|Kristin R. Wildsmith, Ph.D., is currently a scientist in the Pharmacodynamic biomarker group at Genentech. She develops biomarker strategies and quantitative MS assays to support preclinical and clinical trials with a focus on multiplexed, targeted-proteomic assays. Kristin completed her postdoctoral training with Randall Bateman at Washington University in St. Louis. She studied the kinetics of proteins implicated in Alzheimer’s disease using the SILK approach (in vivo stable-isotope labeled-kinetics). In Kristin’s graduate studies, she used mass spectrometry to elucidate the metabolism of lipids implicated in cardiovascular disease. Kristin received her Ph.D. in Biochemistry and Molecular Biology from St. Louis University and her B.S. in Chemistry from Furman University.
Skyline & Panorama Case Study: Targeted proteomics enables Alzheimer’s disease biomarker development
Developing biomarkers is no easy task, yet they are critical for successful drug development and for clinical diagnostics. To help fill the gap between discovery and clinical validation, with the help of Skyline, we developed a targeted-proteomic, multiple reaction monitoring (MRM) assay for the quantitation of 39 peptides corresponding to 30 cerebrospinal fluid (CSF) proteins. The candidate biomarkers were selected from multiple proteomic discovery experiments and biology that linked them to Alzheimer’s disease (AD). As the leading cause of dementia, Alzheimer’s disease is perhaps the most feared disease of the aging. Although CSF levels of Abeta42, tau, and p-tau181 are well established as diagnostic biomarkers of AD, there is a need for additional CSF biomarkers of neuronal function that continue to change during disease progression and could be used in clinical trials. We evaluated the candidate biomarkers in a pilot study using longitudinal CSF samples collected from aged, cognitively-normal control individuals, mildly-cognitive impaired (MCI) and AD subjects. Using a targeted proteomics approach, we confirmed previous findings for a subset of markers, defined longitudinal performance of our panel of markers, and established a flexible proteomics method for robust multiplexed analyses.