Personalized Genetic Testing and Norovirus Susceptibility
Bibliographic record
Abstract
BACKGROUND: The availability of direct-to-consumer personalized genetic testing has enabled the public to access and interpret their own genetic information. Various genetic traits can be determined including resistance to norovirus through a nonsense mutation (G428A) in the FUT2 gene. Although this trait is believed to confer resistance to the most dominant norovirus genotype (GII.4), the spectrum of resistance to other norovirus strains is unknown. The present report describes a cluster of symptomatic norovirus GI.6 infection in a family identified to have norovirus resistance through personalized genetic testing. CASE PRESENTATION: In January 2013, four members of a family determined by a direct-to-consumer genetic test to be homozygous for the norovirus resistance trait (A/A genotype for single nucleotide polymorphism rs601338) developed symptoms consistent with acute viral gastroenteritis. Stool and vomitus samples were submitted for enteric viral pathogen testing. Samples were positive for norovirus GI.6 in three of the four cases. CONCLUSIONS: The present report is the first to describe norovirus GI.6 infection in patients with the G428A nonsense mutation in FUT2; this cluster of cases suggests that the G428A mutation in FUT2 may not confer resistance to norovirus GI.6. Direct-to-consumer genetic testing is empowering members of the public to identify novel associations with their genetic traits. Expert consultation is important for the interpretation of personalized genetic test results, and follow-up laboratory testing can confirm any potentially novel associations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".