guest ::
| Home > Publications Database > Glitter in the Darkness? Nonfibrillar β-Amyloid Plaque Components Significantly Impact the β-Amyloid PET Signal in Mouse Models of Alzheimer Disease. > print |
| Home > Publications Database > Glitter in the Darkness? Nonfibrillar β-Amyloid Plaque Components Significantly Impact the β-Amyloid PET Signal in Mouse Models of Alzheimer Disease. > print |
| 001 | 164000 | ||
| 005 | 20241206141617.0 | ||
| 024 | 7 | _ | |a 10.2967/jnumed.120.261858 |2 doi |
| 024 | 7 | _ | |a pmid:34016733 |2 pmid |
| 024 | 7 | _ | |a pmc:PMC8717179 |2 pmc |
| 024 | 7 | _ | |a 0022-3123 |2 ISSN |
| 024 | 7 | _ | |a 0097-9058 |2 ISSN |
| 024 | 7 | _ | |a 0161-5505 |2 ISSN |
| 024 | 7 | _ | |a 1535-5667 |2 ISSN |
| 024 | 7 | _ | |a 2159-662X |2 ISSN |
| 024 | 7 | _ | |a altmetric:106220575 |2 altmetric |
| 037 | _ | _ | |a DZNE-2022-00669 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Biechele, Gloria |b 0 |
| 245 | _ | _ | |a Glitter in the Darkness? Nonfibrillar β-Amyloid Plaque Components Significantly Impact the β-Amyloid PET Signal in Mouse Models of Alzheimer Disease. |
| 260 | _ | _ | |a New York, NY |c 2022 |b Soc. |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1733490955_23991 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a β-amyloid (Aβ) 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 Aβ PET with gold standard immunohistochemical assessments, the relative contributions of fibrillar and nonfibrillar Aβ components to the in vivo Aβ PET signal remain unclear. Thus, we obtained 2 murine cerebral amyloidosis models that present with distinct Aβ plaque compositions and performed regression analysis between immunohistochemistry and Aβ PET to determine the biochemical contributions to Aβ PET signal in vivo. Methods: We investigated groups of AppNL-G-F and APPPS1 mice at 3, 6, and 12 mo of age by longitudinal 18F-florbetaben Aβ PET and with immunohistochemical analysis of the fibrillar and total Aβ burdens. We then applied group-level intermodality regression models using age- and genotype-matched sets of fibrillar and nonfibrillar Aβ data (predictors) and Aβ PET results (outcome) for both Aβ 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 Aβ content alone sufficed to explain the Aβ PET findings in either AD model. However, a regression model compiling fibrillar and nonfibrillar Aβ together with the estimate of individual heterogeneity and age at scanning could explain a 93% of variance of the Aβ PET signal (P < 0.001). Fibrillar Aβ burden had a 16-fold higher contribution to the Aβ PET signal than nonfibrillar Aβ. However, given the relatively greater abundance of nonfibrillar Aβ, we estimate that nonfibrillar Aβ produced 79% ± 25% of the net in vivo Aβ PET signal in AppNL-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 Aβ PET signal. Conclusion: Taken together, the in vivo Aβ PET signal derives from the composite of fibrillar and nonfibrillar Aβ plaque components. Although fibrillar Aβ has inherently higher PET tracer binding, the greater abundance of nonfibrillar Aβ plaque in AD-model mice contributes importantly to the PET signal. |
| 536 | _ | _ | |a 352 - Disease Mechanisms (POF4-352) |0 G:(DE-HGF)POF4-352 |c POF4-352 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de |
| 650 | _ | 7 | |a PET signal |2 Other |
| 650 | _ | 7 | |a amyloid |2 Other |
| 650 | _ | 7 | |a fibrillar |2 Other |
| 650 | _ | 7 | |a mouse |2 Other |
| 650 | _ | 7 | |a nonfibrillar |2 Other |
| 650 | _ | 2 | |a Plaque, Amyloid |2 MeSH |
| 700 | 1 | _ | |a Sebastian Monasor, Laura |0 P:(DE-2719)2812269 |b 1 |
| 700 | 1 | _ | |a Wind, Karin |0 P:(DE-2719)9001653 |b 2 |
| 700 | 1 | _ | |a Blume, Tanja |0 P:(DE-2719)2811522 |b 3 |
| 700 | 1 | _ | |a Parhizkar, Samira |b 4 |
| 700 | 1 | _ | |a Arzberger, Thomas |0 P:(DE-2719)2811333 |b 5 |
| 700 | 1 | _ | |a Sacher, Christian |b 6 |
| 700 | 1 | _ | |a Beyer, Leonie |b 7 |
| 700 | 1 | _ | |a Eckenweber, Florian |b 8 |
| 700 | 1 | _ | |a Gildehaus, Franz-Josef |b 9 |
| 700 | 1 | _ | |a von Ungern-Sternberg, Barbara |b 10 |
| 700 | 1 | _ | |a Willem, Michael |0 P:(DE-2719)9000433 |b 11 |
| 700 | 1 | _ | |a Bartenstein, Peter |b 12 |
| 700 | 1 | _ | |a Cumming, Paul |b 13 |
| 700 | 1 | _ | |a Rominger, Axel |0 P:(DE-2719)9000971 |b 14 |
| 700 | 1 | _ | |a Herms, Jochen |0 P:(DE-2719)2810441 |b 15 |
| 700 | 1 | _ | |a Lichtenthaler, Stefan F |0 P:(DE-2719)2181459 |b 16 |
| 700 | 1 | _ | |a Haass, Christian |0 P:(DE-2719)2202037 |b 17 |
| 700 | 1 | _ | |a Tahirovic, Sabina |0 P:(DE-2719)2442036 |b 18 |
| 700 | 1 | _ | |a Brendel, Matthias |0 P:(DE-2719)9001539 |b 19 |
| 773 | _ | _ | |a 10.2967/jnumed.120.261858 |g Vol. 63, no. 1, p. 117 - 124 |0 PERI:(DE-600)2040222-3 |n 1 |p 117 - 124 |t Journal of nuclear medicine |v 63 |y 2022 |x 0022-3123 |
| 909 | C | O | |p VDB |o oai:pub.dzne.de:164000 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 1 |6 P:(DE-2719)2812269 |
| 910 | 1 | _ | |a External Institute |0 I:(DE-HGF)0 |k Extern |b 2 |6 P:(DE-2719)9001653 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 3 |6 P:(DE-2719)2811522 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 5 |6 P:(DE-2719)2811333 |
| 910 | 1 | _ | |a External Institute |0 I:(DE-HGF)0 |k Extern |b 11 |6 P:(DE-2719)9000433 |
| 910 | 1 | _ | |a External Institute |0 I:(DE-HGF)0 |k Extern |b 14 |6 P:(DE-2719)9000971 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 15 |6 P:(DE-2719)2810441 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 16 |6 P:(DE-2719)2181459 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 17 |6 P:(DE-2719)2202037 |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 18 |6 P:(DE-2719)2442036 |
| 910 | 1 | _ | |a External Institute |0 I:(DE-HGF)0 |k Extern |b 19 |6 P:(DE-2719)9001539 |
| 913 | 1 | _ | |a DE-HGF |b Gesundheit |l Neurodegenerative Diseases |1 G:(DE-HGF)POF4-350 |0 G:(DE-HGF)POF4-352 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-300 |4 G:(DE-HGF)POF |v Disease Mechanisms |x 0 |
| 914 | 1 | _ | |y 2022 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-01-27 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2021-01-27 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-01-27 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b J NUCL MED : 2021 |d 2022-11-19 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2022-11-19 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2022-11-19 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2022-11-19 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2022-11-19 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2022-11-19 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2022-11-19 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2022-11-19 |
| 915 | _ | _ | |a IF >= 10 |0 StatID:(DE-HGF)9910 |2 StatID |b J NUCL MED : 2021 |d 2022-11-19 |
| 920 | 1 | _ | |0 I:(DE-2719)1140003 |k AG Tahirovic |l Juvenile Neurodegeneration |x 0 |
| 920 | 1 | _ | |0 I:(DE-2719)1110001 |k AG Herms |l Translational Brain Research |x 1 |
| 920 | 1 | _ | |0 I:(DE-2719)1140013 |k Neuropathology / Brainbank |l Neuropathology / Brainbank |x 2 |
| 920 | 1 | _ | |0 I:(DE-2719)1110006 |k AG Lichtenthaler |l Neuroproteomics |x 3 |
| 920 | 1 | _ | |0 I:(DE-2719)1110007 |k AG Haass |l Molecular Neurodegeneration |x 4 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-2719)1140003 |
| 980 | _ | _ | |a I:(DE-2719)1110001 |
| 980 | _ | _ | |a I:(DE-2719)1140013 |
| 980 | _ | _ | |a I:(DE-2719)1110006 |
| 980 | _ | _ | |a I:(DE-2719)1110007 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|