# A shared foundation for single genetic investigations of immune responses

> **NIH NIH U01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2022 · $155,483

## Abstract

Abstract
The genetic architecture of the different diseases and traits studied in the AMP projects are
relatively well known and have continued to expand over time. While some causal modeling
using LD score regression and other Mendelian Randomization techniques have been pursued
in each disease to various extents; these efforts have not systematically looked at this collection
of diseases together in a unified fashion. Further, we can enrich the deployment of these
methods with up-to-date results with the genetic architecture of a variety of immune-related
traits that have been mapped in the AMP projects as well as disease-related endophenotypes:
single cell data from individual cell types from blood and tissue, modules of co-expressed
genes, proteins and metabolites from tissue and blood, as well as individual genes, proteins or
metabolites that may be of particular interest. We will therefore bring all up-to-date to bear on
examining whether and how genetic susceptibility to a variety of inflammatory, metabolic, and
neurologic diseases converge onto different immune responses in peripheral blood, other fluid
compartments, and the target tissue of each disease.

## Key facts

- **NIH application ID:** 10518096
- **Project number:** 3U01AG061356-04S2
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** DAVID ALAN BENNETT
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $155,483
- **Award type:** 3
- **Project period:** 2018-09-30 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10518096

## Citation

> US National Institutes of Health, RePORTER application 10518096, A shared foundation for single genetic investigations of immune responses (3U01AG061356-04S2). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10518096. Licensed CC0.

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