deCODE MI™

Analyzes five SNPs in the CYP2C19 gene that affect response to the anti-platelet drug clopidogrel. This test identifies those who may need adjustment of their clopidogrel dose or who should be put on an alternative medicaiton to prevent recurrent adverse cardiovascular events.

Screening and prevention

How deCODE MI™ can help.

More Comprehensive Risk Assessment

Understanding a patient’s risk of cardiovascular disease is the prerequisite for effective prevention, including decisions and follow-through on life style modification and medication. deCODE MI™ detects genetic risk factors for heart attack that are independent of traditional risk factors, helping to provide a more complete picture of individual susceptibility as well as important information on risk of early-onset disease.

Integration with established risk modelling tools

The results of deCODE MI™ are presented as a numerical score of individual risk of heart attack compared to the population average. Because this risk is complementary to that conferred by traditional risk factors, deCODE MI™ results can be used directly to modify scores from the Framingham, Reynolds, or ARIC tools. This can impact the recommended prevention strategies and medication for a substantial proportion of patients.

Empowering physicians and patients

Preventive measures for MI are to a great extent dependent on successful changes in lifestyle. deCODE MI™ results can give physicians’ advice extra emphasis and impact, and provide their patients with additional incentive to follow through on that advice.

Clinically relevant risk for a significant proportion of patients.

deCODE MI™ returns results that range from 0.31- to 2.1-fold the general population risk of heart attack. About 5.5 % of people of European descent who take deCODE MI™ will receive a score of 1.5 or above, or ≥50% increased risk of MI compared to the population average. This is a greater increase in risk than that conferred by being in the top quintile of LDL cholesterol.

A large clinical utility study by Ballantyne et al using data from the ARIC cohort showed that adding the deCODE MI™ 9p21 risk variant to traditional risk factors in the ARIC cohort significantly increased the accuracy of MI risk prediction; 18 percent of patients in the intermediate and intermediate-high risk categories were reclassified into higher or lower risk categories, changing their LDL cholesterol targets⁽¹⁾. A study by Humphries et al analyzing data on 2742 men in the prospective NPHS trial in the UK showed that the 9p21 risk marker significantly increased the accuracy of MI risk prediction when added to the Framingham risk score (LR p = 0.01), with 22% of patients changing risk categories⁽²⁾. In study by Paynter et al it can be demonstrated from the published data that patients in the intermediate- and intermediate-high-risk categories (as determined by using either the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults [ATP III] risk score or Reynolds Risk Score) are reclassified by knowledge of variation at 9p21, at a rate of 12% to 14%^(3,4).

The highest risk result from deCODE MI™, which obtains for individuals who are homozygous (carry two copies) of the risk versions of all eight SNP markers, is 3.9-fold the average population risk. It is important to note that genotype combinations for the eight markers that convey such extreme risk are very rare. For example, genotype combinations that give risk grater than 3.0 are only found in one out of 240.000 individuals. Because such results are so rare, we believe that they should be used only with a great degree caution for modifying individual assessed risk. Accordingly, in the result reports a cut-off of 2.1-fold increase is used for modification of the patient’s lifetime risk. This is equivalent to a 90% lifetime risk, without considering other risk factors.

For East Asians, large-scale validation data is available for only the 9p21 marker (rs10757278) and a marker on chromosome 12 (rs3782886) that is unique to East Asians. Homozygosity for both risk alleles (about 3% of East Asians) is associated with about 1.95-fold the population average risk of for MI (a 95% increase). Approximately 23% of people of East Asian descent have between 1.4- and 1.95-fold the average population risk as a result of testing for these two markers. At present, the large-scale validation studies necessary to accurately interpret the impact of the markers in the test have been carried out only in populations of European and East Asian descent.

This content was last reviewed on March 16, 2011.