Abstract：
Junctional epidermolysis bullosa (JEB) is a rare autosomal recessive genodermatosis with a broad spectrum of phenotypes. Current genotype-phenotype paradigms are insufficient to accurately predict JEB subtype and characteristics from genotype, particularly for splice site variants, which account for over a fifth of disease-causing variants in JEB. This study evaluated the genetic and clinical findings from a JEB cohort, investigating genotype-phenotype correlations through bioinformatic analyses and comparison with previously reported variants. Eighteen unique variants in LAMB3, LAMA3, LAMC2, or COL17A1 were identified from 17 individuals. Seven had severe JEB, 9 had intermediate JEB, and 1 had laryngo-onycho-cutaneous syndrome. Seven variants were previously unreported. Deep phenotyping was completed for all intermediate JEB cases and demonstrated substantial variation between individuals. Splice site variants underwent analysis with SpliceAI, a state-of-the-art artificial intelligence tool, to predict resultant transcripts. Predicted functional effects included exon skipping and cryptic splice site activation, which provided potential explanations for disease severity and in most cases correlated with laminin-332 immunofluorescence. RT-PCR was performed for 1 case to investigate resultant transcripts produced from the splice site variant. This study expands the JEB genomic and phenotypic landscape. Artificial intelligence tools show potential for predicting the functional effects of splice site variants and may identify candidates for confirmatory laboratory investigation. Investigation of RNA transcripts will help to further elucidate genotype-phenotype correlations for novel variants.
摘要：
连接性大疱性表皮松解症（JEB）是一种罕见的常染色体隐性遗传性遗传性皮肤病，具有广泛的表型。当前的基因型-表型范式不足以准确预测基因型的JEB亚型和特征，特别是剪接位点突变，占JEB致病突变的五分之一以上。这项研究评估了来自JEB队列的遗传和临床发现，通过生物信息学分析并与以前报道的突变进行比较，调查基因型-表型相关性。从17个个体中鉴定了LAMB3、LAMA3、LAMC2或COL17A1中的18个独特突变。七个有严重的JEB，9个中间JEB和1个喉甲皮肤综合征。七个突变以前没有报道。所有中间JEB病例均完成了深度表型鉴定，并显示出个体之间的实质性差异。用SpleeAI分析剪接位点突变，最先进的人工智能工具，以预测结果的转录本。预测的功能效应包括外显子跳跃和隐蔽剪接位点激活，这提供了疾病严重程度的潜在解释，在大多数情况下与lamimin-332免疫荧光相关。对一个病例进行RT-PCR以研究由剪接位点突变产生的所得转录物。这项研究扩展了JEB基因组和表型景观。AI工具显示出预测剪接位点突变的功能效应的潜力，并可能确定用于验证性实验室研究的候选者。RNA转录本的研究将有助于进一步阐明新突变的基因型-表型相关性。
