Analysis of 17 genes detects mutations in 81% of 811 patients with lissencephaly.
Analysis of 17 genes detects mutations in 81% of 811 patients with lissencephaly.
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DOI：
10.1038/gim.2018.8
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发表时间：
2018-11
期刊：
影响因子：
--
通讯作者：
Dobyns WB
中科院分区：
文献类型：
--
作者：
Di Donato N;Timms AE;Aldinger KA;Mirzaa GM;Bennett JT;Collins S;Olds C;Mei D;Chiari S;Carvill G;Myers CT;Rivière JB;Zaki MS;University of Washington Center for Mendelian Genomics;Gleeson JG;Rump A;Conti V;Parrini E;Ross ME;Ledbetter DH;Guerrini R;Dobyns WB
评估811例无脑或皮质下带状异位症患者的诊断率和基因-表型相关性。我们收集了756名30岁以上的无脑畸形儿童的DNA。许多人被检测到17p13.3的缺失和Lis1、DCX和ARX的突变，但很少有其他基因。在这些被检测的基因中，有216个仍未被解决，并通过17个基因(ACTB、ACTG1、ARX、CRADD、DCX、LIS1、TUBA1A、TUBA8、TUBB2B、TUBB、TUBB3、TUBG1、KIF2A、KIF5C、DYNC1H1、RELN和VLDLR)或通过整个外显子组测序进行检测。在另一家机构研究的55名患者被添加为验证队列。整个队列中的总突变频率为81%。LIS1占40%，其次是DCX(23%)、TUBA1A(5%)和DYNC1H1(3%)。其他基因占患者的1%或更少。19%的基因仍未解决，这表明还有其他几个基因有待发现。未解决的患者多为后部大脑回、皮质下带状异位或轻度额叶大脑回。大脑成像模式与单个无脑相关基因的突变相关，也与生物途径相关。我们提出了第一个基于潜在分子机制的LIS分类系统。
To estimate diagnostic yield and genotype-phenotype correlations in a cohort of 811 patients with lissencephaly or subcortical band heterotopia. We collected DNA from 756 children with lissencephaly over 30 years. Many were tested for deletion 17p13.3 and mutations of LIS1, DCX and ARX, but few other genes. Among those tested, 216 remained unsolved and were tested by a targeted panel of 17 genes (ACTB, ACTG1, ARX, CRADD, DCX, LIS1, TUBA1A, TUBA8, TUBB2B, TUBB, TUBB3, TUBG1, KIF2A, KIF5C, DYNC1H1, RELN and VLDLR) or by whole exome sequencing. 55 patients studied in another institution were added as a validation cohort. The overall mutation frequency in the entire cohort was 81%. LIS1 accounted for 40% of patients, followed by DCX (23%), TUBA1A (5%), and DYNC1H1 (3%). Other genes accounted for 1% or less of patients. 19% remained unsolved, which suggests that several additional genes remain to be discovered. The majority of unsolved patients had posterior pachygyria, subcortical band heterotopia or mild frontal pachygyria. The brain-imaging pattern correlates with mutations in single lissencephaly-associated genes, as well as in biological pathways. We propose the first LIS classification system based on the underlying molecular mechanisms.
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期刊：
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