<i>UGT1A</i> and <i>UGT2B</i> Genetic Variation Alters Nicotine and Nitrosamine Glucuronidation in European and African American Smokers
Bibliographic record
Abstract
BACKGROUND: Identifying sources of variation in the nicotine and nitrosamine metabolic inactivation pathways is important to understanding the relationship between smoking and cancer risk. Numerous UGT1A and UGT2B enzymes are implicated in nicotine and nitrosamine metabolism in vitro; however, little is known about their roles in vivo. METHODS: Within UGT1A1, UGT1A4, UGT1A9, UGT2B7, UGT2B10, and UGT2B17, 47 variants were genotyped, including UGT2B10*2 and UGT2B17*2. The association between variation in these UGTs and glucuronidation activity within European and African American current smokers (n = 128), quantified as urinary ratios of the glucuronide over unconjugated compound for nicotine, cotinine, trans-3'-hydroxycotinine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), was investigated in regression models assuming a dominant effect of variant alleles. RESULTS: Correcting for multiple testing, three UGT2B10 variants were associated with cotinine glucuronidation, rs2331559 and rs11726322 in European Americans and rs835309 in African Americans (P ≤ 0.0002). Additional variants predominantly in UGT2B10 were nominally associated with nicotine (P = 0.008-0.04) and cotinine (P = <0.001-0.02) glucuronidation in both ethnicities in addition to UGT2B10*2 in European Americans (P = 0.01, P < 0.001). UGT2B17*2 (P = 0.03) in European Americans and UGT2B7 variants (P = 0.02-0.04) in African Americans were nominally associated with 3HC glucuronidation. UGT1A (P = 0.007-0.01), UGT2B10 (P = 0.02), and UGT2B7 (P = 0.02-0.03) variants in African Americans were nominally associated with NNAL glucuronidation. CONCLUSIONS: Findings from this initial in vivo study support a role for multiple UGTs in the glucuronidation of tobacco-related compounds in vivo, in particular UGT2B10 and cotinine glucuronidation. IMPACT: Findings also provide insight into ethnic differences in glucuronidation activity, which could be contributing to ethnic disparities in the risk for smoking-related cancers. Cancer Epidemiol Biomarkers Prev; 24(1); 94-104. ©2014 AACR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".