| Title: | Autoencoder-based phenotyping of ophthalmic images highlights genetic loci influencing retinal morphology and provides informative biomarkers |
| Journal: | Bioinformatics |
| Published: | 9 Dec 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39657956/ |
| DOI: | https://doi.org/10.1093/bioinformatics/btae732 |
Publication 14234
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Abstract
MOTIVATION: Genome-wide association studies (GWAS) have been remarkably successful in identifying associations between genetic variants and imaging-derived phenotypes. To date, the main focus of these analyses has been on established, clinically-used imaging features. We sought to investigate if deep learning approaches can detect more nuanced patterns of image variability.</p>
RESULTS: We used an autoencoder to represent retinal optical coherence tomography (OCT) images from 31,135 UK Biobank participants. For each subject, we obtained a 64-dimensional vector representing features of retinal structure. GWAS of these autoencoder-derived imaging parameters identified 118 statistically significant loci; 41 of these associations were also significant in a replication study. These loci encompassed variants previously linked with retinal thickness measurements, ophthalmic disorders and/or neurodegenerative conditions. Notably, the generated retinal phenotypes were found to contribute to predictive models for glaucoma and cardiovascular disorders. Overall, we demonstrate that self-supervised phenotyping of OCT images enhances the discoverability of genetic factors influencing retinal morphology and provides epidemiologically-informative biomarkers.</p>
AVAILABILITY: Code and data links available at https://github.com/tf2/autoencoder-oct.</p>
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.</p>
6 Authors
- Panagiotis I Sergouniotis
- Adam Diakite
- Kumar Gaurav
- Biobank Eye and Vision Consortium
- Ewan Birney
- Tomas Fitzgerald
3 Applications
| Application ID | Title |
|---|---|
| 2112 | Automated macular thickness measurements and association with potential risk factors and systemic disease |
| 49978 | Copy number variation from whole exome sequencing in the UK Biobank |
| 53144 | Understanding the impact of rare DNA variants in molecular phenotypes & ophthalmic disease risk |
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