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Latest Development on Genetics of Common Retinal Diseases
Li Jia Chen1,2,3, Zhen Ji Chen1, Chi Pui Pang1,3,4
1Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China.
Asia-Pacific Journal of Ophthalmology (Philadelphia, Pa.)
|March 27, 2023
Summary
Complex retinal diseases like neovascular AMD and PCV are sight-threatening. Advanced genomics identified associated genes, but AI is now crucial for personalized medicine by analyzing genetic and lifestyle data for risk prediction.
Area of Science:
- Ophthalmology and Genetics
- Retinal Disease Research
Background:
- Common, pan-ethnic retinal diseases such as neovascular age-related macular degeneration (nAMD), polypoidal choroidal vasculopathy (PCV), and central serous chorioretinopathy are major causes of vision loss.
- These conditions share features of choroidopathy and neovascularization, with complex, multifactorial etiologies involving genetic and environmental factors.
Purpose of the Study:
- To review the genetic basis of complex retinal diseases.
- To highlight the role of advanced genomic technologies and emerging artificial intelligence (AI) in understanding disease etiology and enabling precision medicine.
Main Methods:
- Review of candidate gene analyses, linkage analysis, genome-wide association studies (GWAS), and next-generation sequencing (NGS) including whole-exome and whole-genome sequencing.
- Discussion of the impact of AI in analyzing integrated genetic, investigative, and lifestyle data.
Main Results:
- Advanced genomic technologies have identified numerous genes associated with these retinal diseases.
- Despite progress, the complex interplay of multiple genetic and environmental factors, including aging, smoking, and lifestyle, remains challenging to fully elucidate.
- Individual genetic markers with clinical value are not yet established.
Conclusions:
- The genetic architecture of complex retinal diseases is intricate and not fully understood.
- Artificial intelligence offers a promising avenue for integrating diverse data to establish predictive factors for disease risk, progression, and prognosis.
- AI-driven insights are expected to advance individualized precision medicine for managing these sight-threatening retinal conditions.
