How to Explore an Endocrine Cause of Hypertension

Endocrine causes of hypertension: literature review and practical approach

Hypertension (HTN) affects more than 30% of adults worldwide. It is the most frequent modifiable cardiovascular (CV) risk factor, and is responsible for more than 10 million death every year. Among patients with HTN, we usually distinguish secondary HTN, that is HTN due to an identified cause, and primary HTN, in which no underlying cause has been found. It is estimated that secondary hypertension represents between 5 and 15% of hypertensive patients [1]. Therefore, routine screening of patients for secondary HTN would be too costly and is not recommended. In addition to the presence of signs suggesting a specific secondary cause, screening is based on specific criteria. Identifying secondary HTN can be beneficial for patients in certain situations, because it may lead to specific treatments, and allow better control of blood pressure and sometimes even a cure. Besides, it is now known that secondary HTN are more associated with morbidity and mortality than primary HTN. The main causes of secondary HTN are endocrine and renovascular (mainly due to renal arteries abnormalities). The most frequent endocrine cause is primary aldosteronism, which diagnosis can lead to specific therapies. Pheochromocytoma and Cushing syndrome also are important causes, and can have serious complications. Other causes are less frequent and can be suspected on specific situations. In this article, we will describe the endocrine causes of HTN and discuss their treatments.

Pheochromocytoma: a changing perspective and current concepts

This article aims to review current concepts in diagnosing and managing pheochromocytoma and paraganglioma (PPGL). Personalized genetic testing is vital, as 40-60% of tumors are linked to a known mutation. Tumor DNA should be sampled first. Next-generation sequencing is the best and most cost-effective choice and also helps with the expansion of current knowledge. Recent advancements have also led to the increased incorporation of regulatory RNA, metabolome markers, and the NETest in PPGL workup. PPGL presentation is highly volatile and nonspecific due to its multifactorial etiology. Symptoms mainly derive from catecholamine (CMN) excess or mass effect, primarily affecting the cardiovascular system. However, paroxysmal nature, hypertension, and the classic triad are no longer perceived as telltale signs. Identifying high-risk subjects and diagnosing patients at the correct time by using appropriate personalized methods are essential. Free plasma/urine catecholamine metabolites must be first-line examinations using liquid chromatography with tandem mass spectrometry as the gold standard analytical method. Reference intervals should be personalized according to demographics and comorbidity. The same applies to result interpretation. Threefold increase from the upper limit is highly suggestive of PPGL. Computed tomography (CT) is preferred for pheochromocytoma due to better cost-effectiveness and spatial resolution. Unenhanced attenuation of >10HU in non-contrast CT is indicative. The choice of extra-adrenal tumor imaging is based on location. Functional imaging with positron emission tomography/computed tomography and radionuclide administration improves diagnostic accuracy, especially in extra-adrenal/malignant or familial cases. Surgery is the mainstay treatment when feasible. Preoperative α-adrenergic blockade reduces surgical morbidity. Aggressive metastatic PPGL benefits from systemic chemotherapy, while milder cases can be managed with radionuclides. Short-term postoperative follow-up evaluates the adequacy of resection. Long-term follow-up assesses the risk of recurrence or metastasis. Asymptomatic carriers and their families can benefit from surveillance, with intervals depending on the specific gene mutation. Trials primarily focusing on targeted therapy and radionuclides are currently active. A multidisciplinary approach, correct timing, and personalization are key for successful PPGL management.

Diagnosis of covert coarctation of the aorta in adolescents

Objectives

By reviewing the diagnostic process for adolescents with coarctation of the aorta (CoA) in our institution, we analyzed the reasons for delayed diagnosis of CoA. We also proposed a diagnostic protocol to improve the detection rate of CoA.

Methods

In this retrospective study, we included 48 patients aged 12-18 years who were diagnosed with CoA in our hospital from January 2000 to November 2022. Clinical data from involved cases in local hospitals and our institution were collected.

Results

All patients had blood pressure (BP) measurements in upper and lower extremities in our institution. They all had hypertension, 29 (60.4%) of whom had known histories of the same. BP in the upper limbs of 47 (97.9%) patients was ≥20 mmHg higher than that in the lower limbs, and BP in the upper limb of 1 (2.1%) patient was greater than 0 and less than 20 mmHg than that in the lower limb. Echocardiography (ECHO) was performed in all patients, computed tomography (CT) or magnetic resonance imaging (MRI) was performed in 44 patients (91.7%). There were 38 (79.2%) patients who visited local hospitals. Among them, a total of 20 (52.6%) patients had their right upper extremity BP measured, 18 (47.4%) only had their left upper extremity BP measured, and 16 (42.1%) had their lower extremity BP measured. ECHO was performed in 27 (56.2%) patients and CT/MRI was performed in 18 (37.5%) patients. The detection rate for CT/MRI was 100%, and those of ECHO were 72.9% and 18.5% at our institution and a local hospital, respectively. Forty-eight (100%) and 23 (60.5%) patients were detected in our institution and local hospitals (P < 0.0001).

Conclusion

We recommend measuring BP in the bilateral upper extremities. Measurement of BP in the lower extremities is recommended if hypertension is diagnosed. MRI/CT is recommended when BP in the upper extremity is greater than that in the lower extremity.

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.