# Using long-range technologies as a multi-omic approach to understand Alzheimer's disease in brain tissue

> **NIH NIH R01** · MAYO CLINIC  JACKSONVILLE · 2020 · $619,340

## Abstract

PROJECT SUMMARY/ABSTRACT
Our long-term goal is to help develop a meaningful therapeutic and pre-symptomatic diagnostic
for Alzheimer’s disease because, while a disease-altering therapeutic is essential, it will not be
sufficient without a diagnostic that identifies disease before symptoms onset. We seek to
contribute to these long-term goals by helping identify specific molecular modifications, and
therefore specific mechanisms, driving disease using long-range optical DNA mapping and
sequencing technologies. Unfortunately, most Alzheimer’s disease genes are only implicated
through common non-functional variants, and it is still unclear how most Alzheimer’s disease
genes are involved in disease. Likewise, individual RNA isoforms in diseased brains for top
Alzheimer’s disease genes and their involvement in disease are poorly understood. Functional
variants and RNA sequencing at the isoform level in diseased brain tissue will provide specific
mechanisms to target for therapeutics and diagnostics. Large short-read sequencing efforts are
already ongoing to identify small functional variants involved in Alzheimer’s disease, but structural
DNA variants—many of which directly affect downstream RNA and proteins—also cause
neurodegenerative diseases. We hypothesize that undiscovered SVs and aberrant RNA isoforms
play a direct role in Alzheimer’s disease. A thorough study in diseased brain using long-range
DNA and RNA technologies will complement current short-read efforts, providing important
disease insights.

## Key facts

- **NIH application ID:** 10030834
- **Project number:** 1R01AG068331-01
- **Recipient organization:** MAYO CLINIC  JACKSONVILLE
- **Principal Investigator:** Mark T W Ebbert
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $619,340
- **Award type:** 1
- **Project period:** 2020-09-15 → 2020-10-01

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10030834

## Citation

> US National Institutes of Health, RePORTER application 10030834, Using long-range technologies as a multi-omic approach to understand Alzheimer's disease in brain tissue (1R01AG068331-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10030834. Licensed CC0.

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