences in COPD susceptibility and severity. COPD-associated comethylation modules contained genes previously associated with lung disease and inflammation and recapitulated known COPD-associated genes. The genes implicated by differential methylation and WGCNA analysis may provide mechanistic targets contributing to COPD susceptibility, exacerbations, and outcomes among African-Americans.
Trial registration
Trial Registration: NCT00774176, Registry: ClinicalTrials.gov, URL: www.clinicaltrials.gov, Date of Enrollment of First Participant: June 2004, Date Registered: 04 January 2008 (retrospectively registered).
Electronic supplementary material
The online version of this article (doi:10.1186/s12931-016-0459-8) contains supplementary material, which is available to authorized users.
doi:10.1186/s12931-016-0459-8
PMCID: PMC5097392  PMID: 27814717
Chronic obstructive pulmonary disease; DNA methylation; Microarray; Weighted gene coexpression network analysis; Smoking
3.  The Role of Vitamin D in the Transcriptional Program of Human Pregnancy 
PLoS ONE  2016;11(10):e0163832.
Background
Patterns of gene expression of human pregnancy are poorly understood. In a trial of vitamin D supplementation in pregnant women, peripheral blood transcriptomes were measured longitudinally on 30 women and used to characterize gene co-expression networks.
Objective
Studies suggest that increased maternal Vitamin D levels may reduce the risk of asthma in early life, yet the underlying mechanisms have not been examined. In this study, we used a network-based approach to examine changes in gene expression profiles during the course of normal pregnancy and evaluated their association with maternal Vitamin D levels.
Design
The VDAART study is a randomized clinical trial of vitamin D supplementation in pregnancy for reduction of pediatric asthma risk. The trial enrolled 881 women at 10–18 weeks of gestation. Longitudinal gene expression measures were obtained on thirty pregnant women, using RNA isolated from peripheral blood samples obtained in the first and third trimesters. Differentially expressed genes were identified using significance of analysis of microarrays (SAM), and clustered using a weighted gene co-expression network analysis (WGCNA). Gene-set enrichment was performed to identify major biological pathways.
Results
Comparison of transcriptional profiles between first and third trimesters of pregnancy identified 5839 significantly differentially expressed genes (FDR<0.05). Weighted gene co-expression network analysis clustered these transcripts into 14 co-expression modules of which two showed significant correlation with maternal vitamin D levels. Pathway analysis of these two modules revealed genes enriched in immune defense pathways and extracellular matrix reorganization as well as genes enriched in notch signaling and transcription factor networks.
Conclusion
Our data show that gene expression profiles of healthy pregnant women change during the course of pregnancy and suggest that maternal Vitamin D levels influence transcriptional profiles. These alterations of the maternal transcriptome may contribute to fetal immune imprinting and reduce allergic sensitization in early life.
Trial Registration
clinicaltrials.gov NCT00920621
doi:10.1371/journal.pone.0163832
PMCID: PMC5053446  PMID: 27711190
4.  Study to Improve Cardiovascular Outcomes in high-risk older patieNts (ICON1) with acute coronary syndrome: study design and protocol of a prospective observational study 
BMJ Open  2016;6(8):e012091.
Introduction
The ICON1 study (a study to Improve Cardiovascular Outcomes in high-risk older patieNts with acute coronary syndrome) is a prospective observational study of older patients (≥75 years old) with non-ST-elevation acute coronary syndrome managed by contemporary treatment (pharmacological and invasive). The aim of the study was to determine the predictors of poor cardiovascular outcomes in this age group and to generate a risk prediction tool.
Methods and analysis
Participants are recruited from 2 tertiary hospitals in the UK. Baseline evaluation includes frailty, comorbidity, cognition and quality-of-life measures, inflammatory status assessed by a biomarker panel, including microRNAs, senescence assessed by telomere length and telomerase activity, cardiovascular status assessed by arterial stiffness, endothelial function, carotid intima media thickness and left ventricular systolic and diastolic function, and coronary plaque assessed by virtual histology intravascular ultrasound and optical coherence tomography. The patients are followed-up at 30 days and at 1 year for primary outcome measures of death, myocardial infarction, stroke, unplanned revascularisation, bleeding and rehospitalisation.
Ethics and dissemination
The study has been approved by the regional ethics committee (REC 12/NE/016). Findings of the study will be presented in scientific sessions and will be published in peer-reviewed journals.
Trial registration number
NCT01933581: Pre-results.
doi:10.1136/bmjopen-2016-012091
PMCID: PMC5013351  PMID: 27554105
Study design; acute coronary syndrome; older patients
5.  Engaging older patients in cardiovascular research: observational analysis of the ICON-1 study 
Open Heart  2016;3(2):e000436.
Background
As a consequence of population ageing, the number of older patients presenting with acute coronary syndrome (ACS) is increasing. The historical underrepresentation of older patients in many pivotal ACS clinical trials undermines the practice of evidence-based medicine in this high-risk cohort. This study evaluates the feasibility of recruitment of older patients to a longitudinal, clinical study.
Methods
The study to Improve Cardiovascular Outcomes in high-risk patieNts with ACS (ICON-1) is an observational, prospective cohort study investigating predictors of poor outcome in older patients with ACS. All patients aged ≥75 years, referred to a tertiary cardiovascular centre in the North East of England for coronary angiography with a view to urgent percutaneous coronary intervention, were screened for inclusion. A screening log was prospectively maintained, and a detailed analysis was performed to identify the factors associated with recruitment and non-recruitment to ICON-1.
Results
Of the 629 patients screened over 34 months, 457 (72.7%) satisfied the a priori-defined study inclusion/exclusion criteria. Of those eligible to participate, 300 (68.5%) provided informed consent and were recruited to the study; 59 (13.5%) were unable to consent due to a lack of capacity or limitations in communication, and 79 patients (18.0%) declined to participate in the study. Those lacking adequate capacity to consent were older than those able to provide informed consent (83.0±4.7 vs 81.0±4.7 years, p=0.002). Women were more likely to decline than men (25.1% vs 10.0%, p<0.001).
Conclusions
The recruitment of patients was robust, comparing favourably to previous longitudinal studies within this age group. Although enrolling older people to research remains challenging, this cohort is enthusiastic to participate. The contribution of older patients must not be ignored, particularly in the setting of an ever-ageing population, in whom cardiovascular disease burden is high.
Trial registration number
NCT01933581; Pre-results.
doi:10.1136/openhrt-2016-000436
PMCID: PMC4975868  PMID: 27547431
CORONARY ARTERY DISEASE; AGEING
6.  Smoking-Associated Site-Specific Differential Methylation in Buccal Mucosa in the COPDGene Study 
DNA methylation is a complex, tissue-specific phenomenon that can reflect both endogenous factors and exogenous exposures. Buccal brushings represent an easily accessible source of DNA, which may be an appropriate surrogate tissue in the study of environmental exposures and chronic respiratory diseases. Buccal brushings were obtained from a subset of current and former smokers from the COPDGene study. Genome-wide DNA methylation data were obtained in the discovery cohort (n = 82) using the Illumina HumanMethylation450K array. Empirical Bayes methods were used to test for differential methylation by current smoking status at 468,219 autosomal CpG sites using linear models adjusted for age, sex, and race. Pyrosequencing was performed in a nonoverlapping replication cohort (n = 130). Current smokers were significantly younger than former smokers in both the discovery and replication cohorts. Seven CpG sites were associated with current smoking at a false discovery rate less than 0.05 in the discovery cohort. Six of the seven significant sites were pyrosequenced in the replication cohort; five CpG sites, including sites annotated to CYP1B1 and PARVA, were replicated. Correlations between cumulative smoke exposure and time since smoking cessation were observed in a subset of the significantly associated CpG sites. A significant correlation between reduced lung function and increased radiographic emphysema with methylation at cg02162897 (CYP1B1) was observed among female subjects. Site-specific methylation of DNA isolated from buccal mucosa is associated with exposure to cigarette smoke, and may provide insights into the mechanisms underlying differential susceptibility toward the development of smoking-related chronic respiratory diseases.
doi:10.1165/rcmb.2014-0103OC
PMCID: PMC4566042  PMID: 25517428
DNA methylation; smoking; buccal mucosa
7.  Circulating MicroRNAs: Association with Lung Function in Asthma 
PLoS ONE  2016;11(6):e0157998.
Background
MicroRNAs are key transcriptional and network regulators previously associated with asthma susceptibility. However, their role in relation to asthma severity has not been delineated.
Objective
We hypothesized that circulating microRNAs could serve as biomarkers of changes in lung function in asthma patients.
Methods
We isolated microRNAs from serum samples obtained at randomization for 160 participants of the Childhood Asthma Management Program. Using a TaqMan microRNA array containing 754 microRNA primers, we tested for the presence of known asthma microRNAs, and assessed the association of the individual microRNAs with lung function as measured by FEV1/FVC, FEV1% and FVC%. We further tested the subset of FEV1/FVC microRNAs for sex-specific and lung developmental associations.
Results
Of the 108 well-detected circulating microRNAs, 74 (68.5%) had previously been linked to asthma susceptibility. We found 22 (20.3%), 4 (3.7%) and 8 (7.4%) microRNAs to be associated with FEV1/FVC, FEV1% and FVC%, respectively. 8 (of 22) FEV1/FVC, 3 (of 4) FEV1% and 1 (of 8) FVC% microRNAs had functionally validated target genes that have been linked via genome wide association studies to asthma and FEV1 change. Among the 22 FEV1/FVC microRNAs, 9 (40.9%) remain associated with FEV1/FVC in boys alone in a sex-stratified analysis (compared with 3 FEV1/FVC microRNAs in girls alone), 7 (31.8%) were associated with fetal lung development, and 3 (13.6%) in both. Ontology analyses revealed enrichment for pathways integral to asthma, including PPAR signaling, G-protein coupled signaling, actin and myosin binding, and respiratory system development.
Conclusions
Circulating microRNAs reflect asthma biology and are associated with lung function differences in asthmatics. They may represent biomarkers of asthma severity.
doi:10.1371/journal.pone.0157998
PMCID: PMC4928864  PMID: 27362794
8.  A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma 
Human Molecular Genetics  2015;24(11):3005-3020.
Recent advances in genetics have spurred rapid progress towards the systematic identification of genes involved in complex diseases. Still, the detailed understanding of the molecular and physiological mechanisms through which these genes affect disease phenotypes remains a major challenge. Here, we identify the asthma disease module, i.e. the local neighborhood of the interactome whose perturbation is associated with asthma, and validate it for functional and pathophysiological relevance, using both computational and experimental approaches. We find that the asthma disease module is enriched with modest GWAS P-values against the background of random variation, and with differentially expressed genes from normal and asthmatic fibroblast cells treated with an asthma-specific drug. The asthma module also contains immune response mechanisms that are shared with other immune-related disease modules. Further, using diverse omics (genomics, gene-expression, drug response) data, we identify the GAB1 signaling pathway as an important novel modulator in asthma. The wiring diagram of the uncovered asthma module suggests a relatively close link between GAB1 and glucocorticoids (GCs), which we experimentally validate, observing an increase in the level of GAB1 after GC treatment in BEAS-2B bronchial epithelial cells. The siRNA knockdown of GAB1 in the BEAS-2B cell line resulted in a decrease in the NFkB level, suggesting a novel regulatory path of the pro-inflammatory factor NFkB by GAB1 in asthma.
doi:10.1093/hmg/ddv001
PMCID: PMC4447811  PMID: 25586491
9.  Genome-wide site-specific differential methylation in the blood of individuals with Klinefelter Syndrome 
Klinefelter syndrome (KS) (47 XXY) is a common sex-chromosome aneuploidy with an estimated prevalence of 1 in every 660 male births. Investigations into the associations between DNA methylation and the highly variable clinical manifestations of KS have largely focused on the supernumerary X chromosome; systematic investigations of the epigenome have been limited. We obtained genome-wide DNA methylation data from peripheral blood using the Illumina HumanMethylation450K platform in 5 KS (47 XXY), 102 male (46 XY), and 113 female (46 XX) control subjects participating in the chronic obstructive pulmonary disease (COPD) Gene Study. Empirical Bayes-mediated models were used to test for differential methylation by KS status. CpG sites with a false-discovery rate <0.05 from the first-generation HumanMethylation27K platform were further examined in an independent replication cohort of 2 KS subjects, 590 male, and 495 female controls drawn from the International COPD Genetics Network (ICGN). Differential methylation at sites throughout the genome were identified, including 86 CpG sites that were differentially methylated in KS subjects relative to both male and female controls. CpG sites annotated to the HEN1 methyltransferase homolog 1 (HENMT1), calcyclin-binding protein (CACYBP), and GTPase-activating protein (SH3 domain)-binding protein 1 (G3BP1) genes were among the “KS-specific” loci that were replicated in ICGN. We therefore conclude that site-specific differential methylation exists throughout the genome in KS. The functional impact and clinical relevance of these differentially methylated loci should be explored in future studies.
doi:10.1002/mrd.22483
PMCID: PMC4439255  PMID: 25988574
[MeSH]: Klinefelter syndrome; DNA methylation; epigenomics; XXY syndrome
10.  Glucocorticoid Genes and the Developmental Origins of Asthma Susceptibility and Treatment Response 
Antenatal corticosteroids enhance lung maturation. However, the importance of glucocorticoid genes on early lung development, asthma susceptibility, and treatment response remains unknown. We investigated whether glucocorticoid genes are important during lung development and their role in asthma susceptibility and treatment response. We identified genes that were differentially expressed by corticosteroids in two of three genomic datasets: lymphoblastoid cell lines of participants in the Childhood Asthma Management Program, a glucocorticoid chromatin immunoprecipitation/RNA sequencing experiment, or a murine model; these genes made up the glucocorticoid gene set (GCGS). Using gene expression profiles from 38 human fetal lungs and C57BL/6J murine fetal lungs, we identified developmental genes that were in the top 5% of genes contributing to the top three principal components (PCs) most highly associated with post-conceptional age. Glucocorticoid genes that were enriched in this set of developmental genes were then included in the developmental glucocorticoid gene set (DGGS). We then investigated whether glucocorticoid genes are important during lung development, and their role in asthma susceptibility and treatment response. A total of 232 genes were included in the GCGS. Analysis of gene expression demonstrated that glucocorticoid genes were enriched in lung development (P = 7.02 × 10−26). The developmental GCGS was enriched for genes that were differentially expressed between subjects with asthma and control subjects (P = 4.26 × 10−3) and were enriched after treatment of subjects with asthma with inhaled corticosteroids (P < 2.72 × 10−4). Our results show that glucocorticoid genes are overrepresented among genes implicated in fetal lung development. These genes influence asthma susceptibility and treatment response, suggesting their involvement in the early ontogeny of asthma.
doi:10.1165/rcmb.2014-0109OC
PMCID: PMC4491138  PMID: 25192440
glucocorticoid genes; lung development; asthma; asthma treatment
11.  Genome-Wide Expression Profiles Identify Potential Targets for Gene by Environment Interactions in Asthma Severity 
Background
Gene by environment interaction (G × E) studies utilizing GWAS data are often underpowered after adjustment for multiple comparisons. Differential gene expression, in response to the exposure of interest, may capture the most biologically relevant genes at the genome-wide level.
Methods
We used differential genome-wide expression profiles from the Home Allergens and Asthma Birth cohort in response to Der f 1 allergen (sensitized vs. non-sensitized) to inform a G × E study of dust mite exposure and asthma severity. Polymorphisms in differentially expressed genes were identified in GWAS data from CAMP, a clinical trial in childhood asthmatics. Home dust mite allergen (< or ≥ 10µg/g dust) was assessed at baseline, and (≥ 1) severe asthma exacerbation (emergency room (ER) visit or hospitalization for asthma in the first trial year) served as the disease severity outcome. The Genetics of Asthma in Costa Rica (GACRS) study, and a Puerto Rico/Connecticut asthma cohortwere used for replication.
Results
IL-9, IL-5 and PRG2 expression was up-regulated in Der f 1 stimulated PBMCs from dust mite sensitized individuals (adj. p value <0.04). IL-9 polymorphisms (rs11741137, rs2069885, rs1859430) showed evidence for interaction with dust mite in CAMP (p=0.02 to 0.03), with replication in GACRS (p=0.04). Subjects with the dominant genotype for these IL-9 polymorphisms were more likely to report a severe asthma exacerbation if exposed to elevated dust mite.
Conclusions
Genome-wide differential gene expression in response to dust mite allergen identified IL-9, a biologically plausible gene target that may interact with environmental dust mite to increase severe asthma exacerbations in children.
doi:10.1016/j.jaci.2015.02.035
PMCID: PMC4763940  PMID: 25913104
12.  Genetic control of gene expression at novel and established chronic obstructive pulmonary disease loci 
Human Molecular Genetics  2014;24(4):1200-1210.
Genetic risk loci have been identified for a wide range of diseases through genome-wide association studies (GWAS), but the relevant functional mechanisms have been identified for only a small proportion of these GWAS-identified loci. By integrating results from the largest current GWAS of chronic obstructive disease (COPD) with expression quantitative trait locus (eQTL) analysis in whole blood and sputum from 121 subjects with COPD from the ECLIPSE Study, this analysis identifies loci that are simultaneously associated with COPD and the expression of nearby genes (COPD eQTLs). After integrative analysis, 19 COPD eQTLs were identified, including all four previously identified genome-wide significant loci near HHIP, FAM13A, and the 15q25 and 19q13 loci. For each COPD eQTL, fine mapping and colocalization analysis to identify causal shared eQTL and GWAS variants identified a subset of sites with moderate-to-strong evidence of harboring at least one shared variant responsible for both the eQTL and GWAS signals. Transcription factor binding site (TFBS) analysis confirms that multiple COPD eQTL lead SNPs disrupt TFBS, and enhancer enrichment analysis for loci with the strongest colocalization signals showed enrichment for blood-related cell types (CD3 and CD4+ T cells, lymphoblastoid cell lines). In summary, integrative eQTL and GWAS analysis confirms that genetic control of gene expression plays a key role in the genetic architecture of COPD and identifies specific blood-related cell types as likely participants in the functional pathway from GWAS-associated variant to disease phenotype.
doi:10.1093/hmg/ddu525
PMCID: PMC4806382  PMID: 25315895
13.  A Comparative Study of Tests for Homogeneity of Variances with Application to DNA Methylation Data 
PLoS ONE  2015;10(12):e0145295.
Variable DNA methylation has been associated with cancers and complex diseases. Researchers have identified many DNA methylation markers that have different mean methylation levels between diseased subjects and normal subjects. Recently, researchers found that DNA methylation markers with different variabilities between subject groups could also have biological meaning. In this article, we aimed to help researchers choose the right test of equal variance in DNA methylation data analysis. We performed systematic simulation studies and a real data analysis to compare the performances of 7 equal-variance tests, including 2 tests recently proposed in the DNA methylation analysis literature. Our results showed that the Brown-Forsythe test and trimmed-mean-based Levene's test had good performance in testing for equality of variance in our simulation studies and real data analyses. Our results also showed that outlier profiles could be biologically very important.
doi:10.1371/journal.pone.0145295
PMCID: PMC4684215  PMID: 26683022
14.  Expression Quantitative Trait Loci Information Improves Predictive Modeling of Disease Relevance of Non-Coding Genetic Variation 
PLoS ONE  2015;10(10):e0140758.
Disease-associated loci identified through genome-wide association studies (GWAS) frequently localize to non-coding sequence. We and others have demonstrated strong enrichment of such single nucleotide polymorphisms (SNPs) for expression quantitative trait loci (eQTLs), supporting an important role for regulatory genetic variation in complex disease pathogenesis. Herein we describe our initial efforts to develop a predictive model of disease-associated variants leveraging eQTL information. We first catalogued cis-acting eQTLs (SNPs within 100kb of target gene transcripts) by meta-analyzing four studies of three blood-derived tissues (n = 586). At a false discovery rate < 5%, we mapped eQTLs for 6,535 genes; these were enriched for disease-associated genes (P < 10−04), particularly those related to immune diseases and metabolic traits. Based on eQTL information and other variant annotations (distance from target gene transcript, minor allele frequency, and chromatin state), we created multivariate logistic regression models to predict SNP membership in reported GWAS. The complete model revealed independent contributions of specific annotations as strong predictors, including evidence for an eQTL (odds ratio (OR) = 1.2–2.0, P < 10−11) and the chromatin states of active promoters, different classes of strong or weak enhancers, or transcriptionally active regions (OR = 1.5–2.3, P < 10−11). This complete prediction model including eQTL association information ultimately allowed for better discrimination of SNPs with higher probabilities of GWAS membership (6.3–10.0%, compared to 3.5% for a random SNP) than the other two models excluding eQTL information. This eQTL-based prediction model of disease relevance can help systematically prioritize non-coding GWAS SNPs for further functional characterization.
doi:10.1371/journal.pone.0140758
PMCID: PMC4608673  PMID: 26474488
15.  Genome-wide interaction studies reveal sex-specific asthma risk alleles 
Human Molecular Genetics  2014;23(19):5251-5259.
Asthma is a complex disease with sex-specific differences in prevalence. Candidate gene studies have suggested that genotype-by-sex interaction effects on asthma risk exist, but this has not yet been explored at a genome-wide level. We aimed to identify sex-specific asthma risk alleles by performing a genome-wide scan for genotype-by-sex interactions in the ethnically diverse participants in the EVE Asthma Genetics Consortium. We performed male- and female-specific genome-wide association studies in 2653 male asthma cases, 2566 female asthma cases and 3830 non-asthma controls from European American, African American, African Caribbean and Latino populations. Association tests were conducted in each study sample, and the results were combined in ancestry-specific and cross-ancestry meta-analyses. Six sex-specific asthma risk loci had P-values < 1 × 10−6, of which two were male specific and four were female specific; all were ancestry specific. The most significant sex-specific association in European Americans was at the interferon regulatory factor 1 (IRF1) locus on 5q31.1. We also identify a Latino female-specific association in RAP1GAP2. Both of these loci included single-nucleotide polymorphisms that are known expression quantitative trait loci and have been associated with asthma in independent studies. The IRF1 locus is a strong candidate region for male-specific asthma susceptibility due to the association and validation we demonstrate here, the known role of IRF1 in asthma-relevant immune pathways and prior reports of sex-specific differences in interferon responses.
doi:10.1093/hmg/ddu222
PMCID: PMC4159149  PMID: 24824216
16.  The metabolomics of asthma control: a promising link between genetics and disease 
Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative “omics” approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), ­ using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites—monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.
doi:10.1002/iid3.61
PMCID: PMC4578522  PMID: 26421150
Albuterol; asthma; epigenetics; genetics; metabolomics
17.  Pharmacogenomics: novel loci identification via integrating gene differential analysis and eQTL analysis 
Human Molecular Genetics  2014;23(18):5017-5024.
Nearly one-half of asthmatic patients do not respond to the most commonly prescribed controller therapy, inhaled corticosteroids (ICS). We conducted an expression quantitative trait loci (eQTL) analysis using >300 expression microarrays (from 117 lymphoblastoid cell lines) in corticosteroid (dexamethasone) treated and untreated cells derived from asthmatic subjects in the Childhood Asthma Management Program (CAMP) clinical trial. We then tested the associations of eQTL with longitudinal change in airway responsiveness to methacholine (LnPC20) on ICS. We identified 2484 cis-eQTL affecting 767 genes following dexamethasone treatment. A significant over-representation of lnPC20-associated cis-eQTL [190 single-nucleotide polymorphisms (SNPs)] among differentially expressed genes (odds ratio = 1.76, 95% confidence interval: 1.35–2.29) was noted in CAMP Caucasians. Forty-six of these 190 clinical associations were replicated in CAMP African Americans, including seven SNPs near six genes meeting criteria for genome-wide significance (P < 2 × 10−7). Notably, the majority of genome-wide findings would not have been uncovered via analysis of untreated samples. These results indicate that identifying eQTL after relevant environmental perturbation enables identification of true pharmacogenetic variants.
doi:10.1093/hmg/ddu191
PMCID: PMC4140460  PMID: 24770851
18.  The metabolomics of asthma control: a promising link between genetics and disease 
Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative “omics” approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), ­ using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites—monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.
doi:10.1002/iid3.61
PMCID: PMC4578522  PMID: 26421150
Albuterol; asthma; epigenetics; genetics; metabolomics
19.  Inhaled corticosteroid treatment modulates ZNF432 gene variant's effect on bronchodilator response in asthmatics 
Background
Single nucleotide polymorphisms (SNPs) influence a patient's response to inhaled corticosteroids and β2-agonists, and the effect of treatment with inhaled corticosteroids is synergistic with the effect of β2-agonists. We hypothesized that use of inhaled corticosteroids could influence the effect of SNPs associated with bronchodilator response.
Objective
To assess whether, among asthma subjects, the association of SNPs with bronchodilator response is different between those treated with inhaled corticosteroids vs. those on placebo.
Methods
A genome-wide association analysis was conducted using 581 white subjects from the Childhood Asthma Management Program (CAMP). Using data for 449,540 SNPs, we conducted a gene by environment analysis in PLINK with inhaled corticosteroid treatment as the environmental exposure and bronchodilator response as the outcome measure. We attempted to replicate the top 12 SNPs in the Leukotriene Modifier Or Corticosteroid or Corticosteroid-Salmeterol (LOCCS) Trial.
Results
The combined P-value for the CAMP and LOCCS populations was 4.81E-08 for rs3752120, which is located in the zinc finger protein gene ZNF432, and has unknown function.
Conclusions
Inhaled corticosteroids appear to modulate the association of bronchodilator response with variant(s) in the ZNF432 gene among adults and children with asthma.
Clinical Implications
Clinicians who treat asthma patients with inhaled corticosteroids should be aware that the patient's genetic makeup likely influences response as measured in lung function.
Capsule Summary
Our study suggests that inhaled corticosteroids could influence the effect of multiple SNPs associated with bronchodilator response across the genome.
doi:10.1016/j.jaci.2013.09.037
PMCID: PMC3943570  PMID: 24280104
asthma; bronchodilator response; lung function; inhaled corticosteroids; single nucleotide polymorphisms; zinc finger proteins; ZNF432
20.  Haploinsufficiency of Hedgehog interacting protein causes increased emphysema induced by cigarette smoke through network rewiring 
Genome Medicine  2015;7(1):12.
Background
The HHIP gene, encoding Hedgehog interacting protein, has been implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS), and our subsequent studies identified a functional upstream genetic variant that decreased HHIP transcription. However, little is known about how HHIP contributes to COPD pathogenesis.
Methods
We exposed Hhip haploinsufficient mice (Hhip+/-) to cigarette smoke (CS) for 6 months to model the biological consequences caused by CS in human COPD risk-allele carriers at the HHIP locus. Gene expression profiling in murine lungs was performed followed by an integrative network inference analysis, PANDA (Passing Attributes between Networks for Data Assimilation) analysis.
Results
We detected more severe airspace enlargement in Hhip+/- mice vs. wild-type littermates (Hhip+/+) exposed to CS. Gene expression profiling in murine lungs suggested enhanced lymphocyte activation pathways in CS-exposed Hhip+/- vs. Hhip+/+ mice, which was supported by increased numbers of lymphoid aggregates and enhanced activation of CD8+ T cells after CS-exposure in the lungs of Hhip+/-mice compared to Hhip+/+ mice. Mechanistically, results from PANDA network analysis suggested a rewired and dampened Klf4 signaling network in Hhip+/- mice after CS exposure.
Conclusions
In summary, HHIP haploinsufficiency exaggerated CS-induced airspace enlargement, which models CS-induced emphysema in human smokers carrying COPD risk alleles at the HHIP locus. Network modeling suggested rewired lymphocyte activation signaling circuits in the HHIP haploinsufficiency state.
Electronic supplementary material
The online version of this article (doi:10.1186/s13073-015-0137-3) contains supplementary material, which is available to authorized users.
doi:10.1186/s13073-015-0137-3
PMCID: PMC4355149  PMID: 25763110
21.  Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods 
Background
Exacerbations of chronic obstructive pulmonary disease (COPD), characterized by acute deterioration in symptoms, may be due to bacterial or viral infections, environmental exposures, or unknown factors. Exacerbation frequency may be a stable trait in COPD patients, which could imply genetic susceptibility. Observing the genes, networks, and pathways that are up- and down-regulated in COPD patients with differing susceptibility to exacerbations will help to elucidate the molecular signature and pathogenesis of COPD exacerbations.
Methods
Gene expression array and plasma biomarker data were obtained using whole-blood samples from subjects enrolled in the Treatment of Emphysema With a Gamma-Selective Retinoid Agonist (TESRA) study. Linear regression, weighted gene co-expression network analysis (WGCNA), and pathway analysis were used to identify signatures and network sub-modules associated with the number of exacerbations within the previous year; other COPD-related phenotypes were also investigated.
Results
Individual genes were not found to be significantly associated with the number of exacerbations. However using network methods, a statistically significant gene module was identified, along with other modules showing moderate association. A diverse signature was observed across these modules using pathway analysis, marked by differences in B cell and NK cell activity, as well as cellular markers of viral infection. Within two modules, gene set enrichment analysis recapitulated the molecular signatures of two gene expression experiments; one involving sputum from asthma exacerbations and another involving viral lung infections. The plasma biomarker myeloperoxidase (MPO) was associated with the number of recent exacerbations.
Conclusion
A distinct signature of COPD exacerbations may be observed in peripheral blood months following the acute illness. While not predictive in this cross-sectional analysis, these results will be useful in uncovering the molecular pathogenesis of COPD exacerbations.
Electronic supplementary material
The online version of this article (doi:10.1186/s12920-014-0072-y) contains supplementary material, which is available to authorized users.
doi:10.1186/s12920-014-0072-y
PMCID: PMC4302028  PMID: 25582225
Network analysis; Chronic obstructive pulmonary disease; Gene expression profiling; Biomarker
22.  Integrated genome-wide association, coexpression network, and expression single nucleotide polymorphism analysis identifies novel pathway in allergic rhinitis 
BMC Medical Genomics  2014;7:48.
Background
Allergic rhinitis is a common disease whose genetic basis is incompletely explained. We report an integrated genomic analysis of allergic rhinitis.
Methods
We performed genome wide association studies (GWAS) of allergic rhinitis in 5633 ethnically diverse North American subjects. Next, we profiled gene expression in disease-relevant tissue (peripheral blood CD4+ lymphocytes) collected from subjects who had been genotyped. We then integrated the GWAS and gene expression data using expression single nucleotide (eSNP), coexpression network, and pathway approaches to identify the biologic relevance of our GWAS.
Results
GWAS revealed ethnicity-specific findings, with 4 genome-wide significant loci among Latinos and 1 genome-wide significant locus in the GWAS meta-analysis across ethnic groups. To identify biologic context for these results, we constructed a coexpression network to define modules of genes with similar patterns of CD4+ gene expression (coexpression modules) that could serve as constructs of broader gene expression. 6 of the 22 GWAS loci with P-value ≤ 1x10−6 tagged one particular coexpression module (4.0-fold enrichment, P-value 0.0029), and this module also had the greatest enrichment (3.4-fold enrichment, P-value 2.6 × 10−24) for allergic rhinitis-associated eSNPs (genetic variants associated with both gene expression and allergic rhinitis). The integrated GWAS, coexpression network, and eSNP results therefore supported this coexpression module as an allergic rhinitis module. Pathway analysis revealed that the module was enriched for mitochondrial pathways (8.6-fold enrichment, P-value 4.5 × 10−72).
Conclusions
Our results highlight mitochondrial pathways as a target for further investigation of allergic rhinitis mechanism and treatment. Our integrated approach can be applied to provide biologic context for GWAS of other diseases.
doi:10.1186/1755-8794-7-48
PMCID: PMC4127082  PMID: 25085501
Genome-wide association study; Allergic rhinitis; Coexpression network; Expression single-nucleotide polymorphism; Coexpression module; Pathway; Mitochondria; Hay fever; Allergy
23.  A genome-wide association study of bronchodilator response in asthmatics 
The pharmacogenomics journal  2013;14(1):41-47.
Reversibility of airway obstruction in response to β2-agonists is highly variable among asthmatics, which is partially attributed to genetic factors. In a genome-wide association study of acute bronchodilator response (BDR) to inhaled albuterol, 534,290 single nucleotide polymorphisms (SNPs) were tested in 403 white trios from the Childhood Asthma Management Program using five statistical models to determine the most robust genetic associations. The primary replication phase included 1397 polymorphisms in three asthma trials (pooled n=764). The second replication phase tested 13 SNPs in three additional asthma populations (n=241, n=215, and n=592). An intergenic SNP on chromosome 10, rs11252394, proximal to several excellent biological candidates, significantly replicated (p=1.98×10−7) in the primary replication trials. An intronic SNP (rs6988229) in the collagen (COL22A1) locus also provided strong replication signals (p=8.51×10−6). This study applied a robust approach for testing the genetic basis of BDR and identified novel loci associated with this drug response in asthmatics.
doi:10.1038/tpj.2013.5
PMCID: PMC3706515  PMID: 23508266
pharmacogenetics; asthma; bronchodilator response; genome-wide association study; albuterol
24.  Gene expression analysis uncovers novel Hedgehog interacting protein (HHIP) effects in human bronchial epithelial cells 
Genomics  2013;101(5):263-272.
Hedgehog Interacting Protein (HHIP) was implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS). However, it remains unclear how HHIP contributes to COPD pathogenesis. To identify genes regulated by HHIP, we performed gene expression microarray analysis in a human bronchial epithelial cell line (Beas-2B) stably infected with HHIP shRNAs. HHIP silencing led to differential expression of 296 genes; enrichment for variants nominally associated with COPD was found. Eighteen of the differentially expressed genes were validated by real-time PCR in Beas-2B cells. Seven of 11 validated genes tested in human COPD and control lung tissues demonstrated significant gene expression differences. Functional annotation indicated enrichment for extracellular matrix and cell growth genes. Network modeling demonstrated that the extracellular matrix and cell proliferation genes influenced by HHIP tended to be interconnected. Thus, we identified potential HHIP targets in human bronchial epithelial cells that may contribute to COPD pathogenesis.
doi:10.1016/j.ygeno.2013.02.010
PMCID: PMC3659826  PMID: 23459001
Hedgehog interacting protein (HHIP); Gene expression profiling; COPD (Chronic obstructive pulmonary disease); extracellular matrix (ECM); network modeling
25.  Assessing Discrimination of Risk Prediction Rules in a Clustered Data Setting* 
Lifetime data analysis  2012;19(2):242-256.
The AUC (area under ROC curve) is a commonly used metric to assess discrimination of risk prediction rules; however, standard errors of AUC are usually based on the Mann-Whitney U test that assumes independence of sampling units. For ophthalmologic applications, it is desirable to assess risk prediction rules based on eye-specific outcome variables which are generally highly, but not perfectly correlated in fellow eyes (eg. progression of individual eyes to age-related macular degeneration (AMD)). In this article, we use the extended Mann-Whitney U test (Rosner et al, 2009) for the case where subunits within a cluster may have different progression status and assess discrimination of different prediction rules in this setting. Both data analyses based on progression of AMD and simulation studies show reasonable accuracy of this extended Mann-Whitney U test to assess discrimination of eye-specific risk prediction rules.
doi:10.1007/s10985-012-9240-6
PMCID: PMC3622772  PMID: 23263872
risk prediction; ROC curves; clustered data; GEE

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