Bioinformatics and biomolecular tools for biomarker discovery in peripheral blood lymphocytes from patients with Sporadic Amyotrophic Lateral Sclerosis

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Baciu, C. (2012). Bioinformatics and biomolecular tools for biomarker discovery in peripheral blood lymphocytes from patients with Sporadic Amyotrophic Lateral Sclerosis. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Sporadic Amyotrophic lateral sclerosis (sALS) is a complex, invariably fatal, disease with a poorly understood cause, despite many studies. Diagnostic biomarkers that precede active symptoms would be an immense help to clinicians, for patient management, following the progress of clinical studies, and uncovering early events in the development and progression of the disease. Combining bioinformatics of microarrays and molecular biology assays we analyzed and extended the results from experiments performed on peripheral blood lymphocyte (PBL) fractions from an sALS and a normal-matched coronary artery disease (CAD) study. We developed a novel computational pipeline (LO-BaFL) to improve the power and discrimination of identifying differentially expressed (DE) genes on long-oligonucleotide arrays. From sALS samples we performed quantitative polymerase chain reaction (qPCR) validation assays that linked three novel genes, ACTG1, B2M, and ILKAP, to sALS. Selected regions of the DE transcripts were sequenced, which revealed a new, albeit non ALS-linked mutation. Genes revealed as DE by LO-BaFL were examined through pathway and network interaction analysis. Heightened profiles are seen in the immune response signature, apoptosis and responses to chemical stimulus; these correspond well to phenotypes associated with sALS and are good candidates for a simplified blood-based biomarker signature.

Details
Author

Baciu, Cristina

Title

Bioinformatics and biomolecular tools for biomarker discovery in peripheral blood lymphocytes from patients with Sporadic Amyotrophic Lateral Sclerosis

Physical Description

1 online resource (129 pages) : PDF

Date

2012

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Sporadic Amyotrophic lateral sclerosis (sALS) is a complex, invariably fatal, disease with a poorly understood cause, despite many studies. Diagnostic biomarkers that precede active symptoms would be an immense help to clinicians, for patient management, following the progress of clinical studies, and uncovering early events in the development and progression of the disease. Combining bioinformatics of microarrays and molecular biology assays we analyzed and extended the results from experiments performed on peripheral blood lymphocyte (PBL) fractions from an sALS and a normal-matched coronary artery disease (CAD) study. We developed a novel computational pipeline (LO-BaFL) to improve the power and discrimination of identifying differentially expressed (DE) genes on long-oligonucleotide arrays. From sALS samples we performed quantitative polymerase chain reaction (qPCR) validation assays that linked three novel genes, ACTG1, B2M, and ILKAP, to sALS. Selected regions of the DE transcripts were sequenced, which revealed a new, albeit non ALS-linked mutation. Genes revealed as DE by LO-BaFL were examined through pathway and network interaction analysis. Heightened profiles are seen in the immune response signature, apoptosis and responses to chemical stimulus; these correspond well to phenotypes associated with sALS and are good candidates for a simplified blood-based biomarker signature.

Genre

doctoral dissertations

Subjects--Topics

Bioinformatics

Degree

Ph.D.

Keywords

LO-BaFL
Microarray Analysis
Molecular Sequencing
Pathway Analysis
Sporadic Amyotrophic Lateral Sclerosis

Subject Area

Information Technology

Advisor(s)

Weller, Jennifer

Committee Members

Mougeot, Jean-Luc
Sell, Susan
Loraine, Ann
Guo, Jun-Tao

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2012.

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Rights Holder Information

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Identifier

Baciu_uncc_0694D_10280

Permalink

http://hdl.handle.net/20.500.13093/etd:1798