Our recent publications:
Carlyle, B.C.; Trombetta, B.A.; Arnold, S.E. Proteomic Approaches for the Discovery of Biofluid Biomarkers of Neurodegenerative Dementias. Proteomes 2018, 6, 32.
Our recent biofluid biomarkers review: http://www.mdpi.com/2227-7382/6/3/32
Increasingly Alzheimer’s Disease (AD) is being defined as a disease of abnormal beta amyloid pathology. Clinically, an individual can still only be definitely diagnosed at autopsy, when a pathologist notes the presence of amyloid plaques in the brain. In research, we can identify amyloid pathology in live individuals by measuring low levels of b amyloid42 peptide in the cerebrospinal fluid (CSF), or high amyloid plaque signals in Positron Emission Tomography (PET) brain scans. Although abnormal amyloid CSF levels may define AD, they don’t do a good job of predicting disease severity, disease progression, or detecting the disease before symptoms appear. For this reason, it is important to define new biomarkers of AD that may enable us to diagnose the disease earlier, tell us more about the disease processes that are active in the brain, and screen patients towards appropriate new treatments. In this review, Becky and Bianca discuss how proteomic mass-spectrometry techniques and multiplexed Enzyme-linked Immunosorbent Assays (ELISAs) may be used to help research into biomarker discovery, and also discuss some of the challenges facing this rapidly developing field.
Trombetta, B.A.; Carlyle, B.C.; Koenig, A.M.; Shaw, L.M.; Trojanowski, J.Q.; Wolk, D.A.; Locascio, J.J.; Arnold, S.E. (2018) The technical reliability and biotemporal stability of cerebrospinal fluid biomarkers for profiling multiple pathophysiologies in Alzheimer's disease. PLOS ONE 13(3): e0193707.
Development and validation of the CMP3 panel: https://doi.org/10.1371/journal.pone.0193707
Alzheimer's disease (AD) is a complex disease driven by multiple biological processes, including neurodegeneration, inflammation, vascular injury, and metabolic dysfunction. Our goal is to create a comprehensive collection of multi-plex and single-plex commercial assays that measures novel biomarkers in cerebrospinal fluid (CSF) related to these pathways for use in translational research settings and in clinical trials. In developing this panel, we focused on vetting three key aspects for each assay: 1) whether the assay was sensitive enough to measure the target in CSF, 2) how reproducible the measurements were over repeat experiments, and 3) the biological stability of each target in CSF over a short-term time period. These evaluations are necessary to ensure that the panel can be used as a sensitive and reliable routine measurement for monitoring drug response in clinical trials and profiling subtypes of AD. In this paper, we identified 32 biomarkers that could be consistently quantified and stable over short-term repeat CSF collections. A subset of these biomarkers form the basis of the CMP3 panel, which is currently being evaluated for its use as a practical way to suggest personalized treatments or interventions.
Arnold, S.E. and Betensky, R.A., 2018. Multicrossover Randomized Controlled Trial Designs in A lzheimer Disease. Annals of neurology.
A discussion of multi-crossover, randomized controlled trial designs: https://onlinelibrary.wiley.com/doi/abs/10.1002/ana.25280
Traditional clinical drug trials with multiple treatment groups and a control group are often very large, long, and expensive to conduct. Worse yet, they are often insensitive to the clinical changes resulting from interventions and fail to detect how each unique Alzheimer’s patient responds to an intervention. However, many of these problems are eliminated by implementing a multi-crossover design in which a subject serves as their own control and undergoes randomized, double-blinded treatment in which they are either receiving the drug or a placebo. Clinical outcomes can then be compared between treatment blocks to determine the efficacy of the drug for each patient. This type of trial eliminates the problems of heterogeneity and is much more sensitive to the study’s outcome, while also allowing for an unbiased examination of the efficacy of a treatment for a single subject. Furthermore, multiple subjects’ data can be combined to estimate efficacy for the patient population using a much smaller sample size than required in a traditional clinical drug trial. These multi-crossover trials allow for more accurate estimations and assessments of treatment effects, mechanisms of action, pharmacokinetics, and pharmacodynamics using fewer costly resources than traditional clinical trials