Aldosterone-producing Adenoma, Essential Hypertension, Idiopathic Aldosteronism, Primary Aldosteronism
Conditions
Brief summary
Primary aldosteronism (PA), characterized by overt renin-independent aldosterone production, is the most common form endocrine hypertension. Compared with blood pressure-matched cases of essential hypertension (EH), PA is associated with a higher risk of cardiovascular morbidity and mortality. It is estimated that PA affects at least 10% of hypertensive patients and up to 25% of treatment-resistant hypertension. The major subtypes of PA are comprised of bilateral idiopathic hyperaldosteronism (IHA) and unilateral aldosterone-producing adenoma (APA). The screening, confirmatory testing, and subtype differentiation of PA for therapeutic management is a multi-step and complex process, resulting in low screening rates and poor clinical recognition. PA is an independent risk factor for metabolic morbidity. Metabolomic profiling is a relatively new strategy for the diagnosis and prognosis of disease through identification and quantification of various metabolites. In the current study, we aimed to investigate the potential biomakers for discriminating PA from EH, as well as subtype classification for PA, by untargeted metabolomics.
Interventions
DIAGNOSTIC_TESTliquid chromatography-mass spectrometry (LC/MS)
Metabolomics is a rapidly evolving high-throughput technology that allows the measurement of the entire complement of metabolites generated by biochemical reactions under certain conditions in biological fluids or tissues. This technology has been used extensively to identify biomarkers in various cancers, nervous system diseases, cardiovascular diseases, pituitary diseases, and other diseases. The identification of biomarkers can be clinically useful for a more accurate diagnosis, prognosis, and treatment choice as well as disease monitoring. Among mass spectrometry (MS) methods, liquid chromatography- mass spectrometry (LC-MS) has been recognized as a robust metabolomics tool and has been widely applied in metabolite identification and quantification due to its high sensitivity, peak resolution, and reproducibility.
Sponsors
Third Military Medical University
Study design
Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No
Inclusion criteria
* According to 2010 Chinese guidelines for the management of Essential hypertension (EH), EH was defined as systolic blood pressure (SBP) ≥140 mm Hg, diastolic blood pressure (DBP) ≥90 mm Hg, and use of antihypertensive medicine within 2 weeks and excluded from PA through ARR or confirmatory testing. * Patients were confirmed to be diagnosed with Primary aldosteronism (PA) in accordance with the Endocrine Society Clinical Practice Guideline criteria. Patients with an aldosterone-to-renin ratio (ARR) \> 3.7 (ng/dL) further conformed with one of the following confirmatory tests: saline infusion test or captopril-inhibition test. Adrenal CT scans and Adrenal venous sampling (AVS) were performed for PA subtype classification. * Patients with idiopathic hyperaldosteronism (IHA) were determined based on the absence of obvious adenoma on adrenal CT and bilateral aldosterone overproduction. * Patients with aldosterone-producing adenoma (APA) were identified based on macroadenoma \>1 cm on adrenal CT, unilateral hypersecretion of aldosterone, and pathological confirmation. * Signed informed consent and agreed to participate in this study.
Exclusion criteria
* other subtypes of secondary hypertension, including renal hypertension, renovascular hypertension, and adrenal hypertension (i.e., pheochromocytoma and Cushing syndrome). * adrenal cortical carcinoma * acute infection at the time of assessment * severe cardiovascular or cerebrovascular disease, liver or renal dysfunction, tumors, autoimmune disease or mental disorders. * history of adrenalectomy * alcohol abuse or pregnancy
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The potential biomarkers for primary aldosteronism subtype classification via untargeted metabolomics | 4 months | The differentially expressed metabolites between idiopathic aldosteronism (IHA) and aldosterone-producing adenoma (APA) will be identified by untargeted metabolomics. The differentially expressed metabolites with good discriminative capability for determination of APA from IHA can serve as biomarkers for PA subtype classification. |
| The predictive models for PA diagnosis and subtype classification by machine learning | 4 months | The predictive models will be constructed through the application of machine learning, integrating clinical data with differentially expressed metabolites for the diagnosis and subtype classification of PA |
| The potential biomarkers for primary aldosteronism diagnosis via untargeted metabolomics | 4 months | The differentially expressed metabolites between primary aldosteronism (PA) and essential hypertension (EH) will be identified by untargeted metabolomics. The differentially expressed metabolites with good discriminative capability for determination of PA from EH can serve as biomarkers for PA diagnosis. |
Countries
China
Outcome results
None listed