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Genomic structural equation modeling elucidates the genetic mechanisms underlying allostatic load
Songhao Chai1, Wenjun Jin2, Zhenghao Cui2
1The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450001, China.
Comprehensive Psychoneuroendocrinology
|July 6, 2026
Summary
This study reveals the shared genetic basis of allostatic load (AL), a measure of cumulative stress burden. Genetic factors influencing cardiovascular, inflammatory, and metabolic traits converge on key regulatory pathways.
Area of Science:
- Genetics
- Systems Biology
- Metabolic Disease
Background:
- Allostatic load (AL) reflects cumulative physiological stress across multiple systems.
- AL is linked to cardiometabolic and inflammatory diseases, but its genetic basis is unclear.
Purpose of the Study:
- To characterize the shared genetic architecture of allostatic load.
- To identify genetic factors contributing to the cardiovascular, inflammatory, and metabolic components of AL.
Main Methods:
- Genomic Structural Equation Modeling (Genomic SEM) integrated GWAS data for five AL-related phenotypes.
- A common-factor model derived a latent genetic factor for AL.
- Downstream analyses included functional annotation, fine-mapping, TWAS, and pathway enrichment.
Main Results:
- A shared genetic architecture for AL was supported by a well-fitting common-factor model.
- AL-associated variants were enriched in regulatory regions, implicating metabolic, neuroendocrine, and immune pathways.
- Key genes like HNF4A, MLXIPL, BDNF, and SH2B1 were prioritized, with enrichment in neuronal tissues.
Conclusions:
- This study elucidates the polygenic architecture of an AL-related latent factor.
- Genetic liability for AL converges on metabolic, immune, neuroendocrine, and neural pathways.
- Findings offer a systems-level view of physiological burden and disease vulnerability.
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