Association between Drug-Metabolizing Enzymes Polymorphisms and Diffuse Large B-Cell Lymphoma Risk in the Middle Eastern Population.
Bibliographic record
Abstract
Abstract The last four decades have seen significant increase in the incidence of non-Hodgkin’s lymphoma (NHL) as a possible result of increasing environmental carcinogens exposure. Based on the increasing evidence for the association between carcinogens exposure related cancer risk and xenobiotic gene polymorphisms. We have undertaken a case control study on xenobiotic gene polymorphisms in Saudi individuals with a diagnosis of diffuse large B-cell lymphoma (DLBCL). Polymorphisms in five genes (CYP1A1, GSTT1, GSTP1, GSTM1 and NQO1) were characterized in 187 individuals with DLBCL and 513 normal controls using polymerase chain reaction (PCR) based method. We chose the Saudi population as our study population because of its high consanguinity and its relative genetic homogeneity. The CYP1A1*2C, GSTT1 null and GSTP1 TT genotype were all found to be significant predictors of DLBCL risk (odds ratio 6.62, 11.94 and 3.42 respectively). None of the other alleles tested for proved to be significant indicators of DLBCL risk. These results suggest that the risk of DLBCL may indeed be associated with xenobiotics - metabolism and thus with environmental exposures. Table 1 Distribution of polymorphisms in healthy population and lymphoma patients. Polymorphism Genotype Control group Lymphoma patients p OR CYP1A1 −/− 384(76.5%) 104(78.8%) *2A −/2A 105(20.9%) 24(18.18%) 0.543 0.844 2A/2A 13(2.6%) 3(2.27%) 1.000 0.852 2A allele 13% 11.36% 0.659 0.839 CYP1A1 −/− 443(88.2%) 121(91.66%) *2B −/2B 50(10%) 10(7.58%) 0.505 0.732 2B/2B 9(1.8%) 1(0.76%) 0.697 0.407 2B allele 6.8% 4.55% 0.424 0.646 CYP1A1 −/− 497(99%) 125(94.7%) *2C −/2C 5(1%) 4(3.03%) 0.090 3.181 2C/2C 0 3(2.27%) 0.008 ND 2C allele 0.5% 3.8% 0.011 6.627 NQO1 C609T CC 295 (58.5%) 94 (62.7%) CT 177 (35.1%) 37 (24.7%) 0.051 0.656 TT 32 (6.4%) 19 (8.7%) 0.059 1.863 CT+TT 209 (41.5%) 56 (37.3%) 0.395 0.841 GSTP1 2293 CC 389 (76.3%) 113 (77.9%) CT 113 (22.2%) 24 (16.6%) 0.240 0.731 TT 8 (1.5%) 8 (5.5%) 0.017 3.422 CT+TT 121 (23.7%) 32 (22%) 0.739 0.910 GSTP1 A1578G AA 170 (33.5%) 56 (35%) AG 271 (53.5%) 96 (60%) 0.772 1.075 GG 66 (13%) 8 (5%) 0.013 0.368 AG+GG 337 (66.5%) 104 (65%) 0.774 0.937 GSTT1 P 385 (75%) 36 (20.1%) D 128 (25%) 143 (79.9%) <0.001 11.948 GSTM1 P 233 (45.4%) 91 (50%) D 280 (54.6%) 91 (50%) 0.300 0.832 Table 2 Distribution of combined GSTT1 and GSTM1 polymorphisms in case and control group. Genotype Control Case p OR Null: Complete deletion of GSTT1 and GSTM1 allele Present 423 (82.8%) 109 (60.9%) Double Null 88 (17.2%) 70 (39.1%) <0.001 3.087
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 | 0.001 | 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) | 0.002 | 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".