Neuro-psycho MMSig: multimodal mechanism enrichment platform for neuropsychiatric disorders.

Abstract

Introduction: Understanding the pathophysiology of neurodegenerative and psychiatric disorders requires integrating multimodal data.

Methods: We present Neuro-PsychoMMSig, a web-based platform that identifies disease-specific multimodal mechanistic signatures by integrating multi-omics datasets with causal knowledge graphs (KGs). The platform incorporates six curated KGs (Alzheimer's disease, Parkinson's disease, epilepsy, schizophrenia, bipolar disorder, and type-2 diabetes mellitus) and four network-based algorithms: Clinical Patient Embeddings (CLEP), Candidate Mechanism Perturbation Amplitude (CMPA), Gene Set Enrichment Analysis (GSEA), and CAusal Robust Mapping method in meta-Analysis (CARMA). These tools facilitate qualitative exploration of biomarker interactions and quantitative clinical analysis, including patient stratification, pathway enrichment, and variant fine-mapping.

Results: Application to public Alzheimer's and schizophrenia datasets identified specific biological dysregulations, including G1/S cell cycle phase transition in Alzheimer's disease, and clustered distinct patient subgroups.

Conclusion: Neuro-PsychoMMSig offers a locally deployable tool for biomarker discovery, patient subtyping, and mechanistic hypothesis generation.