Abstract
BACKGROUND: Hypertension is a chronic condition and a leading risk factor for cardiovascular disease, stroke, and premature mortality worldwide. While blood pressure (BP) monitoring-via clinical, home, or ambulatory measurements-remains the primary diagnostic tool, each method is limited by variability, device inaccuracy, and difficulties in detecting atypical BP patterns such as masked or white-coat hypertension. These challenges underscore the need for innovative, complementary diagnostic approaches. OBJECTIVE: This systematic review and meta-analysis aims to synthesize current evidence on the role of metabolomic profiling in the detection and understanding of hypertension. Specifically, it seeks to evaluate whether metabolomics can identify preclinical metabolic signatures, improve diagnostic accuracy, and elucidate pathophysiological mechanisms underlying hypertension, thereby complementing traditional BP monitoring. METHODS: A systematic search will be conducted in PubMed, Embase, Web of Science, Scopus, and CENTRAL from inception to the present supplemented with manual screening of metabolomics repositories (MetaboLights and Metabolomics Workbench) to ensure comprehensive coverage. This systematic review will include studies involving adults (aged ≥18 years) that investigate metabolomic biomarkers in hypertension using validated analytical platforms such as nuclear magnetic resonance spectroscopy, gas chromatography-mass spectrometry, or liquid chromatography-mass spectrometry. Eligible studies must stratify participants into hypertensive, prehypertensive, or normotensive groups and report associations between metabolites and BP measurements. Two independent reviewers will conduct study selection, data extraction, and risk-of-bias assessment using version 2 of the Cochrane risk-of-bias tool for randomized trials and the Risk of Bias in Nonrandomized Studies of Interventions and Risk of Bias in Nonrandomized Studies of Exposures tools, with evidence certainty evaluated via the Grading of Recommendations Assessment, Development, and Evaluation framework. A meta-analysis will be performed where possible using random-effects models and subgroup analyses to address heterogeneity. RESULTS: Database search, screening, and data extraction are ongoing as of January 2026. The results will summarize metabolomic profiles (such as stearidonate and hexadecadienoate), diagnostic accuracy metrics (eg, area under the curve and sensitivity), and metabolic pathways associated with hypertension once data synthesis is completed. The systematic review and meta-analysis is expected to be published in August 2026. CONCLUSIONS: This review will identify metabolites showing consistent hypertension associations and document methodological requirements for clinical translation, including standardization of sample collection, analytical platforms, and data processing. The findings will inform longitudinal validation studies and establish evidence-based pathways for potential applications in hypertension risk assessment and clinical trial design. Validation of consistently identified metabolite-hypertension associations in independent, prospective cohorts will be critical for establishing causality and assessing the temporal stability of metabolomic signatures. The review will also identify methodological gaps requiring standardization, such as sample collection protocols, analytical platform harmonization, and data processing procedures, which must be addressed before metabolomic findings can be translated into clinical applications.