Early Diagnosis of Syndromic Congenital Cataracts in a Large Cohort of Congenital Cataracts

center dot PURPOSE: To explore the factors related to the diagnosis yield of syndromic congenital cataracts and describe the phenotype -genotype correlation in congenital cataract patients. center dot DESIGN: Prospective cohort study. center dot METHODS: Setting : the participants from underwent clinical examinations between 2021 and 2022. Facial and anterior eye segment photographs, preand postoperative ocular parameters, and medical and family histories were recorded. Bioinformatics analysis was performed using whole-exome sequencing data. Statistical and correlation analyses were performed using the basic characteristics, deep phenotype, and genotype data. Participants : 115 patients with unrelated congenital cataract. Interventions : performing clinical examinations, whole-exome sequencing, and bioinformatics analysis for all participants. Main outcomes and measures : factors related to the genetic diagnosis yield of syndromic congenital cataracts. center dot RESULTS: Bilaterally asymmetrical cataracts were identified to be associated with syndromic congenital cataracts. The overall genetic diagnostic yield in the cohort was 72.2%. In total, 34.8% of the probands were early diagnosed with various syndromes with the help of genetic information. A phenotype -genotype correlation was detected for some genes and deep phenotypes. center dot CONCLUSIONS: We highlight the importance of screening syndromic diseases in the patients with asymmetrical congenital cataracts. Application of whole-exome sequencing helps provide early diagnosis and treatment for the patients with syndromic congenital cataracts. This study also achieved a high genetic diagnostic yield, expanded the genotypic spectrum, and found phenotypegenotype correlations. A comprehensive analysis of cataract symmetricity, family history, and deep phenotypes makes the genotype prediction of some congenital cataract patients possible. (Am J Ophthalmol 2024;263: 206-213. (c) 2023 Elsevier Inc. All rights reserved.)