Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

To identify gene markers which differentiate between AERD and ATA with a high discriminative power.

ABSTRACT: Aspirin-exacerbated respiratory disease (AERD) has association with severe asthma and aspirin can cause asthma to worsen, often in the form of a severe and sudden attack. The oral aspirin challenge (OAC) is the gold standard to confirm the diagnosis of AERD but it is time consuming and produces serious complications in some cases. Therefore more efficient and practical method is needed to predict AERD patients. The aim of the present study was to identify AERD-related gene expression in peripheral blood mononuclear cells (PBMCs) and examine the diagnostic potential of these candidate gene(s) for predicting AERD. To do this, RNAs from 24 subjects with AERD and 18 subjects with aspirin-tolerant asthma (ATA) were subjected to microarray analysis of ~34,560 genes. In total, 10 genes were selected as candidate gene markers by applying p ≤ 0.001(t-test) and ≥ 8-fold change and to correct for multiple comparisons, the false discovery rate (FDR) analyses were performed. By applying multiple logistic regression analysis, among possible 1023 models (210–1), a model consisting of CNKSR3, SPTBN2, and IMPACT was selected as candidate set, because this set showed the best AUC (0.98) with 88% sensitivity and 89% specificity. For validation, mRNA levels by real-time PCR on PBMCs from two population sets in a gene-chip study and another replication sample: 20 AERD, 20 ATA, and 8 normal controls, were significantly different between groups with 100% sensitivity and 100% specificity in each of the two population sets. However, IMPACT gene didn’t differentiate between AERD and normal controls. The set of the two genes (CNKSR3 and SPTBN2) showed the best AUC (0.96) with 88% sensitivity and 94% specificity in a gene chip study sample. In addition, this set showed perfect discriminative power with AUC (1.0, 100% sensitivity and 100% specificity) in each of the two population sets: the gene-chip samples and the replication samples. It also showed perfect discrimination for AERD form NC (AUC 1.0) and ATA from NC (AUC 1.0). In conclusion, we developed the two gene markers (CNKSR3 and SPTBN2) of PBMC which differentiate between AERD and ATA with a perfect discriminative power. These gene markers may be an efficient and practical method useful for predicting AERD. Total 24 AERD (Aspirin-exacerbated respiratory disease) and 18 ATA(aspirin-tolerant asthma) samples were used to find bio-markers using 35K op-array.

ORGANISM(S): Homo sapiens

SUBMITTER: Seung-Woo Shin

PROVIDER: E-GEOD-45847 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Aspirin-exacerbated respiratory disease (AERD) has association with severe asthma and aspirin can cause asthma to worsen, often in the form of a severe and sudden attack. The oral aspirin challenge (OAC) is the gold standard to confirm the diagnosis of AERD but it is time consuming and produces serious complications in some cases. Therefore more efficient and practical method is needed to predict AERD patients. The aim of the present study was to identify AERD-related gene expression in peripheral blood mononuclear cells (PBMCs) and examine the diagnostic potential of these candidate gene(s) for predicting AERD. To do this, RNAs from 24 subjects with AERD and 18 subjects with aspirin-tolerant asthma (ATA) were subjected to microarray analysis of ~34,560 genes. In total, 10 genes were selected as candidate gene markers by applying p ≤ 0.001(t-test) and ≥ 8-fold change and to correct for multiple comparisons, the false discovery rate (FDR) analyses were performed. By applying multiple logistic regression analysis, among possible 1023 models (210–1), a model consisting of CNKSR3, SPTBN2, and IMPACT was selected as candidate set, because this set showed the best AUC (0.98) with 88% sensitivity and 89% specificity. For validation, mRNA levels by real-time PCR on PBMCs from two population sets in a gene-chip study and another replication sample: 20 AERD, 20 ATA, and 8 normal controls, were significantly different between groups with 100% sensitivity and 100% specificity in each of the two population sets. However, IMPACT gene didn’t differentiate between AERD and normal controls. The set of the two genes (CNKSR3 and SPTBN2) showed the best AUC (0.96) with 88% sensitivity and 94% specificity in a gene chip study sample. In addition, this set showed perfect discriminative power with AUC (1.0, 100% sensitivity and 100% specificity) in each of the two population sets: the gene-chip samples and the replication samples. It also showed perfect discrimination for AERD form NC (AUC 1.0) and ATA from NC (AUC 1.0). In conclusion, we developed the two gene markers (CNKSR3 and SPTBN2) of PBMC which differentiate between AERD and ATA with a perfect discriminative power. These gene markers may be an efficient and practical method useful for predicting AERD.

Project description:Differentially methylated oral squamous cell carcinoma (OSCC) biomarkers, identified in-vitro and validated in well-characterized surgical specimens, have shown poor clinical correlation in cohorts with different risk profiles. To overcome this lack of relevance we used the HumanMethylation27 BeadChip, publicly available methylation and expression array data, and Quantitative Methylation Specific PCR to uncover differential methylation in OSCC clinical samples with heterogeneous risk profiles. A two stage-design consisting of Discovery and Prevalence screens was used to identify differential promoter methylation and deregulated pathways in patients diagnosed with OSCC and head and neck squamous cell carcinoma. Promoter methylation of KIF1A (k=0.64), HOXA9 (k=0.60), NID2 (k=0.60), and EDNRB (k=0.60) had a moderate to substantial agreement with clinical diagnosis in the Discovery screen. HOXA9 had 68% sensitivity, 100% specificity and a 0.81 AUC. NID2 had 71% sensitivity, 100% specificity and a 0.79 AUC. In the Prevalence screen HOXA9 (k=0.82) and NID2 (k=0.80) had an almost perfect agreement with histologic diagnosis. HOXA9 had 85% sensitivity, 97% specificity and a 0.95 AUC. NID2 had 87% sensitivity, 95% specificity and a 0.91 AUC. A HOXA9 and NID2 gene panel had 94% sensitivity, 97% specificity and a 0.97 AUC. In saliva from OSCC cases and controls HOXA9 had 75% sensitivity, 53% specificity and a 0.75 AUC. NID2 had 87% sensitivity, 21% specificity and a 0.73 AUC. This Phase I Biomarker Development Trial identified a panel of differentially methylated genes in normal and OSCC clinical samples from patients with heterogeneous risk profiles. This panel may be useful for early detection and cancer prevention studies. The 12 samples analyzed comprise equal numbers of three tissue-types: Primary oral squamous cell carcinoma, Oral leukoplakia and Normal oral mucosa. Gender, age and smoking-status were approximately equally represented in these goups. Normal oral mucosa served as a control.

Dataset Information

To identify gene markers which differentiate between AERD and ATA with a high discriminative power.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets