Morphometric Inverse Divergence Networks Combined with HYDRA Identify Parkinson’s Disease Subtypes with Distinct Transcriptomic and Serum Biomarker Profiles

Parkinson’s disease (PD) is the second most common age-related neurodegenerative disorder, yet it remains unclear whether cortical architecture can reveal biologically distinct subtypes with distinct molecular and serum biomarker signatures. Two hundred PD patients and 121 healthy controls underwent structural MRI. Subject-specific cortical similarity networks were constructed using Morphometric INverse Divergence (MIND), and subtypes were identified with HYDRA. Spatial patterns were linked to regional gene expression from the Allen Human Brain Atlas through partial least squares regression, followed by functional and cell-type enrichment analyses. Serum neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) were quantified using single-molecule array assays. No significant MIND differences emerged when PD patients were analysed as a single group. HYDRA identified two subtypes (ARI = 0.85) with divergent cortical organization that only partially overlapped with conventional motor phenotypes. Cluster 1 exhibited temporo-parietal MIND increases associated with synaptic and oligodendroglial signatures, without serum biomarker associations. Cluster 2 showed widespread fronto-cingulate MIND reductions enriched for mitochondrial, lysosomal, and proteostatic pathways, including the KEGG Parkinson’s disease pathway, and these reductions correlated with higher serum NfL and GFAP. These findings reveal two biologically distinct PD subtypes with divergent molecular architecture and systemic neurodegeneration beyond conventional motor phenotyping.