Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE137847 | GEO | 2019/09/23

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration.

Project description:Genome-wide association studies (GWAS) have identified genetic variants associated with age-related macular degeneration (AMD), one of the leading causes of blindness in the elderly. However, it has been challenging to identify the cell types associated with AMD given the genetic complexity of the disease. Here we perform massively parallel single-cell RNA sequencing (scRNA-seq) of human retinas using two independent platforms, and report the first single-cell transcriptomic atlas of the human retina. Using a multi-resolution network-based analysis, we identify all major retinal cell types, and their corresponding gene expression signatures. Heterogeneity is observed within macroglia, suggesting that human retinal glia are more diverse than previously thought. Finally, GWAS-based enrichment analysis identifies glia, vascular cells, and cone photoreceptors to be associated with the risk of AMD. These data provide a detailed analysis of the human retina, and show how scRNA-seq can provide insight into cell types involved in complex, inflammatory genetic diseases.

| S-EPMC6814749 | biostudies-literature

Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration [Microfluidics]

Project description:Here we perform massively parallel single-cell RNA sequencing (scRNA-seq) of human retinas using two independent platforms, and report the single-cell transcriptomic atlas of the human retina. Using a multi-resolution network-based analysis, we identify all major retinal cell types, and their corresponding gene expression signatures.

2019-09-21 | GSE137537 | GEO

Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration [Seq-Well]

2019-09-23 | GSE137846 | GEO

Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration

Project description:Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration

| PRJNA573654 | ENA

Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration [Microfluidics]

Project description:Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration [Microfluidics]

| PRJNA565928 | ENA

Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration [Seq-Well]

Project description:Single-cell Transcriptomic Atlas of the Human Retina Identifies Cell Types Associated with Age-Related Macular Degeneration [Seq-Well]

| PRJNA573659 | ENA

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

Project description: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.

| S-EPMC10912779 | biostudies-literature

Transcriptomic and proteomic retinal pigment epithelium signatures of age-related macular degeneration

Project description:To identify disease-specific transcriptional programs in retinal pigment epithelium (RPE) cells, fibroblasts from 43 patients with geographic atrophy (GA) were reprogrammed into induced pluripotent stem cells (iPSCs) before being differentiated into RPE and compared to those from 36 healthy individuals. 127,659 RPE cells were profiled via single cell RNA-sequencing (scRNA-seq) and cell classification identified 7 cellular states related to RPE maturation.

2022-06-20 | E-MTAB-11642 | biostudies-arrayexpress

Transcriptomic and proteomic retinal pigment epithelium signatures of age-related macular degeneration.

Project description:Induced pluripotent stem cells generated from patients with geographic atrophy as well as healthy individuals were differentiated to retinal pigment epithelium (RPE) cells. By integrating transcriptional profiles of 127,659 RPE cells generated from 43 individuals with geographic atrophy and 36 controls with genotype data, we identified 439 expression Quantitative Trait (eQTL) loci in cis that were associated with disease status and specific to subpopulations of RPE cells. We identified loci linked to two genes with known associations with geographic atrophy - PILRB and PRPH2, in addition to 43 genes with significant genotype x disease interactions that are candidates for novel genetic associations for geographic atrophy. On a transcriptome-only level, we identified molecular pathways significantly upregulated in geographic atrophy-RPE including in mitochondrial functions, metabolic pathways, and extracellular cellular matrix reorganisation. We subsequently implemented a large-scale proteomics analysis, confirming modification in proteins associated with these pathways. We also identified six significant protein (p) QTL that regulate protein expression in the RPE cells and in geographic atrophy - two of which share variants with cis-eQTL, including proteins involve in mitochondrial biology and neuodegeneration. Investigation of mitochondrial functions in the two cohorts confirmed a modification of respiration etc…. This study provides strong proof of concept of the validity of using iPSC for the modeling of complex diseases. It is the first to use a large scale patient -derived iPSC cohort to uncover important differences in RPE homeostasis associated with geographic atrophy. It clearly identifies mitochondrial activity as a core constitutive difference of the RPE from patients with geographic atrophy, and could be a target of potential therapies for this condition (STACEY/MATT).

2022-06-01 | PXD029501 | Pride

Single-cell RNA Sequencing Identifies Natural Kill Cell-Related Transcription Factors Associated With Age-Related Macular Degeneration.

Project description:BackgroundAge-related Macular Degeneration (AMD) poses a growing global health concern as the leading cause of central vision loss in elderly people.ObjectionThis study focuses on unraveling the intricate involvement of Natural Killer (NK) cells in AMD, shedding light on their immune responses and cytokine regulatory roles.MethodsTranscriptomic data from the Gene Expression Omnibus database were utilized, employing single-cell RNA-seq analysis. High-dimensional weighted gene co-expression network analysis (hdWGCNA) and single-cell regulatory network inference and clustering (SCENIC) analysis were applied to reveal the regulatory mechanisms of NK cells in early-stage AMD patients. Machine learning models, such as random forests and decision trees, were employed to screen hub genes and key transcription factors (TFs) associated with AMD.ResultsDistinct cell clusters were identified in the present study, especially the T/NK cluster, with a notable increase in NK cell abundance observed in AMD. Cell-cell communication analyses revealed altered interactions, particularly in NK cells, indicating their potential role in AMD pathogenesis. HdWGCNA highlighted the turquoise module, enriched in inflammation-related pathways, as significantly associated with AMD in NK cells. The SCENIC analysis identified key TFs in NK cell regulatory networks. The integration of hub genes and TFs identified CREM, FOXP1, IRF1, NFKB2, and USF2 as potential predictors for AMD through machine learning.ConclusionThis comprehensive approach enhances our understanding of NK cell dynamics, signaling alterations, and potential predictive models for AMD. The identified TFs provide new avenues for molecular interventions and highlight the intricate relationship between NK cells and AMD pathogenesis. Overall, this study contributes valuable insights for advancing our understanding and management of AMD.

| S-EPMC11325330 | biostudies-literature