Dataset Information

Incorporating Differential Gene Expression Analysis with Predictive Biomarkers to Identify Novel Therapeutic Drugs for Fuchs Endothelial Corneal Dystrophy.

ABSTRACT:

Purpose

Based on the differential gene expression analysis for predictive biomarkers with RNA-Sequencing data from Fuchs endothelial corneal dystrophy (FECD) patients, we are aiming to evaluate the efficacy of Library of Integrated Network-based Cellular Signatures (LINCS) perturbagen prediction software to identify novel pharmacotherapeutic targets that can revert the pathogenic gene expression signatures and reverse disease phenotype in FECD.

Methods

A publicly available RNA-seq dataset was used to compare corneal endothelial specimens from controls and patients with FECD. Based on the differential gene expression analysis for predictive biomarkers, we evaluated the efficacy of LINCS perturbagen prediction software to identify novel therapeutic targets that can revert the pathogenic gene expression signatures and reverse disease phenotypes in FECD.

Results

The RNA-seq dataset of the corneal endothelial cells from FECD patients revealed the differential gene expression signatures of FECD. Many of the differential expressed genes are related to canonical pathways of the FECD pathogenesis, such as extracellular matrix reorganization and immunological response. The expression levels of genes VSIG2, IL18, and ITGB8 were significantly increased in FECD compared with control. Meanwhile, the expression levels of CNGA3, SMOX, and CERS1 were significantly lower in the FECD than in control. We employed LINCS L1000 Characteristic Direction Signature Search Engine (L1000-CDS2) to investigate pathway-based molecular treatment. L1000-CDS2 predicted that small molecule drugs such as histone deacetylase (HDAC) inhibitors might be a potential candidate to reverse the pathological gene expression signature in FECD.

Conclusions

Based on differential gene expression signatures, several candidate drugs have been identified to reverse the disease phenotypes in FECD. Gene expression signature with LINCS small molecule prediction software can discover novel preclinical drug candidates for FECD.

SUBMITTER: Wen H

PROVIDER: S-EPMC8260298 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Incorporating Differential Gene Expression Analysis with Predictive Biomarkers to Identify Novel Therapeutic Drugs for Fuchs Endothelial Corneal Dystrophy.

Wen Huaming H Gallo Ryan A RA Huang Xiaosheng X Cai Jiamin J Mei Shaoyi S Farooqi Ammad Ahmad AA Zhao Jun J Tao Wensi W

Journal of ophthalmology 20210628

<h4>Purpose</h4>Based on the differential gene expression analysis for predictive biomarkers with RNA-Sequencing data from Fuchs endothelial corneal dystrophy (FECD) patients, we are aiming to evaluate the efficacy of Library of Integrated Network-based Cellular Signatures (LINCS) perturbagen prediction software to identify novel pharmacotherapeutic targets that can revert the pathogenic gene expression signatures and reverse disease phenotype in FECD.<h4>Methods</h4>A publicly available RNA-seq ...[more]

PMID: 34258047

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Project description:PurposeTo develop a model to predict corneal improvement after Descemet membrane endothelial keratoplasty (DMEK) for Fuchs endothelial corneal dystrophy (FECD) from Scheimpflug tomography.DesignCross-sectional study.ParticipantsForty-eight eyes (derivation group) and 45 eyes (validation group) with a range of severity of FECD undergoing DMEK.MethodsScheimpflug 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 measuresPredictive power (R 2) and mean difference between predicted and observed change in CCT.ResultsThe 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 (R 2 = 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 (R 2 = 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 (R 2 = 0.78; 95% CI, 0.68-0.88), and the mean difference was 4 μm (predicted minus observed).ConclusionsScheimpflug 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.

Project description:Fuchs’ endothelial corneal dystrophy (FECD) is a progressive vision impairing disease caused by thickening of Descemet’s membrane and gradual degeneration and loss of corneal endothelial cells. The aim of this study was to identify differentially expressed genes between FECD-affected and unaffected corneal endothelium to gain insight into the pathophysiological mechanisms underlying this disease. Microarray gene expression analysis was performed on total RNA from FECD-affected and unaffected corneal endothelium-Descemet’s membrane (CE-DM) specimens using the Illumina HumanHT-12 v3.0 expression array. RNA from pools of FECD-affected (n=3 per pool) and individual unaffected (n=3) specimens was used for comparison. Altered expression of a sub-set of differentially expressed genes was validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in independent specimens. Bioinformatics analysis was performed using InnateDB to reveal functional relationships among the differentially expressed genes and molecular pathways involved in the disease. A total of 16,513 genes were found expressed in the corneal endothelium of which 142 genes were differentially expressed between FECD-affected and unaffected endothelium (log2 fold-change ≥1.5, corrected p-value ≤0.05). Most of the genes were up-regulated (126) and a small proportion down-regulated (16) in affected corneal endothelium. Of the twelve genes prioritised for validation, differential expression of 10 genes, including those ranked 57th and 81st by significance validated by qRT-PCR (8 up-regulated and 2 downregulated, corrected p ≤0.05), one gene showed a trend for up-regulation in affected endothelium, consistent with the microarray analysis and another was up-regulated in an independent study indicating robustness of the differential expression dataset. Bioinformatic analysis revealed significant over-representation of differentially expressed genes in extracellular matrix reorganisation, cellular remodelling, immune response, and inflammation. Network analysis showed functional inter-relatedness of the majority of the dysregulated genes and revealed known direct functional relationships between 20 of the genes; many of these genes have roles in macrophage differentiation, phagocytosis and inflammation. This is the second report of microarray gene expression analysis in FECD. This study revealed a set of highly dysregulated genes in the corneal endothelium in FECD. More than a third of the dysregulated genes in the disease have been discovered for the first time and thus are novel. The dysregulated genes strongly suggest the presence of phagocytic cells, most likely immune cells, and inflammation in corneal endothelium in the disease. This study provides a molecular framework for delineating the mechanisms underlying these cellular processes in FECD.

Dataset Information

Incorporating Differential Gene Expression Analysis with Predictive Biomarkers to Identify Novel Therapeutic Drugs for Fuchs Endothelial Corneal Dystrophy.

Purpose

Methods

Results

Conclusions

Publications

Incorporating Differential Gene Expression Analysis with Predictive Biomarkers to Identify Novel Therapeutic Drugs for Fuchs Endothelial Corneal Dystrophy.

Similar Datasets

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