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The Lp(a)HORIZON trial's full results confirm that pelacarsen, despite slashing lipoprotein(a) levels by nearly 78%, did not reduce major adverse cardiovascular events compared to placebo in patients with established heart disease. Presented at AHA 2026 and published in the NEJM, the neutral findings have shaken confidence in Lp(a) as a treatment target — but experts urge caution before abandoning the hypothesis entirely, pointing to ongoing trials with next-generation siRNA therapies.
The highly anticipated Lp(a)HORIZON trial has delivered a sobering verdict: pelacarsen (Novartis), an antisense oligonucleotide that dramatically lowers lipoprotein(a) levels, failed to reduce major adverse cardiovascular events (MACE) in patients with pre-existing heart disease. Full results, presented at the AHA 2026 Scientific Sessions and simultaneously published in the New England Journal of Medicine, showed a MACE rate of 12.3% with pelacarsen vs. 12.1% with placebo — essentially identical. Novartis has since announced it will discontinue pelacarsen's cardiovascular development program.
Despite the disappointment, leading cardiologists are urging the field not to abandon the Lp(a) hypothesis. Experts point out that the trial enrolled a well-optimized secondary prevention population with already-low LDL and blood pressure, potentially leaving little room to demonstrate additional benefit. Questions also remain about whether pelacarsen's ~78% Lp(a) reduction was sufficient, whether the right population was targeted, and whether the drug's tolerability issues may have offset any potential gains.
By the Numbers:
Why it matters: This is the first large-scale trial to directly test whether lowering Lp(a) reduces cardiovascular risk — and the answer, at least for pelacarsen in secondary prevention, is no. But with siRNA therapies achieving even greater Lp(a) reductions and trials underway in primary prevention and other populations, the Lp(a) story is far from over. For now, clinicians should continue measuring Lp(a) as a risk marker and optimizing conventional risk factors.
