Whole blood transcriptomic signature of Cushing's syndrome.

OBJECTIVE: Cushing's syndrome is characterized by high morbidity and mortality with high interindividual variability. Easily measurable biomarkers, in addition to the hormone assays currently used for diagnosis, could reflect the individual biological impact of glucocorticoids. The aim of this study is to identify such biomarkers through the analysis of whole blood transcriptome. DESIGN: Whole blood transcriptome was evaluated in 57 samples from patients with overt Cushing's syndrome, mild Cushing's syndrome, eucortisolism, and adrenal insufficiency. Samples were randomly split into a training cohort to set up a Cushing's transcriptomic signature and a validation cohort to assess this signature. METHODS: Total RNA was obtained from whole blood samples and sequenced on a NovaSeq 6000 System (Illumina). Both unsupervised (principal component analysis) and supervised (Limma) methods were used to explore the transcriptome profile. Ridge regression was used to build a Cushing's transcriptome predictor. RESULTS: The transcriptomic profile discriminated samples with overt Cushing's syndrome. Genes mostly associated with overt Cushing's syndrome were enriched in pathways related to immunity, particularly neutrophil activation. A prediction model of 1500 genes built on the training cohort demonstrated its discriminating value in the validation cohort (accuracy .82) and remained significant in a multivariate model including the neutrophil proportion (P = .002). Expression of FKBP5, a single gene both overexpressed in Cushing's syndrome and implied in the glucocorticoid receptor signaling, could also predict Cushing's syndrome (accuracy .76). CONCLUSIONS: Whole blood transcriptome reflects the circulating levels of glucocorticoids. FKBP5 expression could be a nonhormonal marker of Cushing's syndrome.

PIT-EASY survey: validation of the European Pituitary Pathology Group proposal for reporting pituitary neuroendocrine tumors.

The aim of this multicenter prospective survey called PIT-EASY was to assess the relevance of the European Pituitary Pathology Group (EPPG) diagnostic tools for pituitary neuroendocrine tumors (PitNETs) to improve the quality of their histological diagnosis. Each center performed at least 30 histological cases of PitNETs using the EPPG tools and assessed their value using a scorecard with 10 questions. For each center, the histological cases were carried out by pathologists with varying levels of expertise in pituitary pathology defined as junior, intermediate, and expert. Two hundred and ninety histological cases were collected from six French and Italian centers. The three EPPG tools were validated and regarded as helpful for a more accurate and time-efficient diagnosis. The usefulness of level 2 and level 3 of the "EPPG's multi-step approach for immunohistochemistry" including pituitary transcription factors (PIT1, TPIT, and SF1) and chromogranin, SSTRs, and P53 respectively was higher in "other non-functioning" (silent plurihormonal PIT1, silent corticotroph, and null cell): 88% vs 32%, p < 10-6 and 42% vs 14%, p = 0.002, respectively. The diagnostic algorithm proved more useful for junior pathologists (p = 0.0001) and those with intermediate experience. PIT-EASY survey confirmed the importance of a standardized approach to PitNETs for an accurate and reproducible diagnosis and served as validation of the EPPG proposal. The tool appeared to be of practical value to junior participants and staff with intermediate experience for safe routine diagnostic reporting.

DXA-derived lumbar bone strain index corrected for kyphosis is associated with vertebral fractures and trabecular bone score in acromegaly.

PURPOSE: The bone strain index (BSI) is a marker of bone deformation based on a finite element analysis inferred from dual X-ray absorptiometry (DXA) scans, that has been proposed as a predictor of fractures in osteoporosis (i.e., higher BSI indicates a lower bone's resistance to loads with consequent higher risk of fractures). We aimed to investigate the association between lumbar BSI and vertebral fractures (VFs) in acromegaly. METHODS: Twenty-three patients with acromegaly (13 males, mean age 58 years; three with active disease) were evaluated for morphometric VFs, trabecular bone score (TBS), bone mineral density (BMD) and BSI at lumbar spine, the latter being corrected for the kyphosis as measured by low-dose X-ray imaging system (EOS®-2D/3D). RESULTS: Lumbar BSI was significantly higher in patients with VFs as compared to those without fractures (2.90 ± 1.46 vs. 1.78 ± 0.33, p = 0.041). BSI was inversely associated with TBS (rho -0.44; p = 0.034), without significant associations with BMD (p = 0.151), age (p = 0.500), BMI (p = 0.957), serum IGF-I (p = 0.889), duration of active disease (p = 0.434) and sex (p = 0.563). CONCLUSIONS: Lumbar BSI corrected for kyphosis could be proposed as integrated parameter of spine arthropathy and osteopathy in acromegaly helping the clinicians in identifying patients with skeletal fragility possibly predisposed to VFs.

Whole blood transcriptome signature predicts severe forms of COVID-19: Results from the COVIDeF cohort study.

COVID-19 is associated with heterogeneous outcome. Early identification of a severe progression of the disease is essential to properly manage the patients and improve their outcome. Biomarkers reflecting an increased inflammatory response, as well as individual features including advanced age, male gender, and pre-existing comorbidities, are risk factors of severe COVID-19. Yet, these features show limited accuracy for outcome prediction. The aim was to evaluate the prognostic value of whole blood transcriptome at an early stage of the disease. Blood transcriptome of patients with mild pneumonia was profiled. Patients with subsequent severe COVID-19 were compared to those with favourable outcome, and a molecular predictor based on gene expression was built. Unsupervised classification discriminated patients who would later develop a COVID-19-related severe pneumonia. The corresponding gene expression signature reflected the immune response to the viral infection dominated by a prominent type I interferon, with IFI27 among the most over-expressed genes. A 48-genes transcriptome signature predicting the risk of severe COVID-19 was built on a training cohort, then validated on an external independent cohort, showing an accuracy of 81% for predicting severe outcome. These results identify an early transcriptome signature of severe COVID-19 pneumonia, with a possible relevance to improve COVID-19 patient management.

Prediction of adrenal insufficiency after pituitary surgery: a retrospective study using beckman access cortisol assay.

PURPOSE: Identifying patients requiring glucocorticoid replacement therapy after pituitary surgery is challenging as the tests commonly used for the diagnosis of secondary adrenal insufficiency (SAI) are not recommended in the immediate postoperative period. There are controversial data on the role of postoperative days' morning cortisol, with no specific data for each cortisol assay. The aim of this study is to investigate the reliability of 8.00 a.m. cortisol of the first and second postoperative days in predicting SAI. METHODS: Data of patients underwent pituitary surgery in Humanitas Research Hospital in Italy, from March 2017 to August 2022, were retrospectively analyzed. Definitive diagnosis of SAI was made through ACTH test 1 µg six weeks after surgery. Cortisol was measured through Beckman Access Cortisol and the diagnosis of SAI was made if cortisol peak was below 14.8 µg/dL (408 nmol/L) at 30 or 60 min after stimulus. RESULTS: Of the sixty-four patients enrolled, seven developed SAI. The ROC curves demonstrated that both first- and second-day postoperative 8.00 a.m. cortisol predict SAI (AUC 0.94 and 0.95, respectively). The optimal thresholds were 15.6 µg/dL (430.3 nmol/L; accuracy 89%) for the first day and 11.5 µg/dL (317.2 nmol/L, accuracy 81%) for the second day. Patients who developed SAI had larger tumors (p = 0.004) and lower fT4 (p = 0.038) before surgery. CONCLUSIONS: Clinicians might rely on the first- and second- postoperative days 8.00 a.m. cortisol to identify patients to discharge with glucocorticoid replacement therapy waiting for the confirmation of SAI through the ACTH test.

ACTH Stimulation Test for the Diagnosis of Secondary Adrenal Insufficiency: Light and Shadow.

Secondary Adrenal Insufficiency (SAI) is a condition characterized by inappropriately low ACTH secretion due to a disease or injury to the hypothalamus or the pituitary. The evaluation when suspected is often challenging for the non-specific symptoms, the rarity of the disease, and the pitfalls associated with laboratory tests. A prompt and correct diagnosis of SAI is essential because although an adequate hormonal replacement therapy could be lifesaving, inappropriate life-long therapy with steroids can be harmful. The gold standard test for assessing the hypothalamus-pituitary-adrenal axis (HPA) is the insulin tolerance test (ITT), but due to safety issues is not widely used. Conversely, the ACTH stimulation test is a safer and well-tolerated tool for SAI diagnosis. However, data about its diagnostic accuracy show great variability due to both technical and interpretative aspects, such as dose, route of administration, the timing of the test, and assay used for cortisol measurements. Consequently, the clinical background of the patient and the pretest probability of HPA axis impairment become of paramount importance. We aimed to summarize the recent literature evidence in the conduction and interpretation of the ACTH stimulation test for the diagnosis of SAI to provide updated insights on its correct use in clinical practice.

Looking at the spine in controlled Acromegaly.

Skeletal fragility with high risk of vertebral fractures (VFs) is an emerging complication of growth hormone (GH) hypersecretion. VFs often coexist with spine arthropathy and both clinical conditions negatively impact on quality of life of acromegalic subjects. Management of spine osteopathy and arthropathy in acromegaly could be challenging since both complications can persist or even progress after biochemical control of disease. This article analyzes the latest evidence about possible pathophysiological links between VFs and spine arthropathy in active and controlled acromegaly, as well as the diagnostic and therapeutic aspects concerning the holistic management of acromegalic osteo-arthropathy.