Animal models for preclinical research on multifactorial human conditions: The case of cardiovascular-kidney-metabolic syndrome

Cardiovascular-kidney-metabolic (CKM) syndrome is a complex, multisystem condition that remains challenging to study due to the lack of a standardized, comprehensive animal model. This study conducted a meta-analysis of 919 preclinical experimental protocols (1993-2024) to evaluate how well existing rodent models—ranging from genetic mutations to diet-induced interventions—replicate the metabolic, renal, and cardiovascular comorbidities characteristic of human CKM.

The researchers assessed the models' ability to mirror clinical features such as obesity, diabetes (hyperglycemia and HbA1c levels), hypertension, and renal impairment (glomerulosclerosis and albuminuria). They used sensitivity analysis and publication bias testing (following PRISMA protocols) to ensure the robustness of the data synthesis.

The meta-analysis revealed substantial heterogeneity across experimental approaches. While no model perfectly captured all facets of the disease, rodent models involving mutations in the leptin gene or receptor, specifically Lepob/ob, Leprdb mice, and Ob-ZSF1 or Zucker diabetic fatty (ZDF) rats, provided the most complete representation of metabolic features.

Renal performance indicators varied significantly across models. Ob-ZSF1 and Zucker diabetic fatty rats were identified as having the most pronounced multifactorial impact, displaying a combination of metabolic dysfunction and measurable renal impairment. The study also highlighted important associations in these models, such as how elevated blood pressure and hyperglycemia exacerbate renal markers like albuminuria. However, cardiac-specific data—such as left ventricular function—was notably scarce, appearing in fewer than 5% of the reviewed studies.

Developing effective treatments for CKM requires animal models that capture the complex, interdependent nature of diabetes, hypertension, and organ damage. This research suggests that current models are often limited by their focus on single systems or specific aspects of pathology, failing to replicate the systemic complexity of human CKM. By providing a quantitative ranking of how various models perform across these distinct criteria, this study offers a guide for researchers to choose better-suited models for specific research goals, ultimately increasing the translatability of preclinical findings to clinical trials.