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A Phenome-Wide Comparative Analysis of Individualized Network Heterogeneity Across Treatment-Response Subphenotypes

Shuang Guan1, Yinli Shi1, Sicun Wang1

  • 1Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.

Biology
|June 11, 2026
PubMed

Insights

This study reveals how individual patient differences affect treatment outcomes for coronary heart disease using a novel network analysis. It identifies specific gene patterns linked to treatment response, enabling personalized cardiovascular medicine.

Area of Science:

  • Genomics
  • Systems Biology
  • Precision Medicine

Background:

  • Coronary heart disease (CHD) exhibits significant heterogeneity in treatment effects (HTE).
  • Understanding the molecular basis of HTE is crucial for personalized cardiovascular interventions.
  • Danhong injection (DHI) is a treatment for CHD with variable patient responses.

Purpose of the Study:

  • To elucidate the molecular mechanisms underlying HTE in CHD patients treated with DHI.
  • To develop a novel framework for analyzing individualized treatment effects.
  • To identify patient-specific network architectures associated with treatment efficacy.

Main Methods:

  • Integrated clinical phenotyping and transcriptomic data from CHD patients.
  • Employed an individualized network analysis framework (Pheno-NM).
  • Identified efficacy-based subgroups and analyzed gene network properties.

Main Results:

  • Identified three efficacy-based subgroups, with the best-responding subgroup (D(+)S(+)) showing a complex gene network.
  • The key hub gene ORM1 in the D(+)S(+) subgroup is linked to platelet activation.
  • Patient-specific symptom improvement correlated with unique functional module connectivity and gene expression (e.g., HSBP1L1, KCNG2).
  • Six core network topological parameters significantly correlated with treatment efficacy and differed between subgroups (p < 0.05).
  • Significant differential gene expression observed for genes including IQCD and MTFR1.

Conclusions:

  • Established a novel joint phenotype-genetic network modeling paradigm for HTE.
  • Provided a molecular framework for understanding HTE in cardiovascular interventions.
  • Demonstrated the potential for personalized cardiovascular treatments by revealing patient-specific network architectures.

Keywords:
group-levelheterogeneity of treatment effectindividual-levelindividualized networknetwork analysis

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