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Podium Presentations: Wednesday, July 22, 2015
BRAIN PHOSPHOPROTEOME NETWORK ANALYSIS DISCRIMINATES ALZHEIMER’S DISEASE FROM OTHER TAUOPATHIES
Eric B. Dammer1, Rujing Ren2, Duc M. Duong1, Andrew K. Lee2, Marla Gearing2, James J. Lah2, Allan I. Levey2, Nicholas T. Seyfried3, 1 Emory University School of Medicine, Atlanta, GA, USA; 2Emory University, Atlanta, GA, USA; 3Emory University School of Medicine, Atlanta, GA, USA. Contact e-mail:
[email protected] Background: Neurofibrillary tangles (NFT), scaffolds of highly phosphorylated tau protein, are a core pathological feature of Alzheimer’s disease (AD) and several other neurodegenerative diseases collectively termed tauopathies, which include progressive supranuclear palsy (PSP), corticobasal degeneration (CBD) and certain frontotemporal dementias. There are six isoforms of human tau in brain and over 40 serine (S), threonine (T), and tyrosine (Y) tau phosphorylation sites have been identified. Progressive site-specific phosphorylation of tau at specific S/T/Y sites is hypothesized to cause both functional deficits as well as gain-of-function toxicity that ultimately lead to NFT formation, synaptic loss, and cognitive dysfunction. Despite being clinically distinct diseases it remains unclear whether site-specific tau phosphorylation differs between AD and other tauopathies. Methods: Following tissue homogenization and in-solution trypsin digestion, phosphopeptides were enriched by an optimized immobilized metal affinity chromatography (IMAC) protocol using ferric chloride from individual AD, tauopathy (CBD and PSP) and age-matched control postmortem human brain tissues (n¼ 7 per group). Liquid chromatographytandem mass spectrometry (LC-MS/MS) was subsequently employed to identify and quantify tau phosphopeptides among other globally enriched phosphopeptides from each tissue sample. Accurate peptide mass and retention time was used to derive signal intensity for every phosphopeptide across LC-MS/MS runs for each case. Results: In total, 77 tau phosphopeptides representing 32 S/T/Y sites were analyzed by WeiGhted Correlation Network Analysis (WGCNA) to delineate tau phosphosites co-enriched in a disease specific manner. Correlated intensity with other phosphopeptides from the same samples, and the phosphorylation pattern of tau itself each suggest that mechanisms underlying site-specific tau phosphorylation differ between AD and other tauopathies. Conclusions: This study highlights the utility of mass spectrometry based proteomics to quantify tau and other brain phosphosignatures with potential to discriminate AD from other tauopathies. O4-12-04
PERK INHIBITION IMPROVES STRUCTURAL AND FUNCTIONAL ABNORMALITIES IN TAU TRANSGENIC MICE
Shelby E. Meier, Michelle C. Bell, Alexandria Ingram, Danielle N. Lyons, David K. Powell, Moriel Vandsburger, Joe F. Abisambra, University of Kentucky, Lexington, KY, USA. Contact e-mail:
[email protected] Background: A major challenge in tauopathy research is the lack of effective therapeutic strategies. This is partly due to unclear understanding of the pathogenic mechanisms leading to tau pathogenesis. We recently established that the most toxic form of tau chronically activates the endoplasmic reticulum (ER) stress sensor PERK. Under conditions of ER stress, PERK momentarily inhibits RNA translation. If sustained, as it occurs in tauopathies, long-term attenuation of protein synthesis weakens and kills tau-bearing cells. Methods: We inhibited PERK with a novel compound, GSK2606414, in rTg4510 tau transgenic model. Mice were treated
from 4 to 7 months of age, which coincides with mild cognitive defects, moderate neuron loss, and early tau pathology. Every month during the treatment course, we measured neuronal function and brain volume by adapting an innovative imaging technique called MEMRI (manganese-enhanced MRI). At the end of treatment, we performed cognitive testing and quantified changes in tau pathology. Results: The drug effectively inhibited PERK in the tau transgenic mice. In addition, drug-treated tau mice showed virtually complete recovery of brain 1) structure and 2) function, 3) significant cognitive improvements, and 4) dramatically reduced soluble tau levels. Meanwhile, pathological tau deposits remained the same as vehicle-treated transgenic controls. Conclusions: These data suggest that PERK is a potent therapeutic target for tauopathies. A major advantage of our strategy is preventative/early therapeutic paradigm of our study. Therefore, the therapeutic potential of PERK inhibition could impact early and late stage tauopathic patients. Future efforts aim to develop safe and effective PERK inhibitors for the clinic. O4-12-05
INTERACTION BETWEEN MICROTUBULEASSOCIATED PROTEIN TAU AND RNA BINDING PROTEINS STIMULATES TAU MISFOLDING AND STRESS GRANULE FORMATION
Tara Vanderweyde1, Kathrerine Youmans-Kidder1, Daniel J. Apicco1, Peter E.A. Ash1, Casey Cook2, Leonard Petrucelli2, Benjamin Wolozin1, 1 Boston University School of Medicine, Boston, MA, USA; 2Mayo Clinic, Jacksonville, FL, USA. Contact e-mail:
[email protected] Background: Microtubule associated protein tau (Tau) is predom-
inantly expressed in axons, but the accumulation of misfolded/ aggregated Tau in the somatic and dendritic compartments is a pathological hallmark of Alzheimer’s disease (AD). The reason for this mislocalization and the role of dendritic tau is poorly understood. Identifying the biological signals that regulate this process could highlight novel therapeutic targets for AD. RNA binding proteins (RBPs) are a class of about 800 proteins that function in the nucleus to regulate mRNA maturation. RBPs also function in the cytoplasm where they regulate RNA translation, trafficking, sequestration and degradation; in neurons, these RNA functions occur mainly in the soma and dendrite. Increasing evidence links neurological disease processes to dysfunction of neuronal RBPs, RNA granules and stress granules (SGs). We have recently shown that RBPs, including TIA1, colocalize with neuropathology in brain tissue of subjects with Alzheimer’s disease (AD) and fulfill the criteria of SGs. We hypothesized that Tau might function to regulate SG formation and the translational stress response. Methods: We used primary cultures of cortical neurons from tau knockout mice and TIA-1 knockout mice to examine the effects of tau on formation of stress granules containing TIA-1, and the effects of TIA-1 on tau misfolding. We examined the interactions of these proteins using immunocytochemistry, super-resolution imaging, immunoprecipitations, mass spectroscopy/proteomics, development of photo-convertible constructs and live cell imaging. Results: We now report a novel function for tau in regulating dendritic RNA granules. Tau accelerates SG formation and is required for normal interactions of TIA1 with proteins linked to RNA metabolism. Loss of tau abrogates interactions of TIA1 with proteins linked to RNA metabolism, including ribosomal proteins and RNA binding proteins. TIA1 associated SGs also stimulate the pathophysiology of tau, increasing tau misfolding, slowing tau catabolism and
Podium Presentations: Wednesday, July 22, 2015
stimulating neurodegeneration. The role of tau in translational biology identifies novel pharmacological interventions, such that preventing SG formation pharmacologically or via TIA1 knockout reduces tau granules and blocks tau-mediated neurodegeneration. Conversely, stimulating SG formation increases tau granules and promotes neurodegeneration. Conclusions: These results present novel functions for tau, and point to new routes for pharmacotherapy of tauopathies.
O4-12-06
THE ALZHEIMER’S METABOLOME: IDENTIFICATION OF NOVEL MARKERS AND TREATMENT TARGETS
Rima Kaddurah-Daouk1, Mitch A. Kling2, Leslie M. Shaw2, Steven E. Arnold2, John Q. Trojanowski2, Jon B. Toledo2, Andrew J. Saykin3, Sungeun Kim3, Li Shen3, Xianlin Han4, Dayan B. Goodenowe5, Tara Smith5, Vijitha Senanayake5, P. Murali Doraiswamy1, 1Duke University Medical Center, Durham, NC, USA; 2University of Pennsylvania, Philadelphia, PA, USA; 3Indiana University School of Medicine, Indianapolis, IN, USA; 4Sanford-Burnham Medical Research Institute, Orlando, FL, USA; 5Phenomenome Discoveries Inc., Saskatoon, SK, Canada. Contact e-mail:
[email protected]
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the metabolome in early and late AD. Both serum and CSF samples were profiled (30-60 per group AD, MCI and controls). Univariate and multivariate analyses was used to define between-group differences; partial least square-discriminant analysis models to classify diagnostic groups and pathway and network analysis to connect metabolic changes. Subjects enrolled in ADNI I study (close to 800) are profiled to replicate initial findings and to link peripheral metabolic changes with genetic and imaging data. Results: Metabolites and their ratios revealed changes within tryptophan, tyrosine, methionine, and purine metabolic pathways. Partial correlation network showed total tau most directly related to purine pathway metabolite xanthine and a tyrosine pathway metabolites; amyloid-beta (Ab42) was related directly to an unidentified metabolite and indirectly to 5-indole acetic acid (5HIAA) and methionine. We used stepwise logistic regression models with cross-validation to assess the ability of metabolite markers from two metabolomics platforms GCTOF and LCECA to discriminate between clinically diagnosed AD participants and cognitively normal controls (testing area under the curve: 0.70 and 0.96, respectively). Lipidomics
Background: Metabolomics an area of high priority for development
at NIH (Common Funds Initiative) provides powerful tools to measure hundreds to thousands of metabolites to define trajectory of biochemical changes, perturbations within and across biochemical pathways, and their relationship to clinical and pathologic progression in Alzheimer’s disease (AD). Such information can lead to new insights about disease mechanism and development of signatures as biomarkers for disease and progression. Metabotypes (metabolic state of patient) captures net interactions between genome, environment and gut microbiome interactions providing information that can possibly bridge the gap between genotype, phenotype and disease subtypes. Methods: We used GCTOF/MS, LC/MS, LCECA metabolomics platforms as well as shot gun lipidomics to define
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