Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Both obesity and low vitamin D levels have been associated with allergic asthma (AA) severity. In the present study, severity of AA was associated with obesity but to the in vitro IgE production. In those patients, higher levels of IL-5, IL-6 and IL-17 were quantified in CD4+ T-cell cultures as compared with patients with mild and moderate AA. In addition, the lowest IL-10 levels were detected in the cell cultures from patients with a worse prognosis. Interestingly, the occurrence of AA elevates the plasma levels of leptin, and this adipokine was positively correlated with the release of IL-5, IL-6 and IL-17, but inversely correlated with IL-10 production, by CD4+ T-cells from patients. In AA-derived CD4+ T-cell cultures, 1,25(OH)2D3 was less efficient at inhibiting IL-5, IL-6 and IL-17 production, and up regulating IL-10 release, as those from healthy subjects. Interestingly, the in vitro immunomodulatory effects of vitamin D were inversely correlated with serum leptin levels. In summary, our findings suggested that obesity, probably due to the overproduction of leptin, negatively impacts AA as it favors imbalance between Th2/Th17 and regulatory phenotypes. The deleterious effects of leptin may also be due to its ability to counter-regulate the immunosuppressive effects of vitamin D.
Pubmed ID: 31173888
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
View all literature mentions