Plasma metabolomic profile varies with glucocorticoid dose in patients with congenital adrenal hyperplasia

Serum metabolomics of treatment response in myasthenia gravis

OBJECTIVE

High-dose prednisone use, lasting several months or longer, is the primary initial therapy for myasthenia gravis (MG). Upwards of a third of patients do not respond to treatment. Currently no biomarkers can predict clinical responsiveness to corticosteroid treatment. We conducted a discovery-based study to identify treatment responsive biomarkers in MG using sera obtained at study entry to the thymectomy clinical trial (MGTX), an NIH-sponsored randomized, controlled study of thymectomy plus prednisone versus prednisone alone.

METHODS

We applied ultra-performance liquid chromatography coupled with electro-spray quadrupole time of flight mass spectrometry to obtain comparative serum metabolomic and lipidomic profiles at study entry to correlate with treatment response at 6 months. Treatment response was assessed using validated outcome measures of minimal manifestation status (MMS), MG-Activities of Daily Living (MG-ADL), Quantitative MG (QMG) score, or a strictly defined composite measure of response.

RESULTS

Increased serum levels of phospholipids were associated with treatment response as assessed by QMG, MMS, and the Responders classification, but all measures showed limited overlap in metabolomic profiles, in particular the MG-ADL. A panel including histidine, free fatty acid (13:0), γ-cholestenol and guanosine was highly predictive of the strictly defined treatment response measure. The AUC in Responders' prediction for these markers was 0.90 irrespective of gender, age, thymectomy or baseline prednisone use. Pathway analysis suggests that xenobiotic metabolism could play a major role in treatment resistance. There was no association with outcome and gender, age, thymectomy or baseline prednisone use.

INTERPRETATION

We have defined a metabolomic and lipidomic profile that can now undergo validation as a treatment predictive marker for MG patients undergoing corticosteroid therapy. Metabolomic profiles of outcome measures had limited overlap consistent with their assessing distinct aspects of treatment response and supporting unique biological underpinning for each outcome measure. Interindividual variation in prednisone metabolism may be a determinate of how well patients respond to treatment.

Association of low-dose glucocorticoid use and infection occurrence in systemic lupus erythematosus patients: a prospective cohort study

BACKGROUND

Infection is a major cause of mortality in patients with systemic lupus erythematosus (SLE). Therefore, minimizing the risk of infection is an important clinical goal to improve the long-term prognosis of SLE patients. Treatment with ≥7.5 mg prednisolone (PSL) or equivalent has been reported to increase the risk of infections. However, it remains unclear whether <7.5 mg PSL or equivalent dose affects the risk of infection in SLE patients. This study evaluated the association between the occurrence of infection in patients with SLE and low-dose glucocorticoid (GC) usage, especially <7.5 mg PSL or equivalent, to explore the GC dose that could reduce infection occurrence.

METHODS

This prospective cohort study included patients from the Japanese multicenter registry of patients with SLE (defined as ≥4 American College of Rheumatology 1997 revised criteria) over 20 years of age. The PSL dose was categorized as PSL 0-2.5, 2.6-5.0, 5.1-7.5, and 7.6-15.0 mg. The primary outcome was infection requiring hospitalization. We conducted a multivariable analysis using time-dependent Cox regression analysis to assess the hazard ratio of infection occurrence compared with a dose of 0-2.5 mg PSL or equivalent in the other three PSL dose groups. Based on previous reports and clinical importance, the covariates selected were age, sex, and concurrent use of immunosuppressants with GC. In addition, two sensitivity analyses were conducted.

RESULTS

The mean age of the 509 SLE patients was 46.7 years; 89.0% were female, and 77.2% used multiple immunosuppressants concomitantly. During the observation period, 52 infections requiring hospitalization occurred. The incidence of infection with a PSL dose of 5.0-7.5 mg was significantly higher than that in the PSL 0-2.5 mg group (adjusted hazard ratio: 6.80, 95% confidence interval: 2.17-21.27). The results of the two sensitivity analyses were similar.

CONCLUSIONS

Our results suggested that the use of 5.0-7.5 mg PSL or equivalent could pose an infection risk in SLE patients. This finding indicates that PSL dose should be reduced to as low as possible in SLE patients to avoid infection.

Approach to the Patient With Glucocorticoid-induced Adrenal Insufficiency

Glucocorticoid-induced adrenal insufficiency is caused by exogenous glucocorticoid suppression of the hypothalamic-pituitary-adrenal axis and is the most prevalent form of adrenal insufficiency. The condition is important to diagnose given the risk of life-threatening adrenal crisis and impact on patients' quality of life. The diagnosis is made with a stimulation test such as the ACTH test. Until now, testing for glucocorticoid-induced adrenal insufficiency has often been based on clinical suspicion rather than routinely but accumulating evidence indicates that a significant number of cases will remain unrecognized. During ongoing oral glucocorticoid treatment or initially after withdrawal, ~50% of patients have adrenal insufficiency, but, outside clinical studies, ≤ 1% of patients have adrenal testing recorded. More than 70% of cases are identified during acute hospital admission, where the diagnosis can easily be missed because symptoms of adrenal insufficiency are nonspecific and overlap those of the underlying and intercurrent conditions. Treatment of severe glucocorticoid-induced adrenal insufficiency should follow the principles for treatment of central adrenal insufficiency. The clinical implications and thus indication to treat mild-moderate adrenal deficiency after glucocorticoid withdrawal has not been established. Also, the indication of adding stress dosages of glucocorticoid during ongoing glucocorticoid treatment remains unclear. In patients with established glucocorticoid-induced adrenal insufficiency, high rates of poor confidence in self-management and delayed glucocorticoid administration in the acute setting with an imminent adrenal crisis call for improved awareness and education of clinicians and patients. This article reviews different facets of glucocorticoid-induced adrenal insufficiency and discusses approaches to the condition in common clinical situations.

Metabolomic Abnormalities in Serum from Untreated and Treated Dogs with Hyper- and Hypoadrenocorticism

The adrenal glands play a major role in metabolic processes, and both excess and insufficient serum cortisol concentrations can lead to serious metabolic consequences. Hyper- and hypoadrenocorticism represent a diagnostic and therapeutic challenge. Serum samples from dogs with untreated hyperadrenocorticism (n = 27), hyperadrenocorticism undergoing treatment (n = 28), as well as with untreated (n = 35) and treated hypoadrenocorticism (n = 23) were analyzed and compared to apparently healthy dogs (n = 40). A validated targeted proton nuclear magnetic resonance (¹H NMR) platform was used to quantify 123 parameters. Principal component analysis separated the untreated endocrinopathies. The serum samples of dogs with untreated endocrinopathies showed various metabolic abnormalities with often contrasting results particularly in serum concentrations of fatty acids, and high- and low-density lipoproteins and their constituents, which were predominantly increased in hyperadrenocorticism and decreased in hypoadrenocorticism, while amino acid concentrations changed in various directions. Many observed serum metabolic abnormalities tended to normalize with medical treatment, but normalization was incomplete when compared to levels in apparently healthy dogs. Application of machine learning models based on the metabolomics data showed good classification, with misclassifications primarily observed in treated groups. Characterization of metabolic changes enhances our understanding of these endocrinopathies. Further assessment of the recognized incomplete reversal of metabolic alterations during medical treatment may improve disease management.

Untargeted Plasma Metabolomics Unravels a Metabolic Signature for Tissue Sensitivity to Glucocorticoids in Healthy Subjects: Its Implications in Dietary Planning for a Healthy Lifestyle

In clinical practice, differences in glucocorticoid sensitivity among healthy subjects may influence the outcome and any adverse effects of glucocorticoid therapy. Thus, a fast and accurate methodology that could enable the classification of individuals based on their tissue glucocorticoid sensitivity would be of value. We investigated the usefulness of untargeted plasma metabolomics in identifying a panel of metabolites to distinguish glucocorticoid-resistant from glucocorticoid-sensitive healthy subjects who do not carry mutations in the human glucocorticoid receptor (NR3C1) gene. Applying a published methodology designed for the study of glucocorticoid sensitivity in healthy adults, 101 healthy subjects were ranked according to their tissue glucocorticoid sensitivity based on 8:00 a.m. serum cortisol concentrations following a very low-dose dexamethasone suppression test. Ten percent of the cohort, i.e., 11 participants, on each side of the ranking, with no NR3C1 mutations or polymorphisms, were selected, respectively, as the most glucocorticoid-sensitive and most glucocorticoid-resistant of the cohort to be analyzed and compared with untargeted blood plasma metabolomics using gas chromatography–mass spectrometry (GC–MS). The acquired metabolic profiles were evaluated using multivariate statistical analysis methods. Nineteen metabolites were identified with significantly lower abundance in the most sensitive compared to the most resistant group of the cohort, including fatty acids, sugar alcohols, and serine/threonine metabolism intermediates. These results, combined with a higher glucose, sorbitol, and lactate abundance, suggest a higher Cori cycle, polyol pathway, and inter-tissue one-carbon metabolism rate and a lower fat mobilization rate at the fasting state in the most sensitive compared to the most resistant group. In fact, this was the first study correlating tissue glucocorticoid sensitivity with serine/threonine metabolism. Overall, the observed metabolic signature in this cohort implies a worse cardiometabolic profile in the most glucocorticoid-sensitive compared to the most glucocorticoid-resistant healthy subjects. These findings offer a metabolic signature that distinguishes most glucocorticoid-sensitive from most glucocorticoid-resistant healthy subjects to be further validated in larger cohorts. Moreover, they support the correlation of tissue glucocorticoid sensitivity with insulin resistance and metabolic syndrome-associated pathways, further emphasizing the need for nutritionists and doctors to consider the tissue glucocorticoid sensitivity in dietary and exercise planning, particularly when these subjects are to be treated with glucocorticoids.

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.

Blood metabolomics in infants enrolled in a dose escalation pilot trial of budesonide in surfactant

BACKGROUND

The pathogenesis of BPD includes inflammation and oxidative stress in the immature lung. Corticosteroids improve respiratory status and outcome, but the optimal treatment regimen for benefit with low systemic effects is uncertain.

METHODS

In a pilot dose escalation trial, we administered ≤5 daily doses of budesonide in surfactant to 24 intubated premature infants (Steroid And Surfactant in ELGANs (SASSIE)). Untargeted metabolomics was performed on dried blood spots using UPLC-MS/MS. Tracheal aspirate IL-8 concentration was determined as a measure of lung inflammation.

RESULTS

Metabolomics data for 829 biochemicals were obtained on 121 blood samples over 96 h from 23 infants receiving 0.025, 0.05, or 0.1 mg budesonide/kg. Ninety metabolites were increased or decreased in a time- and dose-dependent manner at q ≤ 0.1 with overrepresentation in lipid and amino acid super pathways. Different dose response patterns occurred, with negative regulation associated with highest sensitivity to budesonide. Baseline levels of 22 regulated biochemicals correlated with lung inflammation (IL-8), with highest significance for sphingosine and thiamin.

CONCLUSIONS

Numerous metabolic pathways are regulated in a dose-dependent manner by glucocorticoids, which apparently act via distinct mechanisms that impact dose sensitivity. The findings identify candidate blood biochemicals as biomarkers of lung inflammation and systemic responses to corticosteroids.

IMPACT

Treatment of premature infants in respiratory failure with 0.1 mg/kg intra-tracheal budesonide in surfactant alters levels of ~11% of detected blood biochemicals in discrete time- and dose-dependent patterns. A subset of glucocorticoid-regulated biochemicals is associated with lung inflammatory status as assessed by lung fluid cytokine concentration. Lower doses of budesonide in surfactant than currently used may provide adequate anti-inflammatory responses in the lung with fewer systemic effects, improving the benefit:risk ratio.

Clinical outcomes and characteristics of P30L mutations in congenital adrenal hyperplasia due to 21-hydroxylase deficiency

Despite numerous studies in the field of congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency, some clinical variability of the presentation and discrepancies in the genotype/phenotype correlation are still unexplained. Some, but not all, discordant phenotypes caused by mutations with known enzyme activity have been explained by in silico structural changes in the 21-hydroxylase protein. The incidence of P30L mutation varies in different populations and is most frequently found in several Central and Southeast European countries as well as Mexico. Patients carrying P30L mutation present predominantly as non-classical CAH; however, simple virilizing forms are found in up to 50% of patients. Taking into consideration the residual 21-hydroxulase activity present with P30L mutation this is unexpected. Different mechanisms for increased androgenization in patients carrying P30L mutation have been proposed including influence of different residues, accompanying promotor allele variability or mutations, and individual androgene sensitivity. Early diagnosis of patients who would present with SV is important in order to improve outcome. Outcome studies of CAH have confirmed the uniqueness of this mutation such as difficulties in phenotype classification, different fertility, growth, and psychologic issues in comparison with other genotypes. Additional studies of P30L mutation are warranted.

Effect of congenital adrenal hyperplasia treated by glucocorticoids on plasma metabolome: a machine-learning-based analysis

Background. Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency leads to impaired cortisol biosynthesis. Treatment includes glucocorticoid supplementation. We studied the specific metabolomics signatures in CAH patients using two different algorithms. Methods. In a case-control study of CAH patients matched on sex and age with healthy control subjects, two metabolomic analyses were performed: one using MetaboDiff, a validated differential metabolomic analysis tool and the other, using Predomics, a novel machine-learning algorithm. Results. 168 participants were included (84 CAH patients). There was no correlation between plasma cortisol levels during glucocorticoid supplementation and metabolites in CAH patients. Indoleamine 2,3-dioxygenase enzyme activity was correlated with ACTH (rho coefficient = −0.25, p-value = 0.02), in CAH patients but not in controls subjects. Overall, 33 metabolites were significantly altered in CAH patients. Main changes came from: purine and pyrimidine metabolites, branched aminoacids, tricarboxylic acid cycle metabolites and associated pathways (urea, glucose, pentose phosphates). MetaboDiff identified 2 modules that were significantly different between both groups: aminosugar metabolism and purine metabolism. Predomics found several interpretable models which accurately discriminated the two groups (accuracy of 0.86 and AUROC of 0.9). Conclusion. CAH patients and healthy control subjects exhibit significant differences in plasma metabolomes, which may be explained by glucocorticoid supplementation.

Glucocorticoid deficiency causes transcriptional and post-transcriptional reprogramming of glutamine metabolism

Background

Deficient glucocorticoid biosynthesis leading to adrenal insufficiency is life-threatening and is associated with significant co-morbidities. The affected pathways underlying the pathophysiology of co-morbidities due to glucocorticoid deficiency remain poorly understood and require further investigation.

Methods

To explore the pathophysiological processes related to glucocorticoid deficiency, we have performed global transcriptional, post-transcriptional and metabolic profiling of a cortisol-deficient zebrafish mutant with a disrupted ferredoxin (fdx1b) system.

Findings

fdx1b^−/− mutants show pervasive reprogramming of metabolism, in particular of glutamine-dependent pathways such as glutathione metabolism, and exhibit changes of oxidative stress markers. The glucocorticoid-dependent post-transcriptional regulation of key enzymes involved in de novo purine synthesis was also affected in this mutant. Moreover, fdx1b^−/− mutants exhibit crucial features of primary adrenal insufficiency, and mirror metabolic changes detected in primary adrenal insufficiency patients.

Interpretation

Our study provides a detailed map of metabolic changes induced by glucocorticoid deficiency as a consequence of a disrupted ferredoxin system in an animal model of adrenal insufficiency. This improved pathophysiological understanding of global glucocorticoid deficiency informs on more targeted translational studies in humans suffering from conditions associated with glucocorticoid deficiency.

Fund

Marie Curie Intra-European Fellowships for Career Development, HGF-programme BIFTM, Deutsche Forschungsgemeinschaft, BBSRC.