Likelihood ratios for genome medicine

Alexander A Morgan^1,², Rong Chen¹ and Atul J Butte^1,³^*

* Corresponding author: Atul J Butte abutte@stanford.edu

¹ Department of Pediatrics and the Department of Medicine, Stanford University School of Medicine, 251 Campus Drive, MS-5415, Stanford, CA 94305-5479, USA
² Biomedical Informatics Training Program, Stanford University School of Medicine, 251 Campus Drive, Stanford, CA 94305, USA
³ Lucile Packard Children's Hospital, 725 Welch Road, Palo Alto, CA 94304, USA

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Genome Medicine 2010, 2:30 doi:10.1186/gm151

The electronic version of this article is the complete one and can be found online at: http://genomemedicine.com/content/2/5/30

Published:

17 May 2010

Abstract

Patients are beginning to present to healthcare providers with the results of high-throughput individualized genotyping, and interpreting these results in the context of the explosive growth of literature linking individual variants with disease may seem daunting. However, we suggest that results of a personal genomic analysis may be viewed as a panel of many tests for multiple diseases. By using well-established methods of evidence based medicine, these very many parallel tests may be combined using likelihood ratios to report a post-test probability of disease for use in patient assessment.

Introduction

Although there has been continuing discussion and debate over the ethical implications and clinical utility of a large-scale genotyping for an individual patient [1-3], the issue is somewhat moot. Patients are now being genotyped using either (i) measurement platforms run by several different direct-to-consumer companies that sequence nearly a million single nucleotide polymorphisms (SNPs) [4], or (ii) whole genome sequencing, which is beginning to be offered to selected individuals [5-8]. Patients are beginning to present to their healthcare provider before or during an evaluation, including an extensive genotyping scan [9]. It may appear overwhelming and a nearly impossible task to take the complexity of genetic variation and interpret it in the context of the enormous amount of literature on human genetics [10], some of which seems mercurial and contradictory. However daunting, it is incumbent upon a healthcare provider to try to help patients make informed decisions in light of the information available, and to not ignore this genetic information.