MS based approaches for diabetes biomarker discovery

Award Information
Agency:
Department of Health and Human Services
Branch
n/a
Amount:
$738,777.00
Award Year:
2005
Program:
STTR
Phase:
Phase I
Contract:
1R42DK071290-01
Agency Tracking Number:
DK071290
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Intrinsic Bioprobes, Inc.
Intrinsic Bioprobes, Inc., 625 S Smith Rd, Ste 22, Tempe, AZ, 85281
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
URBAN KIERNAN
(480) 804-1778
UKIERNAN@INTRINSICBIO.COM
Business Contact:
(480) 804-1778
DNEDELKOV@INTRINSICBIO.COM
Research Institution:
YALE UNIVERSITY

YALE UNIVERSITY
47 COLLEGE STREET, SUITE 203
NEW HAVEN, CT, 06520

Nonprofit college or university
Abstract
DESCRIPTION (provided by applicant): The objective of this proposal is to apply novel affinity mass spectrometry (AMS) technologies to identify protein biomarkers for pre-diabetes or type 2 diabetes. The methodology used combines micro-affinity protein capture from complex biological solutions with mass spectrometric detection. In this first phase (R21), we will screen the provided plasma and blood cell samples to identify candidate proteins, and protein profiles, that can appropriately differentiate sample origin from 1 of the 3 groups (normal, pre-diabetic and diabetic; as determined by the administration of an oral glucose tolerance test). Both plasma and blood cell samples will be assayed with affinity pipettes derivatized with poly- and monoclonal antibodies for specific protein target analysis. Additionally, groups of proteins will be analyzed via hydrophilic and hydrophobic ligands, metal chelating ligands, and other wide-specificity affinity surfaces. Each of these ligand surfaces possesses specific affinity characteristics that will result in the capture and purification of individual or whole groups of proteins. Protein variations observed as a result of qualitative and/or quantitative differences, that have statistical significance and correctly group samples according to their origin, will be viewed as potential biomarkers. In the second (validation) phase (R33), we will validate the discovered biomarker(s) via the application of the same methods and approaches to a larger group of sample cohorts through the use of high throughput parallel robotic processing. In the event that multiple protein biomarkers are validated, AMS panels for diabetes will be developed. This will be achieved through the construction of multi-analyte affinity pipettes that will selectively retrieve the targeted biomarkers that differentiate healthy from diseased states. Such panels will also be subject to the same validation process that each of its components endured. The ultimate result of this research will be validated protein biomarkers for pre-and type 2 diabetes and technology that are ready for clinical screening and diagnosis of the disease.

* information listed above is at the time of submission.

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