Abstract

Abstract Background: Glucocorticoids are among the most prescribed medications for various indications, and treatment with glucocorticoids is associated with increased morbidity and mortality. A biomarker allowing quantification of glucocorticoid action could improve treatment safety and efficacy. Objective: To identify and validate circulating biomarkers of glucocorticoid action using a clinical experimental study and multi-omic network analysis. Methods: In a randomized, controlled, crossover, single-blind trial, 10 subjects without endogenous glucocorticoid production (Addison’s disease) received intravenous hydrocortisone infusion in a circadian pattern (physiological glucocorticoid exposure) or isotonic saline (glucocorticoid withdrawal) over 22 hours. Food intake and sample collections were standardized during both treatment periods. The transcriptomes of peripheral blood mononuclear cells and adipose tissue, plasma miRNAome and serum metabolome were collected at 7 AM (end of infusion). These multi-omic data were compared between the two interventions, within and between subjects, using network analysis of higher order interactions along with statistical and machine learning approaches. Samples from 120 subjects with varying glucocorticoid exposure from independent studies were used for the replication of the miRNA findings. The study was pre-registered at ClinicalTrials.gov with identifier NCT02152553. Results: We identified a transcriptomic profile derived from both peripheral blood mononuclear cells and adipose tissue, and a multi-omic signature including genes, miRNAs and metabolites that were associated with glucocorticoid exposure. Within the multi-omic signature we identified a single microRNA (miR-122-5p, p=0.009) regulated by glucocorticoid exposure, which we then replicated as a novel biomarker of glucocorticoid action in 120 subjects from independent studies (0.01 ≤ p ≤ 0.05). Conclusions: The discovery of miR-122-5p as a novel circulating biomarker of glucocorticoid action may have a significant impact on clinical practice. Our data also improves the understanding of glucocorticoid action and may have impact on future studies on the mechanistic understanding for the role of glucocorticoids in the etiology of common diseases, such as cardiovascular disease and obesity.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.