Open AccessSerum HDL cholesterol uptake capacity in subjects from the MASHAD cohort study: Its value in determining the risk of cardiovascular endpoints
Author(s) -
Aghasizadeh Malihe,
Samadi Sara,
Sahebkar Amirhossein,
MiriMoghaddam Ebrahim,
Esmaily Habibollah,
Souktanloo Mohamad,
Avan Amir,
Mansoori Amin,
Ferns Gordon A.,
Kazemi Tooba,
GhayourMobarhan Majid
Publication year - 2021
Publication title -
journal of clinical laboratory analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 50
eISSN - 1098-2825
pISSN - 0887-8013
DOI - 10.1002/jcla.23770
Subject(s) - medicine , confounding , cholesterol , logistic regression , cohort , reverse cholesterol transport , proportional hazards model , population , high density lipoprotein , endocrinology , gastroenterology , lipoprotein , environmental health
Background The efficiency of high‐density lipoprotein (HDL) to efflux cholesterol contributes to the reverse cholesterol transport (RCT) pathway as one of HDL’s proposed functions and depends on the ability of HDL to uptake cholesterol. We aimed to investigate cholesterol uptake capacity (CUC) by a newly developed assay in samples from the MASHAD (Mashhad Stroke and Heart Atherosclerotic Disorders) cohort study. Method The study population comprised 153 individuals developed CVD diagnosed by a specialist cardiologist, over 6 years of follow‐up, and 350 subjects without CVD. We used a modified CUC method to evaluate the functionality of HDL in serum samples. Result The CUC assay was highly reproducible with values for inter‐ and intra‐assay variation of 13.07 and 6.65, respectively. The mean serum CUC was significantly lower in the CVD group compared to control ( p = 0.01). Although, there were no significant differences in serum HDL‐C between the groups and there was no significantly association with risk of progressive CVD. Multivariate logistic regression analysis showed that there was a significantly negative association between CUC and risk of CVD after adjustment for confounding parameters (OR = 0.57, 95% CI = 0.38–0.87, p = 0.009). The CUC was also inversely and independently associated with the risk of CVD event using Cox proportional hazards models analysis (HR = 0.62; 95% CI = 0.41–0.94, p = 0.02). We determined the optimum cutoff value of 1.7 a.u for CUC in the population. Furthermore, the CUC value was important in determining the CVD risk stratification derived from data mining analysis. Conclusions Reduced HDL functionality, as measured by CUC, appears to predict CVD in population sample from north‐eastern Iran.