# Supplemental for Detection of Glycopeptides of MCI in Patient Serum

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $274,488

## Abstract

Abstract: Alzheimer’s disease (AD) is a neurodegenerative disorder that accounts for the majority of dementia
cases, which affects around 30 million patients worldwide. Mild cognitive impairment (MCI) has been recognized
as an intermediate state of clinical impairment before advanced AD. Due to changes in the brain triggered by AD
before the presentation of initial symptoms, such as for MCI, there is a need for early-stage diagnosis biomarker
research. However, early-stage diagnosis of AD represents a significant challenge due to a lack of definitive
biomarkers, an overlap of biomarkers with other similar neurodegenerative diseases, and the ability to find
minimally invasive methods for detection of these biomarkers. It has been shown that unique changes in
glycosylation in proteins that involve structural changes in glycan groups may be important as serum biomarkers
for early detection of various diseases. We have identified such potential glycopeptides from patient serum,
which may serve to identify early-stage MCI development. In the proposed work we will thus employ a targeted
mass spectrometry approach to screen patient serum for markers of MCI versus normal based on the detailed
structure of glycans and their site specificity. This will be based on our aim to use a multiplexed Parallel Reaction
Monitoring (PRM-MS) assay to quantitatively detect targeted glycopeptides where we can monitor up to 50 target
markers simultaneously. We will then demonstrate an initial confirmation study using the PRM assay of potential
glycopeptide markers that can discriminate among normal versus MCI patients and determine the performance
of each marker based on its sensitivity/specificity. This work will result in glycopeptide biomarkers of early-stage
MCI using a multiplexed PRM-MS method where these markers will then be available for further clinical
validation. In addition, we will also test this method against samples from other neurodegenerative diseases.

## Key facts

- **NIH application ID:** 10492874
- **Project number:** 3R01CA160254-11S1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** David M. Lubman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $274,488
- **Award type:** 3
- **Project period:** 2012-05-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10492874

## Citation

> US National Institutes of Health, RePORTER application 10492874, Supplemental for Detection of Glycopeptides of MCI in Patient Serum (3R01CA160254-11S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10492874. Licensed CC0.

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