| Title |
Differential gene expression profile in PBMCs from subjects with AERD and ATA: a gene marker for AERD
|
|---|---|
| Published in |
Molecular Genetics and Genomics, March 2012
|
| DOI | 10.1007/s00438-012-0685-9 |
| Pubmed ID | |
| Authors |
SeungWoo Shin, Jong Sook Park, Yoon-Jeong Kim, TaeJeong Oh, Sungwhan An, Choon-Sik Park |
| Abstract |
Aspirin-exacerbated respiratory disease (AERD) is associated with severe asthma and aspirin can cause asthma to worsen, often in the form of a severe and sudden attack. The oral aspirin challenge 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 analyses were performed. By applying multiple logistic regression analysis, among possible 1,023 models (2(10)-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 did not 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 from 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 for predicting AERD. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Colombia | 1 | 3% |
| Unknown | 36 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 22% |
| Student > Doctoral Student | 6 | 16% |
| Student > Master | 6 | 16% |
| Student > Postgraduate | 3 | 8% |
| Student > Bachelor | 2 | 5% |
| Other | 6 | 16% |
| Unknown | 6 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 38% |
| Biochemistry, Genetics and Molecular Biology | 5 | 14% |
| Agricultural and Biological Sciences | 5 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
| Immunology and Microbiology | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 7 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 August 2018.
All research outputs
#8,262,445
of 25,374,917 outputs
Outputs from Molecular Genetics and Genomics
#904
of 3,319 outputs
Outputs of similar age
#55,354
of 172,464 outputs
Outputs of similar age from Molecular Genetics and Genomics
#3
of 6 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 3,319 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 72% of its peers.
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