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).
Abstract

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