influences on embryonic heart and vertebral formation
Dr Duncan Sparrow, Victor Chang Cardiac Research Institute, Sydney
Fri 14th November
Leolin Price LT
UCL Institute of Child Health
30 Guilford Street, London WC1N 1EH
Can a genetic study anticipate the outcome of a randomized trial?
ICS researchers (Michael Holmes as first author and Prof. Aroon Hingorani, Prof. Philippa Talmud and Dr Juan Pablo Casas as senior authors) have recently published the findings from their study into elevated levels of secretory phospholipase A2 and its possible link to heart disease.
Drug discovery in cardiovascular disease is facing unprecedented challenges due to a high rate of failures of randomized clinical trails (RCTs) which carry important financial repercussions.
A recent example of an RCT that was stopped because it failed to show benefit of the drug on heart disease prevention was the VISTA-16 trial. In this case, the drug, varespladib, inhibited an enzyme (secretory phosholipase A2) that was thought to play an important role in atherosclerosis. Atherosclerosis is the process by which arteries become diseased, and over time (many years), this disease process can lead to a heart attack.
In the current study, available online in Journal of the American College of Cardiology, UCL researchers used a gene variant that has an effect on circulating levels of secretory phospholipase A2. By using a genetic technique called Mendelian randomization, they found that individuals that carried the gene variant resulting in elevated levels of secretory phospholipase A2, did not have an altered risk of heart disease. These findings indicated that elevated levels of secretory phospholipase A2 are unlikely to cause heart disease.
Importantly, these findings predicted the failure of the VISTA-16 RCT. Had the genetic findings been available previously, they might have influenced the decision to pursue secretory phospholipase A2 as a drug target.
Collectively, the findings of such studies suggest that Mendelian randomization “trials” should be considered as an important tool available for drug development. Ultimately, this should help identify which drug targets should be prioritized for RCTs, and help provide new therapies for disease prevention.