The Association of HDL2b with Metabolic Syndrome Among Normal HDL-C Populations in Southern China

Diabetes Metab Syndr Obes. 2024 Jan 23:17:363-377. doi: 10.2147/DMSO.S446859. eCollection 2024.

Abstract

Background: 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.

Grants and funding

We would like to express our gratitude to all the subjects who participated in the study, which was supported by Municipal Science and Technology Innovation Commission University Stability Support Project (Project No.2020082 2123122001) and also supported by Key technical projects of the Municipal Science and Technology Innovation Commission (Project No. JSGG2020022515 2709802) and National Natural Science Fund (Project No. 81873620), and also supported by Provincial Natural Science Fund (Project No.2021A151501 0972).