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Silverman, Edwin

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Silverman

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Edwin

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Silverman, Edwin
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    Haploinsufficiency of Hedgehog interacting protein causes increased emphysema induced by cigarette smoke through network rewiring
    (BioMed Central, 2015) Lao, Taotao; Glass, Kimberly; Qiu, Weiliang; Polverino, Francesca; Gupta, Kushagra; Morrow, Jarrett; Mancini, John Dominic; Vuong, Linh; Perrella, Mark; Hersh, Craig; Owen, Caroline; Quackenbush, John; Yuan, Guo-Cheng; Silverman, Edwin; Zhou, Xiaobo
    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.
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    A comparison of visual and quantitative methods to identify interstitial lung abnormalities
    (BioMed Central, 2015) Kliment, Corrine R.; Araki, Tetsuro; Doyle, Tracy; Gao, Wei; Dupuis, Josée; Latourelle, Jeanne C.; Zazueta, Oscar E.; Fernandez, Isis E.; Nishino, Mizuki; Okajima, Yuka; Ross, James; Estépar, Raúl San José; Diaz, Alejandro A.; Lederer, David J.; Schwartz, David A.; Silverman, Edwin; Rosas, Ivan; Washko, George; O’Connor, George T.; Hatabu, Hiroto; Hunninghake, Gary
    Background: Evidence suggests that individuals with interstitial lung abnormalities (ILA) on a chest computed tomogram (CT) may have an increased risk to develop a clinically significant interstitial lung disease (ILD). Although methods used to identify individuals with ILA on chest CT have included both automated quantitative and qualitative visual inspection methods, there has been not direct comparison between these two methods. To investigate this relationship, we created lung density metrics and compared these to visual assessments of ILA. Methods: To provide a comparison between ILA detection methods based on visual assessment we generated measures of high attenuation areas (HAAs, defined by attenuation values between −600 and −250 Hounsfield Units) in >4500 participants from both the COPDGene and Framingham Heart studies (FHS). Linear and logistic regressions were used for analyses. Results: Increased measures of HAAs (in ≥10 % of the lung) were significantly associated with ILA defined by visual inspection in both cohorts (P < 0.0001); however, the positive predictive values were not very high (19 % in COPDGene and 13 % in the FHS). In COPDGene, the association between HAAs and ILA defined by visual assessment were modified by the percentage of emphysema and body mass index. Although increased HAAs were associated with reductions in total lung capacity in both cohorts, there was no evidence for an association between measurement of HAAs and MUC5B promoter genotype in the FHS. Conclusion: Our findings demonstrate that increased measures of lung density may be helpful in determining the severity of lung volume reduction, but alone, are not strongly predictive of ILA defined by visual assessment. Moreover, HAAs were not associated with MUC5B promoter genotype.
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    Genome-wide assessment of gene-by-smoking interactions in COPD
    (Nature Publishing Group UK, 2018) Park, Boram; Koo, So-My; An, Jaehoon; Lee, MoonGyu; Kang, Hae Yeon; Qiao, Dandi; Cho, Michael; Sung, Joohon; Silverman, Edwin; Yang, Hyeon-Jong; Won, Sungho
    Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables—forced expiratory volume in 1 s (FEV1). We found that variations in FEV1 were different among smoking status. Thus, we considered a linear mixed model for association analysis under heteroscedasticity according to smoking status. We found a previously identified locus near SOX9 on chromosome 17 to be the most significant based on a joint test of the main and interaction effects of smoking. Smoking interactions were replicated with Gene-Environment of Interaction and phenotype (GENIE), Multi-Ethnic Study of Atherosclerosis-Lung (MESA-Lung), and COPDGene studies. We found that individuals with minor alleles, rs17765644, rs17178251, rs11870732, and rs4793541, tended to have lower FEV1 values, and lung function decreased much faster with age for smokers. There have been very few reports to replicate a common variant gene-smoking interaction, and our results revealed that statistical models for gene-smoking interaction analyses should be carefully selected.
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    WISARD: workbench for integrated superfast association studies for related datasets
    (BioMed Central, 2018) Lee, Sungyoung; Choi, Sungkyoung; Qiao, Dandi; Cho, Michael; Silverman, Edwin; Park, Taesung; Won, Sungho
    Background: A Mendelian transmission produces phenotypic and genetic relatedness between family members, giving family-based analytical methods an important role in genetic epidemiological studies—from heritability estimations to genetic association analyses. With the advance in genotyping technologies, whole-genome sequence data can be utilized for genetic epidemiological studies, and family-based samples may become more useful for detecting de novo mutations. However, genetic analyses employing family-based samples usually suffer from the complexity of the computational/statistical algorithms, and certain types of family designs, such as incorporating data from extended families, have rarely been used. Results: We present a Workbench for Integrated Superfast Association studies for Related Data (WISARD) programmed in C/C++. WISARD enables the fast and a comprehensive analysis of SNP-chip and next-generation sequencing data on extended families, with applications from designing genetic studies to summarizing analysis results. In addition, WISARD can automatically be run in a fully multithreaded manner, and the integration of R software for visualization makes it more accessible to non-experts. Conclusions: Comparison with existing toolsets showed that WISARD is computationally suitable for integrated analysis of related subjects, and demonstrated that WISARD outperforms existing toolsets. WISARD has also been successfully utilized to analyze the large-scale massive sequencing dataset of chronic obstructive pulmonary disease data (COPD), and we identified multiple genes associated with COPD, which demonstrates its practical value. Electronic supplementary material The online version of this article (10.1186/s12920-018-0345-y) contains supplementary material, which is available to authorized users.
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    Nitric oxide synthase polymorphisms, gene expression and lung function in chronic obstructive pulmonary disease
    (BioMed Central, 2013) Aminuddin, Farzian; Hackett, Tillie-Louise; Stefanowicz, Dorota; Saferali, Aabida; Paré, Peter D; Gulsvik, Amund; Bakke, Per; Cho, Michael; Litonjua, Augusto A.; Lomas, David A; Anderson, Wayne H; Beaty, Terri H; Silverman, Edwin; Sandford, Andrew J
    Background: Due to the pleiotropic effects of nitric oxide (NO) within the lungs, it is likely that NO is a significant factor in the pathogenesis of chronic obstructive pulmonary disease (COPD). The aim of this study was to test for association between single nucleotide polymorphisms (SNPs) in three NO synthase (NOS) genes and lung function, as well as to examine gene expression and protein levels in relation to the genetic variation. Methods: One SNP in each NOS gene (neuronal NOS (NOS1), inducible NOS (NOS2), and endothelial NOS (NOS3)) was genotyped in the Lung Health Study (LHS) and correlated with lung function. One SNP (rs1800779) was also analyzed for association with COPD and lung function in four COPD case–control populations. Lung tissue expression of NOS3 mRNA and protein was tested in individuals of known genotype for rs1800779. Immunohistochemistry of lung tissue was used to localize NOS3 expression. Results: For the NOS3 rs1800779 SNP, the baseline forced expiratory volume in one second in the LHS was significantly higher in the combined AG + GG genotypic groups compared with the AA genotypic group. Gene expression and protein levels in lung tissue were significantly lower in subjects with the AG + GG genotypes than in AA subjects. NOS3 protein was expressed in the airway epithelium and subjects with the AA genotype demonstrated higher NOS3 expression compared with AG and GG individuals. However, we were not able to replicate the associations with COPD or lung function in the other COPD study groups. Conclusions: Variants in the NOS genes were not associated with lung function or COPD status. However, the G allele of rs1800779 resulted in a decrease of NOS3 gene expression and protein levels and this has implications for the numerous disease states that have been associated with this polymorphism.
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    Susceptibility to Chronic Mucus Hypersecretion, a Genome Wide Association Study
    (Public Library of Science, 2014) Dijkstra, Akkelies E.; Smolonska, Joanna; van den Berge, Maarten; Wijmenga, Ciska; Zanen, Pieter; Luinge, Marjan A.; Platteel, Mathieu; Lammers, Jan-Willem; Dahlback, Magnus; Tosh, Kerrie; Hiemstra, Pieter S.; Sterk, Peter J.; Spira, Avi; Vestbo, Jorgen; Nordestgaard, Borge G.; Benn, Marianne; Nielsen, Sune F.; Dahl, Morten; Verschuren, W. Monique; Picavet, H. Susan J.; Smit, Henriette A.; Owsijewitsch, Michael; Kauczor, Hans U.; de Koning, Harry J.; Nizankowska-Mogilnicka, Eva; Mejza, Filip; Nastalek, Pawel; van Diemen, Cleo C.; Cho, Michael; Silverman, Edwin; Crapo, James D.; Beaty, Terri H.; Lomas, David A.; Bakke, Per; Gulsvik, Amund; Bossé, Yohan; Obeidat, M. A.; Loth, Daan W.; Lahousse, Lies; Rivadeneira, Fernando; Uitterlinden, Andre G.; Hofman, Andre; Stricker, Bruno H.; Brusselle, Guy G.; van Duijn, Cornelia M.; Brouwer, Uilke; Koppelman, Gerard H.; Vonk, Judith M.; Nawijn, Martijn C.; Groen, Harry J. M.; Timens, Wim; Boezen, H. Marike; Postma, Dirkje S.
    Background: Chronic mucus hypersecretion (CMH) is associated with an increased frequency of respiratory infections, excess lung function decline, and increased hospitalisation and mortality rates in the general population. It is associated with smoking, but it is unknown why only a minority of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA) study of CMH in Caucasian populations. Methods: GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed by replication and meta-analysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (≥20 pack-years). Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism (SNP). Results: A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25×10−6, OR = 1.17), located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1) on chromosome 3. The risk allele (G) was associated with higher mRNA expression of SATB1 (4.3×10−9) in lung tissue. Presence of CMH was associated with increased SATB1 mRNA expression in bronchial biopsies from COPD patients. SATB1 expression was induced during differentiation of primary human bronchial epithelial cells in culture. Conclusions: Our findings, that SNP rs6577641 is associated with CMH in multiple cohorts and is a cis-eQTL for SATB1, together with our additional observation that SATB1 expression increases during epithelial differentiation provide suggestive evidence that SATB1 is a gene that affects CMH.
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    A diVIsive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease
    (BioMed Central, 2014) Menche, Jörg; Sharma, Amitabh; Cho, Michael; Mayer, Ruth J; Rennard, Stephen I; Celli, Bartolome; Miller, Bruce E; Locantore, Nick; Tal-Singer, Ruth; Ghosh, Soumitra; Larminie, Chris; Bradley, Glyn; Riley, John H; Agusti, Alvar; Silverman, Edwin; Barabasi, Albert-Laszlo
    Background: An important step toward understanding the biological mechanisms underlying a complex disease is a refined understanding of its clinical heterogeneity. Relating clinical and molecular differences may allow us to define more specific subtypes of patients that respond differently to therapeutic interventions. Results: We developed a novel unbiased method called diVIsive Shuffling Approach (VIStA) that identifies subgroups of patients by maximizing the difference in their gene expression patterns. We tested our algorithm on 140 subjects with Chronic Obstructive Pulmonary Disease (COPD) and found four distinct, biologically and clinically meaningful combinations of clinical characteristics that are associated with large gene expression differences. The dominant characteristic in these combinations was the severity of airflow limitation. Other frequently identified measures included emphysema, fibrinogen levels, phlegm, BMI and age. A pathway analysis of the differentially expressed genes in the identified subtypes suggests that VIStA is capable of capturing specific molecular signatures within in each group. Conclusions: The introduced methodology allowed us to identify combinations of clinical characteristics that correspond to clear gene expression differences. The resulting subtypes for COPD contribute to a better understanding of its heterogeneity.
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    A Simplified Score to Quantify Comorbidity in COPD
    (Public Library of Science, 2014) Putcha, Nirupama; Puhan, Milo A.; Drummond, M. Bradley; Han, MeiLan K.; Regan, Elizabeth A.; Hanania, Nicola A.; Martinez, Carlos H.; Foreman, Marilyn; Bhatt, Surya P.; Make, Barry; Ramsdell, Joe; Demeo, Dawn; Barr, R. Graham; Rennard, Stephen I.; Martinez, Fernando; Silverman, Edwin; Crapo, James; Wise, Robert A.; Hansel, Nadia N.
    Importance Comorbidities are common in COPD, but quantifying their burden is difficult. Currently there is a COPD-specific comorbidity index to predict mortality and another to predict general quality of life. We sought to develop and validate a COPD-specific comorbidity score that reflects comorbidity burden on patient-centered outcomes. Materials and Methods Using the COPDGene study (GOLD II-IV COPD), we developed comorbidity scores to describe patient-centered outcomes employing three techniques: 1) simple count, 2) weighted score, and 3) weighted score based upon statistical selection procedure. We tested associations, area under the Curve (AUC) and calibration statistics to validate scores internally with outcomes of respiratory disease-specific quality of life (St. George's Respiratory Questionnaire, SGRQ), six minute walk distance (6MWD), modified Medical Research Council (mMRC) dyspnea score and exacerbation risk, ultimately choosing one score for external validation in SPIROMICS. Results: Associations between comorbidities and all outcomes were comparable across the three scores. All scores added predictive ability to models including age, gender, race, current smoking status, pack-years smoked and FEV1 (p<0.001 for all comparisons). Area under the curve (AUC) was similar between all three scores across outcomes: SGRQ (range 0·7624–0·7676), MMRC (0·7590–0·7644), 6MWD (0·7531–0·7560) and exacerbation risk (0·6831–0·6919). Because of similar performance, the comorbidity count was used for external validation. In the SPIROMICS cohort, the comorbidity count performed well to predict SGRQ (AUC 0·7891), MMRC (AUC 0·7611), 6MWD (AUC 0·7086), and exacerbation risk (AUC 0·7341). Conclusions: Quantifying comorbidity provides a more thorough understanding of the risk for patient-centered outcomes in COPD. A comorbidity count performs well to quantify comorbidity in a diverse population with COPD.
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    A genome-wide association study identifies risk loci for spirometric measures among smokers of European and African ancestry
    (BioMed Central, 2015) Lutz, Sharon M.; Cho, Michael; Young, Kendra; Hersh, Craig; Castaldi, Peter; McDonald, Merry-Lynn N; Regan, Elizabeth; Mattheisen, Manuel; Demeo, Dawn; Parker, Margaret; Foreman, Marilyn; Make, Barry J.; Jensen, Robert L.; Casaburi, Richard; Lomas, David A.; Bhatt, Surya P.; Bakke, Per; Gulsvik, Amund; Crapo, James D.; Beaty, Terri H.; Laird, Nan; Lange, Christoph; Hokanson, John E.; Silverman, Edwin
    Background: Pulmonary function decline is a major contributor to morbidity and mortality among smokers. Post bronchodilator FEV1 and FEV1/FVC ratio are considered the standard assessment of airflow obstruction. We performed a genome-wide association study (GWAS) in 9919 current and former smokers in the COPDGene study (6659 non-Hispanic Whites [NHW] and 3260 African Americans [AA]) to identify associations with spirometric measures (post-bronchodilator FEV1 and FEV1/FVC). We also conducted meta-analysis of FEV1 and FEV1/FVC GWAS in the COPDGene, ECLIPSE, and GenKOLS cohorts (total n = 13,532). Results: Among NHW in the COPDGene cohort, both measures of pulmonary function were significantly associated with SNPs at the 15q25 locus [containing CHRNA3/5, AGPHD1, IREB2, CHRNB4] (lowest p-value = 2.17 × 10−11), and FEV1/FVC was associated with a genomic region on chromosome 4 [upstream of HHIP] (lowest p-value = 5.94 × 10−10); both regions have been previously associated with COPD. For the meta-analysis, in addition to confirming associations to the regions near CHRNA3/5 and HHIP, genome-wide significant associations were identified for FEV1 on chromosome 1 [TGFB2] (p-value = 8.99 × 10−9), 9 [DBH] (p-value = 9.69 × 10−9) and 19 [CYP2A6/7] (p-value = 3.49 × 10−8) and for FEV1/FVC on chromosome 1 [TGFB2] (p-value = 8.99 × 10−9), 4 [FAM13A] (p-value = 3.88 × 10−12), 11 [MMP3/12] (p-value = 3.29 × 10−10) and 14 [RIN3] (p-value = 5.64 × 10−9). Conclusions: In a large genome-wide association study of lung function in smokers, we found genome-wide significant associations at several previously described loci with lung function or COPD. We additionally identified a novel genome-wide significant locus with FEV1 on chromosome 9 [DBH] in a meta-analysis of three study populations. Electronic supplementary material The online version of this article (doi:10.1186/s12863-015-0299-4) contains supplementary material, which is available to authorized users.
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    Sexually-dimorphic targeting of functionally-related genes in COPD
    (BioMed Central, 2014) Glass, Kimberly; Quackenbush, John; Silverman, Edwin; Celli, Bartolome; Rennard, Stephen I; Yuan, Guo-Cheng; Demeo, Dawn
    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.