Identification of glucocorticoid-related molecular signature by whole blood methylome analysis

Development of double-layer poly (amino acid) modified electrochemical sensor for sensitive and direct detection of betamethasone in cosmetics

Screening for illegal use of glucocorticoids (GCs) in cosmetics by electrochemical methods is extremely challenging due to the poor electrochemical activity of GCs. In this study, poly-L-Serine/poly-Taurine modified electrode (P(Tau)/P(L-Ser)/GCE) was prepared for sensitive and direct determination of betamethasone in cosmetics by a simple two-step in situ electropolymerization reaction. The relevant parameters of preparation and electroanalytical conditions were respectively studied, including the concentration of polymerization solution, the number of scanning circles and the scanning rate. The SEM and EDS mapping demonstrated successful preparation of P(Tau)/P(L-Ser)/GCE. The electro-catalytic properties of the obtained electrodes were investigated using cyclic voltammetry and differential pulse voltammetry methods, showing a remarkable improvement of sensitivity for the detection of betamethasone due to the synergic effect of both P(L-Ser) and P(Tau). In addition, we investigated the electrochemical reduction of betamethasone on the surface of modified electrode. It was found that the process was controlled by diffusion effect and involved the transfer of two electrons and two protons. Then the electrochemical sensor method based on P(Tau)/P(L-Ser)/GCE was established and delivered a linear response to betamethasone concentration from 0.5 to 20 μg mL-1 with a limit of detection of 32.2 ng mL-1, with excellent recoveries (98.1%-106.8%) and relative standard deviations (＜4.8%). Furthermore, the established electrochemical sensor method was compared with conventional HPLC method. The results showed that both of them were comparable. Moreover, the established electrochemical sensor method was with the merits of short analysis time, environmentally friendly, low cost and easy to achieve in-site detection.

Epigenetic Mechanisms Modulated by Glucocorticoids With a Focus on Cushing Syndrome

In Cushing syndrome (CS), prolonged exposure to high cortisol levels results in a wide range of devastating effects causing multisystem morbidity. Despite the efficacy of treatment leading to disease remission and clinical improvement, hypercortisolism-induced complications may persist. Since glucocorticoids use the epigenetic machinery as a mechanism of action to modulate gene expression, the persistence of some comorbidities may be mediated by hypercortisolism-induced long-lasting epigenetic changes. Additionally, glucocorticoids influence microRNA expression, which is an important epigenetic regulator as it modulates gene expression without changing the DNA sequence. Evidence suggests that chronically elevated glucocorticoid levels may induce aberrant microRNA expression which may impact several cellular processes resulting in cardiometabolic disorders. The present article reviews the evidence on epigenetic changes induced by (long-term) glucocorticoid exposure. Key aspects of some glucocorticoid-target genes and their implications in the context of CS are described. Lastly, the effects of epigenetic drugs influencing glucocorticoid effects are discussed for their ability to be potentially used as adjunctive therapy in CS.

Biomarkers of aging through the life course: A Recent Literature Update

Purpose of review

The development of biomarkers of aging has greatly advanced epidemiological studies of aging processes. However, much debate remains on the timing of aging onset and the causal relevance of these biomarkers. In this review, we discuss the most recent biomarkers of aging that have been applied across the life course.

Recent findings

The most recently developed aging biomarkers that have been applied across the life course can be designated into three categories: epigenetic clocks, epigenetic markers of chronic inflammation, and mitochondrial DNA copy number. While these have been applied at different life stages, the development, validation, and application of these markers has been largely centered on populations of older adults. Few studies have examined trajectories of aging biomarkers across the life course. As the wealth of molecular and biochemical data increases, emerging biomarkers may be able to capture complex and system-specific aging processes. Recently developed biomarkers include novel epigenetic clocks; clocks based on ribosomal DNA, transcriptomic profiles, proteomics, metabolomics, and inflammatory markers; clonal hematopoiesis of indeterminate potential gene mutations; and multi-omics approaches.

Summary

Attention should be placed on aging at early and middle life stages to better understand trajectories of aging biomarkers across the life course. Additionally, novel biomarkers will provide greater insight into aging processes. The specific mechanisms of aging reflected by these biomarkers should be considered when interpreting results.

Pitfalls in the Diagnosis and Management of Hypercortisolism (Cushing Syndrome) in Humans; A Review of the Laboratory Medicine Perspective

Biochemical confirmation of a diagnosis of hypercortisolism (Cushing syndrome) is vital to direct further investigations, especially given the overlap with non-autonomous conditions, such as pseudo-Cushing, and the morbidity associated with missed diagnoses. A limited narrative review was performed focusing on the laboratory perspective of the pitfalls of making a biochemical diagnosis of hypercortisolism in those presenting with presumed Cushing syndrome. Although analytically less specific, immunoassays remain cheap, quick, and reliable in most situations. Understanding cortisol metabolism can help with patient preparation, specimen selection (e.g., consideration of urine or saliva for those with possible elevations of cortisol binding globulin concentration), and method selection (e.g., mass spectrometry if there is a high risk of abnormal metabolites). Although more specific methods may be less sensitive, this can be managed. The reduction in cost and increasing ease of use makes techniques such as urine steroid profiles and salivary cortisone of interest in future pathway development. In conclusion, the limitations of current assays, particularly if well understood, do not impede diagnosis in most cases. However, in complex or borderline cases, there are other techniques to consider to aid in the confirmation of hypercortisolism.

New advances in endocrine hypertension: from genes to biomarkers

Hypertension (HT) is a major cardiovascular risk factor that affects 10% to 40% of the general population in an age-dependent manner. Detection of secondary forms of HT is particularly important because it allows the targeted management of the underlying disease. Among hypertensive patients, the prevalence of endocrine HT reaches up to 10%. Adrenal diseases are the most frequent cause of endocrine HT and are associated with excess production of mineralocorticoids (mainly primary aldosteronism), glucocorticoids (Cushing syndrome), and catecholamines (pheochromocytoma). In addition, a few rare diseases directly affecting the action of mineralocorticoids and glucocorticoids in the kidney also lead to endocrine HT. Over the past years, genomic and genetic studies have allowed improving our knowledge on the molecular mechanisms of endocrine HT. Those discoveries have opened new opportunities to transfer knowledge to clinical practice for better diagnosis and specific treatment of affected subjects. In this review, we describe the physiology of adrenal hormone biosynthesis and action, the clinical and biochemical characteristics of different forms of endocrine HT, and their underlying genetic defects. We discuss the impact of these discoveries on diagnosis and management of patients, as well as new perspectives related to the use of new biomarkers for improved patient care.

In Situ Metabolomics of Cortisol-Producing Adenomas

BACKGROUND

Recent advances in omics techniques have allowed detailed genetic characterization of cortisol-producing adrenal adenoma (CPA). In contrast, the pathophysiology of CPAs has not been elucidated in detail on the level of tumor metabolic alterations.

METHODS

The current study conducted a comprehensive mass spectrometry imaging (MSI) map of CPAs in relation to clinical phenotypes and immunohistochemical profiles of steroidogenic enzymes. The study cohort comprised 46 patients with adrenal tumors including CPAs (n 35) and nonfunctional adenomas (n 11).

RESULTS

Severity of cortisol hypersecretion was significantly correlated with 29 metabolites (adjusted P 0.05). Adrenal androgens derived from the classic androgen pathway were inversely correlated with both cortisol secretion (rs 0.41, adjusted P 0.035) and CYP11B1 expression (rs 0.77, adjusted P 2.00E-08). The extent of cortisol excess and tumor CYP11B1 expression further correlated with serotonin (rs 0.48 and 0.62, adjusted P 0.008 and 2.41E-05). Tumor size was found to be correlated with abundance of 13 fatty acids (adjusted P 0.05) and negatively associated with 9 polyunsaturated fatty acids including phosphatidic acid 38:8 (rs 0.56, adjusted P 0.009).

CONCLUSIONS

MSI reveals novel metabolic links between endocrine function and tumorigenesis, which will further support the understanding of CPA pathophysiology.

Evaluation of cross-platform compatibility of a DNA methylation-based glucocorticoid response biomarker

Background

Identifying blood-based DNA methylation patterns is a minimally invasive way to detect biomarkers in predicting age, characteristics of certain diseases and conditions, as well as responses to immunotherapies. As microarray platforms continue to evolve and increase the scope of CpGs measured, new discoveries based on the most recent platform version and how they compare to available data from the previous versions of the platform are unknown. The neutrophil dexamethasone methylation index (NDMI 850) is a blood-based DNA methylation biomarker built on the Illumina MethylationEPIC (850K) array that measures epigenetic responses to dexamethasone (DEX), a synthetic glucocorticoid often administered for inflammation. Here, we compare the NDMI 850 to one we built using data from the Illumina Methylation 450K (NDMI 450).

Results

The NDMI 450 consisted of 22 loci, 15 of which were present on the NDMI 850. In adult whole blood samples, the linear composite scores from NDMI 450 and NDMI 850 were highly correlated and had equivalent predictive accuracy for detecting DEX exposure among adult glioma patients and non-glioma adult controls. However, the NDMI 450 scores of newborn cord blood were significantly lower than NDMI 850 in samples measured with both assays.

Conclusions

We developed an algorithm that reproduces the DNA methylation glucocorticoid response score using 450K data, increasing the accessibility for researchers to assess this biomarker in archived or publicly available datasets that use the 450K version of the Illumina BeadChip array. However, the NDMI850 and NDMI450 do not give similar results in cord blood, and due to data availability limitations, results from sample types of newborn cord blood should be interpreted with care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01352-1.

Whole blood methylome-derived features to discriminate endocrine hypertension

Background

Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches.

Results

Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods—Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine—predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL.

Conclusions

The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01347-y.