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Multidisciplinary Approach to Obesity Management: A Case Report
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Beyond BMI: Rethinking Obesity Metrics and Cardiovascular Risk in the Era of Precision Medicine
Maria-Daniela Tanasescu1, Andrei-Mihnea Rosu2, Alexandru Minca1
1Department of Semiology-Emergency University Hospital, Carol Davila University of Medicine and Pharmacy, 022328 Bucharest, Romania.
Diagnostics (Basel, Switzerland)
|December 11, 2025
Summary
Body mass index (BMI) is limited for classifying obesity and cardiovascular risk. New precision medicine approaches using fat distribution and multi-omic data offer better risk prediction and personalized treatment strategies.
Area of Science:
- Cardiology
- Metabolic Health
- Precision Medicine
Background:
- Obesity is a major cardiovascular disease risk factor.
- Body mass index (BMI) lacks precision in assessing individual cardiometabolic risk due to limitations in capturing fat distribution and metabolic health.
- Current obesity classification fails to account for individual variability.
Purpose of the Study:
- To review the limitations of BMI in obesity classification and cardiovascular risk assessment.
- To explore emerging precision medicine strategies for redefining obesity.
- To highlight alternative metrics for improved cardiovascular risk stratification.
Main Methods:
- Narrative review of 35 articles (2018-2025).
- Analysis of advances in imaging, metabolomics, and genomic profiling.
- Synthesis of data on metabolically healthy vs. unhealthy phenotypes.
Main Results:
- Alternative metrics like visceral adipose tissue (VAT), epicardial adipose tissue (EAT), and waist-to-hip ratio (WHR) offer superior cardiovascular outcome prediction.
- Metabolomic and genomic profiling enable multi-omic phenotyping for enhanced risk assessment.
- Epicardial adipose tissue (EAT) plays a significant role in heart failure and arrhythmias.
- Glucagon-like peptide-1 (GLP-1) receptor agonists show cardioprotective effects.
Conclusions:
- Redefining obesity through biologically informed, phenotype-based models is crucial for managing cardiometabolic disease.
- Precision medicine approaches promise improved risk stratification, earlier detection, and individualized therapies.
- Overcoming implementation barriers like cost and guideline integration is necessary for clinical adoption.
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