Cell-specific Gene Regulatory Networks in Alzheimer’s Disease

Abstract

Alzheimer’s disease (AD) does not affect all brain cells in the same way, and a
cell’s dysfunction is thought to involve changes in how its genes are regulated rather
than only changes in their expression. Gene regulatory networks (GRNs) model these
regulatory decisions, and recent single-cell methods can infer a separate network for
each individual cell. How such cell-specific networks change in disease, and whether
any changes are shared across cell types or unique to particular ones, remains largely
unexplored. This work asks which regulatory relationships differ between AD and
healthy cells, and to what extent these differences are cell-type specific. To address
this, the cell-specific GRN method ScReNI is reimplemented in Python and applied
to paired single-nucleus RNA and ATAC data from the SEA-AD cohort (27 donors),
inferring one network per cell for microglia and an excitatory-neuron subclass (L2/3
IT). A differential pipeline then compares the networks against disease severity at
the level of individual transcription-factor-to-target edges and of co-regulated gene
modules, complemented by a module-preservation test, treating the donor as the unit of replication. The inferred networks change relatively little with disease: no edge survives stringent correction and weight-based filtering, the module co-regulation structure is preserved, and no module-specific shift is detected in either cell type. The one robust signal is a modest, severity-graded decline in overall regulatory activity in L2/3 IT neurons that persists after adjusting for sequencing depth and is absent in microglia. The results are best read as an absence of strong evidence rather than evidence of absence, motivating larger cohorts and broader gene panels in future work.