4.6 Article

Genetic spectrum and clinical features in a cohort of Chinese patients with autosomal recessive cerebellar ataxias

期刊

TRANSLATIONAL NEURODEGENERATION
卷 10, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s40035-021-00264-z

关键词

Autosomal recessive cerebellar ataxias; Chinese; Genetic spectrum; Structural variation; Clinical features

资金

  1. National Natural Science Foundation of China [82071260]
  2. Research Foundation for Distinguished Scholar of Zhejiang University [188020-193810101/089]

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This study investigated 54 Chinese ARCA patients using WES and CNV analysis, identifying 38 mutations and achieving a positive molecular diagnostic rate of 46.3%. Mutations in 10 different genes were identified in 25 patients, with SACS, SYNE1, and ADCK3 being the most common. Clinical features of patients with mutations in these genes were summarized.
Background Although many causative genes have been uncovered in recent years, genetic diagnosis is still missing for approximately 50% of autosomal recessive cerebellar ataxia (ARCA) patients. Few studies have been performed to determine the genetic spectrum and clinical profile of ARCA patients in the Chinese population. Methods Fifty-four Chinese index patients with unexplained autosomal recessive or sporadic ataxia were investigated by whole-exome sequencing (WES) and copy number variation (CNV) calling with ExomeDepth. Likely causal CNV predictions were validated by CNVseq. Results Thirty-eight mutations including 29 novel ones were identified in 25 out of the 54 patients, providing a 46.3% positive molecular diagnostic rate. Ten different genes were involved, of which four most common genes were SACS, SYNE1, ADCK3 and SETX, which accounted for 76.0% (19/25) of the positive cases. The de novo microdeletion in SACS was reported for the first time in China and the uniparental disomy of ADCK3 was reported for the first time worldwide. Clinical features of the patients carrying SACS, SYNE1 and ADCK3 mutations were summarized. Conclusions Our results expand the genetic spectrum and clinical profiles of ARCA patients, demonstrate the high efficiency and reliability of WES combined with CNV analysis in the diagnosis of suspected ARCA, and emphasize the importance of complete bioinformatics analysis of WES data for accurate diagnosis.

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