Genetic variation near CXCL12 is associated with susceptibility to HIV-related non-Hodgkin lymphoma
Bibliographic record
Abstract
Abstract Human immunodeficiency virus (HIV) infection is associated with a substantially increased risk of non-Hodgkin lymphoma (NHL). High plasma viral load, low CD4+ T cell counts and absence of antiretroviral treatment (ART) are known predictive factors for NHL. Even in the era of suppressive ART, HIV-infected individuals remain at increased risk of developing NHL compared to the general population. To search for human genetic determinants of HIV-associated NHL, we performed case-control genome-wide association studies (GWAS) in three cohorts of HIV+ patients of European ancestry and meta-analyzed the results. In total, 278 cases and 1924 matched controls were included. We observed a significant association with NHL susceptibility in the C-X-C motif chemokine ligand 12 ( CXCL12 ) region on chromosome 10. A fine mapping analysis identified rs7919208 as the most likely causal variant (P = 4.77e-11). The G>A polymorphism creates a new transcription factor binding site for BATF and JUND. Analyses of topologically associating domains and promoter capture Hi-C data revealed significant interactions between the rs7919208 region and the promoter of CXCL12 , also known as stromal-derived factor 1 ( SDF-1 ). These results suggest a modulatory role of CXCL12 regulation in the increased susceptibility to NHL observed in the HIV-infected population.
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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 | 0.000 | 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) | 0.007 | 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".