# Characterization of response to lipid-modifying regimens for atherosclerotic cardiovascular disease using electronic health records

> **NIH NIH K01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $177,498

## Abstract

PROJECT SUMMARY/ABSTRACT
Recent pharmacological advancements have reduced the burden of atherosclerotic cardiovascular disease
(ASCVD), the leading cause of mortality in the United States, but more work is necessary to further improve
patient outcomes. In particular, we do not thoroughly understand how individual patients respond to lipid
lowering therapies over time including the demographic, clinical and genetic variables which modify response.
Data from randomized controlled trials (RCTs) have largely shaped the evidence base for the clinical
management of lipid-modifying therapeutic regimens, but answer narrow questions in participants who may not
be representative of the broader population at risk for ASCVD. Thus, we cannot rely on RCTs to comprehensively
guide pharmaceutical care. Electronic health records (EHRs) are a valuable and efficient resource for evaluating
lipid-modifying therapies. Results from EHRs can complement RCT findings to provide more comprehensive
treatment recommendations. The overall objective of this proposal is to advance our understanding of how
patients respond to lipid-modifying agents for the prevention of ASCVD. We anticipate that novel markers can
identify responders, non-responders, and adverse-effect responders to different lipid-modifying regimens. We
will use EHRs from Kaiser Permanente Northern California (KPNC) to characterize therapy response. Members
of KPNC (~3.5 million members) represent a broad and diverse background of patients with ASCVD or at risk
for ASCVD. In addition, KPNC EHRs represent health records from an integrated healthcare delivery system
with an exceptionally long period of follow-up (1996-present), allowing for the application of innovative
methodologies to evaluate therapy response. In Aim 1, Dr. Akinyemi Oni-Orisan (Principal Investigator) will
model longitudinal non-HDL-C levels for the development of a lipid-modifying drug dosing algorithm using non-
linear mixed effects modeling. In Aim 2, Dr. Oni-Orisan will characterize the efficacy and safety of lipid-
modifying regimens for ASCVD using Cox regression. In Aim 3, Dr. Oni-Orisan will identify genetic predictors
of statin response using genome wide association studies. Findings from this proposal will (1) identify predictors
of response to lipid-modifying drug regimens, (2) uncover key biological pathways important to lipid-modifying
drug response, and (3) aid clinicians in providing individualized care that will reduce the public health burden
of ASCVD. Dr. Oni-Orisan will be mentored by a team of experienced researchers with expertise in mathematical
modeling, biostatistics, epidemiology, genomics, and lipidology. The University of California, San Francisco is
one of the leading biomedical research centers in the world. Dr. Oni-Orisan will take advantage of the rich
resources within this research environment to complete the proposal. Overall, the research, training, and
institutional environment described in this proposal will...

## Key facts

- **NIH application ID:** 10450093
- **Project number:** 5K01HL143109-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Akinyemi Oni-Orisan
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $177,498
- **Award type:** 5
- **Project period:** 2018-07-15 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10450093

## Citation

> US National Institutes of Health, RePORTER application 10450093, Characterization of response to lipid-modifying regimens for atherosclerotic cardiovascular disease using electronic health records (5K01HL143109-05). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10450093. Licensed CC0.

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