A generalised computer vision model for improved glaucoma screening using fundus images.

IMPORTANCE: Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection is paramount yet challenging, particularly in resource-limited settings. A novel, computer vision-based model for glaucoma screening using fundus images could enhance early and accurate disease detection. OBJECTIVE: To develop and validate a generalised deep-learning-based algorithm for screening glaucoma using fundus image. DESIGN, SETTING AND PARTICIPANTS: The glaucomatous fundus data were collected from 20 publicly accessible databases worldwide, resulting in 18,468 images from multiple clinical settings, of which 10,900 were classified as healthy and 7568 as glaucoma. All the data were evaluated and downsized to fit the model's input requirements. The potential model was selected from 20 pre-trained models and trained on the whole dataset except Drishti-GS. The best-performing model was further trained to classify healthy and glaucomatous fundus images using Fastai and PyTorch libraries. MAIN OUTCOMES AND MEASURES: The model's performance was compared against the actual class using the area under the receiver operating characteristic (AUROC), sensitivity, specificity, accuracy, precision and the F1-score. RESULTS: The high discriminative ability of the best-performing model was evaluated on a dataset comprising 1364 glaucomatous discs and 2047 healthy discs. The model reflected robust performance metrics, with an AUROC of 0.9920 (95% CI: 0.9920-0.9921) for both the glaucoma and healthy classes. The sensitivity, specificity, accuracy, precision, recall and F1-scores were consistently higher than 0.9530 for both classes. The model performed well on an external validation set of the Drishti-GS dataset, with an AUROC of 0.8751 and an accuracy of 0.8713. CONCLUSIONS AND RELEVANCE: This study demonstrated the high efficacy of our classification model in distinguishing between glaucomatous and healthy discs. However, the model's accuracy slightly dropped when evaluated on unseen data, indicating potential inconsistencies among the datasets-the model needs to be refined and validated on larger, more diverse datasets to ensure reliability and generalisability. Despite this, our model can be utilised for screening glaucoma at the population level.

THE FIGHT INHERITED RETINAL BLINDNESS! PROJECT: A NEW TREATMENT OUTCOME AND NATURAL HISTORY REGISTRY FOR INHERITED RETINAL DISEASE.

PURPOSE: To design and build a new disease registry to track the natural history and outcomes of approved gene therapy in patients with inherited retinal diseases (IRDs). METHODS: A core committee of 6 members was convened to oversee the construction of the FIRB! module. A further 11 experts formed a steering committee, which discussed disease classification and variables to form minimum datasets via a consensus approach. RESULTS: The web-based FIRB! registry records baseline demographic, clinical and genetic data together with follow-up data. The Human Phenotype Ontology and Monarch Disease Ontology nomenclature were incorporated within the FIRB! architecture to standardise nomenclature. The registry software assigns individual diagnoses to one of 7 broad phenotypic groups, with minimum datasets dependent upon the broad phenotypic group. Additionally, minimum datasets were agreed upon for patients undergoing approved gene therapy with voretigene neparvovec (Luxturna). New patient entries can be completed in 5 minutes, and follow-up data can be entered in 2 minutes. CONCLUSIONS: Fight Inherited Retinal Blindness! (FIRB!) is an organized, web-based system that uses observational study methods to collect uniform data from IRD patients to track natural history and (uniquely) treatment outcomes. It is free to Users, who have control over their data.

Emerging trends in virus and virus-like particle gene therapy delivery to the brain.

Recent advances in gene therapy and gene-editing techniques offer the very real potential for successful treatment of neurological diseases. However, drug delivery constraints continue to impede viable therapeutic interventions targeting the brain due to its anatomical complexity and highly restrictive microvasculature that is impervious to many molecules. Realizing the therapeutic potential of gene-based therapies requires robust encapsulation and safe and efficient delivery to the target cells. Although viral vectors have been widely used for targeted delivery of gene-based therapies, drawbacks such as host genome integration, prolonged expression, undesired off-target mutations, and immunogenicity have led to the development of alternative strategies. Engineered virus-like particles (eVLPs) are an emerging, promising platform that can be engineered to achieve neurotropism through pseudotyping. This review outlines strategies to improve eVLP neurotropism for therapeutic brain delivery of gene-editing agents.

Highly Accurate and Precise Automated Cup-to-Disc Ratio Quantification for Glaucoma Screening.

Objective: An enlarged cup-to-disc ratio (CDR) is a hallmark of glaucomatous optic neuropathy. Manual assessment of the CDR may be less accurate and more time-consuming than automated methods. Here, we sought to develop and validate a deep learning-based algorithm to automatically determine the CDR from fundus images. Design: Algorithm development for estimating CDR using fundus data from a population-based observational study. Participants: A total of 181 768 fundus images from the United Kingdom Biobank (UKBB), Drishti_GS, and EyePACS. Methods: FastAI and PyTorch libraries were used to train a convolutional neural network-based model on fundus images from the UKBB. Models were constructed to determine image gradability (classification analysis) as well as to estimate CDR (regression analysis). The best-performing model was then validated for use in glaucoma screening using a multiethnic dataset from EyePACS and Drishti_GS. Main Outcome Measures: The area under the receiver operating characteristic curve and coefficient of determination. Results: Our gradability model vgg19_batch normalization (bn) achieved an accuracy of 97.13% on a validation set of 16 045 images, with 99.26% precision and area under the receiver operating characteristic curve of 96.56%. Using regression analysis, our best-performing model (trained on the vgg19_bn architecture) attained a coefficient of determination of 0.8514 (95% confidence interval [CI]: 0.8459-0.8568), while the mean squared error was 0.0050 (95% CI: 0.0048-0.0051) and mean absolute error was 0.0551 (95% CI: 0.0543-0.0559) on a validation set of 12 183 images for determining CDR. The regression point was converted into classification metrics using a tolerance of 0.2 for 20 classes; the classification metrics achieved an accuracy of 99.20%. The EyePACS dataset (98 172 healthy, 3270 glaucoma) was then used to externally validate the model for glaucoma classification, with an accuracy, sensitivity, and specificity of 82.49%, 72.02%, and 82.83%, respectively. Conclusions: Our models were precise in determining image gradability and estimating CDR. Although our artificial intelligence-derived CDR estimates achieve high accuracy, the CDR threshold for glaucoma screening will vary depending on other clinical parameters. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Assessing the Efficacy of Synthetic Optic Disc Images for Detecting Glaucomatous Optic Neuropathy Using Deep Learning.

Purpose: Deep learning architectures can automatically learn complex features and patterns associated with glaucomatous optic neuropathy (GON). However, developing robust algorithms requires a large number of data sets. We sought to train an adversarial model for generating high-quality optic disc images from a large, diverse data set and then assessed the performance of models on generated synthetic images for detecting GON. Methods: A total of 17,060 (6874 glaucomatous and 10,186 healthy) fundus images were used to train deep convolutional generative adversarial networks (DCGANs) for synthesizing disc images for both classes. We then trained two models to detect GON, one solely on these synthetic images and another on a mixed data set (synthetic and real clinical images). Both the models were externally validated on a data set not used for training. The multiple classification metrics were evaluated with 95% confidence intervals. Models' decision-making processes were assessed using gradient-weighted class activation mapping (Grad-CAM) techniques. Results: Following receiver operating characteristic curve analysis, an optimal cup-to-disc ratio threshold for detecting GON from the training data was found to be 0.619. DCGANs generated high-quality synthetic disc images for healthy and glaucomatous eyes. When trained on a mixed data set, the model's area under the receiver operating characteristic curve attained 99.85% on internal validation and 86.45% on external validation. Grad-CAM saliency maps were primarily centered on the optic nerve head, indicating a more precise and clinically relevant attention area of the fundus image. Conclusions: Although our model performed well on synthetic data, training on a mixed data set demonstrated better performance and generalization. Integrating synthetic and real clinical images can optimize the performance of a deep learning model in glaucoma detection. Translational Relevance: Optimizing deep learning models for glaucoma detection through integrating DCGAN-generated synthetic and real-world clinical data can be improved and generalized in clinical practice.

Genetic and cellular basis of impaired phagocytosis and photoreceptor degeneration in CLN3 disease.

Purpose: CLN3 Batten disease (also known as Juvenile Neuronal Ceroid Lipofuscinosis; JNCL) is a lysosomal storage disorder that typically initiates with retinal degeneration but is followed by seizure onset, motor decline and premature death. Patient-derived CLN3 disease iPSC-RPE cells show defective phagocytosis of photoreceptor outer segments (POSs). Because modifier genes are implicated in CLN3 disease, our goal here was to investigate a direct link between CLN3 mutation and POS phagocytosis defect. Methods: Isogenic control and CLN3 mutant stem cell lines were generated by CRISPR-Cas9-mediated biallelic deletion of exons 7 and 8. A transgenic CLN3 Δ 7-8/ Δ 7-8 ( CLN3 ) Yucatan miniswine was also used to study the impact of CLN3 Δ 7-8/ Δ 7-8 mutation on POS phagocytosis. POS phagocytosis by cultured RPE cells was analyzed by Western blotting and immunohistochemistry. Electroretinogram, optical coherence tomography and histological analysis of CLN3 Δ 7/8 and wild-type miniswine eyes were carried out at 6-, 36-, or 48-month age. Results: CLN3 Δ 7-8/ Δ 7-8 RPE ( CLN3 RPE) displayed reduced POS binding and consequently decreased uptake of POS compared to isogenic control RPE cells. Furthermore, wild-type miniswine RPE cells phagocytosed CLN3 Δ 7-8/ Δ 7-8 POS less efficiently than wild-type POS. Consistent with decreased POS phagocytosis, lipofuscin/autofluorescence was decreased in CLN3 miniswine RPE at 36 months-of-age and was followed by almost complete loss of photoreceptors at 48 months of age. Conclusions: CLN3 Δ 7-8/ Δ 7-8 mutation (that affects up to 85% patients) affects both RPE and POSs and leads to photoreceptor cell loss in CLN3 disease. Furthermore, both primary RPE dysfunction and mutant POS independently contribute to impaired POS phagocytosis in CLN3 disease.

Deep Learning-Based Identification of Intraocular Pressure-Associated Genes Influencing Trabecular Meshwork Cell Morphology.

Purpose: Genome-wide association studies have recently uncovered many loci associated with variation in intraocular pressure (IOP). Artificial intelligence (AI) can be used to interrogate the effect of specific genetic knockouts on the morphology of trabecular meshwork cells (TMCs) and thus, IOP regulation. Design: Experimental study. Subjects: Primary TMCs collected from human donors. Methods: Sixty-two genes at 55 loci associated with IOP variation were knocked out in primary TMC lines. All cells underwent high-throughput microscopy imaging after being stained with a 5-channel fluorescent cell staining protocol. A convolutional neural network was trained to distinguish between gene knockout and normal control cell images. The area under the receiver operator curve (AUC) metric was used to quantify morphological variation in gene knockouts to identify potential pathological perturbations. Main Outcome Measures: Degree of morphological variation as measured by deep learning algorithm accuracy of differentiation from normal controls. Results: Cells where LTBP2 or BCAS3 had been perturbed demonstrated the greatest morphological variation from normal TMCs (AUC 0.851, standard deviation [SD] 0.030; and AUC 0.845, SD 0.020, respectively). Of 7 multigene loci, 5 had statistically significant differences in AUC (P < 0.05) between genes, allowing for pathological gene prioritization. The mitochondrial channel most frequently showed the greatest degree of morphological variation (33.9% of cell lines). Conclusions: We demonstrate a robust method for functionally interrogating genome-wide association signals using high-throughput microscopy and AI. Genetic variations inducing marked morphological variation can be readily identified, allowing for the gene-based dissection of loci associated with complex traits. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Induced pluripotent stem cell derived pericytes respond to mediators of proliferation and contractility.

BACKGROUND: Pericytes are multifunctional contractile cells that reside on capillaries. Pericytes are critical regulators of cerebral blood flow and blood-brain barrier function, and pericyte dysfunction may contribute to the pathophysiology of human neurological diseases including Alzheimers disease, multiple sclerosis, and stroke. Induced pluripotent stem cell (iPSC)-derived pericytes (iPericytes) are a promising tool for vascular research. However, it is unclear how iPericytes functionally compare to primary human brain vascular pericytes (HBVPs). METHODS: We differentiated iPSCs into iPericytes of either the mesoderm or neural crest lineage using established protocols. We compared iPericyte and HBVP morphologies, quantified gene expression by qPCR and bulk RNA sequencing, and visualised pericyte protein markers by immunocytochemistry. To determine whether the gene expression of neural crest iPericytes, mesoderm iPericytes or HBVPs correlated with their functional characteristics in vitro, we quantified EdU incorporation following exposure to the key pericyte mitogen, platelet derived growth factor (PDGF)-BB and, contraction and relaxation in response to the vasoconstrictor endothelin-1 or vasodilator adenosine, respectively. RESULTS: iPericytes were morphologically similar to HBVPs and expressed canonical pericyte markers. However, iPericytes had 1864 differentially expressed genes compared to HBVPs, while there were 797 genes differentially expressed between neural crest and mesoderm iPericytes. Consistent with the ability of HBVPs to respond to PDGF-BB signalling, PDGF-BB enhanced and a PDGF receptor-beta inhibitor impaired iPericyte proliferation. Administration of endothelin-1 led to iPericyte contraction and adenosine led to iPericyte relaxation, of a magnitude similar to the response evoked in HBVPs. We determined that neural crest iPericytes were less susceptible to PDGFR beta inhibition, but responded most robustly to vasoconstrictive mediators. CONCLUSIONS: iPericytes express pericyte-associated genes and proteins and, exhibit an appropriate physiological response upon exposure to a key endogenous mitogen or vasoactive mediators. Therefore, the generation of functional iPericytes would be suitable for use in future investigations exploring pericyte function or dysfunction in neurological diseases.

Patient experiences and perceived value of genetic testing in inherited retinal diseases: a cross-sectional survey.

This study evaluated patient experiences with genetic testing for inherited retinal diseases (IRDs) and the association between underlying knowledge, testing outcomes, and the perceived value of the results. An online survey was distributed to adults with IRDs and parents/guardians of dependents with IRDs who had had genetic testing. Data included details of genetic testing, pre- and post- test perceptions, Decision Regret Scale, perceived value of results, and knowledge of gene therapy. Of 135 responses (85% from adults with IRDs), genetic testing was primarily conducted at no charge through public hospitals (49%) or in a research setting (30%). Key motivations for genetic testing were to confirm IRD diagnosis and to contribute towards research. Those who had received a genetic diagnosis (odds ratio: 6.71; p < 0.001) and those self-reported to have good knowledge of gene therapy (odds ratio: 2.69; p = 0.018) were more likely to have gained confidence in managing their clinical care. For over 80% of respondents, knowing the causative gene empowered them to learn more about their IRD and explore opportunities regarding clinical trials. Key genetic counselling information needs include resources for family communications, structured information provision, and ongoing genetic support, particularly in the context of emerging ocular therapies, to enhance consistency in information uptake.

Wnt dose escalation during the exit from pluripotency identifies tranilast as a regulator of cardiac mesoderm.

Wnt signaling is a critical determinant of cell lineage development. This study used Wnt dose-dependent induction programs to gain insights into molecular regulation of stem cell differentiation. We performed single-cell RNA sequencing of hiPSCs responding to a dose escalation protocol with Wnt agonist CHIR-99021 during the exit from pluripotency to identify cell types and genetic activity driven by Wnt stimulation. Results of activated gene sets and cell types were used to build a multiple regression model that predicts the efficiency of cardiomyocyte differentiation. Cross-referencing Wnt-associated gene expression profiles to the Connectivity Map database, we identified the small-molecule drug, tranilast. We found that tranilast synergistically activates Wnt signaling to promote cardiac lineage differentiation, which we validate by in vitro analysis of hiPSC differentiation and in vivo analysis of developing quail embryos. Our study provides an integrated workflow that links experimental datasets, prediction models, and small-molecule databases to identify drug-like compounds that control cell differentiation.

High throughput functional profiling of genes at intraocular pressure loci reveals distinct networks for glaucoma.

INTRODUCTION: Primary open angle glaucoma (POAG) is a leading cause of blindness globally. Characterized by progressive retinal ganglion cell degeneration, the precise pathogenesis remains unknown. Genome-wide association studies (GWAS) have uncovered many genetic variants associated with elevated intraocular pressure (IOP), one of the key risk factors for POAG. We aimed to identify genetic and morphological variation that can be attributed to trabecular meshwork cell (TMC) dysfunction and raised IOP in POAG. METHODS: 62 genes across 55 loci were knocked-out in a primary human TMC line. Each knockout group, including five non-targeting control groups, underwent single-cell RNA-sequencing (scRNA-seq) for differentially-expressed gene (DEG) analysis. Multiplexed fluorescence coupled with CellProfiler image analysis allowed for single-cell morphological profiling. RESULTS: Many gene knockouts invoked DEGs relating to matrix metalloproteinases and interferon-induced proteins. We have prioritized genes at four loci of interest to identify gene knockouts that may contribute to the pathogenesis of POAG, including ANGPTL2, LMX1B, CAV1, and KREMEN1. Three genetic networks of gene knockouts with similar transcriptomic profiles were identified, suggesting a synergistic function in trabecular meshwork cell physiology. TEK knockout caused significant upregulation of nuclear granularity on morphological analysis, while knockout of TRIOBP, TMCO1 and PLEKHA7 increased granularity and intensity of actin and the cell-membrane. CONCLUSION: High-throughput analysis of cellular structure and function through multiplex fluorescent single-cell analysis and scRNA-seq assays enabled the direct study of genetic perturbations at the single-cell resolution. This work provides a framework for investigating the role of genes in the pathogenesis of glaucoma and heterogenous diseases with a strong genetic basis.

Genome-Wide Meta-analysis Identifies Risk Loci and Improves Disease Prediction of Age-Related Macular Degeneration.

PURPOSE: To identify age-related macular degeneration (AMD) risk loci and to establish a polygenic prediction model. DESIGN: Genome-wide association study (GWAS) and polygenic risk score (PRS) construction. PARTICIPANTS: We included 64 885 European patients with AMD and 568 740 control participants (with overlapped samples) in the UK Biobank, Genetic Epidemiology Research on Aging (GERA), International AMD Consortium, FinnGen, and published early AMD GWASs in meta-analyses, as well as 733 European patients with AMD and 20 487 control participants from the Canadian Longitudinal Study on Aging (CLSA) and non-Europeans from the UK Biobank and GERA for polygenic risk score validation. METHODS: A multitrait meta-analysis of GWASs comprised 64 885 patients with AMD and 568 740 control participants; the multitrait approach accounted for sample overlap. We constructed a PRS for AMD based on both previously reported as well as unreported AMD loci. We applied the PRS to nonoverlapping data from the CLSA. MAIN OUTCOME MEASURES: We identified several single nucleotide polymorphisms associated with AMD and established a PRS for AMD risk prediction. RESULTS: We identified 63 AMD risk loci alongside the well-established AMD loci CFH and ARMS2, including 9 loci that were not reported in previous GWASs, some of which previously were linked to other eye diseases such as glaucoma (e.g., HIC1). We applied our PRS to nonoverlapping data from the CLSA. A new PRS was constructed using the PRS method, PRS-CS, and significantly improved the prediction accuracy of AMD risk compared with PRSs from previously published datasets. We further showed that even people who carry all the well-known AMD risk alleles at CFH and ARMS2 vary considerably in their AMD risk (ranging from close to 0 in individuals with low PRS to > 50% in individuals with high PRS). Although our PRS was derived in individuals of European ancestry, the PRS shows potential for predicting risk in people of East Asian, South Asian, and Latino ancestry. CONCLUSIONS: Our findings improve the knowledge of the genetic architecture of AMD and help achieve better accuracy in AMD prediction. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Genetic risk of glaucoma is associated with vascular and retinal nerve fibre wedge defects.

PURPOSE: To evaluate the association between localised vascular and retinal nerve fibre layer (RNFL) loss and genetic risk for glaucoma and cardiovascular disease using polygenic risk scores (PRS). METHODS: 858 eyes were included from 455 individuals with suspect and early manifest primary open angle glaucoma. Eyes were characterised as having localised vascular and/or RNFL wedge-shaped defects by scrutiny of optical coherence tomography angiography (OCTA) and OCT images, respectively. Investigations included associations with pre-established scores for genetic risk of glaucoma and cardiovascular disease in the context of glaucoma risk factors and systemic vascular disease outcomes. RESULTS: Higher genetic risk for glaucoma was associated with both vascular wedge defects and RNFL defects (p < 0.001 and p = 0.020, respectively). A greater genetic risk of glaucoma was associated with the presence of multiple vascular wedges per eye (p = 0.005). Glaucoma progression based on global RNFL loss was associated with vascular and RNFL wedge defects (p ≤ 0.001 and p = 0.008, respectively). The glaucoma PRS was significantly associated with vascular, but not RNFL, wedge defects after controlling for disc haemorrhage (p = 0.007 and p = 0.070, respectively). Vascular wedge defects were not related to the cardiovascular PRS. CONCLUSION: Individuals with a higher genetic risk of glaucoma based on the PRS were more likely to have retinal vascular defects, as well as structural glaucomatous loss, but this did not relate to systemic cardiovascular risk. This possibly implies a local pathophysiology for the vascular defects in some cases, which may have clinical relevance in the early stages of glaucoma and in individuals at high genetic risk.

The landscape of genomic structural variation in Indigenous Australians.

Indigenous Australians harbour rich and unique genomic diversity. However, Aboriginal and Torres Strait Islander ancestries are historically under-represented in genomics research and almost completely missing from reference datasets1-3. Addressing this representation gap is critical, both to advance our understanding of global human genomic diversity and as a prerequisite for ensuring equitable outcomes in genomic medicine. Here we apply population-scale whole-genome long-read sequencing4 to profile genomic structural variation across four remote Indigenous communities. We uncover an abundance of large insertion-deletion variants (20-49 bp; n = 136,797), structural variants (50 b-50 kb; n = 159,912) and regions of variable copy number (>50 kb; n = 156). The majority of variants are composed of tandem repeat or interspersed mobile element sequences (up to 90%) and have not been previously annotated (up to 62%). A large fraction of structural variants appear to be exclusive to Indigenous Australians (12% lower-bound estimate) and most of these are found in only a single community, underscoring the need for broad and deep sampling to achieve a comprehensive catalogue of genomic structural variation across the Australian continent. Finally, we explore short tandem repeats throughout the genome to characterize allelic diversity at 50 known disease loci5, uncover hundreds of novel repeat expansion sites within protein-coding genes, and identify unique patterns of diversity and constraint among short tandem repeat sequences. Our study sheds new light on the dimensions and dynamics of genomic structural variation within and beyond Australia.

AAV capsid bioengineering in primary human retina models.

Adeno-associated viral (AAV) vector-mediated retinal gene therapy is an active field of both pre-clinical as well as clinical research. As with other gene therapy clinical targets, novel bioengineered AAV variants developed by directed evolution or rational design to possess unique desirable properties, are entering retinal gene therapy translational programs. However, it is becoming increasingly evident that predictive preclinical models are required to develop and functionally validate these novel AAVs prior to clinical studies. To investigate if, and to what extent, primary retinal explant culture could be used for AAV capsid development, this study performed a large high-throughput screen of 51 existing AAV capsids in primary human retina explants and other models of the human retina. Furthermore, we applied transgene expression-based directed evolution to develop novel capsids for more efficient transduction of primary human retina cells and compared the top variants to the strongest existing benchmarks identified in the screening described above. A direct side-by-side comparison of the newly developed capsids in four different in vitro and ex vivo model systems of the human retina allowed us to identify novel AAV variants capable of high transgene expression in primary human retina cells.

WITHDRAWN: Genome-wide risk prediction of primary open-angle glaucoma across multiple ancestries.

This manuscript has been withdrawn by medRxiv following a formal request by the QIMR Berghofer Medical Research Institute Research Integrity Office owing to lack of author consent.

Universal cell donor lines: A review of the current research.

Human embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) hold promise for transplantation medicine. Diverse human leukocyte antigen (HLA) profiles necessitate autologous cells or multiple cell lines for therapeutics, incurring time and cost. Advancements in CRISPR-Cas9 and cellular therapies have led to the conceptualization of "off-the-shelf" universal cell donor lines, free of immune rejection. Overcoming immune rejection is a challenge. This review outlines strategies to modulate the major histocompatibility complex (MHC) to generate a universal cell donor line. Upon bypassing MHC mismatch, multifaceted approaches are required to generate foreign host-tolerated cells. Universal cells harbor risks, namely immune escape and tumor formation. To mitigate, we review safety mechanisms enabling donor cell inactivation or removal. Achieving a universal cell line would reduce treatment wait time, eliminate donor search, and reduce graft-versus-host disease risk without immunosuppression. The pursuit of universally tolerated cells is under way, ready to transform transplantation and regenerative medicine.

A semi-automated pipeline for quantifying drusen-like deposits in human induced pluripotent stem cell-derived retinal pigment epithelium cells.

Age-Related Macular Degeneration (AMD) is a highly prevalent form of retinal disease amongst Western communities over 50 years of age. A hallmark of AMD pathogenesis is the accumulation of drusen underneath the retinal pigment epithelium (RPE), a biological process also observable in vitro. The accumulation of drusen has been shown to predict the progression to advanced AMD, making accurate characterisation of drusen in vitro models valuable in disease modelling and drug development. More recently, deposits above the RPE in the subretinal space, called reticular pseudodrusen (RPD) have been recognized as a sub-phenotype of AMD. While in vitro imaging techniques allow for the immunostaining of drusen-like deposits, quantification of these deposits often requires slow, low throughput manual counting of images. This further lends itself to issues including sampling biases, while ignoring critical data parameters including volume and precise localization. To overcome these issues, we developed a semi-automated pipeline for quantifying the presence of drusen-like deposits in vitro, using RPE cultures derived from patient-specific induced pluripotent stem cells (iPSCs). Using high-throughput confocal microscopy, together with three-dimensional reconstruction, we developed an imaging and analysis pipeline that quantifies the number of drusen-like deposits, and accurately and reproducibly provides the location and composition of these deposits. Extending its utility, this pipeline can determine whether the drusen-like deposits locate to the apical or basal surface of RPE cells. Here, we validate the utility of this pipeline in the quantification of drusen-like deposits in six iPSCs lines derived from patients with AMD, following their differentiation into RPE cells. This pipeline provides a valuable tool for the in vitro modelling of AMD and other retinal disease, and is amenable to mid and high throughput screenings.

Study profile: the Genetics of Glaucoma Study.

PURPOSE: Glaucoma, a major cause of irreversible blindness, is a highly heritable human disease. Currently, the majority of the risk genes for glaucoma are unknown. We established the Genetics of Glaucoma Study (GOGS) to identify disease genes and improve genetic prediction of glaucoma risk and response to treatment. PARTICIPANTS: More than 5700 participants with glaucoma or a family history of glaucoma were recruited through a media campaign and the Australian Government healthcare service provider, Services Australia, making GOGS one of the largest genetic studies of glaucoma globally. The mean age of the participants was 65.30±9.36 years, and 62% were female. Participants completed a questionnaire obtaining information about their glaucoma-related medical history such as family history, glaucoma status and subtypes, surgical procedures, and prescriptions. The questionnaire also obtained information about other eye and systemic diseases. Approximately 80% of the participants provided a DNA sample and ~70% consented to data linkage to their Australian Government Medicare and Pharmaceutical Benefits Scheme schedules. FINDINGS TO DATE: 4336 GOGS participants reported that an optometrist or ophthalmologist has diagnosed them with glaucoma and 3639 participants reported having a family history of glaucoma. The vast majority of the participants (N=4393) had used at least one glaucoma-related medication; latanoprost was the most commonly prescribed drug (54% of the participants who had a glaucoma prescription). A subset of the participants reported a surgical treatment for glaucoma including a laser surgery in 2008 participants and a non-laser operation in 803 participants. Several comorbid eye and systemic diseases were also observed; the most common reports were ocular hypertension (53% of the participants), cataract (48%), hypertension (40%), nearsightedness (31%), astigmatism (22%), farsightedness (16%), diabetes (12%), sleep apnoea (11%) and migraines (10%). FUTURE PLANS: GOGS will contribute to the global gene-mapping efforts as one of the largest genetic studies for glaucoma. We will also use GOGS to develop or validate genetic risk prediction models to stratify glaucoma risk, particularly in individuals with a family history of glaucoma, and to predict clinical outcomes (eg, which medication works better for an individual and whether glaucoma surgery is required). GOGS will also help us answer various research questions about genetic overlap and causal relationships between glaucoma and its comorbidities.

Distribution of Axial Length in Australians of Different Age Groups, Ethnicities, and Refractive Errors.

Purpose: Treatments are available to slow myopic axial elongation. Understanding normal axial length (AL) distributions will assist clinicians in choosing appropriate treatment for myopia. We report the distribution of AL in Australians of different age groups and refractive errors. Methods: Retrospectively collected spherical equivalent refraction (SER) and AL data of 5938 individuals aged 5 to 89 years from 8 Australian studies were included. Based on the SER, participants were classified as emmetropes, myopes, and hyperopes. Two regression model parameterizations (piece-wise and restricted cubic splines [RCS]) were applied to the cross-sectional data to analyze the association between age and AL. These results were compared with longitudinal data from the Raine Study where the AL was measured at age 20 (baseline) and 28 years. Results: A piece-wise regression model (with 1 knot) showed that myopes had a greater increase in AL before 18 years by 0.119 mm/year (P < 0.001) and after 18 years by 0.011 mm/year (P < 0.001) compared to emmetropes and hyperopes, with the RCS model (with 3 knots) showing similar results. The longitudinal data from the Raine Study revealed that, when compared to emmetropes, only myopes showed a significant change in the AL in young adulthood (by 0.016 mm/year, P < 0.001). Conclusions: The AL of myopic eyes increases more rapidly in childhood and slightly in early adulthood. Further studies of longitudinal changes in AL, particularly in childhood, are required to guide myopia interventions. Translational Relevance: The axial length of myopic eyes increases rapidly in childhood, and there is a minimal increase in the axial length in non-myopic eyes after 18 years of age.