Purine nucleoside phosphorylase enables dual metabolic checkpoints that prevent T cell immunodeficiency and TLR7-associated autoimmunity
Bibliographic record
Abstract
Purine nucleoside phosphorylase (PNP) enables the breakdown and recycling of guanine nucleosides. PNP insufficiency in humans is paradoxically associated with both immunodeficiency and autoimmunity, but the mechanistic basis for these outcomes is incompletely understood. Here, we identify two immune lineage-dependent consequences of PNP inactivation dictated by distinct gene interactions. During T cell development, PNP inactivation is synthetically lethal with downregulation of the dNTP triphosphohydrolase SAMHD1. This interaction requires deoxycytidine kinase activity and is antagonized by microenvironmental deoxycytidine. In B lymphocytes and macrophages, PNP regulates Toll-like receptor 7 signaling by controlling the levels of its (deoxy)guanosine nucleoside ligands. Overriding this regulatory mechanism promotes germinal center formation in the absence of exogenous antigen and accelerates disease in a mouse model of autoimmunity. This work reveals that one purine metabolism gene protects against immunodeficiency and autoimmunity via independent mechanisms operating in distinct immune lineages and identifies PNP as a potentially novel metabolic immune checkpoint.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".