Figure 4. A CSF injury–homeostasis axis tracks disease severity and can be approximated by C5 and NRCAM.

(a) Hierarchical clustering of random-effects-pooled pairwise correlations among the 13 CSF meta-program (MP) activities. (b) PCA of GSVA-derived MP activities across 10,560 CSF samples. Bars, variance explained; line, cumulative variance. Significance assessed against 1,000 permutations (dark bars, FDR < 0.05; muted bars). (c) Proteins ranked by random-effects-pooled Spearman correlation with PC1. Axis-positive (red; n = 71) and axis-negative (blue; n = 236) proteins were defined by |ρ| ≥ 0.40 and FDR ≤ 0.05. (d) GSEA of proteins ordered by pooled PC1 association. Bars, absolute normalized enrichment score (|NES|). (e) Network of significantly enriched gene sets associated with PC1. Nodes, gene sets; edges, Jaccard overlap. (f) Diagnostic groups ranked by mean injury–homeostasis axis score. Heatmap, mean GSVA-derived MP activity; upper margin, MP loadings on PC1; right margin, mean axis scores with 95% CI. (g–i) Multiple clinical endpoint analysis of the axis and MPs in central nervous system lymphoma (CNSL; g), leptomeningeal disease (LMD; h) and glioma (i). CNSL endpoints comprised early versus absent treatment response (n = 34), treatment stage (n = 115), overall survival (OS; n = 33) and tumour burden (n = 30). LMD endpoints comprised LMD status (n = 71), treatment response (n = 90), OS (n = 23), early versus absent treatment response (n = 23) and time to first LMD-negative assessment after treatment (n = 16). Glioma endpoints comprised OS (n = 137), primary versus recurrent disease (n = 115) and WHO grade 2 versus grade 4 disease (n = 237). Binary, continuous and time-to-event endpoints were analysed using logistic regression, correlation or linear models, and Cox regression, respectively. Red, associations with adverse states or outcomes; blue, favourable associations. (j) Pan-oncology synthesis of clinical associations. Points, pooled endpoints (per diagnosis); boxes, median and IQR, marginal tiles; significance (shaded, FDR < 0.05). (k) Differential axis and MP profiles in an external neurodegenerative cohort comprising Alzheimer’s disease (AD; n = 1,883), dementia with Lewy bodies (DLB; n = 763), frontotemporal dementia (FTD; n = 772) and Parkinson’s disease (PD; n = 1,465)⁸². (l) Axis and MP differences between progressive and relapsing–remitting multiple sclerosis (n = 978), and between oligoclonal-band-positive and -negative CSF (n = 800). Bars, standardized mean differences (Cohen’s d). (m) Linear models approximating the injury–homeostasis axis. Models in the Riviere-Cazaux cohort compare intact C5, C5a, C5b–6 and NRCAM combinations; models in the Bader cohort compare C5 and NRCAM with total CSF protein, leukocyte count and the CSF-to-serum albumin quotient (QAlb). The target was injury-homeostasis score calculated as the eigenscore of GSVA enrichment for axis-positive and axis-negative protein sets, with C5 and NRCAM removed before scoring to prevent target leakage. Bader models were trained in the Astral subset (n = 1,627) and evaluated without refitting in held-out pooled timsTOF subsets (n = 4,854). Performance was assessed by R², Spearman ρ and root-mean-square error (RMSE). (n) Observed versus C5–NRCAM-predicted axis scores in held-out Bader timsTOF samples. Dashed line, identity; solid line, linear fit. (o) Random-effects meta-analysis of cohort-specific R² values for C5–NRCAM models across 34 cohorts and 10,559 samples. (p) Integrated model contrasting low-axis neuronal–synaptic homeostasis and CNS barrier integrity with high-axis complement- and plasma-associated inflammation, barrier disruption and injury.