Distinct cerebrospinal fluid proteomic signatures in sporadic Creutzfeldt-Jakob disease subtypes

Giuseppe Mario Bentivenga, Angela Mammana, Dea Gogishvili, Simone Baiardi, Erica Vittoriosi, Andrea Mastrangelo, Agustina Ranieri, Isabel M. Houtkamp, Kathrin Brockmann, Sanne Abeln, Sabina Capellari, Piero Parchi.

Abstract

INTRODUCTION: Sporadic Creutzfeldt-Jakob disease (sCJD) encompasses six main clinicopathological subtypes. To date, no accurate biomarkers are available for the antemortem diagnosis and prognostication of sCJD subtypes.

METHODS: We measured 797 unique proteins in the cerebrospinal fluid (CSF) of 126 sCJD patients (42 MM(V)1, 42 VV2, and 42 MV2K) and 42 non-neurodegenerative controls (CTRL) using the proximity extension assay, a high throughput proteomic technology.

RESULTS: We identified distinct proteomic profiles across sCJD subtypes, revealing novel biomarkers for their differentiation. Key proteins included HDGF, FOSB, PAG1, APEX1, CCDC80, WASF1, and GPC1. Among the biomarkers correlating with survival, CCDC80 emerged as the strongest prognostic factor. Functional enrichment analyses revealed distinct dysregulated biological pathways across subtypes.

DISCUSSION: We identified CSF protein signatures associated with the most common sCJD subtypes, proposing novel biomarkers for in vivo subtype diagnosis and prognostication and highlighting distinct molecular mechanisms underlying disease heterogeneity.

Figure 1. Study overview. Our dual analytical approach combined machine learning (ML) with pathway-centric methodology using Weighted Gene Co-expression Network Analysis (WGCNA) followed by hierarchical HotNet to identify molecular hubs within these networks. Integrating supervised and unsupervised approaches provided complementary insights: several biomarkers identified with classical ML approaches function as molecular hubs within key dysregulated modules, suggesting their direct pathogenetic roles in sCJD, enabling discovery of novel biological relationships unbiased by prior clinical categorisation. This comprehensive proteomic profiling uncovers distinct CSF signatures associated with common sCJD subtypes, proposing novel biomarkers for in vivo subtyping and prognostication while highlighting molecular mechanisms underlying disease heterogeneity, potentially guiding future therapeutic interventions.

Details:

• Folder analyses contains the code developed in the study