Association between carotid intima-media thickness and pericardial fat in the Multi-Ethnic Study of Atherosclerosis

Elsayed Z Soliman1, Jingzhong Ding, Fang-Chi Hsu

  • 1Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston Salem, North Carolina 27104, USA. esoliman@wfubmc.edu

Insights

Pericardial fat (PF) is linked to carotid intima-media thickness (IMT), a marker of atherosclerosis. This association may not be independent of overall adiposity or common risk factors.

Area of Science:

  • Cardiology
  • Vascular Biology
  • Radiology

Background:

  • Carotid intima-media thickness (IMT) is a key subclinical marker for atherosclerosis and a significant predictor of stroke.
  • Pericardial fat (PF), the adipose tissue surrounding the heart, has been correlated with various atherosclerosis risk factors.

Purpose of the Study:

  • To investigate the relationship between carotid IMT and PF.
  • To determine if this association is independent of established atherosclerosis risk factors and overall adiposity measures.

Main Methods:

  • Utilized linear regression analysis on a sample of 996 participants from the Multi-Ethnic Study of Atherosclerosis (MESA).
  • Assessed associations between common carotid artery (CCA) IMT and internal carotid artery (ICA) IMT with PF using carotid ultrasound and chest CT data.

Main Results:

  • A significant positive correlation was found between PF and both CCA-IMT and ICA-IMT.
  • Initial analyses showed significant associations between PF and IMT in both sexes, which persisted after adjusting for age and ethnicity.
  • However, these associations became non-significant after further adjustment for common atherosclerosis risk factors and measures of adiposity (BMI or waist circumference).

Conclusions:

  • Pericardial fat is associated with carotid IMT in the general population.
  • This association appears to be dependent on markers of overall adiposity and common atherosclerosis risk factors, suggesting it may not be an independent predictor.
Abstract

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