Genome-wide association study of chronic hepatitis B virus infection reveals a novel candidate risk allele on 11q22.3
Bibliographic record
Abstract
BACKGROUND: Hepatitis B virus (HBV) affects millions of people worldwide. While some people are able to clear the virus following the first encounter, those who develop chronic infection manifest remarkable clinical heterogeneity that ranges from asymptomatic carrier state to cirrhosis and hepatocellular carcinoma. Despite extensive studies, little is known about genetic host factors that influence the outcome of chronic HBV infection. Thus, we conducted this study to investigate the genetic risk of developing active liver disease among chronic carriers of HBV. METHODS: In this study, we conducted a genome-wide association study (GWAS) on a cohort of patients with chronic HBV infection. RESULTS: One particular SNP that is 16 kb upstream of Ferredoxin 1 was found to have an association with complicated chronic HBV infection (cirrhosis and hepatocellular carcinoma) that reached GWAS significance, and was successfully validated on an independent set of samples. CONCLUSIONS: This first GWAS in an Arab population further demonstrates the utility of this approach in elucidating the genetic risk of HBV infection-related complications and highlights the advantage of conducting GWAS in different ethnicities to achieve that goal.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".