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@ARTICLE{Palleis:154328,
      author       = {Palleis, Carla and Sauerbeck, Julia and Beyer, Leonie and
                      Harris, Stefanie and Schmitt, Julia and Morenas-Rodriguez,
                      Estrella and Finze, Anika and Nitschmann, Alexander and
                      Ruch-Rubinstein, Francois and Eckenweber, Florian and
                      Biechele, Gloria and Blume, Tanja and Shi, Yuan and
                      Weidinger, Endy and Prix, Catharina and Bötzel, Kai and
                      Danek, Adrian and Rauchmann, Boris-Stephan and Stöcklein,
                      Sophia and Lindner, Simon and Unterrainer, Marcus and
                      Albert, Nathalie L. and Wetzel, Christian and Rupprecht,
                      Rainer and Rominger, Axel and Bartenstein, Peter and Herms,
                      Jochen and Perneczky, Robert and Haass, Christian and Levin,
                      Johannes and Höglinger, Günter and Brendel, Matthias},
      title        = {{I}n {V}ivo {A}ssessment of {N}euroinflammation in
                      4‐{R}epeat {T}auopathies},
      journal      = {Movement disorders},
      volume       = {36},
      number       = {4},
      issn         = {1531-8257},
      address      = {New York, NY},
      publisher    = {Wiley},
      reportid     = {DZNE-2021-00182},
      pages        = {883 - 894},
      year         = {2021},
      note         = {ISSN 1531-8257 not unique: **3 hits**.},
      abstract     = {Sleep complaints are the most prevalent syndromes in older
                      adults, particularly in women. Moreover, they are frequently
                      accompanied with a high level of depression and stress.
                      Although several diffusion tensor imaging (DTI) studies
                      reported associations between sleep quality and brain white
                      matter (WM) microstructure, it is still unclear whether
                      gender impacts the effect of sleep quality on structural
                      alterations, and whether these alterations mediate the
                      effects of sleep quality on emotional regulation. We
                      included 389 older participants (176 females, age = 65.5 ±
                      5.5 years) from the 1000BRAINS project. Neuropsychological
                      examinations covered the assessments of sleep quality,
                      depressive symptomatology, current stress level, visual
                      working memory, and selective attention ability. Based on
                      the DTI dataset, the diffusion parameter maps, including
                      fractional anisotropy (FA), mean diffusivity (MD), axial
                      diffusivity (AD), and radial diffusivity (RD), were
                      calculated and normalized to a population-specific FA
                      template. According to the global Pittsburgh Sleep Quality
                      Index (PSQI), 119 poor sleepers (PSQI: 10∼17) and 120 good
                      sleepers (PSQI: 3∼6) were identified. We conducted a two
                      by two (good sleepers/poor sleepers) × (males/females)
                      analysis of variance by using tract-based spatial statistics
                      (TBSS) and JHU-ICBM WM atlas-based comparisons. Moreover, we
                      performed a voxel-wise correlation analysis of brain WM
                      microstructure with the neuropsychological tests. Finally,
                      we applied a mediation analysis to explore if the brain WM
                      microstructure mediates the relationship between sleep
                      quality and emotional regulation. No significant differences
                      in brain WM microstructure were detected on the main effect
                      of sleep quality. However, the MD, AD, and RD of pontine
                      crossing tract and bilateral inferior cerebellar peduncle
                      were significant lower in the males than females. Voxel-wise
                      correlation analysis revealed that FA and RD values in the
                      corpus callosum were positively related with depressive
                      symptomatology and negatively related with current stress
                      levels. Additionally, we found a significantly positive
                      association between higher FA values in visual-related WM
                      tracts and better outcomes in a visual pattern recognition
                      test. Furthermore, a mediation analysis suggested that
                      diffusion metrics within the corpus callosum partially
                      mediated the associations between poor sleep quality/high
                      stress and depressive symptomatology.},
      keywords     = {Aged / Alzheimer Disease / Animals / Brain: diagnostic
                      imaging / Brain: metabolism / Cross-Sectional Studies /
                      Female / Humans / Male / Mice / Middle Aged / Supranuclear
                      Palsy, Progressive: diagnostic imaging / Supranuclear Palsy,
                      Progressive: genetics / Tauopathies: diagnostic imaging /
                      Tauopathies: genetics / tau Proteins: genetics / tau
                      Proteins: metabolism},
      cin          = {AG Haass / AG Herms / U Clinical Researchers - München /
                      AG Levin / AG Höglinger 1 / Clinical Research (Munich)},
      ddc          = {610},
      cid          = {I:(DE-2719)1110007 / I:(DE-2719)1110001 /
                      I:(DE-2719)7000003 / I:(DE-2719)1111016 / I:(DE-2719)1110002
                      / I:(DE-2719)1111015},
      pnm          = {342 - Disease Mechanisms and Model Systems (POF3-342) / 344
                      - Clinical and Health Care Research (POF3-344) / 352 -
                      Disease Mechanisms (POF4-352) / 354 - Disease Prevention and
                      Healthy Aging (POF4-354) / 353 - Clinical and Health Care
                      Research (POF4-353)},
      pid          = {G:(DE-HGF)POF3-342 / G:(DE-HGF)POF3-344 /
                      G:(DE-HGF)POF4-352 / G:(DE-HGF)POF4-354 /
                      G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:33245166},
      doi          = {10.1002/mds.28395},
      url          = {https://pub.dzne.de/record/154328},
}