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Updated: May 6, 2026
Immunohistochemical Detection of 5-Methylcytosine and 5-Hydroxymethylcytosine in Developing and Postmitotic Mouse Retina
Published on: August 29, 2018
Integration of multi-omics data reveals dysregulated RNA methylation in retinal pigment epithelium drives age-related
Ya-Jun Gong1, Zhi-Lin Zou1, Kai-Rui Qiu1
1State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University; Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science; Guangdong Basic Research Center of Excellence for Major Blinding Eye Diseases Prevention and Treatment, Guangzhou 510060, Guangdong Province, China.
Aim:
To investigate the role of RNA methylation in retinal pigment epithelial (RPE) cells in age-related macular degeneration (AMD).
Methods:
RNA methylation-related gene expression profiles of AMD patient and normal control retinal pigment epithelium were evaluated by single-cell transcriptome from 34 samples (11 from normal donors and 23 from AMD patients). The causal relationship between RNA methylation dysfunction and AMD was analyzed by summary-data-based Mendelian randomization (SMR) using AMD GWAS data and multi-omics quantitative trait loci (QTL), including expression QTLs (eQTLs), protein QTLs (pQTLs), splicing QTLs (sQTLs), and m6A-QTLs (mQTLs). Additionally, machine learning models were applied to validate the causal association between RNA methylation dysfunction and AMD using Bulk RNA sequencing data from 31 normal donors and 37 AMD patients.
Results:
The single-cell transcriptome data analysis revealed massive dysregulation of RNA methylation-related gene expression in the RPE of AMD patients. SMR revealed causal associations between key RNA methylation regulators (METTL3, NSUN6, and MRM1, etc.) and AMD onset. Machine learning models further validated these findings and demonstrated a high accuracy of AMD risk prediction by using the above-identified RNA methylation-related genes: METTL3, NSUN6, and MRM1. Furthermore, METTL3 and NSUN6 were found to have a protective effect, while MRM1 was associated with an increased risk of AMD.
Conclusion:
The results reveal the implication of dysregulation of RNA methylation-related gene expression in the RPE of AMD patients and further demonstrated a causal association between RNA methylation-related genes (METTL3, NSUN6, and MRM1) and AMD. These findings highlight the importance of RNA methylation in the pathogenesis of AMD and offer potential biomarkers and therapeutic targets for AMD management.
Insights
RNA methylation is dysregulated in age-related macular degeneration (AMD) retinal cells. Key genes like METTL3 and NSUN6 show protective effects, while MRM1 increases AMD risk, offering potential therapeutic targets.
Area of Science:
- Ophthalmology
- Genetics
- Molecular Biology
Background:
- Age-related macular degeneration (AMD) is a leading cause of vision loss.
- The role of RNA methylation in retinal pigment epithelial (RPE) cells in AMD pathogenesis is not fully understood.
Purpose of the Study:
- To investigate the role of RNA methylation in RPE cells in the context of AMD.
- To identify specific RNA methylation-related genes causally associated with AMD.
Main Methods:
- Single-cell transcriptome analysis of RPE cells from AMD patients and normal controls.
- Summary-data-based Mendelian randomization (SMR) analysis using AMD GWAS and multi-omics QTL data.
- Machine learning models for validating causal associations and predicting AMD risk.
Main Results:
- Significant dysregulation of RNA methylation-related gene expression was observed in AMD RPE cells.
- Causal associations were identified between key RNA methylation regulators (METTL3, NSUN6, MRM1) and AMD onset.
- METTL3 and NSUN6 demonstrated a protective effect, while MRM1 was associated with increased AMD risk, with high prediction accuracy.
Conclusions:
- Dysregulation of RNA methylation in RPE cells is implicated in AMD pathogenesis.
- Specific RNA methylation genes (METTL3, NSUN6, MRM1) show a causal link to AMD.
- These genes represent potential biomarkers and therapeutic targets for AMD management.
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