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Sequencing of idiopathic pulmonary fibrosis-related genes reveals independent single gene associations.

ABSTRACT: Previous studies investigating a genetic basis for idiopathic pulmonary fibrosis (IPF) have focused on resequencing single genes in IPF kindreds or cohorts to determine the genetic contributions to IPF. None has investigated interactions among the candidate genes.To compare the frequencies and interactions of mutations in six IPF-associated genes in a cohort of 132 individuals with IPF with those of a disease-control cohort of 192 individuals with chronic obstructive pulmonary disease (COPD) and the population represented in the Exome Variant Server.We resequenced the genes encoding surfactant proteins A2 (SFTPA2), and C (SFTPC), the ATP binding cassette member A3 (ABCA3), telomerase (TERT), thyroid transcription factor (NKX2-1) and mucin 5B (MUC5B) and compared the collapsed frequencies of rare (minor allele frequency <1%), computationally predicted deleterious variants in each cohort. We also genotyped a common MUC5B promoter variant that is over-represented in individuals with IPF.We found 15 mutations in 14 individuals (11%) in the IPF cohort: (SFTPA2 (n=1), SFTPC (n=5), ABCA3 (n=4) and TERT (n=5)). No individual with IPF had two different mutations, but one individual with IPF was homozygous for p.E292V, the most common ABCA3 disease-causing variant. We did not detect an interaction between any of the mutations and the MUC5B promoter variant.Rare mutations in SFTPA2, SFTPC and TERT are collectively over-represented in individuals with IPF. Genetic analysis and counselling should be considered as part of the IPF evaluation.

SUBMITTER: Coghlan MA

PROVIDER: S-EPMC4265083 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Sequencing of idiopathic pulmonary fibrosis-related genes reveals independent single gene associations.

Coghlan Meghan A MA Shifren Adrian A Huang Howard J HJ Russell Tonya D TD Mitra Robi D RD Zhang Qunyuan Q Wegner Daniel J DJ Cole F Sessions FS Hamvas Aaron A

BMJ open respiratory research 20141210 1

<h4>Background</h4>Previous studies investigating a genetic basis for idiopathic pulmonary fibrosis (IPF) have focused on resequencing single genes in IPF kindreds or cohorts to determine the genetic contributions to IPF. None has investigated interactions among the candidate genes.<h4>Objective</h4>To compare the frequencies and interactions of mutations in six IPF-associated genes in a cohort of 132 individuals with IPF with those of a disease-control cohort of 192 individuals with chronic obs ...[more]

PMID: 25553246

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Project description:Aging plays a significant role in the occurrence and development of idiopathic pulmonary fibrosis (IPF). In this study, we aimed to identify and verify potential aging-associated genes involved in IPF using bioinformatic analysis. The mRNA expression profile dataset GSE150910 available in the Gene Expression Omnibus (GEO) database and R software were used to identify the differentially expressed aging-related genes involved in IPF. Hub gene expression was validated by other GEO datasets. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on differentially expressed aging-related genes. Subsequently, aging-related genes were further screened using three techniques (least absolute shrinkage and selection operator (LASSO) regression, support vector machine, and random forest), and the receiver operating characteristic curves were plotted based on screening results. Finally, real-time quantitative polymerase chain reaction (qRT-PCR) was performed to verify the RNA expression of the six differentially expressed aging-related genes using the blood samples of patients with IPF and healthy individuals. Sixteen differentially expressed aging-related genes were detected, of which the expression of 12 were upregulated and four were downregulated. GO and KEGG enrichment analyses indicated the presence of several enriched terms related to senescence and apoptotic mitochondrial changes. Further screening by LASSO regression, support vector machine, and random forest identified six genes (IGF1, RET, IGFBP2, CDKN2A, JUN, and TFAP2A) that could serve as potential diagnostic biomarkers for IPF. Furthermore, qRT-PCR analysis indicated that among the above-mentioned six aging-related genes, only the expression levels of IGF1, RET, and IGFBP2 in patients with IPF and healthy individuals were consistent with the results of bioinformatic analysis. In conclusion, bioinformatics analysis identified 16 potential aging-related genes associated with IPF, and clinical sample validation suggested that among these, IGF1, RET, and IGFBP2 might play a role in the incidence and prognosis of IPF. Our findings may help understand the pathogenesis of IPF.

Project description:Background Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease with limited therapeutic options. Recent studies have demonstrated that chemokines play a vital role in IPF pathogenesis. In the present study, we explored whether the gene signature associated with chemokines could be used as a reliable biological marker for patients with IPF. Methods Chemokine-related differentially expressed genes (CR-DEGs) in IPF and control lung tissue samples were identified using data from the Gene Expression Omnibus database. A chemokine-related signature of the diagnostic model was established using the LASSO-Cox regression. In addition, unsupervised cluster analysis was conducted using consensus-clustering algorithms. The CIBERSORT algorithm was used to calculate immune cell infiltration across patient subgroups. Finally, we established a mouse model of bleomycin-induced pulmonary fibrosis and a model of fibroblasts treated with TGFβ1. Expression levels of chemokine-related signature genes were determined using real-time quantitative polymerase chain reaction (RT-qPCR). Results We established a chemokine-related eleven-gene signature of a diagnostic model consisting of CXCL2, CCRL2, ARRB1, XCL1, GRK5, PPBP, CCL19, CCL13, CCL11, CXCL6, and CXCL13, which could easily distinguish between IPF patients and controls. Additionally, we identified two subtypes of IPF samples based on chemokine-related gene expression. Pulmonary function parameters and stromal scores were significantly higher in subtype 1 than in subtype 2. Several immune cell types, especially plasma cells and macrophages, differ significantly between the two subtypes. RT-qPCR results showed that the expression levels of Cxcl2 and Ccl2 increased considerably in bleomycin-induced mice. Meanwhile, Arrb1, Ccrl2, Grk5, and Ppbp expression was significantly reduced. Furthermore, multiple chemokine-related genes were altered in TGFβ1 or TNFα-induced fibroblast cells. Conclusions A novel chemokine-related eleven-signature of diagnostic model was developed. These genes are potential biomarkers of IPF and may play essential roles in its pathogenesis.

Project description:Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive pulmonary fibrotic disease with unknown etiology and poor outcomes. It severely affects the quality of life. In this study, we comprehensively analyzed the expression of N6-methyladenosine (m6A) RNA methylation regulators using gene expression data from various tissue sources in IPF patients and healthy volunteers. Methods: The gene expression matrix and clinical characteristics of IPF patients were retrieved from the Gene Expression Omnibus database. A random forest model was used to construct diagnosis signature m6A regulators. Regression analysis and correlation analysis were used to identify prognosis m6A regulators. Consensus cluster analysis was used to construct different m6A prognosis risk groups, then functional enrichment, immune infiltration and drug sensitivity analysis were performed. Result: Five candidate m6A genes from lung tissue were used to predict the incidence, and the incidence was validated using datasets from bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells. Subsequently, the BALF dataset containing outcomes data was used for the prognosis analysis of m6A regulators. METTL14, G3BP2, and ZC3H13 were independent protective factors. Using correlation analysis with lung function in the lung tissue-derived dataset, METTL14 was a protective factor in IPF. Based on METTL14 and G3BP2, a consensus cluster analysis was applied to distinguish the prognostic m6A regulation patterns. The low-risk group's prognosis was significantly better than the high-risk group. Biological processes regulated by various risk groups included fibrogenesis and cell adhesion. Analysis of immune cell infiltration showed upregulation of neutrophils in the m6A high-risk group. Subsequently, five m6A high-risk group sensitive drugs and one m6A low-risk group sensitive drug were identified. Discussion: These findings suggest that m6A regulators are involved in the diagnosis and prognosis of IPF, and m6A patterns are a method to identify IPF outcomes.

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Sequencing of idiopathic pulmonary fibrosis-related genes reveals independent single gene associations.

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Sequencing of idiopathic pulmonary fibrosis-related genes reveals independent single gene associations.

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