ArticleAllergy, asthma & immunology research2011
Asthma-predictive genetic markers in gene expression profiling of peripheral blood mononuclear cells.
Article in Allergy, asthma & immunology research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Lysosome and Cytoskeleton Pathways Are Robustly Enriched in the Blood of Septic Patients: A Meta-Analysis of Transcriptomic Data.Mediators of inflammation · 2015Pooled it
- LMAN1 is a receptor for house dust mite allergens.Cell reports · 2023Article
- The Role of Systems Biology in Deciphering Asthma Heterogeneity.Life (Basel, Switzerland) · 2022Review
- Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis.Scientific reports · 2022Article
- Derangement of cell cycle markers in peripheral blood mononuclear cells of asthmatic patients as a reliable biomarker for asthma control.Scientific reports · 2021Article
- Transcriptional Changes in Chronic Rhinosinusitis with Asthma Favor a Type 2 Molecular Endotype Independent of Polyp Status.Journal of asthma and allergy · 2021Article
- Whole blood vs PBMC: compartmental differences in gene expression profiling exemplified in asthma.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2019Article
- Tripartite motif-containing protein 37 is overexpressed in human glioma and its downregulation inhibits human glioma cell growthInternational journal of clinical and experimental pathology · 2018Article
- Precision autophagy directed by receptor regulators - emerging examples within the TRIM family.Journal of cell science · 2016Review
- DNA methylation profiles of airway epithelial cells and PBMCs from healthy, atopic and asthmatic children.PloS one · 2012Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeWe sought to identify asthma-related genes and to examine the potential of these genes to predict asthma, based on expression levels.
methodsThe 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.
resultsIn 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.
conclusionsMEPE, MLSTD1, and TRIM37 may be useful biomarkers for asthma.
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