High density lipoprotein in atherosclerosis and coronary heart disease: Where do we stand today?

Evangelia Zvintzou1, Dimitra Sotiria Karampela1, Aggeliki Vakka1

  • 1University of Patras, School of Medicine, Department of Pharmacology, Rio Achaias, TK 26500, Greece.

Vascular Pharmacology
|October 25, 2021
PubMed

Insights

High density lipoprotein cholesterol (HDL-C) levels and cardiovascular disease (CVD) risk follow a U-shaped curve. HDL particle function, not just levels, impacts atherosclerosis, questioning HDL-C-raising drug efficacy.

Area of Science:

  • Biochemistry
  • Epidemiology
  • Pharmacology

Background:

  • Cardiovascular disease (CVD) risk is linked to high density lipoprotein cholesterol (HDL-C) levels, exhibiting a U-shaped curve.
  • Optimal HDL-C ranges vary by sex: 40-70 mg/dl for men and 50-70 mg/dl for women.
  • HDL particles have diverse structural and functional attributes, influencing their role as antiatherogenic or proatherogenic.

Purpose of the Study:

  • To critically review current literature on HDL, focusing on biochemistry, epidemiology, and pharmacology.
  • To evaluate the suitability of experimental drugs and clinical trial designs targeting HDL-C-raising hypotheses.
  • To discuss HDL's role in atherosclerosis prevention based on structure and function.

Main Methods:

  • Compilation and critical analysis of existing scientific literature on HDL.
  • Review of data from clinical trials investigating HDL-C.
  • Examination of HDL structure and function in relation to atherosclerosis.

Main Results:

  • The relationship between HDL-C and CVD risk is complex, not linear.
  • HDL particle heterogeneity suggests function is more critical than mere concentration.
  • Clinical trials targeting HDL-C-raising have yielded questionable results.

Conclusions:

  • The efficacy of HDL-C-raising strategies is doubtful due to HDL particle diversity.
  • Understanding HDL structure and function is crucial for effective atherosclerosis prevention.
  • Discrepancies between mouse models and human responses may explain failed pharmacological interventions.

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