The serum fraction of blood is an ideal material in which to search for novel biomarkers for disease. It is easily obtained through relatively non-invasive means, routinely collected, and a rich treasure-trove of information about the health of an individual. Cells react to signal molecules, take up nutrients, and release waste products, fragments that are the result of proteolysis, and other molecules out into the bloodstream. If these components are unique to the cells in question, that part of the complex mixture that is the blood stream can potentially characterize the health of the tissue or organ those cells are a part of. Serum is dense with proteins that span over ten orders of magnitude in size and abundance. The top 22 most abundant proteins in serum account for 99% of the total protein. These abundant proteins are well-characterized and not useful in a search for novel biomarkers for disease. Removal of these large proteins is accomplished using an organic-solvent precipitation step. Analyzing the resultant mixture of low-molecular-weight serum peptides using cLC-MS produces large, data-rich, and very complex data files. We have developed a manual analysis method we have developed that is capable of performing all of the processing steps necessary to identify novel biomarkers for disease as well as a method for the sequencing of low-abundance, highly charged peptide species without additional sample preparation. These methods are applied to two serum sample sets collected to investigate two pregnancy-related diseases: preterm birth, and preeclampsia. Three novel biomarkers of preterm birth have been identified and a combination of these with 5 previously studied markers can predict women who will have preterm birth with a sensitivity of 89.9% and a specificity of 81.0%. Nineteen different molecular species have been identified that predict women at risk for preeclampsia with a p-value of <0.05. Weighted combinations of various groups of the 19 biomarkers can increase the sensitivity up to 96% and the specificity up to 100%. The use of cLC-MS in the search for novel serum biomarkers of pregnancy-related disease allows for seamless integration from potential biomarker selection to polypeptide sequence identification.
| Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-2896 |
| Date | 28 July 2009 |
| Creators | Merrell, Karen |
| Publisher | BYU ScholarsArchive |
| Source Sets | Brigham Young University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | http://lib.byu.edu/about/copyright/ |
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