Large-scale study enables new insights into rare eye disorders

The retina is a layered tissue that receives light and converts it into a signal that can be interpreted by the brain. Each retinal layer comprises different cell types that play a unique role in this light conversion process. These layers can be non-invasively imaged and identified with high resolution using optical coherence tomography (OCT), a service now commonly offered by many opticians. These images are commonly used in the clinic to aid the diagnosis of eye disorders.  

Rare diseases of the retina called retinal dystrophies are frequently caused by inherited mutations in genes expressed by light-detecting cells found in the retina called photoreceptor cells (PRCs). These mutations cause the retina to function incorrectly, resulting in sight impairment or even blindness. Although these individual diseases are rare, together they are the leading cause of blindness in working-age adults. 

In a new study, published in the journal PLOS Genetics, researchers used OCT images and the corresponding genomic and medical information of more than 30,000 participants stored in the UK Biobank to gain insights into retinal dystrophies. The researchers conducted genome-wide association studies (GWAS) on the UK Biobank data to look for genetic variations linked to differences in the thickness of the PRC layers. (GWAS involve rapidly scanning markers across the complete sets of DNA, or genomes, of many people to find genetic variations associated with a particular disease.) This led them to identify genomic variations associated with the thickness of one or more of the PRC layers. 

Some of these genetic variants were known to be linked to eye diseases, but surprisingly, a number of relatively common genetic variants were near genes known to cause rare genetic eye diseases when disrupted. In one case, the researchers were able to explore how combinations of common variants near genes known to be involved in rare eye diseases change the structure of the retina. This gives more confidence when looking into specific rare disease collections to see how these specific common variants might impact disease. 

“Systematic bioinformatic analysis of large-scale participant data cohorts is driving the future of genomic medicine,” said Omar Mahroo, Professor of Retinal Neuroscience at University College London. “Having access to these data and being able to make these connections between disease phenotypes [characteristics] and genetic variation will open many new opportunities for modern disease diagnosis and therapeutics.” 

Medical Xpress, March 9, 2023; see source articleDOI: 10.1371