Urinary free cortisol analyses: Enhancing their clinical performance in Cushing’s syndrome management by means of LC-MS/MS

Posted on April 10, 2026 by MaryO

Highlights

  • An LC-MS/MS method was developed for UFC, cortisone and dexamethasone monitoring.
  • Direct injection was found to be suitable, even in cases of hypocortisolism.
  • Cortisone and cortisol/cortisone ratio complementary role in UFC tests was proved.
  • Dexamethasone monitoring in urine allowed to exclude invalid samples.
  • Population-based LC-MS/MS reference ranges were established.

Abstract

24 h urinary free cortisol (UFC) analysis constitutes one of the three first level recommended tests in Cushing’s syndrome (CS) diagnostic confirmation work up. However, it occasionally leads to inaccurate results due to the use of immunoassays (IAs) or the concomitant administration of exogenous glucocorticoids, among others.
This study aimed to develop a rapid and accurate LC-MS/MS method which may ultimately replace the use of IAs, and also provide relevant clinical information through the simultaneous monitoring of UFC, cortisone, and dexamethasone.
An LC-MS/MS method based on direct injection approach was developed and fully characterized for the quantitation of the target analytes. A population-based reference range was established, and the potential supporting role of cortisone and cortisol/cortisone ratio was comprehensively assessed in patients under CS follow-up or clinical suspicion for hypercortisolism. The presence of dexamethasone was also assessed in order to exclude invalid samples from evaluation.
Significant differences were observed for cortisone and cortisol/cortisone ratio between the control group and patients with hyper−/hypocortisolism, and an ideal level of biochemical agreement was observed with UFC LC-MS/MS values when the combination of both biomarkers was considered. Dexamethasone was detected in up to 7.7% of the studied population.
The herein presented LC-MS/MS approach not only offers the possibility of discontinuing the use of IAs, but also provides additional biomarkers which are significantly relevant in CS management, thus enhancing the overall clinical performance of UFC analyses.

Introduction

Cushing’s syndrome (CS) is characterized by a state of hypercortisolism that can be detected and monitored by means of clinical laboratory tests, such as 24 h urinary freecortisol (UFC). UFC measurement constitutes one of the three first level recommended tests, along with overnight 1 mg dexamethasone suppression and late night salivary cortisol tests [1], [2].
UFC levels are in general highly variable, and at least two 24 h urine collections are necessary for screening/monitoring of CS [1], [2]. In addition to this, 24 h urine samples are often further required due to unexpected or biochemically inconsistent results. This makes the process even more tedious for the patient, and ultimately causes delays in CS diagnosis and management.
Such discordant results may derive from an undeclared use of exogenous glucocorticoids or analytical limitations, among other reasons. The latter occurs especially when UFC analyses are performed by immunoassays (IAs), due to their limited specificity.
Therefore, improvements in UFC tests concerning the analytical methodology, and the inclusion of complementary biomarkers that reinforce their clinical interpretation in the light of unexpected/inconsistent results, appear necessary.
Besides, the simultaneous monitoring of exogenous glucocorticoids in UFC analyses, which is not often considered in clinical practice, should be included.
Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been suggested as the most suitable alternative for UFC quantification [3], [4], [5], [6], [7], since it overcomes IAs analytical limitations. Besides, it also allows for the simultaneous monitoring of different analytes.
In the context of CS management, the simultaneous LC-MS/MS determination of UFC and cortisone, as well as the use of cortisol/cortisone ratio have been previously suggested [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]. With regard to the monitoring of exogenous glucocorticoids, at our center (Hospital Universitario Son Espases, Palma, Spain), it would be of particular importance in the case of dexamethasone. This is because the UFC determination is often followed by an overnight 1 mg dexamethasone suppression test, and its intake may occur by mistake prior or during urine collection.
Despite their advantages, LC-MS/MS methods usually require time-consuming sample preparations, e.g. liquid-liquid extraction (LLE) protocols [20], thus not allowing to completely avoid using IAs in most clinical laboratories. In Spain, to the best of our knowledge, all hospitals in the public healthcare system still use IAs for UFC analysis. Mass spectrometry is only available at tertiary-care centers or academic hospitals, where is still used in combination with IAs to cope with the large volume of samples received on a daily basis. In this case, the use of complementary biomarkers in LC-MS/MS UFC analyses would be of particular interest, as discordant results may occur between methods due to IA analytical limitations.
For all these reasons, in the herein presented study, a novel, rapid and accurate LC-MS/MS method based on direct injection approach for the quantitation of UFC, cortisone, and dexamethasone was developed. Given the lack of standardization in reference ranges, appropriate population-based LC-MS/MS reference values were established.
Most research only focuses on the ability of cortisone and cortisol/cortisone ratio to discriminate ectopic ACTH production from other subtypes of CS [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]. For this reason, this study assessed their suitability as complementary biomarkers, and therefore their ability to reinforce the clinical interpretation of UFC analyses.
To the best of our knowledge, they have not been previously assessed in the context of hypocortisolism. This would be of substantial importance in the follow-up of CS since adrenal insufficiency secondary to adrenalectomy/pituitary surgery or pharmacological treatment (e.g. ketoconazole, metyrapone) may occur. Therefore, such scenario was further considered.

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Gene test for growth hormone deficiency developed

Posted on April 10, 2026 by MaryO

A new test developed by University of Manchester and NHS scientists could revolutionise the way children with growth hormone deficiency are diagnosed.

Children suspected of having GHD – which cause growth to slow down or stop and other serious physical problems—currently require a test involving fasting for up to 12 hours.

The fasting is followed by an intravenous infusion in hospital and up to 10 blood tests over half a day to measure growth hormone production.

Because the current test is unreliable, it often has to be done twice before growth hormone injections can be prescribed.

Now the discovery—which the team think could be available within 2 to 5 years -could reduce the process to a single blood test, freeing up valuable time and space for the NHS.

Dr. Adam Stevens from The University of Manchester and Dr. Philip Murray from Manchester University NHS Foundation Trust, were part of the team whose results are published in JCI Insight today.

Dr. Stevens said: “We think this is an important development in the way doctors will be able to diagnose growth hormone deficiency – a condition which causes distress to many thousands of children in the UK

“This sort of diagnostic would not be available even a few years ago but thanks to the enormous computing power we have, and advances in genetics, it is now possible for this aspect of care to be made so much easier for patients – and the NHS.

“These volume of data involved is so huge and complicated that traditional data-processing application software is inadequate to deal with it.”

Comparing data from 72 patients with GHD and 26 healthy children, they used high powered computers to examine 30,000 genes—the full gene expression- of each child.

A sophisticated mathematical technique called Random Forest Analysis analysed around three million separate data points to compare different gene patterns between the children with and without GHD.

The research identified 347 genes which when analysed with the computer algorithm can determine whether a child has GHD or not and thus whether they will benefit from treatment.

Growth hormone deficiency (GHD) occurs when the pituitary gland—which is size of a pea- fails to produce enough growth hormone. It more commonly affects children than adults.

Many teenagers with GHD have poor bone strength, fatigue and lack stamina as well as depression, lack of concentration, poor memory and anxiety problems.

GHD occurs in roughly 1 in 5,000 people. Since the mid-1980s, synthetic growth hormones have been successfully used to treat children—and adults—with the deficiency.

Dr. Murray added: “This study provides strong proof of concept, but before it is in a position to be adopted by the NHS, we must carry out a further validation exercise which will involve comparing our new diagnostic with the existing test.

“Once we have crossed that hurdle, we hope to be in a position for this to be adopted within 2 to 5 years – and that can’t come soon enough for these children.”

Child Growth Foundation manager Jenny Child’s daughter has Growth Hormone Deficiency.

She said: Growth Hormone Deficiency isn’t just about growth, as lack of growth hormone impacts the child in many ways, such as lack of strength and they can find it difficult to keep up physically with their peers. It impacts the child’s self-esteem as they are often treated as being much younger, because of their size. Growth hormone treatment allows the child to grow to their genetic potential.

“A growth hormone stimulation test can be very daunting for both child and parents. The test can make the child feel quite unwell and they can experience headaches, nausea and unconsciousness through hypoglycaemia.”

 Explore further: Northern climes make a difference with growth hormone treatment

More information: Philip G. Murray et al. Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency, JCI Insight (2018). DOI: 10.1172/jci.insight.93247

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