QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration.

DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype-environment interaction in retina.

Polygenic Risk Scores for Glaucoma Onset in the Ocular Hypertension Treatment Study.

Importance: Primary open-angle glaucoma (POAG) is a highly heritable disease, with 127 identified risk loci to date. Polygenic risk score (PRS) may provide a clinically useful measure of aggregate genetic burden and improve patient risk stratification. Objective: To assess whether a PRS improves prediction of POAG onset in patients with ocular hypertension. Design, Setting, and Participants: This was a post hoc analysis of the Ocular Hypertension Treatment Study. Data were collected from 22 US sites with a mean (SD) follow-up of 14.0 (6.9) years. A total of 1636 participants were followed up from February 1994 to December 2008; 1077 participants were enrolled in an ancillary genetics study, of which 1009 met criteria for this analysis. PRS was calculated using summary statistics from the largest cross-ancestry POAG meta-analysis, with weights trained using 8 813 496 variants from 449 186 cross-ancestry participants in the UK Biobank. Data were analyzed from July 2022 to December 2023. Exposures: From February 1994 to June 2002, participants were randomized to either topical intraocular pressure-lowering medication or close observation. After June 2002, both groups received medication. Main Outcomes and Measures: Outcome measures were hazard ratios for POAG onset. Concordance index and time-dependent areas under the receiver operating characteristic curve were used to compare the predictive performance of multivariable Cox proportional hazards models. Results: Of 1009 included participants, 562 (55.7%) were female, and the mean (SD) age was 55.9 (9.3) years. The mean (SD) PRS was significantly higher for 350 POAG converters (0.24 [0.95]) compared with 659 nonconverters (-0.12 [1.00]) (P < .001). POAG risk increased 1.36% (95% CI, 1.08-1.64) with each higher PRS decile, with conversion ranging from 9.52% (95% CI, 7.09-11.95) in the lowest PRS decile to 21.81% (95% CI, 19.37-24.25) in the highest decile. Comparison of low-risk and high-risk PRS tertiles showed a 2.0-fold increase in 20-year POAG risk for participants of European and African ancestries. In the subgroup randomized to delayed treatment, each increase in PRS decile was associated with a 0.52-year (95% CI, 0.01-1.03) decrease in age at diagnosis (P = .047). No significant linear association between PRS and age at POAG diagnosis was present in the early treatment group. Prediction models significantly improved with the addition of PRS as a covariate (C index = 0.77) compared with the Ocular Hypertension Treatment Study baseline model (C index = 0.75) (P < .001). Each 1-SD higher PRS conferred a mean hazard ratio of 1.25 (95% CI, 1.13-1.44) for POAG onset. Conclusions and Relevance: Higher PRS was associated with increased risk for POAG in patients with ocular hypertension. The inclusion of a PRS improved the prediction of POAG onset. Trial Registration: ClinicalTrials.gov Identifier: NCT00000125.

Machine Learning-Derived Baseline Visual Field Patterns Predict Future Glaucoma Onset in the Ocular Hypertension Treatment Study.

Purpose: The Ocular Hypertension Treatment Study (OHTS) identified risk factors for primary open-angle glaucoma (POAG) in patients with ocular hypertension, including pattern standard deviation (PSD). Archetypal analysis, an unsupervised machine learning method, may offer a more interpretable approach to risk stratification by identifying patterns in baseline visual fields (VFs). Methods: There were 3272 eyes available in the OHTS. Archetypal analysis was applied using 24-2 baseline VFs, and model selection was performed with cross-validation. Decomposition coefficients for archetypes (ATs) were calculated. A penalized Cox proportional hazards model was implemented to select discriminative ATs. The AT model was compared to the OHTS model. Associations were identified between ATs with both POAG onset and VF progression, defined by mean deviation change per year. Results: We selected 8494 baseline VFs. Optimal AT count was 19. The highest prevalence ATs were AT9, AT11, and AT7. The AT-based prediction model had a C-index of 0.75 for POAG onset. Multivariable models demonstrated that a one-interquartile range increase in the AT5 (hazard ratio [HR] = 1.14; 95% confidence interval [CI], 1.04-1.25), AT8 (HR = 1.22; 95% CI, 1.09-1.37), AT15 (HR = 1.26; 95% CI, 1.12-1.41), and AT17 (HR = 1.17; 95% CI, 1.03-1.31) coefficients conferred increased risk of POAG onset. AT5, AT10, and AT14 were significantly associated with rapid VF progression. In a subgroup analysis by high-risk ATs (>95th percentile or <75th percentile coefficients), PSD lost significance as a predictor of POAG in the low-risk group. Conclusions: Baseline VFs, prior to detectable glaucomatous damage, contain occult patterns representing early changes that may increase the risk of POAG onset and VF progression in patients with ocular hypertension. The relationship between PSD and POAG is modified by the presence of high-risk patterns at baseline. An AT-based prediction model for POAG may provide more interpretable glaucoma-specific information in a clinical setting.

Integrating genetic regulation and single-cell expression with GWAS prioritizes causal genes and cell types for glaucoma.

Primary open-angle glaucoma (POAG), characterized by retinal ganglion cell death, is a leading cause of irreversible blindness worldwide. However, its molecular and cellular causes are not well understood. Elevated intraocular pressure (IOP) is a major risk factor, but many patients have normal IOP. Colocalization and Mendelian randomization analysis of >240 POAG and IOP genome-wide association study (GWAS) loci and overlapping expression and splicing quantitative trait loci (e/sQTLs) in 49 GTEx tissues and retina prioritizes causal genes for 60% of loci. These genes are enriched in pathways implicated in extracellular matrix organization, cell adhesion, and vascular development. Analysis of single-nucleus RNA-seq of glaucoma-relevant eye tissues reveals that the POAG and IOP colocalizing genes and genome-wide associations are enriched in specific cell types in the aqueous outflow pathways, retina, optic nerve head, peripapillary sclera, and choroid. This study nominates IOP-dependent and independent regulatory mechanisms, genes, and cell types that may contribute to POAG pathogenesis.

Phenome- and genome-wide analyses of retinal optical coherence tomography images identify links between ocular and systemic health.

The human retina is a multilayered tissue that offers a unique window into systemic health. Optical coherence tomography (OCT) is widely used in eye care and allows the noninvasive, rapid capture of retinal anatomy in exquisite detail. We conducted genotypic and phenotypic analyses of retinal layer thicknesses using macular OCT images from 44,823 UK Biobank participants. We performed OCT layer cross-phenotype association analyses (OCT-XWAS), associating retinal thicknesses with 1866 incident conditions (median 10-year follow-up) and 88 quantitative traits and blood biomarkers. We performed genome-wide association studies (GWASs), identifying inherited genetic markers that influence retinal layer thicknesses and replicated our associations among the LIFE-Adult Study (N = 6313). Last, we performed a comparative analysis of phenome- and genome-wide associations to identify putative causal links between retinal layer thicknesses and both ocular and systemic conditions. Independent associations with incident mortality were detected for thinner photoreceptor segments (PSs) and, separately, ganglion cell complex layers. Phenotypic associations were detected between thinner retinal layers and ocular, neuropsychiatric, cardiometabolic, and pulmonary conditions. A GWAS of retinal layer thicknesses yielded 259 unique loci. Consistency between epidemiologic and genetic associations suggested links between a thinner retinal nerve fiber layer with glaucoma, thinner PS with age-related macular degeneration, and poor cardiometabolic and pulmonary function with a thinner PS. In conclusion, we identified multiple inherited genetic loci and acquired systemic cardio-metabolic-pulmonary conditions associated with thinner retinal layers and identify retinal layers wherein thinning is predictive of future ocular and systemic conditions.

TIE1 and TEK signalling, intraocular pressure, and primary open-angle glaucoma: a Mendelian randomization study.

BACKGROUND: In primary open-angle glaucoma (POAG), lowering intraocular pressure (IOP) is the only proven way of slowing vision loss. Schlemm's canal (SC) is a hybrid vascular and lymphatic vessel that mediates aqueous humour drainage from the anterior ocular chamber. Animal studies support the importance of SC endothelial angiopoietin-TEK signalling, and more recently TIE1 signalling, in maintaining normal IOP. However, human genetic support for a causal role of TIE1 and TEK signalling in lowering IOP is currently lacking. METHODS: GWAS summary statistics were obtained for plasma soluble TIE1 (sTIE1) protein levels (N = 35,559), soluble TEK (sTEK) protein levels (N = 35,559), IOP (N = 139,555) and POAG (Ncases = 16,677, Ncontrols = 199,580). Mendelian randomization (MR) was performed to estimate the association of genetically proxied TIE1 and TEK protein levels with IOP and POAG liability. Where significant MR estimates were obtained, genetic colocalization was performed to assess the probability of a shared causal variant (PPshared) versus distinct (PPdistinct) causal variants underlying TIE1/TEK signalling and the outcome. Publicly available single-nucleus RNA-sequencing data were leveraged to investigate differential expression of TIE1 and TEK in the human ocular anterior segment. RESULTS: Increased genetically proxied TIE1 signalling and TEK signalling associated with a reduction in IOP (- 0.21 mmHg per SD increase in sTIE1, 95% CI = - 0.09 to - 0.33 mmHg, P = 6.57 × 10-4, and - 0.14 mmHg per SD decrease in sTEK, 95% CI = - 0.03 to - 0.25 mmHg, P = 0.011), but not with POAG liability. Colocalization analysis found that the probability of a shared causal variant was greater for TIE1 and IOP than for TEK and IOP (PPshared/(PPdistinct + PPshared) = 0.98 for TIE1 and 0.30 for TEK). In the anterior segment, TIE1 and TEK were preferentially expressed in SC, lymphatic, and vascular endothelium. CONCLUSIONS: This study provides novel human genetic support for a causal role of both TIE1 and TEK signalling in regulating IOP. Here, combined evidence from cis-MR and colocalization analyses provide stronger support for TIE1 than TEK as a potential IOP-lowering therapeutic target.

Automated detection of genetic relatedness from fundus photographs using Siamese Neural Networks.

Heritability of common eye diseases and ocular traits are relatively high. Here, we develop an automated algorithm to detect genetic relatedness from color fundus photographs (FPs). We estimated the degree of shared ancestry amongst individuals in the UK Biobank using KING software. A convolutional Siamese neural network-based algorithm was trained to output a measure of genetic relatedness using 7224 pairs (3612 related and 3612 unrelated) of FPs. The model achieved high performance for prediction of genetic relatedness; when computed Euclidean distances were used to determine probability of relatedness, the area under the receiver operating characteristic curve (AUROC) for identifying related FPs reached 0.926. We performed external validation of our model using FPs from the LIFE-Adult study and achieved an AUROC of 0.69. An occlusion map indicates that the optic nerve and its surrounding area may be the most predictive of genetic relatedness. We demonstrate that genetic relatedness can be captured from FP features. This approach may be used to uncover novel biomarkers for common ocular diseases.

Deep Ocular Phenotyping Across Primary Open-Angle Glaucoma Genetic Burden.

Importance: Better understanding of primary open-angle glaucoma (POAG) genetics could enable timely screening and promote individualized disease risk prognostication. Objective: To evaluate phenotypic features across genetic burden for POAG. Design, Setting, and Participants: This was a cross-sectional, population-based study conducted from 2006 to 2010. Included participants were individuals from the UK Biobank aged 40 to 69 years. Individuals with non-POAG forms of glaucoma were excluded from the analysis. Data were statistically analyzed from October 2022 to January 2023. Main Outcomes and Measures: POAG prevalence based on structural coding, self-reports, and glaucoma-related traits. Results: Among 407 667 participants (mean [SD] age, 56.3 [8.1] years; 219 183 majority sex [53.8%]) were 14 171 POAG cases. Area under receiver operating characteristic curve for POAG detection was 0.748 in a model including polygenic risk score (PRS), age, sex, and ancestry. POAG prevalence in the highest decile of PRS was 7.4% (3005 of 40 644) vs 1.3% (544 of 40 795) in lowest decile (P < .001). A 1-SD increase in PRS was associated with 1.74 times higher odds of POAG (95% CI, 1.71-1.77), a 0.61-mm Hg increase in corneal-compensated intraocular pressure (IOP; 95% CI, 0.59-0.64), a -0.09-mm Hg decrease in corneal hysteresis (95% CI, -0.10 to -0.08), a 0.08-mm Hg increase in corneal resistance factor (95% CI, 0.06-0.09), and a -0.08-diopter decrease in spherical equivalent (95% CI, -0.11 to -0.07; P < .001 for all). A 1-SD increase in PRS was associated with a thinning of the macula-region retinal nerve fiber layer (mRNFL) of 0.14 µm and macular ganglion cell complex (GCC) of 0.26 µm (P < .001 for both). In the subset of individuals with fundus photographs, a 1-SD increase in PRS was associated with 1.42 times higher odds of suspicious optic disc features (95% CI, 1.19-1.69) and a 0.013 increase in cup-disc ratio (CDR; 95% CI, 0.012-0.014; P < .001 for both). A total of 22 of 5193 fundus photographs (0.4%) in decile 10 had disc hemorrhages, and 27 of 5257 (0.5%) had suspicious optic disc features compared with 9 of 5158 (0.2%) and 10 of 5219 (0.2%), respectively, in decile 1 (P < .001 for both). CDR in decile 10 was 0.46 compared with 0.41 in decile 1 (P < .001). Conclusion and Relevance: Results suggest that PRS identified a group of individuals at substantially higher risk for POAG. Higher genetic risk was associated with more advanced disease, namely higher CDR and corneal-compensated IOP, thinner mRNFL, and thinner GCC. Associations with POAG PRS and corneal hysteresis and greater prevalence of disc hemorrhages were identified. These results suggest that genetic risk is an increasingly important parameter for risk stratification to consider in clinical practice.

Transcriptomic analysis of the ocular posterior segment completes a cell atlas of the human eye.

Although the visual system extends through the brain, most vision loss originates from defects in the eye. Its central element is the neural retina, which senses light, processes visual signals, and transmits them to the rest of the brain through the optic nerve (ON). Surrounding the retina are numerous other structures, conventionally divided into anterior and posterior segments. Here, we used high-throughput single-nucleus RNA sequencing (snRNA-seq) to classify and characterize cells in six extraretinal components of the posterior segment: ON, optic nerve head (ONH), peripheral sclera, peripapillary sclera (PPS), choroid, and retinal pigment epithelium (RPE). Defects in each of these tissues are associated with blinding diseases-for example, glaucoma (ONH and PPS), optic neuritis (ON), retinitis pigmentosa (RPE), and age-related macular degeneration (RPE and choroid). From ~151,000 single nuclei, we identified 37 transcriptomically distinct cell types, including multiple types of astrocytes, oligodendrocytes, fibroblasts, and vascular endothelial cells. Our analyses revealed a differential distribution of many cell types among distinct structures. Together with our previous analyses of the anterior segment and retina, the data presented here complete a "Version 1" cell atlas of the human eye. We used this atlas to map the expression of >180 genes associated with the risk of developing glaucoma, which is known to involve ocular tissues in both anterior and posterior segments as well as the neural retina. Similar methods can be used to investigate numerous additional ocular diseases, many of which are currently untreatable.

Polygenic Risk Score Improves Prediction of Primary Open Angle Glaucoma Onset in the Ocular Hypertension Treatment Study.

Objective or Purpose: Primary open-angle glaucoma (POAG) is a highly heritable disease with 127 identified risk loci. Polygenic risks score (PRS) offers a measure of aggregate genetic burden. In this study, we assess whether PRS improves risk stratification in patients with ocular hypertension. Design: A post-hoc analysis of the Ocular Hypertension Treatment Study (OHTS) data. Setting Participants and/or Controls: 1636 participants were followed from 1994 to 2020 across 22 sites. The PRS was computed for 1009 OHTS participants using summary statistics from largest cross-ancestry POAG metanalysis with weights trained using 8,813,496 variants from 488,395 participants in the UK Biobank. Methods Interventions or Testing: Survival regression analysis, with endpoint as development of POAG, predicted disease onset from PRS incorporating baseline covariates. Main Outcomes and Measures: Outcome measures were hazard ratios for POAG onset. Concordance index and time-dependent AUC were used to compare the predictive performance of multivariable Cox-Proportional Hazards models. Results: Mean PRS was significantly higher for POAG-converters (0.24 ± 0.95) than for non-converters (-0.12 ± 1.00) (p < 0.01). POAG risk increased 1.36% with each higher PRS decile, with conversion ranging from 9.5% in the lowest PRS decile to 21.8% in the highest decile. Comparison of low- and high-risk PRS tertiles showed a 1.8-fold increase in 20-year POAG risk for participants of European and African ancestries (p<0.01). In the subgroup randomized to delayed treatment, each increase in PRS decile was associated with a 0.52-year decrease in age at diagnosis, (p=0.05). No significant linear relationship between PRS and age at POAG diagnosis was present in the early treatment group. Prediction models significantly improved with the addition of PRS as a covariate (C-index = 0.77) compared to OHTS baseline model (C-index=0.75) (p<0.01). One standard deviation higher PRS conferred a mean hazard ratio of 1.25 (CI=[1.13, 1.44]) for POAG onset. Conclusions: Higher PRS is associated with increased risk for, and earlier development of POAG in patients with ocular hypertension. Early treatment may mitigate the risk from high genetic burden, delaying clinically detectable disease by up to 5.2 years. The inclusion of a PRS improves the prediction of POAG onset.

Insights into human health from phenome- and genome-wide analyses of UK Biobank retinal optical coherence tomography phenotypes.

The human retina is a complex multi-layered tissue which offers a unique window into systemic health and disease. Optical coherence tomography (OCT) is widely used in eye care and allows the non-invasive, rapid capture of retinal measurements in exquisite detail. We conducted genome- and phenome-wide analyses of retinal layer thicknesses using macular OCT images from 44,823 UK Biobank participants. We performed phenome-wide association analyses, associating retinal thicknesses with 1,866 incident ICD-based conditions (median 10-year follow-up) and 88 quantitative traits and blood biomarkers. We performed genome-wide association analyses, identifying inherited genetic markers which influence the retina, and replicated our associations among 6,313 individuals from the LIFE-Adult Study. And lastly, we performed comparative association of phenome- and genome- wide associations to identify putative causal links between systemic conditions, retinal layer thicknesses, and ocular disease. Independent associations with incident mortality were detected for photoreceptor thinning and ganglion cell complex thinning. Significant phenotypic associations were detected between retinal layer thinning and ocular, neuropsychiatric, cardiometabolic and pulmonary conditions. Genome-wide association of retinal layer thicknesses yielded 259 loci. Consistency between epidemiologic and genetic associations suggested putative causal links between thinning of the retinal nerve fiber layer with glaucoma, photoreceptor segment with AMD, as well as poor cardiometabolic and pulmonary function with PS thinning, among other findings. In conclusion, retinal layer thinning predicts risk of future ocular and systemic disease. Furthermore, systemic cardio-metabolic-pulmonary conditions promote retinal thinning. Retinal imaging biomarkers, integrated into electronic health records, may inform risk prediction and potential therapeutic strategies.

Large-scale multitrait genome-wide association analyses identify hundreds of glaucoma risk loci.

Glaucoma, a leading cause of irreversible blindness, is a highly heritable human disease. Previous genome-wide association studies have identified over 100 loci for the most common form, primary open-angle glaucoma. Two key glaucoma-associated traits also show high heritability: intraocular pressure and optic nerve head excavation damage quantified as the vertical cup-to-disc ratio. Here, since much of glaucoma heritability remains unexplained, we conducted a large-scale multitrait genome-wide association study in participants of European ancestry combining primary open-angle glaucoma and its two associated traits (total sample size over 600,000) to substantially improve genetic discovery power (263 loci). We further increased our power by then employing a multiancestry approach, which increased the number of independent risk loci to 312, with the vast majority replicating in a large independent cohort from 23andMe, Inc. (total sample size over 2.8 million; 296 loci replicated at P < 0.05, 240 after Bonferroni correction). Leveraging multiomics datasets, we identified many potential druggable genes, including neuro-protection targets likely to act via the optic nerve, a key advance for glaucoma because all existing drugs only target intraocular pressure. We further used Mendelian randomization and genetic correlation-based approaches to identify novel links to other complex traits, including immune-related diseases such as multiple sclerosis and systemic lupus erythematosus.

Transcriptomic Analysis of the Ocular Posterior Segment Completes a Cell Atlas of the Human Eye.

Although the visual system extends through the brain, most vision loss originates from defects in the eye. Its central element is the neural retina, which senses light, processes visual signals, and transmits them to the rest of the brain through the optic nerve (ON). Surrounding the retina are numerous other structures, conventionally divided into anterior and posterior segments. Here we used high-throughput single nucleus RNA sequencing (snRNA-seq) to classify and characterize cells in the extraretinal components of the posterior segment: ON, optic nerve head (ONH), peripheral sclera, peripapillary sclera (PPS), choroid, and retinal pigment epithelium (RPE). Defects in each of these tissues are associated with blinding diseases - for example, glaucoma (ONH and PPS), optic neuritis (ON), retinitis pigmentosa (RPE), and age-related macular degeneration (RPE and choroid). From ∼151,000 single nuclei, we identified 37 transcriptomically distinct cell types, including multiple types of astrocytes, oligodendrocytes, fibroblasts, and vascular endothelial cells. Our analyses revealed a differential distribution of many cell types among distinct structures. Together with our previous analyses of the anterior segment and retina, the new data complete a "Version 1" cell atlas of the human eye. We used this atlas to map the expression of >180 genes associated with the risk of developing glaucoma, which is known to involve ocular tissues in both anterior and posterior segments as well as neural retina. Similar methods can be used to investigate numerous additional ocular diseases, many of which are currently untreatable.

Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation.

How do aberrations in widely expressed genes lead to tissue-selective hereditary diseases? Previous attempts to answer this question were limited to testing a few candidate mechanisms. To answer this question at a larger scale, we developed "Tissue Risk Assessment of Causality by Expression" (TRACE), a machine learning approach to predict genes that underlie tissue-selective diseases and selectivity-related features. TRACE utilized 4,744 biologically interpretable tissue-specific gene features that were inferred from heterogeneous omics datasets. Application of TRACE to 1,031 disease genes uncovered known and novel selectivity-related features, the most common of which was previously overlooked. Next, we created a catalog of tissue-associated risks for 18,927 protein-coding genes (https://netbio.bgu.ac.il/trace/). As proof-of-concept, we prioritized candidate disease genes identified in 48 rare-disease patients. TRACE ranked the verified disease gene among the patient's candidate genes significantly better than gene prioritization methods that rank by gene constraint or tissue expression. Thus, tissue selectivity combined with machine learning enhances genetic and clinical understanding of hereditary diseases.

Interaction of background genetic risk, psychotropic medications, and primary angle closure glaucoma in the UK Biobank.

BACKGROUND/AIMS: Psychotropic medications have been reported as a risk factor for angle closure disease. However, the interaction between background genetic risk for primary angle closure glaucoma (PACG) and susceptibility to angle closure disease among psychotropic medication users has not been investigated. Here we demonstrate the utility of a genome-wide polygenic risk score (PRS) in identifying and risk-stratifying subjects with PACG and investigate the association between PACG genetic burden and exposure to psychotropic medications on prevalent angle closure. METHODS: This analysis used the UK Biobank dataset, a prospective cohort study of 502,506 UK residents. We constructed a PACG PRS for participants using genome-wide association study summary statistics from a multiethnic meta-analysis using the Lassosum method. RESULTS: Among the 441,054 participants, 959 (0.22%) were identified as PACG cases. Individuals with PACG had higher PRS compared to those without PACG (0.24±1.03 SD vs. 0.00±1.00 SD, p<0.001) and PACG prevalence increased with each decile of higher PRS. Among individuals using psychotropic medication, those with PACG had higher average PRS (0.31±1.00 SD vs. 0.00±1.00 SD, p<0.001) and were more likely to have a PRS in upper deciles of polygenic risk (p = 0.04). At each decile of PRS, psychotropic medication use was associated with increased risk of PACG. These effects were more pronounced and significant in higher deciles. CONCLUSION: We demonstrate the utility of a PRS for identifying individuals at higher risk of PACG. Additionally, we demonstrate an important relationship where the association between psychotropic medications use and PACG diagnosis varies across the polygenic risk spectrum.

Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function.

Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.

Photoreceptor Layer Thinning Is an Early Biomarker for Age-Related Macular Degeneration: Epidemiologic and Genetic Evidence from UK Biobank OCT Data.

PURPOSE: Despite widespread use of OCT, an early-stage imaging biomarker for age-related macular degeneration (AMD) has not been identified. Pathophysiologically, the timing of drusen accumulation in relationship to photoreceptor degeneration in AMD remains unclear, as are the inherited genetic variants contributing to these processes. Herein, we jointly analyzed OCT, electronic health record data, and genomic data to characterize the time sequence of changes in retinal layer thicknesses in AMD, as well as epidemiologic and genetic associations between retinal layer thicknesses and AMD. DESIGN: Cohort study. PARTICIPANTS: Forty-four thousand eight hundred twenty-three individuals from the UK Biobank (enrollment age range, 40-70 years; 54% women; median follow-up, 10 years). METHODS: The Topcon Advanced Boundary Segmentation algorithm was used for retinal layer segmentation. We associated 9 retinal layer thicknesses with prevalent AMD (present at enrollment) in a logistic regression model and with incident AMD (diagnosed after enrollment) in a Cox proportional hazards model. Next, we associated AMD-associated genetic alleles, individually and as a polygenic risk score (PRS), with retinal layer thicknesses. All analyses were adjusted for age, age-squared (age2), sex, smoking status, and principal components of ancestry. MAIN OUTCOME MEASURES: Prevalent and incident AMD. RESULTS: Photoreceptor segment (PS) thinning was observed throughout the lifespan of individuals analyzed, whereas retinal pigment epithelium (RPE) and Bruch's membrane (BM) complex thickening started after 57 years of age. Each standard deviation (SD) of PS thinning and RPE-BM complex thickening was associated with incident AMD (PS: hazard ratio [HR], 1.35; 95% confidence interval [CI], 1.23-1.47; P = 3.7 × 10-11; RPE-BM complex: HR, 1.14; 95% CI, 1.06-1.22; P = 0.00024). The AMD PRS was associated with PS thinning (ß, -0.21 SD per twofold genetically increased risk of AMD; 95% CI, -0.23 to -0.19; P = 2.8 × 10-74), and its association with RPE-BM complex was U-shaped (thinning with AMD PRS less than the 92nd percentile and thickening with AMD PRS more than the 92nd percentile). The loci with strongest support for genetic correlation were AMD risk-raising variants Complement Factor H (CFH):rs570618-T, CFH:rs10922109-C, and Age-Related Maculopathy Susceptibility 2 (ARMS2)/High-Temperature Requirement Serine Protease 1 (HTRA1):rs3750846-C on PS thinning and SYN3/Tissue Inhibitor of Metalloprotease 3 (TIMP3):rs5754227-T on RPE-BM complex thickening. CONCLUSIONS: Epidemiologically, PS thinning precedes RPE-BM complex thickening by decades and is the retinal layer most strongly predictive of future AMD risk. Genetically, AMD risk variants are associated with decreased PS thickness. Overall, these findings support PS thinning as an early-stage biomarker for future AMD development.

Gene Set Enrichment Analsyes Identify Pathways Involved in Genetic Risk for Diabetic Retinopathy.

To identify functionally related genes associated with diabetic retinopathy (DR) risk using gene set enrichment analyses applied to genome-wide association study meta-analyses. METHODS: We analyzed DR GWAS meta-analyses performed on 3246 Europeans and 2611 African Americans with type 2 diabetes. Gene sets relevant to 5 key DR pathophysiology processes were investigated: tissue injury, vascular events, metabolic events and glial dysregulation, neuronal dysfunction, and inflammation. Keywords relevant to these processes were queried in 4 pathway and ontology databases. Two GSEA methods, Meta-Analysis Gene set Enrichment of variaNT Associations (MAGENTA) and Multi-marker Analysis of GenoMic Annotation (MAGMA), were used. Gene sets were defined to be enriched for gene associations with DR if the P value corrected for multiple testing (Pcorr) was <.05. RESULTS: Five gene sets were significantly enriched for numerous modest genetic associations with DR in one method (MAGENTA or MAGMA) and also at least nominally significant (uncorrected P < .05) in the other method. These pathways were regulation of the lipid catabolic process (2-fold enrichment, Pcorr = .014); nitric oxide biosynthesis (1.92-fold enrichment, Pcorr = .022); lipid digestion, mobilization, and transport (1.6-fold enrichment, P = .032); apoptosis (1.53-fold enrichment, P = .041); and retinal ganglion cell degeneration (2-fold enrichment, Pcorr = .049). The interferon gamma (IFNG) gene, previously implicated in DR by protein-protein interactions in our GWAS, was among the top ranked genes in the nitric oxide pathway (best variant P = .0001). CONCLUSIONS: These GSEA indicate that variants in genes involved in oxidative stress, lipid transport and catabolism, and cell degeneration are enriched for genes associated with DR risk. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature.

BACKGROUND: The microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health and tumorigenesis. The retinal fundus is a window for human in vivo noninvasive assessment of the microvasculature. Large-scale complementary machine learning-based assessment of the retinal vasculature with phenome-wide and genome-wide analyses may yield new insights into human health and disease. METHODS: We used 97 895 retinal fundus images from 54 813 UK Biobank participants. Using convolutional neural networks to segment the retinal microvasculature, we calculated vascular density and fractal dimension as a measure of vascular branching complexity. We associated these indices with 1866 incident International Classification of Diseases-based conditions (median 10-year follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity. RESULTS: Low retinal vascular fractal dimension and density were significantly associated with higher risks for incident mortality, hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions, as well as corresponding quantitative traits. Genome-wide association of vascular fractal dimension and density identified 7 and 13 novel loci, respectively, that were enriched for pathways linked to angiogenesis (eg, vascular endothelial growth factor, platelet-derived growth factor receptor, angiopoietin, and WNT signaling pathways) and inflammation (eg, interleukin, cytokine signaling). CONCLUSIONS: Our results indicate that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease and provide insights into genes and biological pathways influencing microvascular indices. Moreover, such a framework highlights how deep learning of images can quantify an interpretable phenotype for integration with electronic health record, biomarker, and genetic data to inform risk prediction and risk modification.