Dataset Information

Pathological molecular mechanism of symptomatic late-onset Fuchs endothelial corneal dystrophy by bioinformatic analysis.

ABSTRACT: Fuchs endothelial corneal dystrophy (FECD) is a degenerative disease characterized by corneal endothelial decompensation. FECD causes corneal stromal and epithelial edema and progressively develops into bullous keratopathy, which can eventually lead to blindness. However, the exact pathogenesis is unknown. In this study, we performed an in-depth bioinformatic analysis of the dataset GSE74123 to determine the differentially expressed genes (DEGs) of symptomatic late-onset FECD compared with a normal control. Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were used to analyze the pathological molecular mechanism of FECD. We found that cell senescence, reactive oxygen species (ROS), the extracellular matrix (ECM), epithelial-mesenchymal transition (EMT) and immune response-related genes play an important role in the pathological development of symptomatic late-onset FECD. In addition, we revealed that down-regulated IL-6, enhanced NF-?B activity and a suite of orchestrated chemokine responses induce fibrocyte differentiation from monocyte to dendritic cell maturation. PI3K plays a key role in the molecular mechanism of symptomatic late-onset FECD. This study enhances our understanding of the molecular mechanism of FECD pathogenesis and will improve the diagnostics and therapy of FECD patients in the future.

SUBMITTER: Cui Z

PROVIDER: S-EPMC5963778 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Pathological molecular mechanism of symptomatic late-onset Fuchs endothelial corneal dystrophy by bioinformatic analysis.

Cui Zekai Z Zeng Qiaolang Q Guo Yonglong Y Liu Shiwei S Wang Peiyuan P Xie Mengyuan M Chen Jiansu J

PloS one 20180522 5

Fuchs endothelial corneal dystrophy (FECD) is a degenerative disease characterized by corneal endothelial decompensation. FECD causes corneal stromal and epithelial edema and progressively develops into bullous keratopathy, which can eventually lead to blindness. However, the exact pathogenesis is unknown. In this study, we performed an in-depth bioinformatic analysis of the dataset GSE74123 to determine the differentially expressed genes (DEGs) of symptomatic late-onset FECD compared with a nor ...[more]

PMID: 29787599

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Project description:Purpose To develop a model to predict corneal improvement after Descemet membrane endothelial keratoplasty (DMEK) for Fuchs endothelial corneal dystrophy (FECD) from Scheimpflug tomography. Design Cross-sectional study. Participants Forty-eight eyes (derivation group) and 45 eyes (validation group) with a range of severity of FECD undergoing DMEK. Methods Scheimpflug images were obtained before and after DMEK. Before DMEK, pachymetry map and posterior elevation map patterns were quantified by a special image analysis program measuring tomographic features of edema (loss of regular isopachs, displacement of the thinnest point of the cornea, posterior surface depression). Image-derived novel parameters were combined with instrument-derived parameters, and the relative influences of parameters associated with the change in central corneal thickness (CCT) after DMEK in the derivation group were determined by using a gradient boosting machine learning model. The parameters with highest relative influence were then fit in a linear regression model. The derived model was applied to the validation group. Correlations and agreement were assessed between predicted and observed changes in CCT. Main Outcome Measures Predictive power (R2) and mean difference between predicted and observed change in CCT. Results The gradient boosting machine model identified 4 novel parameters of isopach circularity and eccentricity and 1 instrument-derived parameter (posterior surface radius); preoperative CCT was a poor predictor. In the derivation group, the model strongly predicted the change in CCT after DMEK (R2 = 0.80; 95% confidence interval [CI], 0.71–0.89) and the mean difference between predicted and observed change was, by definition, 0 μm. When the same 5 parameters were fit to the validation group, the model performed very highly (R2 = 0.89; 95% CI, 0.84–0.94). When the coefficient estimates from the derivation model were used to predict the change in CCT in the validation group, the predictive power was also high (R2 = 0.78; 95% CI, 0.68–0.88), and the mean difference was 4 μm (predicted minus observed). Conclusions Scheimpflug tomography maps of corneas with FECD can predict the improvement in CCT after DMEK, independent of preoperative corneal thickness measurement. The model could be applied in clinical practice or for clinical research of FECD.

Dataset Information

Pathological molecular mechanism of symptomatic late-onset Fuchs endothelial corneal dystrophy by bioinformatic analysis.

Publications

Pathological molecular mechanism of symptomatic late-onset Fuchs endothelial corneal dystrophy by bioinformatic analysis.

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