Understanding the genetics and function of complex human retinal phenotypes

The human retina is the tissue at the back of the eye responsible for converting light stimulus into neuronal signal that can be interpreted by the brain. To perform this integral role within the central nervous system, the retina has a complex and layered structure, with each layer performing a vital step in the signal transformation process. Changes in the morphology of this structure are often a consequence of disease, which can affect the function of the eye. Better understanding of the genetics influencing this structure may teach us about the biological processes underlying these diseases as well as general eye development. The retina is imaged routinely in the clinic using optical coherence tomography (OCT), providing a non-invasive imaging technique that produces high-resolution, three-dimensional representations of the retina from which measures describing retinal morphology can be extracted. This thesis summarises my research into the genetic variation underlying retinal morphology. Firstly, I explored the morphology of the inner retina, whose thickness is used as a biomarker of glaucoma, using quantitative phenotypes extracted from OCT. I conducted genome-wide association studies (GWAS) of the thickness of the retinal nerve fibre layer and the ganglion cell inner plexiform layer to understand the genetic variation driving inner retinal morphology. I further explored the causal relationship between the inner retina and glaucoma using Mendelian randomisation analysis. I next performed GWAS of the thickness of the outer retinal layers, including both the component photoreceptor cell layers (the outer nuclear layer, inner segment, and outer segment), and the retinal pigment epithelium layer. I explored how genetic variation was affecting the outer retinal morphology at a higher dimension by looking for genetic variants that were differentially affecting the outer retinal thickness at the central macula compared to the peripheral macula. To further explore the rich dimensionality of OCT data, I developed several image analysis techniques to gain more granular information about the morphological variation being affected by the discovered genetic variants. In doing so I established a novel population level trait and examined its effect on visual acuity. In summary, this thesis provides a well-rounded and detailed look into the genetic variation underlying morphological variation of the retinal layers. As the largest study of retinal layer genetics of its kind, it offers insight into clinical ophthalmology and retinal development, and furthermore opens new avenues for clinical research.Funding was provided via the EMBL international PhD programme

MLCut : exploring Multi-Level Cuts in dendrograms for biological data

Choosing a single similarity threshold for cutting dendrograms is not sufficient for performing hierarchical clustering analysis of heterogeneous data sets. In addition, alternative automated or semi-automated methods that cut dendrograms in multiple levels make assumptions about the data in hand. In an attempt to help the user to find patterns in the data and resolve ambiguities in cluster assignments, we developed MLCut: a tool that provides visual support for exploring dendrograms of heterogeneous data sets in different levels of detail. The interactive exploration of the dendrogram is coordinated with a representation of the original data, shown as parallel coordinates. The tool supports three analysis steps. Firstly, a single-height similarity threshold can be applied using a dynamic slider to identify the main clusters. Secondly, a distinctiveness threshold can be applied using a second dynamic slider to identify “weak-edges” that indicate heterogeneity within clusters. Thirdly, the user can drill-down to further explore the dendrogram structure - always in relation to the original data - and cut the branches of the tree at multiple levels. Interactive drill-down is supported using mouse events such as hovering, pointing and clicking on elements of the dendrogram. Two prototypes of this tool have been developed in collaboration with a group of biologists for analysing their own data sets. We found that enabling the users to cut the tree at multiple levels, while viewing the effect in the original data, isa promising method for clustering which could lead to scientific discoveries.Postprin

BayesPiles: Visualisation Support for Bayesian Network Structure Learning

We address the problem of exploring, combining and comparing large collections of scored, directed networks for understanding inferred Bayesian networks used in biology. In this feld, heuristic algorithms explore the space of possible network solutions, sampling this space based on algorithm parameters and a network score that encodes the statistical fit to the data. The goal of the analyst is to guide the heuristic search and decide how to determine a final consensus network structure, usually by selecting the top-scoring network or constructing the consensus network from a collection of high-scoring networks. BayesPiles, our visualisation tool, helps with understanding the structure of the solution space and supporting the construction of a final consensus network that is representative of the underlying dataset. BayesPiles builds upon and extends MultiPiles to meet our domain requirements. We developed BayesPiles in conjunction with computational biologists who have used this tool on datasets used in their research. The biologists found our solution provides them with new insights and helps them achieve results that are representative of the underlying data

Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries

Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates. Primary open-angle glaucoma (POAG) is highly heritable, yet not well understood from a genetic perspective. Here, the authors perform a meta-analysis of genome-wide association studies in 34,179 POAG cases, identifying 44 previously unreported risk loci and mapping effects across multiple ethnicities

Sub-cellular level resolution of common genetic variation in the photoreceptor layer identifies continuum between rare disease and common variation.

Funder: EMBLFunder: Alcon Young Investigator AwardFunder: UKRI Future Leaders FellowshipPhotoreceptor cells (PRCs) are the light-detecting cells of the retina. Such cells can be non-invasively imaged using optical coherence tomography (OCT) which is used in clinical settings to diagnose and monitor ocular diseases. Here we present the largest genome-wide association study of PRC morphology to date utilising quantitative phenotypes extracted from OCT images within the UK Biobank. We discovered 111 loci associated with the thickness of one or more of the PRC layers, many of which had prior associations to ocular phenotypes and pathologies, and 27 with no prior associations. We further identified 10 genes associated with PRC thickness through gene burden testing using exome data. In both cases there was a significant enrichment for genes involved in rare eye pathologies, in particular retinitis pigmentosa. There was evidence for an interaction effect between common genetic variants, VSX2 involved in eye development and PRPH2 known to be involved in retinal dystrophies. We further identified a number of genetic variants with a differential effect across the macular spatial field. Our results suggest a continuum between common and rare variation which impacts retinal structure, sometimes leading to disease

Comparison of Associations with Different Macular Inner Retinal Thickness Parameters in a Large Cohort: The UK Biobank

Purpose: To describe and compare associations with macular retinal nerve fiber layer (mRNFL), ganglion cell complex (GCC), and ganglion cell–inner plexiform layer (GCIPL) thicknesses in a large cohort. Design: Cross-sectional study. Participants: We included 42 044 participants in the UK Biobank. The mean age was 56 years. Methods: Spectral-domain OCT macular images were segmented and analyzed. Corneal-compensated intraocular pressure (IOPcc) was measured with the Ocular Response Analyzer (Reichert, Corp., Buffalo, NY). Multivariable linear regression was used to examine associations with mean mRNFL, GCC, and GCIPL thicknesses. Factors examined were age, sex, ethnicity, height, body mass index (BMI), smoking status, alcohol intake, Townsend deprivation index, education level, diabetes status, spherical equivalent, and IOPcc. Main Outcome Measures: Thicknesses of mRNFL, GCC, and GCIPL. Results: We identified several novel independent associations with thinner inner retinal thickness. Thinner inner retina was associated with alcohol intake (most significant for GCIPL: –0.46 μm for daily or almost daily intake compared with special occasion only or never [95% confidence interval (CI), 0.61–0.30]; P = 1.1×10–8), greater social deprivation (most significant for GCIPL: –0.28 μm for most deprived quartile compared with least deprived quartile [95% CI, –0.42 to –0.14]; P = 6.6×10–5), lower educational attainment (most significant for mRNFL: –0.36 μm for less than O level compared with degree level [95% CI, –0.45 to 0.26]; P = 2.3×10–14), and nonwhite ethnicity (most significant for mRNFL comparing blacks with whites: –1.65 μm [95% CI, –1.86 to –1.43]; P = 2.4×10–50). Corneal-compensated intraocular pressure was associated most significantly with GCIPL (–0.04 μm/mmHg [95% CI, –0.05 to –0.03]; P = 4.0×10–10) and was not associated significantly with mRNFL (0.00 μm/mmHg [95% CI, –0.01 to 0.01]; P = 0.77). The variables examined explained a greater proportion of the variance of GCIPL (11%) than GCC (6%) or mRNFL (7%). Conclusions: The novel associations we identified may be important to consider when using inner retinal parameters as a diagnostic tool. Associations generally were strongest with GCIPL, particularly for IOP. This suggests that GCIPL may be the superior inner retinal biomarker for macular pathophysiologic processes and especially for glaucoma

Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries

Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates. Primary open-angle glaucoma (POAG) is highly heritable, yet not well understood from a genetic perspective. Here, the authors perform a meta-analysis of genome-wide association studies in 34,179 POAG cases, identifying 44 previously unreported risk loci and mapping effects across multiple ethnicities.Peer reviewe

Genetic variation affects morphological retinal phenotypes extracted from UK Biobank optical coherence tomography images

Optical Coherence Tomography (OCT) enables non-invasive imaging of the retina and is used to diagnose and manage ophthalmic diseases including glaucoma. We present the first large-scale genome-wide association study of inner retinal morphology using phenotypes derived from OCT images of 31,434 UK Biobank participants. We identify 46 loci associated with thickness of the retinal nerve fibre layer or ganglion cell inner plexiform layer. Only one of these loci has been associated with glaucoma, and despite its clear role as a biomarker for the disease, Mendelian randomisation does not support inner retinal thickness being on the same genetic causal pathway as glaucoma. We extracted overall retinal thickness at the fovea, representative of foveal hypoplasia, with which three of the 46 SNPs were associated. We additionally associate these three loci with visual acuity. In contrast to the Mendelian causes of severe foveal hypoplasia, our results suggest a spectrum of foveal hypoplasia, in part genetically determined, with consequences on visual function

Genetic variation affects morphological retinal phenotypes extracted from UK Biobank optical coherence tomography images.

Optical Coherence Tomography (OCT) enables non-invasive imaging of the retina and is used to diagnose and manage ophthalmic diseases including glaucoma. We present the first large-scale genome-wide association study of inner retinal morphology using phenotypes derived from OCT images of 31,434 UK Biobank participants. We identify 46 loci associated with thickness of the retinal nerve fibre layer or ganglion cell inner plexiform layer. Only one of these loci has been associated with glaucoma, and despite its clear role as a biomarker for the disease, Mendelian randomisation does not support inner retinal thickness being on the same genetic causal pathway as glaucoma. We extracted overall retinal thickness at the fovea, representative of foveal hypoplasia, with which three of the 46 SNPs were associated. We additionally associate these three loci with visual acuity. In contrast to the Mendelian causes of severe foveal hypoplasia, our results suggest a spectrum of foveal hypoplasia, in part genetically determined, with consequences on visual function