Primary aldosteronism (PA) is a common cause of secondary hypertension, which is characterized by excessive aldosterone production by the adrenal gland. Excessive aldosterone can significantly increase the risk of cardiovascular disease and stroke. Patients with aldosterone-producing adenoma (APA) or unilateral hyperplasia (UAH) can be cured by unilateral adrenalectomy. The adrenal cortex is the outer part of the adrenal gland and is subdivided into three layers- the zona glomerulosa, the zona fasciculata, and the zona reticularis. And the outermost layer is the zona glomerulosa, and it's full of cells that make the hormone aldosterone. Although it has been investigated that the main cause of APA or UAH is the mutations of different calcium ion channels, including KCNJ5, CACNA1D, CLCN2 et al, it is still unknown whether there are any other changes of other proteins in different layers. Therefore, the investigators designed the study to characterize the proteomics profiles of adrenal adenoma/hyperplasia leading to primary aldosterone and identify biomarkers for early identification of PA by using spatial proteomics. The samples from adrenal adenoma or hyperplasia will be collected and analyzed by spatial proteomics in Hangzhou Jingjie Biotechnology Co., Ltd. The differentially expressed proteins in different layers will be screened out between APA and UAH, APA and its adjacent normal tissues, and UAH and its adjacent normal tissues, respectively. And KEGG analysis will be conducted to determine enriched pathway in these differentially expressed protein, respectively.
Study Type
OBSERVATIONAL
Enrollment
30
There is a clear boundary between adrenal adenoma and surrounding normal tissue. There is no clear boundary between adrenal hyperplasia and surrounding normal tissues.
The Third Affiliated Hospital of the Third Military Medical University
Chongqing, China
Screening for the biomarkers.
Histological validation of the CYP11B2 positive area in APA and UAH by immunohistochemical staining (IHC). Some specimens will be characterized more deeply with advanced spatial proteomics technologies to identify the biomarkers.
Time frame: After APA/UAH resection/biopsy, usually within 6 months
Incorporate biomarkers into the accurate and early diagnosis of PA.
Verifying the relationship between biomarkers and clinical presentations, including plasma aldosterone concentrations (PAC), aldosterone to rein ratio (ARR), direct renin concentration (DRC), and serum potassium, etc. Comparing the relationships between biomarkers and risk factors, including osas and family history, etc. Establishing a mathematical model for diagnosing PA through machine learning and studying the pathogenesis of PA through corresponding animal models.
Time frame: 12 months
Identifying the relationship between biomarkers and the prognosis of PA.
The alteration of blood pressure and medication status are investigated through 3 months followed up. Verifying the relationship between the biomarkers and the function of APA and UAH, as well as the prognosis of PA.
Time frame: 12 months
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