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Statin-dependent and -independent pathways are associated with major adverse cardiovascular events in people with HIV

Márton Kolossváry1, Irini Sereti2, Markella V Zanni1

  • 1Metabolism Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

The Journal of Clinical Investigation
|September 9, 2025
PubMed

Insights

Statin therapy reduces cardiovascular events in people with HIV (PWH). Angiopoietin-related protein 3 (ANGPTL3) and inflammatory pathways contribute to residual risk beyond LDL-cholesterol, impacting major adverse cardiovascular events (MACE).

Area of Science:

  • Cardiology
  • Immunology
  • Genetics

Background:

  • Statin therapy is known to reduce major adverse cardiovascular events (MACE) in people with HIV (PWH).
  • However, residual MACE risk beyond LDL-cholesterol (LDL-C) reduction in PWH remains poorly understood.
  • Identifying these residual risk pathways is crucial for improving cardiovascular outcomes in this population.

Purpose of the Study:

  • To investigate the association of statin-responsive and other inflammatory/metabolic pathways with MACE in PWH.
  • To evaluate the role of specific proteins, including angiopoietin-related protein 3 (ANGPTL3), in residual cardiovascular risk.
  • To develop a machine-learning model for predicting MACE using proteomic data.

Main Methods:

  • Utilized Cox proportional hazards models to analyze MACE associations with proteomic measurements from the REPRIEVE trial.
  • Adjusted for time-updated statin use and baseline atherosclerotic cardiovascular disease risk score.
  • Developed a machine-learning model to predict MACE based on baseline protein levels.

Main Results:

  • Among proteins affected by statins, ANGPTL3 showed the strongest association with MACE (aHR: 2.31), indicating lower ANGPTL3 levels with statin use correlate with reduced MACE risk.
  • Of proteins not altered by statins, 26 were linked to MACE, primarily involving humoral immune response, leukocyte chemotaxis, and cytokine pathways.
  • The machine-learning model incorporating proteomic data achieved a concordance index of 0.74, outperforming traditional risk prediction models (C-index: 0.61).

Conclusions:

  • ANGPTL3 and key inflammatory pathways contribute to residual MACE risk in PWH, independent of LDL-C levels.
  • These findings highlight potential therapeutic targets for mitigating cardiovascular risk in people with HIV.
  • Proteomic profiling offers a promising approach for enhancing MACE prediction in PWH.

Keywords:
AIDS/HIVCardiologyCardiovascular diseaseInflammationMachine learningProteomics

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