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Updated: Jun 6, 2026
05:53
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Concordance study of 3 direct-to-consumer genetic-testing services
Kenta Imai1, Larry J Kricka, Paolo Fortina
1Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.
Clinical Chemistry
|December 17, 2010
Summary
Direct-to-consumer genetic testing shows high SNP data accuracy but varying disease risk assignments. Differences in SNPs and reference populations impact risk results, highlighting the need for ethnicity-matched data.
Area of Science:
- Genetics
- Bioinformatics
- Consumer Health
Background:
- Direct-to-consumer (DTC) genetic testing services offer ancestry and wellness evaluations.
- Large-scale single-nucleotide polymorphism (SNP) testing may contain errors, potentially leading to misclassified health risks.
- Evaluating DTC genetic testing accuracy and disease risk reporting is crucial for consumer understanding.
Purpose of the Study:
- To compare the accuracy and disease risk reporting of different direct-to-consumer (DTC) genetic testing services.
- To assess the concordance of SNP data and the variability in disease risk assignments across multiple testing platforms.
- To identify factors contributing to discrepancies in genetic risk assessment.
Main Methods:
- Comparative analysis of results from three DTC genetic testing services (23andMe, deCODEme, Navigenics) and one genomics analysis service (Expression Analysis).
- Evaluation of single-nucleotide polymorphism (SNP) data concordance across different genotyping platforms (DNA microarray, TaqMan® analysis).
- Assessment of variations in relative disease risk calculations, considering different SNPs and reference populations.
Main Results:
- High concordance rates (>99.6%) were observed for single-nucleotide polymorphism (SNP) data across the evaluated services.
- Significant differences were found in the relative disease risks assigned by DTC services for the same conditions.
- Variations in risk assignment are attributed to the use of different SNPs and reference populations in the analyses.
Conclusions:
- Excellent concordance exists for SNP analyses between different companies and platforms.
- Disparities in disease risk data arise from variations in SNPs utilized and reference population data.
- Further research is needed on the utility of DTC genetic information and the importance of ethnicity-specific risk data.
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