Bmc Med Genomics
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Abdominal aortic aneurysm (AAA) is a dilatation of the aorta affecting most frequently elderly men. Histologically AAAs are characterized by inflammation, vascular smooth muscle cell apoptosis, and extracellular matrix degradation. The mechanisms of AAA formation, progression, and rupture are currently poorly understood. A previous mRNA expression study revealed a large number of differentially expressed genes between AAA and non-aneurysmal control aortas. MicroRNAs (miRNAs), small non-coding RNAs that are post-transcriptional regulators of gene expression, could provide a mechanism for the differential expression of genes in AAA. ⋯ Our genome-wide approach revealed several differentially expressed miRNAs in human AAA tissue suggesting that miRNAs play a role in AAA pathogenesis.
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Conventional prenatal screening tests, such as maternal serum tests and ultrasound scan, have limited resolution and accuracy. ⋯ Our study demonstrates a powerful and reliable methodology for noninvasive prenatal diagnosis.
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Transcriptomic studies in clinical research are essential tools for deciphering the functional elements of the genome and unraveling underlying disease mechanisms. Various technologies have been developed to deduce and quantify the transcriptome including hybridization and sequencing-based approaches. Recently, high density exon microarrays have been successfully employed for detecting differentially expressed genes and alternative splicing events for biomarker discovery and disease diagnostics. The field of transcriptomics is currently being revolutionized by high throughput DNA sequencing methodologies to map, characterize, and quantify the transcriptome. ⋯ Our findings suggest that microarrays remain useful and accurate for transcriptomic analysis of clinical samples with low input requirements, while RNA-seq technology complements and extends microarray measurements for novel discoveries.
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Genes associated with MUC5AC expression in small airway epithelium of human smokers and non-smokers.
Mucus hypersecretion contributes to the morbidity and mortality of smoking-related lung diseases, especially chronic obstructive pulmonary disease (COPD), which starts in the small airways. Despite progress in animal studies, the genes and their expression pattern involved in mucus production and secretion in human airway epithelium are not well understood. We hypothesized that comparison of the transcriptomes of the small airway epithelium of individuals that express high vs low levels of MUC5AC, the major macromolecular component of airway mucus, could be used as a probe to identify the genes related to human small airway mucus production/secretion. ⋯ The identification of the genes associated with increased airway mucin production in humans should be useful in understanding the pathogenesis of airway mucus hypersecretion and identifying therapeutic targets. AUTHOR SUMMARY: Mucus hypersecretion contributes to the morbidity and mortality of smoking-related lung diseases, especially chronic obstructive pulmonary disease (COPD), which starts in the small airways. Little is known about the gene networks associated with the synthesis and secretion of mucins in the human small airway epithelium. Taking advantage of the knowledge that MUC5AC is a major mucin secreted by the small airway epithelium, the expression of MUC5AC in small airway epithelium is highly regulated at the transcriptional level and our observation that healthy nonsmokers have variable numbers of MUC5AC+ secretory cells in the human small airway epithelium, we compared genome-wide gene expression of the small airway epithelium of high vs low MUC5AC expressors from 60 nonsmokers to identify the genes associated with MUC5AC expression. This novel strategy enabled identification of a 73 "MUC5AC-associated core gene" list with 9 categories, which control a series of processes from mucin biosynthesis to mucus secretion. The coordinated gene expression pattern of MUC5AC-associated core genes were corroborated in an independent cohort of 72 healthy smokers. Deep sequencing of small airway epithelium RNA confirmed these observations. This finding will be useful in identifying therapeutic targets to treat small airway mucus hypersecretion.
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The accurate diagnosis of idiopathic pulmonary fibrosis (IPF) is a major clinical challenge. We developed a model to diagnose IPF by applying Bayesian probit regression (BPR) modelling to gene expression profiles of whole lung tissue. ⋯ This study represents the first use of BPR on whole lung tissue; previously, BPR was primarily used to develop predictive models for cancer. This also represents the first report of an independently validated IPF gene expression signature. In summary, BPR is a promising tool for the development of gene expression signatures from non-neoplastic lung tissue. In the future, BPR might be used to develop definitive diagnostic gene signatures for IPF, prognostic gene signatures for IPF or gene signatures for other non-neoplastic lung disorders such as bronchiolitis obliterans.