CBM KG: A Comorbidity-Centric Knowledge Graph Uncovering Causal Pathomechanisms Between COVID-19 and Neurodegenerative Diseases
Heval Ataş, Priya Sethumadhavan, Abish Kaladharan, Renata Vieira de Sá, Adithya Sridhar, Undine Haferkamp, Ole Pleß, Andrea Martí-Sarrias, Sandra Acosta, Tamás Letoha, Anett Hudák, Jochen Ohnmacht, Feng Q. HeFeng, Martin Hofmann‐Apitius, Alpha Tom Kodamullil · bioRxiv (Cold Spring Harbor Laboratory) · 2025
Abstract Summary COVID-19 is increasingly recognized as a potential trigger or accelerator of neurodegenerative diseases such as Alzheimer’s and Parkinson’s. To systematically explore the putative molecular and clinical associations between them, we present CBM KG (Causal Biological Mechanisms Knowledge Graph)—a manually curated, comorbidity-centric resource developed within the EU-funded COMMUTE project. CBM KG integrates over 2,800 cause-and-effect or correlative relationships from 63 peer-reviewed publications, highlighting key mechanisms such as viral entry routes, blood-brain barrier alteration, microglial activation, neuroinflammation, and APOE ε4-associated susceptibility. Each relationship in the graph is fully traceable to its source evidence, ensuring transparency and reproducibility. Unlike general-purpose or single disease-focused knowledge graphs, CBM KG is specifically designed to represent causal biological mechanisms spanning both infectious and neurodegenerative processes. By encoding directional, cause-and-effect relationships, it supports the interpretation of clinical co-occurrences through plausible mechanistic links between overlapping disease pathways, offering high-resolution insights at both molecular and clinical levels. Availability and implementation The BEL files, Neo4j database, and Cytoscape visualization files are publicly available at: https://github.com/SCAI-BIO/CBM-Comorbidity-KG .