The glycosylation patterns on IgA1 antibodies are highly complex and heterogeneous. When there are dysregulations in activities of glycosylation enzymes, the hinge domain of IgA1's, i.e., the peptide domain connecting constant and variable regions, can undergo shifts in glycosylation patterns and become galactose- deficient (Gd). The galactose deficiency, together with other triggers, can lead to an auto-immune response in which patients' own antibodies form complexes with Gd-IgA1's; these complexes precipitate and cause damage in glomeruli, eventually leading to IgA1 nephropathy (IgAN). It is of a great interest to monitor regularly Gd-IgA1's of patients who are predisposed to develop nephropathy. Further, increased understanding of correlations between dynamic variations in glycosylation patterns and the natural development of the disease in individual patients is expected to lead to improved interventions, including individually optimized therapies that could block the formation of offending complexes. None of the current approaches to assess microheterogeneity in glycosylation patterns is completely satisfactory; while elegant, these are also arduous and indirect, limited to highly specialized laboratories and difficult to reproduce in actual patients' samples, in large part due to lack of precise, well-characterized, molecular-level analytical tools We propose to address this issue by systematic isolation of oligonucleotide-based molecular receptors or aptamers that will interact with clusters of different O-glycosides displayed in the hinge subregions. Aptameric receptors will be isolated from large oligonucleotide pools through the process of an in vitro selection and amplification coupled to the affinity separation via interactions with IgA1 hinge regions isolated from both Gd- IgAN patients and healthy controls. Individual aptamers will interact with substructures within the hinge domain, that is, with shorter peptides displaying one or more oligosaccharides. A large number of identified aptamers will be screened for their ability to interact with fractions of polyclonal IgA1's, and a variety of those aptamers that show a quantitatively different response to IgA1s from patients and matched controls will be selected for a more detailed characterization and incorporation in classification sensor arrays (CSAs). As the result of our work, we will have immediately a set of aptamers that would together form a classification sensor array, an artificial nose capable of distinguishing samples belonging to patients with Gd- IgAN from healthy controls, as well as quantifying the extent of shifts in glycosylation patterns. Further molecular-level characterizatio of epitopes (subdomains) that these aptamers recognize is expected to enable studies towards identification of structures that are responsible for auto-immune responses in individual patients, and correlation with secondary triggers of diseases, which are the key step in the rational design of targeted inhibitors of the complex formation.

Public Health Relevance

Complex saccharide structures ('glycans') play crucial roles in a wide range of biological functions and diseases such as autoimmunity, cancer, and nephropathy. We will help elucidate the role of complex glycans in the pathogenesis of IgA nephropathy, one of the most common causes of kidney failure worldwide, by systematically and exhaustively generating oligonucleotide-based receptors (aptamers) for glycan clusters on IgA1 antibodies. This will allow new diagnostic protocols based on pattern recognition with classification arrays and, in the long-term, personalized therapies to prevent antigen-autoantibody interaction and nephropathy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DK109690-02
Application #
9308943
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Gossett, Daniel Robert
Project Start
2016-07-01
Project End
2019-05-31
Budget Start
2017-06-01
Budget End
2019-05-31
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032