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通过《人类孟德尔遗传在线》(OMIM)数据库对遗传性皮肤病进行表型和基因型分析。

Phenotypic and genotypic analyses of genetic skin disease through the Online Mendelian Inheritance in Man (OMIM) database.

作者信息

Feramisco Jamison D, Sadreyev Ruslan I, Murray Mitzi L, Grishin Nick V, Tsao Hensin

机构信息

Department of Dermatology, University of California at San Francisco, San Francisco, California, USA.

出版信息

J Invest Dermatol. 2009 Nov;129(11):2628-36. doi: 10.1038/jid.2009.108. Epub 2009 Jun 18.

Abstract

Despite unprecedented gains in genomic technologies and genotype resolution, there remain tremendous challenges in our ability to capture disease "phenomes." We propose a previously unreported method for deconvolving human disease into elemental features, thereby creating a third space that interacts with both the disease and genotypic spaces. Using cutaneous and noncutaneous clinical findings available through Johns Hopkins University's Online Mendelian Inheritance in Man (OMIM) database, we set out to deconstruct genetic skin disease (GSD) into its various components, to more fully explore the relationship between these features within the complex phenotypic space and to characterize the genotypic space within which these disorders exist. Using OMIM, we defined the current state of GSD as including 560 distinct disorders associated with 501 unique protein-encoding genes. The most common elemental skin features included [corrected] hair/nail phenotypes, while [corrected] the most common systemic features included those associated with developmental, musculoskeletal, and neurological systems. As a proof of principle, we focused on a single skin feature- café-au-lait macules-and partitioned the disease space into hierarchical groupings on the basis of this finding. Finally, functional analyses among GSD loci were mapped back to skin features, providing insights into pigmentary and auditory features. Phenotypic deconvolution provides a framework for analyzing medical disorders and can aid in the organization and elucidation of biological mechanisms related to human disease.

摘要

尽管基因组技术和基因型分辨率取得了前所未有的进展,但我们在捕捉疾病“表型组”方面仍面临巨大挑战。我们提出了一种此前未报道的方法,将人类疾病解卷积为基本特征,从而创建一个与疾病空间和基因型空间相互作用的第三空间。利用通过约翰·霍普金斯大学《人类孟德尔遗传在线》(OMIM)数据库可获得的皮肤和非皮肤临床发现,我们着手将遗传性皮肤病(GSD)解构为其各个组成部分,以更全面地探索这些特征在复杂表型空间内的关系,并描绘这些疾病所存在的基因型空间。利用OMIM,我们将GSD的当前状态定义为包括与501个独特蛋白质编码基因相关的560种不同疾病。最常见的基本皮肤特征包括毛发/指甲表型,而最常见的全身特征包括与发育、肌肉骨骼和神经系统相关的特征。作为原理验证,我们聚焦于单一皮肤特征——咖啡牛奶斑,并基于这一发现将疾病空间划分为分层分组。最后,将GSD基因座之间的功能分析映射回皮肤特征,为色素沉着和听觉特征提供了见解。表型解卷积为分析医学疾病提供了一个框架,并有助于组织和阐明与人类疾病相关的生物学机制。

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