% 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{Winter:1022510,
      author       = {Winter, Nils R. and Leenings, Ramona and Ernsting, Jan and
                      Sarink, Kelvin and Fisch, Lukas and Emden, Daniel and
                      Blanke, Julian and Goltermann, Janik and Opel, Nils and
                      Barkhau, Carlotta and Meinert, Susanne and Dohm, Katharina
                      and Repple, Jonathan and Mauritz, Marco and Gruber, Marius
                      and Leehr, Elisabeth J. and Grotegerd, Dominik and Redlich,
                      Ronny and Jansen, Andreas and Nenadic, Igor and Nöthen,
                      Markus and Forstner, Andreas and Rietschel, Marcella and
                      Groß, Joachim and Bauer, Jochen and Heindel, Walter and
                      Andlauer, Till and Eickhoff, Simon and Kircher, Tilo and
                      Dannlowski, Udo and Hahn, Tim},
      title        = {{M}ore {A}like than {D}ifferent: {Q}uantifying {D}eviations
                      of {B}rain {S}tructure and {F}unction in {M}ajor
                      {D}epressive {D}isorder across {N}euroimaging {M}odalities},
      publisher    = {arXiv},
      reportid     = {FZJ-2024-01500},
      pages        = {1-8},
      year         = {2021},
      abstract     = {Introduction: Identifying neurobiological differences
                      between patients suffering from Major Depressive Disorder
                      (MDD) and healthy individuals has been a mainstay of
                      clinical neuroscience for decades. However, recent meta- and
                      mega-analyses have raised concerns regarding the
                      replicability and clinical relevance of brain alterations in
                      depression. Methods: Here, we systematically investigate
                      healthy controls and MDD patients across a comprehensive
                      range of modalities including structural magnetic resonance
                      imaging (MRI), diffusion tensor imaging, functional
                      task-based and resting-state MRI under near-ideal
                      conditions. To this end, we quantify the upper bounds of
                      univariate effect sizes, predictive utility, and
                      distributional dissimilarity in a fully harmonized cohort of
                      N=1,809 participants. We compare the results to an MDD
                      polygenic risk score (PRS) and environmental variables.
                      Results: The upper bound of the effect sizes range from
                      partial eta squared = .004 to .017, distributions overlap
                      between $89\%$ and $95\%,$ with classification accuracies
                      ranging between $54\%$ and $55\%$ across neuroimaging
                      modalities. This pattern remains virtually unchanged when
                      considering only acutely or chronically depressed patients.
                      Differences are comparable to those found for PRS, but
                      substantially smaller than for environmental variables.
                      Discussion: We provide a large-scale, multimodal analysis of
                      univariate biological differences between MDD patients and
                      controls and show that even under near-ideal conditions and
                      for maximum biological differences, deviations are extremely
                      small and similarity dominates. We sketch an agenda for a
                      new focus of future research in biological psychiatry
                      facilitating quantitative, theory-driven research, an
                      emphasis on computational psychiatry and multivariate
                      machine learning approaches, as well as the utilization of
                      ecologically valid phenotyping.},
      keywords     = {Neurons and Cognition (q-bio.NC) (Other) / Quantitative
                      Methods (q-bio.QM) (Other) / FOS: Biological sciences
                      (Other)},
      cin          = {INM-7},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5251},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.48550/ARXIV.2112.10730},
      url          = {https://juser.fz-juelich.de/record/1022510},
}