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NeuroCNVscore: a tissue-specific framework to prioritise the pathogenicity of CNVs in neurodevelopmental disorders.
Liu, Xuanshi; Xu, Wenjian; Leng, Fei; Zhang, Peng; Guo, Ruolan; Zhang, Yue; Hao, Chanjuan; Ni, Xin; Li, Wei.
Afiliación
  • Liu X; Beijing Children's Hospital, Capital Medical University, Beijing, China.
  • Xu W; Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing, China.
  • Leng F; MOE Key Laboratory of Major Diseaseas in Children, Beijing, China.
  • Zhang P; Genetics and Birth Defects Control Centre, National Centre for Children's Health, Beijing, China.
  • Guo R; Beijing Children's Hospital, Capital Medical University, Beijing, China.
  • Zhang Y; Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, Beijing, China.
  • Hao C; MOE Key Laboratory of Major Diseaseas in Children, Beijing, China.
  • Ni X; Genetics and Birth Defects Control Centre, National Centre for Children's Health, Beijing, China.
  • Li W; Beijing Children's Hospital, Capital Medical University, Beijing, China.
BMJ Paediatr Open ; 7(1)2023 07.
Article en En | MEDLINE | ID: mdl-37407247
ABSTRACT

BACKGROUND:

Neurodevelopmental disorders (NDDs) are associated with altered development of the brain especially in childhood. Copy number variants (CNVs) play a crucial role in the genetic aetiology of NDDs by disturbing gene expression directly at linear sequence or remotely at three-dimensional genome level in a tissue-specific manner. Despite the substantial increase in NDD studies employing whole-genome sequencing, there is no specific tool for prioritising the pathogenicity of CNVs in the context of NDDs.

METHODS:

Using an XGBoost classifier, we integrated 189 features that represent genomic sequences, gene information and functional/genomic segments for evaluating genome-wide CNVs in a neuro/brain-specific manner, to develop a new tool, neuroCNVscore. We used Human Phenotype Ontology to construct an independent NDD-related set.

RESULTS:

Our neuroCNVscore framework (https//github.com/lxsbch/neuroCNVscore) achieved high predictive performance (precision recall=0.82; area under curve=0.85) and outperformed an existing reference method SVScore. Notably, the predicted pathogenic CNVs showed enrichment in known genes associated with autism.

CONCLUSIONS:

NeuroCNVscore prioritises functional, deleterious and pathogenic CNVs in NDDs at whole genome-wide level, which is important for genetic studies and clinical genomic screening of NDDs as well as for providing novel biological insights into NDDs.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Trastorno Autístico / Trastornos del Neurodesarrollo Idioma: En Revista: BMJ Paediatr Open Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Trastorno Autístico / Trastornos del Neurodesarrollo Idioma: En Revista: BMJ Paediatr Open Año: 2023 Tipo del documento: Article