bioRxivNeurosciencePreprint
Spatial Multi-Omics Workflow and Analytical Guidelines for Alzheimer's Neuropathology
Xuehan SuniD, Hannah R. Hudson, Timothy C. Orr, Srinivas KoutarapuiD, Alyssa B. RosenbloomiD, Matthew H. IngallsiD, Oliver BraubachiD, Christopher Dirk KeeneiD, Joseph BeechemiD, Miranda E. OrriD
- Citations
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Abstract
Spatial biology technologies enable high-dimensional profiling within intact tissues, revealing how molecular and cellular organization drives function and disease. As these platforms gain broader adoption, standardized analytical frameworks are needed to ensure data quality and reproducibility. Here, we present an end-to-end pipeline for the GeoMx Digital Spatial Profiler that simultaneously generates whole-transcriptome and 637-protein measurements from user-defined regions within the same tissue sections. The workflow integrates morphology-guided region selection, quality control, normalization, and multi-modal data interpretation. Applied to formalin-fixed cortical tissues from Alzheimers disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, and controls, the framework resolves spatially distinct molecular domains. Transcript and protein signals diverge across amyloid plaque cores and surrounding glial-rich regions, with RNA-protein concordance varying by disease condition, while single-neuron profiling with and without pathogenic tau deposition illustrates protein assay sensitivity. This dataset provides a rigorously validated resource for spatial multi-omic analyses and establishes broadly applicable guidelines for reliable, reproducible profiling of complex tissues.
- organism: human
- assay: spatial transcriptomics
- assay: proteomics
- research focus: spatial domain detection
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
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