Unraveling the shared genetic architecture of metabolic bone diseases via genomic structural equation modeling and multi-omics integration
- 1Department of Orthopedics, Affiliated Rehabilitation Hospital of Nanchang University, Nanchang University, Nanchang, China
Abstract
Background: The shared genetic etiology underlying the comorbidity of skeletal degeneration and metabolic dysregulation remains poorly understood. This study aims to decipher the pleiotropic genetic architecture of multivariate metabolic bone diseases (mvMBDs) through an integrative summary-statistics framework. Methods: We applied Genomic Structural Equation Modeling (Genomic SEM) to integrate genome-wide association study (GWAS) summary statistics for six complex traits: osteoporosis (OP), chronic kidney disease (CKD), type 2 diabetes (T2D), alkaline phosphatase (ALP), high-density lipoprotein (HDL), and C-reactive protein (CRP). Subsequent analyses incorporated robust fine-mapping (SuSiE/FINEMAP), transcriptome-wide association studies (TWAS), and partitioned heritability assessments to identify putative functional loci and regulatory mechanisms. Results: Genomic SEM revealed significant genetic covariance among the six traits, successfully deriving a latent mvMBD construct. We identified 197 genomic risk loci, including 193 lead SNPs that did not achieve genome-wide significance in the six constituent univariate GWAS, predominantly localized in non-coding cis-regulatory elements (e.g., super-enhancers and intronic regions). Fine-mapping and TWAS prioritized critical pleiotropic genes (e.g., MACF1, CETP, SPP1, and HNF1A). Gene-set enrichment analyses identified enrichment for terms related to bone biology, lipid metabolism, and inflammation. Conclusion: Our findings robustly demonstrate that mvMBDs are not isolated clinical entities but rather interconnected systemic syndromes underpinned by glycolipid metabolic dysregulation and shared pleiotropic regulatory networks. This study establishes a novel theoretical paradigm for the genetic basis of metabolic bone diseases, offering promising functional targets for future precision medicine interventions.
Related
- Revisiting Inherited Metabolic Diseases (IMDs) Through the Lens of Selective Autophagy
- Efficient structural information integration into protein language models with implicit mixture-of-experts ProBEiT
- ARCANE: ‘A Reprogrammable Circuit Architecture for Non-model Engineering’ enables sophisticated metabolic control in Yarrowia lipolytica
- Shared Genetic and Regulatory Architecture of Congenital Heart Disease and Autism Spectrum Disorder Revealed by Cross-Tissue Multi-Omic Integration
- Extracellular Vesicle-Mediated Local and Systemic Communication in Metabolic Diseases
BibTeX
@article{yi2026unraveling,
title = {{Unraveling the shared genetic architecture of metabolic bone diseases via genomic structural equation modeling and multi-omics integration}},
author = {Kun Yi and Fan Wang and Feiping Hu and Wenlong Tang and Yang Liu and Bowen Gao and Sining Zhang and Lang Jiang and Jiaxin Ding and Daoping Lei and Junjie Yu and Siyuan Yu and Binghua Wu},
journal = {PLOS One},
year = {2026},
month = oct,
doi = {10.1371/journal.pone.0360386},
url = {https://doi.org/10.1371/journal.pone.0360386},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Unraveling the shared genetic architecture of metabolic bone diseases via genomic structural equation modeling and multi-omics integration
AU - Kun Yi
AU - Fan Wang
AU - Feiping Hu
AU - Wenlong Tang
AU - Yang Liu
AU - Bowen Gao
AU - Sining Zhang
AU - Lang Jiang
AU - Jiaxin Ding
AU - Daoping Lei
AU - Junjie Yu
AU - Siyuan Yu
AU - Binghua Wu
PY - 2026
DA - 2026/10/27
JO - PLOS One
DO - 10.1371/journal.pone.0360386
UR - https://doi.org/10.1371/journal.pone.0360386
AB - Background: The shared genetic etiology underlying the comorbidity of skeletal degeneration and metabolic dysregulation remains poorly understood. This study aims to decipher the pleiotropic genetic architecture of multivariate metabolic bone diseases (mvMBDs) through an integrative summary-statistics framework. Methods: We applied Genomic Structural Equation Modeling (Genomic SEM) to integrate genome-wide association study (GWAS) summary statistics for six complex traits: osteoporosis (OP), chronic kidney disease (CKD), type 2 diabetes (T2D), alkaline phosphatase (ALP), high-density lipoprotein (HDL), and C-reactive protein (CRP). Subsequent analyses incorporated robust fine-mapping (SuSiE/FINEMAP), transcriptome-wide association studies (TWAS), and partitioned heritability assessments to identify putative functional loci and regulatory mechanisms. Results: Genomic SEM revealed significant genetic covariance among the six traits, successfully deriving a latent mvMBD construct. We identified 197 genomic risk loci, including 193 lead SNPs that did not achieve genome-wide significance in the six constituent univariate GWAS, predominantly localized in non-coding cis-regulatory elements (e.g., super-enhancers and intronic regions). Fine-mapping and TWAS prioritized critical pleiotropic genes (e.g., MACF1, CETP, SPP1, and HNF1A). Gene-set enrichment analyses identified enrichment for terms related to bone biology, lipid metabolism, and inflammation. Conclusion: Our findings robustly demonstrate that mvMBDs are not isolated clinical entities but rather interconnected systemic syndromes underpinned by glycolipid metabolic dysregulation and shared pleiotropic regulatory networks. This study establishes a novel theoretical paradigm for the genetic basis of metabolic bone diseases, offering promising functional targets for future precision medicine interventions.
SN - 1932-6203
ER -