| Literature DB >> 26677835 |
Loredana Covolo1, Sara Rubinelli, Elisabetta Ceretti, Umberto Gelatti.
Abstract
BACKGROUND: Direct-to-consumer genetic tests (DTC-GT) are easily purchased through the Internet, independent of a physician referral or approval for testing, allowing the retrieval of genetic information outside the clinical context. There is a broad debate about the testing validity, their impact on individuals, and what people know and perceive about them.Entities:
Keywords: Internet; direct-to-consumer; genetic testing; online market; systematic review
Mesh:
Year: 2015 PMID: 26677835 PMCID: PMC4704942 DOI: 10.2196/jmir.4378
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Figure 1Flow diagram describing the study selection.
Figure 2Research categories.
List of articles on scientific evidence and clinical utility of direct-to-consumer genetic tests.
| Author | Aim of the study | Main findings |
| Adams, 2013 [ | To investigate the reliability and reproducibility of DTC-GT by sending DNA samples to 2 popular companies | DNA samples from 2 individuals were sent to both companies. For 5 of 14 health conditions for which both companies reported relative risk information, the results were conflicting. The significance of relative risk changes was overemphasized, given that they were associated with very small changes in absolute risk. |
| Bloss, 2012 [ | To evaluate the relationship between DTC genomic risk estimates and self-reported disease of individuals who went on to purchase a DTC-GT | For 5 out of 15 total conditions studied, the risk estimates from the test were significantly associated with self-reported family and/or personal health history. |
| Buitendijk, 2014 [ | To explore the practicability and predictive value of DTC tests from four companies for age-related macular degeneration in 3 individuals | Predicted risks varied widely within each individual, and differences between highest and lowest estimates for lifetime risk were up to 12-fold. Within the same person, overall relative risks could be increased as well as decreased, depending on which test was used. None may represent the true disease risk. |
| Imai, 2011 [ | To evaluate 3 DTC services and genomics service and compare the test results obtained for the same individual | The concordance rates between the services for single nucleotide polymorphism (SNP) data were >99.6%. There were some marked differences in the relative disease risks assigned by the DTC services due to different SNPs used to calculate risk for the same disease. |
| Janssens, 2008 [ | To assess the scientific evidence supporting the purported gene-associations for genes included in genomic profiles offered online | The seven companies investigated tested at least 69 polymorphisms in 56 genes. Of the 56 genes tested, 24 were not reviewed in meta-analyses. For the remaining 32 genes, they found 260 meta-analyses that examined 160 unique polymorphism-disease associations, of which only 60 were found to be statistically significant. However the associations were modest. |
| Johnson, 2010 [ | To survey potential notifiable variants on arrays used in genome-wide association studies and DTC genetic services | They identified 298 specific targeted mutations, encompassing 56 disorders. Only 88 out of 298 mutations could be identified as known SNPs in genomic databases. Eighteen out of 88 SNPs were found in commercially available arrays. |
| Kalf, 2013 [ | To examine and compare the methods of 3 companies offering DTC-GT | Predicted risks differed substantially among the companies as a result of differences in the sets of SNPs selected and the average population risks selected by the companies, and in the formulas used for the calculation of risks. |
| Kido, 2013 [ | To evaluate the distributions of disease risk prediction from three DTC companies using three Japanese samples | The overall prediction results were correlated with each other, but not perfectly matched; less than one third mismatching of the opposite direction occurred in 8 diseases of 22. |
| Mihaescu, 2009 [ | To investigate the extent to which updating of risk predictions from commercial genome-wide scans leads to reclassification of individuals from below to above average disease risk or vice versa taking type 2 diabetes as an example | At individual level, 34% of 5297 participants switched between risk categories when risks were updated from 1-18 polymorphisms and 29% switched when age, sex, and body mass index were considered. In total, 39% of participants switched risk categories once and 11% switched twice. |
| Ng, 2009 [ | To compare results of tests purchased from two DTC companies on 13 diseases for 5 individuals | For seven diseases, 50% or less of the predictions of the two companies agreed across 5 individuals. |
| Palomaki, 2013 [ | To review the evidence about the clinical and analytic validity of type 2 diabetes genomic risk profiles promulgated by DTC-GT companies | The quality of evidence for analytic validity was inadequate. Clinical validity ranged from inadequate to convincing for 30 variants identified on five T2D genomic panels. Clinical utility evidence was inadequate. |
| Swan, 2010 [ | To understand the variance in risk interpretation for multigenic conditions among 5 genome-wide DTC genomic companies | Multigenic condition risk interpretation may vary between DTC genomic services due to differences in the average lifetime risk assigned to similar underlying populations, the loci and SNPs selected for analysis, and the quantitative risk assignment methodologies used by DTC genomic companies. |
| Kutz, 2006 [ | To evaluate the results of nutrigenetic tests purchased from four DTC companies for 14 fictitious consumers coming from two DNA samples | All 14 results predicted risk of developing different medical conditions. These predictions were similar for all the fictitious consumers, no matter which DNA or lifestyle description they used. One of the four companies gave contradictory results. |
| Kutz, 2010 [ | To compare results from 10 tests each purchased from four DTC companies on 15 diseases for 5 individuals. To assess whether the tests provided any medically useful information | Each donor received risk predictions for the 15 diseases that varied from company to company. Four of the five donors received test results that conflicted with their factual medical conditions and family histories. |