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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},
}