Plasma glycomics predict cardiovascular disease in patients with ART-controlled HIV infections

FASEB J. 2019 Feb;33(2):1852-1859. doi: 10.1096/fj.201800923R. Epub 2018 Sep 5.

Abstract

Despite effective control of HIV infection with antiretroviral drugs, individuals with HIV have high incidences of secondary diseases. These sequelae, such as cardiovascular disease (CVD), are poorly understood and represent a major health burden. To date, predictive biomarkers of HIV-associated secondary disease have been elusive, making preventative clinical management essentially impossible. Here, we applied a newly developed and easy to deploy, multitarget, and high-throughput glycomic analysis to banked HIV+ human plasma samples to determine whether the glycome may include biomarkers that predict future HIV-associated cardiovascular events or CVD diagnoses. Using 324 patient samples, we identified a glycomic fingerprint that was predictive of future CVD events but independent of CD4 counts, diabetes, age, and birth sex, suggesting that the plasma glycome may serve as a biomarker for specific HIV-associated sequelae. Our findings constitute the discovery of novel glycan biomarkers that could classify patients with HIV with elevated risk for CVD and reveal the untapped prognostic potential of the plasma glycome in human disease.-Oswald, D. M., Sim, E. S., Baker, C., Farhan, O., Debanne, S. M., Morris, N. J., Rodriguez, B. G., Jones, M. B., Cobb, B. A. Plasma glycomics predict cardiovascular disease in patients with ART-controlled HIV infections.

Keywords: CVD; biomarker; glycan; glycome; lectin.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Antiviral Agents / therapeutic use*
  • Biomarkers / blood
  • Carbohydrates / blood*
  • Cardiovascular Diseases / blood
  • Cardiovascular Diseases / complications*
  • Female
  • Glycomics*
  • Glycosylation
  • HIV Infections / blood
  • HIV Infections / complications*
  • HIV Infections / drug therapy*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Proof of Concept Study

Substances

  • Antiviral Agents
  • Biomarkers
  • Carbohydrates