Frederick Rohlfing and Dr. John Kauwe, Department of Biology
Introduction
Alzheimer’s disease (AD) is a severe chronic neurodegenerative disorder and the most common form of dementia1. Unfortunately, there is little understanding of its cause, let alone a cure for the 5.3 million affected Americans2. In my research, a novel proteomics method is being used to identify peptides in the serum that are linked with AD. We have already identified 36 peptides as statistically significant biomarkers and need to characterize these amino acid sequences. By characterizing these biomarkers we will be able to provide important information on how to accurately diagnose AD, its causes, and how to cure it.
Methods
In order to sequence biomarker peptides, we are using the LTQ-Orbitrap XL hybrid mass spectrometer and cLC-ESI-QTOF-MS/MS system. We run the serum samples through our instrument, and set the resolution to only allow the flight path of species with specific mass to charge ratio (m/z) values to isolate the peptide of choice to continue through the instrument. These species are fragmented in the collision cell with nitrogen gas at peptide bonds. The collision fragments are detected by our mass spectrometer. Using Mascot, a search engine with sequence databases that can be used to perform peptide identification from mass spectrometry fragmentation data, we will identify the amino acids in the sequence from the instrumental spectra and then the peptide. By characterizing the amino acid sequence of the peptides we will be able to identify the peptide’s parent protein, locate where these proteins are synthesized, and their relationship to AD.
We have recently received our validation samples that we are also currently processing in a blind fashion to validate the 36 peptide markers found in the original data set.
Progress of the Project
Two of the peptide sequences have been characterized and identified. Problems with the mass spectrometer have delayed the identification timeline and the processing of the final validation samples. The final validation samples have been all run and are currently being analyzed in a blind fashion in order to produce replication for the previously identified 36 statistically significant biomarkers in the original data set. After normalizing our original data, two different combinations of biomarkers had areas under the curves (AUC) of .912 and .908, and 4 other panels of markers had AUC greater than .8. With six combinations of biomarkers over the .8 level of significance, there is great potential for these results to produce a serum diagnoses for AD. The data has also been clumped and no batching effects were found.
Discussion
With the mass spectrometer instrument working, the final steps of validating the original results of the project are expected to be completed quickly and smoothly. The results will provide more clues to diagnosing AD, leading patients to seek early care and delay onset of its debilitating effects.
Acknowledgements
My mentor, Dr. Kauwe, has helped me learn how to take on and overcome the challenges of being a scientist, while always keeping in mind the spiritual nature of all things. I’d also like to acknowledge Dipti Shah, Dr. Graves, and Jesse Cobell who have inspired me with their dedication in the pursuit of discovering the unknown. I’d also like to thank the ORCA committee for funding this project.
References
- Price JL, Morris JC (1999) Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease. Ann Neurol 45:358-368
- Alzheimer’s Association (2010) Alzheimer’s Disease Facts and Figures, Alzheimer’s & Dementia 6:1-70