Emerging Approaches to Profile Accessible Chromatin from Formalin-Fixed Paraffin-Embedded Sections.

Nucleosomes are non-uniformly distributed across eukaryotic genomes, with stretches of 'open' chromatin strongly associated with transcriptionally active promoters and enhancers. Understanding chromatin accessibility patterns in normal tissue and how they are altered in pathologies can provide critical insights to development and disease. With the advent of high-throughput sequencing, a variety of strategies have been devised to identify open regions across the genome, including DNase-seq, MNase-seq, FAIRE-seq, ATAC-seq, and NicE-seq. However, the broad application of such methods to FFPE (formalin-fixed paraffin-embedded) tissues has been curtailed by the major technical challenges imposed by highly fixed and often damaged genomic material. Here, we review the most common approaches for mapping open chromatin regions, recent optimizations to overcome the challenges of working with FFPE tissue, and a brief overview of a typical data pipeline with analysis considerations.

Quantification of Fundus Autofluorescence Features in a Molecularly Characterized Cohort of More Than 3000 Inherited Retinal Disease Patients from the United Kingdom.

Purpose: To quantify relevant fundus autofluorescence (FAF) image features cross-sectionally and longitudinally in a large cohort of inherited retinal diseases (IRDs) patients. Design: Retrospective study of imaging data (55-degree blue-FAF on Heidelberg Spectralis) from patients. Participants: Patients with a clinical and molecularly confirmed diagnosis of IRD who have undergone FAF 55-degree imaging at Moorfields Eye Hospital (MEH) and the Royal Liverpool Hospital (RLH) between 2004 and 2019. Methods: Five FAF features of interest were defined: vessels, optic disc, perimacular ring of increased signal (ring), relative hypo-autofluorescence (hypo-AF) and hyper-autofluorescence (hyper-AF). Features were manually annotated by six graders in a subset of patients based on a defined grading protocol to produce segmentation masks to train an AI model, AIRDetect, which was then applied to the entire imaging dataset. Main Outcome Measures: Quantitative FAF imaging features including area in mm 2 and vessel metrics, were analysed cross-sectionally by gene and age, and longitudinally to determine rate of progression. AIRDetect feature segmentation and detection were validated with Dice score and precision/recall, respectively. Results: A total of 45,749 FAF images from 3,606 IRD patients from MEH covering 170 genes were automatically segmented using AIRDetect. Model-grader Dice scores for disc, hypo-AF, hyper-AF, ring and vessels were respectively 0.86, 0.72, 0.69, 0.68 and 0.65. The five genes with the largest hypo-AF areas were CHM , ABCC6 , ABCA4 , RDH12 , and RPE65 , with mean per-patient areas of 41.5, 30.0, 21.9, 21.4, and 15.1 mm 2 . The five genes with the largest hyper-AF areas were BEST1 , CDH23 , RDH12 , MYO7A , and NR2E3 , with mean areas of 0.49, 0.45, 0.44, 0.39, and 0.34 mm 2 respectively. The five genes with largest ring areas were CDH23 , NR2E3 , CRX , EYS and MYO7A, with mean areas of 3.63, 3.32, 2.84, 2.39, and 2.16 mm 2 . Vessel density was found to be highest in EFEMP1 , BEST1 , TIMP3 , RS1 , and PRPH2 (10.6%, 10.3%, 9.8%, 9.7%, 8.9%) and was lower in Retinitis Pigmentosa (RP) and Leber Congenital Amaurosis genes. Longitudinal analysis of decreasing ring area in four RP genes ( RPGR, USH2A, RHO, EYS ) found EYS to be the fastest progressor at -0.18 mm 2 /year. Conclusions: We have conducted the first large-scale cross-sectional and longitudinal quantitative analysis of FAF features across a diverse range of IRDs using a novel AI approach.

IQCB1 (NPHP5)-Retinopathy: Clinical and Genetic Characterization and Natural History.

PURPOSE: To describe the clinical and genetic features, and explore the natural history of retinopathy associated with IQCB1 variants in children and adults with retinopathy. DESIGN: Retrospective cohort study at a single tertiary care referral center. METHODS: The study recruited 19 patients with retinopathy, harboring likely disease-causing variants in IQCB1. Demographic data and clinical presentation, best corrected visual acuity (BCVA), fundus appearance, optical coherence tomography (OCT) and autofluorescence features, electroretinography (ERG) and molecular genetics are reported. RESULTS: Ten patients had best corrected visual acuity better than 1.0 LogMAR, and BCVA remained stable till the last review. Seven patients had a vision of hand movements or worse in at least one eye at presentation. There was no correlation found between age of onset and severity of vision loss. Nine patients (47.4%) had a diagnosis of end-stage renal failure at presentation. The other 10 patients (52.6%) had a diagnosis of non-syndromic IQCB1-retinopathy and maintained normal renal function until the last follow-up. The mean age at diagnosis of renal failure was 26.3 ±19.8 years. OCT showed ellipsoid zone (EZ) disruption with foveal sparing in 8/13 patients. All patients had stable OCT findings. Full-field ERGs in four adults revealed a severe cone-rod dystrophy and three children had extinguished ERGs. We identified 17 IQCB1 variants, all predicted to cause loss of function. CONCLUSION: IQCB1-retinopathy is a severe early-onset cone-rod dystrophy. The dissociation between severely decreased retinal function and relative preservation of retinal structure over a wide age window makes the disease a candidate for gene therapy.

Epigenetics of Genes Preferentially Expressed in Dissimilar Cell Populations: Myoblasts and Cerebellum.

While studying myoblast methylomes and transcriptomes, we found that CDH15 had a remarkable preference for expression in both myoblasts and cerebellum. To understand how widespread such a relationship was and its epigenetic and biological correlates, we systematically looked for genes with similar transcription profiles and analyzed their DNA methylation and chromatin state and accessibility profiles in many different cell populations. Twenty genes were expressed preferentially in myoblasts and cerebellum (Myob/Cbl genes). Some shared DNA hypo- or hypermethylated regions in myoblasts and cerebellum. Particularly striking was ZNF556, whose promoter is hypomethylated in expressing cells but highly methylated in the many cell populations that do not express the gene. In reporter gene assays, we demonstrated that its promoter's activity is methylation sensitive. The atypical epigenetics of ZNF556 may have originated from its promoter's hypomethylation and selective activation in sperm progenitors and oocytes. Five of the Myob/Cbl genes (KCNJ12, ST8SIA5, ZIC1, VAX2, and EN2) have much higher RNA levels in cerebellum than in myoblasts and displayed myoblast-specific hypermethylation upstream and/or downstream of their promoters that may downmodulate expression. Differential DNA methylation was associated with alternative promoter usage for Myob/Cbl genes MCF2L, DOK7, CNPY1, and ANK1. Myob/Cbl genes PAX3, LBX1, ZNF556, ZIC1, EN2, and VAX2 encode sequence-specific transcription factors, which likely help drive the myoblast and cerebellum specificity of other Myob/Cbl genes. This study extends our understanding of epigenetic/transcription associations related to differentiation and may help elucidate relationships between epigenetic signatures and muscular dystrophies or cerebellar-linked neuropathologies.

Population-Based Artificial Intelligence Assessment of Relationship Between the Risk Factors for Diabetic Retinopathy in Indian Population.

PURPOSE: Risk factors (RFs), like 'body mass index (BMI),' 'age,' and 'gender' correlate with Diabetic Retinopathy (DR) diagnosis and have been widely studied. This study examines how these three secondary RFs independently affect the predictive capacity of primary RFs. METHODS: The dataset consisted of four population-based studies on the prevalence of DR and associated RFs in India between 2001 and 2010. An Autoencoder was employed to categorize RFs as primary or secondary. This study evaluated six primary RFs coupled independently with each secondary RF on five machine-learning models. RESULTS: The secondary RF 'gender' gave a maximum increase in Area under the curve (AUC) score to predict DR when combined separately with 'insulin treatment,' 'fasting plasma glucose,' 'hypertension history,' and 'glycosylated hemoglobin' with a maximum increase in AUC for the Naive Bayes model from 0.573 to 0.646, for the Support Vector Machines (SVM) model from 0.644 to 0.691, for the SVM model from 0.487 to 0.607, and for the Decision Tree model from 0.8 to 0.848, respectively. The secondary RFs 'age' and 'BMI' gave a maximum increase in AUC score to predict DR when combined separately with 'diabetes mellitus duration' and 'systolic blood pressure,' with a maximum increase in AUC for the SVM model from 0.389 to 0.621, and for the Decision Tree model from 0.617 to 0.713, respectively. CONCLUSION: The risk factor 'gender' was the best secondary RF in predicting DR compared to 'age' and 'BMI,' increasing the predictive power of four primary RFs.

Retinopathy secondary to flare-up of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) can have widespread ocular manifestations, and posterior segment involvement may be associated with poor visual outcome. We report a clinical flare-up of SLE presenting as combined vascular occlusion in one eye and drusen-like deposits, which is a newly described entity in both eyes. As an ophthalmologist, a knowledge of such presentations helps us identify and possibly help the rheumatologist titrate treatment accordingly, to prevent severe life-threatening systemic complications.

Comparative proteomics of proliferative diabetic retinopathy in people with Type 2 diabetes highlights the role of inflammation, visual transduction, and extracellular matrix pathways.

Purpose: To explore the vitreous humor proteome from type 2 diabetes subjects with proliferative diabetic retinopathy (PDR) in the Indian population. Methods: We performed mass spectrometry-based label-free quantitative analysis of vitreous proteome of PDR (n = 13) and idiopathic macular hole (IMH; control) subjects (n = 14). Nine samples of PDR and 10 samples of IMH were pooled as case and control, respectively, and compared. Four samples each of PDR and IMH were analyzed individually without pooling to validate the results of the pooled analysis. Comparative quantification was performed using Scaffold software which calculated the fold changes of differential expression. Bioinformatics analysis was performed using DAVID and STRING software. Results: We identified 469 proteins in PDR and 517 proteins in IMH vitreous, with an overlap of 172 proteins. Also, 297 unique proteins were identified in PDR and 345 in IMH. In PDR vitreous, 37 proteins were upregulated (P < 0.05) and 19 proteins were downregulated compared to IMH. Protein distribution analysis clearly demonstrated a separation of protein expression in PDR and IMH. Significantly upregulated proteins included fibrinogen gamma chain, fibrinogen beta chain, and carbonic anhydrase 1 and downregulated proteins included alpha-1-antitrypsin, retinol-binding protein 3, neuroserpin, cystatin C, carboxypeptidase E and cathepsin-D. Conclusion: Diabetic retinopathy pathogenesis involves proteins which belong to inflammation, visual transduction, and extracellular matrix pathways. Validation-based experiments using enzyme-linked immunosorbent assay (ELISA) or western blotting are needed to establish cause and effect relationships of these proteins to the disease state, to develop them as biomarkers or drug molecules.

Machine Learning-Based Diagnosis and Ranking of Risk Factors for Diabetic Retinopathy in Population-Based Studies from South India.

This paper discusses the importance of investigating DR using machine learning and a computational method to rank DR risk factors by importance using different machine learning models. The dataset was collected from four large population-based studies conducted in India between 2001 and 2010 on the prevalence of DR and its risk factors. We deployed different machine learning models on the dataset to rank the importance of the variables (risk factors). The study uses a t-test and Shapely additive explanations (SHAP) to rank the risk factors. Then, it uses five machine learning models (K-Nearest Neighbor, Decision Tree, Support Vector Machines, Logistic Regression, and Naive Bayes) to identify the unimportant risk factors based on the area under the curve criterion to predict DR. To determine the overall significance of risk variables, a weighted average of each classifier's importance is used. The ranking of risk variables is provided to machine learning models. To construct a model for DR prediction, the combination of risk factors with the highest AUC is chosen. The results show that the risk factors glycosylated hemoglobin and systolic blood pressure were present in the top three risk factors for DR in all five machine learning models when the t-test was used for ranking. Furthermore, the risk factors, namely, systolic blood pressure and history of hypertension, were present in the top five risk factors for DR in all the machine learning models when SHAP was used for ranking. Finally, when an ensemble of the five machine learning models was employed, independently with both the t-test and SHAP, systolic blood pressure and diabetes mellitus duration were present in the top four risk factors for diabetic retinopathy. Decision Tree and K-Nearest Neighbor resulted in the highest AUCs of 0.79 (t-test) and 0.77 (SHAP). Moreover, K-Nearest Neighbor predicted DR with 82.6% (t-test) and 78.3% (SHAP) accuracy.

Artificial intelligence in retinal disease: clinical application, challenges, and future directions.

Retinal diseases are a leading cause of blindness in developed countries, accounting for the largest share of visually impaired children, working-age adults (inherited retinal disease), and elderly individuals (age-related macular degeneration). These conditions need specialised clinicians to interpret multimodal retinal imaging, with diagnosis and intervention potentially delayed. With an increasing and ageing population, this is becoming a global health priority. One solution is the development of artificial intelligence (AI) software to facilitate rapid data processing. Herein, we review research offering decision support for the diagnosis, classification, monitoring, and treatment of retinal disease using AI. We have prioritised diabetic retinopathy, age-related macular degeneration, inherited retinal disease, and retinopathy of prematurity. There is cautious optimism that these algorithms will be integrated into routine clinical practice to facilitate access to vision-saving treatments, improve efficiency of healthcare systems, and assist clinicians in processing the ever-increasing volume of multimodal data, thereby also liberating time for doctor-patient interaction and co-development of personalised management plans.

Profiling of idiopathic macular hole vitreous proteome identifies the role of extracellular matrix remodelling, epithelial-mesenchymal transformation and unfolded protein-response pathways.

Purpose: To analyze and describe the proteome of the vitreous humour in eyes with idiopathic macular holes. Methods: We performed mass spectrometry (MS)-based label-free quantitative analysis of the vitreous proteome of idiopathic macular hole (IMH) and control donor vitreous. Comparative quantification was performed using SCAFFOLD software which calculated fold changes of differential expression. Bioinformatics analysis was performed using DAVID and STRING software. Results: A total of 448 proteins were identified by LC-MS/MS in IMH and cadaveric eye vitreous samples, of which 199 proteins were common. IMH samples had 189 proteins that were unique and 60 proteins were present only in the control cadaveric vitreous. We found upregulation of several extracellular matrix (ECM) and cytoskeletal proteins, namely collagen alpha-1 (XVIII) chain, N-cadherin, EFEMP1/fibulin-3, basement membrane-specific heparan sulfate proteoglycan core protein, and target of Nesh-3. Several cytoskeleton proteins, namely tubulin, actin, and fibronectin levels, were significantly lower in IMH vitreous, probably reflecting increased ECM degradation. IMH vitreous also had a downregulation of unfolded protein response-mediated-mediated apoptosis proteins, possibly related to a state of increased cell survival and proliferation, along with a remodelling and aberrant production of ECM contents. Conclusion: The pathogenesis of macular holes may involve ECM remodelling, epithelial-mesenchymal transformation, downregulation of apoptosis, protein folding defects, and complement pathway. The vitreo-retinal milieu in macular holes contain molecules related to both ECM degradation and inhibition of the same, thereby maintaining a homeostasis.

Can artificial intelligence accelerate the diagnosis of inherited retinal diseases? Protocol for a data-only retrospective cohort study (Eye2Gene).

INTRODUCTION: Inherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over 300 genes have been found to be associated with IRDs and identifying the affected gene in patients by molecular genetic testing is the first step towards effective care and patient management. However, genetic diagnosis is currently slow, expensive and not widely accessible. The aim of the current project is to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service. METHODS AND ANALYSIS: The data-only retrospective cohort study involves a target sample size of 10 000 participants, which has been derived based on the number of participants with IRD at three leading UK eye hospitals: Moorfields Eye Hospital (MEH), Oxford University Hospital (OUH) and Liverpool University Hospital (LUH), as well as a Japanese hospital, the Tokyo Medical Centre (TMC). Eye2Gene aims to predict causative genes from retinal images of patients with a diagnosis of IRD. For this purpose, 36 most common causative IRD genes have been selected to develop a training dataset for the software to have enough examples for training and validation for detection of each gene. The Eye2Gene algorithm is composed of multiple deep convolutional neural networks, which will be trained on MEH IRD datasets, and externally validated on OUH, LUH and TMC. ETHICS AND DISSEMINATION: This research was approved by the IRB and the UK Health Research Authority (Research Ethics Committee reference 22/WA/0049) 'Eye2Gene: accelerating the diagnosis of IRDs' Integrated Research Application System (IRAS) project ID: 242050. All research adhered to the tenets of the Declaration of Helsinki. Findings will be reported in an open-access format.

Microbiological Profile of Post-cataract Surgery Endophthalmitis with Usage of Prophylactic Intracameral Moxifloxacin.

PURPOSE: To study the effect of prophylactic intracameral moxifloxacin (ICM) on microbiological profile and antimicrobial sensitivity of culture-proven postoperative endophthalmitis (POE). METHODS: This study evaluated culture-proven POE diagnosed within 6 weeks of cataract surgery over two periods, period-1 (January 2010-March 2015) and period-2 (April 2015-December 2019), before and after introduction of prophylactic ICM, respectively. RESULTS: In period-1, 100 cases of culture-positive POE were reported (1 in 4879, 0.02%), while 20 cases (1 in 24635, 0.004%) were reported in period-2 (5-fold reduction, p < .001). The cumulative culture positivity rate decreased from 27.6% to 17.1% (1.6-fold) . Coagulase-negative Staphylococci (CoNS) were significantly reduced (p = .005). CONCLUSIONS: ICM reduced the incidence of culture-proven POE, CoNS in particular. In future, POE caused by rarer pathogens may become more prevalent due to reduction in the rate of commoner and more virulent pathogens with use of intracameral antibiotics. The moxifloxacin sensitivity of CONS did not show change with the use of ICM. Studies with larger population of POE will be more helpful to understand the trend better.

Perspectives of diabetic retinopathy-challenges and opportunities.

Diabetic retinopathy (DR) may lead to vision-threatening complications in people living with diabetes mellitus. Decades of research have contributed to our understanding of the pathogenesis of diabetic retinopathy from non-proliferative to proliferative (PDR) stages, the occurrence of diabetic macular oedema (DMO) and response to various treatment options. Multimodal imaging has paved the way to predict the impact of peripheral lesions and optical coherence tomography-angiography is starting to provide new knowledge on diabetic macular ischaemia. Moreover, the availability of intravitreal anti-vascular endothelial growth factors has changed the treatment paradigm of DMO and PDR. Areas of research have explored mechanisms of breakdown of the blood-retinal barrier, damage to pericytes, the extent of capillary non-perfusion, leakage and progression to neovascularisation. However, knowledge gaps remain. From this perspective, we highlight the challenges and future directions of research in this field.

Unilateral retinitis pigmentosa associated with cystoid macular oedema.

Retinitis pigmentosa (RP) is the most common inherited cause of blindness in the developed world, characterized by night blindness, reduced central vision and constricted visual field; however, unilateral RP is extremely rare. Macular complications such as cystoid macular oedema (CME), macular holes and vitreoretinal interface alterations, such as epiretinal membranes, have been reported in advanced stages. We describe a patient with unilateral RP presenting with CME, a rare occurrence.

Promoter-Adjacent DNA Hypermethylation Can Downmodulate Gene Expression: TBX15 in the Muscle Lineage.

TBX15, which encodes a differentiation-related transcription factor, displays promoter-adjacent DNA hypermethylation in myoblasts and skeletal muscle (psoas) that is absent from non-expressing cells in other lineages. By whole-genome bisulfite sequencing (WGBS) and enzymatic methyl-seq (EM-seq), these hypermethylated regions were found to border both sides of a constitutively unmethylated promoter. To understand the functionality of this DNA hypermethylation, we cloned the differentially methylated sequences (DMRs) in CpG-free reporter vectors and tested them for promoter or enhancer activity upon transient transfection. These cloned regions exhibited strong promoter activity and, when placed upstream of a weak promoter, strong enhancer activity specifically in myoblast host cells. In vitro CpG methylation targeted to the DMR sequences in the plasmids resulted in 86−100% loss of promoter or enhancer activity, depending on the insert sequence. These results as well as chromatin epigenetic and transcription profiles for this gene in various cell types support the hypothesis that DNA hypermethylation immediately upstream and downstream of the unmethylated promoter region suppresses enhancer/extended promoter activity, thereby downmodulating, but not silencing, expression in myoblasts and certain kinds of skeletal muscle. This promoter-border hypermethylation was not found in cell types with a silent TBX15 gene, and these cells, instead, exhibit repressive chromatin in and around the promoter. TBX18, TBX2, TBX3 and TBX1 display TBX15-like hypermethylated DMRs at their promoter borders and preferential expression in myoblasts. Therefore, promoter-adjacent DNA hypermethylation for downmodulating transcription to prevent overexpression may be used more frequently for transcription regulation than currently appreciated.

Poly ADP-ribosylation of SET8 leads to aberrant H4K20 methylation in mammalian nuclear genome.

In mammalian cells, SET8 mediated Histone H4 Lys 20 monomethylation (H4K20me1) has been implicated in regulating mitotic condensation, DNA replication, DNA damage response, and gene expression. Here we show SET8, the only known enzyme for H4K20me1 is post-translationally poly ADP-ribosylated by PARP1 on lysine residues. PARP1 interacts with SET8 in a cell cycle-dependent manner. Poly ADP-ribosylation on SET8 renders it catalytically compromised, and degradation via ubiquitylation pathway. Knockdown of PARP1 led to an increase of SET8 protein levels, leading to aberrant H4K20me1 and H4K20me3 domains in the genome. H4K20me1 is associated with higher gene transcription levels while the increase of H4K20me3 levels was predominant in DNA repeat elements. Hence, SET8 mediated chromatin remodeling in mammalian cells are modulated by poly ADP-ribosylation by PARP1.

Neuro-ophthalmological manifestations of diabetes mellitus during COVID-19-related lockdown in India.

Purpose: The coronavirus disease 19 (COVID-19) pandemic has resulted in a huge impact on the health care system. Diversion of health care workforce toward management of a high number of COVID-19 cases and lockdown restrictions have affected the follow-up of patients. The objective of this study was to analyze the impact of this situation on the control of diabetes, eventually resulting in related neuro-ophthalmological complications. Methods: This retrospective case series included diabetic patients visiting the neuro-ophthalmology clinic at a tertiary care eye center in India from 25 March 2020 to 25 September 2020 during the lockdown. The incidence of diabetes-related neuro-ophthalmological complications, including third, fourth, sixth nerve palsies and non-arteritic anterior ischemic optic neuropathy (NAION) was evaluated and compared with that of the same period during 2019. Results: Overall disease incidence rate was significantly higher in the year 2020 (60.2%) compared to the previous year of 2019 (29.8%). The proportion of third nerve palsy (4.8% vs 16.3%, P < 0.001) and NAION (0.3% vs 14.3%, P < 0.001) had increased. Even though the percentage of sixth nerve palsy was 25% in 2020, this was not significantly different from 2019. There was a reduction in the percentage of fourth nerve palsy cases from the year 2019 to 2020. Conclusion: There was a significant increase in diabetes-related neuro-ophthalmic complications during the COVID-19 lockdown. This can possibly be attributed to worsening of glycemic control in diabetic patients.