부산대학교 도서관

Tong Chen,1– 3 Shiquan Wu,1 Ling Feng,4 SiYu Long,1 Yu Liu,1,2 WenQian Lu,5 Wenya Chen,1 Guoai Hong,1 Li Zhou,1 Fang Wang,1 Yuechan Luo,1 Hequn Zou1,3,5 1Department of Nephrology, South China Hospital of Shenzhen University, Shenzhen, People’s Republic of China; 2Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, People’s Republic of China; 3Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 4Department of Nephrology, Shenzhen Hospital, Southern Medical University, Shenzhen, People’s Republic of China; 5Department of Medicine, The Chinese University of Hong Kong, Shenzhen, People’s Republic of ChinaCorrespondence: Hequn Zou, School of Medicine, The Chinese University of Hong Kong, Shenzhen, People’s Republic of China, Email zouhequn@cuhk.edu.cnBackground: The annual prevalence of metabolic syndrome (MetS) is increasing. Therefore, early screening and recognition of MetS are critical. This study aimed to evaluate the association between high-density lipoprotein (HDL) subclasses and MetS and to examine whether they could serve as early indicators in a Chinese community-based population with normal high-density lipoprotein cholesterol (HDL-C) levels.Methods: We used microfluidic chip technology to measure HDL subclasses in 463 people with normal HDL levels in 2018. We assessed how HDL subclasses correlated with and predicted insulin resistance (IR) and metabolic syndrome (MetS), evaluated by homeostatic model insulin resistance index (HOMA-IR) and the 2009 International Diabetes Federation (IDF), the American Heart Association (AHA), and the National Heart, Lung, and Blood Institute (NHLBI) criteria, respectively. We used correlation tests and ROC curves for the analysis.Results: The results indicate that there was a negative association between HDL2b% and the risk of IR and MetS in both sexes. Subjects in the highest quartile of HDL2b% had a significantly lower prevalence of IR and MetS than those in the lowest quartile (P< 0.01). Correlation analysis between HDL2b% and metabolic risk factors showed that HDL2b% had a stronger association with these factors than HDL-C did in both sexes. ROC curve analysis also showed that HDL2b% had significant diagnostic value for IR and MetS compared to other lipid indicators.Conclusion: This study showed that MetS alters the distribution of HDL subclasses even when HDL-C levels are within the normal range. HDL-2b% has better diagnostic value for IR and MetS than HDL-C alone and may be a useful marker for early screening.Keywords: HDL subclass, insulin resistance, metabolic syndrome, normal HDL-C population