We mapped the causal control architecture of a human immune cell and used it to nominate druggable, disease-relevant targets. From the Marson-lab genome-scale CRISPRi Perturb-seq atlas (22M primary human CD4+ T cells; rest / 8h / 48h activation) we built the causal trans-regulatory network for every validated knockdown -> differentially-expressed gene is one edge, and characterised its architecture. Finding: the network is hub-dominated and sparse-but-pleiotropic (the top 5% of regulators drive ~78% of all trans-effects). The first causal confirmation of the Pritchard-lab 2026 topology prediction. Across activation, it is shape-invariant but identity-labile; the concentration (Gini ~ 0.92) is pinned across all states while up to 59% of the top hubs are replaced. The cell keeps the shape of its control while swapping out who is in control. Every result survives power, edge-definition, knockdown-efficiency and detectability confounds, and replicates in a different cell type (K562). Why it matters: the hubs that switch on specifically with activation are ~2x enriched for monogenic-disease genes and are druggable (ZAP70, ITK, LCK, PTPRC, IL12RB2). The candidate state-specific control points for immune modulation. All results are reproduced from public data with code, a streaming notebook, and figures on GitHub.
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