Matthias Brendel1, Federico Probst1, Anna Jaworska2, Felix Overhoff1, Viktoria Korzhova2, Nathalie L Albert1, Roswitha Beck1, Simon Lindner1, Franz-Josef Gildehaus1, Karlheinz Baumann3, Peter Bartenstein4, Gernot Kleinberger5, Christian Haass5, Jochen Herms6, Axel Rominger7. 1. Department of Nuclear Medicine, Ludwig-Maximilians-University of Munich, Munich, Germany. 2. DZNE-German Center for Neurodegenerative Diseases, Munich, Germany. 3. Roche Pharma Research and Early Development, Neuroscience Discovery, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland. 4. Department of Nuclear Medicine, Ludwig-Maximilians-University of Munich, Munich, Germany SyNergy, Ludwig-Maximilians-University of Munich, Munich, Germany; and. 5. DZNE-German Center for Neurodegenerative Diseases, Munich, Germany SyNergy, Ludwig-Maximilians-University of Munich, Munich, Germany; and Biomedical Center (BMC), Ludwig-Maximilians-University of Munich, Munich, Germany. 6. DZNE-German Center for Neurodegenerative Diseases, Munich, Germany SyNergy, Ludwig-Maximilians-University of Munich, Munich, Germany; and. 7. Department of Nuclear Medicine, Ludwig-Maximilians-University of Munich, Munich, Germany SyNergy, Ludwig-Maximilians-University of Munich, Munich, Germany; and axel.rominger@med.uni-muenchen.de.
Abstract
UNLABELLED: Amyloid imaging by small-animal PET in models of Alzheimer disease (AD) offers the possibility to track amyloidogenesis and brain energy metabolism. Because microglial activation is thought to contribute to AD pathology, we undertook a triple-tracer small-animal PET study to assess microglial activation and glucose metabolism in association with amyloid plaque load in a transgenic AD mouse model. METHODS: Groups of PS2APP and C57BL/6 wild-type mice of various ages were examined by small-animal PET. We acquired 90-min dynamic emission data with (18)F-GE180 for imaging activated microglia (18-kD translocator protein ligand [TSPO]) and static 30- to 60-min recordings with (18)F-FDG for energy metabolism and (18)F-florbetaben for amyloidosis. Optimal fusion of PET data was obtained through automatic nonlinear spatial normalization, and SUVRs were calculated. For the novel TSPO tracer (18)F-GE180, we then calculated distribution volume ratios after establishing a suitable reference region. Immunohistochemical analyses with TSPO antisera, methoxy-X04 staining for fibrillary β-amyloid, and ex vivo autoradiography served as terminal gold standard assessments. RESULTS: SUVR at 60-90 min after injection gave robust quantitation of (18)F-GE180, which correlated well with distribution volume ratios calculated from the entire recording and using a white matter reference region. Relative to age-matched wild-type, (18)F-GE180 SUVR was slightly elevated in PS2APP mice at 5 mo (+9%; P < 0.01) and distinctly increased at 16 mo (+25%; P < 0.001). Over this age range, there was a high positive correlation between small-animal PET findings of microglial activation with amyloid load (R = 0.85; P < 0.001) and likewise with metabolism (R = 0.61; P < 0.005). Immunohistochemical and autoradiographic findings confirmed the in vivo small-animal PET data. CONCLUSION: In this first triple-tracer small-animal PET in a well-established AD mouse model, we found evidence for age-dependent microglial activation. This activation, correlating positively with the amyloid load, implies a relationship between amyloidosis and inflammation in the PS2APP AD mouse model.
UNLABELLED: Amyloid imaging by small-animal PET in models of Alzheimer disease (AD) offers the possibility to track amyloidogenesis and brain energy metabolism. Because microglial activation is thought to contribute to AD pathology, we undertook a triple-tracer small-animal PET study to assess microglial activation and glucose metabolism in association with amyloid plaque load in a transgenic AD mouse model. METHODS: Groups of PS2APP and C57BL/6 wild-type mice of various ages were examined by small-animal PET. We acquired 90-min dynamic emission data with (18)F-GE180 for imaging activated microglia (18-kD translocator protein ligand [TSPO]) and static 30- to 60-min recordings with (18)F-FDG for energy metabolism and (18)F-florbetaben for amyloidosis. Optimal fusion of PET data was obtained through automatic nonlinear spatial normalization, and SUVRs were calculated. For the novel TSPO tracer (18)F-GE180, we then calculated distribution volume ratios after establishing a suitable reference region. Immunohistochemical analyses with TSPO antisera, methoxy-X04 staining for fibrillary β-amyloid, and ex vivo autoradiography served as terminal gold standard assessments. RESULTS: SUVR at 60-90 min after injection gave robust quantitation of (18)F-GE180, which correlated well with distribution volume ratios calculated from the entire recording and using a white matter reference region. Relative to age-matched wild-type, (18)F-GE180 SUVR was slightly elevated in PS2APP mice at 5 mo (+9%; P < 0.01) and distinctly increased at 16 mo (+25%; P < 0.001). Over this age range, there was a high positive correlation between small-animal PET findings of microglial activation with amyloid load (R = 0.85; P < 0.001) and likewise with metabolism (R = 0.61; P < 0.005). Immunohistochemical and autoradiographic findings confirmed the in vivo small-animal PET data. CONCLUSION: In this first triple-tracer small-animal PET in a well-established AD mouse model, we found evidence for age-dependent microglial activation. This activation, correlating positively with the amyloid load, implies a relationship between amyloidosis and inflammation in the PS2APP AD mouse model.
Authors: Nathalie L Albert; Marcus Unterrainer; Matthias Brendel; Lena Kaiser; Markus Zweckstetter; Paul Cumming; Peter Bartenstein Journal: Eur J Nucl Med Mol Imaging Date: 2019-03-02 Impact factor: 9.236
Authors: Julia K Götzl; Matthias Brendel; Georg Werner; Samira Parhizkar; Laura Sebastian Monasor; Gernot Kleinberger; Alessio-Vittorio Colombo; Maximilian Deussing; Matias Wagner; Juliane Winkelmann; Janine Diehl-Schmid; Johannes Levin; Katrin Fellerer; Anika Reifschneider; Sebastian Bultmann; Peter Bartenstein; Axel Rominger; Sabina Tahirovic; Scott T Smith; Charlotte Madore; Oleg Butovsky; Anja Capell; Christian Haass Journal: EMBO Mol Med Date: 2019-06 Impact factor: 12.137
Authors: Nathalie L Albert; M Unterrainer; D F Fleischmann; S Lindner; F Vettermann; A Brunegraf; L Vomacka; M Brendel; V Wenter; C Wetzel; R Rupprecht; J-C Tonn; C Belka; P Bartenstein; M Niyazi Journal: Eur J Nucl Med Mol Imaging Date: 2017-08-19 Impact factor: 9.236
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Authors: Samira Parhizkar; Thomas Arzberger; Matthias Brendel; Gernot Kleinberger; Maximilian Deussing; Carola Focke; Brigitte Nuscher; Monica Xiong; Alireza Ghasemigharagoz; Natalie Katzmarski; Susanne Krasemann; Stefan F Lichtenthaler; Stephan A Müller; Alessio Colombo; Laura Sebastian Monasor; Sabina Tahirovic; Jochen Herms; Michael Willem; Nadine Pettkus; Oleg Butovsky; Peter Bartenstein; Dieter Edbauer; Axel Rominger; Ali Ertürk; Stefan A Grathwohl; Jonas J Neher; David M Holtzman; Melanie Meyer-Luehmann; Christian Haass Journal: Nat Neurosci Date: 2019-01-07 Impact factor: 24.884
Authors: Jatta S Takkinen; Francisco R López-Picón; Rana Al Majidi; Olli Eskola; Anna Krzyczmonik; Thomas Keller; Eliisa Löyttyniemi; Olof Solin; Juha O Rinne; Merja Haaparanta-Solin Journal: J Cereb Blood Flow Metab Date: 2016-01-01 Impact factor: 6.200