The improvement in diagnostic yield of developmental and epileptic encephalopathy by the multi-omics sequential
Shuang-Hao Yang1, Jiatong Liu2, Yuan Quan3
1Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China; Department of bioinformatics, Chigene (Beijing) Translational Medical Research Center Co. Ltd., Beijing Yizhuang Biomedical Park, 100176, China; Beijing Quanpu Medical Laboratory Co., Ltd., E2, 3rd Floor, No. 88 Kechuang 6th Road, Beijing Yizhuang Biomedical Park, 100176, China.
None:
Despite traditional panel and Whole Exome Sequencing (WES) assays, the causative factors for 60 % of epilepsy cases remain elusive, mainly due to incomplete detection of variant spectrums, and limited ability to interpret variants. Our research developed the multi-omics method of a comprehensive sequential testing methodology, to enhance the diagnostic yield for the etiology. In this study, we performed sequential multi-omics analyses on a cohort of 236 Chinese patients exhibiting recurrent seizures along with developmental delay or intellectual disability. Our study had devised a comprehensive multi-omics variant analysis methodology in a sequential mode. The initial analytical strategy included WES, CNV-seq and in-house cases evidence. If no pathogenic cause was identified, the subsequent analytical approach in the sequential mode included the analysis of WGS SVs, mitochondrial variations, dynamic mutations, and abnormalities in RNA-seq. Our results revealed that the initial step achieved a diagnostic detection rate of 44.1 % (104 cases). Subsequently, WGS and RNA-seq testing were performed, with 33 familial diagnoses tested positive, representing a 14 % increase. Meanwhile our pipeline has elucidated the pathogenicity classification of 72 variants which are either not yet recorded in the ClinVar database or are classified as VUS. Our study achieved an overall positive diagnostic rate of 58.1 % (137/236). In summary, our pipeline can detect comprehensive variant spectrums and provide a clear interpretation of variations with unclear clinical significance, the multi-omics sequential testing approach significantly improves the rate of genetic diagnosis for epileptic disorders.
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