A multi-omics atlas of the human retina at single-cell resolution

Intravitreal MPTP drives retinal ganglion cell loss with oral nicotinamide treatment providing robust neuroprotection

Neurodegenerative diseases have common underlying pathological mechanisms including progressive neuronal dysfunction, axonal and dendritic retraction, and mitochondrial dysfunction resulting in neuronal death. The retina is often affected in common neurodegenerative diseases such as Parkinson's and Alzheimer's disease. Studies have demonstrated that the retina in patients with Parkinson's disease undergoes changes that parallel the dysfunction in the brain. These changes classically include decreased levels of dopamine, accumulation of alpha-synuclein in the brain and retina, and death of dopaminergic nigral neurons and retinal amacrine cells leading to gross neuronal loss. Exploring this disease's retinal phenotype and vision-related symptoms is an important window for elucidating its pathophysiology and progression, and identifying novel ways to diagnose and treat Parkinson's disease. 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is commonly used to model Parkinson's disease in animal models. MPTP is a neurotoxin converted to its toxic form by astrocytes, transported to neurons through the dopamine transporter, where it causes mitochondrial Complex I inhibition and neuron degeneration. Systemic administration of MPTP induces retinal changes in different animal models. In this study, we assessed the effects of MPTP on the retina directly via intravitreal injection in mice (5 mg/mL and 50 mg/mL to 7, 14 and 21 days post-injection). MPTP treatment induced the reduction of retinal ganglion cells-a sensitive neuron in the retina-at all time points investigated. This occurred without a concomitant loss of dopaminergic amacrine cells or neuroinflammation at any of the time points or concentrations tested. The observed neurodegeneration which initially affected retinal ganglion cells indicated that this method of MPTP administration could yield a fast and straightforward model of retinal ganglion cell neurodegeneration. To assess whether this model could be amenable to neuroprotection, mice were treated orally with nicotinamide (a nicotinamide adenine dinucleotide precursor) which has been demonstrated to be neuroprotective in several retinal ganglion cell injury models. Nicotinamide was strongly protective following intravitreal MPTP administration, further supporting intravitreal MPTP use as a model of retinal ganglion cell injury. As such, this model could be utilized for testing neuroprotective treatments in the context of Parkinson's disease and retinal ganglion cell injury.

ICARUS v3, a massively scalable web server for single-cell RNA-seq analysis of millions of cells

MOTIVATION

In recent years, improvements in throughput of single-cell RNA-seq have resulted in a significant increase in the number of cells profiled. The generation of single-cell RNA-seq datasets comprising >1 million cells is becoming increasingly common, giving rise to demands for more efficient computational workflows.

RESULTS

We present an update to our single-cell RNA-seq analysis web server application, ICARUS (available at https://launch.icarus-scrnaseq.cloud.edu.au) that allows effective analysis of large-scale single-cell RNA-seq datasets. ICARUS v3 utilizes the geometric cell sketching method to subsample cells from the overall dataset for dimensionality reduction and clustering that can be then projected to the large dataset. We then extend this functionality to select a representative subset of cells for downstream data analysis applications including differential expression analysis, gene co-expression network construction, gene regulatory network construction, trajectory analysis, cell-cell communication inference, and cell cluster associations to GWAS traits. We demonstrate analysis of single-cell RNA-seq datasets using ICARUS v3 of 1.3 million cells completed within the hour.

AVAILABILITY AND IMPLEMENTATION

ICARUS is available at https://launch.icarus-scrnaseq.cloud.edu.au.

Glial Cell Activation and Immune Responses in Glaucoma: A Systematic Review of Human Postmortem Studies of the Retina and Optic Nerve

Although researched extensively the understanding regarding mechanisms underlying glaucoma pathogenesis remains limited. Further, the exact mechanism behind neuronal death remains elusive. The role of neuroinflammation in retinal ganglion cell (RGC) death has been prominently theorised. This review provides a comprehensive summary of neuroinflammatory responses in glaucoma. A systematic search of Medline and Embase for articles published up to 8th March 2023 yielded 32 studies using post-mortem tissues from glaucoma patients. The raw data were extracted from tables and text to calculate the standardized mean differences (SMDs). These studies utilized post-mortem tissues from glaucoma patients, totalling 490 samples, compared with 380 control samples. Among the included studies, 27 reported glial cell activation based on changes to cellular morphology and molecular staining. Molecular changes were predominantly attributed to astrocytes (62.5%) and microglia (15.6%), with some involvement of Muller cells. These glial cell changes included amoeboid microglial cells with increased CD45 or HLA-DR intensity and hypertrophied astrocytes with increased glial fibrillary acidic protein labelling. Further, changes to extracellular matrix proteins like collagen, galectin, and tenascin-C suggested glial cells' influence on structural changes in the optic nerve head. The activation of DAMPs-driven immune response and the classical complement cascade was reported and found to be associated with activated glial cells in glaucomatous tissue. Increased pro-inflammatory markers such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) were also linked to glial cells. Glial cell activation was also associated with mitochondrial, vascular, metabolic and antioxidant component disruptions. Association of the activated glial cells with pro-inflammatory responses, dysregulation of homeostatic components and antigen presentation indicates that glial cell responses influence glaucoma progression. However, the exact mechanism triggering these responses and underlying interactions remains unexplored. This necessitates further research using human samples for an increased understanding of the precise role of neuroinflammation in glaucoma progression.

Genome-wide association identifies novel ROP risk loci in a multiethnic cohort

We conducted a genome-wide association study (GWAS) in a multiethnic cohort of 920 at-risk infants for retinopathy of prematurity (ROP), a major cause of childhood blindness, identifying 1 locus at genome-wide significance level (p < 5×10-8) and 9 with significance of p < 5×10-6 for ROP ≥ stage 3. The most significant locus, rs2058019, reached genome-wide significance within the full multiethnic cohort (p = 4.96×10-9); Hispanic and European Ancestry infants driving the association. The lead single nucleotide polymorphism (SNP) falls in an intronic region within the Glioma-associated oncogene family zinc finger 3 (GLI3) gene. Relevance for GLI3 and other top-associated genes to human ocular disease was substantiated through in-silico extension analyses, genetic risk score analysis and expression profiling in human donor eye tissues. Thus, we identify a novel locus at GLI3 with relevance to retinal biology, supporting genetic susceptibilities for ROP risk with possible variability by race and ethnicity.

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.

Patterns of Gene Expression, Splicing, and Allele-Specific Expression Vary among Macular Tissues and Clinical Stages of Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is a leading cause of blindness, and elucidating its underlying disease mechanisms is vital to the development of appropriate therapeutics. We identified differentially expressed genes (DEGs) and differentially spliced genes (DSGs) across the clinical stages of AMD in disease-affected tissue, the macular retina pigment epithelium (RPE)/choroid and the macular neural retina within the same eye. We utilized 27 deeply phenotyped donor eyes (recovered within a 6 h postmortem interval time) from Caucasian donors (60-94 years) using a standardized published protocol. Significant findings were then validated in an independent set of well-characterized donor eyes (n = 85). There was limited overlap between DEGs and DSGs, suggesting distinct mechanisms at play in AMD pathophysiology. A greater number of previously reported AMD loci overlapped with DSGs compared to DEGs between disease states, and no DEG overlap with previously reported loci was found in the macular retina between disease states. Additionally, we explored allele-specific expression (ASE) in coding regions of previously reported AMD risk loci, uncovering a significant imbalance in C3 rs2230199 and CFH rs1061170 in the macular RPE/choroid for normal eyes and intermediate AMD (iAMD), and for CFH rs1061147 in the macular RPE/choroid for normal eyes and iAMD, and separately neovascular AMD (NEO). Only significant DEGs/DSGs from the macular RPE/choroid were found to overlap between disease states. STAT1, validated between the iAMD vs. normal comparison, and AGTPBP1, BBS5, CERKL, FGFBP2, KIFC3, RORα, and ZNF292, validated between the NEO vs. normal comparison, revealed an intricate regulatory network with transcription factors and miRNAs identifying potential upstream and downstream regulators. Findings regarding the complement genes C3 and CFH suggest that coding variants at these loci may influence AMD development via an imbalance of gene expression in a tissue-specific manner. Our study provides crucial insights into the multifaceted genomic underpinnings of AMD (i.e., tissue-specific gene expression changes, potential splice variation, and allelic imbalance), which may open new avenues for AMD diagnostics and therapies specific to iAMD and NEO.

Integrated multi-omics single cell atlas of the human retina

Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here, we present an integrated multimodal reference atlas of the most accessible portion of the mammalian central nervous system, the retina. We compiled around 2.4 million cells from 55 donors, including 1.4 million unpublished data points, to create a comprehensive human retina cell atlas (HRCA) of transcriptome and chromatin accessibility, unveiling over 110 types. Engaging the retina community, we annotated each cluster, refined the Cell Ontology for the retina, identified distinct marker genes, and characterized cis-regulatory elements and gene regulatory networks (GRNs) for these cell types. Our analysis uncovered intriguing differences in transcriptome, chromatin, and GRNs across cell types. In addition, we modeled changes in gene expression and chromatin openness across gender and age. This integrated atlas also enabled the fine-mapping of GWAS and eQTL variants. Accessible through interactive browsers, this multimodal cross-donor and cross-lab HRCA, can facilitate a better understanding of retinal function and pathology.

DeMixSC: a deconvolution framework that uses single-cell sequencing plus a small benchmark dataset for improved analysis of cell-type ratios in complex tissue samples

Bulk deconvolution with single-cell/nucleus RNA-seq data is critical for understanding heterogeneity in complex biological samples, yet the technological discrepancy across sequencing platforms limits deconvolution accuracy. To address this, we introduce an experimental design to match inter-platform biological signals, hence revealing the technological discrepancy, and then develop a deconvolution framework called DeMixSC using the better-matched, i.e., benchmark, data. Built upon a novel weighted nonnegative least-squares framework, DeMixSC identifies and adjusts genes with high technological discrepancy and aligns the benchmark data with large patient cohorts of matched-tissue-type for large-scale deconvolution. Our results using a benchmark dataset of healthy retinas suggest much-improved deconvolution accuracy. Further analysis of a cohort of 453 patients with age-related macular degeneration supports the broad applicability of DeMixSC. Our findings reveal the impact of technological discrepancy on deconvolution performance and underscore the importance of a well-matched dataset to resolve this challenge. The developed DeMixSC framework is generally applicable for deconvolving large cohorts of disease tissues, and potentially cancer.

Human retinal ganglion cell neurons generated by synchronous BMP inhibition and transcription factor mediated reprogramming

In optic neuropathies, including glaucoma, retinal ganglion cells (RGCs) die. Cell transplantation and endogenous regeneration offer strategies for retinal repair, however, developmental programs required for this to succeed are incompletely understood. To address this, we explored cellular reprogramming with transcription factor (TF) regulators of RGC development which were integrated into human pluripotent stem cells (PSCs) as inducible gene cassettes. When the pioneer factor NEUROG2 was combined with RGC-expressed TFs (ATOH7, ISL1, and POU4F2) some conversion was observed and when pre-patterned by BMP inhibition, RGC-like induced neurons (RGC-iNs) were generated with high efficiency in just under a week. These exhibited transcriptional profiles that were reminiscent of RGCs and exhibited electrophysiological properties, including AMPA-mediated synaptic transmission. Additionally, we demonstrated that small molecule inhibitors of DLK/LZK and GCK-IV can block neuronal death in two pharmacological axon injury models. Combining developmental patterning with RGC-specific TFs thus provided valuable insight into strategies for cell replacement and neuroprotection.

Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data

Advances in single-cell RNA sequencing (scRNA-seq) techniques have accelerated functional interpretation of disease-associated variants discovered from genome-wide association studies (GWASs). However, identification of trait-relevant cell populations is often impeded by inherent technical noise and high sparsity in scRNA-seq data. Here, we developed scPagwas, a computational approach that uncovers trait-relevant cellular context by integrating pathway activation transformation of scRNA-seq data and GWAS summary statistics. scPagwas effectively prioritizes trait-relevant genes, which facilitates identification of trait-relevant cell types/populations with high accuracy in extensive simulated and real datasets. Cellular-level association results identified a novel subpopulation of naive CD8+ T cells related to COVID-19 severity and oligodendrocyte progenitor cell and microglia subsets with critical pathways by which genetic variants influence Alzheimer's disease. Overall, our approach provides new insights for the discovery of trait-relevant cell types and improves the mechanistic understanding of disease variants from a pathway perspective.