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Asthma-predictive genetic markers in gene expression profiling of peripheral blood mononuclear cells.

ABSTRACT: PURPOSE: We sought to identify asthma-related genes and to examine the potential of these genes to predict asthma, based on expression levels. METHODS: The subjects were 42 asthmatics and 10 normal healthy controls. PBMC RNA was subjected to microarray analysis using a 35K array; t-tests were used to identify genes that were expressed differentially between the two groups. A multiple logistic regression analysis was applied to the differentially expressed genes, and area under the curve (AUC) values from receiver operating characteristic (ROC) curves were obtained. RESULTS: In total, 170 genes were selected using the following criteria: P?0.001 and ?2-fold change. Among these genes, 57 were up-regulated and 113 were down-regulated in asthmatics versus normal controls. A multiple logistic regression analysis was done using more stringent criteria (P?0.001 and ?5-fold change), and eight genes were selected as candidate asthma biomarkers. Using these genes, 255 models (2(8)-1) were generated. Among them, only 85 showed P?0.05 by multiple logistic regression analysis. Based on the AUCs from ROC curves for the 85 models, we found that the best model consisted of the genes MEPE, MLSTD1, and TRIM37. The model showed 0.9928 of the AUC with 98% sensitivity and 80% specificity. CONCLUSIONS: MEPE, MLSTD1, and TRIM37 may be useful biomarkers for asthma.

SUBMITTER: Shin SW

PROVIDER: S-EPMC3178825 | biostudies-other | 2011 Oct

REPOSITORIES: biostudies-other

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Asthma-predictive genetic markers in gene expression profiling of peripheral blood mononuclear cells.

Shin Seung Woo SW Oh Tae Jeong TJ Park Se-Min SM Park Jong Sook JS Jang An Soo AS Park Sung Woo SW Uh Soo Taek ST An Sungwhan S Park Choon-Sik CS

Allergy, asthma & immunology research 20110518 4

<h4>Purpose</h4>We sought to identify asthma-related genes and to examine the potential of these genes to predict asthma, based on expression levels.<h4>Methods</h4>The subjects were 42 asthmatics and 10 normal healthy controls. PBMC RNA was subjected to microarray analysis using a 35K array; t-tests were used to identify genes that were expressed differentially between the two groups. A multiple logistic regression analysis was applied to the differentially expressed genes, and area under the c ...[more]

PMID: 21966607

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Project description:UnlabelledPreeclampsia is a major obstetrical complication affecting maternal and fetal health. While it is clear that there is a substantial placental contribution to preeclampsia pathogenesis, the maternal contribution is less well characterized. We therefore performed a genome-wide transcriptome analysis to explore disease-associated changes in maternal gene expression patterns in peripheral blood mononuclear cells (PBMCs).MethodsPreeclampsia was defined as gestational hypertension, proteinuria and hyperurecimia. Total RNA was isolated from PBMCs obtained from women with uncomplicated pregnancies (n = 5) and women with preeclamptic pregnancies (n = 5). Gene expression analysis was carried out using Agilent oligonucleotide microarrays. Biological pathway analysis was undertaken using Ingenuity Pathway Analysis software. Quantitative real-time PCR (QRTPCR) was performed to validate the gene expression changes of selected genes in normotensive and preeclamptic patients (n = 12 each).ResultsWe identified a total of 368 genes that were differentially expressed in women with preeclampsia compared to normal controls with false discovery rate (FDR) controlled at 10%. In follow up experiments we further analyzed the expression levels of a number of genes that were identified as altered by the microarray data including survivin (BIRC5), caveolin (CAV1), GATA binding protein-1 (GATA1), signal tranducer and activator of transcription 1 (STAT1), E2F transcription factor-1 (E2F1), fibronectin-1 (FN1), interleukin-4 (IL-4), matrix metalloprotease-9 (MMP-9) and WAP four disulfide domain protein (WFDC-1) by QRTPCR. Additionally we performed immuno blot analysis and zymography to verify some of these candidate genes at the protein level. Computational analysis of gene function identified an anti-proliferative and altered immune function cellular phenotype in severe preeclamptic samples.ConclusionsWe have characterized the genome-wide mRNA expression changes associated with preeclampsia-specific genes in circulating maternal blood cells at the time of delivery. In addition to providing information relating to the biological basis of the preeclampsia phenotype, our data provide a number of potential biomarkers for use in the further characterization of this disease.

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Asthma-predictive genetic markers in gene expression profiling of peripheral blood mononuclear cells.

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Asthma-predictive genetic markers in gene expression profiling of peripheral blood mononuclear cells.

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