Glitter in the Darkness? Nonfibrillar beta-Amyloid Plaque Components Significantly Impact the beta-Amyloid PET Signal in Mouse Models of Alzheimer Disease

Biechele, Gloria; Monasor, Laura Sebastian; Wind, Karin; Blume, Tanja; Parhizkar, Samira; Arzberger, Thomas; Sacher, Christian; Beyer, Leonie; Eckenweber, Florian; Gildehaus, Franz-Josef; Ungern-Sternberg, Barbara von; Willem, Michael; Bartenstein, Peter; Cumming, Paul; Rominger, Axel; Herms, Jochen; Lichtenthaler, Stefan F.; Haass, Christian; Tahirovic, Sabina und Brendel, Matthias (2022): Glitter in the Darkness? Nonfibrillar beta-Amyloid Plaque Components Significantly Impact the beta-Amyloid PET Signal in Mouse Models of Alzheimer Disease. In: Journal of Nuclear Medicine, Bd. 63, Nr. 1: S. 117-124

Abstract

beta-amyloid (A beta) PET is an important tool for quantification of amyloidosis in the brain of suspected Alzheimer disease (AD) patients and transgenic AD mouse models. Despite the excellent correlation of A beta PET with gold standard immunohistochemical assessments, the relative contributions of fibrillar and nonfibrillar A beta components to the in vivo A beta PET signal remain unclear. Thus, we obtained 2 murine cerebral amyloidosis models that present with distinct A beta plaque compositions and performed regression analysis between immunohistochemistry and A beta PET to determine the biochemical contributions to A beta PET signal in vivo. Methods: We investigated groups of App(NL-G-F) and APPPS1 mice at 3, 6, and 12 mo of age by longitudinal F-18-florbetaben A beta PET and with immunohistochemical analysis of the fibrillar and total A beta burdens. We then applied group-level intermodality regression models using age- and genotype-matched sets of fibrillar and nonfibrillar A beta data (predictors) and A beta PET results (outcome) for both A beta mouse models. An independent group of double-hit APPPS1 mice with dysfunctional microglia due to knockout of triggering receptor expression on myeloid cells 2 (Trem2(-/-)) served for validation and evaluation of translational impact. Results: Neither fibrillar nor nonfibrillar A beta content alone sufficed to explain the A beta PET findings in either AD model. However, a regression model compiling fibrillar and nonfibrillar A beta together with the estimate of individual heterogeneity and age at scanning could explain a 93% of variance of the A beta PET signal (P < 0.001). Fibrillar A beta burden had a 16-fold higher contribution to the A beta PET signal than nonfibrillar A beta. However, given the relatively greater abundance of nonfibrillar A beta, we estimate that nonfibrillar A beta produced 79% +/- 25% of the net in vivo A beta PET signal in App(NL-G-F) mice and 25% +/- 12% in APPPS1 mice. Corresponding results in separate groups of APPPS1/Trem2(-/-) and APPPS1/Trem2(+/+) mice validated the calculated regression factors and revealed that the altered fibrillarity due to Trem2 knockout impacts the A beta PET signal. Conclusion: Taken together, the in vivo A beta PET signal derives from the composite of fibrillar and nonfibrillar A beta plaque components. Although fibrillar A beta has inherently higher PET tracer binding, the greater abundance of nonfibrillar A beta plaque in AD-model mice contributes importantly to the PET signal.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin ; Medizin > Munich Cluster for Systems Neurology (SyNergy)
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 0161-5505
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198