
Despite several observational studies showing that lipoprotein(a), or Lp(a), is associated with myocardial infarction (MI)1, 2, only circumstantial evidence exists regarding the causal nature of this association. Observational epidemiological studies, even with a sound prospective design, can provide hints to disease pathogenesis when the effect size is modest but cannot provide definitive evidence for causal relationships. Much of the current understanding of the causal factors in cardiovascular disease, such as the role of LDL, has been confirmed by randomized clinical trials (RCT)3, 4. However, RCTs are not always feasible. In the case of Lp(a), the modest effect size and the lack of specific Lp(a) lowering therapy are major obstacles to obtaining causal evidence for its role in cardiovascular disease. In this issue of JAMA, Kamstrup and colleagues 5 provide insights using a “Mendelian randomization” approach and provide evidence for the causal role of Lp(a) in MI. This study elegantly demonstrates how Mendelian randomization can be used to improve the evidence for causality from observational studies and highlights the advantages and limitations of such an approach.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 189 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
