Primary Aldosteronism
Conditions
Brief summary
Primary aldosteronism is a prevalent yet underdiagnosed cause of secondary hypertension, contributing to significant cardiovascular morbidity and renal dysfunction. Despite affecting up to 20% of hypertensive patients, PA is frequently missed because it lacks distinctive clinical features and often presents with nonspecific symptoms like resistant hypertension or subtle electrolyte imbalances. The diagnostic pathway involves a stepwise approach: initial screening via the aldosterone-to-renin ratio, confirmatory testing (e.g., saline suppression or captopril challenge), and subtype differentiation using adrenal venous sampling to distinguish unilateral adenoma from bilateral hyperplasia. This complexity, combined with clinician unfamiliarity and variable access to specialized centers, perpetuates underdiagnosis. Early identification and tailored treatment are paramount in improving outcomes for patients with primary aldosteronism. In this study, we will conduct a comprehensive multi-omics analysis on three sample types: 1) blood and urine samples from patients with primary aldosteronism, primary hypertension, and healthy controls; and 2) adrenal tissue samples from patients undergoing adrenalectomy for aldosterone-producing adenomas. We aim to systematically identify differentially expressed biomarkers that could serve as potential early diagnostic markers for primary aldosteronism. The findings may provide new insights into disease pathogenesis and contribute to improving early detection and personalized treatment strategies for this condition.
Interventions
Without intervention
Sponsors
Study design
Eligibility
Inclusion criteria
1. Diagnosed with primary aldosteronism , primary hypertension , or age- and sex-matched healthy controls; 2. Aged 18-80 years with complete medical records; 3. Willing to participate voluntarily and provide informed consent.
Exclusion criteria
1. History of chemotherapy or radiotherapy in the adrenal region ; 2. Positive serological or nucleic acid test results for HIV, hepatitis B, or hepatitis C , or a prior confirmed diagnosis; 3. Individuals with malignancies or autoimmune disorders ; 4. Study withdrawal during the trial period
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Multi-omics data and analysis results | May 2025 to May 2029 | Collect various types of biological samples and utilize advanced proteomics and metabolomics technologies to obtain comprehensive omics data. Based on this, combine machine learning algorithms to deeply mine multi-omics data and clinical information, aiming to screen novel biomarkers for the prediction, classification, and diagnosis of primary aldosteronism, and construct a high-precision prediction model. |
Countries
China