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Published on: April 19, 2013
Human genetics suggests differing causal pathways from HMGCR inhibition to coronary artery disease and type 2
Seongwon Hwang1, Ville Karhunen1, Ashish Patel1
1MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.
Insights
Statins impact coronary artery disease (CAD) and type 2 diabetes (T2D) risk through distinct pathways. Understanding these separate causal routes, involving LDL-C and BMI, may enable targeted interventions for cardiovascular and metabolic health.
Area of Science:
- Genetics
- Pharmacology
- Epidemiology
Background:
- Statins effectively lower low-density lipoprotein cholesterol (LDL-C) and reduce coronary artery disease (CAD) risk.
- However, statin use is associated with an increased risk of developing type 2 diabetes (T2D).
Purpose of the Study:
- To investigate the distinct causal pathways linking genetic variants in the HMGCR gene region to CAD and T2D.
- To determine if the risk factors for CAD and T2D influenced by statins are shared or independent.
Main Methods:
- Utilized colocalization and multivariable Mendelian randomization analyses focusing on genetic variants within the HMGCR gene region.
- Employed Bayesian model averaging to identify the most probable causal risk factors for T2D and CAD.
Main Results:
- LDL-C and body mass index (BMI) showed distinct genetic predictors, indicating separate causal pathways for CAD and T2D.
- Multivariable Mendelian randomization identified LDL-C and BMI as causal for CAD, and BMI as causal for T2D.
- Colocalization analyses confirmed distinct associations: LDL-C with CAD, and BMI with T2D.
Conclusions:
- Cardiovascular (CAD) and metabolic (T2D) effects of statins operate through different causal pathways.
- These distinct pathways suggest potential for separate targeted interventions to mitigate statin-associated risks and optimize drug targeting.
Background:
Statins lower low-density lipoprotein cholesterol (LDL-C) and reduce the risk of coronary artery disease (CAD). However, they also increase the risk of type 2 diabetes (T2D).
Methods:
We consider genetic variants in the region of the HMGCR gene, which encodes the target of statins, and their associations with downstream consequences of statins. We use various statistical methods to identify causal pathways influencing CAD and T2D, and investigate whether these are the same or different for the two diseases.
Results:
Colocalization analyses indicate that LDL-C and body mass index (BMI) have distinct genetic predictors in this gene region, suggesting that they do not lie on the same causal pathway. Multivariable Mendelian randomization analyses restricted to variants in the HMGCR gene region revealed LDL-C and BMI as causal risk factors for CAD, and BMI as a causal risk factor for T2D, but not LDL-C. A Bayesian model averaging method prioritized BMI as the most likely causal risk factor for T2D, and LDL-C as the second most likely causal risk factor for CAD (behind ubiquinone). Colocalization analyses provided consistent evidence of LDL-C colocalizing with CAD, and BMI colocalizing with T2D; evidence was inconsistent for colocalization of LDL-C with T2D, and BMI with CAD.
Conclusions:
Our analyses suggest cardiovascular and metabolic consequences of statin usage are on different causal pathways, and hence could be influenced separately by targeted interventions. More broadly, our analysis workflow offers potential insights to identify pathway-specific causal risk factors that could provide possible repositioning or refinement opportunities for existing drug targets.
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