Addison Disease
Conditions
Keywords
Biomarker, Glucocorticoids, Metabolism, Pharmacology, Metabolomics
Brief summary
The investigators have shown that patients with adrenal insufficiency (Addison's disease), a rare disorder, have doubled the expected mortality rate in Sweden despite Standard of Care glucocorticoid (GC) replacement. One % of the Swedish population are, however, receiving GCs for inflammatory diseases, but management is empirical and adjusted to underlying disease activity. The desired anti-inflammatory therapeutic effects cannot be differentiated from the adverse metabolic (osteoporosis, obesity, diabetes mellitus) and immunosuppressive side effects of GC. This frequently results in suboptimal GC therapy with adverse effects due to over-dosing or poor efficacy due to under-dosing. The primary aim is to identify a biomarker for the metabolic effects of GCs. Patients with Addison's disease completely lack endogenous GCs and can therefore be considered a human GC knock-out model. They can therefore be studied during near-physiological exposure and during GC starvation. This will uniquely allow a very clean biomarker identification model (using transcriptomics, proteomics and metabolomics). The secondary aim is to validate candidate biomarker(s) in a dose-response study using the same patient population. A biomarker of GC actions will make it possible to individualised therapy during pharmacological GC treatment. It would allow GC replacement to be monitored in Addison's disease and could become a specific diagnostic tool in patients with GC deficiency and excess (Cushings syndrome).
Interventions
DRUGHydrocortisone
DRUGPlacebo
Sponsors
Vastra Gotaland Region
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT
Masking
SINGLE (Subject)
Eligibility
Sex/Gender
ALL
Age
20 Years to 60 Years
Healthy volunteers
No
Inclusion criteria
* Primary adrenal insufficiency under stable glucocorticoid replacement therapy (15-30 mg of Hydrocortisone stable dose the last 3 months) due to autoimmune adrenalitis (disease diagnosed at least 12 months before inclusion), age 20-60 years, BMI 20-30 kg/m2, and ability to comply with the protocol procedures.
Exclusion criteria
* Glucocorticoid replacement therapy for indication other than primary adrenal treatment, any treatment with sex hormones inclusive contraceptive drugs, treatment with levothyroxine, diabetes mellitus, renal or liver failure, significant and symptomatic cardiovascular disease.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Protein profile changes between a state of GC starvation and near physiological GC exposure. | Changes in proteome (g/dl or umol/l) during 24 hours under two different states of GC exposure. | Using mass spectrometry, protein profile changes in blood, urine and adipose tissue are going to be identified between four points of time during two states: morning and midnight during near physiological GC exposure (sampling 1 and 2), morning and midnight during GC starvation (sampling 3 and 4). Quantitative measurements of all proteins will be used in the bioinformatic analysis. The bioinformatics strategic consists of a stepwise approach based on random forest analysis. Key features in the analysis include finding candidate markers that are increased during normal GC exposure (sampling 1 and 2), reduced during GC starvation (sampling 3 and 4) and exclusion of factors with high variability within normal subjects. Putative biomarkers will go through two levels of internal cross-validation. The investigators would like that this part of the project is not going to be public. |
| Metabolite profile changes between a state of GC starvation and near physiological GC exposure. | Changes in metabolome (units depending on the kind of metabolome) during 24 hours under two different states of GC exposure. | Using mass spectrometry, metabolite profile changes in blood, urine and adipose tissue are going to be identified between four points of time during two states: morning and midnight during near physiological GC exposure (sampling 1 and 2), morning and midnight during GC starvation (sampling 3 and 4). Quantitative measurements of all metabolites will be used in the bioinformatic analysis. The bioinformatics strategic consists of a stepwise approach based on random forest analysis. Key features in the analysis include finding candidate markers that are increased during normal GC exposure (sampling 1 and 2), reduced during GC starvation (sampling 3 and 4) and exclusion of factors with high variability within normal subjects. Putative biomarkers will go through two levels of internal cross-validation. The investigators would like that this part of the project is not going to be public. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| mRNA/miRNA profile changes between a state of GC starvation and near physiological GC exposure. | Changes in mRNA/miRNA (Svedberg Unit, S) during 24 hours under two different states of GC exposure. | Using array based transcriptomics (both mRNA & miRNA), mRNA/miRNA profile changes in blood, urine and adipose tissue are going to be identified between four points of time during two states: morning and midnight during near physiological GC exposure (sampling 1 and 2), morning and midnight during GC starvation (sampling 3 and 4). Quantitative measurements of all mRNA/miRNA´s will be used in the bioinformatic analysis. The bioinformatics strategic consists of a stepwise approach based on random forest analysis. Key features in the analysis include finding candidate markers that are increased during normal GC exposure (sampling 1 and 2), reduced during GC starvation (sampling 3 and 4) and exclusion of factors with high variability within normal subjects. Putative biomarkers will go through two levels of internal cross-validation. The investigators would like that this part of the project is not going to be public. |
Countries
Sweden
Outcome results
None listed