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Usage Information

CTNND1 variants cause familial exudative vitreoretinopathy through the Wnt/cadherin axis
Mu Yang, … , Xiaoyan Ding, Zhenglin Yang
Mu Yang, … , Xiaoyan Ding, Zhenglin Yang
Published June 14, 2022
Citation Information: JCI Insight. 2022;7(14):e158428. https://doi.org/10.1172/jci.insight.158428.
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Research Article Genetics Ophthalmology

CTNND1 variants cause familial exudative vitreoretinopathy through the Wnt/cadherin axis

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Abstract

Familial exudative vitreoretinopathy (FEVR) is a hereditary disorder that can cause vision loss. CTNND1 encodes a cellular adhesion protein p120-catenin (p120), which is essential for vascularization with unclear function in postnatal physiological angiogenesis. Here, we applied whole-exome sequencing to 140 probands of FEVR families and identified 3 candidate variants in the human CTNND1 gene. We performed inducible deletion of Ctnnd1 in the postnatal mouse endothelial cells (ECs) and observed typical phenotypes of FEVR with reactive gliosis. Using unbiased proteomics analysis combined with experimental approaches, we conclude that p120 is critical for the integrity of adherens junctions (AJs) and that p120 activates Wnt signaling activity by protecting β-catenin from glycogen synthase kinase 3 beta–ubiqutin–guided (Gsk3β-ubiquitin–guided) degradation. Treatment of CTNND1-depleted human retinal microvascular ECs with Gsk3β inhibitors LiCl or CHIR-99021 enhanced cell proliferation. Moreover, LiCl treatment increased vessel density in Ctnnd1-deficient mouse retinas. Variants in CTNND1 caused FEVR by compromising the expression of AJs and Wnt signaling activity. Genetic interactions between p120 and β-catenin or α-catenin revealed by double-heterozygous deletion in mice showed that p120 regulates vascular development through the Wnt/cadherin axis. In conclusion, variants in CTNND1 can cause FEVR through the Wnt/cadherin axis.

Authors

Mu Yang, Shujin Li, Li Huang, Rulian Zhao, Erkuan Dai, Xiaoyan Jiang, Yunqi He, Jinglin Lu, Li Peng, Wenjing Liu, Zhaotian Zhang, Dan Jiang, Yi Zhang, Zhilin Jiang, Yeming Yang, Peiquan Zhao, Xianjun Zhu, Xiaoyan Ding, Zhenglin Yang

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Usage data is cumulative from June 2022 through June 2023.

Usage JCI PMC
Text version 6,192 192
PDF 687 109
Figure 551 5
Supplemental data 212 21
Citation downloads 70 0
Totals 7,712 327
Total Views 8,039

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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