Abstract
Objectives. Before-and-after transcriptomics in rheumatic disease often yields no reproducible
treatment signal, though disease-state stratification is robust. We asked whether exposure and
response-prediction labels fall below the detection floor of the designs defining them, while
matched disease-state labels do not.
Methods. Eight public datasets were analysed (paired juvenile dermatomyositis n = 10; RA before/after
methotrexate, n = 28 pairs; lupus nephritis n = 10; controlled exposures; a single-cell dose series).
Response labels in current use (one benchmark trajectory, five published signatures) were audited in
every analysable source cohort, using effect sizes (dz) against each design's exact minimum detectable
effect.
Results. Disease-state labels were detectable: the interferon signature declined in 10/10 juvenile
dermatomyositis patients (p = 0.002; 59.5% of score variance). No exposure label cleared its design
floor in any clinical cohort; a drug-matched methotrexate prior was nominally significant in juvenile
dermatomyositis yet did not clear its floor (dz = -0.80; CI spanning it). Exposure became detectable
only where prior-context and intensity were jointly favourable (multi-day target tissue dz = 1.24,
q = 0.018; well-level pseudobulk dz = +3.70, floor 1.80). Audited response labels failed in 14 of 15
cohorts (93%; descriptive binomial 95% CI 68-100): eleven below their floors, three sign-reversed;
the largest training cohort pooled to zero (dz = +0.07; I2 = 69%). Effect size ordered reported AUCs
monotonically.
Conclusion. Under conventional treatment intensities, exposure and response-prediction labels are
either undetectable below the design floor or detected with a sign that does not replicate;
disease-state labels are detectable. Part of the negative literature reflects a design floor.