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Proteomic Risk Score for Prediction of Incident Hypertension.

Minkwan Kim1, Hamed Tavolinejad2,3, Mateo Bustamante2,3

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Summary

A novel proteomic risk score (ProtRS) significantly improves prediction of incident hypertension, outperforming traditional risk factors and genetic data. This proteomic approach offers enhanced hypertension risk stratification and insights into disease mechanisms.

Keywords:
biomarkersgenetic risk scorehypertensionproteomicsrisk assessment

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Area of Science:

  • Cardiovascular Disease Research
  • Proteomics and Biomarker Discovery
  • Precision Medicine

Background:

  • Proteomic signatures show promise in predicting cardiometabolic diseases.
  • Accurate prediction of incident hypertension is crucial for targeted prevention strategies.

Purpose of the Study:

  • To evaluate if a proteomic risk score (ProtRS) enhances the prediction of incident hypertension.
  • To assess the added value of ProtRS beyond established demographic, clinical, and genetic risk factors.

Main Methods:

  • A ProtRS was developed using penalized Cox regression in a UK Biobank Proteomics cohort (n=25,158).
  • The ProtRS was validated in an independent UK Biobank test set (n=10,781) and the Asklepios study (n=793).
  • Model performance was assessed by comparing risk prediction with and without the ProtRS, including adjustments for covariates and polygenic risk scores (PRS).

Main Results:

  • In UK Biobank, a higher ProtRS was strongly associated with incident hypertension (HR, 1.68).
  • Adding ProtRS significantly improved model fit, discrimination (C-index increased from 0.745 to 0.765), and reclassification (NRI, 19.0%).
  • External validation in Asklepios confirmed ProtRS association with hypertension risk (HR, 1.32) and improved model discrimination.

Conclusions:

  • A proteomic risk score (ProtRS) significantly enhances prediction of incident hypertension beyond current demographic, clinical, and genetic information.
  • Proteomic data offers a valuable tool for individualized hypertension risk stratification.
  • Pathway analysis suggests biologic insights into hypertension development, including neutrophil degranulation and PI3K signaling.