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

Background: Glucocorticoids are among the most commonly prescribed drugs, but there is no biomarker that can quantify their action. The aim of the study was to identify and validate circulating biomarkers of glucocorticoid action. Methods: In a randomized, crossover, single-blind, discovery study, 10 subjects with primary adrenal insufficiency (and no other endocrinopathies) were admitted at the in-patient clinic and studied during physiological glucocorticoid exposure and withdrawal. A randomization plan before the first intervention was used. Besides mild physical and/or mental fatigue and salt craving, no serious adverse events were observed. The transcriptome in peripheral blood mononuclear cells and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions using integrated multi-omic analysis. Results: We identified a transcriptomic profile derived from two tissues and a multi-omic cluster, both predictive of glucocorticoid exposure. A microRNA (miR-122-5p) that was correlated with genes and metabolites regulated by glucocorticoid exposure was identified (p=0.009) and replicated in independent studies with varying glucocorticoid exposure (0.01 ≤ p≤0.05). Conclusions: We have generated results that construct the basis for successful discovery of biomarker(s) to measure effects of glucocorticoids, allowing strategies to individualize and optimize glucocorticoid therapy, and shedding light on disease etiology related to unphysiological glucocorticoid exposure, such as in cardiovascular disease and obesity. Funding: The Swedish Research Council (Grant 2015-02561 and 2019-01112); The Swedish federal government under the LUA/ALF agreement (Grant ALFGBG-719531); The Swedish Endocrinology Association; The Gothenburg Medical Society; Wellcome Trust; The Medical Research Council, UK; The Chief Scientist Office, UK; The Eva Madura's Foundation; The Research Foundation of Copenhagen University Hospital; and The Danish Rheumatism Association. Clinical trial number: NCT02152553.

Several diseases, including asthma, arthritis, some skin conditions, and cancer, are treated with medications called glucocorticoids, which are synthetic versions of human hormones. These drugs are also used to treat people with a condition call adrenal insufficiency who do not produce enough of an important hormone called cortisol. Use of glucocorticoids is very common, the proportion of people in a given country taking them can range from 0.5% to 21% of the population depending on the duration of the treatment. But, like any medication, glucocorticoids have both benefits and risks: people who take glucocorticoids for a long time have an increased risk of diabetes, obesity, cardiovascular disease, and death. Because of the risks associated with taking glucocorticoids, it is very important for physicians to tailor the dose to each patient's needs. Doing this can be tricky, because the levels of glucocorticoids in a patient's blood are not a good indicator of the medication's activity in the body. A test that can accurately measure the glucocorticoid activity could help physicians personalize treatment and reduce harmful side effects. As a first step towards developing such a test, Chantzichristos et al. identified a potential way to measure glucocorticoid activity in patient's blood. In the experiments, blood samples were collected from ten patients with adrenal insufficiency both when they were on no medication, and when they were taking a glucocorticoid to replace their missing hormones. Next, the blood samples were analyzed to determine which genes were turned on and off in each patient with and without the medication. They also compared small molecules in the blood called metabolites and tiny pieces of genetic material called microRNAs that turn genes on and off. The experiments revealed networks of genes, metabolites, and microRNAs that are associated with glucocorticoid activity, and one microRNA called miR-122-5p stood out as a potential way to measure glucocorticoid activity. To verify this microRNA's usefulness, Chantzichristos et al. looked at levels of miR-122-5p in people participating in three other studies and confirmed that it was a good indicator of the glucocorticoid activity. More research is needed to confirm Chantzichristos et al.'s findings and to develop a test that can be used by physicians to measure glucocorticoid activity. The microRNA identified, miR-122-5p, has been previously linked to diabetes, so studying it further may also help scientists understand how taking glucocorticoids may increase the risk of developing diabetes and related diseases.

A polymorphism in the CYP17A1 gene influences the therapeutic response to steroidogenesis inhibitors in Cushing's syndrome.

CONTEXT: Steroidogenesis inhibitors, such as ketoconazole (KTZ) and metyrapone (MTP), are used to lower hypercortisolism in patients with Cushing's syndrome (CS). Cortisol normalization is not reached in all patients taking these medications. OBJECTIVE: To test the hypothesis that variants in genes affecting steroidogenesis contribute to different responses to KTZ and/or MTP in patients with CS. PATIENTS AND METHODS: Fifty-four CS patients (46 women; mean [±SD] age, 39.7±12.7; 83% with Cushing's disease [CD] and 17% with an adrenal adenoma) preoperatively treated with KTZ (20%), MTP (37%) or a combination of both (43%). Thirty-nine of these (72%) were described in a previous study investigating the outcome of preoperative treatment with KTZ or MTP in CS patients. Following single-nucleotide polymorphisms (SNPs) were analysed: rs6410 (CYP11B1 gene), rs1799998 and rs4546 (CYP11B2 gene), and rs6163 (CYP17A1 gene). The associations between SNPs and cortisol levels at the end of medical treatment were evaluated. RESULTS: Normalization of urinary free cortisol (UFC) was achieved in 50% of patients after 5 months of treatment. Patients carrying the CC genotype of SNP rs6163 were more likely to be controlled than AC/AA (OR 0.25 [95%CI, 0.075-0.88]; P=.031). When only patients reaching eucortisolism after medical treatment were analysed, median interquartile range (IQR) duration of treatment was shorter in patients carrying the CC genotype of SNP rs6163 as compared to AA/AC carriers (4 [4.57] months vs 5.2 [6.1] months; P=.026). CONCLUSIONS: A polymorphism in the CYP17A1 gene was associated with the response to steroidogenesis inhibitors in CS. Genetic differences in the steroidogenic enzymes might account for inter-individual variations in the responsiveness to adrenal-blocking agents.

Reverse feeding suppresses the activity of the GH axis in rats and induces a preobesogenic state.

Reversed feeding (RF) is known to disrupt hormone rhythmicity and metabolism. Although these effects may be mediated in part by phase inversion of glucocorticoid secretion, the precise mechanism is incompletely characterized. In this study, we demonstrate that acute nocturnal food deprivation in male rats suppressed the amplitude of spontaneous GH secretion during the dark phase by 62% (P < 0.001), without affecting baseline secretion. Prolonged RF, which reduced pituitary weight (by 22%; P < 0.05), also suppressed GH pulse height sufficiently to reduce skeletal growth (by 4-5%; P < 0.01) and terminal liver weight (by 11%; P < 0.001). Despite this suppression of the GH axis, proportionate adiposity was not elevated, probably due to the accompanying 16% reduction in cumulative food intake (P < 0.01). We demonstrate that RF also resulted in phase inversion of core clock gene expression in liver, abdominal white adipose tissue (WAT) and skeletal muscle, without affecting their expression patterns in the suprachiasmatic nucleus. In addition, RF resulted in phase inversion of hepatic peroxisome proliferator-activated receptor γ2 mRNA expression, a 3- to 5-fold elevation in fatty acid synthase mRNA in WAT in both light- and dark-phase samples (P < 0.01) and an elevation in muscle uncoupling protein 3 mRNA expression at the beginning of the light phase (P < 0.01). Consumption of a high-fat diet increased inguinal (by 36%; P < 0.05) and retroperitoneal WAT weight (by 72%; P < 0.01) only in RF-maintained rats, doubling the efficiency of lipid accumulation (P < 0.05). Thus, RF not only desynchronizes central and peripheral circadian clocks, and suppresses nocturnal GH secretion, but induces a preobesogenic state.