# Core C: Spatial Multiomics Core

> **NIH NIH U19** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $1,304,574

## Abstract

SPATIAL MULTIOMICS CORE: PROJECT SUMMARY/ABSTRACT
To investigate how disease relevant changes, such as Alzheimer’s disease, are linked to specific risk factors
(e.g., age-related changes, protein aggregates, vascular pathologies, etc.) to alter the spatial arrangement
of cell types in the brain and their gene expression profiles, we need to build high-resolution maps of brain
tissue at the cellular level in individuals with and without pathology. Building these maps requires proper
characterization of the pathological features, as well as a reproducible workflow for data generation and
imaging. To this end, the Spatial Multiomics Core will work closely with the Biospecimen Core, the Integrated
Computational Analysis Core, and the four Projects to provide standardized, high quality generation and
integration of large-scale spatial molecular data. Thus, the overall proposal will directly address an unmet
need in the field to provide state of the art, rigorous, spatially resolved transcriptomic and proteomic data
acquisition and integration methods, applied to human postmortem tissue at scale. This Core encompasses
the generation of this data required for the research in the four main Projects in this proposal. Specifically,
this Core will perform spatially resolved transcriptomics (ST) and multiplexed proteomics using iterative
indirect immunofluorescence imaging (4i) experiments in postmortem tissue spanning a range of ages and
pathologies and age-matched controls. The overarching aims of this core are: i) to build and optimize robust
workflows based on existing protocols, to thereby enable the generation of Project data at high throughput
and scale (Aims 1 and 2); and ii) to adopt new protocols for imaging-based validation studies on fixed and
frozen tissue, to thereby enable the integration of new technology into the multiomics workflow (Aim 3). The
completion of these objectives will provide a standardized body of data and analysis workflows for the
Projects in this proposal, setting the stage for the careful cell type and gene expression signature analyses
carried out in all of these projects. Finally, this overall framework will ultimately provide a rigorously curated,
large-scale data set that will enable novel understanding of how differing etiologies produce specific
pathological features, how these relate to physiology in each CNS cell type, and how the dysfunction in the
various assemblies of cell types within brain regions lead to differing clinical presentation.

## Key facts

- **NIH application ID:** 10935935
- **Project number:** 5U19AG074862-02
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Hemali Phatnani
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,304,574
- **Award type:** 5
- **Project period:** 2023-09-30 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10935935

## Citation

> US National Institutes of Health, RePORTER application 10935935, Core C: Spatial Multiomics Core (5U19AG074862-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10935935. Licensed CC0.

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