Figure 2. The mass-spectrometry-accessible core CSF proteome and its biological organization.

(a) Workflow for defining the core CSF proteome. Detection tiers assigned by coverage-aware detection (CAD) lower bound 95% CI: Tier A, ≥0.80; Tier B, ≥0.50 to <0.80; Tier C, ≥0.20 to <0.50; Tier D, <0.20; Tier E, insufficient evidence (Supplementary Note 1). (b) Protein detection by number of studies. Absolute (upper) and proportional (middle) protein counts; Median within-study detection (bottom). Colored by detection tier. (c) Number of proteins per detection tier. (d) Detection rates in core CSF proteome (Tier A/B) in lumbar versus cranial CSF, compared across studies (n = 14 lumbar, 8 cranial). (e) External validation in 12 hold-out CSF studies. Precision–recall curves show recovery of tiered proteins; AUPRC and observed held-out detection rate are indicated. (f, g) Biological associations of CSF detectability. Data are log₂ odds ratios comparing proteins in the highest (n = 553) versus lowest (n = 553) quintiles of observed detection for tissue/cell (f) or protein-class (g) annotations. (h, i) CSF protein detection model performance. Predicted detection rate correlated with observed detection across proteins (h; dashed line, identity; solid line, decile means) and discriminated Tier A/B core proteins from non-core candidates (i; AUROC = 0.83, AUPRC = 0.69), outperforming the Waury et al. CSF model on the same benchmark¹⁴. (j) Consensus co-clustering matrix used to resolve six core classes (CC1-CC6). Protein class probabilities were estimated by latent-class modeling using tissue origin, subcellular compartment, and release mechanism features. Fill colour, pairwise co-cluster probability; annotated margin, the six core classes (CC1–CC6). (k) Functional annotation of the six core classes. Bars, top enriched pathways as −log10(FDR); boxed labels, representative markers.