# Glycoengineering IgA1 in IgA nephropathy

> **NIH NIH R21** · BRIGHAM AND WOMEN'S HOSPITAL · 2020 · $227,145

## Abstract

ABSTRACT
IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide and often progresses to
end stage renal disease due to the absence of disease-specific modifying therapies. Unlike many other
autoimmune diseases, an autoantigen in IgAN has been identified and characterized. Altered O-glycosylation
in the heavy chain of IgA1 exposes antigenic determinants, which are targets of naturally occurring IgG1
and, to a lesser extent, IgA1 antibodies. The resulting circulating immune complexes together with
complement deposit in the kidney to promote mesangial cell proliferation and matrix expansion, which in turn
induce glomerular dysfunction. The objective of this proposal is to develop novel glycoengineering
techniques to restore glycosylation of the IgA and thus inhibit its autoantigenicity. Successful completion of
this proposal could lead to the development of a new disease-specific therapeutic strategy for the treatment
of IgA. This is a high-risk proposal as there are conceivable pitfalls with developing the techniques for
restoring glycosylation. The high-reward is the potential to normalize IgA1 glycan structures and thus avert
the generation and subsequent deposition of pathogenic IgA1-anti-IgA1 immune complexes and associated
glomerulonephritis.

## Key facts

- **NIH application ID:** 10072958
- **Project number:** 1R21AI154930-01
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Robert McCullough Anthony
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $227,145
- **Award type:** 1
- **Project period:** 2020-06-03 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10072958

## Citation

> US National Institutes of Health, RePORTER application 10072958, Glycoengineering IgA1 in IgA nephropathy (1R21AI154930-01). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10072958. Licensed CC0.

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