Determination of genotypes using a fully automated molecular detection system.

Abstract:

CONTEXT:Although the value of pharmacogenomics to improve patient outcomes has become increasingly clear, adoption in medical practice has been slow, which can be attributed to several factors, including complicated and expensive testing procedures and required equipment, lack of training by private practice physicians, and reluctance of both private and commercial payers to reimburse for such testing. OBJECTIVES:To evaluate a fully automated molecular detection system for human genotyping assays, starting with anticoagulated whole blood samples, and to perform all sample preparation, assay, and analysis steps automatically with actionable results reported by the system's software. DESIGN:The genotypes of 254 random individuals were determined by performing bidirectional DNA sequencing, and that information was used to statistically train the imaging software of the automated molecular detection system to distinguish the 3 possible genotypes (ie, homozygous wild type, heterozygous, and homozygous mutant) at each of 3 different loci (CYP2C9*2, CYP2C9*3, and VKORC1). RESULTS:The resulting software algorithm was able to correctly identify the genotypes of all 254 individuals (100%) evaluated without any further user analysis. CONCLUSIONS:The EncompassMDx workstation (Rheonix, Inc, Ithaca, New York) is a molecular detection system that can automatically determine the genotypes of individuals in an unattended manner. Considerably less technical expertise was required to achieve results identical to those obtained using more complex, time-consuming, and expensive bidirectional DNA sequencing. This optimized system may dramatically simplify and reduce the costs of pharmacogenomics testing, thus leading to more-widespread use.

journal_name

Arch Pathol Lab Med

authors

Spizz G,Chen Z,Li P,McGuire IC,Klimkiewicz P,Zysling D,Yasmin R,Hungerford W,Thomas B,Wilding G,Mouchka G,Young L,Zhou P,Montagna RA

doi

10.5858/arpa.2014-0059-OA

subject

Has Abstract

pub_date

2015-06-01 00:00:00

pages

805-11

issue

6

eissn

0003-9985

issn

1543-2165

journal_volume

139

pub_type

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