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

Photoreceptor 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.

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.

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

[This corrects the article DOI: 10.1371/journal.pgen.1009497.].

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.

FFPred 3: feature-based function prediction for all Gene Ontology domains.

Predicting protein function has been a major goal of bioinformatics for several decades, and it has gained fresh momentum thanks to recent community-wide blind tests aimed at benchmarking available tools on a genomic scale. Sequence-based predictors, especially those performing homology-based transfers, remain the most popular but increasing understanding of their limitations has stimulated the development of complementary approaches, which mostly exploit machine learning. Here we present FFPred 3, which is intended for assigning Gene Ontology terms to human protein chains, when homology with characterized proteins can provide little aid. Predictions are made by scanning the input sequences against an array of Support Vector Machines (SVMs), each examining the relationship between protein function and biophysical attributes describing secondary structure, transmembrane helices, intrinsically disordered regions, signal peptides and other motifs. This update features a larger SVM library that extends its coverage to the cellular component sub-ontology for the first time, prompted by the establishment of a dedicated evaluation category within the Critical Assessment of Functional Annotation. The effectiveness of this approach is demonstrated through benchmarking experiments, and its usefulness is illustrated by analysing the potential functional consequences of alternative splicing in human and their relationship to patterns of biological features.