Abstract
Aims: The present study aims to provide a comprehensive analytical and biological validation of an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for analysis of salivary cortisol and its inactive metabolite cortisone. Variation in cortisol awakening response (CAR) over one week were investigated.
Methods: Saliva samples were collected from 19 healthy volunteers. To determine CAR, participants collected saliva samples at three time points: immediately after awakening, 15 and 30 minutes thereafter. The same procedure was repeated each morning over one week period. In addition, all participants filled in diaries containing information about duration of sleep, time of awakening, smoking, and coffee and alcohol intake. Upon collection, the saliva samples were stored at -20°C until analysis. Prior to analysis, the saliva samples were thawed and spiked with internal standard and extracted using solid phase extraction columns (Oasis Prime-HLB). The identification and quantification of cortisol and cortisone were performed using the developed UPLC-MS/MS method, on a Waters Aquity TQ-XS system.
Results: The obtained limits of quantification (LoQ) were 1ng/ml for cortisol and 500pg/ml for cortisone. Intra-assay accuracy values of calibration points were between 83-111%. The mean levels of cortisol and cortisone in the total sample were 3.55 ± 1.99 ng/ml and 10.51 ± 3.46 ng/ml, respectively. In the first 30 minutes after awakening, there was a 70% increase in the average cortisol levels (CAR) and a 49% increase in the levels of cortisone. A high intra-individual variability of CAR was observed over the week (CV ranged between 17.9-68.9%), whereas the inter-individual variability of the average CAR equaled 28.2%. Furthermore, the changes in CAR were related to variables from participants’ diaries.
Conclusion: The UPLC-MS/MS method has shown to be a sensitive and specific technique for determination of salivary cortisol and cortisone. However, in the clinical context, CAR data should be interpreted with precaution due to high inter- and intra-individual variability.
Methods: Saliva samples were collected from 19 healthy volunteers. To determine CAR, participants collected saliva samples at three time points: immediately after awakening, 15 and 30 minutes thereafter. The same procedure was repeated each morning over one week period. In addition, all participants filled in diaries containing information about duration of sleep, time of awakening, smoking, and coffee and alcohol intake. Upon collection, the saliva samples were stored at -20°C until analysis. Prior to analysis, the saliva samples were thawed and spiked with internal standard and extracted using solid phase extraction columns (Oasis Prime-HLB). The identification and quantification of cortisol and cortisone were performed using the developed UPLC-MS/MS method, on a Waters Aquity TQ-XS system.
Results: The obtained limits of quantification (LoQ) were 1ng/ml for cortisol and 500pg/ml for cortisone. Intra-assay accuracy values of calibration points were between 83-111%. The mean levels of cortisol and cortisone in the total sample were 3.55 ± 1.99 ng/ml and 10.51 ± 3.46 ng/ml, respectively. In the first 30 minutes after awakening, there was a 70% increase in the average cortisol levels (CAR) and a 49% increase in the levels of cortisone. A high intra-individual variability of CAR was observed over the week (CV ranged between 17.9-68.9%), whereas the inter-individual variability of the average CAR equaled 28.2%. Furthermore, the changes in CAR were related to variables from participants’ diaries.
Conclusion: The UPLC-MS/MS method has shown to be a sensitive and specific technique for determination of salivary cortisol and cortisone. However, in the clinical context, CAR data should be interpreted with precaution due to high inter- and intra-individual variability.
| Original language | English |
|---|---|
| Pages (from-to) | 88-88 |
| Journal | Journal of Psychosomatic Research |
| Volume | 109 |
| DOIs | |
| Publication status | Published - Jun 2018 |