Association of Lipid Fractions With Risks for Coronary Artery Disease and Diabetes | Cardiology | JAMA Cardiology | JAMA Network
[Skip to Navigation]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address Please contact the publisher to request reinstatement.
[Skip to Navigation Landing]
Original Investigation
September 2016

Association of Lipid Fractions With Risks for Coronary Artery Disease and Diabetes

Author Affiliations
  • 1University College London Genetics Institute, University College London, London, England
  • 2Farr Institute at University College London, London, England
  • 3Department of Medicine, Imperial College London, London, England
  • 4Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, England
  • 5The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, England
  • 6Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
  • 7Department of Surgery, University of Pennsylvania, Philadelphia, Pennsylvania
  • 8Division of Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
  • 9Durrer Center for Cardiovascular Research, Netherlands Heart Institute, Utrecht, Netherlands
  • 10Institute of Cardiovascular Science, University College London, London, England
  • 11Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, Scotland
  • 12Cardiovascular Genetics, British Heart Foundation Laboratories, Institute Cardiovascular Science, University College London, London, United Kingdom
JAMA Cardiol. 2016;1(6):692-699. doi:10.1001/jamacardio.2016.1884

Importance  Low-density lipoprotein cholesterol (LDL-C) is causally related to coronary artery disease (CAD), but the relevance of high-density lipoprotein cholesterol (HDL-C) and triglycerides (TGs) is uncertain. Lowering of LDL-C levels by statin therapy modestly increases the risk of type 2 diabetes, but it is unknown whether this effect is specific to statins.

Objective  To investigate the associations of 3 routinely measured lipid fractions with CAD and diabetes through mendelian randomization (MR) using conventional MR and making use of newer approaches, such as multivariate MR and MR-Egger, that address the pleiotropy of genetic instruments where relevant.

Design, Setting, and Participants  Published data from genome-wide association studies were used to construct genetic instruments and then applied to investigate associations between lipid fractions and the risk of CAD and diabetes using MR approaches that took into account pleiotropy of genetic instruments. The study was conducted from March 12 to December 31, 2015.

Main Outcomes and Measures  Coronary artery disease and diabetes.

Results  Genetic instruments composed of 130 single-nucleotide polymorphisms (SNPs) were used for LDL-C (explaining 7.9% of its variance), 140 SNPs for HDL-C (6.6% of variance), and 140 SNPs for TGs (5.9% of variance). A 1-SD genetically instrumented elevation in LDL-C levels (equivalent to 38 mg/dL) and TG levels (equivalent to 89 mg/dL) was associated with higher CAD risk; odds ratios (ORs) were 1.68 (95% CI, 1.51-1.87) for LDL-C and 1.28 (95% CI, 1.13-1.45) for TGs. The corresponding OR for HDL-C (equivalent to a 16-mg/dL increase) was 0.95 (95% CI, 0.85-1.06). All 3 lipid traits were associated with a lower risk of type 2 diabetes. The ORs were 0.79 (95% CI, 0.71-0.88) for LDL-C and 0.83 (95% CI, 0.76-0.90) for HDL-C per 1-SD elevation. For TG, the MR estimates for diabetes were inconsistent, with MR-Egger giving an OR of 0.83 (95%CI, 0.72-0.95) per 1-SD elevation.

Conclusions and Relevance  Routinely measured lipid fractions exhibit contrasting associations with the risk of CAD and diabetes. Increased LDL-C, HDL-C, and possibly TG levels are associated with a lower risk of diabetes. This information will be relevant to the design of clinical trials of lipid-modifying agents, which should carefully monitor participants for dysglycemia and the incidence of diabetes.