Huang Yu, Syed Mohammad Ghouse, Chen Ruiye, Li Cong, Shang Xianwen, Wang Wei, Zhang Xueli, Zhang Xiayin, Tang Shulin, Liu Jing, Liu Shunming, Srinivasan Sundar, Hu Yijun, Mookiah Muthu Rama Krishnan, Wang Huan, Trucco Emanuele, Yu Honghua, Palmer Colin, Zhu Zhuoting, Doney Alexander S F, He Mingguang
Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510080, China.
Geroscience. 2025 Apr;47(2):2613-2629. doi: 10.1007/s11357-024-01481-w. Epub 2025 Jan 8.
With the development of deep learning (DL) techniques, there has been a successful application of this approach to determine biological age from latent information contained in retinal images. Retinal age gap (RAG) defined as the difference between chronological age and predicted retinal age has been established previously to predict the age-related disease. In this study, we performed discovery genome-wide association analysis (GWAS) on the RAG using the 31,271 UK Biobank participants and replicated our findings in 8034 GoDARTS participants. The genetic correlation between RAGs predicted from the two cohorts was 0.67 (P = 0.021). After meta-analysis, we found 13 RAG loci which might be related to retinal vessel density and other aging processes. The SNP-wide heritability (h) of RAG was 0.15. Meanwhile, by performing Mendelian randomization analysis, we found that glycated hemoglobin, inflammation hemocytes, and anemia might be associated with accelerated retinal aging. Our study explored the biological implications and molecular-level mechanism of RAG, which might enable causal inference of the aging process as well as provide potential pharmaceutical intervention targets for further treatment.
随着深度学习（DL）技术的发展，这种方法已成功应用于从视网膜图像中包含的潜在信息来确定生物年龄。视网膜年龄差距（RAG）定义为实际年龄与预测视网膜年龄之间的差异，此前已被确立用于预测与年龄相关的疾病。在本研究中，我们对31271名英国生物银行参与者的RAG进行了全基因组关联分析（GWAS）发现，并在8034名GoDARTS参与者中重复了我们的发现。两个队列预测的RAG之间的遗传相关性为0.67（P = 0.021）。经过荟萃分析，我们发现了13个可能与视网膜血管密度和其他衰老过程相关的RAG位点。RAG的单核苷酸多态性广义遗传力（h）为0.15。同时，通过进行孟德尔随机化分析，我们发现糖化血红蛋白、炎症血细胞和贫血可能与视网膜加速衰老有关。我们的研究探讨了RAG的生物学意义和分子水平机制，这可能有助于对衰老过程进行因果推断，并为进一步治疗提供潜在的药物干预靶点。
