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. 2018 Jan 15;12(1):1.
doi: 10.1186/s40246-018-0132-z.

Ensemble Genomic Analysis in Human Lung Tissue Identifies Novel Genes for Chronic Obstructive Pulmonary Disease

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Free PMC article

Ensemble Genomic Analysis in Human Lung Tissue Identifies Novel Genes for Chronic Obstructive Pulmonary Disease

Jarrett D Morrow et al. Hum Genomics. .
Free PMC article

Abstract

Background: Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) significantly associated with chronic obstructive pulmonary disease (COPD). However, many genetic variants show suggestive evidence for association but do not meet the strict threshold for genome-wide significance. Integrative analysis of multiple omics datasets has the potential to identify novel genes involved in disease pathogenesis by leveraging these variants in a functional, regulatory context.

Results: We performed expression quantitative trait locus (eQTL) analysis using genome-wide SNP genotyping and gene expression profiling of lung tissue samples from 86 COPD cases and 31 controls, testing for SNPs associated with gene expression levels. These results were integrated with a prior COPD GWAS using an ensemble statistical and network methods approach to identify relevant genes and observe them in the context of overall genetic control of gene expression to highlight co-regulated genes and disease pathways. We identified 250,312 unique SNPs and 4997 genes in the cis(local)-eQTL analysis (5% false discovery rate). The top gene from the integrative analysis was MAPT, a gene recently identified in an independent GWAS of lung function. The genes HNRNPAB and PCBP2 with RNA binding activity and the gene ACVR1B were identified in network communities with validated disease relevance.

Conclusions: The integration of lung tissue gene expression with genome-wide SNP genotyping and subsequent intersection with prior GWAS and omics studies highlighted candidate genes within COPD loci and in communities harboring known COPD genes. This integration also identified novel disease genes in sub-threshold regions that would otherwise have been missed through GWAS.

Trial registration: ClinicalTrials.gov NCT00608764 NCT00292552.

Keywords: Bayesian methods; Ensemble methods; Expression QTL; Integrative genomics; Network medicine; eQTL.

Conflict of interest statement

Ethics approval and consent to participate

Subjects provided written informed consent for the use of excess lung tissue for research. IRB approval was obtained at Partners Healthcare (parent company of Brigham and Women’s Hospital), Temple University, and St. Elizabeth’s Hospital. The methods for lung tissue research were carried out in accordance with the relevant guidelines.

Competing interests

Drs. Morrow, Platig, Zhou, Qiu, Marchetti, Criner, Celli, Glass, Quackenbush report no competing interests related to this manuscript.

Dr. Cho has received compensation from GSK.

Dr. DeMeo has received compensation from Novartis.

Dr. Bueno has received compensation from Myriad Genetics, Inc., Siemens, Verastem, Inc., Genentech, Inc., Gritstone Oncology, Inc., HTG Molecular Diagnostics, Inc., Neil Leifer, Esq, Morrison Mahoney, David Weiss, LLC, Balick & Balick, LLC, Hartford Hospital, Cleveland Clinic/Conference, Aspen Lung Conference, Case Western Reserve, North Shore University, Castle Bioscience, Novartis Institutes for Biomedical Research, AstraZebeca, imCORE/Roche, Arthur Tuverson, LLC, Ferraro Law Firm, Rice Dolan & Kershaw, Satterly & Kelly, LLC, Exosome, Inc.

Dr. Washko has received compensation from Boehringer Ingelheim, GlaxoSmithKline, Janssen Pharmaceuticals, BTG Interventional Medicine, Regeneron, Quantitative Imaging Solutions and ModoSpira, and his Spouse works for Biogen.

Dr. Silverman has received compensation from COPD Foundation, GlaxoSmithKline, Merck and Novartis,

Dr. Hersh has received consulting fees from AstraZeneca, Concert Pharmaceuticals, Mylan, and grant support from Boehrinher Ingelheim.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Graphical overview of the study methods and process. The cis- and trans-eQTLs identified in lung tissue were integrated with prior GWAS using Bayesian and network methods. The network communities identified were interrogated for evidence of differential gene expression and differential DNA methylation by COPD status
Fig. 2
Fig. 2
Plot of COPD GWAS p values vs. the cis-eQTL p values. Each point in the plot represents a cis-eQTL result with an rsID found in the prior GWAS. GWAS p values (y axis) are plotted against the expression QTL p values (x axis). A vertical dotted line indicates the threshold of significance (FDR < 5%) for the eQTL. Horizontal lines delineate genome-wide significant (red) and sub-threshold (blue) GWAS p values. The significant (red; FDR < 5%) and nominally significant (blue; p < 0.05) eGenes from gene expression profiling in COPD lung tissue are highlighted
Fig. 3
Fig. 3
Community 202 from CONDOR analysis that contains the Sherlock-derived genes CHRNA5, HNRNPAB, IREB2, and PCBP2. Community genes are listed in (Additional file 1: Table S6). (Red = SNP, yellow = SNP with GWAS p < 10−4, square = Sherlock gene, gray = gene, green = gene with differentially methylated site (p < 0.05 and effect > 5%), light blue = gene with differentially expressed probe (p < 0.05), and cyan = gene with differentially methylated site and differentially expressed probe)
Fig. 4
Fig. 4
Community 222 from CONDOR analysis that contains the Sherlock-derived gene ACVR1B. Community genes are listed in (Additional file 1: Table S6). (Red = SNP, yellow = SNP with GWAS p < 10−4, square = Sherlock gene, gray = gene, green = gene with differentially methylated site (p < 0.05 and effect > 5%), light blue = gene with differentially expressed probe (p < 0.05), and cyan = gene with differentially methylated site and differentially expressed probe)
Fig. 5
Fig. 5
Community 113 from CONDOR analysis that contains the Sherlock-derived gene CDH23. The central genes PSMC1 and CTDSPL2 partially overlap and are obstructed in the figure. Community genes are listed in (Additional file 1: Table S6). (Red = SNP, yellow = SNP with GWAS p < 10−4, square = Sherlock gene, gray = gene, green = gene with differentially methylated site (p < 0.05 and effect > 5%), light blue = gene with differentially expressed probe (p < 0.05), cyan = gene with differentially methylated site and differentially expressed probe)

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