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Single-cell RNA sequencing in vision research: Insights into human retinal health and disease

Thu, 2020-12-31 05:00

Prog Retin Eye Res. 2020 Dec 28:100934. doi: 10.1016/j.preteyeres.2020.100934. Online ahead of print.

ABSTRACT

Gene expression provides valuable insight into cell function. As such, vision researchers have frequently employed gene expression studies to better understand retinal physiology and disease. With the advent of single-cell RNA sequencing, expression experiments provide an unparalleled resolution of information. Instead of studying aggregated gene expression across all cells in a heterogenous tissue, single-cell technology maps RNA to an individual cell, which facilitates grouping of retinal and choroidal cell types for further study. Single-cell RNA sequencing has been quickly adopted by both basic and translational vision researchers, and single-cell level gene expression has been studied in the visual systems of animal models, retinal organoids, and primary human retina, RPE, and choroid. These experiments have generated detailed atlases of gene expression and identified new retinal cell types. Likewise, single-cell RNA sequencing investigations have characterized how gene expression changes in the setting of many retinal diseases, including how choroidal endothelial cells are altered in age-related macular degeneration. In addition, this technology has allowed vision researcher to discover drivers of retinal development and model rare retinal diseases with induced pluripotent stem cells. In this review, we will overview the growing number of single-cell RNA sequencing studies in the field of vision research. We will summarize experimental considerations for designing single-cell RNA sequencing experiments and highlight important advancements in retinal, RPE, choroidal, and retinal organoid biology driven by this technology. Finally, we generalize these findings to genes involved in retinal degeneration and outline the future of single-cell expression experiments in studying retinal disease.

PMID:33383180 | DOI:10.1016/j.preteyeres.2020.100934

Predominance of hyperopia in autosomal dominant Best vitelliform macular dystrophy

Fri, 2020-11-27 05:00

Br J Ophthalmol. 2020 Nov 26:bjophthalmol-2020-317763. doi: 10.1136/bjophthalmol-2020-317763. Online ahead of print.

ABSTRACT

BACKGROUND/AIMS: Patients with BEST1-associated autosomal dominant Best vitelliform macular dystrophy (AD-BVMD) have been reported to be hyperopic, but the prevalence of refractive error has not been described. This study aimed to characterise the type and degree of refractive error in a large cohort of patients with AD-BVMD compared with an age-similar group with ABCA4-associated Stargardt disease.

METHODS: This was a retrospective chart review of consecutive patients with molecularly confirmed AD-BVMD and Stargardt macular dystrophy seen at a single academic centre. Demographic information, including age, gender and genotype were extracted from the chart. The best corrected visual acuity (BCVA), as well as type and degree of refractive error on manifest refraction for each eye on each visit, were recorded and compared.

RESULTS: A total of 178 eyes from 89 patients with AD-BVMD (35 women, 54 men; mean age 36.6 years) and 306 eyes from 153 patients (94 women, 59 men, mean age 30.2 years) with Stargardt disease were included in the study. Mean BCVA was excellent for both AD-BVMD and Stargardt eyes (logMAR 0.23 vs logMAR 0.31, respectively; p=0.55). At initial refraction, 73.0% of AD-BVMD eyes (130/178) were hyperopic, with mean spherical equivalent (SE) +1.38 dioptres (median +0.88) whereas 80.7% of Stargardt eyes (247/306) were myopic, with mean SE of -1.76 dioptres (median -1.19) (p<0.001).

CONCLUSION: Patients with AD-BVMD are predominantly hyperopic, whereas those with Stargardt disease are predominantly myopic. The findings provide further evidence of a role for BEST1 in ocular growth and development.

PMID:33243830 | DOI:10.1136/bjophthalmol-2020-317763

Patient derived stem cells for discovery and validation of novel pathogenic variants in inherited retinal disease

Sun, 2020-11-01 05:00

Prog Retin Eye Res. 2020 Oct 29:100918. doi: 10.1016/j.preteyeres.2020.100918. Online ahead of print.

ABSTRACT

Our understanding of inherited retinal disease has benefited immensely from molecular genetic analysis over the past several decades. New technologies that allow for increasingly detailed examination of a patient's DNA have expanded the catalog of genes and specific variants that cause retinal disease. In turn, the identification of pathogenic variants has allowed the development of gene therapies and low-cost, clinically focused genetic testing. Despite this progress, a relatively large fraction (at least 20%) of patients with clinical features suggestive of an inherited retinal disease still do not have a molecular diagnosis today. Variants that are not obviously disruptive to the codon sequence of exons can be difficult to distinguish from the background of benign human genetic variations. Some of these variants exert their pathogenic effect not by altering the primary amino acid sequence, but by modulating gene expression, isoform splicing, or other transcript-level mechanisms. While not discoverable by DNA sequencing methods alone, these variants are excellent targets for studies of the retinal transcriptome. In this review, we present an overview of the current state of pathogenic variant discovery in retinal disease and identify some of the remaining barriers. We also explore the utility of new technologies, specifically patient-derived induced pluripotent stem cell (iPSC)-based modeling, in further expanding the catalog of disease-causing variants using transcriptome-focused methods. Finally, we outline bioinformatic analysis techniques that will allow this new method of variant discovery in retinal disease. As the knowledge gleaned from previous technologies is informing targets for therapies today, we believe that integrating new technologies, such as iPSC-based modeling, into the molecular diagnosis pipeline will enable a new wave of variant discovery and expanded treatment of inherited retinal disease.

PMID:33130253 | DOI:10.1016/j.preteyeres.2020.100918

The Varying Optical Coherence Tomography Appearance of the Inner Choroid with Age: Possible Explanation and Histologic Correlate

Mon, 2020-10-26 05:00

Retina. 2020 Sep 21. doi: 10.1097/IAE.0000000000002985. Online ahead of print.

ABSTRACT

PURPOSE: To investigate the reflectivity of the structural optical coherence tomography images of the inner choroid as it relates to potential structural composition.

METHODS: The reflectivity of slab images 29 - 49 µm and 45 - 65 µm below the RPE, obtained with the Zeiss Plex Elite 9000, were evaluated. The mean and standard deviation of a group of subjects with no ocular disorders were determined. Binarization of the images was done a threshold level established at the mean plus one standard deviation for each slab depth. The proportion of area binarized was evaluated with generalized estimating equations. Representative histologic images obtained from autopsy donors were stained with Masson's trichrome, a staining method helpful in evaluating collagen and ground substance of tissue.

RESULTS: There were 67 eyes of 38 subjects with a mean age of 44.5 (range 22 - 82) years. Using generalized estimating equations, age was found to be a significant predictor for the proportion of binarized pixels in both the 29 - 49 µm (P=.034) and the 45 - 65 µm (P<.001) slabs. The histologic specimens illustrated the loss of ground substance with increasing compaction of collagen fibers in the choroidal stroma with advancing age.

CONCLUSIONS: The reflectivity from the inner choroid is not uniform and changes with age. As suggested by the histologic specimens, we propose the OCT reflectance from the inner choroid is related, in part, to the packing density of collagen fibers present there.

PMID:33104324 | DOI:10.1097/IAE.0000000000002985

Reply

Wed, 2020-10-21 05:00

Retina. 2020 Nov;40(11):e68-e69. doi: 10.1097/IAE.0000000000002958.

NO ABSTRACT

PMID:33086372 | DOI:10.1097/IAE.0000000000002958