Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized...

Area of Science:

• Endocrinology
• Molecular Biology
• Pharmacogenomics

Background:

• Glucocorticoids are widely prescribed but lack biomarkers to quantify their effects.
• Accurate measurement of glucocorticoid action is crucial for optimizing treatment.

Purpose of the Study:

• To identify and validate circulating biomarkers for glucocorticoid action.
• To enable personalized glucocorticoid therapy and understand disease etiology.

Main Methods:

• A randomized, crossover, single-blind study in 10 subjects with primary adrenal insufficiency.
• Integrated multi-omic analysis of transcriptome, plasma miRNAome, and serum metabolomics.
• Comparison of these omics between physiological glucocorticoid exposure and withdrawal.

Main Results:

• Identified a transcriptomic profile predictive of glucocorticoid exposure.
• Discovered microRNA (miR-122-5p) correlated with glucocorticoid-regulated genes and metabolites (p=0.009).
• Replicated miR-122-5p findings in independent studies with varying glucocorticoid exposure (0.01 ≤ p≤0.05).

Conclusions:

• Established a basis for discovering biomarkers to measure glucocorticoid effects.
• Potential for individualizing and optimizing glucocorticoid therapy.
• Insights into diseases linked to unphysiological glucocorticoid exposure, like cardiovascular disease and obesity.