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

By I. Kullo, H. Jouni, Erin Austin, Sherry‐Ann Brown, Teresa M Kruisselbrink, I. Isseh, Raad A. Haddad, Tariq S. Marroush, Khader Shameer, J. Olson and 5 more. 2016

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Background Whether knowledge of genetic risk for coronary heart disease (CHD) affects health-related outcomes is unknown. We investigated whether incorporating a genetic risk score (GRS) in CHD risk estimates lowers low-density lipoprotein cholesterol (LDL-C) levels. Methods and Results Participants (n=203, 45–65 years old, at intermediate risk for CHD, and not on statins) were randomized to receive their 10-year probability of CHD based either on a conventional risk score (CRS) or CRS + GRS (+GRS). Participants in the +GRS group were stratified as having high (+H-GRS) or average/low (+L-GRS) GRS. Risk was disclosed by a genetic counselor followed by shared decision-making regarding statin therapy with a physician. We compared the primary endpoint of LDL-C levels at 6 months and assessed whether any differences were due to changes in dietary fat intake, physical activity levels or statin use. Participants (mean age 59.4±5 years, 48% men, mean 10-year CHD risk 8.5±4.1%) were allocated to receive either CRS (n=100) or +GRS (n=103). At the end of the study period, the +GRS group had a lower LDL-C than the CRS group (96.5±32.7 vs. 105.9±33.3 mg/dL; P=0.04). +H-GRS participants had lower LDL-C levels (92.3±32.9 mg/dL) than CRS participants (P=0.02) but not +L-GRS participants (100.9±32.2 mg/dL; P=0.18). Statins were initiated more often in the +GRS group than in the CRS group (39% vs. 22%, P<0.01). No significant differences in dietary fat intake and physical activity levels were noted. Conclusions Disclosure of CHD risk estimates that incorporated genetic risk information led to lower LDL-C levels than disclosure of CHD risk based on conventional risk factors alone. Clinical Trial Registration Information ClinicalTrials.gov. Identifier: NCT01936675.

Subfields: Genetics, Surgery

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Citations in the corpus

Machine learning in cardiovascular medicine: are we there yet? (2018, background): “13 In addition to genomics, emerging molecular profiling technology including transcriptomics, proteomics, epigenomics, metabolomics and compiling longitudinal microbiome data could provide new insights into the pathophysiology of CVDs (see table 1 and figure 2).”
Identification of 64 Novel Genetic Loci Provides an Expanded View on the Genetic Architecture of Coronary Artery Disease (2017, background): “Recent data suggests that instead of operating in a deterministic fashion, high genetic risk is indeed modifiable by lifestyle,(27) pharmacotherapy,(28) and also by incorporation of genetic risk into shared decision-making sessions with patients.(29) In conclusion, our GWAS, meta-analyses, and bioin”
Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting (2017, background): “Furthermore, disclosure of genetic risk may motivate greater adherence with statin therapy.(37) Our analyses have potential limitations.”
The critical needs and challenges for genetic architecture studies in Africa (2018, background): “cost tests that can outpace the clinical status quo [74,75].”
Behavioral Impact of Return of Genetic Test Results for Complex Disease: Systematic Review and Meta-analysis (2018, unknown): “The present study comprehensively expands on this preliminary result and expands the finding of significant positive changes in risk carriers Table 2 Bias Evaluations Study Selection Detection Attrition Reporting Other Studies reporting unadjusted statistics Aspinwall et al. (2008) Low Unclear High ”