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Rosenbloom, A.

Publications and source records attributed to Rosenbloom, A..

2 recordsLinked to original sources

Spatial Multi-Omics Workflow and Analytical Guidelines for Alzheimer's Neuropathology

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.

neuroscience↗

High-Plex Multiomic Analysis in FFPE Tissue at Single-Cellular and Subcellular Resolution by Spatial Molecular Imaging

The Spatial Molecular Imaging platform (CosMxTM SMI, NanoString Technologies, Seattle, WA) utilizes high-plex in-situ imaging chemistry for both RNA and protein detection. This automated instrument provides 1000s of plex, at high sensitivity (1 to 2 copies/cell), very low error rate (0.0092 false calls/cell) and background ([~]0.04 counts/cell). The imaging system generates three-dimensional super-resolution localization of analytes at [~]2 million cells per sample, four samples per run. Cell segmentation is morphology-based using antibodies, compatible with FFPE samples. Multiomic data (980 RNAs, 108 proteins) were measured at subcellular resolution using FFPE tissues (non-small cell lung (NSCLC) and breast cancer) and allowed identification of over 18 distinct cell types, 10 unique tumor microenvironments, and 100 pairwise ligand-receptor interactions. Over 800,000 single cells and [~]260 million transcripts data are released into the public domain allowing extended data analysis by the entire spatial biology research community.

genomics↗