# Project 1: Discovery of proteins with altered abundance and stability

> **NIH NIH U19** · UNIVERSITY OF WASHINGTON · 2020 · $498,693

## Abstract

Abstract
Despite the association between the levels of CSF Aβ42, tau, phosphorylated tau and underlying AD
pathology, measures of biomarker accuracy for clinical diagnosis vary widely between studies. Given that
other neurodegenerative conditions can present with AD-like clinical symptoms, and individuals with AD
frequently have comorbid pathologies, additional markers are needed that can aid in differential diagnosis and
identify mixed pathologies. Over the last decade, many candidate biomarkers have been identified, reflecting a
range of pathophysiological processes including cholesterol metabolism, neuroinflammation and amyloid
processing. However, few, have been adopted in clinical practice or been validated in large independent
cohorts1.
The MacCoss lab and others have been pioneering the development of next generation proteomics methods
as an alternative to the classic stochastic mass spectrometry-based methods. These new methods offer a
hybrid between a targeted and global proteomics strategy. While mass spectrometry data is collected in an
unbiased way, the data is analyzed in a targeted strategy where specific peptides, albeit 1000s are analyzed
using prior information. Thus, the reproducible targeting, throughput, and confident MS/MS-based
quantification of parallel reaction monitoring (PRM) can be combined with classical discovery methods' ability
to qualitatively detect thousands of proteins. These new methods based on systematically collected mass
spectrometry data can offer similar quantitative figures of merit and can be validated in analogous fashion to
clinical assays.
Despite advances in proteomics technologies, most attempts at discovering new CSF markers have either
used 1) stochastic sampling methods (e.g. data dependent acquisition) with poorly characterized quantitative
performance, 2) small sample cohorts, 3) focused entirely on total CSF, 4) ignored protein processing, and 5)
did not consider protein misfolding or stability. The purpose of this project within the cooperative research
program is to take our methods to another level – apply true quantitative methods to large well
characterized cohorts and extend them to functionally relevant subpopulations.
We have a CSF assay that can measure >1050 proteins from completely unfractionated material with figures
of merit of within/between day precision, linearity, LOD/LOQ, etc... Furthermore, we can use this assay on
subsets of the CSF proteome to assess functionally relevant aspects of the neurobiology including quantity as
part of solution or CSF particles, intact protein MW, and protein stability. Finally, we have enough throughput
to apply these analyses on a scale sufficient to eliminate the chance that an observation is due to an aberrant
subpopulation.

## Key facts

- **NIH application ID:** 9854154
- **Project number:** 1U19AG065156-01
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Michael MacCoss
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $498,693
- **Award type:** 1
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9854154

## Citation

> US National Institutes of Health, RePORTER application 9854154, Project 1: Discovery of proteins with altered abundance and stability (1U19AG065156-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9854154. Licensed CC0.

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