TY  - EJOUR
AU  - Winter, Nils R.
AU  - Leenings, Ramona
AU  - Ernsting, Jan
AU  - Sarink, Kelvin
AU  - Fisch, Lukas
AU  - Emden, Daniel
AU  - Blanke, Julian
AU  - Goltermann, Janik
AU  - Opel, Nils
AU  - Barkhau, Carlotta
AU  - Meinert, Susanne
AU  - Dohm, Katharina
AU  - Repple, Jonathan
AU  - Mauritz, Marco
AU  - Gruber, Marius
AU  - Leehr, Elisabeth J.
AU  - Grotegerd, Dominik
AU  - Redlich, Ronny
AU  - Jansen, Andreas
AU  - Nenadic, Igor
AU  - Nöthen, Markus
AU  - Forstner, Andreas
AU  - Rietschel, Marcella
AU  - Groß, Joachim
AU  - Bauer, Jochen
AU  - Heindel, Walter
AU  - Andlauer, Till
AU  - Eickhoff, Simon
AU  - Kircher, Tilo
AU  - Dannlowski, Udo
AU  - Hahn, Tim
TI  - More Alike than Different: Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder across Neuroimaging Modalities
PB  - arXiv
M1  - FZJ-2024-01500
SP  - 1-8
PY  - 2021
AB  - 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.
KW  - Neurons and Cognition (q-bio.NC) (Other)
KW  - Quantitative Methods (q-bio.QM) (Other)
KW  - FOS: Biological sciences (Other)
LB  - PUB:(DE-HGF)25
DO  - DOI:10.48550/ARXIV.2112.10730
UR  - https://juser.fz-juelich.de/record/1022510
ER  -