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

Choi, M.; Hwang, S.; Kim, K.-S.; Choi, J.; Park, K.; Kim, D.-G.

2025-10-03 bioinformatics
10.1101/2025.10.01.679749 bioRxiv
Show abstract

Disentangling normal aging from disease driven transcriptional change remains a major obstacle for spatial genomics. We introduce the Delta-Delta ({Delta}{Delta}) Method, a contrastive trajectory framework that resolves a four-dimensional progression (genes x cell types x brain regions x time) by subtracting the wild type (WT) aging trajectory from the transgenic (TG) trajectory to yield a pure disease trajectory ({Delta}{Delta}log2FC). 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 -synuclein TG mice and age matched WT controls at 6 and 10 months across hippocampus and midbrain, {Delta}{Delta} 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 {Delta}{Delta} 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.

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