ArticlePLoS genetics2024
iGWAS: Image-based genome-wide association of self-supervised deep phenotyping of retina fundus images.
Article in PLoS genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Beyond the Classics: The Synergy of AI and Genomics Reveals an Expanded Repertoire of Pigmentation Genes.Journal of experimental zoology. Part B, Molecular and developmental evolution · 2026Review
- From GWAS Signals to Molecular Mechanisms: Explainable AI for Causal Gene Prioritization and Biomolecular Target Interpretation.Biomolecules · 2026Review
- Genetic analysis of imaging-derived phenotypes.Nature reviews. Genetics · 2026Review
- Image feature embedding with a deep learning framework improves genome-wide association studies on dog endophenotypes.Science advances · 2026Article
- Structure-aware retinal disentanglement reveals the genetic architecture of ocular and systemic diseases.PLOS digital health · 2026Article
- HistoGWAS: an AI-enabled framework for automated genetic analysis of tissue phenotypes in histology cohorts.Genome biology · 2026Article
- An Artificial Intelligence Method for Phenotyping of OCT-Derived Thickness Maps Using Unsupervised and Self-supervised Deep Learning.Journal of imaging informatics in medicine · 2026Article
- Cardiovascular-kidney-metabolic syndrome: candidate subtypes and genetic risk factors.BMC medical genomics · 2026Article
- Deep-learning-derived glaucoma-related endophenotypes enable novel genome-wide genetic and functional discovery.Research square · 2026Article
- Genome-wide association study reveals genetic architecture and evolution of human retinal pigmentation.Science advances · 2026Article
- REECAP: Contrastive learning of retinal aging reveals genetic loci linking morphology to eye disease.medRxiv : the preprint server for health sciences · 2025Article
- Deep-learning-derived glaucoma-related endophenotypes enable novel genome-wide genetic and functional discovery.medRxiv : the preprint server for health sciences · 2025Article
- Integration of Genetic and Imaging Data for Alzheimer's Disease Diagnosis and Interpretation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Mendelian randomization study implicates inflammaging biomarkers in retinal vasculature, cardiovascular diseases, and longevity.Science advances · 2025Article
- Autoencoder-based phenotyping of ophthalmic images highlights genetic loci influencing retinal morphology and provides informative biomarkers.Bioinformatics (Oxford, England) · 2024Article
- TransferGWAS of T1-weighted brain MRI data from UK Biobank.PLoS genetics · 2024Article
- Phenotypic and genetic characteristics of retinal vascular parameters and their association with diseases.Nature communications · 2024Article
- Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction.Nature genetics · 2024Article
- Eye-brain connections revealed by multimodal retinal and brain imaging genetics.Nature communications · 2024Article
- Unsupervised representation learning improves genomic discovery and risk prediction for respiratory and circulatory functions and diseases.medRxiv : the preprint server for health sciences · 2023Article
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14 authors.
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Abstract
Existing imaging genetics studies have been mostly limited in scope by using imaging-derived phenotypes defined by human experts. Here, leveraging new breakthroughs in self-supervised deep representation learning, we propose a new approach, image-based genome-wide association study (iGWAS), for identifying genetic factors associated with phenotypes discovered from medical images using contrastive learning. Using retinal fundus photos, our model extracts a 128-dimensional vector representing features of the retina as phenotypes. After training the model on 40,000 images from the EyePACS dataset, we generated phenotypes from 130,329 images of 65,629 British White participants in the UK Biobank. We conducted GWAS on these phenotypes and identified 14 loci with genome-wide significance (p<5×10-8 and intersection of hits from left and right eyes). We also did GWAS on the retina color, the average color of the center region of the retinal fundus photos. The GWAS of retina colors identified 34 loci, 7 are overlapping with GWAS of raw image phenotype. Our results establish the feasibility of this new framework of genomic study based on self-supervised phenotyping of medical images.
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