The accuracy of type 2 diabetes risk assessment in the general population could be improved with the implementation of genetic testing, according to research presented at the 51st European Association for the Study of Diabetes Annual Meeting.
“Large-scale genome-wide association studies (GWAS) have revealed more than 80 genic loci associated with prevalent type 2 diabetes, improving the understanding of molecular pathways leading to the disease,” the researchers wrote. “However, practical usefulness of such results in [type 2 diabetes] prevention is still heavily disputed.”
Krista Fischer, PhD, of the Estonian Genome Center at the University of Tartu in Estonia, and colleagues evaluated data from the Estonian Biobank cohort on 10,273 individuals to determine the relationship between genetic risk score for type 2 diabetes with both prevalent and incident type 2 diabetes and cardiovascular mortality. Follow-up was conducted for a median 5.5 years.
Overall, there were 1,181 cases of prevalent and 386 incident type 2 diabetes cases.
Compared with the whole cohort, the odds for type 2 diabetes prevalence in the highest genetic risk score quintile were 2.2 times higher. Similarly, the odds for type 2 diabetes prevalence in participants in the highest genetic risk score quintile were 3.66 times higher compared with participants in the lowest genetic risk score quintile.
There was a 1.78 times higher estimated hazard for developing type 2 diabetes among participants in the highest genetic risk score quintile compared with the whole cohort and 2.72 times higher estimated hazard compared with participants in the lowest genetic risk score quintile. A significantly higher risk for CV mortality was found among participants in the highest genetic risk score quintile for type 2 diabetes (adjusted HR = 1.25; 95% CI, 1.06-1.48).
“Our results indicate that implementation of genetic testing in routine risk assessment could greatly improve the accuracy of [type 2 diabetes] risk assessment in [the] general population,” the researchers wrote.
Fischer K, et al. Abstract #9. Presented at: 51st EASD Annual Meeting; Sept. 14-18, 2015; Stockholm.
The researchers report no relevant financial disclosures.