Limitations of current animal models in atherosclerosis: an integrative multiomics perspective

Introduction

Recent years have brought significant advances in understanding the molecular basis of atherosclerotic cardiovascular diseases (ASCVD). With multiple untreated and untargeted pathological pathways, atherosclerosis requires a comprehensive treatment strategy. Some of these gaps are being addressed by the European COST Action AtheroNET (Network for implementing multiomic approaches in ASCVD prevention and research; https://atheronet.eu/). AtheroNET embraces the use of multiple omics technologies and datashare/integration across institutions and disciplines, through machine learning/artificial intelligence (ML/AI), aiming to identify new biomarkers and bring novel paradigms in prevention, diagnosis, and treatment of ASCVD (Figure 1).¹

Figure 1.

The role of international collaboration (COST Action AtheroNET, CA21153) in biomarker discovery and therapy development for atherosclerotic cardiovascular diseases (ASCVD)

Challenges in accurately modelling human disease

A major challenge in atherosclerosis research is absence of preclinical model that fully replicates complexity of human disease. The heterogeneity of available animal models underscores the importance of aligning their selection with a specific research question, rather than conforming to a “universal” model. AtheroNET has provided diverse perspectives through reviewing in vitro² and in vivo³ models. Through the knowledge exchange, our own research, and use of publicly available multiomic datasets in atherosclerosis, we now identified areas of agreement and disagreement. Existing research interest in this area invited us to offer views and well-grounded conclusions, paving the path towards future sustainable and reliable use of animal and cellular models of ASCVD.

Leveraging multiomics research in atherosclerosis

Multiomics approaches have significantly advanced ASCVD field by offering unbiased molecular insights that enable systems-level, multi-layered characterisation of plaque composition, cellular function, and disease pathobiology. Through holistic view, researchers can capture the complex, multi-layered biological processes that drive plaque formation and progression, which could not otherwise be explained fully using single-omic approaches. A comprehensive introduction into the various layers of omic data and their use for diagnostics and treatment of ASCVD is summarized in a recent review paper by AtheroNET investigators.⁴ Further, a complete list of widely used publicly available multiomics platforms is provided in Mitić et al.³

Data integration

A promising direction for the field is the integration of diverse datasets into a comprehensive resource, such as the emerging ‘Cardiovascular Disease Atlas’ (https://ngdc.cncb.ac.cn/cvd/). Inspired by the successful implementation of similar integrative platforms in oncology, with the Cancer Genome Atlas (TCGA) and tumour boards, CVD research could now adopt a similarly collaborative and interdisciplinary approach.⁵ Unlike cancer care, where early molecular profiling has become a norm and a standard, the CVD management heavily relies on the symptom-driven interventions. In response to these imminent challenges, AtheroNET is developing a database research tool—Cardio2share (manuscript in preparation)—designed to not only enable sharing of diverse multiomics datasets but to connect molecular profiles to assist with CVD care.

Sustainability and need for standardization for research in atherosclerosis

Atherosclerosis studies typically require prolonged housing of mice that is labour intensive and costly.⁶ The consistent reporting of animal usage requires compliance with the ARRIVE guidelines (Animals in Research: Reporting In Vivo Experiments). Although the adherence to the 3Rs (Replacement, Reduction, Refinement) has improved in recent years, the challenges remain in balancing scientific utility with welfare and resource expenditure.⁷ Refinements of existing animal models have enabled the more efficient generation of genetically challenging models, while standardisation of multiomics data integration could further enhance relevance by allowing cross-data comparisson, without increasing animal use. Alongside this, the development of in vitro systems using renewable human-derived tissues and organoids (aka 3Dmodels) has offered a complementary path to align with sustainability practices while advancing mechanistic insight.

Future perspectives and direction for atherosclerosis research

The future of ASCVD research is poised for some transformative breakthroughs. This is already driven by innovations in single-cell biology, multiomics, functional genomics, and collaborative data integration. Techniques like single-cell sequencing and spatial multiomics will remain critical in deciphering the complex molecular and cellular interplays that further affect regulatory networks in atherosclerosis. Mapping genetic risk loci to cell-type specific and functionally associated mechanisms will directly enable uncovering novel therapeutic targets and provide insights into disease pathogenesis. Moreover, identifying a dysregulated pathway or gene expression profiles linked to ASCVD pathogenesis has the potential to advance the field of RNA Therapeutics.⁸

Conclusion

Continued collaboration between international researchers will help bridge the gap between molecular and clinical research by facilitating the integration of diagnostic data with plaque omics data. These collaborations drive our understanding of the underlying molecular processes and help extract clinically relevant insights from diverse patient cohorts, ultimately improving patient stratification based on key biological parameters. International networks, like the COST Action AtheroNET, will play essential role in advancing immunomodulation profiling strategies,⁹ testing new therapeutic targets, and developing personalized treatment interventions. The integration of these datasets, supported by standardized analysis pipelines and robust ethical frameworks, will be essential for translating discoveries into clinical practice. Ultimately, these efforts should seek to link the diagnostic CT-image data with plaque cellular composition and patient’s clinical and genetic information.¹⁰ Together, these initiatives pave the way for a more comprehensive understanding of ASCVD and support the development of more effective, personalised therapies.

Declarations

Disclosure of Interest

T.M. is Associate Editor and editorial board member to Cellular and Molecular Life Sciences (CMLS). N.A. is the CEO and co-founder of the biotechnology company Biosfer Teslab. D.K. has nothing to declare. All others declare no other conflict of interest.

Funding

This article is based upon work from COST Action AtheroNET (CA21153), supported by COST (European Cooperation in Science and Technology). T.M. is supported by the Zhejiang University-University of Edinburgh Institute (ZJU-UoE Institute) and was supported by the British Heart Foundation (BHF) Research Excellence Award REA3 (RE/18/5/34216). D.K. is supported by the Hellenic Foundation for Research and Innovation (HFRI) Research Program ‘Funding Projects in Leading-Edge Sectors—RRFQ: Basic Research Financing’ (horizontal support for all sciences) (grant no. 15529) and MSCA Staff Exchanges Program CardioSCOPE (grant no 101086397).