Development and Implementation of an Integrated Preclinical Atherosclerosis Database

Rachel R Xiang ¹, Yihua Wang ¹, Megan M Shuey ²

⁰Molecular Cardiology Research Institute, Tufts Medical Center, Boston, MA (R.R.X., Y.W., B.V.C., I.Z.J.).

Circulation. Genomic and Precision Medicine +

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April 2, 2024

View abstract on PubMed

Summary

Integrating preclinical data from mouse models of atherosclerosis can improve the translation of basic science discoveries to clinical care. This study created a database of atherosclerosis research to enable comprehensive analysis and accelerate disease research.

Area Of Science

Cardiovascular Research
Translational Medicine
Bioinformatics

Background

Preclinical animal models are crucial for understanding human disease mechanisms, yet translation to clinical practice remains limited.
Thousands of publications support causative inferences from animal studies, but a lack of integration hinders progress.
An integrated approach to preclinical data offers potential for improved translational success in medicine.

Purpose Of The Study

To develop a comprehensive database of preclinical atherosclerosis research using common mouse models.
To facilitate integrated analyses of experimental conditions, interventions, and outcomes from published studies.
To provide a resource for interrogating the global impact of atherosclerosis research and improving translational outcomes.

Main Methods

Extracted data from mouse models of atherosclerosis (ApoE-knockout and LDLR-knockout) published in key journals.
Collected predefined variables including animal sex, diet, intervention, and plaque pathologies (size, inflammation, lipid content).
Developed procedures for data standardization, intervention attribution, and transformation for transcriptomics software.

Main Results

Created a preclinical atherosclerosis database integrating hundreds of genes tested in vivo.
The database includes detailed information on experimental conditions and outcomes from published atherosclerosis research.
Standardized data extraction and transformation methods are provided for community use.

Conclusions

The database serves as a resource for interrogating specific data subsets related to plaque pathologies, cell types, or sex.
Provided methods and software can expand the dataset and be applied to other human diseases studied in preclinical models.
This integrated approach aims to enhance the translation of preclinical findings into clinical advancements.

Keywords:

atherosclerosis database mice, transgenic plaque, atherosclerotic translational research, biomedical