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@INPROCEEDINGS{Lalia:283080,
      author       = {Lalia, Manvir and Wagner, Stephan and Hummel, Selina and
                      Thevis, Justus and Prtvar, Danilo and Zatcepin, Artem and
                      Zenatti, Valerio and Bartos, Laura and Tahirovic, Sabina and
                      Brendel, Matthias and Gnörich, Johannes},
      title        = {{C}ell-{T}ype {S}pecific {C}ontributions to {M}etabolic
                      {C}onnectivity in an {A}lzheimer’s {D}isease {M}ouse
                      {M}odel},
      journal      = {Alzheimer's and dementia},
      volume       = {21},
      number       = {Suppl 8},
      issn         = {1552-5260},
      reportid     = {DZNE-2025-01487},
      pages        = {e109909},
      year         = {2025},
      abstract     = {The integration of molecular imaging and multivariate
                      connectivity approaches has emerged as a novel approach to
                      gain insights into the underlying pathophysiology in
                      neurodegenerative diseases. Metabolic connectivity, in
                      particular, has already demonstrated disease-related pattern
                      changes in both human and mammalian brains. However, the
                      cellular sources of disconnected brain regions have not been
                      investigated in detail. This study aimed to elucidate the
                      driving cellular sources of metabolic connectivity in an
                      Alzheimer's disease (AD) mouse model and wild-type mice
                      (WT).After intravenous injection of 45MBq F-18-FDG, a static
                      PET/MRI was performed on APPNL-G-F and age- and sex-matched
                      WT controls to obtain maps of regional FDG uptake and
                      metabolic connectivity. To calculate the inter-regional
                      correlations for metabolic connectivity, 26 delineated brain
                      regions were used, resulting in a 26 × 26 matrix of
                      Pearson's correlation coefficient pairs. Subsequently, the
                      brain was extracted and separated into fore- and hindbrain
                      to achieve region-specific isolation of microglia,
                      astrocytes, oligodendrocytes, and neurons. The radioactivity
                      of each cell fraction was measured to quantify the
                      cell-specific FDG-uptake (Figure 1D).APPNL-G-F mice
                      demonstrated higher FDG uptake compared to WT, along with a
                      significantly increased metabolic connectivity between fore-
                      and hindbrain (Figure 1A-C). Among all cell types,
                      microglial exhibited the highest single-cell FDG uptake, in
                      both mouse models (Figure 1E). In APPNL-G-F mice, microglia,
                      astrocytes, and oligodendrocytes displayed increased FDG
                      uptake, while neurons exhibited reduced uptake compared to
                      WT. The correlation between forebrain and hindbrain cellular
                      FDG uptake was significant across all cell types in the
                      APPNL-G-F model (microglia r=0.89, p = 0.0006; astrocytes
                      r=0.65, p = 0.042; oligodendrocytes r=0.77, p = 0.025 and
                      neurons r=0.51, p = 0.005). In contrast, WT mice did not
                      exhibit any significant correlation in single-cell uptake
                      between forebrain and hindbrain. Notably, region-specific
                      microglial FDG uptake correlated significantly with
                      respective FDG-PET signals in APPNL-G-F mice (forebrain
                      r=0.89, p = 0.007; hindbrain r=0.8, p = 0.014), whereas no
                      significant correlation was observed for other cell
                      types.These findings suggest that microglia are the primary
                      drivers of the increased forebrain-hindbrain metabolic
                      connectivity observed in the AD mouse model. Further RNA
                      expression analyses could provide valuable insights into the
                      molecular mechanisms underlying microglial metabolic
                      coupling in neurodegeneration.},
      month         = {Jul},
      date          = {2025-07-27},
      organization  = {Alzheimer’s Association
                       International Conference, Toronto
                       (Canada), 27 Jul 2025 - 31 Jul 2025},
      keywords     = {Animals / Alzheimer Disease: diagnostic imaging / Alzheimer
                      Disease: metabolism / Alzheimer Disease: pathology /
                      Positron-Emission Tomography / Mice / Brain: diagnostic
                      imaging / Brain: metabolism / Brain: pathology / Disease
                      Models, Animal / Fluorodeoxyglucose F18 / Magnetic Resonance
                      Imaging / Mice, Transgenic / Male / Female / Microglia:
                      metabolism / Neurons: metabolism / Astrocytes: metabolism /
                      Radiopharmaceuticals / Fluorodeoxyglucose F18 (NLM
                      Chemicals) / Radiopharmaceuticals (NLM Chemicals)},
      cin          = {AG Haass / AG Tahirovic},
      ddc          = {610},
      cid          = {I:(DE-2719)1110007 / I:(DE-2719)1140003},
      pnm          = {352 - Disease Mechanisms (POF4-352)},
      pid          = {G:(DE-HGF)POF4-352},
      typ          = {PUB:(DE-HGF)1 / PUB:(DE-HGF)16},
      pubmed       = {pmid:41434580},
      pmc          = {pmc:PMC12725383},
      doi          = {10.1002/alz70862_109909},
      url          = {https://pub.dzne.de/record/283080},
}