Structural connectomic signatures of childhood maltreatment across affective and psychotic disorders

Exposure to childhood maltreatment (CM) is a crucial risk factor for affective disorders and schizophrenia, which are linked to structural brain network alterations. We hypothesized a significant association between CM and brain structural connectivity in a transdiagnostic sample. Participants included patients with major depressive disorder (n = 827), bipolar disorder (n = 134), schizophrenia spectrum disorders (n = 118), and healthy controls (n = 932) aged 18-65 from the Marburg-Muenster Affective Disorders Cohort Study. Structural brain networks were reconstructed from structural and diffusion-weighted MRI. CM was assessed using the Childhood Trauma Questionnaire (CTQ) based on established cut-offs. Analyses of covariance investigated the main effect of CM and the interaction of diagnosis and CM on global network metrics. In addition, network-based statistic (NBS) analyses were performed to identify the underlying subnetworks. History of CM was positively associated with the number of connections (p<sub>FDR</sub>=0.01; CM: 95 %-CI=[533.9; 540.6], No CM: 95 %-CI=[529.1; 535.0]), normalized (p<sub>FDR</sub>=0.02; CM: 95 %-CI=[0.860; 0.863], No CM: 95 %-CI=[0.857; 0.860]) and non-normalized network efficiency (p<sub>FDR</sub>=0.01; CM: 95 %-CI=[0.405; 0.407], No CM: 95 %-CI=[0.403; 0.405]) and negatively associated with normalized network clustering (p<sub>FDR</sub>=0.045; CM: 95 %-CI=[4.976; 5.065], No CM: 95 %-CI=[5.100; 5.150]). There were no significant interaction effects of CM and diagnosis. NBS analyses revealed a large network of edges, in which individuals with CM exhibited higher structural connectivity compared to those without, which persisted after correcting for diagnosis. These findings indicate a connectome signature of CM, marked by hyperconnectivity, across major mental disorders and in healthy individuals, suggesting that CM affects connectome architecture independent of present psychiatric diagnoses.

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Journal
European Neuropsychopharmacology
Published
2025-10-13
DOI
https://doi.org/10.1016/j.euroneuro.2025.09.009
Citations
1
Primary Topic
Child Abuse and Trauma
Type
article
Field-Weighted Citation Impact
2.31
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Structural connectomic signatures of childhood maltreatment across affective and psychotic disorders

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article

Structural connectomic signatures of childhood maltreatment across affective and psychotic disorders

Andreas Jansen, Martijn P. van den Heuvel, Benjamín Straube, Janik Goltermann, Elisabeth Johanna Leehr, Marius Gruber, Dominik Grotegerd, Susanne L. Meinert, Sharmili Edwin Thanarajah, Hannah Meinert, Nils R. Winter, Jonathan Repple, Linda Meredith Bonnekoh, Sean N. Fischer, Florian Thomas‐Odenthal, Nina Alexander, Henry P. Staub, Igor Nenadić, Nils Opel, Frederike Stein, Paula Usemann, Udo Dannlowski, Tilo T. J. Kircher, Marc Pawlitzki, Kira F. Ahrens, Lea Teutenberg, Hamidreza Jamalabadi, Judith Krieger, Andreas Reif, Georg Romer, Paula Rehm, Tim Hahn, Kira Flinkenflügel, Ruth Helena Fellmeth, Christoph Jurischka, Julia M. Hubbert, Nina V Werthern, Cathrine Thams
article en
1 citations

Abstract

Exposure to childhood maltreatment (CM) is a crucial risk factor for affective disorders and schizophrenia, which are linked to structural brain network alterations. We hypothesized a significant association between CM and brain structural connectivity in a transdiagnostic sample. Participants included patients with major depressive disorder (n = 827), bipolar disorder (n = 134), schizophrenia spectrum disorders (n = 118), and healthy controls (n = 932) aged 18-65 from the Marburg-Muenster Affective Disorders Cohort Study. Structural brain networks were reconstructed from structural and diffusion-weighted MRI. CM was assessed using the Childhood Trauma Questionnaire (CTQ) based on established cut-offs. Analyses of covariance investigated the main effect of CM and the interaction of diagnosis and CM on global network metrics. In addition, network-based statistic (NBS) analyses were performed to identify the underlying subnetworks. History of CM was positively associated with the number of connections (p<sub>FDR</sub>=0.01; CM: 95 %-CI=[533.9; 540.6], No CM: 95 %-CI=[529.1; 535.0]), normalized (p<sub>FDR</sub>=0.02; CM: 95 %-CI=[0.860; 0.863], No CM: 95 %-CI=[0.857; 0.860]) and non-normalized network efficiency (p<sub>FDR</sub>=0.01; CM: 95 %-CI=[0.405; 0.407], No CM: 95 %-CI=[0.403; 0.405]) and negatively associated with normalized network clustering (p<sub>FDR</sub>=0.045; CM: 95 %-CI=[4.976; 5.065], No CM: 95 %-CI=[5.100; 5.150]). There were no significant interaction effects of CM and diagnosis. NBS analyses revealed a large network of edges, in which individuals with CM exhibited higher structural connectivity compared to those without, which persisted after correcting for diagnosis. These findings indicate a connectome signature of CM, marked by hyperconnectivity, across major mental disorders and in healthy individuals, suggesting that CM affects connectome architecture independent of present psychiatric diagnoses.

European NeuropsychopharmacologyVol. 100
Goethe University Frankfurt (DE), Philipps University of Marburg (DE), University of Münster (DE), Düsseldorf University Hospital (DE), Fraunhofer Institute for Translational Medicine and Pharmacology (DE), Amsterdam Neuroscience (NL), Klinik für Psychosomatik (DE), University Hospital Frankfurt (DE), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Heinrich Heine University Düsseldorf (DE), University of Göttingen (DE), Charité - Universitätsmedizin Berlin (DE), Bethel University (US)
Openalex Percentile: Top 10%
Child Abuse and Trauma
2.31
DOIOpen Access PDFOpenAlex
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