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).
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Enrollment
11
Sahlgrenska University Hospital
Gothenburg, Västra Götaland County, Sweden
Protein profile changes between a state of GC starvation and near physiological 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.
Time frame: Changes in proteome (g/dl or umol/l) during 24 hours under two different states of GC exposure.
Metabolite profile changes between a state of GC starvation and near physiological 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.
Time frame: Changes in metabolome (units depending on the kind of metabolome) during 24 hours under two different states of GC exposure.
mRNA/miRNA profile changes between a state of GC starvation and near physiological 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.
Time frame: Changes in mRNA/miRNA (Svedberg Unit, S) during 24 hours under two different states of GC exposure.
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.