ArticleInvestigative ophthalmology & visual science2025
Diverse-Ancestry GWAS of Age-Related Macular Degeneration on 16,108 Examined Cases and 18,038 Controls.
Article in Investigative ophthalmology & visual science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Article
- Functional polymorphisms in pigmentation-related genesBiochemistry and biophysics reports · 2026Article
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14 authors.
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Abstract
Purpose: In 2016, the International Age-related Macular Degeneration Genomics Consortium analyzed data from approximately 50,000 individuals (IAMDGC 1.0) and identified 52 variants across 34 loci associated with advanced AMD (adAMD) in individuals of European ancestry and did not include diverse ancestries, fine-mapping per ancestry, or a predictive model with/without the contributions of one lead genetic risk locus, CFH. Therefore, we analyzed full cross-ancestry IAMDGC data, utilizing the newest imputation panel, and identified genetic risk loci across and between ancestries contributing to AMD. Methods: In this IAMDGC 2.0 analysis, we included cross-ancestry data via custom exome chip imputed genome-wide via TOPMedv2, in 16,108 ophthalmologically confirmed adAMD cases and 18,038 examined AMD-free controls. We included both male and female subjects and four diverse ancestries. Data were analyzed from June 2021 to May 2024. Results: Utilizing diverse ancestry data (cases/controls = 15,616/16,723 European, 50/357 African, 207/322 Asian, and 235/636 Other), we identified 28 loci at P < 5 × 10-8, including 2 additional AMD loci compared to IAMDGC 1.0 (SERPINA1 and CPN1). Fine-mapping supported one ancestry-shared signal around HTRA1/ARMS2 and nine signals around CFH without African ancestry contribution. The 52-variant genetic risk score with and the 44-variant score without CFH predicted adAMD in all ancestries (area under the curve [AUC] = 0.80/0.75, 0.65/0.64, and 0.80/0.79, respectively). Conclusions: Our results indicate that the genetic underpinning of adAMD is mostly shared between ancestries. We also identify the CFH variant as being less relevant in specific ancestries, indicating a difference in pathogenic burden between ancestries. We increased the available genomic data for AMD over 300-fold with the IAMDGC 2.0 imputation, making it a valuable resource for further AMD genetic analysis.
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