title: Integration of multi-microarray datasets to identify chronic obstructive pulmonary disease-related miRNAs.
abstract: Currently, the mechanisms underlying chronic obstructive pulmonary disease (COPD) remain unclear. As potential biomarkers, microRNAs (miRNAs), which modulate the levels of specific genes and proteins, are important for enhancing our understanding of the mechanisms behind COPD. Although there have been a number of miRNA expression profiling analyses strategies used to document miRNA expression changes during physiological and pathological processes or used to identify differentially expressed miRNAs in disease or control samples, the study results have been inconsistently replicated using different datasets. For this reason, many findings cannot be well synthesized and interpreted. To address this issue, we used a multiple co-inertia analysis (MCIA) method to extract potential COPD-related miRNAs using three COPD microarray datasets. The results showed that miR-223, miR-132, and miR-199a-5p are obviously associated with COPD, and these results are consistent with the highly significant differentially-expressed miRNAs that were observed across three microarray datasets. Moreover, when miR-223, miR-132, and miR-199a-5p are taken as predictors to classify the samples of three datasets, the pooled sensitivity and specificity is 0.96 and 0.75, respectively, thereby suggesting that these three miRNAs can effectively distinguish COPD patients and controls.
authors.affiliation: School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China.|Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, 100069, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Hua
authors.affiliation: School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China.|Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, 100069, China.
authors.forename: Weiying
authors.initials: W
authors.lastname: Zheng
authors.affiliation: School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China.|Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, 100069, China.
authors.forename: Hong
authors.initials: H
authors.lastname: Xia
authors.affiliation: School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China.|Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, 100069, China.
authors.forename: Ping
authors.initials: P
authors.lastname: Zhou
authors.affiliation: Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100028, China.
authors.forename: Li
authors.initials: L
authors.lastname: An
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000032:analysis; D003198:Computer Simulation; D057225:Data Mining / Q000379:methods; D030541:Databases, Genetic; D005819:Genetic Markers / Q000235:genetics; D006801:Humans; D035683:MicroRNAs / Q000032:analysis / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis* / Q000235:genetics*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018511:Systems Integration; D059467:Transcriptome / Q000235:genetics
chemical_list: D015415:Biomarkers; D005819:Genetic Markers; D035683:MicroRNAs; C547077:MIRN132 microRNA, human; C525067:MIR223, human; C531408:mirn199 microRNA, human
keywords: Chronic obstructive pulmonary disease; differentially expressed; miRNAs; multiple co-inertia