# Project 4: Integrative analysis of spatial molecular features and clinico-pathological characteristics

> **NIH NIH U19** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $1,591,238

## Abstract

PROJECT 4: PROJECT SUMMARY/ABSTRACT
Over the past two decades, we have come to appreciate that the aging brain harbors a multiplicity of
neuropathologies and that AD proteinopathy often coexists with other pathologic features such as Lewy Bodies
and TDP43 proteinopathy. However, the impact of co-occurrence remains poorly understood. Co-occurrence
also increases with advancing age, highlighting that age is a critical risk factor for all of the neuropathologies that
we examine in our 3D Aging & Alzheimer Brain Program. This project aims to profile brain tissue from a large
(n=300) set of diverse individuals to create a complementary resource to those produced in Projects 1-3. Here,
we profile a random sample of participants in the RUSH cohorts to capture the heterogeneity seen in the older
population. In addition, we leverage their detailed ante-mortem characterization of neuropsychologic function to
relate molecular data and the cellular attributes identified in Projects 1-3 to cognitive decline, the ultimate,
clinically meaningful outcome in AD. Amyloid, tau and CAA all influence cognitive performance in the ROSMAP
cohorts. In particular, preliminary results from single nucleus RNAseq data suggest a critical role for a new
microglial subtype, Microglia 13 (Mi13), in AD and CAA. Thus, the new 3D dataset that we propose to generate
and distribute as part of this Project will enable us to test a specific hypothesis that we have today and to uncover
new insights from unbiased analyses. Our samples also include 100 African-American (AA) participants from the
ROSMAP and MARS cohorts that have the same clinicopathologic traits and multiomic brain data as the 200
non-hispanic white (NHW) participants. Here, we therefore explicitly complement the other Projects, which focus
on Non-Hispanic White participants, by sampling a large number of AA subjects so that we can assess the
generalizability of our findings to a broader population. The integrated analysis of the data in this project with the
attributes identified in the other three projects will lead to a new set of candidate proteins involved in cognitive
decline, which will be used to profile a replication cohort of an independent set of participants. Thus, the key
goals for us are (1) the creation of an easily repurposable, high-impact dataset, (2) the testing of a current
hypothesis and (3) assembly of an important set of new insights into AD and CAA that can be used to seed
further investigation, including some dedicated to AA. Overall, this Project creates a unique reference data set
that can be repurposed for a multitude of uses and leveraged to design a next generation of spatial transcriptomic
(ST) studies for other neurodegenerative diseases.

## Key facts

- **NIH application ID:** 10935943
- **Project number:** 5U19AG074862-02
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** PHILIP L DE JAGER
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,591,238
- **Award type:** 5
- **Project period:** 2023-09-30 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10935943

## Citation

> US National Institutes of Health, RePORTER application 10935943, Project 4: Integrative analysis of spatial molecular features and clinico-pathological characteristics (5U19AG074862-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10935943. Licensed CC0.

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