Optimization of statin regimens for atherosclerotic cardiovascular disease prevention using polygenic risk scores and real-world evidence (OSCARS)
Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of mortality worldwide and statin treatment remains a cornerstone of cholesterol management guidelines aimed at reducing ASCVD risk. While previous modifications of these guidelines have increased the number of statin-eligible patients, a lower threshold for statin eligibility has not been found to improve the number-needed-to-treat (NNT) for ASCVD prevention. A precision medicine approach that improves both the sensitivity and specificity of statin eligibility criteria in future guideline revisions (among individuals not currently considered candidates for statins) would be expected to beneficially reduce NNT. Emerging evidence from genetic substudies of statin randomized controlled trials (RCTs) demonstrates that coronary heart disease (CHD) polygenic risk scores independently modify statin relative risk reduction (independent of statin-induced atherogenic cholesterol lowering) in a manner that has the potential to improve the specificity and sensitivity of statin therapy selection. Furthermore, hypothesis-generating findings suggest that CHD polygenic risk scores may predict enhanced statin benefit from particular statin types and doses. However, the generalizability of these results is adversely impacted by lack of heterogeneity in the RCT study population demographics and statin regimens as well by limited length of patient follow-up and sample size. Further studies are necessary to better understand how polygenic risk scores modify statin benefit before this precision medicine tool can be considered for clinical implementation.
Our primary goal in this project is to translate prior proof-of-concept evidence into a clinically-relevant and actionable tool for use of statins in ASCVD prevention that has the potential to be incorporated into national guidelines. To accomplish this goal, we will leverage data from the Kaiser Permanente Research Bank (KPRB) and the Veterans Affairs Million Veteran Program (MVP), which are two of the largest electronic health record-linked biobanks in the United States. These prospective cohorts are ideal for developing and validating this tool because they are large (>400,000 participants each), ethnically diverse (~25% historically excluded groups), have long-term follow-up (>25 years), and contain real-world data (comprehensive electronic health records).
In Aim 1, we will assess the relationship between CHD polygenic risk scores and statin relative risk reduction for various ASCVD outcomes in diverse populations.
In Aim 2, we will determine the extent to which the association between CHD polygenic risk scores and statin-induced ASCVD risk reduction is related to statin type and dose.
In Aim 3, we will develop a precision medicine tool for statin-induced ASCVD relative risk reduction.
The aims will be carried out by an established multidisciplinary team of experts in clinical pharmacology, clinical lipidology, cardiovascular epidemiology, statistical genetics, and ethical, legal, and social implications (ELSI). Findings will use genetic background + traditional ASCVD risk factors to inform (1) the selection of statins n individuals not previously considered to be eligible as well as (2) the tailoring of dose and type for statin users.