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Published on: October 12, 2017
Lipoprotein(a) and cardiovascular disease: prediction, attributable risk fraction, and estimating benefits from novel
Paul Welsh1, Claire Welsh2, Carlos A Celis-Morales1,3
1Institute of Cardiovascular and Medical Sciences, University of Glasgow, BHF Glasgow Cardiovascular Research Centre, 126 University Place, Glasgow G12 8TA, UK.
Insights
Elevated lipoprotein (a) [Lp(a)] significantly increases cardiovascular disease (CVD) risk. Measuring Lp(a) can aid in predicting CVD events and identifying individuals who may benefit from Lp(a)-lowering therapies.
Area of Science:
- Cardiovascular Medicine
- Genetics
- Epidemiology
Background:
- Lipoprotein (a) [Lp(a)] is an independent risk factor for cardiovascular disease (CVD).
- Understanding the population attributable fraction (PAF) of elevated Lp(a) is crucial for public health strategies.
- The utility of Lp(a) measurement in refining CVD risk prediction models requires further investigation.
Purpose of the Study:
- To determine the population attributable fraction (PAF) associated with elevated Lp(a) levels.
- To evaluate the effectiveness of incorporating Lp(a) measurements into existing CVD risk prediction models.
- To assess the potential impact of Lp(a)-lowering therapies on CVD risk.
Main Methods:
- Analysis of UK Biobank data from 413,734 participants.
- Cox proportional hazards models were used to assess associations between Lp(a) and various CVD outcomes.
- C-index was calculated to evaluate the improvement in CVD risk prediction models with Lp(a) inclusion.
Main Results:
- A 1 SD increment in log Lp(a) was associated with a 12% increased hazard of fatal/non-fatal CVD after adjusting for classical risk factors.
- Lp(a) levels >100 nmol/L and >175 nmol/L were associated with PAFs of 5.8% and 3.0% for CVD, respectively.
- Adding Lp(a) to risk models improved the C-index by +0.0017 in primary prevention, suggesting enhanced predictive accuracy.
Conclusions:
- Population screening for elevated Lp(a) can identify individuals at higher CVD risk.
- Measurement of Lp(a) can improve cardiovascular risk prediction, particularly in primary prevention.
- Targeted use of Lp(a)-lowering drugs, if proven effective, could significantly reduce CVD events in individuals with markedly elevated Lp(a).
Aims:
To investigate the population attributable fraction due to elevated lipoprotein (a) (Lp(a)) and the utility of measuring Lp(a) in cardiovascular disease (CVD) risk prediction.
Methods And Results:
In 413 734 participants from UK Biobank, associations of serum Lp(a) with composite fatal/non-fatal CVD (n = 10 066 events), fatal CVD (n = 3247), coronary heart disease (CHD; n = 18 292), peripheral vascular disease (PVD; n = 2716), and aortic stenosis (n = 901) were compared using Cox models. Median Lp(a) was 19.7 nmol/L (interquartile interval 7.6-75.3 nmol/L). About 20.8% had Lp(a) values >100 nmol/L; 9.2% had values >175 nmol/L. After adjustment for classical risk factors, 1 SD increment in log Lp(a) was associated with a hazard ratio for fatal/non-fatal CVD of 1.12 [95% confidence interval (CI) 1.10-1.15]. Similar associations were observed with fatal CVD, CHD, PVD, and aortic stenosis. Adding Lp(a) to a prediction model containing traditional CVD risk factors in a primary prevention group improved the C-index by +0.0017 (95% CI 0.0008-0.0026). In the whole cohort, Lp(a) above 100 nmol/L was associated with a population attributable fraction (PAF) of 5.8% (95% CI 4.9-6.7%), and for Lp(a) above 175 nmol/L the PAF was 3.0% (2.4-3.6%). Assuming causality and an achieved Lp(a) reduction of 80%, an ongoing trial to lower Lp(a) in patients with CVD and Lp(a) above 175 nmol/L may reduce CVD risk by 20.0% and CHD by 24.4%. Similar benefits were also modelled in the whole cohort, regardless of baseline CVD.
Conclusion:
Population screening for elevated Lp(a) may help to predict CVD and target Lp(a) lowering drugs, if such drugs prove efficacious, to those with markedly elevated levels.
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