Scholarlink

Background <p>Hypertension, a major modifiable risk factor for cardiovascular disease, exhibits significant heterogeneity due to genetic, metabolic, and environmental influences. Traditional one-size-fits-all management is inadequate, necessitating predictive, preventive, and personalized medicine (3PM) approaches.</p> Study objective <p>This review critically evaluates 3PM’s application in hypertension, focusing on leveraging biomarkers, artificial intelligence (AI), and digital health for risk stratification, early intervention, and tailored therapies.</p> Key discussion <p>The 3PM framework leverages AI-driven integration of multi-omics, retinal imaging like ViT models, and hemodynamic profiling for risk prediction and treatment response forecasting; genetic profiling such as&#xa0;<i>MTHFR</i>,&#xa0;<i>UMOD</i>&#xa0;variants, urinary proteomics (CKD273 classifier), and microbiome-guided nutrition for early intervention; and pharmacogenomics, digital phenotyping like smartphone-guided dosing, and novel therapies such as aprocitentan and finerenone for personalized efficacy. Specific findings include aprocitentan reducing systolic BP by −15.3&#xa0;mmHg in resistant hypertension,&#xa0;<i>UMOD</i>-guided torasemide use lowering BP by 8.5&#xa0;mmHg in carriers, and microbiome-based nutrition reducing systolic BP by 14% in hyperglycemic patients. Key challenges include limited biomarker validation, “black box” AI algorithms, high costs, interoperability gaps, and equity barriers.</p> Conclusion <p>3PM transforms hypertension management by enabling proactive, individualized care. However, rigorous validation, affordable diagnostics, pragmatic trials, and equitable access are essential to bridge translational gaps and achieve personalized cardiology’s full potential.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The use of predictive, preventive, and personalized medical approaches to optimize hypertension management

  • 期刊论文

  • 发表日期：

    2025年10月15日

查看全文
  • Ousman Bajinka,
  • Lamarana Jallow,
  • Yanjun Zhang,
  • Xiaoxia Feng,
  • Xianquan Zhan,
  • Na Li

摘要

Background

Hypertension, a major modifiable risk factor for cardiovascular disease, exhibits significant heterogeneity due to genetic, metabolic, and environmental influences. Traditional one-size-fits-all management is inadequate, necessitating predictive, preventive, and personalized medicine (3PM) approaches.

Study objective

This review critically evaluates 3PM’s application in hypertension, focusing on leveraging biomarkers, artificial intelligence (AI), and digital health for risk stratification, early intervention, and tailored therapies.

Key discussion

The 3PM framework leverages AI-driven integration of multi-omics, retinal imaging like ViT models, and hemodynamic profiling for risk prediction and treatment response forecasting; genetic profiling such as MTHFR, UMOD variants, urinary proteomics (CKD273 classifier), and microbiome-guided nutrition for early intervention; and pharmacogenomics, digital phenotyping like smartphone-guided dosing, and novel therapies such as aprocitentan and finerenone for personalized efficacy. Specific findings include aprocitentan reducing systolic BP by −15.3 mmHg in resistant hypertension, UMOD-guided torasemide use lowering BP by 8.5 mmHg in carriers, and microbiome-based nutrition reducing systolic BP by 14% in hyperglycemic patients. Key challenges include limited biomarker validation, “black box” AI algorithms, high costs, interoperability gaps, and equity barriers.

Conclusion

3PM transforms hypertension management by enabling proactive, individualized care. However, rigorous validation, affordable diagnostics, pragmatic trials, and equitable access are essential to bridge translational gaps and achieve personalized cardiology’s full potential.