Genetic Information May Indicate Risk for Cardiovascular Events in Type 2 Diabetes

Share this content:
Researchers investigate certain SNPs for prediction of cardiovascular events in diabetes patients.
Researchers investigate certain SNPs for prediction of cardiovascular events in diabetes patients.

Single nucleotide polymorphisms at the Niemann-Pick C1-like 1 gene locus may significantly predict cardiovascular (CV) events in coronary artery disease (CAD) patients with type 2 diabetes, according to new data.

Results were presented at the American College of Cardiology's (ACC) 65th Annual Scientific Sessions.

Niemann-Pick C1-like 1 (NPC1L1) is involved in dietary cholesterol absorption and is the molecular target of the LDL-lowering drug ezetimibe. Genetic variation at NPC1L1 locus has been linked with CV event risk, but the association of NPC1L1 variants with CV events has only been shown in the general population.

“This has never been looked at in diabetes patients and it has been suggested that they may benefit more than others,” said lead study author Christoph Saely, MD, professor of preventive cardiology and consultant at the Academic Teaching Hospital Feldkirch in Austria.

Dr Saely and his colleagues prospectively investigated the impact of NPC1L1 tagging single nucleotide polymorphisms (SNPs) rs3187907, rs10264715, rs4720470, rs217420, rs17655652, and rs17725246 on the incidence of vascular events. The analysis included in 943 patients undergoing coronary angiography for the evaluation of stable CAD. Among the 943 patients, 241 had type 2 diabetes (24.6%).  

The investigators found that after a mean follow-up of 3.5 years, 172 first vascular events occurred in the total cohort and 55 first vascular events occurred in the diabetes cohort.

The researchers used genotyping by microarray analysis using the MetaboChip (Illumina Inc, San Diego, CA). Single nucleotide polymorphisms (SNPs) rs3187907, rs10264715, rs4720470, rs217420, rs17655652, and rs17725246 were selected as NPC1L1 tagging SNPs. In addition, they selected variants rs217434, rs2072183 and rs41279633.   

The researchers reported that variants rs3187907, rs10264715, rs217420, rs17725246 as well as rs217434, rs2072183, and rs41279633 significantly predicted CV events both in the total study population and diabetes cohort, after multivariate adjustment including for statin use. The study demonstrated that tagging variants rs4720470 and rs17655652 did not predict CV events in either the total study population or the diabetes cohort.

Dr Saely told Endocrinology Advisor that additional studies are now warranted to help further determine the molecular consequences of common genetic variants. 

Brian Ference, MD, a member of the ACC Prevention of Cardiovascular Disease Committee and director of the Cardiovascular Genomic Research Center at Wayne State University School of Medicine in Detroit, said this study may raise more questions than it answers.  

“This is far in excess in what has been found in other studies. The implication is that the sample size is so small it may be a chance finding,” Dr Ference said in an interview with Endocrinology Advisor. “The people with diabetes appear to have a slight higher risk, but there is no plausible reason why that would be the case.”

This area of medicine is on in its infancy, he noted, explaining that clinicians in the not too distant future should be able to use genotypes to identify risk factors early in patients with type 2 diabetes who may be most vulnerable to potential problems. 

“In patients with diabetes, we may be able to find out which patients are more vulnerable to weight gain. Genomics has a lot of promise in the future. It will probably help with direct disease management,” said Dr Ference.

Reference

  1. Muendlin A, Leiherer A, Saely C, et al. Single Nucleotide Polymorphisms at the Niemann-PickC1-Like1 Gene Locus Significantly Predict Cardiovascular Events in Coronary Patients With Type 2 Diabetes. Presented at: ACC 65th Scientific Sessions; April 1-4, 2016; Chicago, IL.
You must be a registered member of Endocrinology Advisor to post a comment.

Sign Up for Free e-Newsletters

CME Focus