@unpublished{pittir22042,
           month = {September},
           title = {Understanding Immunosenescence in Aging-Related Diseases
With Quantitative Proteomics},
          author = {Zhiyun Cao},
            year = {2014},
        keywords = {Immunosenescence, Aging, Aging-related diseases,sepsis, Alzheimer's disease, Quantitative proteomics},
             url = {http://d-scholarship-dev.library.pitt.edu/22042/},
        abstract = {Immunosenescence refers to the gradual deterioration of the immune system during aging. It is widely accepted that immunosenescence is characterized by diminished immune response, low-grade inflammation, and increased propensity for autoimmunity. These changes in the immune system increase the risk and mortality of diseases among the elderly. Poor response to immunotherapies as a result of immunosenescence can further worsen this situation. Fundamental understanding of immunosenescence is helpful for the prevention and treatment of aging-related diseases. Genomics, transcriptomics, proteomics, and metabolomics can give insight to molecular mechanisms of immunosenescence and its contribution to aging-related diseases. In particular, work presented in this dissertation takes advantage of proteomics methods to understand immunosenescence in two aging-related diseases-sepsis and Alzheimer?s disease (AD).        
        To better study sepsis and AD, novel proteomics platforms are developed in this dissertation. Firstly, a robust platform is developed to improve the coverage of the human plasma proteome and establish statistical criteria for the determination of differentially-expressed proteins. Secondly, a novel data acquisition method using pulsed Q dissociation (PQD) in triple-stage mass spectrometry (MS3) is developed for isobaric tags-based quantitation. This method increases the number of identified and quantified proteins without compromising quantitative accuracy. 
In sepsis studies, proteins involved in inflammation, acute phase response, coagulation, and lipid metabolism are associated with age-related risk of severe sepsis among community-acquired pneumonia patients. In AD studies, a human double transgenic knock-in amyloid precursor protein/presenilin-1 (APP/PS-1) mouse model is employed. The proteome of T-cells and other immune cells (e.g., B-cells and macrophages) from this model is characterized and provides a reference map for future studies. T-cells from APP/PS-1 mice have increased oxidative stress during the progression of AD. Proteomics analysis of T-cells from this mouse model provides molecular basis for this phenomenon. Proteins related to cytoskeleton, energy metabolism, apoptosis, and molecular chaperones are also differentially expressed during AD progression.
Overall, works in this dissertation provide novel platforms for protein identification and quantitation. Application of proteomics platforms to the studies of sepsis and AD provides insight to the molecular mechanisms of immunosenescence. Results from these studies may be helpful for the development of novel diagnosis and treatments.}
}