Use of genetic risk information improves LDL-C levels


Incorporating a Genetic Risk Score into Coronary Heart Disease Risk Estimates: Effect on LDL Cholesterol Levels (the MIGENES Clinical Trial)

Literature - Kullo IJ, et al. Circulation 2016


Kullo IJ, Jouni H, Austin EE, et al.
Circulation 2016;133:1181-1188

Background

The interest about the use of genetic testing for disease risk assessment is growing in parallel with the availability of these genetic tests [1]. There are data associating certain multiple loci with CHD, independently of traditional risk factors [2,3], presenting the potential of improving the accuracy of CHD risk assessment. Moreover, a genetic risk score (GRS) based on multiple CHD susceptibility single nucleotide polymorphisms (SNPs) has been studied, and was found to be associated with higher rates of CHD events [4-8]. However, it is not known whether knowledge of genetic risk for CHD affects health-related outcomes.
In this study, it was evaluated whether disclosing a GRS for CHD leads to lowering of LDL-C levels. This was done by incorporating the GRS into the CHD risk estimates in combination with a conventional risk score (CRS), in 203 participants at intermediate CHD risk who were not treated with statins at the beginning of the study. This genetically informed risk score (+GRS) was compared with the CRS alone, and after 6 months it was assessed whether participants with a higher GRS (+H-GRS) had lower LDL-C levels compared with those with average or low GRS (+L-GRS).

Main results

LDL-C: At the end of the study period
  • the +GRS group had lower LDL-C levels compared with the CRS group – the difference was  9.4 mg/dL (96.5±32.7 vs.  105.9±33.3 mg/dL; P=0.04)
  • the +H-GRS group had lower LDL-C levels compared with CRS participants (difference: 13.6 mg/dL; 92.3±32.9 mg/dL; P=0.02)
  • the +H-GRS group had also lower LDL-C levels  compared with +L-GRS participants (difference: 8.6 mg/dL; 100.9±32.2 mg/dL; P=0.18)
When the values at 6 months after CHD disclosure were compared to baseline values, the mean LDL-C change was -13.6±31.3 mg/dL in the CRS group vs. -23.3±33.6 mg/dL in the +GRS group (P=0.03)

Statins:
  • statins were initiated more often in the +GRS group than in the CRS group (39% vs. 22%, P<0.01)
  • a higher proportion of +H-GRS participants (49.1%) were on statins than CRS (21.9%, P<0.01) and +L-GRS (28.6%, P=0.03) participants
  • after adjustment for statin initiation, the group randomization was not significantly associated with the end of study LDL-C levels (P=0.74)

No significant differences in dietary fat intake and physical activity levels were observed.

Conclusion

Genetic risk information for CHD can be incorporated into the risk assessment process. Individuals who received a GRS in addition to a conventional risk estimate for CHD had lower LDL-C levels 6 months later compared with participants who received only a conventional risk score. Shared decision making after CHD risk disclosure led to a greater proportion of patients who received CHD genetic risk being initiated on a statin medication. The lowering of LDL-C was greatest in individuals with a high GRS for CHD compared with participants who did not receive GRS. The disclosure of a GRS did not lead to significant changes in dietary fat intake, physical activity levels, or anxiety.

Editorial comment [9]

In their editorial, Natarajan and O’Donnell state that the study by Kullo et al is useful to understand how a CHD genetic risk score can contribute to lipid lowering.  ‘Kullo et al are to be commended for an ambitious design and meticulous training program for use of genetic information by implementation of GRS based algorithm within the real world context of a health system with an electronic health record (EHR). The conceptualization of genetic risk by both providers and patients can be highly varied, and Kullo et al provide initial insights about applying common, complex genetics in the clinic. Kullo et al have provided an important initial step demonstrating that trials integrating genomics-based decision-making for the prevention and treatment of CHD and other forms of CVD can be successfully conducted. A careful review of this important trial warrants careful interpretation of its results and of the implications for future precision medicine trials.’

Find this article online at http://circ.ahajournals.org/content/133/12/1181.abstract

References

1. Manolio TA. Bringing genome-wide association findings into clinical use. Nat Rev Genet. 2013;14:549-558
2. The Coronary Artery Disease (C4D) Genetics Consortium. A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease. Nat Genet. 2011;43:339-344
3. Deloukas P, Kanoni S, Willenborg C, et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet. 2013;45:25-33
4. Ganna A, Magnusson PK, Pedersen NL, et al. Multilocus genetic risk scores for coronary heart disease prediction. Arterioscler Thromb Vasc Biol. 2013;33:2267-2272
5. Tikkanen E, Havulinna AS, Palotie A, et al. Genetic risk prediction and a 2-stage risk screening strategy for coronary heart disease. Arterioscler Thromb Vasc Biol.2013;33:2261-2266
6. Mega JL, Stitziel NO, Smith JG, et al. Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials. Lancet. 2015;385:2264-2271
7. Morrison AC, Bare LA, Chambless LE, et al. Prediction of coronary heart disease risk using a genetic risk score: The Atherosclerosis Risk in Communities Study. Am J Epidemiol. 2007;166:28-35
8. Ripatti S, Tikkanen E, Orho-Melander M, et al. A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses. Lancet. 2010;376:1393-1400
9. Natarajan P, O’Donnell CJ. Reducing Cardiovascular Risk Using Genomic Information in the Era of Precision Medicine. Circulation 2016;133:1155-1159

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