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Saferali A, Kim W, Chase RP, Vollmers C, Silverman EK, Cho MH, Castaldi PJ, Hersh CP. Overlap between COPD genetic association results and transcriptional quantitative trait loci. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.08.24310079. [PMID: 39040180 PMCID: PMC11261918 DOI: 10.1101/2024.07.08.24310079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Rationale Genome-wide association studies (GWAS) have identified multiple genetic loci associated with chronic obstructive pulmonary disease (COPD). When integrated with GWAS results, expression quantitative trait locus (eQTL) studies can provide insight into biological mechanisms involved in disease by identifying single nucleotide polymorphisms (SNPs) that contribute to whole gene expression. However, there are multiple genetically driven regulatory and isoform-specific effects which cannot be detected in traditional eQTL analyses. Here, we identify SNPs that are associated with alternative splicing (sQTL) in addition to eQTLs to identify novel functions for COPD associated genetic variants. Methods We performed RNA sequencing on whole blood from 3743 subjects in the COPDGene Study. RNA sequencing data from lung tissue of 1241 subjects from the Lung Tissue Research Consortium (LTRC), and whole genome sequencing data on all subjects. Associations between all SNPs within 1000 kb of a gene (cis-) and splice and gene expression quantifications were tested using tensorQTL. In COPDGene a total of 11,869,333 SNPs were tested for association with 58,318 splice clusters, and 8,792,206 SNPs were tested for association with 70,094 splice clusters in LTRC. We assessed colocalization with COPD-associated SNPs from a published GWAS[1]. Results After adjustment for multiple statistical testing, we identified 28,110 splice-sites corresponding to 3,889 unique genes that were significantly associated with genotype in COPDGene whole blood, and 58,258 splice-sites corresponding to 10,307 unique genes associated with genotype in LTRC lung tissue. We found 7,576 sQTL splice-sites corresponding to 2,110 sQTL genes were shared between whole blood and lung, while 20,534 sQTL splice-sites in 3,518 genes were unique to blood and 50,682 splice-sites in 9,677 genes were unique to lung. To determine what proportion of COPD-associated SNPs were associated with transcriptional splicing, we performed colocalization analysis between COPD GWAS and sQTL data, and found that 38 genomic windows, corresponding to 38 COPD GWAS loci had evidence of colocalization between QTLs and COPD. The top five colocalizations between COPD and lung sQTLs include NPNT , FBXO38 , HHIP , NTN4 and BTC . Conclusions A total of 38 COPD GWAS loci contain evidence of sQTLs, suggesting that analysis of sQTLs in whole blood and lung tissue can provide novel insights into disease mechanisms.
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Seo M, Park S, Kim W, Jung JY, Bak SH, Silverman EK, Park J. Multi-center Korean cohort study based on RNA-sequencing data targeting COPD patients. Sci Data 2024; 11:593. [PMID: 38844491 PMCID: PMC11156965 DOI: 10.1038/s41597-024-03389-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 05/20/2024] [Indexed: 06/09/2024] Open
Abstract
In 2023, WHO ranked chronic obstructive pulmonary disease (COPD) as the third leading cause of death, with 3.23 million fatalities in 2019. The intricate nature of the disease, which is influenced by genetics, environment, and lifestyle, is evident. The effect of air pollution and changes in atmospheric substances because of global warming highlight the need for this research. These environmental shifts are associated with the emergence of various respiratory infections such as COVID-19. RNA sequencing is pivotal in airway diseases, including COPD, as it enables comprehensive transcriptome analysis, biomarker discovery, and uncovers novel pathways. It facilitates personalized medicine by tracking dynamic changes in gene expression in response to various triggers. However, the limited research on East Asian populations may overlook the unique nuances of COPD development and progression. Bridging this gap and using peripheral blood samples for systemic analysis are crucial for comprehensive and globally applicable COPD diagnosis and treatment.
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Affiliation(s)
- Minseok Seo
- Department of Computer and Information Science, Korea University, Sejong, Republic of Korea
| | - Sinwoo Park
- Department of Computer and Information Science, Korea University, Sejong, Republic of Korea
| | - WooJin Kim
- Department of Internal Medicine, School of Medicine, Kangwon National University, Kangwon National University Hospital, Chuncheon, Republic of Korea
| | - Ji Ye Jung
- Division of Pulmonology, Department of Internal Medicine, Institute of Chest Diseases, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - So Hyeon Bak
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Edwin K Silverman
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jinkyeong Park
- Department of Pulmonary, Allergy and Critical Care Medicine, Kyung Hee University College of Medicine, Kyung Hee University Hospital at Gangdong, Seoul, Republic of Korea.
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Zhuang Y, Xing F, Ghosh D, Hobbs BD, Hersh CP, Banaei-Kashani F, Bowler RP, Kechris K. Deep learning on graphs for multi-omics classification of COPD. PLoS One 2023; 18:e0284563. [PMID: 37083575 PMCID: PMC10121008 DOI: 10.1371/journal.pone.0284563] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 04/03/2023] [Indexed: 04/22/2023] Open
Abstract
Network approaches have successfully been used to help reveal complex mechanisms of diseases including Chronic Obstructive Pulmonary Disease (COPD). However despite recent advances, we remain limited in our ability to incorporate protein-protein interaction (PPI) network information with omics data for disease prediction. New deep learning methods including convolution Graph Neural Network (ConvGNN) has shown great potential for disease classification using transcriptomics data and known PPI networks from existing databases. In this study, we first reconstructed the COPD-associated PPI network through the AhGlasso (Augmented High-Dimensional Graphical Lasso Method) algorithm based on one independent transcriptomics dataset including COPD cases and controls. Then we extended the existing ConvGNN methods to successfully integrate COPD-associated PPI, proteomics, and transcriptomics data and developed a prediction model for COPD classification. This approach improves accuracy over several conventional classification methods and neural networks that do not incorporate network information. We also demonstrated that the updated COPD-associated network developed using AhGlasso further improves prediction accuracy. Although deep neural networks often achieve superior statistical power in classification compared to other methods, it can be very difficult to explain how the model, especially graph neural network(s), makes decisions on the given features and identifies the features that contribute the most to prediction generally and individually. To better explain how the spectral-based Graph Neural Network model(s) works, we applied one unified explainable machine learning method, SHapley Additive exPlanations (SHAP), and identified CXCL11, IL-2, CD48, KIR3DL2, TLR2, BMP10 and several other relevant COPD genes in subnetworks of the ConvGNN model for COPD prediction. Finally, Gene Ontology (GO) enrichment analysis identified glycosaminoglycan, heparin signaling, and carbohydrate derivative signaling pathways significantly enriched in the top important gene/proteins for COPD classifications.
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Affiliation(s)
- Yonghua Zhuang
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
- Biostatistics Shared Resource, University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Fuyong Xing
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Debashis Ghosh
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Brian D. Hobbs
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Craig P. Hersh
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Farnoush Banaei-Kashani
- Department of Computer Science and Engineering, University of Colorado Denver, Denver, CO, United States of America
| | | | - Katerina Kechris
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
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Hobbs BD, Morrow JD, Wang XW, Liu YY, DeMeo DL, Hersh CP, Celli BR, Bueno R, Criner GJ, Silverman EK, Cho MH. Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue. BMC Pulm Med 2023; 23:115. [PMID: 37041558 PMCID: PMC10091624 DOI: 10.1186/s12890-023-02389-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 03/15/2023] [Indexed: 04/13/2023] Open
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 (FEV1) % predicted (82 vs. 31, p = 0.017). In contrast, the ECC clusters showed stronger evidence of separation by COPD case status (48.2% vs. 81.8%, p = 0.013) and similar stratification by median FEV1% predicted (82 vs. 30.5, p = 0.0059). ECC clusters using both gene expression and methylation were identical to the ECC clustering solution generated using methylation data alone. Both methods selected clusters with differentially expressed transcripts enriched for interleukin signaling and immunoregulatory interactions between lymphoid and non-lymphoid cells. 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.
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Affiliation(s)
- Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA.
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
| | - Xu-Wen Wang
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Bartolome R Celli
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Raphael Bueno
- Division of Thoracic Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Gerard J Criner
- Division of Pulmonary and Critical Care Medicine, Temple University School of Medicine, Philadelphia, PA, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Ave, Rm 460, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Buschur KL, Riley C, Saferali A, Castaldi P, Zhang G, Aguet F, Ardlie KG, Durda P, Craig Johnson W, Kasela S, Liu Y, Manichaikul A, Rich SS, Rotter JI, Smith J, Taylor KD, Tracy RP, Lappalainen T, Graham Barr R, Sciurba F, Hersh CP, Benos PV. Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis. Respir Res 2023; 24:30. [PMID: 36698131 PMCID: PMC9875487 DOI: 10.1186/s12931-023-02316-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 01/05/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) varies significantly in symptomatic and physiologic presentation. Identifying disease subtypes from molecular data, collected from easily accessible blood samples, can help stratify patients and guide disease management and treatment. METHODS Blood gene expression measured by RNA-sequencing in the COPDGene Study was analyzed using a network perturbation analysis method. Each COPD sample was compared against a learned reference gene network to determine the part that is deregulated. Gene deregulation values were used to cluster the disease samples. RESULTS The discovery set included 617 former smokers from COPDGene. Four distinct gene network subtypes are identified with significant differences in symptoms, exercise capacity and mortality. These clusters do not necessarily correspond with the levels of lung function impairment and are independently validated in two external cohorts: 769 former smokers from COPDGene and 431 former smokers in the Multi-Ethnic Study of Atherosclerosis (MESA). Additionally, we identify several genes that are significantly deregulated across these subtypes, including DSP and GSTM1, which have been previously associated with COPD through genome-wide association study (GWAS). CONCLUSIONS The identified subtypes differ in mortality and in their clinical and functional characteristics, underlining the need for multi-dimensional assessment potentially supplemented by selected markers of gene expression. The subtypes were consistent across cohorts and could be used for new patient stratification and disease prognosis.
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Affiliation(s)
- Kristina L Buschur
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Joint CMU-Pitt PhD Program in Computational Biology, Pittsburgh, PA, USA
- Division of General Medicine, Columbia University Medical Center, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Craig Riley
- Division of Pulmonary Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Aabida Saferali
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Peter Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Grace Zhang
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Francois Aguet
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Peter Durda
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Silva Kasela
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Yongmei Liu
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Josh Smith
- Northwest Genome Center, University of Washington, Seattle, WA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Russell P Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Biochemistry, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - R Graham Barr
- Division of General Medicine, Columbia University Medical Center, New York, NY, USA
| | - Frank Sciurba
- Division of Pulmonary Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Panayiotis V Benos
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
- Joint CMU-Pitt PhD Program in Computational Biology, Pittsburgh, PA, USA.
- Department of Epidemiology, University of Florida, 2004 Mowry Rd, Gainesville, FL, 32603, USA.
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6
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Morrow JD, Castaldi PJ, Chase RP, Yun JH, Kinney GL, Silverman EK, Hersh CP. Hepatitis C and HIV detection by blood RNA-sequencing in cohort of smokers. Sci Rep 2023; 13:1357. [PMID: 36693932 PMCID: PMC9873751 DOI: 10.1038/s41598-023-28156-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 01/13/2023] [Indexed: 01/26/2023] Open
Abstract
Detection of viruses by RNA and DNA sequencing has improved the understanding of the human virome. We sought to identify blood viral signatures through secondary use of RNA-sequencing (RNA-seq) data in a large study cohort. The ability to reveal undiagnosed infections with public health implications among study subjects with available sequencing data could enable epidemiologic surveys and may lead to diagnosis and therapeutic interventions, leveraging existing research data in a clinical context. We detected viral RNA in peripheral blood RNA-seq data from a COPD-enriched population of current and former smokers. Correlation between viral detection and both reported infections and relevant disease outcomes was evaluated. We identified Hepatitis C virus RNA in 228 subjects and HIV RNA in 30 subjects. Overall, we observed 31 viral species, including Epstein-Barr virus and Cytomegalovirus. We observed an enrichment of Hepatitis C and HIV infections among subjects reporting liver disease and HIV infections, respectively. Higher interferon expression scores were observed in the subjects with Hepatitis C and HIV infections. Through secondary use of RNA-seq from a cohort of current and former smokers, we detected peripheral blood viral signatures. We identified HIV and Hepatitis C virus (HCV), highlighting potential public health implications for the approach described this study. We observed correlations with reported infections, chronic infection outcomes and the host transcriptomic response, providing evidence to support the validity of the approach.
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Affiliation(s)
- Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.
| | - Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Robert P Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Jeong H Yun
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Gregory L Kinney
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
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Mechanism of Action of Decitabine in the Treatment of Acute Myeloid Leukemia by Regulating LINC00599. Anal Cell Pathol (Amst) 2023; 2023:2951519. [PMID: 36874552 PMCID: PMC9977558 DOI: 10.1155/2023/2951519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 02/03/2023] [Accepted: 02/04/2023] [Indexed: 02/24/2023] Open
Abstract
Objective Acute myeloid leukemia (AML) is a heterogeneous malignancy with a low long-term survival rate. The aim of this study was to investigate the effects of decitabine (DAC) treatment cell proliferation and apoptosis in AML and role of the expression of LINC00599 and, consequently, miR-135a-5p. Materials and Methods Human promyelocytic leukemia cells (HL-60) and human acute lymphatic leukemia (CCRF-CEM) cells were treated with various concentrations of DAC. Cell proliferation in each group was detected using the cell counting kit 8. For each group, apoptosis and reactive oxygen species (ROS) levels were detected using flow cytometry. Reverse transcription polymerase chain reaction (RT-PCR) was performed to examine the expression of lncRNA LINC00599. The expression of apoptosis-related proteins was analyzed using western blotting. The regulatory relationship between miR-135a-5p and LINC00599 was verified by constructing miR-135a-5p mimics, miR-135a-5p inhibit, wild type LINC00599 3'-untranslated region (UTR), and mutant LINC00599 3'-UTR. Ki-67 expression in the tumor tissues of nude mice was detected using immunofluorescent assays. Results Both DAC and LINC00599 Inhibit groups were able to significantly reduce the proliferation of HL60 and CCRF-CEM cells, increase apoptosis, upregulate the expression of Bad, cleaved caspase-3, and miR-135a-5p, downregulate the expression of Bcl-2, and elevate ROS levels in cells, with these effects being more pronounced after combined treatment with DAC and LINC00599 Inhibit. In comparison to mimic NC, the miR-135a-5p mimic group significantly decreased the relative fluorescence activity ratio of LINC00599 3'-UTR wild-type CCRF-CEM cells. The LINC00599 Inhibit and miR-135a-5p mimic groups exhibited substantially reduced proliferation of HL60 and CCRF-CEM cells, increased apoptosis, upregulated Bad, cleaved caspase-3, and miR-135a-5p expression, along with downregulated Bcl-2 and LINC00599 expression and increased ROS levels in cells; these effects were more pronounced after LINC00599 Inhibit was combined with miR-135a-5p mimics. In vivo experiments revealed that both DAC and LINC00599 Inhibit were able to considerably reduce the long diameter, short meridian, volume, and mass of tumors, increase miR-135a-5p expression, and decrease LINC00599 and ki-67 expression in tumor tissues of nude mice. This effect was more pronounced when the DAC and LINC00599 Inhibit were used in combination. Conclusion DAC regulates the expression of miR-135a-5p by regulating the expression of LINC00599, which in turn affects cell proliferation, apoptosis, and tumor proliferation. Our findings provide a theoretical basis for improving the clinical outcome of AML.
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Majarian TD, Bentley AR, Laville V, Brown MR, Chasman DI, de Vries PS, Feitosa MF, Franceschini N, Gauderman WJ, Marchek C, Levy D, Morrison AC, Province M, Rao DC, Schwander K, Sung YJ, Rotimi CN, Aschard H, Gu CC, Manning AK. Multi-omics insights into the biological mechanisms underlying statistical gene-by-lifestyle interactions with smoking and alcohol consumption. Front Genet 2022; 13:954713. [PMID: 36544485 PMCID: PMC9760722 DOI: 10.3389/fgene.2022.954713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 11/18/2022] [Indexed: 12/12/2022] Open
Abstract
Though both genetic and lifestyle factors are known to influence cardiometabolic outcomes, less attention has been given to whether lifestyle exposures can alter the association between a genetic variant and these outcomes. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium's Gene-Lifestyle Interactions Working Group has recently published investigations of genome-wide gene-environment interactions in large multi-ancestry meta-analyses with a focus on cigarette smoking and alcohol consumption as lifestyle factors and blood pressure and serum lipids as outcomes. Further description of the biological mechanisms underlying these statistical interactions would represent a significant advance in our understanding of gene-environment interactions, yet accessing and harmonizing individual-level genetic and 'omics data is challenging. Here, we demonstrate the coordinated use of summary-level data for gene-lifestyle interaction associations on up to 600,000 individuals, differential methylation data, and gene expression data for the characterization and prioritization of loci for future follow-up analyses. Using this approach, we identify 48 genes for which there are multiple sources of functional support for the identified gene-lifestyle interaction. We also identified five genes for which differential expression was observed by the same lifestyle factor for which a gene-lifestyle interaction was found. For instance, in gene-lifestyle interaction analysis, the T allele of rs6490056 (ALDH2) was associated with higher systolic blood pressure, and a larger effect was observed in smokers compared to non-smokers. In gene expression studies, this allele is associated with decreased expression of ALDH2, which is part of a major oxidative pathway. Other results show increased expression of ALDH2 among smokers. Oxidative stress is known to contribute to worsening blood pressure. Together these data support the hypothesis that rs6490056 reduces expression of ALDH2, which raises oxidative stress, leading to an increase in blood pressure, with a stronger effect among smokers, in whom the burden of oxidative stress is greater. Other genes for which the aggregation of data types suggest a potential mechanism include: GCNT4×current smoking (HDL), PTPRZ1×ever-smoking (HDL), SYN2×current smoking (pulse pressure), and TMEM116×ever-smoking (mean arterial pressure). This work demonstrates the utility of careful curation of summary-level data from a variety of sources to prioritize gene-lifestyle interaction loci for follow-up analyses.
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Affiliation(s)
- Timothy D. Majarian
- Program in Metabolism, Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, United States
| | - Vincent Laville
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, France
| | - Michael R. Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - W. James Gauderman
- Biostatistics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States
| | - Casey Marchek
- Program in Metabolism, Broad Institute of MIT and Harvard, Cambridge, MA, United States,Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, United States
| | - Daniel Levy
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MA, United States
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Michael Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Dabeeru C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Karen Schwander
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States,Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Yun Ju Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, United States
| | - Hugues Aschard
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, France,Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - C. Charles Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Alisa K. Manning
- Program in Metabolism, Broad Institute of MIT and Harvard, Cambridge, MA, United States,Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, United States,Department of Medicine and Harvard Medical School, Boston, MA, United States,*Correspondence: Alisa K. Manning,
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9
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Palzer EF, Wendt CH, Bowler RP, Hersh CP, Safo SE, Lock EF. sJIVE: Supervised Joint and Individual Variation Explained. Comput Stat Data Anal 2022; 175:107547. [PMID: 36119152 PMCID: PMC9481062 DOI: 10.1016/j.csda.2022.107547] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Analyzing multi-source data, which are multiple views of data on the same subjects, has become increasingly common in molecular biomedical research. Recent methods have sought to uncover underlying structure and relationships within and/or between the data sources, and other methods have sought to build a predictive model for an outcome using all sources. However, existing methods that do both are presently limited because they either (1) only consider data structure shared by all datasets while ignoring structures unique to each source, or (2) they extract underlying structures first without consideration to the outcome. The proposed method, supervised joint and individual variation explained (sJIVE), can simultaneously (1) identify shared (joint) and source-specific (individual) underlying structure and (2) build a linear prediction model for an outcome using these structures. These two components are weighted to compromise between explaining variation in the multi-source data and in the outcome. Simulations show sJIVE to outperform existing methods when large amounts of noise are present in the multi-source data. An application to data from the COPDGene study explores gene expression and proteomic patterns associated with lung function.
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Affiliation(s)
- Elise F. Palzer
- Division of Biostatistics, University of Minnesota, Minneapolis, 55455, USA
| | - Christine H. Wendt
- Division of Pulmonary, Allergy and Critical Care, University of Minnesota, Minneapolis, 55455, USA
| | - Russell P. Bowler
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, National Jewish Health, Denver, CO, USA
| | - Craig P. Hersh
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Sandra E. Safo
- Division of Biostatistics, University of Minnesota, Minneapolis, 55455, USA
| | - Eric F. Lock
- Division of Biostatistics, University of Minnesota, Minneapolis, 55455, USA
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10
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Vieujean S, Caron B, Haghnejad V, Jouzeau JY, Netter P, Heba AC, Ndiaye NC, Moulin D, Barreto G, Danese S, Peyrin-Biroulet L. Impact of the Exposome on the Epigenome in Inflammatory Bowel Disease Patients and Animal Models. Int J Mol Sci 2022; 23:7611. [PMID: 35886959 PMCID: PMC9321337 DOI: 10.3390/ijms23147611] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/05/2022] [Accepted: 07/06/2022] [Indexed: 02/07/2023] Open
Abstract
Inflammatory bowel diseases (IBD) are chronic inflammatory disorders of the gastrointestinal tract that encompass two main phenotypes, namely Crohn's disease and ulcerative colitis. These conditions occur in genetically predisposed individuals in response to environmental factors. Epigenetics, acting by DNA methylation, post-translational histones modifications or by non-coding RNAs, could explain how the exposome (or all environmental influences over the life course, from conception to death) could influence the gene expression to contribute to intestinal inflammation. We performed a scoping search using Medline to identify all the elements of the exposome that may play a role in intestinal inflammation through epigenetic modifications, as well as the underlying mechanisms. The environmental factors epigenetically influencing the occurrence of intestinal inflammation are the maternal lifestyle (mainly diet, the occurrence of infection during pregnancy and smoking); breastfeeding; microbiota; diet (including a low-fiber diet, high-fat diet and deficiency in micronutrients); smoking habits, vitamin D and drugs (e.g., IBD treatments, antibiotics and probiotics). Influenced by both microbiota and diet, short-chain fatty acids are gut microbiota-derived metabolites resulting from the anaerobic fermentation of non-digestible dietary fibers, playing an epigenetically mediated role in the integrity of the epithelial barrier and in the defense against invading microorganisms. Although the impact of some environmental factors has been identified, the exposome-induced epimutations in IBD remain a largely underexplored field. How these environmental exposures induce epigenetic modifications (in terms of duration, frequency and the timing at which they occur) and how other environmental factors associated with IBD modulate epigenetics deserve to be further investigated.
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Affiliation(s)
- Sophie Vieujean
- Hepato-Gastroenterology and Digestive Oncology, University Hospital CHU of Liège, 4000 Liege, Belgium;
| | - Bénédicte Caron
- Department of Gastroenterology NGERE (INSERM U1256), Nancy University Hospital, University of Lorraine, Vandœuvre-lès-Nancy, F-54052 Nancy, France; (B.C.); (V.H.)
| | - Vincent Haghnejad
- Department of Gastroenterology NGERE (INSERM U1256), Nancy University Hospital, University of Lorraine, Vandœuvre-lès-Nancy, F-54052 Nancy, France; (B.C.); (V.H.)
| | - Jean-Yves Jouzeau
- CNRS (French National Centre for Scientific Research), Laboratoire IMoPA, Université de Lorraine, UMR 7365, F-54000 Nancy, France; (J.-Y.J.); (P.N.); (D.M.); (G.B.)
| | - Patrick Netter
- CNRS (French National Centre for Scientific Research), Laboratoire IMoPA, Université de Lorraine, UMR 7365, F-54000 Nancy, France; (J.-Y.J.); (P.N.); (D.M.); (G.B.)
| | - Anne-Charlotte Heba
- NGERE (Nutrition-Genetics and Exposure to Environmental Risks), National Institute of Health and Medical Research, University of Lorraine, F-54000 Nancy, France; (A.-C.H.); (N.C.N.)
| | - Ndeye Coumba Ndiaye
- NGERE (Nutrition-Genetics and Exposure to Environmental Risks), National Institute of Health and Medical Research, University of Lorraine, F-54000 Nancy, France; (A.-C.H.); (N.C.N.)
| | - David Moulin
- CNRS (French National Centre for Scientific Research), Laboratoire IMoPA, Université de Lorraine, UMR 7365, F-54000 Nancy, France; (J.-Y.J.); (P.N.); (D.M.); (G.B.)
| | - Guillermo Barreto
- CNRS (French National Centre for Scientific Research), Laboratoire IMoPA, Université de Lorraine, UMR 7365, F-54000 Nancy, France; (J.-Y.J.); (P.N.); (D.M.); (G.B.)
- Lung Cancer Epigenetics, Max-Planck-Institute for Heart and Lung Research, 61231 Bad Nauheim, Germany
- International Laboratory EPIGEN, Consejo de Ciencia y Tecnología del Estado de Puebla (CONCYTEP), Universidad de la Salud del Estado de Puebla, Puebla 72000, Mexico
| | - Silvio Danese
- Gastroenterology and Endoscopy, IRCCS Ospedale San Raffaele and University Vita-Salute San Raffaele, 20132 Milan, Italy;
| | - Laurent Peyrin-Biroulet
- Department of Gastroenterology NGERE (INSERM U1256), Nancy University Hospital, University of Lorraine, Vandœuvre-lès-Nancy, F-54052 Nancy, France; (B.C.); (V.H.)
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11
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Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney. DISEASE MARKERS 2022; 2022:4752184. [PMID: 35756490 PMCID: PMC9217527 DOI: 10.1155/2022/4752184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 05/10/2022] [Accepted: 05/25/2022] [Indexed: 11/17/2022]
Abstract
Background Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and overall survival (OS) of pRTK patients and constructed a model to predict their prognosis. Methods We accessed RNA sequencing data and corresponding clinical data of pRTK from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. An expression profile of immune-related genes (Irgenes) and lncRNAs of pRTK was extracted from the RNA sequencing data. IrlncRNAs were defined by co-expression analysis of lncRNAs and Irgenes. The limma R package was used to identify differential expression IrlncRNAs. Univariate and multivariate Cox regression analyses were conducted to build a prognostic IrlncRNAs model. The performance of this prognostic model was validated by multimethods, like ROC curve analysis. Results A total of 1097 IrlncRNAs were defined. Univariate Cox regression analysis identified 7 IrlncRNAs (AC004791.2, AP003068.23, RP11-54O7.14, RP11-680F8.1, TBC1D3P1-DHX40P1, TUNAR, and XXbac-BPG308K3.5) and were significantly associated with OS. Multivariate regression analysis constructed the best prognostic model based on the expression of AC004791.2, AP003068.23, RP11-54O7.14, TBC1D3P1-DHX40P1, and TUNAR. According to the prognostic model, a risk score of each patient was calculated, and patients were divided into high-risk and low-risk groups accordingly. The survival time of low-risk patients was significantly better than high-risk patients (p < 0.001). Univariate (hazard ratio 1.098, 95% confidence interval 1.048-1.149, p value <0.001) and multivariate (hazard ratio 1.095, 95% confidence interval 1.043-1.150, p value <0.001) analyses confirmed that the prognostic model was reliable and independent in prediction of OS. Time-dependent ROC analysis showed that 1-year survival AUC of prognostic model, stage, age, and sex was 0.824, 0.673, 0.531, and 0.495, respectively, which suggested that the prognostic model was the best predictor of survival in pRTK patients. Conclusions The prognostic model based on 5 IrlncRNAs was robust and could better predict the survival of pRTK than other clinical factors. Additionally, the mechanism of regulation and action of prognosis-associated lncRNAs could provide new avenues for basic research to explore the mechanism of tumor initiation and development in order to prevent and treat pRTK.
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Chen J, Tang S, Ke S, Cai JJ, Osorio D, Golovko A, Morpurgo B, Guo S, Sun Y, Winkle M, Calin GA, Tian Y. Ablation of long noncoding RNA MALAT1 activates antioxidant pathway and alleviates sepsis in mice. Redox Biol 2022; 54:102377. [PMID: 35763934 PMCID: PMC9241053 DOI: 10.1016/j.redox.2022.102377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/12/2022] [Accepted: 06/15/2022] [Indexed: 12/04/2022] Open
Abstract
The metastasis-associated lung adenocarcinoma transcript1 (MALAT1) is a long noncoding RNA (lncRNA) and is known for its role in cancer development and prognosis. In this study, we report that MALAT1 plays an important role in regulating acute inflammatory responses in sepsis. In patient samples, MALAT1 expression was positively correlated with severity of sepsis. In cultured macrophages, LPS treatment significantly induced MALAT1 expression, while genetic ablation of MALAT1 greatly reduced proinflammatory cytokine levels. Furthermore, MALAT1-ablated mice had significantly increased survival rates in cecal ligation and puncture (CLP)-induced sepsis and LPS-induced endotoxemia. One novel and salient feature of MALAT1-ablated mice is greatly reduced ROS level in macrophages and other cell types and increased glutathione/oxidized glutathione (GSH/GSSG) ratio in macrophages, suggesting an increased antioxidant capacity. We showed a mechanism for MALAT1 ablation leading to enhanced antioxidant capacity is through activation of methionine cycle by epitranscriptomical regulation of methionine adenosyltransferase 2A (MAT2A). MAT2A 3′UTR can be methylated by METTL16 which was known to directly bind to MALAT1. MALAT1 ablation was found to reduce methylation in MAT2A hairpin1 and increase MAT2A protein levels. Our results suggest a MALAT1-METTL16-MAT2A interactive axis which may be targeted for treatments of sepsis.
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Affiliation(s)
- Jingshu Chen
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Tx, 77843, USA
| | - Shu Tang
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Tx, 77843, USA
| | - Sui Ke
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Tx, 77843, USA
| | - James J Cai
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Tx, 77843, USA
| | - Daniel Osorio
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Tx, 77843, USA
| | - Andrei Golovko
- Texas A&M Institute for Genomic Medicine (TIGM), College Station, TX, 77843, USA
| | - Benjamin Morpurgo
- Texas A&M Institute for Genomic Medicine (TIGM), College Station, TX, 77843, USA
| | - Shaodong Guo
- Department of Nutrition, Texas A&M University, College Station, Tx, 77843, USA
| | - Yuxiang Sun
- Department of Nutrition, Texas A&M University, College Station, Tx, 77843, USA
| | - Melanie Winkle
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, Tx, 77230, USA
| | - George A Calin
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, Tx, 77230, USA
| | - Yanan Tian
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Tx, 77843, USA.
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13
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Moll M, Hobbs BD, Menon A, Ghosh AJ, Putman RK, Hino T, Hata A, Silverman EK, Quackenbush J, Castaldi PJ, Hersh CP, McGeachie MJ, Sin DD, Tal-Singer R, Nishino M, Hatabu H, Hunninghake GM, Cho MH. Blood gene expression risk profiles and interstitial lung abnormalities: COPDGene and ECLIPSE cohort studies. Respir Res 2022; 23:157. [PMID: 35715807 PMCID: PMC9204872 DOI: 10.1186/s12931-022-02077-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 06/03/2022] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND Interstitial lung abnormalities (ILA) are radiologic findings that may progress to idiopathic pulmonary fibrosis (IPF). Blood gene expression profiles can predict IPF mortality, but whether these same genes associate with ILA and ILA outcomes is unknown. This study evaluated if a previously described blood gene expression profile associated with IPF mortality is associated with ILA and all-cause mortality. METHODS In COPDGene and ECLIPSE study participants with visual scoring of ILA and gene expression data, we evaluated the association of a previously described IPF mortality score with ILA and mortality. We also trained a new ILA score, derived using genes from the IPF score, in a subset of COPDGene. We tested the association with ILA and mortality on the remainder of COPDGene and ECLIPSE. RESULTS In 1469 COPDGene (training n = 734; testing n = 735) and 571 ECLIPSE participants, the IPF score was not associated with ILA or mortality. However, an ILA score derived from IPF score genes was associated with ILA (meta-analysis of test datasets OR 1.4 [95% CI: 1.2-1.6]) and mortality (HR 1.25 [95% CI: 1.12-1.41]). Six of the 11 genes in the ILA score had discordant directions of effects compared to the IPF score. The ILA score partially mediated the effects of age on mortality (11.8% proportion mediated). CONCLUSIONS An ILA gene expression score, derived from IPF mortality-associated genes, identified genes with concordant and discordant effects on IPF mortality and ILA. These results suggest shared, and unique biologic processes, amongst those with ILA, IPF, aging, and death.
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Affiliation(s)
- Matthew Moll
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Brian D Hobbs
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Aravind Menon
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Auyon J Ghosh
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Rachel K Putman
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Takuya Hino
- Harvard Medical School, Boston, MA, 02115, USA
- Department of Radiology, Center for Pulmonary Functional Imaging, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Akinori Hata
- Harvard Medical School, Boston, MA, 02115, USA
- Department of Radiology, Center for Pulmonary Functional Imaging, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Edwin K Silverman
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - John Quackenbush
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Peter J Castaldi
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
- Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, Canada
| | - Craig P Hersh
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Michael J McGeachie
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Don D Sin
- Centre for Heart Lung Innovation, St. Paul's Hospital, and Department of Medicine (Respiratory Division), University of British Columbia, Vancouver, BC, Canada
| | | | - Mizuki Nishino
- Harvard Medical School, Boston, MA, 02115, USA
- Department of Radiology, Center for Pulmonary Functional Imaging, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Hiroto Hatabu
- Harvard Medical School, Boston, MA, 02115, USA
- Department of Radiology, Center for Pulmonary Functional Imaging, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Gary M Hunninghake
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Michael H Cho
- Channing Division for Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA.
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA.
- Harvard Medical School, Boston, MA, 02115, USA.
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14
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Learning processes in hierarchical pairs regulate entire gene expression in cells. Sci Rep 2022; 12:7549. [PMID: 35534510 PMCID: PMC9085877 DOI: 10.1038/s41598-022-10998-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 04/18/2022] [Indexed: 11/25/2022] Open
Abstract
Expression of numerous genes is precisely controlled in a cell in various contexts. While genetic and epigenetic mechanisms contribute to this regulation, how each mechanism cooperates to ensure the proper expression patterns of the whole gene remains unclear. Here, I theoretically show that the repetition of simple biological processes makes cells functional with the appropriate expression patterns of all genes if the inappropriateness of current expression ratios is roughly fed back to the epigenetic states. A learning pair model is developed, in which two factors autonomously approach the target ratio by repeating two stochastic processes; competitive amplification with a small addition term and decay depending on the difference between the current and target ratios. Furthermore, thousands of factors are self-regulated in a hierarchical-pair architecture, in which the activation degrees competitively amplify, while transducing the activation signal, and decay at four different probabilities. Changes in whole-gene expression during human early embryogenesis and hematopoiesis are reproduced in simulation using this epigenetic learning process in a single genetically-determined hierarchical-pair architecture of gene regulatory cascades. On the background of this learning process, I propose the law of biological inertia, which means that a living cell basically maintains the expression pattern while renewing its contents.
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15
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Yun JH, Lee S, Srinivasa P, Morrow J, Chase R, Saferali A, Xu Z, Cho M, Castaldi P, Hersh CP. An interferon-inducible signature of airway disease from blood gene expression profiling. Eur Respir J 2022; 59:2100569. [PMID: 34649980 PMCID: PMC9245457 DOI: 10.1183/13993003.00569-2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 09/24/2021] [Indexed: 11/05/2022]
Abstract
BACKGROUND The molecular basis of airway remodelling in chronic obstructive pulmonary disease (COPD) remains poorly understood. We identified gene expression signatures associated with chest computed tomography (CT) scan airway measures to understand molecular pathways associated with airway disease. METHODS In 2396 subjects in the COPDGene Study, we examined the relationship between quantitative CT airway phenotypes and blood transcriptomes to identify airway disease-specific genes and to define an airway wall thickness (AWT) gene set score. Multivariable regression analyses were performed to identify associations of the AWT score with clinical phenotypes, bronchial gene expression and genetic variants. RESULTS Type 1 interferon (IFN)-induced genes were consistently associated with AWT, square root wall area of a hypothetical airway with 10 mm internal perimeter (Pi10) and wall area percentage, with the strongest enrichment in AWT. A score derived from 18 genes whose expression was associated with AWT was associated with COPD-related phenotypes including reduced lung function (forced expiratory volume in 1 s percentage predicted β= -3.4; p<0.05) and increased exacerbations (incidence rate ratio 1.7; p<0.05). The AWT score was reproducibly associated with AWT in bronchial samples from 23 subjects (β=3.22; p<0.05). The blood AWT score was associated with genetic variant rs876039, an expression quantitative trait locus for IKZF1, a gene that regulates IFN signalling and is associated with inflammatory diseases. CONCLUSIONS A gene expression signature with IFN-stimulated genes from peripheral blood and bronchial brushings is associated with CT AWT, lung function and exacerbations. Shared genes and genetic associations suggest viral responses and/or autoimmune dysregulation as potential underlying mechanisms of airway disease in COPD.
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Affiliation(s)
- Jeong H Yun
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Sool Lee
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Pooja Srinivasa
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Jarrett Morrow
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Robert Chase
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Aadbida Saferali
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Zhonghui Xu
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michael Cho
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Peter Castaldi
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Dept of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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16
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Kim JS, Axelsson GT, Moll M, Anderson MR, Bernstein EJ, Putman RK, Hida T, Hatabu H, Hoffman EA, Raghu G, Kawut SM, Doyle MF, Tracy R, Launer LJ, Manichaikul A, Rich SS, Lederer DJ, Gudnason V, Hobbs BD, Cho MH, Hunninghake GM, Garcia CK, Gudmundsson G, Barr RG, Podolanczuk AJ. Associations of Monocyte Count and Other Immune Cell Types with Interstitial Lung Abnormalities. Am J Respir Crit Care Med 2022; 205:795-805. [PMID: 34929108 PMCID: PMC10394677 DOI: 10.1164/rccm.202108-1967oc] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Rationale: Higher blood monocyte counts are associated with worse survival in adults with clinically diagnosed pulmonary fibrosis. Their association with the development and progression of interstitial lung abnormalities (ILA) in humans is unknown. Objectives: We evaluated the associations of blood monocyte count, and other immune cell types, with ILA, high-attenuation areas, and FVC in four independent cohorts. Methods: We included participants with measured monocyte counts and computed tomographic (CT) imaging enrolled in MESA (Multi-Ethnic Study of Atherosclerosis, n = 484), AGES-Reykjavik (Age/Gene Environment Susceptibility Study, n = 3,547), COPDGene (Genetic Epidemiology of COPD, n = 2,719), and the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points, n = 646). Measurements and Main Results: After adjustment for covariates, a 1-SD increment in blood monocyte count was associated with ILA in MESA (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.0-1.8), AGES-Reykjavik (OR, 1.2; 95% CI, 1.1-1.3), COPDGene (OR, 1.3; 95% CI, 1.2-1.4), and ECLIPSE (OR, 1.2; 95% CI, 1.0-1.4). A higher monocyte count was associated with ILA progression over 5 years in AGES-Reykjavik (OR, 1.2; 95% CI, 1.0-1.3). Compared with participants without ILA, there was a higher percentage of activated monocytes among those with ILA in MESA. Higher monocyte count was associated with greater high-attenuation areas in MESA and lower FVC in MESA and COPDGene. Associations of other immune cell types were less consistent. Conclusions: Higher blood monocyte counts were associated with the presence and progression of interstitial lung abnormalities and lower FVC.
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Affiliation(s)
- John S Kim
- Department of Medicine, and.,Department of Medicine, Columbia University, New York, New York
| | - Gísli Thor Axelsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Icelandic Heart Association, Kopavogur, Iceland
| | - Matthew Moll
- Division of Pulmonary and Critical Care and.,Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | | | | | | | - Tomoyuki Hida
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts.,Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hiroto Hatabu
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Eric A Hoffman
- Department of Radiology.,Department of Medicine, and.,Department of Biomedical Engineering, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Ganesh Raghu
- Department of Medicine, University of Washington, Seattle, Washington
| | - Steven M Kawut
- Department of Medicine and.,Department of Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Margaret F Doyle
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Colchester, Vermont
| | - Russell Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Colchester, Vermont
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute of on Aging, National Institutes of Health, Bethesda, Maryland
| | - Ani Manichaikul
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Stephen S Rich
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia
| | | | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Icelandic Heart Association, Kopavogur, Iceland
| | - Brian D Hobbs
- Division of Pulmonary and Critical Care and.,Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Michael H Cho
- Division of Pulmonary and Critical Care and.,Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | | | | | - Gunnar Gudmundsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Department of Respiratory Medicine and Sleep, Landspitali University Hospital, Reykjavik, Iceland
| | - R Graham Barr
- Department of Medicine, Columbia University, New York, New York.,Department of Epidemiology, Mailman School of Public Health, New York, New York; and
| | - Anna J Podolanczuk
- Department of Medicine, Columbia University, New York, New York.,Division of Pulmonary and Critical Care Medicine, Weill Cornell Medical Center, New York, New York
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17
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Ghosh AJ, Saferali A, Lee S, Chase R, Moll M, Morrow J, Yun J, Castaldi PJ, Hersh CP. Blood RNA sequencing shows overlapping gene expression across COPD phenotype domains. Thorax 2022; 77:115-122. [PMID: 34168019 PMCID: PMC8711128 DOI: 10.1136/thoraxjnl-2020-216401] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 05/21/2021] [Indexed: 02/03/2023]
Abstract
RATIONALE COPD can be assessed using multidimensional grading systems with components from three domains: pulmonary function tests, symptoms and systemic features. Clinically, measures may be used interchangeably, though it is not known if they share similar pathobiology. OBJECTIVE To use RNA sequencing (RNA-seq) to determine if there is an overlap in the underlying biological mechanisms and consequences driving different components of the multidimensional grading systems. METHODS Whole blood was collected for RNA-seq from current and former smokers in the Genetic Epidemiology of COPD study. We tested the overlap in gene expression and biological pathways associated with case-control status and quantitative COPD phenotypes within and between the three domains. RESULTS In 2647 subjects, there were 3030 genes differentially expressed in any of the three domains or case-control status. There were five genes that overlapped between the three domains and case-control status, including G protein-coupled receptor 15(GPR15), sestrin 1 (SESN1) and interferon-induced guanylate-binding protein 1 (GBP1), which were associated with longitudinal decline in FEV1. The overlap between the three domains was enriched for pathways related to cellular components. CONCLUSIONS We identified gene sets and pathways that overlap between 12 COPD-related phenotypes and case-control status. There were no pathways represented in the overlap between the three domains and case-control status, but we identified multiple genes that demonstrated a consistent pattern of expression across several of the phenotypes. Patterns of gene expression correlation were generally similar to the correlation of clinical phenotypes in the PFT and symptom domains but not the systemic features.
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Affiliation(s)
- Auyon J Ghosh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Aabida Saferali
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Sool Lee
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Robert Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Matthew Moll
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Jarrett Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Jeong Yun
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
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18
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Moll M, Boueiz A, Ghosh AJ, Saferali A, Lee S, Xu Z, Yun JH, Hobbs BD, Hersh CP, Sin DD, Tal-Singer R, Silverman EK, Cho MH, Castaldi PJ. Development of a Blood-based Transcriptional Risk Score for Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 2022; 205:161-170. [PMID: 34739356 PMCID: PMC8787248 DOI: 10.1164/rccm.202107-1584oc] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 11/03/2021] [Indexed: 01/17/2023] Open
Abstract
Rationale: The ability of peripheral blood biomarkers to assess chronic obstructive pulmonary disease (COPD) risk and progression is unknown. Genetics and gene expression may capture important aspects of COPD-related biology that predict disease activity. Objectives: Develop a transcriptional risk score (TRS) for COPD and assess the contribution of the TRS and a polygenic risk score (PRS) for disease susceptibility and progression. Methods: We randomly split 2,569 COPDGene (Genetic Epidemiology of COPD) participants with whole-blood RNA sequencing into training (n = 1,945) and testing (n = 624) samples and used 468 ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points) COPD cases with microarray data for replication. We developed a TRS using penalized regression (least absolute shrinkage and selection operator) to model FEV1/FVC and studied the predictive value of TRS for COPD (Global Initiative for Chronic Obstructive Lung Disease 2-4), prospective FEV1 change (ml/yr), and additional COPD-related traits. We adjusted for potential confounders, including age and smoking. We evaluated the predictive performance of the TRS in the context of a previously derived PRS and clinical factors. Measurements and Main Results: The TRS included 147 transcripts and was associated with COPD (odds ratio, 3.3; 95% confidence interval [CI], 2.4-4.5; P < 0.001), FEV1 change (β, -17 ml/yr; 95% CI, -28 to -6.6; P = 0.002), and other COPD-related traits. In ECLIPSE cases, we replicated the association with FEV1 change (β, -8.2; 95% CI, -15 to -1; P = 0.025) and the majority of other COPD-related traits. Models including PRS, TRS, and clinical factors were more predictive of COPD (area under the receiver operator characteristic curve, 0.84) and annualized FEV1 change compared with models with one risk score or clinical factors alone. Conclusions: Blood transcriptomics can improve prediction of COPD and lung function decline when added to a PRS and clinical risk factors.
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Affiliation(s)
- Matthew Moll
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Adel Boueiz
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Auyon J. Ghosh
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | | | - Sool Lee
- Channing Division of Network Medicine
- Department of Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, North Carolina
| | | | - Jeong H. Yun
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Brian D. Hobbs
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Craig P. Hersh
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Don D. Sin
- Centre for Heart Lung Innovation, St. Paul’s Hospital, Vancouver, British Columbia, Canada
- Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; and
| | | | - Edwin K. Silverman
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Michael H. Cho
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Peter J. Castaldi
- Channing Division of Network Medicine
- Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
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19
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Ohmomo H, Harada S, Komaki S, Ono K, Sutoh Y, Otomo R, Umekage S, Hachiya T, Katanoda K, Takebayashi T, Shimizu A. DNA Methylation Abnormalities and Altered Whole Transcriptome Profiles after Switching from Combustible Tobacco Smoking to Heated Tobacco Products. Cancer Epidemiol Biomarkers Prev 2022; 31:269-279. [PMID: 34728466 PMCID: PMC9398167 DOI: 10.1158/1055-9965.epi-21-0444] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/29/2021] [Accepted: 10/18/2021] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND The use of heated tobacco products (HTP) has increased exponentially in Japan since 2016; however, their effects on health remain a major concern. METHODS Tsuruoka Metabolome Cohort Study participants (n = 11,002) were grouped on the basis of their smoking habits as never smokers (NS), past smokers (PS), combustible tobacco smokers (CS), and HTP users for <2 years. Peripheral blood mononuclear cells were collected from 52 participants per group matched to HTP users using propensity scores, and DNA and RNA were purified from the samples. DNA methylation (DNAm) analysis of the 17 smoking-associated DNAm biomarker genes (such as AHRR, F2RL3, LRRN3, and GPR15), as well as whole transcriptome analysis, was performed. RESULTS Ten of the 17 genes were significantly hypomethylated in CS and HTP users compared with NS, among which AHRR, F2RL3, and RARA showed intermediate characteristics between CS and NS; nonetheless, AHRR expression was significantly higher in CS than in the other three groups. Conversely, LRRN3 and GPR15 were more hypomethylated in HTP users than in NS, and GPR15 expression was markedly upregulated in all the groups when compared with that in NS. CONCLUSIONS HTP users (switched from CS <2 years) display abnormal DNAm and transcriptome profiles, albeit to a lesser extent than the CS. However, because the molecular genetic effects of long-term HTP use are still unknown, long-term molecular epidemiologic studies are needed. IMPACT This study provides new insights into the molecular genetic effects on DNAm and transcriptome profiles in HTP users who switched from CS.
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Affiliation(s)
- Hideki Ohmomo
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Sei Harada
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku-ku, Tokyo, Japan
| | - Shohei Komaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Kanako Ono
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Yoichi Sutoh
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Ryo Otomo
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - So Umekage
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Tsuyoshi Hachiya
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan
| | - Kota Katanoda
- Division of Cancer Statistics Integration, National Cancer Center Research Institute, Chuo, Tokyo, Japan
| | - Toru Takebayashi
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Shinjuku-ku, Tokyo, Japan
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Yahaba, Shiwa, Iwate, Japan.,Corresponding Author: Atsushi Shimizu, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate 028-3694, Japan. Phone: 81-19-651-5110, ext. 5473; E-mail:
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20
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Xu L, Dong Z. LINC00599 influences smoke-related chronic obstructive pulmonary disease and regulates CSE-induced epithelial cell apoptosis and inflammation by targeting miR-212-5p/BASP1 axis. Hum Exp Toxicol 2022; 41:9603271221146790. [PMID: 36541900 DOI: 10.1177/09603271221146790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
LINC00599 has been reported to be upregulated in response to cigarette smoking. However, the effect and underlying mechanism of LINC00599 in chronic obstructive pulmonary disease (COPD) are still under exploration. In this study, LINC00599 was upregulated in the COPD patients and was of clinical value to distinguish COPD patients. COPD cell models were established using 16HBE cells under cigarette smoke extract (CSE) treatment. LINC00599 levels were elevated in a dose and time-dependent way in response to CSE stimulation. The effect of LINC00599 on CSE-induced 16HBE cells was explored. The results showed that LINC00599 deficiency reversed the CSE-induced inhibition on cell viability and proliferation, and rescued the CSE-induced enhancement on cell 16HBE cell apoptosis and inflammation response. Moreover, LINC00599 bound with miR-212-5p to upregulate the BASP1 (brain abundant membrane attached signal protein 1) expression. MiR-212-5p was expressed at a low level in the tissue samples of COPD patients, and its levels were upregulated in LINC00599 silenced cells. BASP1 was targeted by miR-212-5p and its upregulation was identified in the tissue samples of COPD patients and cell models. BASP1 levels were downregulated after miR-212-5p overexpression or LINC00599 silencing. Moreover, the rescue assays demonstrated that BASP1 overexpression reversed the effect of silenced LINC00599 on 16HBE cells after CSE treatment, which indicated that LINC00599 promoted the COPD development by regulating BASP1 expression. In conclusion, LINC00599 facilitated CSE-induced cell apoptosis and inflammation response, while inhibiting the cell viability and proliferation in COPD progression via modulating miR-212-5p/BASP1 axis.
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Affiliation(s)
- Liyun Xu
- Department of Respiratory Medicine, Shanghai Pulmonary Hospital, Tongji University Affiliated Shanghai Pulmonary Hospital, Shanghai, China
| | - Zhiyi Dong
- Department of Integrated Chinese and Western Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
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21
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Mao Y, Huang P, Wang Y, Wang M, Li MD, Yang Z. Genome-wide methylation and expression analyses reveal the epigenetic landscape of immune-related diseases for tobacco smoking. Clin Epigenetics 2021; 13:215. [PMID: 34886889 PMCID: PMC8662854 DOI: 10.1186/s13148-021-01208-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 12/01/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Smoking is a major causal risk factor for lung cancer, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and is the main preventable cause of deaths in the world. The components of cigarette smoke are involved in immune and inflammatory processes, which may increase the prevalence of cigarette smoke-related diseases. However, the underlying molecular mechanisms linking smoking and diseases have not been well explored. This study was aimed to depict a global map of DNA methylation and gene expression changes induced by tobacco smoking and to explore the molecular mechanisms between smoking and human diseases through whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq). RESULTS We performed WGBS on 72 samples (36 smokers and 36 nonsmokers) and RNA-seq on 75 samples (38 smokers and 37 nonsmokers), and cytokine immunoassay on plasma from 22 males (9 smokers and 13 nonsmokers) who were recruited from the city of Jincheng in China. By comparing the data of the two groups, we discovered a genome-wide methylation landscape of differentially methylated regions (DMRs) associated with smoking. Functional enrichment analyses revealed that both smoking-related hyper-DMR genes (DMGs) and hypo-DMGs were related to synapse-related pathways, whereas the hypo-DMGs were specifically related to cancer and addiction. The differentially expressed genes (DEGs) revealed by RNA-seq analysis were significantly enriched in the "immunosuppression" pathway. Correlation analysis of DMRs with their corresponding gene expression showed that genes affected by tobacco smoking were mostly related to immune system diseases. Finally, by comparing cytokine concentrations between smokers and nonsmokers, we found that vascular endothelial growth factor (VEGF) was significantly upregulated in smokers. CONCLUSIONS In sum, we found that smoking-induced DMRs have different distribution patterns in hypermethylated and hypomethylated areas between smokers and nonsmokers. We further identified and verified smoking-related DMGs and DEGs through multi-omics integration analysis of DNA methylome and transcriptome data. These findings provide us a comprehensive genomic map of the molecular changes induced by smoking which would enhance our understanding of the harms of smoking and its relationship with diseases.
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Affiliation(s)
- Ying Mao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Peng Huang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yan Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Maiqiu Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ming D Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. .,Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China.
| | - Zhongli Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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22
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Improved prediction of smoking status via isoform-aware RNA-seq deep learning models. PLoS Comput Biol 2021; 17:e1009433. [PMID: 34634029 PMCID: PMC8530282 DOI: 10.1371/journal.pcbi.1009433] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 10/21/2021] [Accepted: 09/08/2021] [Indexed: 11/19/2022] Open
Abstract
Most predictive models based on gene expression data do not leverage information related to gene splicing, despite the fact that splicing is a fundamental feature of eukaryotic gene expression. Cigarette smoking is an important environmental risk factor for many diseases, and it has profound effects on gene expression. Using smoking status as a prediction target, we developed deep neural network predictive models using gene, exon, and isoform level quantifications from RNA sequencing data in 2,557 subjects in the COPDGene Study. We observed that models using exon and isoform quantifications clearly outperformed gene-level models when using data from 5 genes from a previously published prediction model. Whereas the test set performance of the previously published model was 0.82 in the original publication, our exon-based models including an exon-to-isoform mapping layer achieved a test set AUC (area under the receiver operating characteristic) of 0.88, which improved to an AUC of 0.94 using exon quantifications from a larger set of genes. Isoform variability is an important source of latent information in RNA-seq data that can be used to improve clinical prediction models. Predictive models based on gene expression are already a part of medical decision making for selected situations such as early breast cancer treatment. Most of these models are based on measures that do not capture critical aspects of gene splicing, but with RNA sequencing it is possible to capture some of these aspects of alternative splicing and use them to improve clinical predictions. Building on previous models to predict cigarette smoking status, we show that measures of alternative splicing significantly improve the accuracy of these predictive models.
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23
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Morrow JD, Castaldi PJ, Chase RP, Yun JH, Lee S, Liu YY, Hersh CP. Peripheral blood microbial signatures in current and former smokers. Sci Rep 2021; 11:19875. [PMID: 34615932 PMCID: PMC8494912 DOI: 10.1038/s41598-021-99238-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 09/15/2021] [Indexed: 12/13/2022] Open
Abstract
The human microbiome has a role in the development of multiple diseases. Individual microbiome profiles are highly personalized, though many species are shared. Understanding the relationship between the human microbiome and disease may inform future individualized treatments. We hypothesize the blood microbiome signature may be a surrogate for some lung microbial characteristics. We sought associations between the blood microbiome signature and lung-relevant host factors. Based on reads not mapped to the human genome, we detected microbial nucleic acids through secondary use of peripheral blood RNA-sequencing from 2,590 current and former smokers with and without chronic obstructive pulmonary disease (COPD) from the COPDGene study. We used the Genome Analysis Toolkit (GATK) microbial pipeline PathSeq to infer microbial profiles. We tested associations between the inferred profiles and lung disease relevant phenotypes and examined links to host gene expression pathways. We replicated our analyses using a second independent set of blood RNA-seq data from 1,065 COPDGene study subjects and performed a meta-analysis across the two studies. The four phyla with highest abundance across all subjects were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. In our meta-analysis, we observed associations (q-value < 0.05) between Acinetobacter, Serratia, Streptococcus and Bacillus inferred abundances and Modified Medical Research Council (mMRC) dyspnea score. Current smoking status was associated (q < 0.05) with Acinetobacter, Serratia and Cutibacterium abundance. All 12 taxa investigated were associated with at least one white blood cell distribution variable. Abundance for nine of the 12 taxa was associated with sex, and seven of the 12 taxa were associated with race. Host-microbiome interaction analysis revealed clustering of genera associated with mMRC dyspnea score and smoking status, through shared links to several host pathways. This study is the first to identify a bacterial microbiome signature in the peripheral blood of current and former smokers. Understanding the relationships between systemic microbial signatures and lung-related phenotypes may inform novel interventions and aid understanding of the systemic effects of smoking.
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Affiliation(s)
- Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.
| | - Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Robert P Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Jeong H Yun
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Sool Lee
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
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24
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Shen W, Wang S, Wang R, Zhang Y, Tian H, Yang X, Wei W. Analysis of the polarization states of the alveolar macrophages in chronic obstructive pulmonary disease samples based on miRNA-mRNA network signatures. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1333. [PMID: 34532470 PMCID: PMC8422127 DOI: 10.21037/atm-21-3815] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 08/12/2021] [Indexed: 12/12/2022]
Abstract
Background Multiple gene expression studies have been performed to investigate the biomarkers of chronic obstructive pulmonary disease (COPD). However, few studies have related COPD to macrophage cells. Methods The gene expression levels of clinical samples of COPD smokers (COPD; n=6), healthy smokers (Smoke; n=11), and never smokers (Never; n=4) were downloaded from the Gene Expression Omnibus (GEO) repository of GSE124180. The expression levels of messenger RNAs (mRNAs) and microRNAs (miRNAs) in macrophage cells of M0 (n=7), M1 (n=7), and M2 (n=7) were downloaded from the GEO repository of GSE46903 and GSE51307. Differentially expressed (DE) mRNAs (DEmRNAs) were identified by edgeR and GEO2R, with an adjusted P value <0.05 and |log2fold change (FC)| ≥1 chosen as the cut-off threshold. The potential target genes of miRNA were identified using miRanda (v3.3a) and TargetScan (v6.0) with default settings. Gene Ontology (GO) and Reactome pathway analyses were performed. Results The composition of macrophages was quite different between COPD, Never, and Smoke samples. The proportion of M1 cells was lower than that of M0 and M2 cells in Smokers and COPD samples. Most of the genes specifically up-regulated in M1 are related to inflammation/immunity. The expression levels of miR-30a-5p, miR-200c-3p, miR-20b-5p, miR-199b-5p, and miR-301b-3p in M1 macrophages were all lower than that of M0. Their expression levels in M2 macrophages compared with M1 varied, with higher expression in miR-30a-5p, miR-20b-5p, and lower expression in miR-200c-3p, and miR-301b-3p. The mRNAs of the fms related receptor tyrosine kinase 1 (FLT1), cardiotrophin like cytokine factor 1 (CLCF1), phosphodiesterase 4D (PDE4D), coagulation factor III, and tissue factor (F3) were dysregulated in COPD and macrophage cells. Conclusions The present study mined the miRNA-mRNA signature which might play an essential role in COPD and macrophage polarization.
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Affiliation(s)
- Wen Shen
- Respiratory Medicine Department, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shukun Wang
- Respiratory Medicine Department, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ruili Wang
- Respiratory Medicine Department, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yang Zhang
- Respiratory Medicine Department, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Hong Tian
- Respiratory Medicine Department, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiaolei Yang
- Respiratory Medicine Department, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Wei Wei
- Respiratory Medicine Department, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
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25
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LINC01414/LINC00824 genetic polymorphisms in association with the susceptibility of chronic obstructive pulmonary disease. BMC Pulm Med 2021; 21:213. [PMID: 34233676 PMCID: PMC8261955 DOI: 10.1186/s12890-021-01579-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 06/24/2021] [Indexed: 11/18/2022] Open
Abstract
Objective Chronic obstructive pulmonary disease (COPD) is a complicated multi-factor, multi-gene disease. Here, we aimed to assess the association of genetic polymorphisms in LINC01414/ LINC00824 and interactions with COPD susceptibility. Methods Three single nucleotide polymorphisms (SNPs) in LINC01414/LINC00824 was genotyped by Agena MassARRAY platform among 315 COPD patients and 314 controls. Logistic analysis adjusted by age and gender were applied to estimate the genetic contribution of selected SNPs to COPD susceptibility. Results LINC01414 rs699467 (OR = 0.73, 95% CI 0.56–0.94, p = 0.015) and LINC00824 rs7815944 (OR = 0.56, 95% CI 0.31–0.99, p = 0.046) might be protective factors for COPD occurrence, while LINC01414 rs298207 (OR = 2.88, 95% CI 1.31–6.31, p = 0.008) risk-allele was related to the increased risk of COPD in the whole population. Rs7815944 was associated with the reduced risk of COPD in the subjects aged > 70 years (OR = 0.29, p = 0.005). Rs6994670 (OR = 0.57, p = 0.007) contribute to a reduced COPD risk, while rs298207 (OR = 7.94, p = 0.009) was related to a higher susceptibility to COPD at age ≤ 70 years. Rs298207 (OR = 2.54, p = 0.043) and rs7815944 (OR = 0.43, p = 0.028) variants was associated COPD risk among males. Rs7815944 (OR = 0.16, p = 0.031) was related to the reduced susceptibility of COPD in former smokers. Moreover, the association between rs298207 genotype and COPD patients with dyspnea was found (OR = 0.50, p = 0.016), and rs7815944 was related to COPD patients with wheezing (OR = 0.22, p = 0.008). Conclusion Our finding provided further insights into LINC01414/LINC00824 polymorphisms at risk of COPD occurrence and accumulated evidence for the genetic susceptibility of COPD. Supplementary Information The online version contains supplementary material available at 10.1186/s12890-021-01579-3.
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Silva CP, Kamens HM. Cigarette smoke-induced alterations in blood: A review of research on DNA methylation and gene expression. Exp Clin Psychopharmacol 2021; 29:116-135. [PMID: 32658533 PMCID: PMC7854868 DOI: 10.1037/pha0000382] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Worldwide, smoking remains a threat to public health, causing preventable diseases and premature mortality. Cigarette smoke is a powerful inducer of DNA methylation and gene expression alterations, which have been associated with negative health consequences. Here, we review the current knowledge on smoking-related changes in DNA methylation and gene expression in human blood samples. We identified 30 studies focused on the association between active smoking, DNA methylation modifications, and gene expression alterations. Overall, we identified 1,758 genes with differentially methylated sites (DMS) and differentially expressed genes (DEG) between smokers and nonsmokers, of which 261 were detected in multiple studies (≥4). The most frequently (≥10 studies) reported genes were AHRR, GPR15, GFI1, and RARA. Functional enrichment analysis of the 261 genes identified the aryl hydrocarbon receptor repressor and T cell pathways (T helpers 1 and 2) as influenced by smoking status. These results highlight specific genes for future mechanistic and translational research that may be associated with cigarette smoke exposure and smoking-related diseases. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Affiliation(s)
- Constanza P. Silva
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania, 16802, United States of America
| | - Helen M. Kamens
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, Pennsylvania, 16802, United States of America.,Correspondence concerning this article should be addressed to Helen M. Kamens, 228 Biobehavioral Health Building, The Pennsylvania State University, University Park, PA 16802; ; Phone number: 814-865-1269; Fax number: 814-863-7525
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Zalewski DP, Ruszel KP, Stępniewski A, Gałkowski D, Bogucki J, Komsta Ł, Kołodziej P, Chmiel P, Zubilewicz T, Feldo M, Kocki J, Bogucka-Kocka A. Dysregulation of microRNA Modulatory Network in Abdominal Aortic Aneurysm. J Clin Med 2020; 9:jcm9061974. [PMID: 32599769 PMCID: PMC7355415 DOI: 10.3390/jcm9061974] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/13/2020] [Accepted: 06/22/2020] [Indexed: 12/16/2022] Open
Abstract
Abdominal artery aneurysm (AAA) refers to abdominal aortic dilatation of 3 cm or greater. AAA is frequently underdiagnosed due to often asymptomatic character of the disease, leading to elevated mortality due to aneurysm rupture. MiRNA constitute a pool of small RNAs controlling gene expression and is involved in many pathologic conditions in human. Targeted panel detecting altered expression of miRNA and genes involved in AAA would improve early diagnosis of this disease. In the presented study, we selected and analyzed miRNA and gene expression signatures in AAA patients. Next, generation sequencing was applied to obtain miRNA and gene-wide expression profiles from peripheral blood mononuclear cells in individuals with AAA and healthy controls. Differential expression analysis was performed using DESeq2 and uninformative variable elimination by partial least squares (UVE-PLS) methods. A total of 31 miRNAs and 51 genes were selected as the most promising biomarkers of AAA. Receiver operating characteristics (ROC) analysis showed good diagnostic ability of proposed biomarkers. Genes regulated by selected miRNAs were determined in silico and associated with functional terms closely related to cardiovascular and neurological diseases. Proposed biomarkers may be used for new diagnostic and therapeutic approaches in management of AAA. The findings will also contribute to the pool of knowledge about miRNA-dependent regulatory mechanisms involved in pathology of that disease.
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Affiliation(s)
- Daniel P. Zalewski
- Chair and Department of Biology and Genetics, Medical University of Lublin, 4a Chodźki St., 20-093 Lublin, Poland; (D.P.Z.); (P.C.)
| | - Karol P. Ruszel
- Chair of Medical Genetics, Department of Clinical Genetics, Medical University of Lublin, 11 Radziwiłłowska St., 20-080 Lublin, Poland; (K.P.R.); (J.B.); (J.K.)
| | - Andrzej Stępniewski
- Ecotech Complex Analytical and Programme Centre for Advanced Environmentally Friendly Technologies, University of Marie Curie-Skłodowska, 39 Głęboka St., 20-612 Lublin, Poland;
| | - Dariusz Gałkowski
- Department of Pathology and Laboratory Medicine, Rutgers - Robert Wood Johnson Medical School, One Robert Wood Johnson Place, New Brunswick, NJ 08903-0019, USA;
| | - Jacek Bogucki
- Chair of Medical Genetics, Department of Clinical Genetics, Medical University of Lublin, 11 Radziwiłłowska St., 20-080 Lublin, Poland; (K.P.R.); (J.B.); (J.K.)
| | - Łukasz Komsta
- Chair and Department of Medicinal Chemistry, Medical University of Lublin, 4 Jaczewskiego St., 20-090 Lublin, Poland;
| | - Przemysław Kołodziej
- Laboratory of Diagnostic Parasitology, Chair and Department of Biology and Genetics, Medical University of Lublin, 4a Chodźki St., 20-093 Lublin, Poland;
| | - Paulina Chmiel
- Chair and Department of Biology and Genetics, Medical University of Lublin, 4a Chodźki St., 20-093 Lublin, Poland; (D.P.Z.); (P.C.)
| | - Tomasz Zubilewicz
- Chair and Department of Vascular Surgery and Angiology, Medical University of Lublin, 11 Staszica St., 20-081 Lublin, Poland; (T.Z.); (M.F.)
| | - Marcin Feldo
- Chair and Department of Vascular Surgery and Angiology, Medical University of Lublin, 11 Staszica St., 20-081 Lublin, Poland; (T.Z.); (M.F.)
| | - Janusz Kocki
- Chair of Medical Genetics, Department of Clinical Genetics, Medical University of Lublin, 11 Radziwiłłowska St., 20-080 Lublin, Poland; (K.P.R.); (J.B.); (J.K.)
| | - Anna Bogucka-Kocka
- Chair and Department of Biology and Genetics, Medical University of Lublin, 4a Chodźki St., 20-093 Lublin, Poland; (D.P.Z.); (P.C.)
- Correspondence: ; Tel.: +48-81-448-7232
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Papoutsopoulou S, Satsangi J, Campbell BJ, Probert CS. Review article: impact of cigarette smoking on intestinal inflammation-direct and indirect mechanisms. Aliment Pharmacol Ther 2020; 51:1268-1285. [PMID: 32372449 DOI: 10.1111/apt.15774] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 04/13/2020] [Accepted: 04/16/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND The inflammatory bowel diseases, Crohn's disease and ulcerative colitis are related multifactorial diseases. Their pathogenesis is influenced by each individual's immune system, the environmental factors within exposome and genetic predisposition. Smoking habit is the single best-established environmental factor that influences disease phenotype, behaviour and response to therapy. AIM To assess current epidemiological, experimental and clinical evidence that may explain how smoking impacts on the pathogenesis of inflammatory bowel disease. METHODS A Medline search for 'cigarette smoking', in combination with terms including 'passive', 'second-hand', 'intestinal inflammation', 'Crohn's disease', 'ulcerative colitis', 'colitis'; 'intestinal epithelium', 'immune system', 'intestinal microbiota', 'tight junctions', 'mucus', 'goblet cells', 'Paneth cells', 'autophagy'; 'epigenetics', 'genes', 'DNA methylation', 'histones', 'short noncoding/long noncoding RNAs'; 'carbon monoxide/CO' and 'nitric oxide/NO' was performed. RESULTS Studies found evidence of direct and indirect effects of smoking on various parameters, including oxidative damage, impairment of intestinal barrier and immune cell function, epigenetic and microbiota composition changes, that contribute to the pathogenesis of inflammatory bowel disease. CONCLUSIONS Cigarette smoking promotes intestinal inflammation by affecting the function and interactions among intestinal epithelium, immune system and microbiota/microbiome.
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Affiliation(s)
- Stamatia Papoutsopoulou
- Gastroenterology Research Unit, Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Jack Satsangi
- Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Barry J Campbell
- Gastroenterology Research Unit, Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Chris S Probert
- Gastroenterology Research Unit, Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
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Poulet C, Njock MS, Moermans C, Louis E, Louis R, Malaise M, Guiot J. Exosomal Long Non-Coding RNAs in Lung Diseases. Int J Mol Sci 2020; 21:E3580. [PMID: 32438606 PMCID: PMC7279016 DOI: 10.3390/ijms21103580] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 05/14/2020] [Accepted: 05/15/2020] [Indexed: 12/13/2022] Open
Abstract
Within the non-coding genome landscape, long non-coding RNAs (lncRNAs) and their secretion within exosomes are a window that could further explain the regulation, the sustaining, and the spread of lung diseases. We present here a compilation of the current knowledge on lncRNAs commonly found in Chronic Obstructive Pulmonary Disease (COPD), asthma, Idiopathic Pulmonary Fibrosis (IPF), or lung cancers. We built interaction networks describing the mechanisms of action for COPD, asthma, and IPF, as well as private networks for H19, MALAT1, MEG3, FENDRR, CDKN2B-AS1, TUG1, HOTAIR, and GAS5 lncRNAs in lung cancers. We identified five signaling pathways targeted by these eight lncRNAs over the lung diseases mentioned above. These lncRNAs were involved in ten treatment resistances in lung cancers, with HOTAIR being itself described in seven resistances. Besides, five of them were previously described as promising biomarkers for the diagnosis and prognosis of asthma, COPD, and lung cancers. Additionally, we describe the exosomal-based studies on H19, MALAT1, HOTAIR, GAS5, UCA1, lnc-MMP2-2, GAPLINC, TBILA, AGAP2-AS1, and SOX2-OT. This review concludes on the need for additional studies describing the lncRNA mechanisms of action and confirming their potential as biomarkers, as well as their involvement in resistance to treatment, especially in non-cancerous lung diseases.
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Affiliation(s)
- Christophe Poulet
- Department of Rheumatology, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (M.-S.N.); (M.M.)
- Fibropôle Research Group, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (E.L.); (R.L.)
- GIGA-I3 Research Group, GIGA Institute, University of Liège (ULiege) and University Hospital of Liège (CHULiege), 4000 Liège, Belgium;
| | - Makon-Sébastien Njock
- Department of Rheumatology, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (M.-S.N.); (M.M.)
- Fibropôle Research Group, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (E.L.); (R.L.)
- GIGA-I3 Research Group, GIGA Institute, University of Liège (ULiege) and University Hospital of Liège (CHULiege), 4000 Liège, Belgium;
- Department of Respiratory Diseases, University Hospital of Liège (CHULiege), 4000 Liège, Belgium
| | - Catherine Moermans
- GIGA-I3 Research Group, GIGA Institute, University of Liège (ULiege) and University Hospital of Liège (CHULiege), 4000 Liège, Belgium;
- Department of Respiratory Diseases, University Hospital of Liège (CHULiege), 4000 Liège, Belgium
| | - Edouard Louis
- Fibropôle Research Group, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (E.L.); (R.L.)
- GIGA-I3 Research Group, GIGA Institute, University of Liège (ULiege) and University Hospital of Liège (CHULiege), 4000 Liège, Belgium;
- Department of Gastroenterology, University Hospital of Liège (CHULiege), 4000 Liège, Belgium
| | - Renaud Louis
- Fibropôle Research Group, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (E.L.); (R.L.)
- GIGA-I3 Research Group, GIGA Institute, University of Liège (ULiege) and University Hospital of Liège (CHULiege), 4000 Liège, Belgium;
- Department of Respiratory Diseases, University Hospital of Liège (CHULiege), 4000 Liège, Belgium
| | - Michel Malaise
- Department of Rheumatology, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (M.-S.N.); (M.M.)
- Fibropôle Research Group, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (E.L.); (R.L.)
- GIGA-I3 Research Group, GIGA Institute, University of Liège (ULiege) and University Hospital of Liège (CHULiege), 4000 Liège, Belgium;
| | - Julien Guiot
- Fibropôle Research Group, University Hospital of Liège (CHULiege), 4000 Liège, Belgium; (E.L.); (R.L.)
- GIGA-I3 Research Group, GIGA Institute, University of Liège (ULiege) and University Hospital of Liège (CHULiege), 4000 Liège, Belgium;
- Department of Respiratory Diseases, University Hospital of Liège (CHULiege), 4000 Liège, Belgium
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30
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Wilson AC, Kumar PL, Lee S, Parker MM, Arora I, Morrow JD, Wouters EFM, Casaburi R, Rennard SI, Lomas DA, Agusti A, Tal-Singer R, Dransfield MT, Wells JM, Bhatt SP, Washko G, Thannickal VJ, Tiwari HK, Hersh CP, Castaldi PJ, Silverman EK, McDonald MLN. Heme metabolism genes Downregulated in COPD Cachexia. Respir Res 2020; 21:100. [PMID: 32354332 PMCID: PMC7193359 DOI: 10.1186/s12931-020-01336-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 03/11/2020] [Indexed: 11/27/2022] Open
Abstract
INTRODUCTION Cachexia contributes to increased mortality and reduced quality of life in Chronic Obstructive Pulmonary Disease (COPD) and may be associated with underlying gene expression changes. Our goal was to identify differential gene expression signatures associated with COPD cachexia in current and former smokers. METHODS We analyzed whole-blood gene expression data from participants with COPD in a discovery cohort (COPDGene, N = 400) and assessed replication (ECLIPSE, N = 114). To approximate the consensus definition using available criteria, cachexia was defined as weight-loss > 5% in the past 12 months or low body mass index (BMI) (< 20 kg/m2) and 1/3 criteria: decreased muscle strength (six-minute walk distance < 350 m), anemia (hemoglobin < 12 g/dl), and low fat-free mass index (FFMI) (< 15 kg/m2 among women and < 17 kg/m2 among men) in COPDGene. In ECLIPSE, cachexia was defined as weight-loss > 5% in the past 12 months or low BMI and 3/5 criteria: decreased muscle strength, anorexia, abnormal biochemistry (anemia or high c-reactive protein (> 5 mg/l)), fatigue, and low FFMI. Differential gene expression was assessed between cachectic and non-cachectic subjects, adjusting for age, sex, white blood cell counts, and technical covariates. Gene set enrichment analysis was performed using MSigDB. RESULTS The prevalence of COPD cachexia was 13.7% in COPDGene and 7.9% in ECLIPSE. Fourteen genes were differentially downregulated in cachectic versus non-cachectic COPD patients in COPDGene (FDR < 0.05) and ECLIPSE (FDR < 0.05). DISCUSSION Several replicated genes regulating heme metabolism were downregulated among participants with COPD cachexia. Impaired heme biosynthesis may contribute to cachexia development through free-iron buildup and oxidative tissue damage.
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Affiliation(s)
- Ava C Wilson
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Preeti L Kumar
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Sool Lee
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Margaret M Parker
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Itika Arora
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Emiel F M Wouters
- Centre of expertise for chronic organ failure, Horn, the Netherlands
| | - Richard Casaburi
- Rehabilitation Clinical Trials Center, Los Angeles Biomedical Research Institute at Harbor Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stephen I Rennard
- Department of Medicine, Nebraska Medical Center, Omaha, NE, USA
- BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - David A Lomas
- UCL Respiratory, Division of Medicine, University College London, London, UK
| | - Alvar Agusti
- Fundació Investigació Sanitària Illes Balears (FISIB), Ciber Enfermedades Respiratorias (CIBERES), Barcelona, Catalunya, Spain
- Thorax Institute, Hospital Clinic, IDIBAPS, University of Barcelona, Barcelona, Spain
| | | | - Mark T Dransfield
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - J Michael Wells
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Surya P Bhatt
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - George Washko
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Victor J Thannickal
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Merry-Lynn N McDonald
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA.
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Regan EA, Hersh CP, Castaldi PJ, DeMeo DL, Silverman EK, Crapo JD, Bowler RP. Omics and the Search for Blood Biomarkers in Chronic Obstructive Pulmonary Disease. Insights from COPDGene. Am J Respir Cell Mol Biol 2020; 61:143-149. [PMID: 30874442 DOI: 10.1165/rcmb.2018-0245ps] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
There is an unmet need for blood biomarkers in diagnosis and prognosis of chronic obstructive pulmonary disease (COPD). The search for these biomarkers has been revolutionized by high-throughput sequencing techniques and multiplex platforms that can measure thousands of gene transcripts, proteins, or metabolites. We review COPDGene (Genetic Epidemiology of COPD) project publications that include DNA methylation, transcriptomic, proteomic, and metabolomic blood biomarkers and discuss their impact on COPD. Key contributions from COPDGene include identification of DNA methylation effects from smoking and genetic variation, new transcriptomic signatures in the blood, identification of protein biomarkers associated with severity and progression (e.g., sRAGE [soluble receptor for advanced glycosylation end products], inflammatory cytokines IL-6 and IL-8), and identification of small molecules (ceramides and sphingomyelin) that may be pathogenic. COPDGene studies have revealed that some of the COPD genome-wide association study polymorphisms are strongly associated with blood biomarkers (e.g., rs2070600 in AGER is a pQTL [protein quantitative trait locus] for sRAGE), underscoring the importance of combining omics results. Investigators have developed molecular networks identifying lower CD4+ resting memory cells associated with COPD. Genes, proteins, and metabolite networks are particularly important because the explanatory value of any single molecule is small (1-10%) compared with panels of multiple markers. COPDGene has been a useful resource in the identification and validation of multiple biomarkers for COPD. These biomarkers, either combined in multiple biomarker panels or integrated with other omics data types, may lead to novel diagnostic and prognostic tests for COPD phenotypes and may be relevant for assessing novel therapies.
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Affiliation(s)
- Elizabeth A Regan
- 1Department of Medicine, National Jewish Health, Denver, Colorado; and
| | - Craig P Hersh
- 2Channing Division of Network Medicine and.,3Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Peter J Castaldi
- 2Channing Division of Network Medicine and.,3Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Dawn L DeMeo
- 2Channing Division of Network Medicine and.,3Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Edwin K Silverman
- 2Channing Division of Network Medicine and.,3Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - James D Crapo
- 1Department of Medicine, National Jewish Health, Denver, Colorado; and
| | - Russell P Bowler
- 1Department of Medicine, National Jewish Health, Denver, Colorado; and
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32
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Boueiz A, Pham B, Chase R, Lamb A, Lee S, Naing ZZC, Cho MH, Parker MM, Sakornsakolpat P, Hersh CP, Crapo JD, Stergachis AB, Tal-Singer R, DeMeo DL, Silverman EK, Zhou X, Castaldi PJ. Integrative Genomics Analysis Identifies ACVR1B as a Candidate Causal Gene of Emphysema Distribution. Am J Respir Cell Mol Biol 2019; 60:388-398. [PMID: 30335480 DOI: 10.1165/rcmb.2018-0110oc] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified multiple associations with emphysema apicobasal distribution (EABD), but the biological functions of these variants are unknown. To characterize the functions of EABD-associated variants, we integrated GWAS results with 1) expression quantitative trait loci (eQTL) from the Genotype Tissue Expression (GTEx) project and subjects in the COPDGene (Genetic Epidemiology of COPD) study and 2) cell type epigenomic marks from the Roadmap Epigenomics project. On the basis of these analyses, we selected a variant near ACVR1B (activin A receptor type 1B) for functional validation. SNPs from 168 loci with P values less than 5 × 10-5 in the largest GWAS meta-analysis of EABD were analyzed. Eighty-four loci overlapped eQTL, with 12 of these loci showing greater than 80% likelihood of harboring a single, shared GWAS and eQTL causal variant. Seventeen cell types were enriched for overlap between EABD loci and Roadmap Epigenomics marks (permutation P < 0.05), with the strongest enrichment observed in CD4+, CD8+, and regulatory T cells. We selected a putative causal variant, rs7962469, associated with ACVR1B expression in lung tissue for additional functional investigation, and reporter assays confirmed allele-specific regulatory activity for this variant in human bronchial epithelial and Jurkat immune cell lines. ACVR1B expression levels exhibit a nominally significant association with emphysema distribution. EABD-associated loci are preferentially enriched in regulatory elements of multiple cell types, most notably T-cell subsets. Multiple EABD loci colocalize to regulatory elements that are active across multiple tissues and cell types, and functional analyses confirm the presence of an EABD-associated functional variant that regulates ACVR1B expression, indicating that transforming growth factor-β signaling plays a role in the EABD phenotype. Clinical trial registered with www.clinicaltrials.gov (NCT00608764).
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Affiliation(s)
- Adel Boueiz
- 1 Channing Division of Network Medicine.,2 Division of Pulmonary and Critical Care Medicine
| | | | | | | | - Sool Lee
- 1 Channing Division of Network Medicine
| | | | - Michael H Cho
- 1 Channing Division of Network Medicine.,2 Division of Pulmonary and Critical Care Medicine
| | | | | | - Craig P Hersh
- 1 Channing Division of Network Medicine.,2 Division of Pulmonary and Critical Care Medicine
| | - James D Crapo
- 3 Pulmonary Medicine, National Jewish Health, Denver, Colorado; and
| | | | | | - Dawn L DeMeo
- 1 Channing Division of Network Medicine.,2 Division of Pulmonary and Critical Care Medicine
| | - Edwin K Silverman
- 1 Channing Division of Network Medicine.,2 Division of Pulmonary and Critical Care Medicine
| | - Xiaobo Zhou
- 1 Channing Division of Network Medicine.,2 Division of Pulmonary and Critical Care Medicine
| | - Peter J Castaldi
- 1 Channing Division of Network Medicine.,6 Division of General Medicine and Primary Care, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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Devadoss D, Long C, Langley RJ, Manevski M, Nair M, Campos MA, Borchert G, Rahman I, Chand HS. Long Noncoding Transcriptome in Chronic Obstructive Pulmonary Disease. Am J Respir Cell Mol Biol 2019; 61:678-688. [PMID: 31486667 PMCID: PMC6890411 DOI: 10.1165/rcmb.2019-0184tr] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2019] [Accepted: 09/03/2019] [Indexed: 12/17/2022] Open
Abstract
Chronic airway inflammation from recurring exposures to noxious environmental stimuli results in a progressive and irreversible airflow limitation and the lung parenchymal damage that characterizes chronic obstructive pulmonary disease (COPD). The large variability observed in the onset and progression of COPD is primarily driven by complex gene-environment interactions. The transcriptomic and epigenetic memory potential of lung epithelial and innate immune cells drive responses, such as mucus hyperreactivity and airway remodeling, that are tightly regulated by various molecular mechanisms, for which several candidate susceptibility genes have been described. However, the recently described noncoding RNA species, in particular the long noncoding RNAs, may also have an important role in modulating pulmonary responses to chronic inhalation of toxic substances and the development of COPD. This review outlines the features of long noncoding RNAs that have been implicated in regulating the airway inflammatory responses to cigarette smoke exposure and their possible association with COPD pathogenesis. As COPD continues to debilitate the increasingly aging population and contribute to higher morbidity and mortality rates worldwide, the search for better biomarkers and alternative therapeutic options is pivotal.
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Affiliation(s)
- Dinesh Devadoss
- Department of Immunology and Nano-Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida
| | - Christopher Long
- Department of Immunology and Nano-Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida
| | - Raymond J. Langley
- Department of Pharmacology, University of South Alabama, Mobile, Alabama
| | - Marko Manevski
- Department of Immunology and Nano-Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida
| | - Madhavan Nair
- Department of Immunology and Nano-Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida
| | - Michael A. Campos
- Pulmonary Section, Miami Veterans Administration Medical Center, Miami, Florida
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Miller School of Medicine, University of Miami, Coral Gables, Florida; and
| | - Glen Borchert
- Department of Pharmacology, University of South Alabama, Mobile, Alabama
| | - Irfan Rahman
- Department of Environmental Medicine, University of Rochester Medical Center, Rochester, New York
| | - Hitendra S. Chand
- Department of Immunology and Nano-Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida
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34
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Parker MM, Chase RP, Lamb A, Reyes A, Saferali A, Yun JH, Himes BE, Silverman EK, Hersh CP, Castaldi PJ. Correction to: RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking. BMC Med Genomics 2019; 12:166. [PMID: 31739789 PMCID: PMC6859605 DOI: 10.1186/s12920-019-0617-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Margaret M Parker
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA.,Harvard Medical School, Boston, MA, 02115, USA
| | - Robert P Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA
| | - Andrew Lamb
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA
| | - Alejandro Reyes
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Aabida Saferali
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA.,Harvard Medical School, Boston, MA, 02115, USA
| | - Jeong H Yun
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Blanca E Himes
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA.,Harvard Medical School, Boston, MA, 02115, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA.,Harvard Medical School, Boston, MA, 02115, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, USA. .,Harvard Medical School, Boston, MA, 02115, USA. .,Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
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35
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Yun JH, Chase R, Parker MM, Saferali A, Castaldi PJ, Silverman EK. Peripheral Blood Gene Expression Signatures of Eosinophilic Chronic Obstructive Pulmonary Disease. Am J Respir Cell Mol Biol 2019; 61:398-401. [PMID: 31469299 PMCID: PMC6839929 DOI: 10.1165/rcmb.2019-0112le] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Affiliation(s)
- Jeong H. Yun
- Brigham and Women’s HospitalBoston, Massachusettsand
- Harvard Medical SchoolBoston, Massachusetts
| | - Robert Chase
- Brigham and Women’s HospitalBoston, Massachusettsand
| | - Margaret M. Parker
- Brigham and Women’s HospitalBoston, Massachusettsand
- Harvard Medical SchoolBoston, Massachusetts
| | - Aabida Saferali
- Brigham and Women’s HospitalBoston, Massachusettsand
- Harvard Medical SchoolBoston, Massachusetts
| | - Peter J. Castaldi
- Brigham and Women’s HospitalBoston, Massachusettsand
- Harvard Medical SchoolBoston, Massachusetts
| | - Edwin K. Silverman
- Brigham and Women’s HospitalBoston, Massachusettsand
- Harvard Medical SchoolBoston, Massachusetts
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36
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Christenson S, Hersh CP. Found in Translation: Multi-omics Assessment of the Chronic Obstructive Pulmonary Disease-Lung Cancer Interaction. Am J Respir Crit Care Med 2019; 200:276-277. [PMID: 30753788 PMCID: PMC6680298 DOI: 10.1164/rccm.201901-0156ed] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Affiliation(s)
- Stephanie Christenson
- 1Division of Pulmonary, Critical Care, Allergy and Sleep MedicineUniversity of California, San FranciscoSan Francisco, Californiaand
| | - Craig P Hersh
- 2Channing Division of Network MedicineBrigham and Women's HospitalBoston, Massachusetts
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37
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Parker MM, Hao Y, Guo F, Pham B, Chase R, Platig J, Cho MH, Hersh CP, Thannickal VJ, Crapo J, Washko G, Randell SH, Silverman EK, San José Estépar R, Zhou X, Castaldi PJ. Identification of an emphysema-associated genetic variant near TGFB2 with regulatory effects in lung fibroblasts. eLife 2019; 8:e42720. [PMID: 31343404 PMCID: PMC6693893 DOI: 10.7554/elife.42720] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 07/25/2019] [Indexed: 02/06/2023] Open
Abstract
Murine studies have linked TGF-β signaling to emphysema, and human genome-wide association studies (GWAS) studies of lung function and COPD have identified associated regions near genes in the TGF-β superfamily. However, the functional regulatory mechanisms at these loci have not been identified. We performed the largest GWAS of emphysema patterns to date, identifying 10 GWAS loci including an association peak spanning a 200 kb region downstream from TGFB2. Integrative analysis of publicly available eQTL, DNaseI, and chromatin conformation data identified a putative functional variant, rs1690789, that may regulate TGFB2 expression in human fibroblasts. Using chromatin conformation capture, we confirmed that the region containing rs1690789 contacts the TGFB2 promoter in fibroblasts, and CRISPR/Cas-9 targeted deletion of a ~ 100 bp region containing rs1690789 resulted in decreased TGFB2 expression in primary human lung fibroblasts. These data provide novel mechanistic evidence linking genetic variation affecting the TGF-β pathway to emphysema in humans.
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Affiliation(s)
- Margaret M Parker
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
| | - Yuan Hao
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
| | - Feng Guo
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
| | - Betty Pham
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
| | - Robert Chase
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
| | - John Platig
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
| | - Michael H Cho
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
- Division of Pulmonary and Critical Care MedicineBrigham and Women’s HospitalBostonUnited States
| | - Craig P Hersh
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
- Division of Pulmonary and Critical Care MedicineBrigham and Women’s HospitalBostonUnited States
| | - Victor J Thannickal
- Division of Pulmonary, Allergy and Critical Care, Department of MedicineSchool of Medicine, University of Alabama at BirminghamBirminghamUnited States
| | - James Crapo
- Division of Pulmonary, Critical Care and Sleep MedicineNational Jewish HealthDenverUnited States
| | - George Washko
- Division of Pulmonary and Critical Care MedicineBrigham and Women’s HospitalBostonUnited States
| | - Scott H Randell
- Marsico Lung InstituteThe University of North Carolina at Chapel HillChapel HillUnited States
| | - Edwin K Silverman
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
- Division of Pulmonary and Critical Care MedicineBrigham and Women’s HospitalBostonUnited States
| | | | - Xiaobo Zhou
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
| | - Peter J Castaldi
- Channing Division of Network MedicineBrigham and Women’s HospitalBostonUnited States
- Division of General Internal Medicine and Primary CareBrigham and Women’s HospitalBostonUnited States
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38
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Analysis of genetically driven alternative splicing identifies FBXO38 as a novel COPD susceptibility gene. PLoS Genet 2019; 15:e1008229. [PMID: 31269066 PMCID: PMC6634423 DOI: 10.1371/journal.pgen.1008229] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 07/16/2019] [Accepted: 06/04/2019] [Indexed: 11/19/2022] Open
Abstract
While many disease-associated single nucleotide polymorphisms (SNPs) are associated with gene expression (expression quantitative trait loci, eQTLs), a large proportion of complex disease genome-wide association study (GWAS) variants are of unknown function. Some of these SNPs may contribute to disease by regulating gene splicing. Here, we investigate whether SNPs that are associated with alternative splicing (splice QTL or sQTL) can identify novel functions for existing GWAS variants or suggest new associated variants in chronic obstructive pulmonary disease (COPD). RNA sequencing was performed on whole blood from 376 subjects from the COPDGene Study. Using linear models, we identified 561,060 unique sQTL SNPs associated with 30,333 splice sites corresponding to 6,419 unique genes. Similarly, 708,928 unique eQTL SNPs involving 15,913 genes were detected at 10% FDR. While there is overlap between sQTLs and eQTLs, 55.3% of sQTLs are not eQTLs. Co-localization analysis revealed that 7 out of 21 loci associated with COPD (p<1x10-6) in a published GWAS have at least one shared causal variant between the GWAS and sQTL studies. Among the genes identified to have splice sites associated with top GWAS SNPs was FBXO38, in which a novel exon was discovered to be protective against COPD. Importantly, the sQTL in this locus was validated by qPCR in both blood and lung tissue, demonstrating that splice variants relevant to lung tissue can be identified in blood. Other identified genes included CDK11A and SULT1A2. Overall, these data indicate that analysis of alternative splicing can provide novel insights into disease mechanisms. In particular, we demonstrated that SNPs in a known COPD GWAS locus on chromosome 5q32 influence alternative splicing in the gene FBXO38.
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39
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Low LINC00599 expression is a poor prognostic factor in glioma. Biosci Rep 2019; 39:BSR20190232. [PMID: 30867254 PMCID: PMC6443953 DOI: 10.1042/bsr20190232] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 02/26/2019] [Accepted: 03/10/2019] [Indexed: 12/24/2022] Open
Abstract
LINC00599 has been suggested to be involved in physiological and pathological processes including carcinogenesis. However, the clinical and prognostic significance of LINC00599 in glioma patients and the effect of LINC00599 on glioma cell migration and invasion remain unknown. In our results, we first observe the expression of LINC00599 in 31 types of human cancers including tumor tissues and corresponding normal tissues at The Cancer Genome Atlas (TCGA) database, and found that LINC00599 expression levels were only reduced in lower grade glioma (LGG) tissues and glioblastoma multiforme (GBM) tissues compared with normal brain tissues. Moreover, we confirmed levels of LINC00599 expression were decreased in glioma tissues and cell lines compared with matched adjacent normal tissues and normal human astrocytes (NHAs), respectively. Meanwhile, we found that glioma tissues with WHO III-IV grade exhibited lower levels of LINC00599 expression than glioma tissues with I-II grade. The survival analysis at TCGA data showed low LINC00599 expression was associated with poor disease-free survival and overall survival in glioma patients. In vitro study suggested up-regulation of LINC00599 depressed glioma cell migration and invasion through regulating epithelial–mesenchymal transition (EMT) process. In conclusion, LINC00599 acts as a tumor-suppressing long non-coding RNA (lncRNA) in glioma.
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40
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Morrow JD, Chase RP, Parker MM, Glass K, Seo M, Divo M, Owen CA, Castaldi P, DeMeo DL, Silverman EK, Hersh CP. RNA-sequencing across three matched tissues reveals shared and tissue-specific gene expression and pathway signatures of COPD. Respir Res 2019; 20:65. [PMID: 30940135 PMCID: PMC6446359 DOI: 10.1186/s12931-019-1032-z] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Accepted: 03/25/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Multiple gene expression studies have been performed separately in peripheral blood, lung, and airway tissues to study COPD. We performed RNA-sequencing gene expression profiling of large-airway epithelium, alveolar macrophage and peripheral blood samples from the same subset of COPD cases and controls from the COPDGene study who underwent bronchoscopy at a single center. Using statistical and gene set enrichment approaches, we sought to improve the understanding of COPD by studying gene sets and pathways across these tissues, beyond the individual genomic determinants. METHODS We performed differential expression analysis using RNA-seq data obtained from 63 samples from 21 COPD cases and controls (includes four non-smokers) via the R package DESeq2. We tested associations between gene expression and variables related to lung function, smoking history, and CT scan measures of emphysema and airway disease. We examined the correlation of differential gene expression across the tissues and phenotypes, hypothesizing that this would reveal preserved and private gene expression signatures. We performed gene set enrichment analyses using curated databases and findings from prior COPD studies to provide biological and disease relevance. RESULTS The known smoking-related genes CYP1B1 and AHRR were among the top differential expression results for smoking status in the large-airway epithelium data. We observed a significant overlap of genes primarily across large-airway and macrophage results for smoking and airway disease phenotypes. We did not observe specific genes differentially expressed in all three tissues for any of the phenotypes. However, we did observe hemostasis and immune signaling pathways in the overlaps across all three tissues for emphysema, and amyloid and telomere-related pathways for smoking. In peripheral blood, the emphysema results were enriched for B cell related genes previously identified in lung tissue studies. CONCLUSIONS Our integrative analyses across COPD-relevant tissues and prior studies revealed shared and tissue-specific disease biology. These replicated and novel findings in the airway and peripheral blood have highlighted candidate genes and pathways for COPD pathogenesis.
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Affiliation(s)
- Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.
| | - Robert P Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Margaret M Parker
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Kimberly Glass
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Minseok Seo
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Miguel Divo
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Caroline A Owen
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Peter Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
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41
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Al-Obaide MAI, Abdel-Salam ASG, Al-Hmoud ND, Hassani HH, Verma JP. Editorial: Bioinformatics and Biostatistics Applications in Tobacco Smoking Research. Front Public Health 2019; 6:366. [PMID: 30619807 PMCID: PMC6297381 DOI: 10.3389/fpubh.2018.00366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 11/30/2018] [Indexed: 11/17/2022] Open
Affiliation(s)
| | | | | | - Hayfa H Hassani
- Department of Biology, College of Science, University of Baghdad, Baghdad, Iraq
| | - J P Verma
- Department of Sport Psychology, Lakshmibai National Institute of Physical Education, Gwalior, India
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42
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High-Throughput Sequencing in Respiratory, Critical Care, and Sleep Medicine Research. An Official American Thoracic Society Workshop Report. Ann Am Thorac Soc 2019; 16:1-16. [PMID: 30592451 PMCID: PMC6812157 DOI: 10.1513/annalsats.201810-716ws] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
High-throughput, "next-generation" sequencing methods are now being broadly applied across all fields of biomedical research, including respiratory disease, critical care, and sleep medicine. Although there are numerous review articles and best practice guidelines related to sequencing methods and data analysis, there are fewer resources summarizing issues related to study design and interpretation, especially as applied to common, complex, nonmalignant diseases. To address these gaps, a single-day workshop was held at the American Thoracic Society meeting in May 2017, led by the American Thoracic Society Section on Genetics and Genomics. The aim of this workshop was to review the design, analysis, interpretation, and functional follow-up of high-throughput sequencing studies in respiratory, critical care, and sleep medicine research. This workshop brought together experts in multiple fields, including genetic epidemiology, biobanking, bioinformatics, and research ethics, along with physician-scientists with expertise in a range of relevant diseases. The workshop focused on application of DNA and RNA sequencing research in common chronic diseases and did not cover sequencing studies in lung cancer, monogenic diseases (e.g., cystic fibrosis), or microbiome sequencing. Participants reviewed and discussed study design, data analysis and presentation, interpretation, functional follow-up, and reporting of results. This report summarizes the main conclusions of the workshop, specifically addressing the application of these methods in respiratory, critical care, and sleep medicine research. This workshop report may serve as a resource for our research community as well as for journal editors and reviewers of sequencing-based manuscript submissions in our research field.
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43
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Seo M, Qiu W, Bailey W, Criner GJ, Dransfield MT, Fuhlbrigge AL, Reilly JJ, Scholand MB, Castaldi P, Chase R, Parker M, Saferali A, Yun JH, Crapo JD, Cho MH, Beaty TH, Silverman EK, Hersh CP. Genomics and response to long-term oxygen therapy in chronic obstructive pulmonary disease. J Mol Med (Berl) 2018; 96:1375-1385. [PMID: 30353303 DOI: 10.1007/s00109-018-1708-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 10/01/2018] [Accepted: 10/16/2018] [Indexed: 12/19/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide, and long-term oxygen therapy has been shown to reduce mortality in COPD patients with severe hypoxemia. However, the Long-term Oxygen Treatment Trial (LOTT), a large randomized trial, found no benefit of oxygen therapy in COPD patients with moderate hypoxemia. We hypothesized that there may be differences in response to oxygen which depend on genotype or gene expression. In a genome-wide time-to-event analysis of the primary outcome of death or hospitalization in 331 subjects, 97 single nucleotide polymorphisms (SNPs) showed evidence of interaction with oxygen therapy at P < 1e-5, including 7 SNPs near arylsulfatase B (ARSB; P = 6e-6). In microarray expression profiling on 51 whole blood samples from 37 individuals, at screening and/or at 12-month follow-up, ARSB expression was associated with the primary outcome depending on oxygen treatment. The significant SNPs were conditional expression quantitative trait loci for ARSB expression. In a network analysis of genes affected by long-term oxygen, two observed clusters including 26 co-expressed genes were enriched in mitochondrial function. Using data from the observational COPDGene Study, we validated the expression of 25 of these 26 genes, plus ARSB. The effect of long-term oxygen therapy in COPD varied based on ARSB expression and genotype. ARSB has previously been shown to be associated with hypoxemia in human bronchial and colonic epithelial cells and in a mouse model. In peripheral blood, long-term oxygen treatment affected expression of mitochondrial-related genes, a biologically relevant pathway in COPD. SNPs and expression of ARSB are associated with response to long-term oxygen in COPD. The ARSB SNPs were expression quantitative trait loci depending on oxygen therapy. Genes differentially expressed by long-term oxygen were enriched in mitochondrial functions. This suggests a potential biomarker to personalize use of long-term oxygen in COPD.
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Affiliation(s)
- Minseok Seo
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, USA
| | - Weiliang Qiu
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, USA
| | - William Bailey
- Lung Health Center, Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Gerard J Criner
- Department of Thoracic Medicine and Surgery, Temple University, Philadelphia, PA, USA
| | - Mark T Dransfield
- Lung Health Center, Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - John J Reilly
- University of Colorado School of Medicine, Denver, CO, USA
| | - Mary Beth Scholand
- Division of Pulmonary Medicine, University of Utah, Salt Lake City, UT, USA
| | - Peter Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, USA
| | - Robert Chase
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
| | - Margaret Parker
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, USA
| | - Aabida Saferali
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, USA
| | - Jeong H Yun
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, USA
| | - James D Crapo
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, CO, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, USA
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA, 02115, USA.
- Harvard Medical School, Boston, MA, USA.
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44
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Zhang H, Sun D, Li D, Zheng Z, Xu J, Liang X, Zhang C, Wang S, Wang J, Lu W. Long non-coding RNA expression patterns in lung tissues of chronic cigarette smoke induced COPD mouse model. Sci Rep 2018; 8:7609. [PMID: 29765063 PMCID: PMC5954018 DOI: 10.1038/s41598-018-25702-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Accepted: 04/23/2018] [Indexed: 01/14/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) have critical regulatory roles in protein-coding gene expression. Aberrant expression profiles of lncRNAs have been observed in various human diseases. In this study, we investigated transcriptome profiles in lung tissues of chronic cigarette smoke (CS)-induced COPD mouse model. We found that 109 lncRNAs and 260 mRNAs were significantly differential expressed in lungs of chronic CS-induced COPD mouse model compared with control animals. GO and KEGG analyses indicated that differentially expressed lncRNAs associated protein-coding genes were mainly involved in protein processing of endoplasmic reticulum pathway, and taurine and hypotaurine metabolism pathway. The combination of high throughput data analysis and the results of qRT-PCR validation in lungs of chronic CS-induced COPD mouse model, 16HBE cells with CSE treatment and PBMC from patients with COPD revealed that NR_102714 and its associated protein-coding gene UCHL1 might be involved in the development of COPD both in mouse and human. In conclusion, our study demonstrated that aberrant expression profiles of lncRNAs and mRNAs existed in lungs of chronic CS-induced COPD mouse model. From animal models perspective, these results might provide further clues to investigate biological functions of lncRNAs and their potential target protein-coding genes in the pathogenesis of COPD.
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Affiliation(s)
- Haiyun Zhang
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China
| | - Dejun Sun
- Division of Pulmonary Medicine, The People's Hospital of Inner Mongolia, Inner Mongolia Medical University, Hohhot, Inner Mongolia, China
| | - Defu Li
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China
| | - Zeguang Zheng
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China
| | - Jingyi Xu
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China
| | - Xue Liang
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China
| | - Chenting Zhang
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China
| | - Sheng Wang
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China
| | - Jian Wang
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China. .,Division of Translational and Regenerative Medicine, Department of Medicine, The University of Arizona, Tucson, AZ, 85721-0202, USA.
| | - Wenju Lu
- State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510180, China.
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Sakornsakolpat P, Morrow JD, Castaldi PJ, Hersh CP, Bossé Y, Silverman EK, Manichaikul A, Cho MH. Integrative genomics identifies new genes associated with severe COPD and emphysema. Respir Res 2018; 19:46. [PMID: 29566699 PMCID: PMC5863845 DOI: 10.1186/s12931-018-0744-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Accepted: 03/06/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Genome-wide association studies have identified several genetic risk loci for severe chronic obstructive pulmonary disease (COPD) and emphysema. However, these studies do not fully explain disease heritability and in most cases, fail to implicate specific genes. Integrative methods that combine gene expression data with GWAS can provide more power in discovering disease-associated genes and give mechanistic insight into regulated genes. METHODS We applied a recently described method that imputes gene expression using reference transcriptome data to genome-wide association studies for two phenotypes (severe COPD and quantitative emphysema) and blood and lung tissue gene expression datasets. We further tested the potential causality of individual genes using multi-variant colocalization. RESULTS We identified seven genes significantly associated with severe COPD, and five genes significantly associated with quantitative emphysema in whole blood or lung. We validated results in independent transcriptome databases and confirmed colocalization signals for PSMA4, EGLN2, WNT3, DCBLD1, and LILRA3. Three of these genes were not located within previously reported GWAS loci for either phenotype. We also identified genetically driven pathways, including those related to immune regulation. CONCLUSIONS An integrative analysis of GWAS and gene expression identified novel associations with severe COPD and quantitative emphysema, and also suggested disease-associated genes in known COPD susceptibility loci. TRIAL REGISTRATION NCT00608764 , Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: November 2007, Date Registered: January 28, 2008 (retrospectively registered); NCT00292552 , Registry: ClinicalTrials.gov, Date of Enrollment of First Participant: December 2005, Date Registered: February 14, 2006 (retrospectively registered).
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Affiliation(s)
- Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Jarrett D Morrow
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA
| | - Peter J Castaldi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA
- Division of General Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA
| | - Yohan Bossé
- Department of Molecular Medicine, Institut universitaire de cardiologie et de pneumologie de Québec, Laval University, Quebec, Canada
| | - Edwin K Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA
| | - Ani Manichaikul
- Department of Public Health Sciences, Center for Public Health Genomics and Biostatistics Section, University of Virginia, Charlottesville, VA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA.
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Room 451, Boston, MA, 02115, USA.
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