Defining a comprehensive verotype using electronic health records for personalized medicine

被引：50

作者：

Boland, Mary Regina ^{[1
]}

Hripcsak, George ^{[1
]}

Shen, Yufeng ^{[1
,2
]}

Chung, Wendy K. ^{[3
,4
,5
]}

Weng, Chunhua ^{[1
,5
]}

机构：

[1] Columbia Univ, Dept Biomed Informat, New York, NY 10032 USA

[2] Columbia Univ, Dept Syst Biol, New York, NY 10032 USA

[3] Columbia Univ, Dept Pediat, New York, NY 10032 USA

[4] Columbia Univ, Dept Med, New York, NY 10032 USA

[5] Columbia Univ, Irving Inst Clin & Translat Res, New York, NY 10032 USA

来源：

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION | 2013年 / 20卷 / E2期

关键词：

AMYOTROPHIC-LATERAL-SCLEROSIS; GENE-EXPRESSION SIGNATURES; PARKINSONS-DISEASE; NETWORK MEDICINE; BREAST-CANCER; EYE COLOR; SMOKING STATUS; SUBTYPES; ENDOPHENOTYPES; IDENTIFICATION;

D O I：

10.1136/amiajnl-2013-001932

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The burgeoning adoption of electronic health records (EHR) introduces a golden opportunity for studying individual manifestations of myriad diseases, which is called 'EHR phenotyping'. In this paper, we break down this concept by: relating it to phenotype definitions from Johannsen; comparing it to cohort identification and disease subtyping; introducing a new concept called 'verotype' (Latin: vere = true, actually) to represent the 'true' population of similar patients for treatment purposes through the integration of genotype, phenotype, and disease subtype (eg, specific glucose value pattern in patients with diabetes) information; analyzing the value of the 'verotype' concept for personalized medicine; and outlining the potential for using network-based approaches to reverse engineer clinical disease subtypes.

引用

页码：E232 / E238

页数：7

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