Poster No:
681
Submission Type:
Abstract Submission
Authors:
Asma Aman1, Santiago Diaz Torres1, Stuart MacGregor1, Puya Gharahkhani1
Institutions:
1QIMR Berghofer Medical Research Institute, Brisbane, Queensland
First Author:
Asma Aman
QIMR Berghofer Medical Research Institute
Brisbane, Queensland
Co-Author(s):
Introduction:
Primary open-angle glaucoma (POAG) is a neurodegenerative eye disease characterised by retinal ganglion cell death often due to increase in intraocular pressure (IOP). The neurological aetiology of POAG is not comprehensively understood so far, and as a result, there is no current cure for the vision loss it causes. Observational studies have shown relationships between POAG and some visual pathway regions in the brain including optic chiasm (OC), lateral geniculate nucleus (LGN), primary (V1) and secondary visual cortex (V2 and V5). For instance, studies have demonstrated that visual cortex function and structure are affected in glaucoma patients (Nuzzi, 2018). Also, previous research has shown that the diameter and height of the optic chiasm are lower in glaucoma patients (Kashiwagi, 2004). There are no comprehensive studies to investigate the genetic overlap throughout the genome between POAG and visual brain regions, particularly in relation to their shared biological pathways. This study aims to investigate the shared genetic architecture between POAG and the volume of the aforementioned visual pathway regions to better understand the neurological biology of glaucoma.
Methods:
POAG summary statistics were obtained from a multi-trait genome-wide association study with 29,241 cases and 350,181 controls, all of European ancestry (Han, 2023). For the visual regions, we conducted genome-wide association studies (GWASs) for the volume of each region, using around 41,000 European ancestry participants from the UK biobank.
We estimated the genetic correlation between POAG and each region using the LD-score regression method. Also, we developed polygenic risk scores (PRSs) for the volume of each region to predict POAG status using the SBayesRC method. Logistic regression was used to analyse the prediction ability of the PRSs, where we adjusted for age and sex.
Furthermore, GWAS-pairwise method was performed to discover genomic regions with shared causal variants between POAG and each brain region with a posterior probability > 0.8. The summary-data-based Mendelian randomisation (SMR) method was then used to test the causality between gene expression in the shared regions and each phenotype. Blood expression quantitative loci (eQTL) data, which was used as a genetic instrument for gene expression, was obtained from eQTLGen Consortium with 31,684 participants (Võsa, 2021). Multiple testing was corrected for using Benjamini-Hochberg method by adjusting FDR < 0.05 for each phenotype. The HEIDI test was then used to distinguish between pleiotropy and linkage, where genes with HEIDI p-value more than 0.05 were considered pleiotropic genes. Afterwards, we extracted the overlapping genes between both POAG and the visual pathway regions.
Results:
We found a weak but significant genetic correlation between POAG and OC volume (rG= -0.094, p-value= 0.009), indicating a slight inverse genetic relationship. However, there was no other significant genetic correlation between POAG and the other visual brain regions (p-value > 0.05). Similarly, all PRSs showed no significant result, except for OC (OR= 0.96, p-value= 0.0003). The GWAS-pairwise identified 8 shared genomic regions with causal variants common to both POAG and OC. In addition, 6 regions were shared with V2, 5 regions with V1, and 1 region each with V5 and LGN. The SMR analysis revealed 3 overlapping genes between POAG and OC including MSRA gene, which encodes an antioxidant enzyme, ENSG00000269918 and ENSG00000255310 which both are long non-coding RNA genes. Also, the EEF1AKMT2 gene, which is involved in protein methylation, overlapped between POAG and V2.
Conclusions:
Our study findings revealed the shared genetic architecture between POAG and visual pathway regions. Further investigations are required to validate the specific role of these genes in POAG and visual pathways, and to determine whether they could serve as neuroprotective drug targets.
Genetics:
Genetic Association Studies 1
Genetics Other 2
Keywords:
Other - glaucoma; visual pathway regions; PRS; GWAS-pairwise; genetic correlation; SMR; eQTL
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
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Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Structural MRI
For human MRI, what field strength scanner do you use?
1T
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Provide references using APA citation style.
Han, X. (2023). Large-scale multitrait genome-wide association analyses identify hundreds of glaucoma risk loci. Nature Genetics, 55(7), 1116–1125.
Kashiwagi, K. (2004). Association of magnetic resonance imaging of anterior optic pathway with glaucomatous visual field damage and optic disc cupping. Journal of Glaucoma, 13(3), 189–195.
Nuzzi, R. (2018). Changes of Visual Pathway and Brain Connectivity in Glaucoma: A Systematic Review. Frontiers in Neuroscience, 12, 363.
Võsa, U. (2021). Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nature Genetics, 53(9), 1300–1310.
No