Replicable gray matter correlates of depression and the link to neurotransmitter profiles
Poster No:
511
Submission Type:
Abstract Submission
Authors:
Janik Goltermann1, Klaus Berger2, Tilo Kircher3, Tim Hahn4, Udo Dannlowski5
Institutions:
1University of Münster, Münster, Nordrhein-Westfalen, 2Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany, 3Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Hesse, 4University of Münster, Münster, Germany, 5Institute for Translational Psychiatry, Münster, North Rhine-Westphalia
First Author:
Co-Author(s):
Klaus Berger
Institute of Epidemiology and Social Medicine, University of Muenster
Muenster, Germany
Institute of Epidemiology and Social Medicine, University of Muenster
Muenster, Germany
Introduction:
Introduction: Major depressive disorder (MDD) is one of the leading causes of disability (Friedrich, 2017) and is still insufficiently treated (McLachlan, 2018). Despite the relevance of depression and a plethora of research over the past decades, the neurobiological underpinnings of the disorder are still poorly understood. Previous neuroimaging studies have yielded highly heterogeneous results, even across large consortia (Frodl et al., 2017; Gray et al., 2020; Harris et al., 2022) and effect sizes are subtle (Winter et al., 2022). Further, the validity of brain-behavior findings in general have been questioned due to underpowered study samples, overestimated effect sizes and low replicability (Marek et al., 2022). These findings make it highly relevant to systematically investigate the replicability of the neural correlates of psychiatric disorders, such as depression and assess their generalizability to independent cohorts.
Methods:
Methods: Three independent cohorts totaling N=4021 adult participants were analyzed, including lifetime MDD patients (n=1764) and health control (HC) individuals (n=2257). Cohorts were from the MACS (n=1799), the MNC (n=1198) and the BiDirect study (n=1024). Lifetime MDD diagnosis was determined using structured interviews (SCID). Brain-wide association between MDD and gray matter voxel-based morphometry was tested using general linear models, controlling for age, sex and total intracranial volume. Cross-cohort replicability was assessed by inspecting the congruence of significant voxels between the three cohorts, at liberal uncorrected thresholds of p<.001 and using a stringent FWE-corrected threshold of pFWE<.05. Cross-cohort generalizability was investigated using a novel cross-validation implementation for mass-univariate brain-wide analysis, iterating through the three cohorts as independent test sets. Spatial Spearman correlations between brain-wide MDD effects and PET-derived neurotransmitter density maps were calculated using the Neuromaps toolbox (Markello et al., 2022) to investigate the potential link to neurotransmitter receptor profiles.
Results:
Results: Using an uncorrected threshold of p<.001 an overlap in significance congruently between all three cohorts was found in bilateral clusters distributed across the thalamus, insula, as well as the lingual, fusiform and parahippocampal gyri (a total of k=787 voxels; Figure 1). Even at pFWE<.05 all pairwise combinations of cohorts showed an overlap in congruent significance, located mainly within the thalamus, insula, orbitofrontal cortex, and the fusiform and lingual gyri. All observed effect sizes were small (maximum partial R2=.01). Inspecting the threshold-free cohort-wise generalizability of the diagnosis effect using cross-validation yielded largely generalizable effects across cohorts (Figure 2). The identified effects were spatially associated with various neurotransmitter systems, with more pronounced MDD-related gray matter reductions found in regions with higher neurotransmitter density (largest correlations: r=-.35 for D2 receptor (Malén et al., 2022); r=-30 for 5-HT1A receptor (Beliveau et al., 2017)).
·Significance of the HC>MDD contrast at p-uncorrected<.001 across cohorts
·Explained variance in test sets (partial R²) of the diagnosis effect fitted across training sets
Conclusions:
Discussion: Gray matter correlates of depression show substantial replicability and even generalizability between well-powered independent cohorts, despite the small magnitude of effects. Evidence implies a network containing the insula, thalamus and a lingual-parahippocampal complex. Notably, little evidence was found for a replicable or generalizable effect located within the hippocampus, opposed to numerous previous findings. Identified gray matter reductions are potentially related to neurotransmitter activity. Our findings demonstrate the need of replication efforts and the potential utility of cross-validation for univariate analyses in order to ensure the generalizability of findings, thus counteracting current concerns of low replicability.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Methods Development
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems 2
Cortical Anatomy and Brain Mapping
Transmitter Systems
Keywords:
Affective Disorders
MRI
Neurotransmitter
Positron Emission Tomography (PET)
1|2Indicates the priority used for review
Abstract Information
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Provide references using APA citation style.
Friedrich, M. (2017). Depression Is the Leading Cause of Disability Around the World. JAMA, 317(15), 1517.
Frodl, T. et al. (2017). Childhood adversity impacts on brain subcortical structures relevant to depression. Journal of Psychiatric Research, 86, 58–65.
Gray, J. P. et al. (2020). Multimodal Abnormalities of Brain Structure and Function in Major Depressive Disorder: A Meta-Analysis of Neuroimaging Studies. American Journal of Psychiatry, 177(5), 422–434.
Harris, M. A. et al. (2022). Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank. Translational Psychiatry, 12: 1-9.
Malén, T. et al. (2022). Atlas of type 2 dopamine receptors in the human brain: Age and sex dependent variability in a large PET cohort. NeuroImage, 255: 119149.
Marek, S. et al. (2022). Reproducible brain-wide association studies require thousands of individuals. Nature, 603, 654–660.
Markello, R. D. et al. (2022). Neuromaps: Structural and Functional Interpretation of Brain Maps. Nature Methods, 19(11), 1472–1479.
McLachlan, G. (2018). Treatment resistant depression: what are the options? BMJ, 363, k5354.
Winter, N. R. et al. (2022). Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder Across Neuroimaging Modalities. JAMA Psychiatry, 79(9), 879–888.