Research highlight: Investigating the metabolic effects of CETP inhibitiors

Millwood et al. Association of CETP Gene Variants With Risk for Vascular and Nonvascular Diseases Among Chinese Adults. JAMA Cardiol.doi:10.1001/jamacardio.2017.4177

Until recently, it was widely anticipated that increasing blood levels of high-density lipoprotein cholesterol (HDL-C) levels could act as a powerful treatment method for reducing CVD risk. A great deal of effort has been spent developing pharmacological solutions to increase HDL-C levels, in particular a new drug class known as cholesteryl ester transfer protein (CETP) inhibitors. Despite observation study associations between low plasma concentrations of HDL-C and increased CVD risk, CETP inhibitor drug trials have failed or resulted in a very modest efficacy not proportionate to the increase in HDL-C produced. 

A paper published in JAMA earlier this year (Ference, et al. 2017), found that genetic variants in the CETP gene produced modest changes in the corresponding CVD risk, in particular on top of statin therapies. This indicates that the clinical benefit of reducing low-density lipoproteins cholesterol (LDL-C) levels may depend on a similar reduction in the amount of apolipoprotein B containing lipoprotein particles. 

In order to further investigate the impact of increasing HDL-C levels through use of CETP inhibitors on detailed metabolic profiles, Millwood and colleagues used genetic variants in the CETP gene to assess the effects of lowered CETP activity on CVD risk, along with other factors that could indicate potential on-target effects (e.g. risk of eye diseases). Five CETP variants, including an East Asian specific loss-of-function variant (rs2303790), were selected for investigation from a biobank cohort of 151,217 Chinese participants. Among these individuals, 4657 participants provided blood samples which were analysed using high-throughput NMR-based metabolomics to provide metabolic profiling data. The genetic variants were combined in a genetic score weighted to baseline associations with HDL-C levels from metabolic profiles, with CVD-related event incidence reported in a long-term follow-up (median follow-up of 9.2 years). The follow-up method utilised electronic health records, linking each participant’s unique identification number with established registries for morbidity and mortality.  

CETP variants were found to be strongly associated with higher concentrations of HDL-C but did not lower LDL-C levels in this population. The CETP genetic score and loss-of-function variant were found to not be associated with occlusive CVD events or other related vascular diseases. The only association identified was with a nonvascular event, indicating an increased risk for eye diseases due to CETP inhibition. 

This study provides further evidence that suggests that whilst CETP inhibitors are effective at raising HDL-C levels, clinical benefits for CVD are unlikely to be significant unless LDL-C levels are also reduced. Whereas previous studies have been conducted in European populations (which typically feature both higher HDL-C levels also lower LDL-C levels due to CETP genetic variants), this investigation provides evidence from Chinese populations informing future treatment strategies. These findings may also suggest that the association of CETP variants with CVD risk in previous studies could have been influenced by linked lowering of LDL-C levels or other lipid-related factors. 

This study is an example of Nightingale's NMR metabolomics platform being applied in CVD research. Nightingale's platform has been successfully applied to a wide range of research applications and has been featured in over 100 peer-reviewed studies, published in leading biomedical journals. Nightingale’s platform can be utilized to investigate drug target mechanism of action, using genetic variants as a proxy for therapy (Mendelian Randomization). In this study, Nightingale’s platform was used to quantify 225 metabolic measures, including detailed lipid and lipoprotein particle profiles, for 4657 individuals from the China Kadoorie Biobank.

Access to the full paper can be found here