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Article ; Online: Using methylation data to improve transcription factor binding prediction.

Morgan, Daniel / DeMeo, Dawn L / Glass, Kimberly

Epigenetics

2024 Volume 19, Issue 1, Page(s) 2309826

Abstract: Modelling the regulatory mechanisms that determine cell fate, response to external perturbation, and disease state depends on measuring many factors, a task made more difficult by the plasticity of the epigenome. Scanning the genome for the sequence ... ...

Abstract	Modelling the regulatory mechanisms that determine cell fate, response to external perturbation, and disease state depends on measuring many factors, a task made more difficult by the plasticity of the epigenome. Scanning the genome for the sequence patterns defined by Position Weight Matrices (PWM) can be used to estimate transcription factor (TF) binding locations. However, this approach does not incorporate information regarding the epigenetic context necessary for TF binding. CpG methylation is an epigenetic mark influenced by environmental factors that is commonly assayed in human cohort studies. We developed a framework to score inferred TF binding locations using methylation data. We intersected motif locations identified using PWMs with methylation information captured in both whole-genome bisulfite sequencing and Illumina EPIC array data for six cell lines, scored motif locations based on these data, and compared with experimental data characterizing TF binding (ChIP-seq). We found that for most TFs, binding prediction improves using methylation-based scoring compared to standard PWM-scores. We also illustrate that our approach can be generalized to infer TF binding when methylation information is only proximally available,
MeSH term(s)	Humans ; Binding Sites ; Transcription Factors/genetics ; Transcription Factors/metabolism ; DNA Methylation ; Protein Binding ; Gene Expression Regulation
Chemical Substances	Transcription Factors
Language	English
Publishing date	2024-02-01
Publishing country	United States
Document type	Journal Article
ISSN	1559-2308
ISSN (online)	1559-2308
DOI	10.1080/15592294.2024.2309826
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Article ; Online: Circulating Monocytes Are Predictive and Responsive in Moderate-to-Severe Plaque Psoriasis Subjects Treated with Apremilast.

Larson, Emma L / DeMeo, Dustin P / Young, Andrew B / Margevicius, Seunghee / Rutter, Joseph / Davies, Amanda L / Rohan, Craig A / Korman, Neil J / Travers, Jeffrey B / McCormick, Thomas S / Cooper, Kevin D

The Journal of investigative dermatology

2024

Abstract: Monocytes play a critical role in the inflammation associated with psoriasis, and their abnormalities have been reported as biomarkers of cardiovascular event risk, a psoriasis comorbidity. Monocytic cells in chronic inflammatory disorders express ... ...

Abstract	Monocytes play a critical role in the inflammation associated with psoriasis, and their abnormalities have been reported as biomarkers of cardiovascular event risk, a psoriasis comorbidity. Monocytic cells in chronic inflammatory disorders express elevated levels of cAMP phosphodiesterase. Restoring cAMP levels using the oral cAMP phosphodiesterase-4 inhibitor, apremilast, improves clinical outcomes for a subset of patients with psoriasis. We asked whether aberrant monocyte subsets or transcriptomic pathways can function as biomarkers of psoriasis endotypes that can predict enhanced clinical responses to cAMP phosphodiesterase inhibition. A 16-week open-label study of 22 patients with monocyte flow cytometric and transcriptomic analysis was performed. Subjects with elevated hyperadhesive monocyte doublets at baseline were more likely to be responders to apremilast (P < .0001); 82% of subjects with elevated hyperadhesive monocyte doublets achieved 50% reduction in PASI compared with 46% in those without elevated doublets. We observed a significant reduction in hyperadhesive monocyte-containing doublets and monocyte-platelet aggregates, suggesting an effect of apremilast on the adhesiveness of blood monocytes during chronic inflammation. Monocyte differentially expressed gene transcripts predictive of clinical response uncovered pharmacoendotypes with distinct patterns of nucleotide metabolism, energetics, and differentiation. Further study to understand the basis of drug responsiveness and to develop an apremilast psoriasis treatment algorithm using monocyte-refined gene expression is required to validate and become practical in clinical use, offering patients a test that personalizes their likelihood of clinical response.
Language	English
Publishing date	2024-02-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	80136-7
ISSN	1523-1747 ; 0022-202X
ISSN (online)	1523-1747
ISSN	0022-202X
DOI	10.1016/j.jid.2024.01.034
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Article ; Online: The Effect of Limited English Proficiency on Melanoma Diagnosis: A Retrospective Cross-Sectional Study.

Barzallo, Devin / DeMeo, Dustin / De Souza, Larissa / Carroll, Bryan T

Dermatologic surgery : official publication for American Society for Dermatologic Surgery [et al.

2022 Volume 48, Issue 11, Page(s) 1255–1256

MeSH term(s)	Humans ; Limited English Proficiency ; Cross-Sectional Studies ; Retrospective Studies ; Melanoma/diagnosis
Language	English
Publishing date	2022-09-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	1227586-4
ISSN	1524-4725 ; 1076-0512
ISSN (online)	1524-4725
ISSN	1076-0512
DOI	10.1097/DSS.0000000000003599
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Article ; Online: Optimism is associated with respiratory symptoms and functional status in chronic obstructive pulmonary disease.

Koo, Hyeon-Kyoung / Hoth, Karin F / Make, Barry J / Regan, Elizabeth A / Crapo, James D / Silverman, Edwin K / DeMeo, Dawn L

Respiratory research

2022 Volume 23, Issue 1, Page(s) 19

Abstract: Background: Optimism is the general belief that good things will occur in the future; optimism is modifiable by cognitive behavioral therapy (CBT). Previous studies have associated higher optimism with improved health outcomes and lower all-cause ... ...

Abstract	Background: Optimism is the general belief that good things will occur in the future; optimism is modifiable by cognitive behavioral therapy (CBT). Previous studies have associated higher optimism with improved health outcomes and lower all-cause mortality. Research question: Investigate association between optimism and disease-related characteristics in chronic obstructive pulmonary disease (COPD). Study design and methods: Current and former smokers with/without COPD and Preserved Ratio Impaired Spirometry (PRISm) from the 10-year follow-up visit for the Genetic Epidemiology of COPD (COPDGene) study were included. Optimism was assessed at the 10-year visit using the Life Orientation Test-Revised. Models of optimism as a predictor of lung function, COPD-associated phenotypes including exacerbations, and functional assessments, were adjusted for demographic confounders, smoking status, and comorbidities. Results: Among 1967 subjects, higher optimism was significantly associated with older age, non-Hispanic white race, marital status, quitting smoking status, absence of COPD, and absence of depression. In multivariable analysis, higher optimism was independently associated with fewer prior exacerbations of COPD (coef = - 0.037, P < 0.001). Higher optimism was also related to better MMRC scores (coef = - 0.041, P < 0.001), CAT scores (coef = - 0.391, P < 0.001), SGRQ scores (coef = - 0.958, P < 0.001), BODE index (coef = - 0.059, P < 0.001), and longer 6-min walk distance (coef = 10.227, P < 0.001). After stratification by severity of COPD, these associations with optimism were still significant in all groups. No significant association was observed for cross-sectional FEV Interpretation: Fewer exacerbations and less severe respiratory symptoms and higher functional capacity were associated with higher optimism, which may impact health outcomes in current and former smokers with and without COPD. Optimism is a modifiable trait and these results may further support a role for CBT to improve outcomes in COPD.
MeSH term(s)	Aged ; Aged, 80 and over ; Comorbidity ; Cross-Sectional Studies ; Disease Progression ; Female ; Follow-Up Studies ; Forced Expiratory Volume/physiology ; Forecasting ; Functional Status ; Humans ; Lung/physiopathology ; Male ; Middle Aged ; Pulmonary Disease, Chronic Obstructive/diagnosis ; Pulmonary Disease, Chronic Obstructive/physiopathology ; Quality of Life ; Retrospective Studies ; Severity of Illness Index ; Smoking/adverse effects ; Smoking/physiopathology ; Spirometry ; Surveys and Questionnaires
Language	English
Publishing date	2022-01-29
Publishing country	England
Document type	Journal Article ; Multicenter Study ; Observational Study
ZDB-ID	2041675-1
ISSN	1465-993X ; 1465-993X
ISSN (online)	1465-993X
ISSN	1465-993X
DOI	10.1186/s12931-021-01922-6
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Article ; Online: Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue.

Hobbs, Brian D / Morrow, Jarrett D / Wang, Xu-Wen / Liu, Yang-Yu / DeMeo, Dawn L / Hersh, Craig P / Celli, Bartolome R / Bueno, Raphael / Criner, Gerard J / Silverman, Edwin K / Cho, Michael H

BMC pulmonary medicine

2023 Volume 23, Issue 1, Page(s) 115

Abstract: Background: Chronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD ... ...

Abstract	Background: Chronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD heterogeneity is captured in omics of lung tissue is not known. Methods: We clustered gene expression and methylation data in 78 lung tissue samples from former smokers with normal lung function or severe COPD. We applied two integrative omics clustering methods: (1) Similarity Network Fusion (SNF) and (2) Entropy-Based Consensus Clustering (ECC). Results: SNF clusters were not significantly different by the percentage of COPD cases (48.8% vs. 68.6%, p = 0.13), though were different according to median forced expiratory volume in one second (FEV Conclusions: Unsupervised clustering analysis from integrated gene expression and methylation data in lung tissue resulted in clusters with modest concordance with COPD, though were enriched in pathways potentially contributing to COPD-related pathology and heterogeneity.
MeSH term(s)	Humans ; Smoking ; Pulmonary Disease, Chronic Obstructive ; Lung ; Forced Expiratory Volume ; Cluster Analysis
Language	English
Publishing date	2023-04-11
Publishing country	England
Document type	Journal Article
ZDB-ID	2059871-3
ISSN	1471-2466 ; 1471-2466
ISSN (online)	1471-2466
ISSN	1471-2466
DOI	10.1186/s12890-023-02389-5
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Article ; Online: Early Diagnosis and Treatment of Chronic Obstructive Pulmonary Disease: The Costs and Benefits of Case Finding.

Aaron, Shawn D / Montes de Oca, Maria / Celli, Bartolome / Bhatt, Surya P / Bourbeau, Jean / Criner, Gerard J / DeMeo, Dawn L / Halpin, David M G / Han, MeiLan K / Hurst, John R / Krishnan, Jamuna K / Mannino, David / van Boven, Job F M / Vogelmeier, Claus F / Wedzicha, Jadwiga A / Yawn, Barbara P / Martinez, Fernando J

American journal of respiratory and critical care medicine

2024 Volume 209, Issue 8, Page(s) 928–937

MeSH term(s)	Humans ; Cost-Benefit Analysis ; Pulmonary Disease, Chronic Obstructive/diagnosis ; Pulmonary Disease, Chronic Obstructive/therapy ; Smoking ; Early Diagnosis
Language	English
Publishing date	2024-02-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	1180953-x
ISSN	1535-4970 ; 0003-0805 ; 1073-449X
ISSN (online)	1535-4970
ISSN	0003-0805 ; 1073-449X
DOI	10.1164/rccm.202311-2120PP
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Article ; Online: DRAGON: Determining Regulatory Associations using Graphical models on multi-Omic Networks.

Shutta, Katherine H / Weighill, Deborah / Burkholz, Rebekka / Guebila, Marouen Ben / DeMeo, Dawn L / Zacharias, Helena U / Quackenbush, John / Altenbuchinger, Michael

Nucleic acids research

2022 Volume 51, Issue 3, Page(s) e15

Abstract: 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 ... ...

Abstract	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).
MeSH term(s)	Humans ; Multiomics ; Software ; Computer Simulation ; Transcriptome ; Neoplasms/genetics ; Gene Regulatory Networks
Language	English
Publishing date	2022-12-19
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkac1157
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Article ; Online: A statistical physics approach for disease module detection.

Wang, Xu-Wen / Qiao, Dandi / Cho, Michael H / DeMeo, Dawn L / Silverman, Edwin K / Liu, Yang-Yu

Genome research

2022 Volume 32, Issue 10, Page(s) 1918–1929

Abstract: Extensive evidence indicates that the pathobiological processes of a complex disease are associated with perturbation in specific neighborhoods of the human protein-protein interaction (PPI) network (also known as the interactome), often referred to as ... ...

Abstract	Extensive evidence indicates that the pathobiological processes of a complex disease are associated with perturbation in specific neighborhoods of the human protein-protein interaction (PPI) network (also known as the interactome), often referred to as the disease module. Many computational methods have been developed to integrate the interactome and omics profiles to extract context-dependent disease modules. Yet, existing methods all have fundamental limitations in terms of rigor and/or efficiency. Here, we developed a statistical physics approach based on the random-field Ising model (RFIM) for disease module detection, which is both mathematically rigorous and computationally efficient. We applied our RFIM approach to genome-wide association studies (GWAS) of ten complex diseases to examine its performance for disease module detection. We found that our RFIM approach outperforms existing methods in terms of computational efficiency, connectivity of disease modules, and robustness to the interactome incompleteness.
MeSH term(s)	Humans ; Genome-Wide Association Study/methods ; Protein Interaction Maps ; Physics ; Algorithms
Language	English
Publishing date	2022-10-11
Publishing country	United States
Document type	Journal Article
ZDB-ID	1284872-4
ISSN	1549-5469 ; 1088-9051 ; 1054-9803
ISSN (online)	1549-5469
ISSN	1088-9051 ; 1054-9803
DOI	10.1101/gr.276690.122
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Article ; Online: DNA methylation perturbations may link altered development and aging in the lung.

Kachroo, Priyadarshini / Morrow, Jarrett D / Vyhlidal, Carrie A / Gaedigk, Roger / Silverman, Edwin K / Weiss, Scott T / Tantisira, Kelan G / DeMeo, Dawn L

Aging

2021 Volume 13, Issue 2, Page(s) 1742–1764

Abstract: Fetal perturbations in DNA methylation during lung development may reveal insights into the enduring impacts on adult lung health and disease during aging that have not been explored altogether before. We studied the association between genome-wide DNA- ... ...

Abstract	Fetal perturbations in DNA methylation during lung development may reveal insights into the enduring impacts on adult lung health and disease during aging that have not been explored altogether before. We studied the association between genome-wide DNA-methylation and post-conception age in fetal-lung (n=78, 42 exposed to in-utero-smoke (IUS)) tissue and chronological age in adult-lung tissue (n=160, 114 with Chronic Obstructive Pulmonary Disease) using multi-variate linear regression models with covariate adjustment and tested for effect modification by phenotypes. Overlapping age-associations were evaluated for functional and tissue-specific enrichment using the Genotype-Tissue-Expression (GTEx) project. We identified 244 age-associated differentially methylated positions and 878 regions overlapping between fetal and adult-lung tissues. Hyper-methylated CpGs (96%) were enriched in transcription factor activity (FDR adjusted P=2x10
MeSH term(s)	Aged ; Aging/genetics ; Aging/metabolism ; Aging/pathology ; CpG Islands ; DNA Methylation ; Epigenesis, Genetic ; Female ; Humans ; Lung/metabolism ; Lung/pathology ; Male ; Middle Aged ; Phenotype ; Pulmonary Disease, Chronic Obstructive/genetics ; Pulmonary Disease, Chronic Obstructive/metabolism ; Pulmonary Disease, Chronic Obstructive/pathology
Language	English
Publishing date	2021-01-19
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	1945-4589
ISSN (online)	1945-4589
DOI	10.18632/aging.202544
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Article: Computational Deconvolution of Cell Type-Specific Gene Expression in COPD and IPF Lungs Reveals Disease Severity Associations.

Ryu, Min Hyung / Yun, Jeong H / Kim, Kangjin / Gentili, Michele / Ghosh, Auyon / Sciurba, Frank / Barwick, Lucas / Limper, Andrew / Criner, Gerard / Brown, Kevin K / Wise, Robert / Martinez, Fernando J / Flaherty, Kevin R / Cho, Michael H / Castaldi, Peter J / DeMeo, Dawn L / Silverman, Edwin K / Hersh, Craig P / Morrow, Jarrett D

medRxiv : the preprint server for health sciences

2024

Abstract: Rationale: Chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are debilitating diseases associated with divergent histopathological changes in the lungs. At present, due to cost and technical limitations, profiling cell ...

Abstract	Rationale: Chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are debilitating diseases associated with divergent histopathological changes in the lungs. At present, due to cost and technical limitations, profiling cell types is not practical in large epidemiology cohorts (n>1000). Here, we used computational deconvolution to identify cell types in COPD and IPF lungs whose abundances and cell type-specific gene expression are associated with disease diagnosis and severity. Methods: We analyzed lung tissue RNA-seq data from 1026 subjects (COPD, n=465; IPF, n=213; control, n=348) from the Lung Tissue Research Consortium. We performed RNA-seq deconvolution, querying thirty-eight discrete cell-type varieties in the lungs. We tested whether deconvoluted cell-type abundance and cell type-specific gene expression were associated with disease severity. Results: The abundance score of twenty cell types significantly differed between IPF and control lungs. In IPF subjects, eleven and nine cell types were significantly associated with forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO), respectively. Aberrant basaloid cells, a rare cells found in fibrotic lungs, were associated with worse FVC and DLCO in IPF subjects, indicating that this aberrant epithelial population increased with disease severity. Alveolar type 1 and vascular endothelial (VE) capillary A were decreased in COPD lungs compared to controls. An increase in macrophages and classical monocytes was associated with lower DLCO in IPF and COPD subjects. In both diseases, lower non-classical monocytes and VE capillary A cells were associated with increased disease severity. Alveolar type 2 cells and alveolar macrophages had the highest number of genes with cell type-specific differential expression by disease severity in COPD and IPF. In IPF, genes implicated in the pathogenesis of IPF, such as matrix metallopeptidase 7, growth differentiation factor 15, and eph receptor B2, were associated with disease severity in a cell type-specific manner. Conclusion: Utilization of RNA-seq deconvolution enabled us to pinpoint cell types present in the lungs that are associated with the severity of COPD and IPF. This knowledge offers valuable insight into the alterations within tissues in more advanced illness, ultimately providing a better understanding of the underlying pathological processes that drive disease progression.
Language	English
Publishing date	2024-04-24
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.03.26.24304775
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