Sexually-dimorphic targeting of functionally-related genes in COPD

Background: There is growing evidence that many diseases develop, progress, and respond to therapy differently in men and women. This variability may manifest as a result of sex-specific structures in gene regulatory networks that influence how those networks operate. However, there are few methods to identify and characterize differences in network structure, slowing progress in understanding mechanisms driving sexual dimorphism. Results: Here we apply an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation), to model sex-specific networks in blood and sputum samples from subjects with Chronic Obstructive Pulmonary Disease (COPD). We used a jack-knifing approach to build an ensemble of likely networks for each sex. By adapting statistical methods to compare these network ensembles, we were able to identify strong differential-targeting patterns associated with functionally-related sets of genes, including those involved in mitochondrial function and energy metabolism. Network analysis also identified several potential sex- and disease-specific transcriptional regulators of these pathways. Conclusions: Network analysis yielded insight into potential mechanisms driving sexual dimorphism in COPD that were not evident from gene expression analysis alone. We believe our ensemble approach to network analysis provides a principled way to capture sex-specific regulatory relationships and could be applied to identify differences in gene regulatory patterns in a wide variety of diseases and contexts. Electronic supplementary material The online version of this article (doi:10.1186/s12918-014-0118-y) contains supplementary material, which is available to authorized users

Epidemiology, genetics, and subtyping of preserved ratio impaired spirometry (PRISm) in COPDGene.

BackgroundPreserved Ratio Impaired Spirometry (PRISm), defined as a reduced FEV1 in the setting of a preserved FEV1/FVC ratio, is highly prevalent and is associated with increased respiratory symptoms, systemic inflammation, and mortality. Studies investigating quantitative chest tomographic features, genetic associations, and subtypes in PRISm subjects have not been reported.MethodsData from current and former smokers enrolled in COPDGene (n = 10,192), an observational, cross-sectional study which recruited subjects aged 45-80 with ≥10 pack years of smoking, were analyzed. To identify epidemiological and radiographic predictors of PRISm, we performed univariate and multivariate analyses comparing PRISm subjects both to control subjects with normal spirometry and to subjects with COPD. To investigate common genetic predictors of PRISm, we performed a genome-wide association study (GWAS). To explore potential subgroups within PRISm, we performed unsupervised k-means clustering.ResultsThe prevalence of PRISm in COPDGene is 12.3%. Increased dyspnea, reduced 6-minute walk distance, increased percent emphysema and decreased total lung capacity, as well as increased segmental bronchial wall area percentage were significant predictors (p-value <0.05) of PRISm status when compared to control subjects in multivariate models. Although no common genetic variants were identified on GWAS testing, a significant association with Klinefelter's syndrome (47XXY) was observed (p-value < 0.001). Subgroups identified through k-means clustering include a putative "COPD-subtype", "Restrictive-subtype", and a highly symptomatic "Metabolic-subtype".ConclusionsPRISm subjects are clinically and genetically heterogeneous. Future investigations into the pathophysiological mechanisms behind and potential treatment options for subgroups within PRISm are warranted.Trial registrationClinicaltrials.gov Identifier: NCT000608764

Epigenomic assessment of cardiovascular disease risk and interactions with traditional risk metrics

Background Epigenome-wide association studies for cardiometabolic risk factors have discovered multiple loci associated with incident cardiovascular disease (CVD). However, few studies have sought to directly optimize a predictor of CVD risk. Furthermore, it is challenging to train multivariate models across multiple studies in the presence of study- or batch effects. Methods and Results Here, we analyzed existing DNA methylation data collected using the Illumina HumanMethylation450 microarray to create a predictor of CVD risk across 3 cohorts: Women's Health Initiative, Framingham Heart Study Offspring Cohort, and Lothian Birth Cohorts. We trained Cox proportional hazards-based elastic net regressions for incident CVD separately in each cohort and used a recently introduced cross-study learning approach to integrate these individual scores into an ensemble predictor. The methylation-based risk score was associated with CVD time-to-event in a held-out fraction of the Framingham data set (hazard ratio per SD=1.28, 95% CI, 1.10-1.50) and predicted myocardial infarction status in the independent REGICOR (Girona Heart Registry) data set (odds ratio per SD=2.14, 95% CI, 1.58-2.89). These associations remained after adjustment for traditional cardiovascular risk factors and were similar to those from elastic net models trained on a directly merged data set. Additionally, we investigated interactions between the methylation-based risk score and both genetic and biochemical CVD risk, showing preliminary evidence of an enhanced performance in those with less traditional risk factor elevation. Conclusions This investigation provides proof-of-concept for a genome-wide, CVD-specific epigenomic risk score and suggests that DNA methylation data may enable the discovery of high-risk individuals who would be missed by alternative risk metrics.This work was supported by the US Department of Agriculture, Agriculture Research Service (8050–51000-098-00D). Dr. Westerman was additionally supported by National Institutes of Health predoctoral training grant 5T32HL069772-14. The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, US Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. This article was prepared in collaboration with investigators of the WHI but has not been reviewed by the WHI and does not necessarily reflect the opinions of the WHI investigators or the National Heart, Lung, and Blood Institute. The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute in collaboration with Boston University (Contract No. N01-HC-25195 and HHSN268201500001I). This article was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or National Heart, Lung, and Blood Institute. The LBC 1936 is supported by Age UK (Disconnected Mind program) and the Medical Research Council (MR/M01311/1). Methylation typing in LBC 1936 was supported by Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, The Wellcome Trust Institutional Strategic Support Fund, The University of Edinburgh, and The University of Queensland. LBC 1936 work was conducted in the Centre for Cognitive Ageing and Cognitive Epidemiology, which supported Dr. Deary and is supported by the medical Research Council and Biotechnology and Biological Sciences Research Council (MR/K026992/1).S

Residential Proximity to Major Roadways at Birth, DNA Methylation at Birth and Midchildhood, and Childhood Cognitive Test Scores: Project Viva(Massachusetts, USA).

BackgroundEpigenetic variability is hypothesized as a regulatory pathway through which prenatal exposures may influence child development and health.ObjectiveWe sought to examine the associations of residential proximity to roadways at birth and epigenome-wide DNA methylation. We also assessed associations of differential methylation with child cognitive outcomes.MethodsWe estimated residential proximity to roadways at birth using a geographic information system (GIS) and cord blood methylation using Illumina's HumanMethylation450-array in 482 mother-child pairs in Project Viva. We identified individual CpGs associated with residential-proximity-to-roadways at birth using robust linear regression [[Formula: see text]]. We also estimated association between proximity-to-roadways at birth and methylation of the same sites in blood samples collected at age 7-11 y ([Formula: see text]). We ran the same analyses in the Generation R Study for replication ([Formula: see text]). In Project Viva, we investigated associations of differential methylation at birth with midchildhood cognition using linear regression.ResultsLiving closer to major roadways at birth was associated with higher cord blood (and-more weakly-midchildhood blood) methylation of four sites in LAMB2. For each halving of residential-proximity-to-major-roadways, we observed a 0.82% increase in DNA methylation at cg05654765 [95% confidence interval (CI): (0.54%, 1.10%)], 0.88% at cg14099457 [95% CI: (0.56%, 1.19%)], 0.19% at cg03732535 [95% CI: (0.11%, 0.28)], and 1.08% at cg02954987 [95% CI: (0.65%, 1.51%)]. Higher cord blood methylation of these sites was associated with lower midchildhood nonverbal cognitive scores. Our results did not replicate in the Generation R Study.ConclusionsOur discovery results must be interpreted with caution, given that they were not replicated in a separate cohort. However, living close to major roadways at birth was associated with cord blood methylation of sites in LAMB2-a gene known to be linked to axonal development-in our U.S. cohort. Higher methylation of these sites associated with lower nonverbal cognitive scores at age 7-11 y in the same children. https://doi.org/10.1289/EHP2034

DRAGON: Determining Regulatory Associations using Graphical models on multi-Omic Networks

The increasing quantity of multi-omic data, such as methylomic and transcriptomic profiles collected on the same specimen or even on the same cell, provides a unique opportunity to explore the complex interactions that define cell phenotype and govern cellular responses to perturbations. We propose a network approach based on Gaussian Graphical Models (GGMs) that facilitates the joint analysis of paired omics data. This method, called DRAGON (Determining Regulatory Associations using Graphical models on multi-Omic Networks), calibrates its parameters to achieve an optimal trade-off between the network’s complexity and estimation accuracy, while explicitly accounting for the characteristics of each of the assessed omics ‘layers.’ In simulation studies, we show that DRAGON adapts to edge density and feature size differences between omics layers, improving model inference and edge recovery compared to state-of-the-art methods. We further demonstrate in an analysis of joint transcriptome - methylome data from TCGA breast cancer specimens that DRAGON can identify key molecular mechanisms such as gene regulation via promoter methylation. In particular, we identify Transcription Factor AP-2 Beta (TFAP2B) as a potential multi-omic biomarker for basal-type breast cancer. DRAGON is available as open-source code in Python through the Network Zoo package (netZooPy v0.8; netzoo.github.io)

Prenatal maternal antidepressants, anxiety, and depression and offspring DNA methylation: epigenome-wide associations at birth and persistence into early childhood

Background Maternal mood disorders and their treatment during pregnancy may have effects on the offspring epigenome. We aim to evaluate associations of maternal prenatal antidepressant use, anxiety, and depression with cord blood DNA methylation across the genome at birth and test for persistence of associations in early and mid-childhood blood DNA. Methods A discovery phase was conducted in Project Viva, a prospective pre-birth cohort study with external replication in an independent cohort, the Generation R Study. In Project Viva, pregnant women were recruited between 1999 and 2002 in Eastern Massachusetts, USA. In the Generation R Study, pregnant women were recruited between 2002 and 2006 in Rotterdam, the Netherlands. In Project Viva, 479 infants had data on maternal antidepressant use, anxiety, depression, and cord blood DNA methylation, 120 children had DNA methylation measured in early childhood (~ 3 years), and 460 in mid-childhood (~ 7 years). In the Generation R Study, 999 infants had data on maternal antidepressants and cord blood DNA methylation. The prenatal antidepressant prescription was obtained from medical records. At-mid pregnancy, symptoms of anxiety and depression were assessed with the Pregnancy-Related Anxiety Scale and the Edinburgh Postnatal Depression Scale in Project Viva and with the Brief Symptom Inventory in the Generation R Study. Genome-wide DNA methylation was measured using the Infinium HumanMethylation450 BeadChip in both cohorts. Results In Project Viva, 2.9% (14/479) pregnant women were prescribed antidepressants, 9.0% (40/445) experienced high pregnancy-related anxiety, and 8.2% (33/402) reported symptoms consistent with depression. Newborns exposed to antidepressants in pregnancy had 7.2% lower DNA methylation (95% CI, − 10.4, − 4.1; P = 1.03 × 10−8) at cg22159528 located in the gene body of ZNF575, and this association replicated in the Generation R Study (β = − 2.5%; 95% CI − 4.2, − 0.7; P = 0.006). In Project Viva, the association persisted in early (β = − 6.2%; 95% CI − 10.7, − 1.6) but not mid-childhood. We observed cohort-specific associations for maternal anxiety and depression in Project Viva that did not replicate. Conclusions The ZNF575 gene is involved in transcriptional regulation but specific functions are largely unknown. Given the widespread use of antidepressants in pregnancy, as well as the effects of exposure to anxiety and depression, implications of potential fetal epigenetic programming by these risk factors and their impacts on development merit further investigation

Association of IREB2 and CHRNA3 polymorphisms with airflow obstruction in severe alpha-1 antitrypsin deficiency

Background: The development of COPD in subjects with alpha-1 antitrypsin (AAT) deficiency is likely to be influenced by modifier genes. Genome-wide association studies and integrative genomics approaches in COPD have demonstrated significant associations with SNPs in the chromosome 15q region that includes CHRNA3 (cholinergic nicotine receptor alpha3) and IREB2 (iron regulatory binding protein 2). We investigated whether SNPs in the chromosome 15q region would be modifiers for lung function and COPD in AAT deficiency. Methods The current analysis included 378 PIZZ subjects in the AAT Genetic Modifiers Study and a replication cohort of 458 subjects from the UK AAT Deficiency National Registry. Nine SNPs in LOC123688, CHRNA3 and IREB2 were selected for genotyping. Fev$_1$ percent of predicted and Fev$_1$/FVC ratio were analyzed as quantitative phenotypes. Family-based association analysis was performed in the AAT Genetic Modifiers Study. In the replication set, general linear models were used for quantitative phenotypes and logistic regression models were used for the presence/absence of emphysema or COPD. Results: Three SNPs (rs2568494 in IREB2, rs8034191 in LOC123688, and rs1051730 in CHRNA3) were associated with pre-bronchodilator Fev$_1$ percent of predicted in the AAT Genetic Modifiers Study. Two SNPs (rs2568494 and rs1051730) were associated with the post-bronchodilator Fev$_1$ percent of predicted and pre-bronchodilator Fev$_1$/FVC ratio; SNP-by-gender interactions were observed. In the UK National Registry dataset, rs2568494 was significantly associated with emphysema in the male subgroup; significant SNP-by-smoking interactions were observed. Conclusions: IREB2 and CHRNA3 are potential genetic modifiers of COPD phenotypes in individuals with severe AAT deficiency and may be sex-specific in their impact

Systemic Steroid Exposure Is Associated with Differential Methylation in Chronic Obstructive Pulmonary Disease

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

X chromosome associations with chronic obstructive pulmonary disease and related phenotypes: an X chromosome-wide association study

Background The association between genetic variants on the X chromosome to risk of COPD has not been fully explored. We hypothesize that the X chromosome harbors variants important in determining risk of COPD related phenotypes and may drive sex differences in COPD manifestations. Methods Using X chromosome data from three COPD-enriched cohorts of adult smokers, we performed X chromosome specific quality control, imputation, and testing for association with COPD case–control status, lung function, and quantitative emphysema. Analyses were performed among all subjects, then stratified by sex, and subsequently combined in meta-analyses. Results Among 10,193 subjects of non-Hispanic white or European ancestry, a variant near TMSB4X, rs5979771, reached genome-wide significance for association with lung function measured by FEV1/FVC (β 0.020, SE 0.004, p 4.97 × 10–08), with suggestive evidence of association with FEV1 (β 0.092, SE 0.018, p 3.40 × 10–07). Sex-stratified analyses revealed X chromosome variants that were differentially trending in one sex, with significantly different effect sizes or directions. Conclusions This investigation identified loci influencing lung function, COPD, and emphysema in a comprehensive genetic association meta-analysis of X chromosome genetic markers from multiple COPD-related datasets. Sex differences play an important role in the pathobiology of complex lung disease, including X chromosome variants that demonstrate differential effects by sex and variants that may be relevant through escape from X chromosome inactivation. Comprehensive interrogation of the X chromosome to better understand genetic control of COPD and lung function is important to further understanding of disease pathology. Trial registration Genetic Epidemiology of COPD Study (COPDGene) is registered at ClinicalTrials.gov, NCT00608764 (Active since January 28, 2008). Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study (ECLIPSE), GlaxoSmithKline study code SCO104960, is registered at ClinicalTrials.gov, NCT00292552 (Active since February 16, 2006). Genetics of COPD in Norway Study (GenKOLS) holds GlaxoSmithKline study code RES11080, Genetics of Chronic Obstructive Lung Disease.publishedVersio