Abstract

Discovery of Novel Serum Biomarkers for Diagnosing and Staging Alzheimer’s DiseaseDipti Jigar ShahDepartment of Chemistry and Biochemistry, BYUDoctor of PhilosophyAlzheimer’s disease (AD) is an untreatable neurologic disease affecting more than 5 million Americans, most over 60 years of age. Protein plaques and neurofibrillary tangles typify AD brain pathology and are thought to cause the progressive dementia and brain shrinkage observed in AD. Currently there are no methods to diagnose the disease at a time before damage becomes irreversible.Biochemical tests for AD using cerebrospinal fluid analysis or neuroimaging are not yet sufficiently sensitive and specific, and they are invasive. This points to a need for a more easily applied and more sensitive diagnostic test. Although the gross anatomical changes are localized to the brain, AD is likely to involve changes throughout the body. As a result of this, changes in the abundance of certain biomolecules present in the circulation system are likely to occur. Consequently, a serum proteomics approach able to measure such changes, when applied to AD, would likely find quantitative changes in relevant molecules that can help diagnose the disease correctly, ideally early in the disease process. The goal of this work was to discover and validate novel diagnostic serum biomarkers for AD. For biomarker discovery and validation, we used a novel serum proteomics approach involving reversed phase capillary-liquid chromatography-electrospray ionization-quadrupole-time of flight mass spectrometry. Our samples were protein depleted, which helped us survey low molecular weight species in the serum without ion suppression from larger proteins like albumin. We were able to observe more than 8000 molecular species in a single run. The overall project was comprised of four studies: (i) discovery of novel potential serum AD markers, (ii) blinded validation of diagnostically promising biomarkers found in the initial study, with their further chemical identification, (iii) exploring gender-based serum AD biomarkers, and (v) discovery of biomarkers that distinguish early versus moderate stage AD. In the first study, the approach found 38 significant (p < 0.05) biomarkers and 21 near significant (p = 0.05 to 0.099) biomarkers. On using the forward selection approach, we built multi-marker panels with specificities and sensitivities higher than 80%.The second study reports on a blinded validation study that was performed on a new set of serum samples. We focused on the 13 most promising AD biomarkers found as part of the initial study. We successfully validated 4 of these biomarkers that showed highly significant statistical p-values. As part of this study, research was conducted to identify these 4 biomarkers, which was accomplished using tandem mass spectrometry with fragmentation experiments. The third study used data from the initial study but looked at gender specific biomarkers. We found 31 significant and near significant serum AD biomarkers for women, 16 for men, and 25 that were gender independent. Multi-marker panels of AD biomarkers for women or men had sensitivities of >60% and specificities >85%.In the fourth study, cases with moderate AD were compared to cases with very mild or mild AD to find novel biomarkers that could be used for staging. We found 44 significant and near significant biomarkers that were quantitatively different between mild and severe AD. In conclusion, we were successful in accomplishing the goal of this work of finding, validating and identifying novel serum biomarkers that diagnose AD.

Degree

PhD

College and Department

Physical and Mathematical Sciences; Chemistry and Biochemistry

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2014-06-01

Document Type

Dissertation

Handle

http://hdl.lib.byu.edu/1877/etd7065

Keywords

Alzheimer’s disease, low-molecular weight serum proteome, lipid biomarkers, gender-based biomarkers, diagnosis, stage comparisons, validation, biomarker identification

Language

english

Included in

Chemistry Commons

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