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Unraveling 'F' factor: towards a genetic-clinical framework for the musculoskeletal-heart crosstalk in metabolic

Yunqiao Zhou1, Jian Huang1, Xinyi Chen1

  • 1Orthopedics Section 1, Dongzhimen Hospital of Beijing University of Chinese Medicine, No. 5 Haiyuncang Hutong, Dongcheng District, Beijing, 100700, China.

Cardiovascular Diabetology
|June 2, 2026
PubMed

Insights

A new "F" factor links heart and bone aging, improving risk prediction for cardiometabolic multimorbidity. This discovery aids early detection and prevention of age-related diseases.

Area of Science:

  • Gerontology
  • Genetics
  • Cardiology

Background:

  • Cardiometabolic diseases and musculoskeletal degeneration often co-occur, posing challenges to healthy aging.
  • Shared biological mechanisms linking these conditions are not well understood.

Purpose of the Study:

  • To develop an integrative clinical-genetic framework to identify a common frailty factor ('F' factor).
  • To elucidate the 'F' factor's role in systemic vulnerability connecting cardiometabolic multimorbidity (CMM) and musculoskeletal aging.

Main Methods:

  • Utilized the China Health and Retirement Longitudinal Study (CHARLS) cohort.
  • Developed and validated Frailty-Integrated Indices for CMM risk prediction using machine learning.
  • Applied Genomic Structural Equation Modeling (Genomic-SEM) to model a shared latent genetic factor ('F' factor) integrating multiple traits.

Main Results:

  • Frailty-Integrated Indices significantly improved CMM risk prediction (AUC=0.727).
  • Identified a significant shared genetic factor ('F' factor) with novel risk loci, including APOE and SLC22A3.
  • Genes implicated in cellular senescence and cholesterol metabolism, with specific expression in endothelial cells.

Conclusions:

  • Converging evidence supports Musculoskeletal-Heart crosstalk in metabolic aging.
  • The 'F' factor is a genetic correlate of a transdiagnostic state linking genetic predisposition to metabolic dysregulation and functional decline.
  • This research aids multi-level characterization of multimorbidity liability for early risk detection and prevention.
Abstract

Keywords:
Cardiometabolic multimorbidityFrailty-integrated indicesGenomic structural equation modelingMachine learningMetabolic agingMultimorbidity geneticsMusculoskeletal-heart crosstalk

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