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Articles by John Q. Trojanowski
Total Records ( 10 ) for John Q. Trojanowski
  Shaohua Xu , Kurt R. Brunden , John Q. Trojanowski and Virginia M.-Y. Lee
  Background The assembly of tau proteins into paired helical filaments, the building blocks of neurofibrillary tangles, is linked to neurodegeneration in Alzheimer's disease and related tauopathies. A greater understanding of this assembly process could identify targets for the discovery of drugs to treat Alzheimer's disease and related disorders. By using recombinant human tau, we have delineated events leading to the conversion of normal soluble tau into tau fibrils. Methods Atomic force microscopy and transmission electron microscopy methodologies were used to determine the structure of tau assemblies that formed when soluble tau was incubated with heparin for increasing lengths of time. Results Tau initially oligomerizes into spherical nucleation units of 18- to 21-nm diameter that appear to assemble linearly into nascent fibrils. Among the earliest tau fibrils are species that resemble a string of beads formed by linearly aligned spheres that with time seem to coalesce to form straight and twisted ribbon-like filaments, as well as paired helical filaments similar to those found in human tauopathies. An analysis of fibril cross sections at later incubation times revealed three fundamental axial structural features. Conclusions By monitoring tau fibrillization, we showed that different tau filament morphologies coexist. Temporal changes in the predominant tau structural species suggest that tau fibrillization involves the generation of structural intermediates, resulting in the formation of tau fibrils with verisimilitude to their authentic human counterparts.
  Stephen D. Weigand , Prashanthi Vemuri , Heather J. Wiste , Matthew L. Senjem , Vernon S. Pankratz , Paul S. Aisen , Michael W. Weiner , Ronald C. Petersen , Leslie M. Shaw , John Q. Trojanowski , David S. Knopman and Clifford R. Jack
  Background Positron-emission tomography (PET) imaging of amyloid with Pittsburgh Compound B (PIB) and Aβ42 levels in the cerebrospinal fluid (CSF Aβ42) demonstrate a highly significant inverse correlation. Both these techniques are presumed to measure brain Aβ amyloid load. The objectives of this study were to develop a method to transform CSF Aβ42 measures into calculated PIB measures (PIBcalc) of Aβ amyloid load, and to partially validate the method in an independent sample of subjects. Methods In all, 41 subjects from the Alzheimer‘s Disease Neuroimaging Initiative (ADNI) underwent PIB PET imaging and lumbar puncture (LP) at the same time. This sample, referred to as the ”training“ sample (nine cognitively normal subjects, 22 subjects with mild cognitive impairment, and 10 subjects with Alzheimer‘s disease), was used to develop a regression model by which CSF Aβ42 (with apolipoprotein E ɛ4 carrier status as a covariate) was transformed into units of PIB PET (PIBcalc). An independent ”supporting“ sample of 362 ADNI subjects (105 cognitively normal subjects, 164 subjects with mild cognitive impairment, and 93 subjects with Alzheime‘s disease) who underwent LP but not PIB PET imaging had their CSF Aβ42 values converted to PIBcalc. These values were compared with the overall PIB PET distribution found in the ADNI subjects (n = 102). Results A linear regression model demonstrates good prediction of actual PIB PET from CSF Aβ42 measures obtained in the training sample (R2 = 0.77, P < .001). PIBcalc data (derived from CSF Aβ42) in the supporting sample of 362 ADNI subjects who underwent LP but not PIB PET imaging demonstrate group-wise distributions that are highly consistent with the larger ADNI PIB PET distribution and with published PIB PET imaging studies. Conclusion Although the precise parameters of this model are specific for the ADNI sample, we conclude that CSF Aβ42 can be transformed into PIBcalc measures of Aβ amyloid load. Brain Aβ amyloid load can be ascertained at baseline in therapeutic or observational studies by either CSF or amyloid PET imaging and the data can be pooled using well-established multiple imputation techniques that account for the uncertainty in a CSF-based PIBcalc value.
  Bradley T. Hyman , Creighton H. Phelps , Thomas G. Beach , Eileen H. Bigio , Nigel J. Cairns , Maria C. Carrillo , Dennis W. Dickson , Charles Duyckaerts , Matthew P. Frosch , Eliezer Masliah , Suzanne S. Mirra , Peter T. Nelson , Julie A. Schneider , Julie A. Schneider , Bill Thies , John Q. Trojanowski , Harry V. Vinters and Thomas J. Montine
  A consensus panel from the United States and Europe was convened recently to update and revise the 1997 consensus guidelines for the neuropathologic evaluation of Alzheimer's disease (AD) and other diseases of brain that are common in the elderly. The new guidelines recognize the pre-clinical stage of AD, enhance the assessment of AD to include amyloid accumulation as well as neurofibrillary change and neuritic plaques, establish protocols for the neuropathologic assessment of Lewy body disease, vascular brain injury, hippocampal sclerosis, and TDP-43 inclusions, and recommend standard approaches for the workup of cases and their clinico-pathologic correlation.
  Michal J. Figurski , Teresa Waligorska , Jon Toledo , Hugo Vanderstichele , Magdalena Korecka , Virginia M.Y. Lee , John Q. Trojanowski and Leslie M. Shaw
  Background The interassay variability and inconsistency of plasma β-amyloid (Aβ) measurements among centers are major factors precluding the interpretation of results and a substantial obstacle in the meta-analysis across studies of this biomarker. The goal of this investigation was to address these problems by improving the performance of the bioanalytical method. Methods We used the Luminex immunoassay platform with a multiplex microsphere-based reagent kit from Innogenetics. A robotic pipetting system was used to perform crucial steps of the procedure. The performance of this method was evaluated using two kit control samples and two quality control plasma samples from volunteer donors, and by retesting previously assayed patient samples in each run. This setup was applied to process 2454 patient plasma samples from the Alzheimer‘s Disease Neuroimaging Initiative study biofluid repository. We have additionally evaluated the correlations between our results and cerebrospinal fluid (CSF) biomarker data using mixed-effects modeling. Results The average precision values of the kit controls were 8.3% for Aβ1-40 and 4.0% for Aβ1-42, whereas the values for the plasma quality controls were 6.4% for Aβ1-40 and 4.8% for Aβ1-42. From the test–retest evaluation, the average precision was 7.2% for Aβ1-40 and 4.5% for Aβ1-42. The range of final plasma results for Alzheimer‘s Disease Neuroimaging Initiative patients was 13 to 372 pg/mL (median: 164 pg/mL) for Aβ1-40 and 3.5 to 103 pg/mL (median: 39.3 pg/mL) for Aβ1-42. We found that sample collection parameters (blood volume and time to freeze) have a small, but significant, influence on the result. No significant difference was found between plasma Aβ levels for patients with Alzheimer‘s disease and healthy control subjects. We have determined multiple significant correlations of plasma Aβ1-42 levels with CSF biomarkers. The relatively strongest, although modest, correlation was found between plasma Aβ1-42 levels and CSF p-tau181/Aβ1-42 ratio in patients with mild cognitive impairment. Plasma Aβ1-40 correlations with CSF biomarkers were weaker and diminished completely when we used longitudinal data. No significant correlations were found for the plasma Aβ1-42/Aβ1-40 ratio. Conclusions The precision of our robotized method represents a substantial improvement over results reported in the literature. Multiple significant correlations between plasma and CSF biomarkers were found. Although these correlations are not strong enough to support the use of plasma Aβ measurement as a diagnostic screening test, plasma Aβ1-42 levels are well suited for use as a pharmacodynamic marker.
  Mary D. Naylor , Jason H. Karlawish , Steven E. Arnold , Ara S. Khachaturian , Zaven S. Khachaturian , Virginia M.-Y. Lee , Matthew Baumgart , Sube Banerjee , Cornelia Beck , Kaj Blennow , Ron Brookmeyer , Kurt R. Brunden , Kathleen C. Buckwalter , Meryl Comer , Kenneth Covinsky , Lynn Friss Feinberg , Giovanni Frisoni , Colin Green , Renato Maia Guimaraes , Lisa P. Gwyther , Franz F. Hefti , Michael Hutton , Claudia Kawas , David M. Kent , Lewis Kuller , Kenneth M. Langa , Robert W. Mahley , Katie Maslow , Colin L. Masters , Diane E. Meier , Peter J. Neumann , Steven M. Paul , Ronald C. Petersen , Mark A. Sager , Mary Sano , Dale Schenk , Holly Soares , Reisa A. Sperling , Sidney M. Stahl , Vivianna van Deerlin , Yaakov Stern , David Weir , David A. Wolk and John Q. Trojanowski
  To address the pending public health crisis due to Alzheimer‘s disease (AD) and related neurodegenerative disorders, the Marian S. Ware Alzheimer Program at the University of Pennsylvania held a meeting entitled "State of the Science Conference on the Advancement of Alzheimer's Diagnosis, Treatment and Care," on June 21-22, 2012. The meeting comprised four workgroups focusing on Biomarkers; Clinical Care and Health Services Research; Drug Development; and Health Economics, Policy, and Ethics. The workgroups shared, discussed, and compiled an integrated set of priorities, recommendations, and action plans, which are presented in this article.
  Jon B. Toledo , Estefania Toledo , Michael W. Weiner , Clifford R. Jack , William Jagust , Virginia M.-Y. Lee , Leslie M. Shaw and John Q. Trojanowski
  Background There is epidemiological evidence that cardiovascular risk factors (CVRF) also are risk factors for Alzheimer‘s disease, but there is limited information on this from neuropathological studies, and even less from in vivo studies. Therefore, we examined the relationship between CVRF and amyloid-β (Aβ) brain burden measured by Pittsburgh Compound B-positron emission tomography (PiB-PET) studies in the Alzheimer‘s Disease Neuroimaging Initiative. Methods Ninety-nine subjects from the Alzheimer‘s Disease Neuroimaging Initiative cohort who had a PiB-PET study measure, apolipoprotein E genotyping data, and information available on CVRF (body mass index [BMI], systolic blood pressure, diastolic blood pressure [DBP], and cholesterol and fasting glucose test results) were included. Eighty-one subjects also had plasma cortisol, C-reactive protein, and superoxide dismutase 1 measurements. Stepwise regression models were used to assess the relation between the CVRF and the composite PiB-PET score. Results The first model included the following as baseline variables: age, clinical diagnosis, number of apolipoprotein ɛ4 alleles, BMI (P = .023), and DBP (P = .012). BMI showed an inverse relation with PiB-PET score, and DBP had a positive relation with PiB-PET score. In the second adjusted model, cortisol plasma levels were also associated with PiB-PET score (P = .004). Systolic blood pressure, cholesterol, or impaired fasting glucose were not found to be associated with PiB-PET values. Conclusion In this cross-sectional study, we found an association between Aβ brain burden measured in vivo and DBP and cortisol, indicating a possible link between these CVRF and Aβ burden measured by PiB-PET. These findings highlight the utility of biomarkers to explore potential pathways linking diverse Alzheimer‘s disease risk factors.
  John Q. Trojanowski , Steven E. Arnold , Jason H. Karlawish , Mary Naylor , Kurt R. Brunden and Virginia M.-Y. Lee
  The emerging global epidemic of Alzheimer‘s disease (AD) demands novel paradigms to address the two unmet needs of the field: (a) cost-effective health care delivery programs/services, and (b) clinical and basic research to accelerate therapy discovery/development. This report outlines a model demonstration project, the Marian S. Ware Alzheimer Program at the University of Pennsylvania, which was designed to achieve four specific aims: (1) improve the integration and continuity of AD care; (2) identify biomarkers that detect the earliest presence of AD and related neurodegenerative cognitive disorders; (3) enhance both the design and conduct of clinical trials as well as review their results to more effectively test new AD therapies and translate valuable therapies into clinical practice; and (4) discover and develop novel disease-modifying small molecule treatments for AD. The ”Ware-UPenn“ program has been presented in this report as a useful prototype for partnerships between private philanthropy and academia in planning and developing programs to address a major national public health problem.
  Mitchel A. Kling , John Q. Trojanowski , David A. Wolk , Virginia M.Y. Lee and Steven E. Arnold
  Vascular disease was once considered the principal cause of aging-related dementia. More recently, however, research emphasis has shifted to studies of progressive neurodegenerative disease processes, such as those giving rise to neuritic plaques, neurofibrillary tangles, and Lewy bodies. Although these studies have led to critical insights and potential therapeutic strategies, interest in the role of systemic and cerebrovascular disease mechanisms waned and has received relatively less attention and research support. Recent studies suggest that vascular disease mechanisms play an important role in the risk for aging-related cognitive decline and disorders. Vascular disease frequently coexists with cognitive decline in aging individuals, shares many risk factors with dementias considered to be of the ”Alzheimer type,“ and is observed more frequently than expected in postmortem material from individuals manifesting ”specific“ disease stigmata, such as abundant plaques and tangles. Considerable difficulties have emerged in attempting to classify dementias as being related to vascular versus neurodegenerative causes, and several systems of criteria have been used. Despite multiple attempts, a lack of consensus remains regarding the optimal means of incorporating vascular disease into clinical diagnostic, neurocognitive, or neuropathologic classification schemes for dementias. We propose here an integrative, rather than a strictly taxonomic, approach to the study and elucidation of how vascular disease mechanisms contribute to the development of dementias. We argue that, instead of discriminating between, for example, ”Alzheimer's disease,“ ”vascular dementia,“ and other diseases, there is a greater need to focus clinical and research efforts on elucidating specific pathophysiologic mechanisms that contribute to dementia phenotypes and neuropathologic outcomes. We outline a multitiered strategy, beginning with clinical and public health interventions that can be implemented immediately, enhancements to ongoing longitudinal studies to increase their informative value, and new initiatives to capitalize on recent advances in systems biology and network medicine. This strategy will require funding from multiple public and private sources to support collaborative and interdisciplinary research efforts to take full advantage of these opportunities and realize their societal benefits.
  Niklas Mattsson , Ulf Andreasson , Staffan Persson , Maria C. Carrillo , Steven Collins , Sonia Chalbot , Neal Cutler , Diane Dufour- Rainfray , Anne M. Fagan , Niels H.H. Heegaard , Ging-Yuek Robin Hsiung , Bradley Hyman , Khalid Iqbal , D. Richard Lachno , Alberto Lleo , Piotr Lewczuk , Jose L. Molinuevo , Piero Parchi , Axel Regeniter , Robert Rissman , Hanna Rosenmann , Giuseppe Sancesario , Johannes Schroder , Leslie M. Shaw , Charlotte E. Teunissen , John Q. Trojanowski , Hugo Vanderstichele , Manu Vandijck , Marcel M. Verbeek , Henrik Zetterberg , Kaj Blennow and Stephan A. Kaser
  Background The cerebrospinal fluid (CSF) biomarkers amyloid beta 1–42, total tau, and phosphorylated tau are used increasingly for Alzheimer's disease (AD) research and patient management. However, there are large variations in biomarker measurements among and within laboratories. Methods Data from the first nine rounds of the Alzheimer's Association quality control program was used to define the extent and sources of analytical variability. In each round, three CSF samples prepared at the Clinical Neurochemistry Laboratory (Molndal, Sweden) were analyzed by single-analyte enzyme-linked immunosorbent assay (ELISA), a multiplexing xMAP assay, or an immunoassay with electrochemoluminescence detection. Results A total of 84 laboratories participated. Coefficients of variation (CVs) between laboratories were around 20% to 30%; within-run CVs, less than 5% to 10%; and longitudinal within-laboratory CVs, 5% to 19%. Interestingly, longitudinal within-laboratory CV differed between biomarkers at individual laboratories, suggesting that a component of it was assay dependent. Variability between kit lots and between laboratories both had a major influence on amyloid beta 1–42 measurements, but for total tau and phosphorylated tau, between-kit lot effects were much less than between-laboratory effects. Despite the measurement variability, the between-laboratory consistency in classification of samples (using prehoc-derived cutoffs for AD) was high (>90% in 15 of 18 samples for ELISA and in 12 of 18 samples for xMAP). Conclusions The overall variability remains too high to allow assignment of universal biomarker cutoff values for a specific intended use. Each laboratory must ensure longitudinal stability in its measurements and use internally qualified cutoff levels. Further standardization of laboratory procedures and improvement of kit performance will likely increase the usefulness of CSF AD biomarkers for researchers and clinicians.
  Matthew J. Winton , Lionel M. Igaz , Margaret M. Wong , Linda K. Kwong , John Q. Trojanowski and Virginia M.-Y. Lee
  TAR DNA-binding protein 43 (TDP-43) is the disease protein in frontotemporal lobar degeneration with ubiquitin-positive inclusions (FTLD-U) and amyotrophic lateral sclerosis (ALS). Although normal TDP-43 is a nuclear protein, pathological TDP-43 is redistributed and sequestered as insoluble aggregates in neuronal nuclei, perikarya, and neurites. Here we recapitulate these pathological phenotypes in cultured cells by altering endogenous TDP-43 nuclear trafficking and by expressing mutants with defective nuclear localization (TDP-43-ΔNLS) or nuclear export signals (TDP-43-ΔNES). Restricting endogenous cytoplasmic TDP-43 from entering the nucleus or preventing its exit out of the nucleus resulted in TDP-43 aggregate formation. TDP-43-ΔNLS accumulates as insoluble cytoplasmic aggregates and sequesters endogenous TDP-43, thereby depleting normal nuclear TDP-43, whereas TDP-43-ΔNES forms insoluble nuclear aggregates with endogenous TDP-43. Mutant forms of TDP-43 also replicate the biochemical profile of pathological TDP-43 in FTLD-U/ALS. Thus, FTLD-U/ALS pathogenesis may be linked mechanistically to deleterious perturbations of nuclear trafficking and solubility of TDP-43.
 
 
 
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