Advanced lipoprotein profile identifies atherosclerosis better than conventional lipids in type 1 diabetes at high cardiovascular risk
Atherosclerotic cardiovascular disease
DOI:
10.1016/j.numecd.2023.03.025
Publication Date:
2023-04-05T20:46:49Z
AUTHORS (15)
ABSTRACT
People with type 1 diabetes (T1D) present lipoprotein disturbances that could contribute to their increased cardiovascular disease (CVD) risk. We evaluated the relationship between lipoprotein alterations and atherosclerosis in patients with T1D.Cross-sectional study in subjects with T1D, without previous CVD, but high-risk (≥40 years, nephropathy, or ≥10 years of evolution of diabetes with another risk factor). The presence of plaque (intima-media thickness ≥1.5 mm) in the different carotid segments was determined by ultrasound. The advanced lipoprotein profile was analysed by magnetic resonance imaging (1H NMR). We included 189 patients (42% women, 47.8 ± 10.7 years, duration of diabetes 27.3 ± 10.1 years, HbA1c 7.5% [7-8]). Those with carotid plaques (35%) were older, with longer diabetes duration, had a higher prevalence of hypertension, and showed lower and smaller LDL particles (LDL-P) and HDL particles (HDL-P), but higher VLDL particles (VLDL-P). Some LDL, HDL and VLDL-related parameters were associated with atherosclerosis in sex, age and statin use adjusted models (p < 0.05), but after adjusting for multiple confounders, including conventional lipid parameters, only HDL-P (OR 0.440 [0.204-0.951]; p = 0.037), medium HDL-P (OR 0.754 [0.590-0.963]; p = 0.024), HDL-P cholesterol content (OR 0.692 [0.495-0.968]; p = 0.032), 1H NMR LDL-P number/conventional LDL-cholesterol (OR 1.144 [1.026-1.275]; p = 0.015), and 1H NMR non-HDL particle number/conventional non-HDL-cholesterol ratios (OR 1.178 [1.019-1.361], p = 0.026) remained associated with atherosclerosis.In adults with T1D at high-risk, variables related to HDL, LDL and total atherogenic particle number are independently associated with preclinical atherosclerosis. Advanced lipoprotein profiling could be used to identify those at the highest risk of CVD.
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