High-density lipoprotein subclasses and cardiovascular disease and mortality in type 2 diabetes: analysis from the Hong Kong Diabetes Biobank

Qiao Jin, Eric S. H. Lau, Andrea O. Luk, Claudia H. T. Tam, Risa Ozaki, Cadmon K. P. Lim, Hongjiang Wu, Elaine Y. K. Chow, Alice P. S. Kong, Heung Man Lee, Baoqi Fan, Alex C. W. Ng, Guozhi Jiang, Ka Fai Lee, Shing Chung Siu, Grace Hui, Chiu Chi Tsang, Kam Piu Lau, Jenny Y. Leung, Man-wo TsangGrace Kam, Elaine Y. N. Cheung, Ip Tim Lau, June K. Li, Vincent T. Yeung, Emmy Lau, Stanley Lo, Samuel Fung, Chun Chung Chow, Yuk Lun Cheng, Weichuan Yu, Stephen K. W. Tsui, Yu Huang, Hui-yao Lan, Cheuk Chun Szeto, Wing Yee So, Alicia J. Jenkins, Juliana C. N. Chan, Ronald C. W. Ma*, Hong Kong Diabetes Biobank Study Group, including

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

22 Citations (Scopus)
63 Downloads (CityUHK Scholars)

Abstract

Objective: High-density lipoproteins (HDL) comprise particles of different size, density and composition and their vasoprotective functions may differ. Diabetes modifies the composition and function of HDL. We assessed associations of HDL size-based subclasses with incident cardiovascular disease (CVD) and mortality and their prognostic utility. Research design and methods: HDL subclasses by nuclear magnetic resonance spectroscopy were determined in sera from 1991 fasted adults with type 2 diabetes (T2D) consecutively recruited from March 2014 to February 2015 in Hong Kong. HDL was divided into small, medium, large and very large subclasses. Associations (per SD increment) with outcomes were evaluated using multivariate Cox proportional hazards models. C-statistic, integrated discrimination index (IDI), and categorial and continuous net reclassification improvement (NRI) were used to assess predictive value. Results: Over median (IQR) 5.2 (5.0-5.4) years, 125 participants developed incident CVD and 90 participants died. Small HDL particles (HDL-P) were inversely associated with incident CVD [hazard ratio (HR) 0.65 (95% CI 0.52, 0.81)] and all-cause mortality [0.47 (0.38, 0.59)] (false discovery rate < 0.05). Very large HDL-P were positively associated with all-cause mortality [1.75 (1.19, 2.58)]. Small HDL-P improved prediction of mortality [C-statistic 0.034 (0.013, 0.055), IDI 0.052 (0.014, 0.103), categorical NRI 0.156 (0.006, 0.252), and continuous NRI 0.571 (0.246, 0.851)] and CVD [IDI 0.017 (0.003, 0.038) and continuous NRI 0.282 (0.088, 0.486)] over the RECODe model. Conclusion: Small HDL-P were inversely associated with incident CVD and all-cause mortality and improved risk stratification for adverse outcomes in people with T2D. HDL-P may be used as markers for residual risk in people with T2D.
Original languageEnglish
Article number293
JournalCardiovascular Diabetology
Volume21
Online published31 Dec 2022
DOIs
Publication statusPublished - 2022

Funding

This work was supported by a Grant from the Research Grants Council of the Hong Kong Special Administrative Region (CU R4012-18), the NSFC-NHMRC Joint Research Scheme (Ref. 81561128017), Research Grants Council Theme-based Research Scheme (T12-402/13 N), the Focused Innovation Scheme, the Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Fund, and, a Croucher Foundation Senior Medical Research Fellowship, and Research Grants Council Senior Research Fellow (SRFS2021-4S04). The funding sources did not have any role in the design, interpretation of the study, or the decision to publish the results.

Research Keywords

  • Cardiovascular disease
  • High-density lipoprotein particles
  • High-density lipoprotein subclasses
  • Mortality
  • Prognostic marker
  • Residual risk
  • Risk stratification
  • Type 2 diabetes
  • CORONARY-ARTERY-DISEASE
  • MYOCARDIAL-INFARCTION
  • HEART-FAILURE
  • PARTICLE-SIZE
  • RISK
  • POPULATION
  • EVENTS
  • EPIDEMIOLOGY
  • PREDICTION
  • IMPROVE

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

  • RGC-funded

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