Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Department

Biology

First Advisor's Name

DeEtta Kay Mills

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Alejandro Barbieri

Third Advisor's Name

Charles H. Bigger

Fourth Advisor's Name

Ophelia I. Weeks

Fifth Advisor's Name

Wensong Wu

Keywords

Lupus, autoimmune disorders, patient classification, mixed connetive tissue disease, U1 snRNP

Date of Defense

3-21-2014

Abstract

Systemic Lupus Erythematosus (SLE) and Mixed Connective Tissue Disease (MCTD) are chronic, autoimmune disorders that target overlapping autoantigens and exhibit similar clinical manifestations. Despite 40 years of research, a reliable biomarker capable of diagnosing these syndromes has yet to be identified. Previous studies have confirmed that components of the U1 small nuclear ribonucleoprotein complex (U1 snRNP) such as U1A are 1000 fold more autoantigenic than any other nuclear component in SLE patients. Based on these findings, I hypothesize that models derived from the U1 snRNP autoantigenic properties could distinguish SLE from MCTD patients. To test this hypothesis, 30 peptides corresponding to protein regions of the U1 snRNP were tested in triplicates by indirect ELISA in sera from SLE or MCTD subjects. In addition laboratory tests and clinical manifestations data from these patients were included and analyzed in this investigation. Statistical classification methods as well as bioinformatics pattern recognition strategy were employed to determine which combination, if any, of all the variables included in this study provide the best segregation power for SLE and MCTD. The results confirmed that the IgM reactivity for U1 snRNP and U1A have the power to significantly distinguish SLE from MTCD patients as well as identify kidney and lung malfunctions for these subjects (p ≤ 0.05). Furthermore, the data analysis revealed eight novel classification rules for the segregation of SLE and MCTD which are a better classification tool than any of the currently available methods (p ≤ 0.05). Consequently, the results derived from this study support that SLE and MCTD are indeed separate disorders and pioneer the description of eight novel classification criteria capable of significantly discerning between SLE and MCTD patients (p ≤ 0.05).

Identifier

FI14040818

Share

COinS
 

Rights Statement

Rights Statement

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).