ArticlePharmacogenomics and personalized medicine2019
Toxicogenomic analysis of publicly available transcriptomic data can predict food, drugs, and chemical-induced asthma.
Article in Pharmacogenomics and personalized medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Identification of Genes Associated with Familial Focal Segmental Glomerulosclerosis Through Transcriptomics and In Silico Analysis, IncludingInternational journal of molecular sciences · 2024Article
- The Role of Systems Biology in Deciphering Asthma Heterogeneity.Life (Basel, Switzerland) · 2022Review
- As We Drink and Breathe: Adverse Health Effects of Microcystins and Other Harmful Algal Bloom Toxins in the Liver, Gut, Lungs and Beyond.Life (Basel, Switzerland) · 2022Review
- In silico Analysis of Publicly Available Transcriptomics Data Identifies Putative Prognostic and Therapeutic Molecular Targets for Papillary Thyroid Carcinoma.International journal of general medicine · 2022Article
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Authors and funding
4 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background: With the increasing incidence of asthma, more attention is focused on the diverse and complex nutritional and environmental triggers of asthma exacerbations. Currently, there are no established risk assessment tools to evaluate asthma triggering potentials of most of the nutritional and environmental triggers encountered by asthmatic patients. PURPOSE: The objective of this study is to devise a reliable workflow, capable of estimating the toxicogenomic effect of such factors on key player genes in asthma pathogenesis.
methodsGene expression extracted from publicly available datasets of asthmatic bronchial epithelium were subjected to a comprehensive analysis of differential gene expression to identify significant genes involved in asthma development and progression. The identified genes were subjected to Gene Set Enrichment Analysis using a total of 31,826 gene sets related to chemical, toxins, and drugs to identify common agents that share similar asthma-related targets genes and signaling pathways.
resultsOur analysis identified 225 differentially expressed genes between severe asthmatic and healthy bronchial epithelium. Gene Set Enrichment Analysis of the identified genes showed that they are involved in response to toxic substances and organic cyclic compounds and are targeted by 41 specific diets, plants products, and plants related toxins (eg adenine, arachidonic acid, baicalein, caffeic acid, corilagin, curcumin, ellagic acid, luteolin, microcystin-RR, phytoestrogens, protoporphyrin IX, purpurogallin, rottlerin, and salazinic acid). Moreover, the identified chemicals share interesting inflammation-related pathways like NF-κB.
conclusionOur analysis was able to explain and predict the toxicity in terms of stimulating the differentially expressed genes between severe asthmatic and healthy epithelium. Such an approach can pave the way to generate a cost-effective and reliable source for asthma-specific toxigenic reports thus allowing the asthmatic patients, physicians, and medical researchers to be aware of the potential triggering factors with fatal consequences.
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