Novel MIP gene mutation causes autosomal-dominant congenital cataract.

AIM: To identify disease-causative mutations in families with congenital cataract. METHODS: Two Chinese families with autosomal-dominant congenital cataract (ADCC) were recruited and underwent comprehensive eye examinations. Gene panel next-generation sequencing of common pathogenic genes of congenital cataract was performed in the proband of each family. Sanger sequencing was used to valid the candidate gene mutations and sequence the other family members for co-segregation analysis. The effect of sequence changes on protein structure and function was predicted through bioinformatics analysis. Major intrinsic protein (MIP)-wildtype and MIP-G29R plasmids were constructed and microinjected into zebrafish single-cell stage embryos. Zebrafish embryonic lens phenotypes were screened using confocal microscopy. RESULTS: A novel heterozygous mutation (c.85G>A; p.G29R) in the MIP gene was identified in the proband of one family. A known heterozygous mutation (c.97C>T; p.R33C; rs864309693) in MIP was found in the proband of another family. In-silico prediction indicated that the novel mutation might affect the MIP protein function. Zebrafish embryonic lens was uniformly transparent in both wild-type PCS2+MIP and mutant PCS2+MIP. CONCLUSION: Two missense mutations in the MIP gene in Chinese cataract families are identified, and one of which is novel. These findings expand the genetic spectrum of MIP mutations associated with cataracts. The functional studies suggest that the novel MIP mutation might not be a gain-of-function but a loss-of-function mutation.

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

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.