% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Beyer:866306,
      author       = {Beyer, Frauke and Kharabian, Shahrzad and Kratzsch, Jürgen
                      and Schroeter, Matthias L. and Röhr, Susanne and
                      Riedel-Heller, Steffi G. and Villringer, Arno and Witte, A.
                      Veronica},
      title        = {{A} {M}etabolic {O}besity {P}rofile {I}s {A}ssociated
                      {W}ith {D}ecreased {G}ray {M}atter {V}olume in {C}ognitively
                      {H}ealthy {O}lder {A}dults},
      journal      = {Frontiers in aging neuroscience},
      volume       = {11},
      issn         = {1663-4365},
      address      = {Lausanne},
      publisher    = {Frontiers Research Foundation},
      reportid     = {FZJ-2019-05465},
      pages        = {202},
      year         = {2019},
      abstract     = {Obesity is a risk factor for cognitive decline and gray
                      matter volume loss in aging. Studies have shown that
                      different metabolic factors, e.g., dysregulated glucose
                      metabolism and systemic inflammation, might mediate this
                      association. Yet, even though these risk factors tend to
                      co-occur, they have mostly been investigated separately,
                      making it difficult to establish their joint contribution to
                      gray matter volume structure in aging. Here, we therefore
                      aimed to determine a metabolic profile of obesity that takes
                      into account different anthropometric and metabolic measures
                      to explain differences in gray matter volume in aging. We
                      included 748 elderly, cognitively healthy participants (age
                      range: 60 – 79 years, BMI range: 17 – 42 kg/m2) of the
                      LIFE-Adult Study. All participants had complete information
                      on body mass index, waist-to-hip ratio, glycated hemoglobin,
                      total blood cholesterol, high-density lipoprotein,
                      interleukin-6, C-reactive protein, adiponectin and leptin.
                      Voxelwise gray matter volume was extracted from T1-weighted
                      images acquired on a 3T Siemens MRI scanner. We used partial
                      least squares correlation to extract latent variables with
                      maximal covariance between anthropometric, metabolic and
                      gray matter volume and applied permutation/bootstrapping and
                      cross-validation to test significance and reliability of the
                      result. We further explored the association of the latent
                      variables with cognitive performance. Permutation tests and
                      cross-validation indicated that the first pair of latent
                      variables was significant and reliable. The metabolic
                      profile was driven by negative contributions from body mass
                      index, waist-to-hip ratio, glycated hemoglobin, C-reactive
                      protein and leptin and a positive contribution from
                      adiponectin. It positively covaried with gray matter volume
                      in temporal, frontal and occipital lobe as well as
                      subcortical regions and cerebellum. This result shows that a
                      metabolic profile characterized by high body fat, visceral
                      adiposity and systemic inflammation is associated with
                      reduced gray matter volume and potentially reduced executive
                      function in older adults. We observed the highest
                      contributions for body weight and fat mass, which indicates
                      that factors underlying sustained energy imbalance, like
                      sedentary lifestyle or intake of energy-dense food, might be
                      important determinants of gray matter structure in aging.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {571 - Connectivity and Activity (POF3-571)},
      pid          = {G:(DE-HGF)POF3-571},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31427957},
      UT           = {WOS:000478631000001},
      doi          = {10.3389/fnagi.2019.00202},
      url          = {https://juser.fz-juelich.de/record/866306},
}