Taylor NF’s research while affiliated with King's College London and other places

Objective: To assess if 24h urinary cortisol metabolite (UCM) profiles are related to structural cardiac, and arterial, parameters in those with or at risk of Type 2 diabetes mellitus (T2DM). Design and method: 32 participants, 25-77 years, eGFR> 45 mL/min and no serious illness. Urine was collected over 24h. 2D echocardiography and arterial stiffness measures [aortic pulse wave velocity (aPWV) by Arteriograph and cardio-ankle vascular index (CAVI) by VaSera] were performed on the collection day. Steroids were extracted from urine and hydrolysed; derivatives were analysed by GC-MS. Results: Seven UCMs were quantified [tetrahydrocortisol (THF), allo-tetrahydrocortisol (a-THF), tetrahydrocortisone (THE), α-cortol (α-col), β-cortol (β-col), α-cortolone (α-cone), β-cortolone (β-cone)]. Left ventricular mass index (LVMI) correlated positively with 24h cortisol:cortisone metabolites (THF+aTHF+αcol+βcol/THE+αcortolone+βcortolone) and negatively with α:β metabolites (αcol+αcortol/βcol+βcortol), when indexed for body surface area (BSA) and height (r=0.37, 0.48 and r=-0.34,-0.49 respectively). Further, there was a positive relationship between LVMI BSA and THF:THE (r=0.35). aPWV but not CAVI was also related to 24h cortisol:cortisone metabolites (r=0.45). All p<0.05. Regression analysis including age, gender, systolic blood pressure (SBP), arterial stiffness (aPWV or CAVI) and body mass index (BMI; only for RWT), showed an independent association between THF:THE and LVMI BSA and LVMI height and cortisol:cortisone metabolites with LVMI height , p<0.02. SBP, but not arterial stiffness, was also independently related to LVMI BSA and LVMI height in all models. Conclusion: Specific 24h UCMs and UCM ratios (from glucocorticoid/mineralocorticoid, 11βHSD and 20αHSD/20βHSD actions) may be structural cardiac biomarkers in those with or at risk of T2DM.

Objective: To assess if 24 h urinary steroid metabolite profiles are related to vascular parameters such as arterial stiffness and blood pressure (BP) Design and method: 43 eligible participants, 25-81 years, with eGFR > 45 mL/min and no serious illness. Urine was collected over 24 h (12 h day and night samples). Peripheral BP, central pulse wave velocity (aPWV) (by Arteriograph) and cardio ankle vascular index (CAVI) (by VaSera) measures were performed on the collection day. Steroids were extracted from urine aliquots and conjugates hydrolysed by Helix pomatia digestive juice. Free steroids were re-extracted and methyl oxime-trimethylsilyl ether derivatives prepared for GC-MS analysis. Pearson correlation and multiple regression analysis were performed. Results: The urinary steroid metabolites detailed in the figure (figure on the following page) were quantified. Systolic BP and aPWV correlated positively with the ratio of cortisol to cortisone metabolites [aTHF, THF, [alpha]col and [beta]col: THE, [alpha]cone and [beta]cone, (colmets: conemets)]; r = 0.32, 0.37 respectively, p < 0.05 for day samples and r = 0.33, 0.34 respectively, p < 0.05 for night samples. Both BP and aPWV also correlated negatively in the day samples with the ratio [alpha]col, [beta]col, [alpha]cone and [beta]cone: aTHF, THF and THE (20OH: 20oxo); r = -0.33, -0.32 respectively, p < 0.05. Night samples only showed this correlation with diastolic BP r = 0.31, p < 0.05. No correlations were seen with CAVI. Regression analysis with these metabolite ratios (including age and body mass index) did not show they were associated with BP or CAVI (including BP). While aPWV was borderline associated with colmets: conemets, p = 0.077, 20OH: 20oxo was significantly associated (p = 0.026). BP and BMI remained independent predictors. Conclusions: 24 h urinary 20OH:20oxo ratio was independently related to aPWV in those with or at risk of T2D and colmets:conemets had borderline associations with aPWV. There were no associations with the urinary steroids and BP. Copyright

Mitotane (o,p'-DDD), an oral adrenolytic agent for treatment of advanced adrenocortical carcinoma (ACC), is reported to inhibit cortisol biosynthesis in vitro and enhance production from exogenous cortisol of urinary 6β-hydroxycortisol and unidentified polar unconjugated metabolites. We examined urinary steroid profiles by gas chromatography-mass spectrometry of patients with histologically confirmed ACC following surgery, receiving a) hydrocortisone alone (three males and three females) and b) mitotane and hydrocortisone (six males and 11 females). Samples were collected after plasma mitotane had reached the therapeutic range of 14-20 mg/l. Increased excretion of polar unconjugated steroids during mitotane treatment was confirmed, with 6β-hydroxycortisol and 6β-hydroxy-20-dihydrocortisols predominating. The proportion of additionally hydroxylated metabolites was <2% in untreated controls and 52, 35-52% (mean, range) in the mitotane plus hydrocortisone group. Ratios of 5α-/5β- and 20β-/20α-metabolites of administered cortisol were decreased 50-, 15-fold, and 14-, 8-fold respectively (males, females - mean values) but with no change in metabolite ratios that reflect oxidoreduction at C11 or C20. Patterns of decrease in 5α- relative to 5β-reduced metabolites were similar to those of patients with 5α-reductase 2 deficiency or on treatment with the 5α-reductase 2 inhibitor finasteride but different from those of patients on dutasteride, indicating specific inhibition of 5α-reductase 2. We conclude that mitotane causes consistent changes in cortisol catabolism, most of which have not been previously recognised. These need not interfere with early detection of ACC recurrence. Induction of 6β-hydroxylation offers an explanation for a reported decrease in cortisol bioavailability. Mitotane also has potential as a unique steroid metabolic probe for 20β-reduction.

The paper by Arlt et al. (1) on detecting malignancy in adrenocortical tumors illustrates well the benefits of cooperation between centers and of a systematic approach to classifying data, in this case on urinary steroid profiles. We have long used urine steroid profiling as a means of detecting steroid secretion by adrenocortical tumors (2), but definitive guidance on its accuracy in differentiating malignancy has previously been limited to small patient numbers or a limited set of steroid markers. Histological classification systems have already served this field well. They continue to evolve (3) and are undoubtedly the best indicator currently available of malignant potential, but there is room to improve differentiation of adrenocortical adenoma from nodular hyperplasia (4). We wish to offer some pointers on how these approaches could develop further. First, it is important to apply very clear criteria for identifying adrenal neoplasms: Arlt et al. describe their classification as being based on histology and presence of metastases, but only 36/147 cases were given a Weiss score, so it was not possible to judge the performance of their steroid profile findings against this gold standard. In the absence of histology, there are two potential confusing elements: (a) some adrenocortical adenomas might represent dominant nodules in nodular hyperplasia that can remain undetected because of the limited resolution of imaging for sub-centimeter lesions; and (b) not all non-metastatic lesions are necessarily benign, but they could not be diagnosed unless they were evaluated histologically. It would be useful to see the outcome of steroid metabolomic analysis by Arlt et al. applied only to those defined histologically. Second, the greatest need lies in determining the prognosis of those with adrenocortical carcinomas (ACC) on histology that do not have secondaries at presentation. Arlt et al. report no difference of steroid metabolome between those with and without secondaries. Continuing surveillance of ACC patients initially without secondaries may enable histological and steroid pointers to become recognized. Third, although a large set (32) of steroid metabolites was considered, some reported markers of ACC (e.g., Pregnene-3α,16α,20α-triol, ref. 5) were not included. It has been our experience that close examination of profiles obtained unselectively by full scan gas chromatography-mass spectrometry (GC-MS) often reveals new and unexpected markers of ACC and these can prove crucial for detection of relapse. A system akin to the Weiss system of histological scoring, based on number of steroid markers abnormally increased, may also prove to be more accurate and easier for referral laboratories to apply. What is already clear is that if surgical removal of a mass in the adrenal cortex is contemplated, determining presence or absence of markers in a urine steroid profile should be part of the work up. References 1. Arlt W, Biehl M, Taylor AE, Hahner S, Libe R, Hughes BA, Schneider P, Smith DJ, Stiekema H, Krone N, Porfiri E, Opocher G, Bertherat J, Mantero F, Allolio B, Terzolo M, Nightingale P, Shackleton CHL, Bertagna X, Fassnacht M, Stewart PM. 2011. Urine steroid metabolomics as a biomarker tool for detecting malignancy in adrenal tumors. J Clin Endocrinol Metab 96:3775-3784 2. Shackleton CHL, Taylor NF, Honour JW. 1980. An atlas of gas chromatographic profiles of urinary steroids in health and disease Monograph, Packard Becker Ltd. 3. Lau SK, Weiss LM. 2009, The Weiss system for evaluating adrenocortical neoplasms: 25 years later. Hum Pathol 40:757-768 4. Blanes A, Diaz-Cano SJ. 2007. Histologic criteria for adrenocortical proliferative lesions. Anatomic Pathol 127:398-408 5. Tiu SC, Chan AOK, Taylor NF, Leung PY, Choi CH, Shek CC. 2009. Use of urinary steroid profiling for diagnosing and monitoring adrenocortical tumours. Hong Kong Med J 15:463-470