| Title: | Exome-wide genetic risk score (ExGRS) to predict high myopia across multi-ancestry populations |
| Journal: | Communications Medicine |
| Published: | 30 Dec 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39738800/ |
| DOI: | https://doi.org/10.1038/s43856-024-00718-1 |
Publication 14809
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Abstract
BackgroundHigh myopia (HM), characterized by a severe myopic refractive error, stands as a leading cause of visual impairment and blindness globally. HM is a multifactorial ocular disease that presents high genetic heterogeneity. Employing a genetic risk score (GRS) is useful for capturing genetic susceptibility to HM.MethodsThis study assesses the effectiveness of these strategies via incorporating rare variations into the GRS assessment. This study enrolled two independent cohorts: 12,600 unrelated individuals of Han Chinese ancestry from Myopia Associated Genetics and Intervention Consortium (MAGIC) and 8682 individuals of European ancestry from UK Biobank (UKB).ResultsHere, we first estimate the heritability of HM resulting in 0.53 (standard error, 0.06) in the MAGIC cohort and 0.21 (standard error, 0.10) in the UKB cohort by using whole-exome sequencing (WES) data. We generate, optimize, and validate an exome-wide genetic risk score (ExGRS) for HM prediction by combining rare risk genotypes with common variant GRS (cvGRS). ExGRS improved the AUC from 0.819 (cvGRS) to 0.856 for 1219 Han Chinese individuals of an independent testing dataset. Individuals with a top 5% ExGRS confer a 15.57-times (95% CI, 5.70-59.48) higher risk for developing HM compared to the remaining 95% of individuals in MAGIC cohort.ConclusionsOur study suggests that rare variants are a major source of the missing heritability of HM and that ExGRS provides enhanced accuracy for HM prediction in Han Chinese ancestry, shedding new light on research and clinical practice.</p>
14 Authors
- Jian Yuan
- Ruowen Qiu
- Yuhan Wang
- Zhen Ji Chen
- Haojun Sun
- Wei Dai
- Yinghao Yao
- Ran Zhuo
- Kai Li
- Shilai Xing
- Xiaoguang Yu
- Liya Qiao
- Jia Qu
- Jianzhong Su
1 Application
| Application ID | Title |
|---|---|
| 45270 | An artificial intelligence algorithm based on deep learning and molecular diagnosis for identifying ocular diseases. |
Enabling scientific discoveries that improve human health