Isolation of Pure Disease Specific Aging Trajectories in Spatial Transcriptomics via the Delta–Delta Method

Disentangling normal aging from disease driven transcriptional change remains a major obstacle for spatial genomics. We introduce the Delta–Delta (ΔΔ) Method, a contrastive trajectory framework that resolves a four-dimensional progression (genes × cell types × brain regions × time) by subtracting the wild type (WT) aging trajectory from the transgenic (TG) trajectory to yield a pure disease trajectory (ΔΔlog₂FC). The method is platform agnostic, integrates with common spatial transcriptomics workflows, and outputs direction and speed of change summaries, enriched pathways, and region and cell type specific maps. In a demonstration using G2–3 α-synuclein TG mice and age matched WT controls at 6 and 10 months across hippocampus and midbrain, ΔΔ uncovered opposite regional dynamics in glutamatergic neurons and a convergent enrichment of RNA splicing pathways, corroborated by alternative splicing analyses. By explicitly modeling time while controlling for aging within each region and cell type, the ΔΔ Method isolates disease specific molecular programs that are obscured in conventional bulk or single cell analyses, and provides a generalizable framework for trajectory aware mechanistic target prioritization in neurodegeneration and other progressive conditions.