Genomic prediction of coronary heart disease
Authors' conclusion
A GRS based on a large number of SNPs improves CHD risk prediction and encodes different trajectories of lifetime risk not captured by traditional clinical risk scores.
Study context
- Population
- Prospective population cohorts (FINRISK, Framingham Heart Study)
- Participants
- 12,676 vs 3,406
- Comparison
- GRS of 49 310 SNPs, alone and added to Framingham Risk Score (FRS) or ACC/AHA13 scores
- FINRISKn = 12,676
- FHSn = 3,406
- Outcome
- Incident CHD
Methodological detailsgenomic risk score development and external validation in prospective cohorts, 5 prospective population cohorts
- Genomic risk score development and external validation in prospective cohorts
- 5 prospective population cohorts
Performance
As reported in the abstract
Incident CHD, per SD of GRS
GRSHazard ratio (95% CI)
FINRISK, per S.D. of GRS
1.74(1.61–1.86)
Framingham
1.28(1.18–1.38)
Each row per its own increment, as printed
Further findings
10-year risk prediction, GRS added to FRS or ACC/AHA13
- Meta-analysis C-index improvement
- +1.5-1.6%, P < 0.001
- Meta-analysis C-index improvement, age ≥60 years
- +4.6-5.1%, P < 0.001
Lifetime absolute risk trajectories
- Men in top 20% of GRS reached 10% cumulative coronary heart disease (CHD) risk earlier than bottom 20%
- 12-18 y
- High genomic risk partially compensated by low SBP, low cholesterol and non-smoking
Original publication
Genomic prediction of coronary heart disease. Eur Heart J. Published 21 September 2016. doi:10.
Summarised from the published abstract; every number is checked against it