Functionally-informed fine-mapping identifies genetic variants linking increased CHD1L expression and HIV restriction in monocytes
Bibliographic record
Abstract
Human Immunodeficiency Virus Type 1 (HIV) set-point viral load is a strong predictor of disease progression and transmission risk. A recent genome-wide association study in individuals of African ancestries identified a region on chromosome 1 significantly associated with decreased HIV set-point viral load. Knockout of the closest gene, CHD1L, enhanced HIV replication in vitro in myeloid cells. However, it remains unclear if HIV spVL associated variants are associated with CHD1L gene expression changes. Here we apply a heuristic fine-mapping approach to prioritize combinations of variants that explain the majority of set-point viral load variance and identify variants likely driving the association. We assess the combined impact of these variants on CHD1L regulation using publicly available sequencing studies, and test the relationship between CHD1L expression and set-point viral load using imputed CHD1L expression from monocytes. Taken together, this work characterizes genetically regulated CHD1L expression and further expands our knowledge of CHD1L-mediated HIV restriction in monocytes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".