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Updated: Aug 5, 2026

Multidisciplinary Approach to Obesity Management: A Case Report
05:10

Multidisciplinary Approach to Obesity Management: A Case Report

Published on: May 30, 2025

Integrative Multi-Omics Profiling of Dynamic Body Mass Index-Systolic Blood Pressure Trajectories in Obesity for

Ya-Jie Zhai1, Qun-Wei Ma1, Xing-Jian Zhang1

  • 1Department of Endocrinology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China.

Biomedicines
|July 28, 2026
PubMed

Insights

Obesity and blood pressure trajectories significantly impact heart failure (HF) risk. Identifying distinct patterns in body mass index (BMI) and systolic blood pressure (SBP) can improve HF risk prediction.

Area of Science:

  • Cardiology
  • Metabolic Health
  • Genetics

Background:

  • Obesity is a significant risk factor for heart failure (HF).
  • The interplay between dynamic changes in body mass index (BMI) and systolic blood pressure (SBP) and HF risk in obese individuals requires further clarification.
  • Understanding these dynamics is crucial for advancing precision medicine in HF prevention.

Purpose of the Study:

  • To identify distinct joint longitudinal trajectories of BMI and SBP in individuals with obesity.
  • To evaluate the association between these identified trajectories and the risk of overall HF and its subtypes.
  • To explore potential underlying genetic and proteomic mechanisms contributing to differential HF risk.

Main Methods:

  • Utilized group-based multi-trajectory modeling on 14,469 UK Biobank participants with BMI ≥ 30.
  • Applied inverse probability of treatment weighting to assess associations between trajectory groups and HF outcomes.
  • Investigated genetic susceptibility using polygenic risk scores (PRS) and explored plasma proteomic characteristics.

Main Results:

  • Identified four distinct BMI-SBP trajectory patterns: MOMH, SOHN, MOHN, and MOMSH.
  • The SOHN trajectory (severe obesity with high-normal BP progression) showed the highest overall HF risk (HR=3.76).
  • Specific trajectories were linked to increased risk for HF with preserved ejection fraction (HFpEF) and differential genetic/proteomic profiles.

Conclusions:

  • Dynamic trajectory-based phenotyping provides a nuanced understanding of obesity-BP patterns and their association with HF risk.
  • This approach offers a more informative framework for HF risk assessment compared to static indicators.
  • Identified subtypes exhibit distinct nutritional, metabolic, and genetic profiles, paving the way for personalized HF prevention strategies.

Keywords:
group-based multi-trajectory modelingheart failureplasma proteomicspolygenetic risk scoreprognosisrisk stratification

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