Claude Hackathon · Life Sciences — Researcher Track

A human T cell keeps the shape of its control architecture while swapping out who is in control.

The causal trans-regulatory network of 22 million primary human CD4⁺ T cells — Marson-lab genome-scale CRISPRi Perturb-seq (Zhu, Dann et al. 2025), measured at Rest, Stim 8h and Stim 48h.


0.92out-degree Gini (hub-dominance) — invariant across all three states
78%of all causal effects driven by the top 5% of regulators
59%of the top-100 hubs displaced across activation — identity turns over
K562hub-dominance replicates in a non-immune cell type (Replogle 2022)
01

The architecture — hub-dominated & sparse-but-pleiotropic

A tiny minority broadcasts nearly all the causal signal (out-degree Gini 0.92; top 5% → ~78% of edges), while a typical gene receives regulation from a moderate number of inputs (in-degree Gini 0.35). Control is broadcast-concentrated but reception-distributed — the first causal confirmation of the Barton/Pritchard 2026 topology prediction, which was made from heritability alone and never tested on perturbation data.

Lorenz curve of out-degree, rank–out-degree, and in-vs-out Gini per state
02

The rewiring — shape-invariant, identity-labile

Total edges swing ±32% and up to 59% of the top-100 hubs are replaced across Rest→8h→48h, yet hub-dominance stays pinned at Gini ≈ 0.92. The TCR signalosome (CD3, ZAP70, LAT…) switches on as the activation-state broadcaster — measured only among knockdowns validated in both states, so it is genuine rewiring, not a detectability artifact.

Edge-count vs Gini, hub-identity scatter, and top-100 hub displacement
03

Generality — not T-cell-specific

To test whether this is T-cell-specific, we ran the same analysis on a second, fully independent atlas — Replogle 2022 Perturb-seq. The hub-dominated, broadcast-concentrated architecture appears again in K562 (a different cell type, lab and platform), and across K562↔RPE1 the shape holds while hub identity turns over ~80% — so the architecture is a general property of causal gene networks, not a T-cell quirk. Its dynamic shape-invariance now stands as a sharp, falsifiable prediction for the next activation-timecourse atlas — the opening experiment of a full program.

Hub-dominance across systems, broadcast/reception asymmetry, and cross-cell-type scatter
04

Disease relevance — a testable lead

Our turnover axis lets us ask what the atlas paper did not: do the hubs that switch on specifically with activation carry more disease risk than the stable ones? Holding hubness constant, activation-gained hubs are ~2× enriched for monogenic-disease (ClinVar) genes vs stable hubs (OR 2.3, p = 0.01); common-variant autoimmune-GWAS is not enriched, so the signal is specific to monogenic immune genes. The druggable, disease-linked gained hubs — ZAP70, ITK, LCK, PTPRC, IL12RB2 — are candidate state-specific control points: a testable disease hypothesis, not a description.

Disease enrichment of state-specific vs stable hubs, and candidate control points

Why it holds — every confound guarded

  • Power: out-degree ↔ cells/perturbation ρ ≈ −0.20 (negative) — not a sampling artifact
  • Edge definition: hub-dominance identical on validated-KD-only edges (Gini 0.91)
  • KD efficiency: out-degree ↔ regulator expression ρ ≈ +0.20 only
  • Detectability: rewiring measured only among knockdowns validated in both states

Where this scales — a full program

  • Resolve direct vs indirect edges (causal structure learning) → a mechanistic map of which hubs act first-hand vs through cascades.
  • Test the dynamic shape-invariance on a second activation timecourse — a clean, pre-registerable prediction.
  • Delivered (preliminary): state-specific hubs are ~2× enriched for monogenic-disease genes (ZAP70/ITK/LCK/PTPRC/IL12RB2) — extend across states, donors and an inborn-errors-of-immunity panel.
  • Built on the atlas authors' released statistics; the topology framing, the invariance law and the guarded turnover are ours.