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通过计算机辅助图像分析对 MISSLA 和范可尼贫血进行区分,并介绍两例新的 MISSLA 同胞兄妹。

Differentiation of MISSLA and Fanconi anaemia by computer-aided image analysis and presentation of two novel MISSLA siblings.

机构信息

Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.

Berlin Center for Rare Diseases, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.

出版信息

Eur J Hum Genet. 2019 Dec;27(12):1827-1835. doi: 10.1038/s41431-019-0469-3. Epub 2019 Jul 18.

Abstract

Variants in DONSON were recently identified as the cause of microcephaly, short stature, and limb abnormalities syndrome (MISSLA). The clinical spectra of MISSLA and Fanconi anaemia (FA) strongly overlap. For that reason, some MISSLA patients have been clinically diagnosed with FA. Here, we present the clinical data of siblings with MISSLA featuring a novel DONSON variant and summarize the current literature on MISSLA. Additionally, we perform computer-aided image analysis using the DeepGestalt technology to test how distinct the facial features of MISSLA and FA patients are. We show that MISSLA has a specific facial gestalt. Notably, we find that also FA patients feature facial characteristics recognizable by computer-aided image analysis. We conclude that computer-assisted image analysis improves diagnostic precision in both MISSLA and FA.

摘要

DONSON 变异体最近被确定为小头畸形、身材矮小和肢体异常综合征 (MISSLA) 的致病原因。MISSLA 和范可尼贫血症 (FA) 的临床表型有很强的重叠。因此,一些 MISSLA 患者被临床诊断为 FA。在这里,我们呈现了一对具有 DONSON 新型变异体的 MISSLA 同胞的临床数据,并总结了目前关于 MISSLA 的文献。此外,我们使用 DeepGestalt 技术进行计算机辅助图像分析,以测试 MISSLA 和 FA 患者的面部特征有何不同。我们发现 MISSLA 具有特定的面部整体特征。值得注意的是,我们发现通过计算机辅助图像分析也可以识别出 FA 患者的面部特征。我们得出结论,计算机辅助图像分析可以提高 MISSLA 和 FA 的诊断精度。

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PEDIA: prioritization of exome data by image analysis.PEDIA:通过图像分析对外显子组数据进行优先级排序。
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Recognizable phenotypes in CDG.可识别的 CDG 表型。
J Inherit Metab Dis. 2018 May;41(3):541-553. doi: 10.1007/s10545-018-0156-5. Epub 2018 Apr 13.

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