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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Published on: June 21, 2018

Likelihood ratios for genome medicine.

Alexander A Morgan¹, Rong Chen, Atul J Butte

¹Department of Pediatrics and the Department of Medicine, Stanford University School of Medicine, 251 Campus Drive, MS-5415, Stanford, CA 94305-5479, USA. alexmo@stanford.edu.

Genome Medicine

|May 26, 2010

Summary

Interpreting personal genomic analysis results for disease risk can be daunting. Evidence-based medicine methods, using likelihood ratios, can combine genetic test results to calculate post-test disease probability for patient assessment.

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Area of Science:

Genomics
Medical Genetics
Bioinformatics

Background:

High-throughput individualized genotyping is increasingly common in clinical settings.
Interpreting vast literature linking genetic variants to diseases presents challenges.
Personal genomic analysis generates extensive data requiring structured interpretation.

Discussion:

Genomic test results can be conceptualized as a panel of multiple diagnostic tests.
Established evidence-based medicine principles are applicable to genomic data interpretation.
Likelihood ratios provide a quantitative method to integrate multiple genetic findings.

Key Insights:

Personal genomic data can be systematically analyzed for disease risk assessment.
Combining multiple genetic variant assessments improves diagnostic accuracy.
This approach transforms complex genomic data into actionable clinical insights.

Outlook:

Facilitates personalized risk prediction for a wide range of conditions.
Supports informed clinical decision-making in precision medicine.
Enhances the clinical utility of individual genomic sequencing.