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Original Article | Open Access

Unraveling the Shared Genetic Architecture and Molecular Mechanisms Linking Cardiovascular Traits and Glaucoma: A Comprehensive Cross‐Trait Analysis

Junfei Huang1, Zejun Chen1,2, Mengqing Lin3, Bingyu Xu1, Qiang Liu1, Zhengran Li1,2, Jianping Gao4( ), Guoguo Yi5,6 ( ), Min Fu2( )
The Second Clinical School, Southern Medical University, Guangzhou, China
Department of Ophthalmology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
The First Clinical School, Southern Medical University, Guangzhou, China
Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, China
Department of Ophthalmology, The Sixth Affiliated Hospital, Sun Yat‐sen University, Guangzhou, China
Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat‐sen University, Guangzhou, China

Junfei Huang, Zejun Chen and Mengqing Lin contributed equally to this work.

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Abstract

Background

Recent data have indicated a high comorbidity link between cardiovascular characteristics and the risk of glaucoma (Gla), demonstrating a strong comorbidity relationship that warrants investigation into their shared molecular mechanisms and genetic makeup. This study aims to identify shared genetic loci and molecular mechanisms linking cardiovascular traits to glaucoma.

Methods

The genetic overlap between Gla and cardiovascular diseases was examined using genome‐wide association study datasets. Analysis across multiple traits revealed common genomic regions and overlapping gene associations. Pathway analysis via Multi‐marker Analysis of Genomic Annotation and expression quantitative trait loci validation explored functional associations. Single nucleotide polymorphism heritability enrichment was evaluated through linkage disequilibrium.

Results

We detected notable genomic links between eight cardiovascular traits and Gla. The pleiotropic analysis under composite null hypothesis approach revealed 9948 genome‐wide significant loci (p < 0.001), among which 71 showed strong colocalization evidence. Cross‐validation through functional mapping and annotation, Multi‐marker Analysis of Genomic Annotation, and Summary‐based Mendelian randomization analyses identified 24 pleiotropic genes, including six robust candidates (BCAS3, BICC1, FAM213A, ITGB5, NUP160, and TNS1).

Conclusions

This study reveals key genetic connections between cardiovascular traits and Gla, identifying pleiotropic loci and six validated genes as potential targets for early detection and treatment. These findings lay the groundwork for further investigation into the systemic‐ocular interplay linking Gla with cardiovascular disease.

Graphical Abstract

This study investigates the shared genetic architecture between eight cardiovascular traits and glaucoma using comprehensive cross‐trait analysis. We identified 9948 pleiotropic loci, 71 colocalized signals, and 24 shared genes, with BCAS3, BICC1, FAM213A, ITGB5, NUP160, and TNS1 emerging as robust cross‐trait candidates. These findings reveal key molecular mechanisms linking cardiovascular diseases and glaucoma, providing potential targets for early intervention and therapeutic development. FUMA, Functional Mapping and Annotation; GWAS, genome‐wide association study; HDL, high‐definition likelihood; HEIDI, Heterogeneity in Dependent Instruments; LDSC, linkage disequilibrium score regression; MAGMA, multi‐marker analysis of genomic annotation; PLACO, Pleiotropic Analysis under Composite Null Hypothesis; SMR, Summary‐data‐based Mendelian Randomization.

Keywords

cardiovascular phenotypegenetic overlapglaucomapleiotropy analysis

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Medicine Advances
Volume 4 Issue 2,
June 2026
Pages 222-234
DOI: 10.1002/med4.70072

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Cite this article:
Huang J, Chen Z, Lin M, et al. Unraveling the Shared Genetic Architecture and Molecular Mechanisms Linking Cardiovascular Traits and Glaucoma: A Comprehensive Cross‐Trait Analysis. Medicine Advances, 2026, 4(2): 222-234. https://doi.org/10.1002/med4.70072

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Received: 17 July 2025
Revised: 25 September 2025
Accepted: 01 December 2025
Published: 23 June 2026
© 2026 The Author(s). Tsinghua University Press.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.